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 present the percentages of women and men age 15-49 that drank alcohol in the month preceding the survey, according to background characteristics. Table 3.10.1 Use of alcohol: Women Percentage of women age 15-49 who drank alcohol in the past month, and among those who drank alcohol in the past month, the frequency of consumption and the average number of alcoholic drinks consumed each day, by background characteristics, Liberia 2013 Background characteristic Percentage of women who drank alcohol in the past month Number of women Among women who drank alcohol in the past month, the percentage who drank: Number of women who drank alcohol in past month Every day Almost every day 1-2 times per week 2-3 times per month Once a month Average number of drinks per day1 Age 15-19 22.3 2,080 0.8 6.4 16.8 18.9 56.7 1.8 464 20-24 28.5 1,642 3.1 12.2 17.5 23.4 43.8 2.2 467 25-29 28.4 1,611 4.4 8.8 18.9 18.0 49.6 2.1 458 30-34 26.6 1,199 3.9 11.2 23.5 24.3 37.1 2.3 319 35-39 26.5 1,179 6.6 7.9 27.2 22.6 35.3 2.1 312 40-44 27.8 812 6.7 16.6 22.4 19.8 34.4 2.1 226 45-49 32.4 716 10.6 16.1 26.2 19.0 28.0 1.8 232 Maternity status Pregnant 21.5 765 0.9 13.5 17.2 18.7 49.7 2.0 164 Breastfeeding (not pregnant) 22.6 2,170 6.1 7.5 20.7 23.7 41.9 1.6 490 Neither 28.9 6,303 4.3 11.2 21.3 20.3 42.7 2.2 1,824 Residence Urban 29.3 5,633 3.2 11.3 21.2 20.9 43.3 2.3 1,649 Greater Monrovia 31.4 3,361 2.7 7.6 20.8 22.0 46.7 2.6 1,055 Other urban 26.1 2,272 3.9 18.1 21.8 18.9 37.2 1.9 594 Rural 23.0 3,606 7.1 9.1 20.3 20.7 42.5 1.6 829 Region North Western 12.7 837 2.9 8.8 22.4 16.8 48.7 1.5 106 South Central 27.9 4,854 2.7 7.5 19.1 21.8 48.6 2.4 1,355 South Eastern A 20.1 483 2.6 3.5 28.8 26.0 37.9 1.5 97 South Eastern B 30.8 577 3.7 7.2 21.9 15.4 51.7 1.7 178 North Central 29.8 2,488 8.4 18.2 22.6 20.2 30.6 1.7 742 County Bomi 15.9 244 2.5 8.1 12.1 15.7 61.6 1.6 39 Bong 38.3 894 11.1 8.6 16.7 16.7 47.0 1.5 343 Gbarpolu 23.7 182 4.9 9.9 32.0 23.8 28.3 1.6 43 Grand Bassa 15.7 434 1.4 9.0 16.3 25.2 48.0 1.5 68 Grand Cape Mount 5.9 412 (0.0) (7.8) (21.8) (6.1) 64.3) (1.4) 24 Grand Gedeh 26.9 167 4.8 3.4 50.2 23.0 18.6 1.5 45 Grand Kru 34.7 217 1.9 6.3 31.2 20.0 40.5 1.8 75 Lofa 9.0 447 3.0 30.6 36.5 18.0 11.9 2.0 40 Margibi 17.6 744 3.2 6.2 10.7 16.9 62.4 2.1 131 Maryland 29.2 257 5.3 10.0 13.5 12.1 59.1 1.6 75 Montserrado 31.5 3,675 2.7 7.6 20.3 22.2 47.1 2.5 1,156 Nimba 31.3 1,147 6.5 26.1 26.6 23.8 17.0 1.8 359 River Cess 14.8 135 0.0 4.3 16.0 27.5 52.1 1.4 20 River Gee 26.6 103 4.1 2.0 19.3 12.1 62.4 1.4 27 Sinoe 17.8 182 1.1 3.3 6.9 29.3 55.9 1.6 32 Education No education 24.6 3,066 9.5 14.8 22.9 19.8 32.8 1.7 754 Primary 23.4 2,875 3.0 11.8 19.5 17.5 48.1 1.8 672 Secondary and higher 31.9 3,298 1.8 6.8 20.3 23.7 47.1 2.5 1,052 Wealth quintile Lowest 26.3 1,581 9.7 10.6 20.5 20.5 38.6 1.5 416 Second 23.3 1,624 4.7 12.6 25.3 19.6 37.3 1.6 378 Middle 23.9 1,779 4.9 14.8 22.0 18.9 39.5 1.7 425 Fourth 26.2 2,047 3.6 13.3 19.1 19.6 44.4 2.3 537 Highest 32.7 2,207 1.7 5.1 19.5 23.8 49.6 2.7 722 Total 26.8 9,239 4.5 10.6 20.9 20.8 43.0 2.1 2,478 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 The average number of drinks is based on the number of drinks consumed on the days that the woman drank alcohol, for women who had a drink in the past month. 54 • Characteristics of Respondents Table 3.10.2 Use of alcohol: Men Percentage of men age 15-49 who drank alcohol in the past month, and among those who drank alcohol in the past month, the frequency of consumption and the average number of alcoholic drinks consumed each day, by background characteristics, Liberia 2013 Background characteristic Percentage of men who drank alcohol in the past month Number of men Among men who drank alcohol in the past month, the percentage who drank: Number of men who drank alcohol in past month Every day Almost every day 1-2 times per week 2-3 times per month Once a month Average number of drinks per day1 Age 15-19 27.1 890 2.1 7.2 27.6 26.3 36.6 5.1 241 20-24 54.2 696 4.8 7.5 33.8 26.5 27.4 3.8 378 25-29 57.0 673 10.8 8.1 45.2 15.7 20.1 4.0 384 30-34 60.1 575 12.4 15.5 37.9 20.4 13.7 4.0 346 35-39 52.9 469 14.4 14.3 35.5 23.8 12.1 4.4 248 40-44 57.1 482 12.2 10.6 46.3 18.8 12.1 3.9 275 45-49 60.9 332 11.9 11.1 42.4 14.4 19.8 3.8 202 Residence Urban 48.2 2,413 6.6 8.8 36.9 22.1 25.6 4.3 1,163 Greater Monrovia 47.6 1,433 3.4 7.4 35.3 22.4 31.5 4.4 683 Other urban 49.0 980 11.2 10.6 39.1 21.8 17.2 4.1 480 Rural 53.5 1,705 13.6 12.7 40.7 19.4 13.4 3.9 911 Region North Western 35.9 367 15.7 15.0 30.5 21.3 17.2 5.2 132 South Central 50.7 2,149 4.6 7.4 37.1 23.6 27.3 4.1 1,091 South Eastern A 50.3 254 9.3 9.9 40.1 14.3 25.4 3.8 128 South Eastern B 52.0 288 8.3 11.7 50.7 14.2 15.0 3.7 150 North Central 54.2 1,060 18.5 15.1 39.6 19.1 7.7 4.1 574 County Bomi 31.2 97 (7.9) (7.8) (33.8) (32.1) (18.4) (4.7) 30 Bong 56.0 389 23.6 14.1 37.0 20.0 5.3 4.3 218 Gbarpolu 50.2 94 14.6 22.0 36.3 20.8 5.6 4.0 47 Grand Bassa 57.7 204 6.2 9.0 51.9 17.8 15.1 3.3 118 Grand Cape Mount 30.8 176 20.9 12.8 23.7 15.8 26.8 6.5 54 Grand Gedeh 49.9 82 13.4 11.0 45.7 13.0 16.9 3.7 41 Grand Kru 56.2 110 11.6 13.0 55.0 7.1 13.3 3.8 62 Lofa 43.1 219 8.1 8.9 54.8 18.0 10.2 3.8 94 Margibi 57.2 364 4.5 3.9 36.3 31.8 23.5 3.2 208 Maryland 47.6 123 4.6 9.0 48.7 20.3 17.4 3.6 59 Montserrado 48.3 1,582 4.3 8.1 35.1 22.2 30.3 4.4 765 Nimba 58.1 451 18.0 18.1 36.4 18.7 8.8 4.0 262 River Cess 50.7 64 8.6 6.1 33.7 16.5 34.7 3.6 33 River Gee 53.4 55 8.8 14.5 45.6 17.0 14.0 3.9 29 Sinoe 50.4 108 6.6 11.4 39.7 13.9 26.2 4.0 54 Education No education 52.9 533 18.9 15.4 42.6 13.5 9.6 4.1 282 Primary 45.7 1,202 10.7 13.2 37.9 21.8 16.2 4.0 549 Secondary and higher 52.2 2,383 7.1 8.2 38.0 22.2 24.5 4.1 1,243 Wealth quintile Lowest 55.1 749 17.4 12.5 42.6 15.4 12.2 3.8 413 Second 58.2 753 12.2 13.4 39.2 22.6 12.4 3.8 438 Middle 51.0 728 9.6 13.9 42.2 17.9 16.1 3.9 371 Fourth 44.0 864 6.5 8.5 39.4 19.2 26.3 4.3 380 Highest 46.0 1,024 3.2 4.9 31.0 28.0 32.9 4.6 471 Total 50.4 4,118 9.7 10.5 38.6 20.9 20.2 4.1 2,074 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 The average number of drinks is based on the number of drinks consumed on the days that the man drank alcohol, for men who had a drink in the past month. Twenty-seven percent of women and 50 percent of men reported drinking alcohol during the month preceding the survey. Among respondents who drank alcohol in the past month, the percentage of men who Characteristics of Respondents • 55 drank alcohol every day is twice that of the women (10 percent versus 5 percent). The average number of drinks consumed per day for men is also twice that of women (4.1 drinks versus 2.1 drinks). Although the overall proportion of women who consumed alcohol in the past month is low, it is informative to look at the demographic characteristics of this group. By age, the percentage of women who drank alcohol during the month preceding the survey was highest among those age 45-49 (32 percent) and lowest among those age 15-19 (22 percent). A potential cause for concern is the prevalence of drinking among pregnant and breastfeeding women (22 percent and 23 percent, respectively); moreover, among pregnant and breastfeeding women who drank alcohol in the month preceding the interview, 14 and 8 percent, respectively, drank almost every day. By age, the percentage of men who drank alcohol during the month preceding the survey was highest among those age 45-49 (61 percent) and lowest among those age 15-19 (27 percent). The percentage that drank alcohol during the month preceding the survey was slightly higher among rural men than urban men (54 percent and 48 percent, respectively). Among those who drank alcohol in the month preceding the survey, drinking every day was more common for rural men (14 percent) than urban men (7 percent), for men with no education (19 percent) than men with at least some secondary education (7 percent), and for men in the lowest wealth quintile (17 percent) than men in the highest wealth quintile (3 percent). Marriage and Sexual Activity • 57 MARRIAGE AND SEXUAL ACTIVITY 4 arriage is a primary indication of the exposure of women to the risk of pregnancy and therefore is important to the understanding of fertility. Populations in which women marry at a young age tend to initiate childbearing early and have high fertility. More direct measures of the beginning of exposure to pregnancy are age at first intercourse and frequency of intercourse. 4.1 MARITAL STATUS Table 4.1 presents the percent distribution of women and men age 15-49 by current marital status. The proportion of women who have never married (or lived with a man) declines sharply with age, from 84 percent of women age 15-19 to 1 percent of women age 45-49. Marriage is thus nearly universal in Liberia. Although nearly all men eventually marry, men tend to marry later than women, and thus a higher percentage of men than women age 15-49 have never married (43 percent versus 31 percent). Fifty-eight percent of women and 54 percent of men age 15-49 are currently in union (i.e., married or living together with a partner as though married). Eight percent of women and 3 percent of men age 15-49 are separated or divorced. Three percent of women and 1 percent of men age 15-49 are widowed. M Key Findings • Fifty-eight percent of women age 15-49 and 54 percent of men age 15-49 are in union; that is, they are currently married or living with a partner as if married. • Among women age 25-49, the median age at first marriage is 18.8 years; among men age 25-49, the median age at first marriage exceeds 25 years. • Thirteen percent of currently married women are married to men who are in a polygynous union; 6 percent of currently married men are in a polygynous union. • Women and men typically initiate sexual activity before marriage. The median age at first sexual intercourse is 16.2 years for women age 25-49 and 18.3 years for men age 25-49. • About six in ten women and men age 15-49 have had sexual intercourse in the past four weeks. 58 • Marriage and Sexual Activity Table 4.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Liberia 2013 Age Marital status Total Percentage of respondents currently in union Number of respondents Never married Married Living together Divorced Separated Widowed WOMEN 15-19 84.2 3.4 10.9 0.0 1.4 0.0 100.0 14.4 2,080 20-24 41.1 13.5 38.9 0.5 5.4 0.5 100.0 52.5 1,642 25-29 17.6 28.4 44.2 0.4 8.7 0.8 100.0 72.5 1,611 30-34 8.1 37.9 41.9 1.3 8.6 2.2 100.0 79.8 1,199 35-39 3.6 43.5 34.9 2.6 10.1 5.3 100.0 78.4 1,179 40-44 1.5 51.5 24.7 4.8 9.2 8.4 100.0 76.1 812 45-49 0.7 61.9 16.0 2.2 8.7 10.5 100.0 77.9 716 Total 31.0 27.9 30.4 1.3 6.7 2.7 100.0 58.3 9,239 MEN 15-19 98.5 0.3 1.2 0.0 0.0 0.0 100.0 1.5 890 20-24 76.2 6.7 15.1 0.5 1.3 0.3 100.0 21.8 696 25-29 31.5 23.0 41.5 0.6 3.2 0.1 100.0 64.5 673 30-34 12.8 39.9 42.6 0.7 3.7 0.4 100.0 82.5 575 35-39 6.2 58.3 31.3 2.4 1.4 0.3 100.0 89.7 469 40-44 5.2 62.6 24.9 2.3 1.9 3.1 100.0 87.4 482 45-49 0.4 71.1 19.7 3.7 4.0 1.0 100.0 90.9 332 Total 42.5 30.2 23.6 1.1 1.9 0.6 100.0 53.9 4,118 4.2 POLYGYNY Polygyny (the practice of having more than one wife) has implications for the frequency of exposure to sexual activity and, therefore, fertility. The extent of polygyny in Liberia was measured by asking all women currently married or living with a man the question: “Does your husband/partner have other wives, or does he live with other women as if married?” If the answer is yes, the woman is asked: “Including yourself, in total, how many wives or live-in partners does he have?” Currently married men or men living with a woman are asked: “Do you have other wives, or do you live with other women as if married?” If the answer is yes, the man is asked: “Altogether, how many wives or live-in partners do you have?” Table 4.2.1 shows the distribution of currently married women by the number of co-wives, according to selected background characteristics. The majority of married women report their husband or partner has no other wives (86 percent). Thirteen percent of women report their husbands have more than one wife, while 1 percent report that they don’t know if their husbands have other wives. The percentage of currently married women who report that their husband has no other wives is higher than the figure reported in the 2007 LDHS (86 percent versus 78 percent, respectively). The proportion of women with co-wives increases with age, ranging from 6 percent among women age 15- 19 to 19 percent among women age 45-49. The proportions of women who report having no co-wives are lowest in Lofa (69 percent), Grand Kru (73 percent), Grand Cape Mount (76 percent), and River Gee (77 percent). There is an inverse relationship between education and polygyny. Women with no education are less likely to report having no co-wives (82 percent) compared with women with at least some secondary education (91 percent). There is also an inverse relationship between wealth and polygyny. Although 83 percent of currently married women in the lowest two wealth quintiles report that they have no co-wives, 90 percent of women in the highest wealth quintile report no co-wives. Marriage and Sexual Activity • 59 Table 4.2.1 Number of women's co-wives Percent distribution of currently married women age 15-49 by number of co-wives, according to background characteristics, Liberia 2013 Background characteristic Number of co-wives Total Number of women 0 1 2+ Don't know Age 15-19 92.4 5.8 0.0 1.4 100.0 299 20-24 89.0 9.1 0.6 1.0 100.0 862 25-29 89.6 8.5 0.4 1.4 100.0 1,168 30-34 84.9 12.3 1.3 1.3 100.0 957 35-39 82.4 13.1 2.7 1.2 100.0 924 40-44 83.8 12.2 2.4 1.6 100.0 619 45-49 80.5 14.2 4.4 1.0 100.0 557 Residence Urban 88.9 8.3 1.0 1.6 100.0 2,898 Greater Monrovia 90.7 6.7 0.8 1.5 100.0 1,614 Other urban 86.5 10.4 1.2 1.9 100.0 1,283 Rural 82.6 14.0 2.3 0.8 100.0 2,488 Region North Western 80.6 15.1 3.1 1.2 100.0 580 South Central 90.3 7.5 0.7 1.4 100.0 2,481 South Eastern A 84.9 12.6 1.0 1.5 100.0 348 South Eastern B 78.4 17.5 2.5 1.2 100.0 358 North Central 83.2 13.0 2.4 1.1 100.0 1,619 County Bomi 86.8 10.2 1.8 1.1 100.0 145 Bong 84.9 12.0 2.0 0.7 100.0 635 Gbarpolu 86.2 11.9 0.9 1.0 100.0 123 Grand Bassa 90.3 9.3 0.3 0.1 100.0 294 Grand Cape Mount 75.5 18.5 4.6 1.2 100.0 312 Grand Gedeh 83.4 13.7 1.0 1.9 100.0 113 Grand Kru 73.1 19.9 4.7 1.9 100.0 135 Lofa 69.0 22.5 8.2 0.3 100.0 291 Margibi 88.0 10.2 0.0 1.5 100.0 407 Maryland 83.8 14.4 0.5 0.8 100.0 148 Montserrado 90.8 6.5 0.9 1.5 100.0 1,780 Nimba 87.7 9.9 0.5 1.8 100.0 694 River Cess 90.0 8.7 0.7 0.7 100.0 100 River Gee 77.4 19.2 2.4 0.7 100.0 74 Sinoe 82.3 14.7 1.1 1.8 100.0 135 Education No education 81.8 14.3 2.7 1.1 100.0 2,417 Primary 87.3 10.4 0.9 1.2 100.0 1,446 Secondary and higher 91.4 6.1 0.5 1.6 100.0 1,523 Wealth quintile Lowest 83.0 13.8 2.1 0.8 100.0 1,133 Second 83.0 13.7 2.1 1.1 100.0 1,094 Middle 86.0 10.8 1.7 1.0 100.0 1,082 Fourth 88.4 9.6 0.7 1.4 100.0 1,108 Highest 90.2 6.3 1.4 2.1 100.0 968 Total 86.0 10.9 1.6 1.3 100.0 5,386 Note: Total includes 12 women for which information on number of co-wives is missing. Six percent of men age 15-49 report having more than one wife, and the percentage of men in this category generally increases with age (Table 4.2.2). Counties in which 10 percent or more of the men report having more than one wife are Grand Gedeh (10 percent), Lofa (11 percent), River Cess (11 percent), and River Gee (13 percent). The percentage of men who report being in a polygynous union declines with increasing education and wealth. 60 • Marriage and Sexual Activity Table 4.2.2 Number of men's wives Percent distribution of currently married men age 15-49, by number of wives, according to background characteristics, Liberia 2013 Background characteristic Number of wives Total Number of men 1 2+ Age 15-19 * * 100.0 13 20-24 97.2 2.8 100.0 152 25-29 97.4 2.6 100.0 434 30-34 95.8 4.2 100.0 475 35-39 93.2 6.8 100.0 421 40-44 90.8 9.2 100.0 422 45-49 92.4 7.6 100.0 302 Residence Urban 95.5 4.5 100.0 1,150 Greater Monrovia 96.2 3.8 100.0 623 Other urban 94.7 5.3 100.0 526 Rural 93.0 7.0 100.0 1,068 Region North Western 93.1 6.9 100.0 236 South Central 95.8 4.2 100.0 1,033 South Eastern A 90.5 9.5 100.0 147 South Eastern B 90.4 9.6 100.0 158 North Central 94.2 5.8 100.0 644 County Bomi 94.3 5.7 100.0 55 Bong 96.6 3.4 100.0 247 Gbarpolu 94.8 5.2 100.0 63 Grand Bassa 95.1 4.9 100.0 140 Grand Cape Mount 91.6 8.4 100.0 118 Grand Gedeh 90.2 9.8 100.0 44 Grand Kru 91.6 8.4 100.0 65 Lofa 88.6 11.4 100.0 124 Margibi 94.1 5.9 100.0 194 Maryland 90.7 9.3 100.0 58 Montserrado 96.4 3.6 100.0 699 Nimba 94.6 5.4 100.0 273 River Cess 89.4 10.6 100.0 41 River Gee 87.5 12.5 100.0 35 Sinoe 91.3 8.7 100.0 62 Education No education 87.7 12.3 100.0 375 Primary 95.3 4.7 100.0 569 Secondary and higher 95.8 4.2 100.0 1,274 Wealth quintile Lowest 93.0 7.0 100.0 489 Second 93.3 6.7 100.0 463 Middle 94.1 5.9 100.0 433 Fourth 94.8 5.2 100.0 447 Highest 96.9 3.1 100.0 387 Total 94.3 5.7 100.0 2,218 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 4.3 AGE AT FIRST MARRIAGE For most societies, marriage marks the point in a woman’s life when childbearing first becomes socially acceptable. Women who marry early will, on average, have longer exposure to pregnancy and a greater number of lifetime births. Information on age at first marriage was obtained by asking all ever-married respondents the month and year they started living together with their first spouse. Marriage and Sexual Activity • 61 Table 4.3 presents the percentages of both women and men age 15-49 who first married by specific exact ages and their median age at first marriage. The median age at marriage among women has risen by about one year and a half, from 18.4 years among women age 45-49 to 19.9 years among women age 20-24. The proportion of women married by age 15 declined from 17 percent among those age 45-49 to 4 percent among women age 15-19. Overall, four in ten women age 25-49 married by the time they were 18, and six in ten married by age 20. Men tend to enter into marriage at a later age than women. The median age at first marriage among men age 25-49 exceeds age 25, and is therefore at least six years older than women. Only 1 in 6 men age 20-49 marries by age 20, compared with 6 in 10 women in the same age group. Table 4.3 Age at first marriage Percentage of women and men age 15-49 who were first married by specific exact ages and median age at first marriage, according to current age, Liberia 2013 Current age Percentage first married by exact age: Percentage never married Number of respondents Median age at first marriage 15 18 20 22 25 WOMEN 15-19 3.8 na na na na 84.2 2,080 a 20-24 8.8 35.9 50.9 na na 41.1 1,642 19.9 25-29 10.3 35.2 55.4 66.7 76.4 17.6 1,611 19.3 30-34 12.5 42.1 60.1 72.5 81.8 8.1 1,199 18.8 35-39 14.0 46.5 61.6 72.9 83.1 3.6 1,179 18.4 40-44 14.8 46.0 64.0 74.3 84.3 1.5 812 18.5 45-49 16.7 47.2 62.5 74.0 84.9 0.7 716 18.4 20-49 12.1 40.8 57.9 na na 15.6 7,159 19.0 25-49 13.1 42.2 59.9 71.3 81.3 8.0 5,517 18.8 MEN 15-19 0.1 na na na na 98.5 890 a 20-24 0.7 4.7 12.2 na na 76.2 696 a 25-29 1.1 7.8 17.8 31.1 50.7 31.5 673 24.9 30-34 1.2 8.2 18.3 31.1 49.8 12.8 575 25.0 35-39 0.8 8.6 19.4 30.2 49.1 6.2 469 25.2 40-44 0.9 4.8 16.9 28.7 44.5 5.2 482 26.6 45-49 0.7 5.5 12.2 23.7 47.2 0.4 332 25.6 20-49 0.9 6.6 16.2 na na 27.0 3,228 a 25-49 1.0 7.2 17.3 29.5 48.6 13.5 2,531 a Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner na = Not applicable due to censoring a = Omitted because less than 50 percent of the women or men began living with their spouse or partner for the first time before reaching the beginning of the age group Table 4.4 presents the median age at first marriage among women, by background characteristics. Among women age 25-49, median age at marriage is nearly two years older among urban women (19.6) than among rural women (17.8). The lowest median age at marriage is observed in Lofa (17.0 years), while the highest is seen in Montserrrado (20.5 years). There is a marked relationship among women’s level of education and median age at marriage. The median age at first marriage among women age 25-49 with no formal education is 17.8 years, and it rises to 21.6 years among those with at least some secondary education. There is a positive correlation between wealth and age at marriage. The median age at marriage among women age 25-49 in the lowest quintile is four years younger than women in the highest wealth quintile (17.6 and 21.7 years of age, respectively). 62 • Marriage and Sexual Activity Median age at first marriage among women has risen modestly since 2007: from 18.6 to 19.0 among women age 20-49 and from 18.4 to 18.8 among women age 25-49. Table 4.4 Median age at first marriage by background characteristics: Women Median age at first marriage among women age 20-49 and age 25- 49, according to background characteristics, Liberia 2013 Background characteristic Women age 20-49 25-49 Residence Urban 19.9 19.6 Greater Monrovia a 20.7 Other urban 18.9 18.6 Rural 17.9 17.8 Region North Western 17.9 17.8 South Central a 20.0 South Eastern A 18.3 18.0 South Eastern B 18.8 18.5 North Central 17.9 17.8 County Bomi 17.6 17.3 Bong 17.5 17.5 Gbarpolu 18.6 18.5 Grand Bassa 18.2 18.0 Grand Cape Mount 17.8 18.0 Grand Gedeh 18.0 17.7 Grand Kru 19.1 18.7 Lofa 17.0 17.0 Margibi 19.4 19.2 Maryland 19.0 18.7 Montserrado a 20.5 Nimba 18.6 18.2 River Cess 17.5 17.3 River Gee 18.2 17.9 Sinoe 19.1 19.0 Education No education 17.8 17.8 Primary 18.5 18.3 Secondary and higher a 21.6 Wealth quintile Lowest 17.7 17.6 Second 17.8 17.7 Middle 18.6 18.4 Fourth 19.5 19.0 Highest a 21.7 Total 19.0 18.8 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner a = Omitted because less than 50 percent of the respondents began living with their spouse/partners for the first time before reaching the beginning of the age group 4.4 AGE AT FIRST SEXUAL INTERCOURSE Age at first marriage can be used as a proxy for the beginning of exposure to the risk of pregnancy. However, because some women are sexually active before marriage, the age at which women initiate sexual intercourse more precisely marks the beginning of their exposure to reproductive risks. The percentages of women and men who had first sexual intercourse by specific exact ages are presented in Table 4.5. The median age at first intercourse among women age 25-49 is 16.2 years. Twenty-four Marriage and Sexual Activity • 63 percent of women age 25-49 have had sexual intercourse by age 15 and 78 percent by age 18. By age 20, about nine in ten Liberian women have had sexual intercourse. Liberian men exhibit a slightly older median age at first intercourse compared with women. Among men age 25-49, the median age at first intercourse is 18.3 years. Eight percent of men age 25-49 have had sexual intercourse by age 15 and 45 percent by age 18. By age 20, about three in four men have initiated sexual intercourse. Table 4.5 Age at first sexual intercourse Percentage of women and men age 15-49 who had first sexual intercourse by specific exact ages, percentage who never had sexual intercourse, and median age at first sexual intercourse, according to current age, Liberia 2013 Current age Percentage who had first sexual intercourse by exact age: Percentage who never had sexual intercourse Number Median age at first sexual intercourse 15 18 20 22 25 WOMEN 15-19 23.3 na na na na 30.0 2,080 a 20-24 22.9 82.8 96.3 na na 0.7 1,642 16.2 25-29 21.2 76.5 91.5 96.3 97.3 0.0 1,611 16.4 30-34 25.4 78.4 92.3 95.5 96.6 0.0 1,199 16.1 35-39 22.6 79.0 91.1 94.2 95.3 0.0 1,179 16.1 40-44 27.1 78.6 88.6 93.0 93.6 0.0 812 16.1 45-49 27.9 77.2 90.9 93.0 93.6 0.0 716 16.0 20-49 23.9 79.0 92.3 na na 0.2 7,159 16.2 25-49 24.2 77.9 91.1 94.8 95.7 0.0 5,517 16.2 15-24 23.1 na na na na 17.1 3,722 a MEN 15-19 8.9 na na na na 58.9 890 a 20-24 9.4 55.4 86.2 na na 6.3 696 17.7 25-29 8.6 46.7 79.1 94.5 98.8 0.4 673 18.2 30-34 7.4 46.2 77.0 91.3 96.4 0.4 575 18.2 35-39 8.6 46.3 76.0 89.2 96.2 0.0 469 18.2 40-44 7.2 42.7 72.2 87.2 93.4 0.9 482 18.4 45-49 4.8 39.3 68.4 88.2 94.0 0.0 332 18.7 20-49 8.0 47.0 77.7 na na 1.7 3,228 18.2 25-49 7.6 44.8 75.3 90.6 96.1 0.4 2,531 18.3 15-24 9.1 na na na na 35.8 1,587 a na = Not applicable due to censoring a = Omitted because less than 50 percent of the respondents had sexual intercourse for the first time before reaching the beginning of the age group Table 4.6 presents the median age at first sexual intercourse among women and men, by background characteristics. The most notable observation is how little variation is observed by background characteristics. Among women, there are small increases in median age of first sexual intercourse with increasing education and wealth. For example, among women age 25-49, the median age rises from 15.8 among women with no education to 16.7 among women with at least some secondary education, an increase of less than one year. For men age 25- 49, on the other hand, the median age of first sexual intercourse is 18.3 irrespective of education level. 64 • Marriage and Sexual Activity Table 4.6 Median age at first sexual intercourse by background characteristics Median age at first sexual intercourse among women age 20-49 and age 25-49, and median age at first sexual intercourse among men age 20-49 and age 25- 49, according to background characteristics, Liberia 2013 Background characteristic Women age Men age 20-49 25-49 20-49 25-49 Residence Urban 16.4 16.4 18.1 18.3 Greater Monrovia 16.5 16.5 18.2 18.5 Other urban 16.2 16.1 18.0 18.1 Rural 15.9 15.9 18.2 18.3 Region North Western 15.9 16.0 18.4 18.4 South Central 16.4 16.4 18.1 18.3 South Eastern A 15.8 15.8 17.6 17.9 South Eastern B 16.1 16.2 18.0 18.1 North Central 16.0 16.0 18.3 18.4 County Bomi 15.9 15.9 18.6 18.8 Bong 15.8 15.8 18.3 18.4 Gbarpolu 16.1 16.2 18.4 18.5 Grand Bassa 15.9 15.9 18.0 18.0 Grand Cape Mount 15.8 16.0 18.3 18.2 Grand Gedeh 15.8 15.8 17.4 17.3 Grand Kru 16.7 16.9 18.4 18.5 Lofa 16.1 16.1 18.6 18.7 Margibi 16.2 16.2 17.8 17.9 Maryland 15.8 15.8 17.2 17.0 Montserrado 16.5 16.5 18.2 18.4 Nimba 16.2 16.2 18.1 18.1 River Cess 15.5 15.5 17.5 18.1 River Gee 16.0 16.0 18.2 18.3 Sinoe 16.2 16.1 17.8 18.1 Education No education 15.8 15.8 18.3 18.3 Primary 16.1 16.2 18.3 18.3 Secondary and higher 16.7 16.7 18.1 18.3 Wealth quintile Lowest 15.9 16.0 18.1 18.2 Second 15.8 15.8 18.2 18.3 Middle 16.1 16.0 18.1 18.1 Fourth 16.4 16.4 18.1 18.4 Highest 16.7 16.7 18.2 18.5 Total 16.2 16.2 18.2 18.3 4.5 RECENT SEXUAL ACTIVITY In the absence of effective contraception, the probability of becoming pregnant depends highly upon the frequency of intercourse. Information on sexual activity, therefore, can be used to refine measures of exposure to pregnancy. Women and men who have had sex were asked how long ago they most recently had sexual intercourse. Tables 4.7.1 and 4.7.2 show the distribution of women and men by recent sexual activity, according to background characteristics. Marriage and Sexual Activity • 65 Table 4.7.1 Recent sexual activity: Women Percent distribution of women age 15-49 by timing of last sexual intercourse, according to background characteristics, Liberia 2013 Background characteristic Timing of last sexual intercourse Never had sexual intercourse Total Number of women Within the past 4 weeks Within 1 year1 One or more years Age 15-19 38.0 27.0 4.8 30.0 100.0 2,080 20-24 59.0 31.4 8.7 0.7 100.0 1,642 25-29 63.2 28.5 8.2 0.0 100.0 1,611 30-34 63.5 27.3 8.9 0.0 100.0 1,199 35-39 63.5 26.3 10.1 0.0 100.0 1,179 40-44 61.2 26.6 12.3 0.0 100.0 812 45-49 64.8 20.6 14.6 0.0 100.0 716 Marital status Never married 42.3 28.2 7.1 22.2 100.0 2,867 Married or living together 68.7 25.6 5.6 0.0 100.0 5,386 Divorced/separated/widowed 34.0 35.7 30.3 0.0 100.0 987 Marital duration2 0-4 years 61.3 31.4 7.1 0.0 100.0 949 5-9 years 66.2 28.8 5.0 0.0 100.0 862 10-14 years 67.1 24.6 8.0 0.0 100.0 747 15-19 years 69.9 25.8 4.1 0.0 100.0 455 20-24 years 76.2 19.5 4.3 0.0 100.0 439 25+ years 75.1 21.0 4.0 0.0 100.0 330 Married more than once 71.5 23.4 5.1 0.0 100.0 1,604 Residence Urban 57.5 26.5 7.5 8.3 100.0 5,633 Greater Monrovia 59.2 25.0 6.4 9.3 100.0 3,361 Other urban 55.1 28.7 9.2 6.8 100.0 2,272 Rural 55.7 29.0 10.6 4.7 100.0 3,606 Region North Western 54.5 30.6 8.5 6.4 100.0 837 South Central 57.4 26.2 7.3 9.0 100.0 4,854 South Eastern A 54.1 34.5 9.2 2.1 100.0 483 South Eastern B 59.4 28.5 7.3 4.7 100.0 577 North Central 56.3 27.3 11.9 4.3 100.0 2,488 County Bomi 54.4 28.0 10.7 7.0 100.0 244 Bong 57.3 26.4 13.1 3.2 100.0 894 Gbarpolu 54.6 29.1 10.6 5.7 100.0 182 Grand Bassa 68.3 23.2 4.4 4.1 100.0 434 Grand Cape Mount 54.5 32.9 6.2 6.4 100.0 412 Grand Gedeh 51.6 33.4 13.5 1.5 100.0 167 Grand Kru 61.9 30.1 5.5 2.4 100.0 217 Lofa 48.0 26.9 18.3 6.5 100.0 447 Margibi 45.4 31.1 11.9 11.6 100.0 744 Maryland 56.6 27.8 8.4 7.2 100.0 257 Montserrado 58.6 25.5 6.7 9.1 100.0 3,675 Nimba 58.8 28.2 8.4 4.3 100.0 1,147 River Cess 60.7 31.0 6.1 2.0 100.0 135 River Gee 61.3 26.9 8.5 3.3 100.0 103 Sinoe 51.6 38.1 7.6 2.7 100.0 182 Education No education 60.7 25.9 12.4 1.0 100.0 3,066 Primary 50.5 27.0 7.9 14.3 100.0 2,875 Secondary and higher 58.7 29.3 6.1 5.9 100.0 3,298 Wealth quintile Lowest 56.5 27.9 12.1 3.4 100.0 1,581 Second 55.0 28.2 12.0 4.6 100.0 1,624 Middle 55.4 30.3 7.8 6.2 100.0 1,779 Fourth 59.7 25.8 7.1 7.3 100.0 2,047 Highest 56.7 25.9 6.1 11.3 100.0 2,207 Total 56.8 27.5 8.7 6.9 100.0 9,239 Note: Total includes 10 women for whom information on last sexual intercourse is missing. 1 Excludes women who had sexual intercourse within the last 4 weeks 2 Excludes women who are not currently married 66 • Marriage and Sexual Activity Although about nine in ten women age 15-49 have ever had sexual intercourse (Table 4.7.1), only about six in ten women age 15-49 are currently sexually active – that is, they have had sexual intercourse in the four weeks preceding the survey. Twenty-eight percent of women had been sexually active within the 12- month period prior to the survey, although not in the month prior to the interview. Nine percent of women had had sexual intercourse, but not for one or more years. Seven percent of women age 15-49 have never had sexual intercourse. A higher percentage of women between the ages of 20 and 49 is currently sexually active than women age 15-19. Women in union are much more likely to report recent sexual activity than women who are divorced, separated, widowed, or never married; 69 percent of currently married women report being recently sexually active compared with 34 percent of those who are divorced, separated, or widowed and 42 percent of those who never married. Six in ten men age 15-49 report having had sexual intercourse within the four weeks preceding the interview. Twenty-five percent of men had been sexually active within the 12-month period prior to the survey, but not in the month prior to the interview, and 3 percent had not been sexually active for one or more years. Fourteen percent of men age 15-49 had never had sexual intercourse. Although the overall percentage of men who have had sexual intercourse within the past four weeks is comparable to women (59 percent and 57 percent, respectively), the age breakdown differs. Among younger ages (15-24) a higher percentage of women are recently sexually active, as compared with men; among older ages (25-49) a higher percentage of men are recently sexually active, as compared with women. Divorced, separated, or widowed men are also more likely than women to report being recently sexually active (64 percent and 34 percent, respectively). Marriage and Sexual Activity • 67 Table 4.7.2 Recent sexual activity: Men Percent distribution of men age 15-49 by timing of last sexual intercourse, according to background characteristics, Liberia 2013 Background characteristic Timing of last sexual intercourse Never had sexual intercourse Total Number of men Within the past 4 weeks Within 1 year1 One or more years Age 15-19 19.4 18.7 3.0 58.9 100.0 890 20-24 55.7 35.0 3.0 6.3 100.0 696 25-29 71.4 25.5 2.6 0.4 100.0 673 30-34 73.8 24.1 1.5 0.4 100.0 575 35-39 71.4 26.8 1.8 0.0 100.0 469 40-44 77.4 18.4 3.1 0.9 100.0 482 45-49 73.9 22.6 3.5 0.0 100.0 332 Marital status Never married 36.1 26.6 4.3 33.1 100.0 1,749 Married or living together 76.2 22.6 1.1 0.0 100.0 2,218 Divorced/separated/widowed 64.3 28.8 6.9 0.0 100.0 151 Marital duration2 0-4 years 74.1 24.9 0.9 0.0 100.0 510 5-9 years 72.9 25.9 0.9 0.0 100.0 458 10-14 years 70.6 28.6 0.7 0.0 100.0 293 15-19 years 76.6 20.8 2.6 0.0 100.0 158 20-24 years 74.8 24.3 0.8 0.0 100.0 150 25+ years 81.8 11.6 6.6 0.0 100.0 50 Married more than once 83.1 16.2 0.6 0.0 100.0 597 Residence Urban 57.5 24.7 2.6 15.1 100.0 2,413 Greater Monrovia 56.7 26.7 2.6 14.1 100.0 1,433 Other urban 58.7 21.8 2.6 16.7 100.0 980 Rural 60.5 24.3 2.7 12.5 100.0 1,705 Region North Western 61.2 26.0 1.6 11.2 100.0 367 South Central 56.8 25.5 2.8 14.9 100.0 2,149 South Eastern A 62.5 24.8 1.6 10.8 100.0 254 South Eastern B 64.2 21.6 4.3 9.9 100.0 288 North Central 59.5 22.8 2.5 15.2 100.0 1,060 County Bomi 58.5 26.0 3.6 11.9 100.0 97 Bong 60.6 26.0 2.0 11.4 100.0 389 Gbarpolu 61.6 27.3 1.5 9.6 100.0 94 Grand Bassa 68.1 19.1 1.5 11.3 100.0 204 Grand Cape Mount 62.5 25.3 0.6 11.6 100.0 176 Grand Gedeh 54.1 32.7 2.0 10.8 100.0 82 Grand Kru 69.0 20.7 1.2 9.0 100.0 110 Lofa 44.8 31.3 2.9 20.7 100.0 219 Margibi 51.6 25.9 3.6 18.6 100.0 364 Maryland 59.5 24.2 5.7 10.5 100.0 123 Montserrado 56.5 26.2 2.8 14.5 100.0 1,582 Nimba 65.6 15.8 2.6 15.9 100.0 451 River Cess 70.0 18.8 2.5 8.8 100.0 64 River Gee 65.2 17.2 7.1 10.4 100.0 55 Sinoe 64.5 22.4 0.9 12.0 100.0 108 Education No education 61.8 26.7 4.3 7.0 100.0 533 Primary 48.0 20.6 2.4 29.0 100.0 1,202 Secondary and higher 63.5 26.0 2.4 8.1 100.0 2,383 Wealth quintile Lowest 62.5 24.6 2.7 10.1 100.0 749 Second 61.3 24.0 2.7 12.0 100.0 753 Middle 60.1 21.2 2.0 16.8 100.0 728 Fourth 55.5 27.3 0.8 16.4 100.0 864 Highest 55.9 25.0 4.6 14.5 100.0 1,024 Total 58.7 24.5 2.6 14.0 100.0 4,118 Note: Total includes 2 men for whom information on last sexual intercourse is missing. 1 Excludes men who had sexual intercourse within the last 4 weeks 2 Excludes men who are not currently married Fertility • 69 FERTILITY 5 n the 2013 LDHS, data were collected on current and completed fertility. The birth histories of women interviewed in the survey contributed in this chapter to a description of levels and differentials in current fertility. Trends in fertility are explored, including examination of age-specific fertility rates in periods going back 15 to 20 years. Measures of several proximate determinants of fertility that influence exposure to the risk of pregnancy are also presented, including duration of postpartum amenorrhea, postpartum abstinence, and menopause. The chapter also gives information on the age of women at their first birth and on patterns of teenage childbearing. The fertility indicators presented in this chapter are based on reports of reproductive histories provided by women age 15-49. As in the previous LDHS surveys, each woman was asked to provide information on the total number of sons and daughters to whom she had given birth and who were living with her, the number living elsewhere, and the number who had died, in order to obtain the total number of live births. In the birth history, women reported the details of each live birth separately, including such information as name, and month and year of birth in addition to sex and survival status. For children who had died, age at death was recorded. 5.1 CURRENT FERTILITY Measures of current fertility include age-specific fertility rates (ASFRs), the total fertility rate (TFR), the general fertility rate (GFR), and the crude birth rate (CBR). These rates are presented for the three-year period preceding the survey, a period that covers a portion of calendar years 2010 through 2013. The three-year period (rather than a longer or a shorter period) was chosen to calculate rates as a balance among providing the most current information, reducing sampling error, and avoiding problems of the displacement of births. Age-specific fertility rates are useful in understanding the age pattern of fertility. Numerators of ASFRs are calculated by identifying live births that occurred in the period 1 to 36 months preceding the survey (determined from the date of interview and date of birth of the child); they are then classified by the age of the mother (in five-year groups) at the time of the child’s birth. The denominators of these rates are the number of woman-years lived by the survey respondents in each of the five-year age groups during the specified period. I Key Findings • The total fertility rate for Liberia is 4.7 children per woman. This represents a decrease since the 2007 LDHS, which reported 5.2 children per woman. • Fertility among urban women (3.8 children per woman) is markedly lower than among rural women (6.1 children per woman). • The median age at first birth among women 20-49 is 18.9 years. • Among women who had a live birth in the three years preceding the survey, the median duration of postpartum insusceptibility to pregnancy is 13.1 months. • Thirteen percent of women age 30-49 are menopausal. • The median age at first birth among women age 25-49 is 18.9. 70 • Fertility The TFR is a common measure of current fertility and is defined as the number of children a woman would have by the end of her childbearing years if she were to pass through those years bearing children at the current age-specific fertility rates. The GFR represents the number of live births per 1,000 women of reproductive age. The CBR is the number of live births per 1,000 population. The latter two measures are based on birth history data for the three-year period before the survey and on the age-sex distribution of the household population. Table 5.1 shows the age-specific and aggregate fertility measures calculated from the 2013 LDHS. The total fertility rate for Liberia is 4.7 children per woman. Childbearing peaks during age 20-24 and drops sharply after age 39. Fertility among urban women is markedly lower (3.8 children per woman) than among rural women (6.1 children per woman). This pattern of lower fertility in urban areas is evident in every age group. 5.2 FERTILITY BY BACKGROUND CHARACTERISTICS Table 5.2 shows differentials in fertility by residence, region, level of education, and wealth quintile. Among urban areas, Greater Monrovia has a distinctly lower TFR (3.2) than other urban areas (4.8). Rural areas have a notably higher TFR (6.1) on average, with geographic variation across regions (3.8-6.5). Table 5.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of women age 15-49 currently pregnant, and mean number of children ever born to women age 40-49 years, by background characteristics, Liberia 2013 Background characteristic Total fertility rate Percentage of women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 3.8 7.0 5.7 Greater Monrovia 3.2 6.5 5.3 Other urban 4.8 7.7 6.1 Rural 6.1 10.3 6.7 Region North Western 5.8 10.3 7.1 South Central 3.8 6.7 5.8 South Eastern A 6.5 9.6 6.7 South Eastern B 5.9 9.2 7.1 North Central 5.6 10.2 6.2 Education No education 5.9 9.3 6.7 Primary 5.1 9.5 6.2 Secondary and higher 3.4 6.3 4.9 Wealth quintile Lowest 6.6 10.3 6.7 Second 5.9 10.7 6.8 Middle 5.2 9.7 6.4 Fourth 3.9 5.9 5.7 Highest 2.8 6.2 4.9 Total 4.7 8.3 6.2 Note: Total fertility rates are for the period 1-36 months prior to interview. Table 5.1 Current fertility Age-specific and total fertility rates, the general fertility rate, and the crude birth rate for the three years preceding the survey, by residence, Liberia 2013 Age group Residence Total Urban Rural 15-19 121 206 149 20-24 188 285 222 25-29 164 253 200 30-34 140 230 177 35-39 109 165 133 40-44 36 66 50 45-49 11 17 14 TFR(15-49) 3.8 6.1 4.7 GFR 139 214 168 CBR 31.1 38.5 34.4 Notes: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates are for the period 1-36 months prior to interview. TFR: Total fertility rate expressed per woman GFR: General fertility rate expressed per 1,000 women age 15-44 CBR: Crude birth rate, expressed per 1,000 population Fertility • 71 Education and wealth are closely linked to a woman’s fertility. The TFRs for women with no formal education and women who have attended only primary school are 5.9 and 5.1 children per woman, respectively, while the TFR for women with at least some secondary education is 3.4. The TFR decreases with each increase in wealth quintile, ranging from 6.6 children per woman in the lowest wealth quintile to 2.8 children per woman in the highest wealth quintile. Table 5.2 also allows for a general assessment of differential trends in fertility over time among population subgroups. The mean number of children ever born to women age 40-49 is a measure of past fertility. The mean number of children ever born to older women who are nearing the end of their reproductive period is an indicator of average completed fertility of women who began childbearing during the three decades preceding the survey. If fertility were to remain constant over time, and the reported data on children ever born and births during the three years preceding the survey were reasonably accurate, the TFR and the mean number of children ever born for women age 40-49 would be similar. If fertility levels have fallen, the TFR will be substantially lower than the mean number of children ever born among women age 40-49. Overall, a comparison of past (completed) and current (TFR) fertility indicators suggests a decline from 6.2 to 4.7 children per woman. There have been substantial but variable declines in both urban and rural areas, and across education levels and wealth quintiles. The largest declines have occurred among women in urban areas, women with at least some secondary education, and women in the highest wealth quintile. At the time of the survey, 8 percent of interviewed women reported that they were pregnant. This percentage is an underestimate because many women will not yet know for sure that they are pregnant, and other women may not want to declare that they are pregnant. 5.3 FERTILITY TRENDS The data in Table 5.3.1 provide evidence of fluctuations in fertility in Liberia over the past 20 years. The table uses information from the retrospective birth histories obtained from LDHS respondents to examine trends in age-specific fertility rates for successive five- year periods before the survey. To calculate these rates, births were classified according to the period of time in which the birth occurred and the mother’s age at the time of birth. Because women age 50 and above were not interviewed in the survey, the rates are successively truncated for periods more distant from the survey date. For example, rates cannot be calculated for women age 35-39 for the period 15 to 19 years before the survey because these women would have been over the age of 50 at the time of the 2013 LDHS and not interviewed. Fertility has fallen among women in all age groups over the past two decades. Substantial declines in age-specific fertility rates were observed from the period 15 to 19 years before the survey to the period 0 to 4 years before the survey. Fertility decline is steepest among women age 25-29 and age 30-34. Table 5.3.2 and Figure 5.1 show trends in current fertility rates based on successive LDHS surveys. Overall, the TFR declined by 2.0 births between the 1986 and 2013 surveys. The decline in TFR has been consistent across LDHS surveys: 6.7 children per woman in 1986, 6.2 children per woman in 1999/2000, 5.2 children per woman in 2007, and 4.7 children per woman in 2013. Table 5.3.1 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother's age at the time of the birth, Liberia 2013 Mother's age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 147 166 153 170 20-24 219 257 241 256 25-29 201 256 254 260 30-34 174 236 227 [248] 35-39 132 175 [186] 40-44 62 [124] 45-49 [23] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. 72 • Fertility The decline in national TFR between the 2007 and 2013 LDHS bears closer inspection. Whereas, the overall TFR declined from 5.2 children per woman in 2007 to 4.7 children per woman in 2013, there was little, if any, change in TFR by urban-rural residence. Specifically, the TFR for urban women reported in the 2007 LDHS was 3.8, which is identical to that reported in the 2013 LDHS. The TFR for rural women reported in the 2007 LDHS was 6.2 compared with 6.1 in the 2013 LDHS. A key difference between the 2007 LDHS and 2013 LDHS is the sampling frame (see Chapter 1). The percentage of the population living in urban areas is markedly higher in the 2013 LDHS sample than the 2007 LDHS sample. Accordingly, the contribution of urban women to the total TFR is higher in the 2013 LDHS than the 2007 LDHS, and this shift explains much of the decline in total TFR. Figure 5.1 Trends in fertility 0 50 100 150 200 250 300 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group 1986 LDHS 1999/2000 LDHS 2007 LDHS 2013 LDHS Births per 1,000 women 5.4 CHILDREN EVER BORN AND LIVING The distribution of women by the number of children ever born is presented in Table 5.4 for all women and for currently married women. The table also shows the mean number of children ever born to women in each five-year age group. These distributions reflect the accumulation of births among LDHS respondents over the past 30 years and, therefore, their relevance to the current situation is limited. However, the information on children ever born is useful for observing how average family size varies across age groups and for observing the level of primary infertility. On average, women in their early twenties have given birth to Table 5.3.2 Trends in age-specific and total fertility rates Age-specific and total fertility rates (TFR) for the three-year period preceding several surveys, Liberia 1983-2013 Mother’s age at birth 1986 LDHS 1999/2000 LDHS 2007 LDHS 2013 LDHS 15-19 188 135 141 149 20-24 287 279 243 222 25-29 282 241 226 200 30-34 229 211 187 177 35-39 177 171 142 133 40-44 107 112 72 50 45-49 61 83 29 14 TFR 15-49 6.7 6.2 5.2 4.7 Note: Age-specific fertility rates are per 1,000 women. Fertility • 73 more than one child, women in their early thirties have had close to four children, and women at the end of their childbearing years have had almost seven children. Of the 6.6 children ever born to women age 45-49, 5.0 survived to the time of the survey. Results at younger ages for currently married women differ from those for all women because of the large number of unmarried women with minimal fertility. Differences at older ages generally reflect the impact of marital dissolution (either divorce or widowhood). Less than 1 percent of currently married women age 45- 49 have never had a child. If the desire for children is universal in Liberia, this percentage represents a rough measure of primary infertility or the inability to bear children. Table 5.4 Children ever born and living Percent distribution of all women and currently married women age 15-49 by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Liberia 2013 Age Number of children ever born Total Number of women Mean number of children ever born Mean number of living children 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 74.2 22.3 3.4 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 2,080 0.29 0.28 20-24 20.3 36.6 29.1 11.3 2.3 0.5 0.1 0.0 0.0 0.0 0.0 100.0 1,642 1.40 1.26 25-29 6.3 19.8 25.8 22.7 15.5 6.6 2.4 0.7 0.1 0.0 0.0 100.0 1,611 2.55 2.25 30-34 2.5 8.2 18.3 17.2 19.0 16.5 9.0 6.9 1.1 1.1 0.4 100.0 1,199 3.79 3.22 35-39 2.3 4.0 11.1 14.6 14.5 15.2 16.7 9.1 6.1 3.5 3.0 100.0 1,179 4.78 3.95 40-44 1.8 2.3 6.9 9.5 11.6 13.3 16.2 12.2 9.3 9.4 7.5 100.0 812 5.79 4.64 45-49 0.5 2.0 4.0 8.7 10.2 13.3 11.2 12.4 10.1 9.5 17.9 100.0 716 6.64 5.02 Total 22.2 16.9 15.1 11.6 9.2 7.5 6.0 4.2 2.5 2.2 2.5 100.0 9,239 2.89 2.40 CURRENTLY MARRIED WOMEN 15-19 30.6 55.1 13.6 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 299 0.84 0.80 20-24 8.4 33.5 37.8 16.2 3.3 0.6 0.2 0.0 0.0 0.0 0.0 100.0 862 1.75 1.58 25-29 2.9 14.6 26.2 26.2 17.5 8.5 3.0 0.9 0.1 0.0 0.0 100.0 1,168 2.84 2.50 30-34 0.9 7.2 15.2 17.2 20.0 18.6 10.1 7.8 1.3 1.3 0.5 100.0 957 4.04 3.45 35-39 1.9 2.9 10.4 12.7 13.3 15.3 19.6 10.0 6.6 3.9 3.4 100.0 924 5.03 4.13 40-44 1.7 1.4 5.9 7.5 11.3 13.7 17.1 11.7 10.6 10.3 8.7 100.0 619 6.05 4.85 45-49 0.7 1.9 2.7 8.0 10.4 13.6 11.3 11.9 9.1 10.6 19.7 100.0 557 6.82 5.16 Total 4.4 13.7 18.0 15.2 12.5 10.8 9.0 5.9 3.5 3.2 3.7 100.0 5,386 3.92 3.25 5.5 BIRTH INTERVALS Information on the length of birth intervals provides insight into birth spacing patterns, which affect fertility as well as infant and child mortality. Research has shown that children born too soon after a previous birth are at increased risk of poor health, particularly when the interval is less than 24 months. Table 5.5 shows the distribution of births in the five years before the survey by the interval since the preceding birth, according to various background and demographic characteristics. The median birth interval in Liberia is 37.4 months. About 16 percent of all children are born after too short an interval (less than 24 months). The median interval is shorter among births to women under age 30 than among births to older mothers. The median birth interval in urban areas (40.9 months) is slightly higher than in rural areas (35.6 months). Among urban areas, the median birth interval is higher in Greater Monrovia (44.2 months) than in other urban areas (37.7 months). Women with at least some secondary education have a longer median birth interval (43.1 months) than women with no education (36.9 months) or women with at least some primary 74 • Fertility school (36.0 months). Median birth interval increases with each wealth quintile, ranging from 35.1 months in the lowest quintile to 47.6 months in the highest quintile. Table 5.5 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Liberia 2013 Background characteristic Months since preceding birth Total Number of non-first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 3.5 31.3 49.9 11.0 1.2 3.0 100.0 73 26.0 20-29 5.0 12.6 36.3 21.3 10.2 14.6 100.0 2,313 34.7 30-39 5.2 8.0 25.6 23.1 12.7 25.5 100.0 1,970 40.9 40-49 3.5 8.6 24.1 16.3 15.8 31.7 100.0 533 45.2 Sex of preceding birth Male 5.0 10.5 30.2 21.5 11.9 21.0 100.0 2,479 37.8 Female 4.8 10.6 31.5 21.2 11.5 20.4 100.0 2,411 37.1 Survival of preceding birth Living 4.2 10.0 31.5 21.7 11.8 20.7 100.0 4,376 37.6 Dead 10.5 14.9 25.2 18.2 10.7 20.5 100.0 514 35.7 Birth order 2-3 3.9 10.5 31.6 19.7 11.0 23.3 100.0 2,310 37.8 4-6 5.3 10.2 29.7 23.0 12.0 19.8 100.0 1,843 37.9 7+ 6.7 11.7 31.4 22.3 13.2 14.7 100.0 737 36.0 Residence Urban 3.6 8.9 27.9 21.2 11.8 26.7 100.0 2,211 40.9 Greater Monrovia 2.8 7.0 26.4 20.8 11.6 31.5 100.0 1,047 44.2 Other urban 4.3 10.7 29.2 21.6 11.9 22.4 100.0 1,164 37.7 Rural 6.0 11.9 33.3 21.4 11.6 15.7 100.0 2,679 35.6 Region North Western 5.3 11.4 33.1 22.4 12.5 15.3 100.0 605 36.1 South Central 4.1 8.8 28.2 20.1 11.5 27.4 100.0 1,848 41.1 South Eastern A 6.7 13.2 35.5 17.5 12.0 15.1 100.0 400 34.3 South Eastern B 9.0 11.8 36.0 21.0 9.9 12.4 100.0 419 33.5 North Central 4.2 11.3 30.5 23.4 12.0 18.6 100.0 1,617 37.1 County Bomi 4.5 10.6 27.2 27.4 12.6 17.6 100.0 141 39.3 Bong 4.4 10.4 29.7 22.9 14.3 18.3 100.0 644 38.3 Gbarpolu 8.5 11.6 29.2 20.1 12.4 18.1 100.0 130 36.3 Grand Bassa 6.8 10.9 26.6 20.2 10.5 25.0 100.0 291 38.5 Grand Cape Mount 4.4 11.7 37.1 21.1 12.5 13.2 100.0 334 35.1 Grand Gedeh 7.2 6.8 31.6 19.0 13.9 21.5 100.0 120 37.8 Grand Kru 10.7 11.1 39.7 19.3 11.1 8.2 100.0 188 32.4 Lofa 3.5 10.6 25.9 20.8 13.8 25.3 100.0 263 41.3 Margibi 4.9 11.8 35.9 15.7 13.0 18.6 100.0 356 35.2 Maryland 7.9 12.0 30.3 23.2 9.1 17.4 100.0 149 35.9 Montserrado 3.1 7.4 26.4 21.3 11.3 30.6 100.0 1,201 43.5 Nimba 4.2 12.3 33.0 24.8 9.3 16.4 100.0 710 36.1 River Cess 6.4 15.4 37.2 16.6 10.9 13.4 100.0 123 32.5 River Gee 7.1 12.9 37.8 21.2 8.3 12.8 100.0 83 32.5 Sinoe 6.4 16.3 37.2 17.1 11.5 11.5 100.0 157 33.2 Education No education 5.7 10.9 31.0 23.1 12.4 16.9 100.0 2,426 36.9 Primary 5.2 10.4 34.3 19.8 10.5 19.8 100.0 1,392 36.0 Secondary and higher 2.7 9.9 26.1 19.3 11.6 30.3 100.0 1,073 43.1 Wealth quintile Lowest 6.0 13.5 33.1 21.7 11.6 14.1 100.0 1,314 35.1 Second 6.4 11.3 33.7 21.4 11.7 15.5 100.0 1,176 35.4 Middle 4.0 9.6 32.1 22.3 11.9 20.1 100.0 1,034 37.4 Fourth 3.3 10.0 26.5 20.3 11.3 28.6 100.0 816 41.6 Highest 3.0 4.5 23.6 20.0 12.3 36.7 100.0 550 47.6 Total 4.9 10.6 30.9 21.3 11.7 20.7 100.0 4,890 37.4 Note: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. Fertility • 75 5.6 POSTPARTUM AMENORRHEA, ABSTINENCE, AND INSUSCEPTIBILITY Postpartum amenorrhea refers to the interval between childbirth and the return of menstruation. During this period, the risk of pregnancy is greatly reduced. The duration of this protection from conception after childbirth depends on the duration and intensity of breastfeeding and the length of time before the resumption of sexual intercourse. Women who gave birth during the three years prior to the survey were asked about their breastfeeding practices, the duration of amenorrhea, and sexual abstinence. Women are considered insusceptible if they are not exposed to the risk of pregnancy, either because they are amenorrheic or are still abstaining from sex after birth. The results are shown in Table 5.6. Table 5.6 Postpartum amenorrhea, abstinence, and insusceptibility Percentage of births in the three years preceding the survey for which mothers are postpartum amenorrheic, abstaining, and insusceptible, by number of months since birth, and median and mean durations, Liberia 2013 Months since birth Percentage of births for which the mother is: Amenorrheic Abstaining Insusceptible1 Number of births < 2 95.6 99.3 99.8 179 2-3 80.1 96.8 97.6 218 4-5 68.4 87.6 92.6 220 6-7 54.8 75.8 82.7 247 8-9 50.3 65.9 74.7 234 10-11 42.3 61.0 70.3 265 12-13 35.4 45.5 58.1 221 14-15 22.8 23.1 33.0 230 16-17 13.4 27.1 30.3 218 18-19 11.5 10.2 17.9 226 20-21 11.5 14.0 21.3 190 22-23 2.1 7.0 8.6 244 24-25 2.2 3.0 5.0 234 26-27 1.0 2.8 3.6 163 28-29 0.5 1.1 1.5 165 30-31 1.2 1.6 2.8 165 32-33 0.5 0.9 1.2 212 34-35 0.2 0.9 1.0 237 Total 28.1 35.8 40.4 3,867 Median 8.3 11.6 13.1 na Mean 10.1 12.7 14.3 na Note: Estimates are based on status at the time of the survey. na = Not applicable 1 Includes births for which mothers are either still amenorrheic or still abstaining (or both) following birth The period of postpartum abstinence is longer than the period of postpartum amenorrhea, suggesting that the former is a stronger determinant of the length of postpartum insusceptibility in Liberia. The median duration of amenorrhea is 8.3 months, women abstain for a median of 11.6 months, and they are insusceptible to pregnancy for a median of 13.1 months. Almost all women are virtually insusceptible to pregnancy during the first two months after a birth, and both amenorrhea and abstinence are important factors in their insusceptibility. However, abstinence declines more slowly over time than amenorrhea, with the percentage of abstaining mothers higher than the percentage of amenorrheic mothers at almost all time intervals evaluated. 5.7 MEDIAN DURATION OF POSTPARTUM INSUSCEPTIBILITY BY BACKGROUND CHARACTERISTICS In the absence of contraception, variations in postpartum amenorrhea and abstinence are the most important determinants of the interval between births and ultimately the completion of fertility. 76 • Fertility Table 5.7 shows the median durations of postpartum amenorrhea, abstinence, and insusceptibility by selected background characteristics. Although the median duration of postpartum amenorrhea for women age 30-49 is slightly longer than that for women age 15-29 (9.9 months and 7.4 months, respectively), postpartum abstinence among women age 30-49 (11.6 months) and women age 15-29 (11.7 months) is essentially equivalent. Median duration of postpartum insusceptibility is similar for older women and younger women (12.9 and 13.3 months, respectively). Women in rural areas have a longer median duration of amenorrhea than women in urban areas (9.7 versus 6.8 months), but they differ from women in urban areas in median duration of postpartum abstinence by less than one month (12.1 versus 11.3 months). Median duration of postpartum insusceptibility is slightly longer among women in rural areas (13.6 months) than women in urban areas (12.4 months). In urban areas, postpartum insusceptibility is shorter in median duration in Greater Monrovia (11.8 months) than in other urban areas (13.7 months). Table 5.7 Median duration of amenorrhea, postpartum abstinence, and postpartum insusceptibility Median number of months of postpartum amenorrhea, postpartum abstinence, and postpartum insusceptibility following births in the three years preceding the survey, by background characteristics, Liberia 2013 Background characteristic Postpartum amenorrhea Postpartum abstinence Postpartum insusceptibility1 Mother's age 15-29 7.4 11.7 13.3 30-49 9.9 11.6 12.9 Residence Urban 6.8 11.3 12.4 Greater Monrovia 4.5 10.7 11.8 Other urban 10.1 12.2 13.7 Rural 9.7 12.1 13.6 Region North Western 7.4 11.9 13.7 South Central 6.0 10.6 12.2 South Eastern A 8.2 11.3 13.1 South Eastern B 9.2 9.1 12.0 North Central 11.4 13.6 14.4 County Bomi (4.9) (12.8) (13.1) Bong 10.7 13.6 14.0 Gbarpolu (8.8) 11.9 (13.2) Grand Bassa 8.2 7.7 10.3 Grand Cape Mount 7.7 11.2 14.3 Grand Gedeh 7.9 (14.9) (15.1) Grand Kru (9.6) (9.5) (12.7) Lofa 7.8 15.5 (19.3) Margibi 9.5 12.6 13.8 Maryland 8.0 9.0 10.5 Montserrado 4.7 11.0 12.1 Nimba 11.9 13.0 14.2 River Cess 9.6 6.8 11.9 River Gee (11.9) (8.3) (12.4) Sinoe (6.4) 11.7 (12.6) Education No education 11.2 12.5 13.9 Primary 7.7 11.7 13.6 Secondary and higher 6.1 11.0 11.9 Wealth quintile Lowest 11.8 12.2 14.1 Second 9.9 12.6 13.5 Middle 7.5 10.8 13.1 Fourth 6.8 11.6 12.3 Highest (4.3) 9.8 11.5 Total 8.3 11.6 13.1 Note: Medians are based on the status at the time of the survey (current status). Figures in parentheses are based on 25-49 unweighted cases. 1 Includes births for which mothers are either still amenorrheic or still abstaining (or both) following birth Fertility • 77 Postpartum insusceptibility decreases with increasing educational level and wealth quintile. Median duration of postpartum insusceptibility is 13.9 months for women with no education and decreases to 11.9 months for women with at least some secondary education. Among women in the lowest wealth quintile, median duration of postpartum insusceptibility is 14.1 months, compared with 11.5 months among women in the highest wealth quintile. 5.8 MENOPAUSE Fecundity refers to the ability to have children. The risk of pregnancy declines with age as increasing proportions of women become infecund. Although the onset of infecundity is difficult to determine for an individual woman, there are ways of estimating it for a population. Table 5.8 presents data on menopause, an indicator of decreasing exposure to the risk of pregnancy for women age 30 and older. The percentage of women who have reached menopause refers to the population of women who are neither pregnant nor postpartum amenorrheic and have not had a menstrual period in the six months preceding the survey, or women who report being menopausal. Table 5.8 shows that overall, 13 percent of women age 30-49 are menopausal. The proportion of menopausal women increases with age, from 4 percent among women age 30-34 to 56 percent among women age 48-49. 5.9 AGE AT FIRST BIRTH The age at which childbearing begins has an impact on the health and welfare of a mother and her children. In many countries, the postponement of first births has contributed to an overall fertility decline. Table 5.9 shows the distribution of women by age at first birth, according to their current age. The median age at first birth in Liberia is around 19 for most age groups, which is similar to results from the 2007 LDHS. However, more detailed analysis of trends in age at first birth does reveal a decline in early childbearing. For example, whereas 45 percent of women currently age 45-49 gave birth by age 18, only 37 percent of women currently age 20-24 had their first birth by age 18. Table 5.9 Age at first birth Percentage of women age 15-49 who gave birth by exact ages, percentage who have never given birth, and median age at first birth, according to current age, Liberia 2013 Current age Percentage who gave birth by exact age Percentage who have never given birth Number of women Median age at first birth 15 18 20 22 25 15-19 2.5 na na na na 74.2 2,080 a 20-24 5.9 37.0 62.6 na na 20.3 1,642 19.0 25-29 6.4 34.1 60.6 79.4 89.6 6.3 1,611 19.2 30-34 7.2 38.7 62.2 79.0 89.6 2.5 1,199 18.9 35-39 8.9 43.2 62.1 75.2 85.7 2.3 1,179 18.8 40-44 12.0 47.4 65.7 79.4 89.6 1.8 812 18.3 45-49 9.1 45.2 66.2 78.8 87.1 0.5 716 18.4 20-49 7.8 39.6 62.7 na na 7.1 7,159 18.9 25-49 8.3 40.4 62.8 78.4 88.4 3.2 5,517 18.9 na = Not applicable due to censoring a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group Table 5.8 Menopause Percentage of women age 30-49 who are menopausal, by age, Liberia 2013 Age Percentage menopausal1 Number of women 30-34 4.0 1,199 35-39 3.6 1,179 40-41 9.9 380 42-43 13.3 282 44-45 24.0 311 46-47 36.8 229 48-49 55.7 326 Total 12.9 3,906 1 Percentage of all women who are not pregnant and not postpartum amenorrheic whose last menstrual period occurred six or more months preceding the survey 78 • Fertility 5.10 MEDIAN AGE AT FIRST BIRTH BY BACKGROUND CHARACTERISTICS Table 5.10 summarizes the median age at first birth for different age cohorts across residential, educational, and wealth status subgroups. For women age 25-49, the median age at first birth is higher in urban areas than in rural areas (19.2 versus 18.4 years). For this same cohort, age at first birth increases slightly with increasing levels of education and wealth. Women with no education or at least some primary school have their first birth about one year earlier than women with secondary or higher education (18.5 versus 19.6). Women in the lowest wealth quintile have their first birth 1.4 years earlier than women in the highest wealth quintile (18.4 versus 19.8 years). Table 5.10 Median age at first birth Median age at first birth among women age 20-49 and age 25-49, according to background characteristics, Liberia 2013 Background characteristic Women age 20-49 25-49 Residence Urban 19.3 19.2 Greater Monrovia 19.6 19.5 Other urban 18.9 18.9 Rural 18.3 18.4 Region North Western 18.3 18.4 South Central 19.3 19.3 South Eastern A 18.2 18.2 South Eastern B 18.5 18.5 North Central 18.6 18.5 County Bomi 18.2 18.2 Bong 18.2 18.2 Gbarpolu 18.5 18.5 Grand Bassa 18.2 18.1 Grand Cape Mount 18.3 18.5 Grand Gedeh 18.0 18.0 Grand Kru 18.8 19.0 Lofa 18.3 18.4 Margibi 19.4 19.5 Maryland 18.4 18.4 Montserrado 19.5 19.4 Nimba 18.9 18.9 River Cess 17.8 17.7 River Gee 17.9 17.9 Sinoe 18.6 18.7 Education No education 18.4 18.5 Primary 18.4 18.5 Secondary and higher 19.8 19.6 Wealth quintile Lowest 18.3 18.4 Second 18.1 18.2 Middle 18.8 18.9 Fourth 19.1 19.1 Highest a 19.8 Total 18.9 18.9 a = Omitted because less than 50 percent of the women had a birth before reaching the beginning of the age group Fertility • 79 5.11 TEENAGE PREGNANCY AND MOTHERHOOD The issue of adolescent fertility is important for both health and social reasons. Children born to very young mothers are at increased risk of sickness and death. Teenage mothers are more likely to experience adverse pregnancy outcomes and are also more constrained in their ability to pursue educational opportunities than young women who delay childbearing. Table 5.11 shows the percentage of women age 15- 19 who have given birth or were pregnant with their first child at the time of the survey, according to selected background characteristics. Overall, 31 percent of women age 15-19 have begun childbearing. The proportion of teenagers who have had a live birth rises rapidly with age, increasing from 2 percent at age 15 to 54 percent at age 19. Rural teenagers, those with no education, and those in the lower wealth quintiles tend to start childbearing earlier than their urban, better educated, and wealthier peers. Table 5.11 Teenage pregnancy and motherhood Percentage of women age 15-19 who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Liberia 2013 Background characteristic Percentage of women age 15-19 who: Percentage who have begun childbearing Number of women Have had a live birth Are pregnant with first child Age 15 2.0 1.8 3.8 517 16 11.4 7.4 18.7 457 17 27.3 7.0 34.3 336 18 45.7 6.3 52.0 380 19 53.7 6.2 59.9 390 Residence Urban 21.2 5.1 26.3 1,400 Greater Monrovia 15.7 5.2 20.9 858 Other urban 30.0 4.9 35.0 542 Rural 35.2 6.4 41.6 680 Region North Western 26.7 7.4 34.1 168 South Central 19.1 4.8 23.9 1,228 South Eastern A 48.2 7.4 55.6 82 South Eastern B 35.6 7.4 43.0 116 North Central 36.3 6.0 42.3 486 County Bomi 20.9 11.2 32.1 52 Bong 41.5 6.4 47.9 147 Gbarpolu 31.2 7.1 38.3 37 Grand Bassa 38.8 6.7 45.5 88 Grand Cape Mount 28.5 5.0 33.5 79 Grand Gedeh 52.2 5.7 57.9 29 Grand Kru 41.0 5.3 46.3 37 Lofa 34.4 4.0 38.5 85 Margibi 19.5 2.5 22.0 200 Maryland 31.8 8.1 39.9 64 Montserrado 17.2 5.1 22.3 940 Nimba 33.9 6.4 40.3 253 River Cess 47.3 9.9 57.2 22 River Gee 38.4 9.7 48.1 15 Sinoe 45.1 7.1 52.2 31 Education No education 41.3 7.5 48.9 144 Primary 24.8 5.9 30.7 1,155 Secondary and higher 24.5 4.5 29.1 781 Wealth quintile Lowest 39.9 7.1 47.0 247 Second 38.4 6.1 44.5 296 Middle 33.3 6.2 39.6 399 Fourth 23.9 3.4 27.3 489 Highest 11.5 5.8 17.3 650 Total 25.8 5.5 31.3 2,080 Fertility Preferences • 81 FERTILITY PREFERENCES 6 nformation on fertility preferences is of considerable importance to family planning program planners because it allows an assessment of the need for contraception, whether for spacing or limiting births, and of the extent of unwanted and mistimed pregnancies. Data on fertility preferences can also be useful as an indicator of the direction that future fertility patterns may take. In the 2013 LDHS, respondents were asked whether they wanted more children and, if so, how long they would prefer to wait before the next child. They were also asked, if they could start afresh, how many children they would want. 6.1 FERTILITY PREFERENCES BY NUMBER OF LIVING CHILDREN Table 6.1 presents fertility preferences among currently married women and men, by number of living children. When classifying people according to their fertility preferences, the desired timing of the next birth is taken into account. Sixty-three percent of currently married women in Liberia would like to have another child. Among those who want another child, about one-third want a child within the coming two years, while most (about two-thirds) would prefer to wait two or more years before having their next birth. Three in ten married women want no more children. Thus, the majority of women (69 percent) want either to delay their next birth (for two or more years into the future) or end childbearing altogether. The preferences of currently married men generally mirror those of currently married women. As expected, the desire to have children depends on the number of living children a woman or man already has. Seven in ten married women with no children want to have a child soon (within two years). In contrast, the desire to have more children decreases dramatically among women who already have several living children. The proportion reporting that they do not want another child increases from 21 percent among women with three children to 67 percent among women with six or more children. Here too, the preferences of currently married men generally agree with those of currently married women. I Key Findings • More than three in five married women (63 percent) and men (62 percent) would like to have another child. • Approximately three in ten married women and men want no more children. • The ideal number of children is 4.8 for all women and 5.0 for all men. • Overall, 69 percent of all births were wanted at the time of conception, 26 percent were reported as mistimed (wanted later), and 5 percent were unwanted. • The total wanted fertility rate is 4.0 children per woman, compared with the actual fertility rate of 4.7 children per woman. 82 • Fertility Preferences Table 6.1 Fertility preferences by number of living children Percent distribution of currently married women and currently married men age 15-49 by desire for children, according to number of living children, Liberia 2013 Desire for children Number of living children Total 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 70.7 30.5 24.2 18.7 14.4 9.3 10.0 20.5 Have another later3 18.1 57.0 54.5 49.0 32.4 23.9 13.6 39.2 Have another, undecided when 5.1 7.1 6.0 3.4 2.5 0.4 0.4 3.6 Undecided 0.6 3.1 3.4 5.1 4.6 4.5 4.0 4.0 Want no more 0.1 1.4 11.0 20.5 41.9 58.1 66.5 29.6 Sterilized4 0.0 0.0 0.0 0.0 1.1 0.0 0.6 0.3 Declared infecund 5.4 0.9 0.7 3.3 3.0 3.8 4.5 2.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 207 836 1,100 969 787 634 851 5,386 MEN5 Have another soon2 57.5 23.2 25.7 25.7 17.3 15.7 11.8 21.3 Have another later3 37.3 60.7 50.0 40.4 31.2 23.7 21.5 38.6 Have another, undecided when 0.6 4.0 3.9 2.1 2.3 1.8 1.4 2.5 Undecided 3.3 5.2 6.3 12.4 11.2 12.3 8.8 9.0 Want no more 0.6 6.3 13.8 19.1 37.9 46.5 55.2 28.1 Sterilized4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Declared infecund 0.0 0.0 0.1 0.3 0.0 0.0 1.2 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 68 359 414 394 303 258 423 2,218 Note: Totals include 7 women and 4 men with information missing on the desire for children. 1 The number of living children includes the current pregnancy. 2 Wants next birth within 2 years 3 Wants to delay next birth for 2 or more years 4 Includes both female and male sterilization 5 The number of living children includes one additional child if respondent's wife is pregnant (or if any wife is pregnant for men with more than one current wife). 6.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Tables 6.2.1 and 6.2.2 present the percentages of currently married women and men who want no more children, by number of living children and selected background characteristics. Overall, three in ten married women want no more children. The desire to limit childbearing is slightly higher among rural women (35 percent) than among urban women (26 percent). The association between education and the desire to limit childbearing is most evident when women weigh whether or not to have a fifth or sixth child. By the time they have four children, for example, about one- third of women who have no education or primary education only, compared with two-thirds of women who have at least some secondary education, want no more children. Similarly, the association between wealth and the desire to limit childbearing is most evident when women weigh whether or not to have a fifth or sixth child. For example, 35 percent of women in the lowest wealth quintile, compared with 60 percent of women in the highest wealth quintile, want no more children by the time they have four children. For currently married men, Table 6.2.2 suggests that residence, education, and wealth are not strongly associated with the desire to limit childbearing. However, there are too few cases to make comparisons by number of children. Fertility Preferences • 83 Table 6.2.1 Desire to limit childbearing: Women Percentage of currently married women age 15-49 who want no more children, by number of living children, according to background characteristics, Liberia 2013 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 0.2 0.6 11.2 19.2 47.3 64.1 64.0 25.9 Greater Monrovia (0.0) 0.4 14.1 16.2 57.2 73.8 (68.1) 25.1 Other urban 0.6 0.9 6.5 23.5 37.2 52.0 62.3 26.9 Rural 0.0 3.4 10.6 21.8 38.8 52.9 69.0 34.5 Region North Western (1.4) 1.8 8.3 18.7 42.0 58.8 73.4 33.9 South Central 0.0 1.1 13.3 21.8 48.5 66.2 69.8 28.2 South Eastern A (0.0) 4.8 12.4 19.8 27.5 50.6 68.3 33.4 South Eastern B (0.0) 2.8 17.6 28.7 49.7 54.2 68.8 39.7 North Central (0.0) 1.2 6.1 17.3 38.2 48.0 62.2 28.1 County Bomi * (4.1) 5.3 11.8 46.2 (58.9) (63.1) 29.9 Bong * (2.6) 7.3 15.4 34.0 44.3 57.7 28.3 Gbarpolu * (0.0) 7.3 24.8 (29.6) 46.1 71.5 28.8 Grand Bassa * (2.2) 9.0 26.7 42.7 58.0 61.1 35.3 Grand Cape Mount * (1.8) 10.2 19.9 44.2 63.9 77.6 37.8 Grand Gedeh * 1.8 6.6 15.8 (18.9) (46.8) 69.3 27.1 Grand Kru * * (22.1) 37.1 (45.8) (51.9) 59.6 41.3 Lofa * 0.8 4.8 19.7 52.1 (51.2) (65.4) 28.3 Margibi * 5.0 12.2 40.7 26.4 55.1 83.4 34.4 Maryland * (5.6) 13.3 22.0 (54.8) (55.8) 79.4 40.0 Montserrado (0.0) 0.4 13.8 16.1 55.1 72.0 68.3 25.7 Nimba * 0.5 5.9 18.2 36.3 51.6 65.2 27.9 River Cess * (0.0) (10.7) 20.4 (36.6) 60.5 68.4 38.2 River Gee * (0.0) (19.5) (22.0) (44.9) (55.0) 70.0 36.1 Sinoe * 11.5) 18.8 23.1 29.2 44.9 67.3 35.2 Education No education 0.5 3.3 9.9 21.0 37.2 55.3 67.0 36.4 Primary 0.0 1.2 10.5 16.3 36.0 59.4 66.3 25.7 Secondary and higher 0.0 0.6 12.0 23.5 67.3 68.2 69.7 23.6 Wealth quintile Lowest 0.0 3.7 9.0 20.2 34.6 44.4 68.4 32.0 Second (0.9) 2.6 10.4 22.2 38.4 55.9 67.0 35.5 Middle (0.0) 0.1 7.0 20.1 46.3 60.3 65.1 29.8 Fourth (0.0) 1.0 13.4 16.6 39.1 64.2 67.5 24.6 Highest (0.0) 1.0 13.1 24.2 60.0 (74.7) (69.0) 27.4 Total 0.1 1.4 11.0 20.5 43.0 58.1 67.2 29.9 Note: Women who have been sterilized are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The number of living children includes the current pregnancy 84 • Fertility Preferences Table 6.2.2 Desire to limit childbearing: Men Percentage of currently married men age 15-49 who want no more children, by number of living children, according to background characteristics, Liberia 2013 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban (0.0) 8.3 16.3 19.6 43.8 47.5 58.4 28.1 Greater Monrovia * (7.5) (20.9 (15.3) * * * 27.4 Other urban * 9.8 8.2 24.6 46.3 28.5 55.5 28.8 Rural (1.1) 3.1 10.1 18.7 32.5 45.4 53.0 28.2 Region North Western * 3.9 10.4 25.1 44.3 57.0 57.0 32.2 South Central * 5.5 17.2 17.5 42.9 55.2 65.1 28.1 South Eastern A * 1.0 5.4 12.6 17.7 (31.2) 49.8 23.2 South Eastern B * (7.7) 19.6 14.8 (29.1) (48.3) 53.7 32.7 North Central * 9.9 6.5 21.1 34.4 35.5 47.2 26.7 County Bomi * * * (40.2) * * * 43.4 Bong * * (10.3) (31.7) (39.4) * (48.5) 31.4 Gbarpolu * * * (23.1) * (47.5) (57.6) 26.8 Grand Bassa * * (0.0) * * * (58.4) 28.0 Grand Cape Mount * * (11.6) (16.8) (45.4) * (47.5) 29.8 Grand Gedeh * * * * * * (34.8) 13.0 Grand Kru * * * (22.3) * * (45.3) 33.5 Lofa * (7.4) (11.7) (11.1) * (46.9) (40.1) 24.0 Margibi * (0.0) (16.8) (23.2) (48.1) * (69.1) 30.2 Maryland * * * * * * 59.7 36.4 Montserrado * 7.1 19.8 (15.6) (41.7) (66.7) (66.6) 27.5 Nimba * (18.6) (0.0) (9.7) (35.4) (16.6) 48.9 23.8 River Cess * * * * * * (55.3) 32.1 River Gee * * * * * * (59.9) 25.4 Sinoe * * * * * * 54.1 24.4 Education No education * (0.6) (12.5) 14.7 31.9 38.6 57.9 30.2 Primary * 7.9 7.0 14.3 33.5 33.4 50.4 24.0 Secondary and higher (0.9) 6.6 16.2 23.9 43.7 54.8 56.4 29.4 Wealth quintile Lowest * 0.7 15.2 14.2 24.0 42.7 47.2 24.5 Second * 7.2 3.1 18.0 31.6 34.6 61.9 28.7 Middle * 4.7 23.5 22.9 53.9 41.8 50.3 32.7 Fourth * 15.5 22.4 20.4 (34.7) (55.6) 47.9 27.8 Highest * 2.7 (3.8) (21.4) * * (71.6) 27.4 Total 0.6 6.3 13.8 19.1 37.9 46.5 55.2 28.1 Note: Men who have been sterilized or who state in response to the question about desire for children that their wife has been sterilized are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The number of living children includes one additional child if respondent's wife is pregnant (or if any wife is pregnant for men with more than one current wife). 6.3 IDEAL NUMBER OF CHILDREN Women and men, regardless of marital status, were asked what number of children they would choose to have if they could start afresh. Respondents who had no children were asked, “If you could choose exactly the number of children to have in your whole life, how many would that be?” For respondents who had children, the question was rephrased as follows: “If you could go back to the time when you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be?” Responses to these questions are summarized in Table 6.3 for both women and men age 15-49. The data in the top portion of each panel in Table 6.3 indicate that the vast majority of women and men were able to give a numeric answer to this hypothetical question. Only 4 percent of women and 2 percent Fertility Preferences • 85 of men gave a non-numeric answer such as “It is up to God,” “any number,” or “I do not know.” Among all women and men, the mean ideal number of children is 4.8 for women and 5.0 for men. Among currently married women and men, the mean ideal number of children is 5.3 for women and 5.6 for men. Overall, 73 percent of women and 70 percent of men ideally would want four or more children. When interpreting the findings in Table 6.3, it is important to remember that the actual and stated ideal number of children tend to be related. There are several reasons for this. First, to the extent that women are able to fulfil their fertility desires, women who want large families will achieve large families. Second, because women with large families are, on average, older women, they may prefer a greater number of children because of the attitudes towards childbearing to which they were exposed during the early stages of their reproductive lives. Finally, some women may have difficulty admitting that they would prefer fewer children than they currently have if they could begin childbearing again. Such women are likely to report their actual number as their preferred number. Indeed, women who have fewer children do report a smaller ideal number of children than women with more children. The mean ideal number of children among all women with one child is 4.2, compared with 6.9 among all women with six or more children. The relationship between the actual and ideal number of children is also presented for men in Table 6.3. Men who have fewer children report a smaller ideal number of children than men with more children. For example, the average ideal number of children is 3.9 among all men with one child, compared with 7.9 among all men with six or more children. Table 6.3 Ideal number of children by number of living children Percent distribution of women and men 15-49 by ideal number of children, and mean ideal number of children for all respondents and for currently married respondents, according to the number of living children, Liberia 2013 Ideal number of children Number of living children Total 0 1 2 3 4 5 6+ WOMEN1 0 0.2 0.0 0.2 0.2 0.7 0.2 0.6 0.3 1 1.0 0.7 0.7 0.4 0.1 0.0 0.0 0.5 2 15.3 9.1 5.6 1.9 3.1 3.1 1.4 6.9 3 21.1 24.9 15.7 9.6 7.5 6.6 5.8 15.2 4 38.8 37.2 40.6 31.5 28.4 16.3 12.5 32.1 5 11.0 12.4 15.3 17.6 13.7 13.8 11.6 13.5 6+ 10.4 14.1 19.1 34.3 39.9 50.8 59.9 27.3 Non-numeric responses 2.4 1.7 2.8 4.5 6.8 9.2 8.2 4.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,987 1,755 1,591 1,222 945 744 995 9,239 Mean ideal number of children for:2 All women 3.9 4.2 4.4 5.2 5.4 6.1 6.9 4.8 Number of women 1,940 1,725 1,546 1,167 881 675 913 8,849 Currently married women 4.5 4.4 4.5 5.3 5.5 6.2 7.0 5.3 Number of currently married women 199 820 1,067 920 730 573 780 5,089 MEN3 0 1.9 0.4 0.0 0.0 1.0 0.0 0.7 0.9 1 0.9 1.9 0.0 0.0 0.3 0.0 0.4 0.7 2 17.7 13.3 6.7 2.2 6.0 2.8 1.7 10.5 3 17.9 28.1 13.7 16.0 5.2 6.9 3.5 15.3 4 31.0 32.2 41.2 30.1 25.5 15.8 15.9 29.3 5 10.9 10.9 16.5 20.1 16.1 28.8 10.0 14.1 6+ 17.8 11.8 18.7 30.4 43.8 44.3 63.8 27.0 Non-numeric responses 1.9 1.5 3.2 1.1 2.0 1.5 4.0 2.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,572 563 518 443 312 276 433 4,118 Mean ideal number of children for:2 All men 4.3 3.9 4.6 5.2 5.6 6.2 7.9 5.0 Number of men 1,542 555 501 438 306 272 416 4,030 Currently married men 4.3 3.9 4.6 5.3 5.6 6.3 7.9 5.6 Number of currently married men 62 353 403 389 297 254 406 2,164 1 The number of living children includes current pregnancy for women. 2 Means are calculated excluding respondents who gave non-numeric responses. 3 The number of living children includes one additional child if respondent's wife is pregnant (or if any wife is pregnant for men with more than one current wife). 86 • Fertility Preferences 6.4 MEAN IDEAL NUMBER OF CHILDREN BY BACKGROUND CHARACTERISTICS Table 6.4 shows the mean ideal number of children among all women age 15-49, by background characteristics. The mean ideal number of children increases consistently with age, from 4.0 among women age 15-19 to 6.4 among women age 45-49. Women in rural areas have higher family size norms than those in urban areas (5.4 and 4.5 children, respectively). Among urban areas, women in Greater Monrovia have lower family size norms than those in other urban areas (4.2 and 4.9 children, respectively). The mean ideal number of children consistently decreases with increasing education, differing by almost two children between the lowest and highest education categories. The mean ideal number of children also decreases with increasing wealth quintile, also differing by almost two children between the lowest and highest wealth quintiles (5.8 and 4.0, respectively). 6.5 FERTILITY PLANNING STATUS The issue of unplanned and unwanted fertility was investigated in the 2013 LDHS by asking women who had births during the five years before the survey whether the births were wanted at the time (planned), wanted at a later time (mistimed), or not wanted at all (unwanted). The responses to those questions provide a measure of the degree to which Liberian couples have been successful in controlling childbearing. In addition, the information can be used to estimate the effect on fertility if unwanted pregnancies had been prevented. Questions pertaining to the planning status of recent births required the female respondent to recall accurately her wishes at one or more points in the past five years and report them honestly. These questions are subject to recall and accuracy bias in remembering how she felt about a particular pregnancy. She also may not be willing to admit that she had not wanted a child at its conception. Conversely, if the child has become an economic or health burden, she may now claim that it was unwanted. Despite these potential problems of comprehension, recall, and truthfulness, results from previous surveys have yielded plausible responses, with the most probable effect of biases in the answers being net underestimation of the level of unwanted fertility. Table 6.4 Mean ideal number of children by background characteristics Mean ideal number of children for all women age 15-49 by background characteristics, Liberia 2013 Background characteristic Mean Number of women1 Age 15-19 4.0 2,032 20-24 4.3 1,592 25-29 4.7 1,573 30-34 5.2 1,141 35-39 5.4 1,118 40-44 6.0 755 45-49 6.4 638 Residence Urban 4.5 5,439 Greater Monrovia 4.2 3,243 Other urban 4.9 2,197 Rural 5.4 3,410 Region North Western 5.1 806 South Central 4.4 4,665 South Eastern A 5.9 458 South Eastern B 4.9 554 North Central 5.4 2,366 County Bomi 4.8 240 Bong 5.3 786 Gbarpolu 5.0 173 Grand Bassa 5.8 419 Grand Cape Mount 5.4 393 Grand Gedeh 6.1 166 Grand Kru 5.1 209 Lofa 5.3 440 Margibi 4.4 711 Maryland 4.7 249 Montserrado 4.2 3,536 Nimba 5.5 1,140 River Cess 5.5 123 River Gee 5.1 96 Sinoe 6.0 169 Education No education 5.8 2,856 Primary 4.8 2,768 Secondary and higher 4.0 3,224 Wealth quintile Lowest 5.8 1,479 Second 5.4 1,547 Middle 4.9 1,726 Fourth 4.5 1,974 Highest 4.0 2,123 Total 4.8 8,849 1 Number of women who gave a numeric response Fertility Preferences • 87 Table 6.5 shows the distribution of births in the five years before the survey by whether a birth was wanted then, wanted later, or not wanted. Overall, 69 percent of all births were wanted at the time of conception, 26 percent were reported as mistimed (wanted later), and 5 percent were unwanted. The proportion of unwanted births is greater for births that are fourth order or more (10 percent) than for first births (less than 1 percent). Similarly, a much larger proportion of births to older women are unwanted than are those to younger women. Whereas only 1 percent of births to women age 20-24 are unwanted, 35 percent of births to women age 45-49 are unwanted. Table 6.5 Fertility planning status Percent distribution of births to women age 15-49 in the five years preceding the survey (including current pregnancies), by planning status of the birth, according to birth order and mother's age at birth, Liberia 2013 Birth order and mother's age at birth Planning status of birth Total Number of births Wanted then Wanted later Wanted no more Birth order 1 60.1 39.7 0.2 100.0 1,786 2 71.5 27.3 1.1 100.0 1,467 3 75.3 22.8 1.7 100.0 1,118 4+ 71.8 17.8 10.2 100.0 2,896 Mother's age at birth <20 54.3 45.1 0.4 100.0 1,507 20-24 70.6 28.3 1.0 100.0 1,940 25-29 76.0 20.3 3.5 100.0 1,628 30-34 75.4 17.1 7.4 100.0 1,144 35-39 74.3 12.3 12.8 100.0 743 40-44 68.3 10.5 21.3 100.0 260 45-49 55.8 9.5 34.6 100.0 45 Total 69.4 25.9 4.6 100.0 7,267 Note: Total includes 10 women for whom information on planning status of the birth is missing. 6.6 WANTED FERTILITY RATES Responses to the question on the ideal number of children are used to calculate a total “wanted” fertility rate. This measure is calculated in the same manner as the conventional total fertility rate, except that unwanted births are excluded from the numerator. A birth is considered wanted if the number of living children at the time of conception is less than the ideal number of children currently reported by the respondent. Wanted fertility rates express the level of fertility that theoretically would result if all unwanted births were prevented. Comparison of the actual fertility rate with the wanted rate indicates the potential demographic impact of eliminating unwanted births. Table 6.6 shows that the wanted fertility rate is 4.0 children, compared with the actual fertility rate of 4.7 children (rates calculated over the three years prior to the survey). In other words, Liberian women are currently having an average of 0.7 children more than they actually want. The table also shows that regardless of place of residence, level of education, and wealth quintile, the wanted fertility rate is lower than the actual total fertility rate. Women in rural areas have a larger gap between their actual and wanted fertility (1.0) than do women in urban areas (0.5). Women with higher levels of education as well as those in the higher wealth quintiles seem to be the most successful in achieving their fertility goals; that is, the gap between wanted and actual fertility narrows as education and wealth quintile increase. 88 • Fertility Preferences Table 6.6 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Liberia 2013 Background characteristic Total wanted fertility rates Total fertility rate Residence Urban 3.3 3.8 Greater Monrovia 2.7 3.2 Other urban 4.1 4.8 Rural 5.1 6.1 Region North Western 4.8 5.8 South Central 3.2 3.8 South Eastern A 5.6 6.5 South Eastern B 4.5 5.9 North Central 4.8 5.6 Education No education 4.9 5.9 Primary 4.3 5.1 Secondary and higher 2.9 3.4 Wealth quintile Lowest 5.6 6.6 Second 5.1 5.9 Middle 4.4 5.2 Fourth 3.3 3.9 Highest 2.4 2.8 Total 4.0 4.7 Note: Rates are calculated based on births to women age 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 5.2. Family Planning • 89 FAMILY PLANNING 7 amily planning refers to a conscious effort by a couple to limit or space the number of children they want to have through the use of contraceptives. This chapter presents results from the 2013 LDHS on a number of aspects of contraception: knowledge of specific contraceptive methods, attitudes and behavior towards contraceptive use, current use, and sources of current contraceptive methods. This focus is on women who are sexually active because these women have the greatest risk of exposure to pregnancy and therefore the greatest need for regulating their fertility. The results of interviews with men are presented along with those of women because men and women play an equally important role in making decisions about reproductive health and family planning. 7.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Information about contraceptive methods was collected by asking respondents if they had heard of various methods that a couple can use to delay or avoid a pregnancy. Specifically, the interviewer named a method, described it, and then asked whether the respondent had heard of it. In all, the interviewer asked about thirteen different contraceptive methods. Provision was also made in the questionnaire to record any additional methods the respondent had heard of but was not asked about by the interviewer. Contraceptive methods are classified into two broad categories, namely modern methods and traditional methods. Modern methods include female sterilization, male sterilization, the pill, the intrauterine F Key Findings • Knowledge of at least one method of contraception is nearly universal in Liberia: 98 percent of women and 95 percent of men have heard of at least one method. • The contraceptive prevalence rate has increased to 20 percent among currently married women. In 2007, this rate was only 11 percent. • Among currently married women, the contraceptive method most commonly used is injectables (11 percent). • A majority of modern contraceptive users obtain their contraceptives from the public sector (64 percent). Government hospitals are the most common public source (30 percent), followed by government health clinics (27 percent). • Seventy-five percent of modern contraceptive users were informed of side effects or health problems associated with the method they used; 73 percent knew what to do if they experienced side effects, and 72 percent had been told of other methods available. • Only 13 percent of women know that they are most fertile midway between two menstrual periods. • Thirty-one percent of currently married women have an unmet need for family planning services (22 percent for spacing and 9 percent for limiting births). • Among currently married women, only 39 percent of the demand for family planning has been satisfied. 90 • Family Planning device (IUD), injectables, implants, the male condom, the female condom, the lactational amenorrhea method (LAM), emergency contraception, and the CycleBeads® or standard days method. Traditional methods include rhythm (periodic abstinence), withdrawal, and various folk methods such as use of strings and herbs. Table 7.1 shows that knowledge of contraceptive methods is almost universal in Liberia, with 98 percent of all women and 95 percent of all men knowing at least one method of contraception. Modern methods are more widely known than traditional methods; 98 percent of all women know of a modern method, while 55 percent know of a traditional method. Similarly, 95 percent of all men know of a modern method, while 58 percent know of a traditional method. Table 7.1 Knowledge of contraceptive methods Percentage of all respondents, currently married respondents and sexually active unmarried respondents age 15-49 who know any contraceptive method, by specific method, Liberia 2013 Method Women Men All women Currently married women Sexually active unmarried women1 All men Currently married men Sexually active unmarried men1 Any method 98.2 98.6 99.2 94.8 97.9 98.4 Any modern method 98.2 98.6 99.2 94.8 97.9 98.3 Female sterilization 42.1 44.3 42.8 39.7 45.3 46.3 Male sterilization 19.9 19.9 23.1 20.0 23.9 24.1 Pill 97.1 97.7 98.6 77.6 83.6 85.0 IUD 43.5 45.4 48.8 25.2 28.7 31.6 Injectables 94.0 94.6 96.6 66.8 72.9 75.7 Implants 86.5 87.0 91.3 50.4 55.3 61.5 Male condom 94.9 95.2 97.9 94.2 97.4 98.2 Female condom 69.3 69.7 78.6 56.1 62.7 64.8 Lactational amenorrhea (LAM) 7.8 8.2 9.7 8.8 9.2 13.1 Emergency contraception 28.7 28.8 35.6 25.3 28.5 33.4 Cyclebeads/Standard Days 20.1 20.4 24.4 12.3 15.6 12.5 Any traditional method 55.4 57.7 60.1 58.0 66.5 69.7 Rhythm 39.9 40.9 46.0 36.9 41.4 47.5 Withdrawal 48.1 50.0 54.2 55.9 64.1 68.3 Other 2.9 3.4 1.3 2.9 3.7 2.3 Mean number of methods known by respondents 6.9 7.1 7.5 5.7 6.3 6.6 Number of respondents 9,239 5,386 1,548 4,118 2,218 729 1 Had last sexual intercourse within 30 days preceding the survey Women in Liberia have heard of an average of seven contraceptive methods, and men have heard of an average of six methods. Both figures are an increase from those reported in the 2007 LDHS (four methods each for women and men). The pill, male condoms, and injectables are the contraceptive methods most widely known by women in Liberia. Among all women age 15-49, 97 percent have heard of the pill, 95 percent have heard of the male condom, and 94 percent have heard of injectables. Each of these figures is markedly higher than those reported in the 2007 LDHS (82 percent, 79 percent, and 74 percent, respectively). Knowledge of several other modern methods has also dramatically increased. For example, according to the 2013 LDHS, 87 percent of women have heard of implants, 69 percent know of the female condom, and 44 percent are familiar with the IUD. By comparison, according to the 2007 LDHS, only 6 percent of women had heard of implants, 24 percent had heard of the female condom, and 30 percent had heard of the IUD. The most well-known methods of contraception among all men age 15-49 are the male condom (94 percent), the pill (78 percent), and injectables (67 percent). The proportion of men who have heard of each of these methods as well as implants, female condoms, and the IUD is higher than in the 2007 LDHS, just as it is Family Planning • 91 for women. The lactational amenorrhea method (LAM) is the least-known modern contraceptive method among both men (9 percent) and women (8 percent). Knowledge of at least one contraceptive method is higher among currently married women and men than among all women and all men, but varies only minimally by background characteristics (data not shown). For example, for all age groups of currently married women and men, the percentage who know at least one modern family planning method exceeds 95 percent (data not shown). 7.2 CURRENT USE OF CONTRACEPTION Prevalence of contraceptive use among women in Liberia at the time of the survey is one of the principal determinants of their fertility. Changes in prevalence that have occurred over time can indicate the overall success of family planning programs in Liberia. Contraceptive use among all women, currently married women, and sexually active unmarried women, age 15-49, is presented in Table 7.2 The contraceptive prevalence rate (CPR), or the percentage of currently married women in Liberia who use a contraceptive method, is 20 percent, while the CPR for modern contraceptive methods in the country is 19 percent. Among currently married women, the contraceptive method most commonly used is injectables (11 percent). The other modern methods used by currently married women are the pill (5 percent) and implants (2 percent). Less than 1 percent of currently married women use female sterilization, the male condom, or other modern methods. The use of modern contraceptive methods among currently married women increases with age, from 13 percent of those age 15-19 to 23 percent of those ages 20-24, 25-29, and 30-34. Later, use gradually falls to a low of 6 percent among women age 45-49. A similar pattern emerges in the use of injectables, which increase from 11 percent to 15 percent among currently married women age 15-19, 20-24, and 25-29 before declining to a low of 2 percent among women age 45-49. A comparison between CPRs for modern contraceptive methods in the 2007 LDHS and 2013 LDHS shows increases in current use of any modern method (from 10 percent to 19 percent) among currently married women. These increases between the two surveys are seen for all age groups. The overall level of use of modern family planning methods is higher for sexually active unmarried women (35 percent) than for currently married women (19 percent). The most notable difference is that, while only 11 percent of currently married women use injectables, 22 percent of sexually active unmarried women use them. Use of modern contraceptive methods by sexually active unmarried women has increased strikingly up to 35 percent from 23 percent reported in the 2007 LDHS. 92 • Family Planning Table 7.2 Current use of contraception by age Percent distribution of all women, currently married women, and sexually active unmarried women, age 15-49, by contraceptive method currently used, according to age, Liberia 2013 Age Any method Any modern method Modern method Any tradi- tional method Traditional method Not cur- rently using Total Number of women Female sterili- zation Pill Inject- ables Im- plants Male condom Other modern method Rhythm With- drawal Other ALL WOMEN 15-19 17.2 16.4 0.0 2.6 9.8 2.4 1.5 0.0 0.8 0.8 0.0 0.0 82.8 100.0 2,080 20-24 28.6 27.3 0.0 5.5 17.8 2.7 1.2 0.1 1.2 1.2 0.1 0.0 71.4 100.0 1,642 25-29 26.8 24.6 0.0 4.0 16.2 2.9 1.4 0.0 2.1 2.0 0.1 0.0 73.2 100.0 1,611 30-34 25.2 24.9 0.0 6.7 14.2 2.5 0.9 0.5 0.3 0.3 0.0 0.0 74.8 100.0 1,199 35-39 21.6 20.7 0.4 6.0 11.1 2.2 0.6 0.4 0.9 0.9 0.0 0.0 78.4 100.0 1,179 40-44 17.2 15.1 0.5 4.6 8.7 1.1 0.1 0.1 2.1 2.0 0.0 0.1 82.8 100.0 812 45-49 7.3 6.2 1.0 0.9 3.2 0.6 0.2 0.2 1.2 1.2 0.0 0.0 92.7 100.0 716 Total 21.7 20.5 0.2 4.4 12.5 2.3 1.0 0.2 1.2 1.2 0.0 0.0 78.3 100.0 9,239 CURRENTLY MARRIED WOMEN 15-19 13.2 13.2 0.0 2.0 10.7 0.5 0.0 0.0 0.0 0.0 0.0 0.0 86.8 100.0 299 20-24 23.1 22.5 0.0 5.9 14.6 1.8 0.2 0.0 0.6 0.6 0.0 0.0 76.9 100.0 862 25-29 24.9 22.9 0.1 4.3 14.5 3.1 0.9 0.1 2.0 1.8 0.2 0.0 75.1 100.0 1,168 30-34 22.8 22.5 0.0 6.8 12.6 2.2 0.8 0.1 0.3 0.3 0.0 0.0 77.2 100.0 957 35-39 21.2 20.3 0.4 6.5 10.1 2.6 0.2 0.5 0.9 0.9 0.0 0.0 78.8 100.0 924 40-44 16.8 14.7 0.6 4.9 7.8 1.2 0.1 0.1 2.1 2.0 0.0 0.1 83.2 100.0 619 45-49 7.6 6.2 1.2 1.2 2.4 0.8 0.3 0.2 1.5 1.5 0.0 0.0 92.4 100.0 557 Total 20.2 19.1 0.3 5.0 11.2 2.1 0.4 0.2 1.1 1.1 0.0 0.0 79.8 100.0 5,386 SEXUALLY ACTIVE UNMARRIED WOMEN1 15-19 32.9 31.0 0.0 5.4 16.4 4.8 4.4 0.0 1.9 1.8 0.0 0.1 67.1 100.0 623 20-24 42.7 40.3 0.0 5.9 27.4 4.4 2.4 0.2 2.3 2.1 0.2 0.0 57.3 100.0 425 25-29 41.8 37.6 0.0 4.3 25.6 2.3 5.3 0.1 4.2 4.2 0.0 0.0 58.2 100.0 215 30-34 44.1 43.1 0.0 9.6 23.3 3.0 2.0 5.2 1.0 1.0 0.0 0.0 55.9 100.0 110 35-39 32.3 29.9 0.0 7.0 22.4 0.5 0.0 0.0 2.4 2.4 0.0 0.0 67.7 100.0 94 40-44 (26.7) (22.8) (0.0) (3.7) (19.1) (0.0) (0.0) (0.0) (4.0) (4.0) (0.0) (0.0) (73.3) 100.0 40 45-49 (13.8) (13.8) (0.0) (0.0) (13.8) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (86.2) 100.0 41 Total 36.9 34.6 0.0 5.6 21.6 3.7 3.3 0.4 2.3 2.2 0.1 0.0 63.1 100.0 1,548 Note: If more than one method is used, only the most effective method is considered in this tabulation. Users of IUD, Cyclebeads/Standard Days, and lactational amenorrhea method (LAM) are included in any method, any modern method, and other modern method categories. Figures in parentheses are based on 25-49 unweighted cases. 1 Women who have had sexual intercourse within the 30 days preceding the survey 7. 3 CURRENT USE OF CONTRACEPTION BY BACKGROUND CHARACTERISTICS Table 7.3.1 presents information on current use of contraceptives among currently married women age 15-49. Current use of any method of contraception varies by number of living children, residence, region, county, education, and wealth quintile. Few married women without children use any contraceptive method (6 percent), while 21 percent of married women with any living children use a contraceptive method. Women in rural areas are less likely to use contraceptive methods than their counterparts in urban areas (17 percent compared with 23 percent). Among regions, use of contraceptive methods is highest in the South Central (24 percent) and lowest in the North Central (14 percent). By county, contraceptive use is highest in River Gee (31 percent) and Montserrado (28 percent) and lowest in Grand Bassa (8 percent) and Nimba (9 percent). Family Planning • 93 Table 7.3.1 Current use of contraception by background characteristics Percent distribution of currently married women age 15-49 by contraceptive method currently used, according to background characteristics, Liberia 2013 Background characteristic Any method Any modern method Modern method Any tradi- tional method Traditional method Not currently using Total Number of women Female sterili- zation Pill Inject- ables Implants Male condom Other modern method Rhythm With- drawal Other Number of living children 0 6.4 5.5 0.0 1.4 4.0 0.1 0.0 0.0 0.9 0.9 0.0 0.0 93.6 100.0 300 1-2 21.0 19.8 0.0 4.6 12.5 2.0 0.7 0.0 1.2 1.1 0.0 0.0 79.0 100.0 1,973 3-4 21.3 20.2 0.6 4.9 11.5 2.7 0.4 0.1 1.1 0.9 0.1 0.0 78.7 100.0 1,688 5+ 20.9 19.7 0.4 6.4 10.5 1.7 0.2 0.5 1.2 1.1 0.0 0.0 79.1 100.0 1,424 Residence Urban 23.2 21.6 0.2 4.9 12.8 2.8 0.6 0.2 1.6 1.6 0.0 0.0 76.8 100.0 2,898 Greater Monrovia 27.5 25.1 0.2 5.1 15.4 3.4 0.8 0.3 2.4 2.4 0.0 0.0 72.5 100.0 1,614 Other urban 17.7 17.1 0.3 4.7 9.5 2.1 0.4 0.1 0.7 0.7 0.0 0.0 82.3 100.0 1,283 Rural 16.8 16.3 0.3 5.1 9.4 1.1 0.2 0.1 0.5 0.4 0.1 0.1 83.2 100.0 2,488 Region North Western 20.6 20.0 0.0 6.2 12.7 0.8 0.1 0.2 0.6 0.3 0.1 0.2 79.4 100.0 580 South Central 24.2 22.4 0.2 4.7 13.7 2.8 0.6 0.3 1.8 1.8 0.0 0.0 75.8 100.0 2,481 South Eastern A 20.5 20.5 0.2 5.9 12.7 1.4 0.2 0.1 0.0 0.0 0.0 0.0 79.5 100.0 348 South Eastern B 22.4 22.3 0.0 7.1 12.9 1.8 0.5 0.1 0.1 0.1 0.0 0.0 77.6 100.0 358 North Central 13.6 12.8 0.5 4.4 6.1 1.5 0.3 0.0 0.8 0.6 0.1 0.0 86.4 100.0 1,619 County Bomi 19.1 18.0 0.0 2.7 13.8 1.3 0.2 0.0 1.1 1.1 0.0 0.0 80.9 100.0 145 Bong 19.9 18.3 1.1 7.0 7.9 1.9 0.4 0.0 1.6 1.3 0.3 0.0 80.1 100.0 635 Gbarpolu 25.2 23.8 0.0 8.3 13.4 1.2 0.0 0.8 1.4 0.0 0.3 1.1 74.8 100.0 123 Grand Bassa 8.4 8.2 0.0 1.3 6.5 0.5 0.0 0.0 0.2 0.2 0.0 0.0 91.6 100.0 294 Grand Cape Mount 19.4 19.4 0.0 7.0 11.9 0.5 0.0 0.0 0.0 0.0 0.0 0.0 80.6 100.0 312 Grand Gedeh 17.9 17.9 0.2 4.5 10.4 2.0 0.6 0.3 0.0 0.0 0.0 0.0 82.1 100.0 113 Grand Kru 17.6 17.6 0.0 3.8 12.2 1.6 0.0 0.0 0.0 0.0 0.0 0.0 82.4 100.0 135 Lofa 10.0 9.4 0.0 5.4 3.5 0.6 0.0 0.0 0.5 0.5 0.0 0.0 90.0 100.0 291 Margibi 19.5 18.8 0.4 5.5 11.0 1.1 0.5 0.3 0.6 0.6 0.0 0.0 80.5 100.0 407 Maryland 22.7 22.7 0.0 9.6 10.8 1.2 1.2 0.0 0.0 0.0 0.0 0.0 77.3 100.0 148 Montserrado 27.8 25.5 0.2 5.1 15.6 3.6 0.8 0.3 2.3 2.3 0.0 0.0 72.2 100.0 1,780 Nimba 9.3 9.2 0.2 1.7 5.5 1.5 0.3 0.0 0.1 0.1 0.0 0.0 90.7 100.0 694 River Cess 20.0 20.0 0.4 6.3 13.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 80.0 100.0 100 River Gee 30.6 29.9 0.0 8.0 18.4 3.2 0.0 0.3 0.7 0.7 0.0 0.0 69.4 100.0 74 Sinoe 23.0 23.0 0.0 6.8 14.4 1.8 0.0 0.0 0.0 0.0 0.0 0.0 77.0 100.0 135 Education No education 15.3 14.7 0.1 4.7 8.6 0.9 0.1 0.3 0.6 0.5 0.1 0.0 84.7 100.0 2,417 Primary 19.7 18.1 0.5 6.0 9.8 1.5 0.2 0.1 1.6 1.5 0.0 0.0 80.3 100.0 1,446 Secondary and higher 28.6 27.1 0.3 4.5 16.7 4.4 1.1 0.0 1.6 1.6 0.0 0.0 71.4 100.0 1,523 Wealth quintile Lowest 13.5 13.2 0.1 4.2 7.8 0.9 0.0 0.1 0.3 0.3 0.0 0.0 86.5 100.0 1,133 Second 17.1 16.5 0.3 5.9 8.7 1.2 0.3 0.1 0.6 0.3 0.2 0.1 82.9 100.0 1,094 Middle 21.6 21.1 0.4 6.8 10.9 2.7 0.2 0.0 0.6 0.5 0.0 0.1 78.4 100.0 1,082 Fourth 26.2 24.5 0.2 3.4 17.1 2.7 0.5 0.6 1.7 1.7 0.0 0.0 73.8 100.0 1,108 Highest 23.3 20.7 0.3 4.7 11.6 2.9 1.2 0.0 2.6 2.6 0.0 0.0 76.7 100.0 968 Total 20.2 19.1 0.3 5.0 11.2 2.1 0.4 0.2 1.1 1.1 0.0 0.0 79.8 100.0 5,386 Note: If more than one method is used, only the most effective method is considered in this tabulation. Users of IUD, Cyclebeads/Standard Days, and the lactational amenorrhea method (LAM) are included in other modern methods. Contraceptive use is positively associated with women’s level of education and wealth. Fifteen percent of currently married women with no education use contraceptives compared with 29 percent of those with secondary and higher education. Similarly, only 14 percent of women in the lowest wealth quintile use contraceptives compared with 23 to 26 percent of women in the top two wealth quintiles. Table 7.3.2 and Figure 7.1 show trends in contraceptive use among currently married women over the past 27 years, as measured by the 1986, 1999/2000, 2007, and 2013 LDHS. Over this time period, use of contraception has risen from 6 percent in 1986 to 20 percent in 2013. 94 • Family Planning Table 7.3.2 Trends in the current use of contraception Percent distribution of currently married women age 15-49 by contraceptive method currently used, Liberia 1986-2013 Method 1986 LDHS 1999/2000 LDHSa 2007 LDHS 2013 LDHS Any method 6.4 10.0 11.4 20.2 Any modern method 5.5 8.1 10.3 19.1 Female sterilization 1.1 0.6 0.6 0.3 Male sterilization 0.0 0.5 0.0 0.0 Pill 3.3 6.1 3.8 5.0 IUD 0.6 0.8 0.2 0.0 Injectables 0.3 1.0 4.1 11.2 Vaginal methods 0.2 0.5 0.0 0.0 Male condom 0.0 1.3 1.6 0.4 Implants na n/a 0.0 2.1 Other modern method 0.0 n/a 0.0 0.2 Any traditional method 0.9 2.6 1.2 1.1 Rhythm/periodic abstinence 0.6 n/a 1.0 1.1 Withdrawal 0.1 n/a 0.2 0.0 Other traditional method 0.2 n/a 0.0 0.0 Not currently using 93.6 90.0 88.6 79.8 Total 100.0 100.7b 100.0 100.0 Number of women 3,538 9,248 4,540 5,386 aRefers to women age 13-49; however, the number of married women age 13- 14 is so small that it has no effect on the distribution (8 out of 9,248 women). bThe total exceeds 100 percent because women could report use of more than one method in the 1999/2000 survey. The question was also phrased differently in the 1999/2000 LDHS relative to the other LDHS. n/a = not available Figure 7.1 Trends in contraceptive use among currently married women 6 6 1 3 1 0 0 1 10 8 1 6 1 1 1 3 11 10 1 4 0 4 2 1 20 19 0 5 0 11 0 1 ANY METHOD Any modern method Female sterilization Pill IUD Injectables Male condom Any traditional method Percentage of currently married women 1986 LDHS 1999/2000 LDHS 2007 LDHS 2013 LDHS LDHS 2013 Family Planning • 95 7.4 SOURCE OF MODERN CONTRACEPTIVE METHODS Where women obtain the contraceptive methods they use is useful information for family planning program managers and others who plan the distribution of contraceptives. In the 2013 LDHS, all women who reported that they were currently using any modern contraceptive method at the time of the survey were asked where they obtained the method the last time they acquired it. Because women may know the name of the facility but not exactly in which category the source falls (e.g., government or private, health center or clinic), in such cases, the interviewers were instructed to note the full name of the source or facility. Furthermore, supervisors were trained to verify the name and type of source to maintain consistency and improve the accuracy of the information. Table 7.4 shows that 64 percent of users obtain their contraceptives from public sector sources. Government hospitals are the most common public source (30 percent), followed by government health clinics (27 percent). Three in ten women (30 percent) use the private medical sector to obtain contraceptives. Private hospitals and clinics (14 percent) and pharmacies (10 percent) account for the largest proportion of providers from the private medical sector. Five percent of women obtain methods of contraception from other sources, such as shops (3 percent), and friends or relatives (2 percent). The source from which a woman obtains her contraceptive method differs based on the method she uses. For example, 82 percent of implant users obtain this method from a public sector source, typically a government hospital (43 percent) or government clinic (33 percent). In contrast, only 24 percent of condom users obtain male condoms from the public sector. Fifty-two percent of condom users obtain male condoms from the private sector, typically a pharmacy (42 percent). An additional 23 percent of condom users get male condoms from friends or relatives. Table 7.4 Source of modern contraception methods Percent distribution of users of modern contraceptive methods age 15-49 by most recent source of method, according to method, Liberia 2013 Source Pill Injectables Implants Male condom Total Public sector 62.3 64.9 81.7 24.2 64.0 Government hospital 25.8 30.0 42.8 8.2 29.6 Government health center 5.4 5.7 5.9 3.8 5.6 Government clinic 30.4 27.3 33.1 12.2 27.4 Community health volunteer 0.6 1.9 0.0 0.0 1.3 Other public sector 0.1 0.0 0.0 0.0 0.0 Private medical sector 30.5 31.2 17.3 51.9 30.3 Private hospital/clinic 7.2 16.6 14.7 7.1 13.9 Pharmacy 19.3 6.9 0.0 41.5 10.4 Private doctor 1.5 2.8 0.0 0.0 2.0 Planned Parenthood Association of Liberia 1.7 4.1 2.6 0.0 3.1 Mobile clinic 0.8 0.2 0.0 1.6 0.4 Other private medical sector 0.0 0.5 0.0 1.6 0.4 Other source 5.9 3.2 0.8 23.9 4.5 Shop 4.2 2.4 0.8 0.6 2.5 Friend/relatives 1.7 0.8 0.0 23.3 2.0 Other 0.8 0.4 0.2 0.0 0.4 Total 100.0 100.0 100.0 100.0 100.0 Number of women 404 1,151 211 95 1,892 Note: Total includes female sterilization, IUD, and other modern methods but excludes Cyclebeads/Standard Days and the lactational amenorrhea method (LAM). The total also includes 16 cases for which information on the source of contraceptive method is missing. 96 • Family Planning 7.5 USE OF SOCIAL MARKETING BRAND PILLS Evidence suggests that social franchising, which is similar to social marketing, can equitably improve access to and quality of care in family planning (Bishai et al, 2008), a priority area of focus for the Government of Liberia under the Accelerated Action Plan to Reduce Maternal and Neonatal Mortality (Government of Liberia, 2012). Given that unmet need for family planning is high in Liberia (see section 7.10) and there is as yet no discrete national budget for family planning, social franchising offers a cost-effective opportunity to create greater access to affordable contraceptives. Social franchising also presents a mechanism through which youth- friendly sites and services can be fostered and promoted. Through franchise agreements that stipulate provider commitments to youth-friendly approaches and monitoring of adherence to those approaches, social franchising can create greater health care access and uptake of contraceptive use among youth. Women who were currently using oral contraceptives were asked for the brand name of the pills they last used. This information is useful in monitoring the success of social marketing programs that promote a specific brand. Table 7.5 presents the percentages of pill users age 15-49 using various social marketing brands. Overall, 76 percent of pill users use Microgynon and 17 percent use Microlut. Less than 1 percent of pill users use other known brands. The percentage of pill users who use Microgynon is higher than those who use Microlut across all background characteristics. Table 7.5 Use of social marketing brand pills Percentage of pill users age 15-49 using a social marketing brand, by background characteristics, Liberia 2013 Background characteristic Among pill users Percentage using Microlut Percentage using Microgynon Percentage using other known brands Don't know Missing Number of women using the pill Age 15-19 (20.8) (77.2) (0.0) (2.0) (0.0) 54 20-24 15.1 78.3 0.3 5.1 1.2 90 25-29 21.7 66.8 1.2 4.7 5.6 64 30-34 17.6 73.5 0.5 2.3 6.0 81 35-39 21.0 74.0 0.0 5.0 0.0 71 40-44 (4.0) (91.7) (0.0) (4.3) (0.0) 38 45-49 * * * * * 7 Residence Urban 14.9 78.0 0.5 2.8 3.8 235 Greater Monrovia (18.7) (73.0) (0.0) (2.5) (5.7) 131 Other urban 10.0 84.2 1.1 3.2 1.4 104 Rural 20.4 72.6 0.2 6.5 0.4 169 Region North Western 16.5 78.1 0.9 2.2 2.4 44 South Central 19.1 74.4 0.0 2.0 4.5 190 South Eastern A 14.7 64.2 1.1 20.0 0.0 25 South Eastern B 15.4 78.9 0.0 5.8 0.0 34 North Central 15.3 78.7 0.7 5.3 0.0 111 Education No education 15.2 77.5 0.5 6.0 0.7 138 Primary 17.4 73.6 0.6 4.1 4.3 127 Secondary and higher 18.9 75.9 0.0 3.0 2.2 139 Wealth quintile Lowest 20.4 72.4 0.5 5.6 1.0 60 Second 19.2 76.2 0.0 4.6 0.0 84 Middle 19.2 70.5 1.1 4.2 5.0 106 Fourth 11.8 84.4 0.0 3.8 0.0 67 Highest (14.6) (77.2) (0.0) (4.0) (4.2) 87 Total 17.2 75.7 0.4 4.4 2.4 404 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Family Planning • 97 7.6 INFORMED CHOICE Women age 15-49 who are currently using a modern contraceptive method and who started the last episode of use within five years of the survey were asked whether they had been informed about possible side effects or problems of their chosen method, what to do if they experienced side effects, and other methods that they could also use. Their responses give a measure of the quality of family planning service provision. Table 7.6 shows the results from the 2013 LDHS, by method and by source of the current episode of use. Seventy-five percent of users of modern contraceptives were informed about side effects or health problems associated with the method they used, 73 percent were informed about what to do if they experienced side effects, and 72 percent were told of other methods available. Women using implants were the most likely to be informed of side effects, what to do if they experienced side effects, and other methods that they could use. They were followed by users of injectables and users of the pill. Women who got their contraceptive from the public sector were more likely than those who got their contraceptive from another source to be informed of side effects, what to do if they experienced side effects, and other methods that they could use. Table 7.6 Informed choice Among current users of modern methods age 15-49 who started the last episode of use within the five years preceding the survey, the percentage who were informed about possible side effects or problems of that method, the percentage who were informed about what to do if they experienced side effects, and the percentage who were informed about other methods they could use, by method and initial source, Liberia 2013 Method/source Among women who started last episode of use of modern contraceptive method within five years preceding the survey: Percentage who were informed about side effects or problems of method used Percentage who were informed about what to do if experienced side effects Percentage who were informed by a health or family planning worker of other methods that could be used Number of women Method Female sterilization * * * 9 Pill 63.6 61.6 64.2 377 Injectables 76.0 73.9 72.9 1,098 Implants 90.2 88.1 81.3 207 Initial source of method1 Public sector 80.6 77.5 74.9 1,162 Government hospital 85.3 83.7 76.7 521 Government health center 74.8 66.0 69.3 106 Government health clinic 77.5 74.5 75.0 508 Community health worker * * * 27 Private sector 64.8 65.1 67.1 486 Private hospital/clinic 76.3 79.0 77.1 230 Pharmacy 43.1 43.3 45.9 147 Private doctor (42.5) (38.3) (59.7) 34 Planned Parenthood Association of Liberia (89.0) (83.0) (87.2) 64 Mobile clinic * * * 5 Other private sector * * * 7 Shop (42.2) (36.5) (59.5) 32 Total 74.9 72.7 71.9 1,691 Note: Table includes users of only the methods listed individually. Users who got their method from friends/relatives, black baggers/drug peddlers, or other sources that could not be categorized are excluded from this table. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Source at start of current episode of use 98 • Family Planning 7.7 RATES OF DISCONTINUING CONTRACEPTIVE METHODS Couples can realize their reproductive goals only when they consistently use reliable methods of contraception. Of particular concern to family planning programs is the rate at which users discontinue contraceptive methods and the reasons for such discontinuation. Armed with this information, family planning providers are able to better advise potential users of the advantages and disadvantages of each contraceptive method, allowing women to make a more informed decision about the method that best suits their needs. Women age 15-49 who started an episode of contraceptive use within the five years preceding the survey and discontinued it within 12 months were asked the reason for the discontinuation. Table 7.7 presents discontinuation rates, by contraceptive type and by reason for discontinuation. Among all methods, 25 percent of episodes of use were discontinued within 12 months. The pill was most often discontinued (35 percent), followed by injectables (25 percent). The reason for discontinuation varied by method. For example, whereas 5 percent of episodes of pill use were discontinued because of method failure, only 1 percent of episodes of injectable use were discontinued for this reason. Table 7.7 Twelve-month contraceptive discontinuation rates Among women age 15-49 who started an episode of contraceptive use within the five years preceding the survey, the percentage of episodes discontinued within 12 months, by reason for discontinuation and specific method, Liberia 2013 Method Method failure Desire to become pregnant Other fertility related reasons2 Side effects/ health concerns Wanted more effective method Other method related reasons3 Other reasons Any reason4 Switched to another method5 Number of episodes of use6 Pill 5.0 3.6 0.0 12.8 1.0 5.7 6.6 34.8 2.2 639 Injectables 1.0 2.5 0.8 16.5 0.7 2.1 1.5 25.0 1.1 1,445 Implants (0.0) (5.8) (0.0) (2.7) (0.0) (0.0) (0.0) (8.5) (0.0) 185 All methods1 2.1 2.7 0.4 13.0 0.7 3.0 2.9 24.9 1.2 2,506 Note: Figures are based on life table calculations using information on episodes of use that began 3-62 months preceding the survey. 1 Includes IUD, male condom, lactational amenorrhea method (LAM), rhythm method, and withdrawal 2 Includes infrequent sex/husband away, difficult to get pregnant/menopausal, and marital dissolution/separation 3 Includes lack of access/too far, costs too much, and inconvenient to use 4 Reasons for discontinuation are mutually exclusive and add to the total given in this column 5 The episodes of use included in this column are a subset of the discontinued episodes included in the discontinuation rate. A woman is considered to have switched to another method if she used a different method in the month following discontinuation or if she gave "wanted a more effective method" as the reason for discontinuation and started another method within two months of discontinuation. 6 Number of episodes of use includes both episodes of use that were discontinued during the period of observation and episodes of use that were not discontinued during the period of observation 7.8 REASONS FOR DISCONTINUING CONTRACEPTIVE METHODS Table 7.8 shows the percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for the discontinuation, according to specific method. In total, 1,173 discontinuations occurred within this time period. Across all contraceptive methods, the most common reason for discontinuation was health concerns/side effects (44 percent), followed by wanted to become pregnant (17 percent), and became pregnant while using (11 percent). Across specific contraceptive methods, the reasons for discontinuation vary widely. For example, among pill users, 34 percent of discontinuations were because of health concerns/side effects and 16 percent because the user became pregnant while using. Among injectable users, side effects/health concerns were a more common reason for discontinuation (56 percent), while method failure (i.e., becoming pregnant while using the method) was only mentioned by 5 percent. For pill users and injectable users, the percentage who discontinued use because they wanted to become pregnant was similar (15 percent and 17 percent, respectively). Family Planning • 99 Table 7.8 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for discontinuation, according to specific method, Liberia 2013 Reason Pill Injectables Other1 All methods Became pregnant while using 16.3 4.5 37.2 11.4 Wanted to become pregnant 15.3 17.4 19.3 16.9 Husband/partner disapproved 5.6 3.1 8.5 4.4 Wanted more effective method 3.7 3.5 11.8 4.2 Health concerns/side effects 34.0 56.1 11.3 44.4 Lack of access/too far 3.5 4.2 2.2 3.8 Cost too much 0.3 0.7 0.0 0.5 Inconvenient to use 7.7 2.5 5.5 4.7 Up to God/fatalistic 2.2 0.0 0.0 0.8 Difficult to get pregnant/menopausal 0.0 0.3 0.0 0.2 Infrequent sex/husband away 0.3 1.9 0.9 1.2 Marital dissolution/separation 0.0 0.9 0.0 0.5 Other 4.0 1.5 1.6 2.5 Don't know 0.4 0.1 0.0 0.2 Missing 6.7 3.2 1.8 4.4 Total 100.0 100.0 100.0 100.0 Number of discontinuations 440 643 89 1,173 Note: Total includes 2 cases for which information on contraceptive method is missing. 1 IUD, implants, male condom, lactational amenorrhea method (LAM), rhythm method, and withdrawal are included in the discontinuation rate for other methods. 7.9 KNOWLEDGE OF THE FERTILE PERIOD An elementary knowledge of reproductive physiology provides a useful background for successful practice of coitus-associated methods such as withdrawal and condom use. Such knowledge is particularly critical in the use of the rhythm method. The 2013 LDHS included a question designed to obtain information on the respondent’s understanding of when a woman is most likely to become pregnant during the menstrual cycle. Respondents were asked, “From one menstrual period to the next, are there certain days when a woman is more likely to get pregnant if she has sexual relations?” If the reply was yes, the respondent was further asked whether that time was just before a woman’s period begins, during her period, right after her period has ended, or halfway between two periods. Table 7.9 shows that knowledge of the fertile period is minimal among women age 15-49 in Liberia. Only 13 percent of women correctly reported when the fertile period occurs (a woman is most likely to conceive halfway between two periods). The percentage of women who correctly reported the fertile period was higher among users of the rhythm method (32 percent) than nonusers (13 percent), but was still low. Table 7.9 Knowledge of fertile period Percent distribution of women age 15-49 by knowledge of the fertile period during the ovulatory cycle, according to current use of the rhythm method, Liberia 2013 Perceived fertile period Users of rhythm method Nonusers of rhythm method All women Just before her menstrual period begins 0.0 1.2 1.2 During her menstrual period 0.8 1.7 1.7 Right after her menstrual period has ended 52.8 42.7 42.8 Halfway between two menstrual periods 31.9 13.1 13.3 Other 0.0 0.0 0.0 No specific time 12.4 24.2 24.1 Don't know 2.1 17.0 16.9 Total 100.0 100.0 100.0 Number of women 107 9,132 9,239 Note: Total includes 4 cases for which information on knowledge of fertile period is missing. 100 • Family Planning 7.10 NEED AND DEMAND FOR FAMILY PLANNING The proportion of women who want to stop childbearing or who want to space their next birth is a crude measure of the extent of the need for family planning, given that not all of these women are exposed to the risk of pregnancy and some of them may already be using contraception. This section discusses the extent of need and the potential demand for family planning services. Women who want to postpone their next birth for two or more years or who want to stop childbearing altogether but are not using a contraceptive method are said to have an unmet need for family planning. Pregnant women are considered to have an unmet need for spacing or limiting if their pregnancy was mistimed or unwanted. Similarly, amenorrheic women are categorized as having unmet need if their last birth was mistimed or unwanted. Women who are currently using a family planning method are said to have a met need for family planning. The total demand for family planning services comprises those who fall in the met need and unmet need categories. Tables 7.10.1 and 7.10.2 and Figure 7.2 present data on unmet need, met need, and total demand for family planning for currently married women, all women, and women who are not currently married. These indicators help to evaluate the extent to which the family planning program in Liberia meets the demand for services. The definition of unmet need for family planning has been revised to make levels of unmet need comparable over time and across surveys. The unmet need estimate in Figure 7.2 for the 2007 LDHS has been recalculated using the revised definition of unmet need but differs only slightly from the number published in the 2007 final reports. Table 7.10.1 shows that 31 percent of currently married women have an unmet need for family planning services (22 percent for spacing and 9 percent for limiting births). Twenty percent of married women are currently using a contraceptive method. About half of currently married women (51 percent) have a demand for family planning. At present, 39 percent of the potential demand for family planning is being met. Thus, if all married women who said they want to space or limit their children were to use family planning methods, the contraceptive prevalence rate would increase from 20 percent to 51 percent. As shown in Table 7.10.1, as expected, unmet need for spacing is high among younger women, while unmet need for limiting childbearing is higher among older women. There is only a minor difference in unmet need between rural and urban areas, with urban areas at 30 percent and rural areas at 33 percent. Regional differences in unmet need are also relatively small. By county, larger differences are observed. For example, unmet need ranges from a low of 23 percent in River Gee to a high of 41 percent in Maryland. Unmet need varies slightly by woman’s education; it is higher among women with primary education (35 percent) than women with secondary and higher education (32 percent) and those with no education (29 percent). Unmet need is inversely associated with a woman’s wealth status. Among women in the lowest wealth quintile, unmet need is 35 percent, while it is 27 percent among those in the highest wealth quintile. Family Planning • 101 Table 7.10.1 Need and demand for family planning among currently married women Percentage of currently married women age 15-49 with unmet need for family planning, percentage with met need for family planning, the total demand for family planning, and the percentage of the demand for contraception that is satisfied, by background characteristics, Liberia 2013 Background characteristic Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Age 15-19 46.4 0.2 46.6 13.2 0.0 13.2 59.6 0.2 59.8 22.1 22.1 299 20-24 36.5 2.1 38.6 22.7 0.5 23.1 59.2 2.5 61.7 37.4 36.5 862 25-29 28.0 5.5 33.5 20.4 4.5 24.9 48.4 10.0 58.4 42.6 39.2 1,168 30-34 21.7 8.6 30.2 15.4 7.4 22.8 37.1 15.9 53.0 43.0 42.5 957 35-39 15.6 15.8 31.4 7.9 13.2 21.2 23.5 29.1 52.6 40.2 38.5 924 40-44 7.0 20.2 27.2 2.1 14.6 16.8 9.2 34.9 44.0 38.1 33.5 619 45-49 1.9 9.5 11.4 0.5 7.2 7.6 2.3 16.7 19.0 40.2 32.4 557 Residence Urban 22.0 7.5 29.5 15.6 7.6 23.2 37.5 15.1 52.7 44.0 40.9 2,898 Greater Monrovia 20.1 6.5 26.6 18.6 8.9 27.5 38.7 15.4 54.1 50.9 46.4 1,614 Other urban 24.4 8.7 33.1 11.7 6.0 17.7 36.1 14.7 50.8 34.9 33.6 1,283 Rural 22.1 10.9 33.0 10.4 6.4 16.8 32.5 17.3 49.8 33.7 32.7 2,488 Region North Western 23.3 9.5 32.8 12.6 7.9 20.6 35.9 17.4 53.3 38.5 37.5 580 South Central 20.0 7.8 27.9 16.0 8.2 24.2 36.0 16.1 52.0 46.4 43.0 2,481 South Eastern A 22.0 11.5 33.5 13.3 7.1 20.5 35.3 18.6 54.0 37.9 37.9 348 South Eastern B 21.7 11.7 33.4 11.9 10.5 22.4 33.7 22.2 55.8 40.1 39.9 358 North Central 24.7 9.7 34.4 9.3 4.2 13.6 34.1 13.9 48.0 28.3 26.7 1,619 County Bomi 25.2 7.7 32.8 12.3 6.8 19.1 37.5 14.5 51.9 36.8 34.7 145 Bong 23.5 10.0 33.6 13.9 6.0 19.9 37.4 16.0 53.5 37.2 34.2 635 Gbarpolu 26.7 8.9 35.7 17.0 8.2 25.2 43.7 17.1 60.8 41.4 39.2 123 Grand Bassa 20.5 12.7 33.3 4.6 3.8 8.4 25.1 16.5 41.7 20.2 19.6 294 Grand Cape Mount 21.0 10.6 31.6 11.1 8.3 19.4 32.1 18.9 51.0 38.0 38.0 312 Grand Gedeh 20.1 8.5 28.6 12.3 5.6 17.9 32.4 14.1 46.5 38.4 38.4 113 Grand Kru 19.0 12.0 31.1 9.1 8.5 17.6 28.1 20.5 48.7 36.2 36.2 135 Lofa 27.9 8.2 36.1 8.0 1.9 10.0 35.9 10.1 46.1 21.6 20.5 291 Margibi 19.9 8.9 28.8 11.8 7.7 19.5 31.7 16.6 48.3 40.3 39.0 407 Maryland 27.2 13.8 41.0 11.6 11.1 22.7 38.8 24.9 63.7 35.6 35.6 148 Montserrado 20.0 6.8 26.8 18.8 9.1 27.8 38.7 15.9 54.6 51.0 46.8 1,780 Nimba 24.5 10.1 34.6 5.7 3.6 9.3 30.2 13.6 43.8 21.1 21.0 694 River Cess 23.4 13.6 37.0 12.2 7.8 20.0 35.6 21.4 57.0 35.1 35.1 100 River Gee 15.9 6.8 22.6 17.6 13.0 30.6 33.5 19.8 53.2 57.5 56.2 74 Sinoe 22.5 12.5 34.9 15.1 7.9 23.0 37.6 20.4 57.9 39.7 39.7 135 Education No education 18.3 10.4 28.7 7.9 7.4 15.3 26.2 17.8 44.0 34.7 33.4 2,417 Primary 26.0 8.5 34.5 13.7 6.0 19.7 39.6 14.5 54.2 36.3 33.4 1,446 Secondary and higher 24.2 7.4 31.6 21.1 7.6 28.6 45.2 15.0 60.2 47.5 44.9 1,523 Wealth quintile Lowest 23.2 11.9 35.1 8.5 5.0 13.5 31.7 16.9 48.6 27.8 27.1 1,133 Second 22.5 9.6 32.1 9.9 7.1 17.1 32.4 16.7 49.1 34.7 33.6 1,094 Middle 23.5 8.4 31.9 14.1 7.5 21.6 37.6 15.9 53.5 40.4 39.4 1,082 Fourth 21.1 8.1 29.2 19.9 6.3 26.2 41.0 14.4 55.4 47.3 44.2 1,108 Highest 19.6 7.1 26.6 13.5 9.8 23.3 33.1 16.8 49.9 46.6 41.5 968 Total 22.0 9.1 31.1 13.2 7.1 20.2 35.2 16.1 51.3 39.4 37.2 5,386 Note: Numbers in this table correspond to the revised definition of unmet need described in Bradley et al., 2012. 1 Total demand is the sum of unmet need and met need. 2 Percentage of demand satisfied is met need divided by total demand. 3 Modern methods include female sterilization, the pill, IUD, injectables, implants, male condom, female condom, and the lactational amenorrhea method (LAM). Figure 7.2 compares unmet need for family planning among currently married women in the 2007 LDHS and the 2013 LDHS. Unmet need has decreased slightly, from 36 percent in 2007 to 31 percent in 2013. 102 • Family Planning Figure 7.2 Trends in unmet need for family planning 36 31 2007 LDHS 2013 LDHS Percent Note: Estimates for all years are based on the revised definition of unmet need The need for family planning services for all women and women not currently married is presented in Table 7.10.2. The panel on all women follows the trends of currently married women. Overall, the total family planning demand for all women is high (50 percent), especially for those women age 20-24 (63 percent). Total demand is even higher for sexually active, unmarried women (83 percent), although demand drops with increasing age. Family Planning • 103 Table 7.10.2 Need and demand for family planning for all women and for sexually active unmarried women Percentage of all women and women not currently married age 15-49 with unmet need for family planning, percentage with met need for family planning, the total demand for family planning and the percentage of the demand for contraception that is satisfied, by background characteristics, Liberia 2013 Background characteristic Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total ALL WOMEN Age 15-19 28.0 0.1 28.1 17.0 0.2 17.2 44.9 0.3 45.3 37.9 36.1 2,080 20-24 33.2 1.3 34.5 27.8 0.8 28.6 61.0 2.1 63.1 45.3 43.3 1,642 25-29 25.6 4.3 30.0 22.5 4.3 26.8 48.1 8.6 56.7 47.2 43.4 1,611 30-34 19.9 7.4 27.3 18.3 7.0 25.2 38.1 14.4 52.5 48.0 47.4 1,199 35-39 14.8 14.0 28.9 8.7 12.9 21.6 23.6 26.9 50.5 42.8 41.1 1,179 40-44 6.0 16.3 22.3 2.8 14.4 17.2 8.8 30.7 39.5 43.6 38.2 812 45-49 2.5 8.6 11.1 0.7 6.6 7.3 3.3 15.1 18.4 39.7 33.5 716 Residence Urban 21.8 4.4 26.2 19.4 5.2 24.6 41.2 9.6 50.8 48.4 45.0 5,633 Greater Monrovia 20.5 3.5 24.0 23.0 5.5 28.5 43.5 9.0 52.5 54.2 50.0 3,361 Other urban 23.9 5.7 29.5 14.1 4.7 18.8 37.9 10.4 48.3 38.9 36.9 2,272 Rural 21.9 8.2 30.1 11.9 5.4 17.3 33.8 13.5 47.3 36.5 35.6 3,606 Region North Western 21.9 6.8 28.7 15.2 6.6 21.8 37.1 13.4 50.5 43.2 42.3 837 South Central 20.2 4.5 24.7 20.1 5.6 25.6 40.3 10.1 50.4 50.9 47.3 4,854 South Eastern A 22.0 8.8 30.9 15.7 6.2 21.9 37.7 15.1 52.8 41.5 41.3 483 South Eastern B 22.8 8.1 30.9 14.2 7.5 21.7 37.1 15.6 52.6 41.3 41.1 577 North Central 24.8 7.1 32.0 10.5 3.5 14.0 35.3 10.6 46.0 30.5 28.8 2,488 County Bomi 21.7 4.9 26.6 18.2 5.0 23.2 39.9 9.9 49.8 46.7 45.4 244 Bong 22.9 8.2 31.1 15.5 4.5 20.0 38.4 12.7 51.1 39.2 35.7 894 Gbarpolu 23.3 6.0 29.4 19.9 7.4 27.3 43.3 13.4 56.7 48.2 46.3 182 Grand Bassa 21.9 9.4 31.3 8.0 4.4 12.4 29.9 13.8 43.7 28.4 27.1 434 Grand Cape Mount 21.4 8.3 29.7 11.3 7.2 18.5 32.7 15.5 48.2 38.4 38.4 412 Grand Gedeh 19.3 6.1 25.4 18.6 4.2 22.8 37.9 10.3 48.2 47.3 46.6 167 Grand Kru 21.4 7.7 29.1 14.8 5.9 20.7 36.2 13.6 49.8 41.6 41.6 217 Lofa 24.0 5.5 29.5 10.0 2.0 12.0 33.9 7.6 41.5 28.9 27.0 447 Margibi 18.6 5.5 24.1 12.1 5.5 17.6 30.7 11.0 41.7 42.1 40.6 744 Maryland 26.0 9.4 35.4 12.9 7.3 20.2 38.9 16.7 55.6 36.4 36.4 257 Montserrado 20.3 3.7 24.1 23.1 5.7 28.8 43.5 9.4 52.9 54.5 50.4 3,675 Nimba 26.7 6.9 33.6 6.9 3.3 10.1 33.5 10.2 43.7 23.1 23.0 1,147 River Cess 23.9 10.9 34.8 12.0 6.4 18.4 35.9 17.3 53.2 34.6 34.6 135 River Gee 17.9 5.7 23.6 16.5 11.1 27.5 34.4 16.8 51.2 53.8 52.8 103 Sinoe 23.1 9.8 32.9 15.7 8.0 23.7 38.8 17.8 56.7 41.9 41.9 182 Education No education 17.5 9.2 26.6 8.5 6.8 15.4 26.0 16.0 42.0 36.6 35.5 3,066 Primary 24.4 4.8 29.3 14.1 3.8 17.9 38.6 8.7 47.2 38.0 35.3 2,875 Secondary and higher 23.7 3.7 27.4 25.9 5.0 30.9 49.6 8.8 58.3 53.0 49.8 3,298 Wealth quintile Lowest 22.7 9.0 31.7 9.6 4.3 13.9 32.3 13.4 45.6 30.5 29.6 1,581 Second 22.5 7.0 29.5 11.2 5.8 17.0 33.7 12.8 46.5 36.5 35.5 1,624 Middle 22.7 6.0 28.6 16.2 6.1 22.3 38.9 12.0 50.9 43.8 42.8 1,779 Fourth 21.7 4.8 26.5 21.9 4.8 26.7 43.6 9.6 53.2 50.3 47.7 2,047 Highest 20.3 3.7 24.0 20.5 5.3 25.7 40.8 8.9 49.7 51.7 46.1 2,207 Total 21.9 5.9 27.7 16.5 5.3 21.7 38.3 11.1 49.5 43.9 41.5 9,239 SEXUALLY ACTIVE UNMARRIED WOMEN4 Age 15-19 59.1 0.4 59.5 32.4 0.5 32.9 91.5 0.9 92.4 35.6 33.6 623 20-24 44.3 0.8 45.1 41.3 1.4 42.7 85.6 2.2 87.8 48.6 46.0 425 25-29 29.6 1.4 31.0 38.7 3.1 41.8 68.3 4.5 72.8 57.4 51.6 215 30-34 20.5 4.9 25.5 36.5 7.6 44.1 57.0 12.6 69.5 63.4 62.0 110 35-39 22.8 15.9 38.7 20.0 12.3 32.3 42.7 28.2 71.0 45.5 42.1 94 40-44 (7.5) (16.0) (23.5) (15.4) (11.4) (26.7) (22.9) (27.4) (50.3) (53.2) (45.3) 40 45-49 (16.4) (17.5) (33.9) (6.9) (6.9) (13.8) (23.3) (24.4) (47.7) (28.9) (28.9) 41 Residence Urban 42.8 2.1 44.9 36.0 2.6 38.6 78.8 4.7 83.5 46.2 42.8 1,184 Greater Monrovia 41.1 1.2 42.3 40.5 2.9 43.4 81.6 4.1 85.7 50.6 46.8 798 Other urban 46.3 4.0 50.3 26.7 1.9 28.6 73.0 5.9 78.9 36.3 33.7 386 Rural 46.1 4.8 50.9 28.0 3.4 31.5 74.2 8.2 82.4 38.2 37.7 364 Continued… 104 • Family Planning Table 7.10.2 Need and demand for family planning for all women and for sexually active unmarried women—Continued Background characteristic Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Region North Western 44.3 1.6 45.9 36.3 3.9 40.1 80.6 5.4 86.0 46.7 46.2 82 South Central 41.8 1.9 43.8 37.9 3.5 41.4 79.7 5.4 85.1 48.6 45.1 991 South Eastern A 40.8 2.9 43.7 35.1 3.5 38.6 75.9 6.4 82.3 46.9 46.9 52 South Eastern B 39.7 4.7 44.4 27.4 3.5 30.9 67.1 8.2 75.3 41.1 41.1 91 North Central 50.1 4.9 55.0 23.9 0.3 24.1 74.0 5.1 79.2 30.5 28.3 332 County Bomi 37.7 2.7 40.4 49.3 3.6 52.8 86.9 6.3 93.2 56.7 56.7 31 Bong 34.6 5.9 40.5 41.2 0.0 41.2 75.8 5.9 81.7 50.4 45.7 96 Gbarpolu (36.8) (0.0) (36.8) (40.8) (2.6) (43.4) (77.6) (2.6) (80.2) (54.1) (52.1) 20 Grand Bassa 47.6 2.5 50.1 22.5 8.1 30.6 70.1 10.6 80.7 37.9 36.2 62 Grand Cape Mount 55.6 1.4 57.0 20.5 4.9 25.5 76.1 6.4 82.5 30.9 30.9 31 Grand Gedeh 33.8 2.6 36.3 43.5 0.8 44.3 77.3 3.3 80.6 54.9 54.9 23 Grand Kru 36.5 0.9 37.4 28.0 3.6 31.6 64.5 4.5 69.0 45.8 45.8 38 Lofa 49.9 2.5 52.4 25.0 2.0 27.1 75.0 4.5 79.5 34.0 27.9 41 Margibi 56.3 6.2 62.4 20.3 3.7 24.0 76.6 9.9 86.5 27.8 26.3 77 Maryland 44.0 7.3 51.4 27.4 3.2 30.6 71.4 10.5 81.9 37.3 37.3 43 Montserrado 40.1 1.5 41.6 40.6 3.1 43.7 80.7 4.6 85.3 51.2 47.4 853 Nimba 57.8 4.8 62.6 15.2 0.0 15.2 73.0 4.8 77.8 19.5 19.5 195 River Cess (36.8) (5.8) (42.6) (25.2) (2.7) (27.9) (62.0) (8.5) (70.4) (39.6) (39.6) 12 River Gee (33.6) (7.7) (41.4) (25.6) (4.5) (30.1) (59.2) (12.2) (71.5) (42.1) (42.1) 11 Sinoe (52.5) (1.3) (53.8) (30.8) (7.6) (38.5) (83.3) (8.9) (92.3) (41.7) (41.7) 18 Education No education 31.9 9.7 41.7 20.0 6.2 26.2 51.9 15.9 67.8 38.6 38.6 204 Primary 51.7 2.9 54.6 26.5 2.1 28.6 78.2 5.0 83.2 34.4 31.5 501 Secondary and higher 41.6 1.0 42.5 42.0 2.4 44.4 83.6 3.3 86.9 51.1 47.9 843 Wealth quintile Lowest 46.9 3.1 50.0 22.3 3.4 25.7 69.3 6.4 75.7 33.9 33.6 147 Second 47.5 3.9 51.4 25.2 2.5 27.6 72.6 6.4 79.1 34.9 34.0 176 Middle 40.9 5.4 46.3 33.9 2.9 36.8 74.8 8.3 83.1 44.3 44.3 264 Fourth 43.1 1.3 44.4 35.9 4.9 40.8 79.0 6.2 85.2 47.9 46.2 418 Highest 43.1 2.1 45.1 38.9 1.1 40.0 82.0 3.2 85.1 47.0 40.9 544 Total 43.6 2.7 46.3 34.1 2.8 36.9 77.7 5.5 83.2 44.3 41.6 1,548 Note: Numbers in this table correspond to the revised definition of unmet need described in Bradley et al., 2012. Figures in parentheses are based on 25-49 unweighted cases. 1 Total demand is the sum of unmet need and met need. 2 Percentage of demand satisfied is met need divided by total demand. 3 Modern methods include female sterilization, the pill, IUD, injectables, implants, male condom, female condom, and the lactational amenorrhea method (LAM) 4 Women who have had sexual intercourse within 30 days preceding the survey. 7.11 FUTURE USE OF CONTRACEPTION An important indicator of the changing demand for family planning is the extent to which nonusers plan to use contraceptive methods in the future, as this is a forecast of potential demand for services. Currently married women age 15-49 who were not using contraceptives at the time of the survey were asked about their intention to use family planning in the future. Table 7.11 shows that 46 percent of the currently married nonusers indicated that they intend to use family planning methods in the future, while almost half (49 percent) said that they do not intend to use a method in the future. The proportion of women who intend to use a method is highest among women with one to two children and lowest among those with no children and those with at least four children. Family Planning • 105 Table 7.11 Future use of contraception Percent distribution of currently married women age 15-49 who are not using a contraceptive method by intention to use in the future, according to number of living children, Liberia 2013 Intention to use in the future Number of living children1 Total 0 1 2 3 4+ Intends to use 42.5 49.6 51.7 43.8 43.1 45.9 Unsure 5.5 6.0 5.8 5.6 4.1 5.1 Does not intend to use 52.0 43.7 41.5 50.3 52.5 48.5 Missing 0.0 0.7 1.0 0.3 0.3 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 187 678 844 777 1,809 4,296 1 Includes current pregnancy 7.12 EXPOSURE TO FAMILY PLANNING MESSAGES IN THE MEDIA Radio, television, and newspapers and/or magazines are the major sources of information about family planning in the media in Liberia. Information on the level of public exposure to a particular type of media allows policymakers to ensure the use of the most effective media for the various target groups. To assess the effectiveness of such media on the dissemination of family planning information, women and men in the 2013 LDHS were asked whether they had heard messages about family planning on the radio or seen them on television or in newspapers/magazines during the last few months preceding the survey (Table 7.12). Overall, 77 percent of women reported that they had recently heard a family planning message on the radio, 9 percent had seen a message on television, and 7 percent saw messages in newspapers or magazines. These proportions vary little by the woman’s age. However, differences in access to media messages are observed by residence, region, and county. For example, women in urban areas are more likely than those in rural areas to have access to family planning messages on the radio (83 percent and 67 percent, respectively), on television (14 percent and 2 percent respectively), or in newspapers or magazines (10 percent and 1 percent, respectively). Exposure to family planning messages increases as the respondent’s education level and wealth status increases. In general, men had exposure to family planning messages similar to that of women; differentials by background characteristics follow patterns similar to those observed for women. 106 • Family Planning Table 7.12 Exposure to family planning messages Percentage of women and men age 15-49 who heard or saw a family planning message on radio, on television, or in a newspaper or magazine in the past few months, according to background characteristics, Liberia 2013 Background characteristic Women Men Radio Television News- paper/ magazine None of these three media sources Number of women Radio Television News- paper/ magazine None of these three media sources Number of men Age 15-19 74.0 9.7 6.9 25.5 2,080 57.3 5.2 6.5 42.0 890 20-24 79.2 10.2 6.6 20.5 1,642 76.9 8.1 12.5 22.6 696 25-29 80.7 8.8 8.4 19.3 1,611 80.8 11.2 18.5 18.5 673 30-34 79.7 9.6 8.4 20.1 1,199 73.4 5.7 11.7 26.5 575 35-39 75.7 10.0 5.3 24.2 1,179 79.7 10.2 15.0 20.3 469 40-44 73.7 7.8 6.7 26.2 812 85.4 8.7 18.3 14.5 482 45-49 71.2 7.9 4.2 28.8 716 86.0 8.0 14.1 13.9 332 Residence Urban 83.2 14.0 10.4 16.5 5,633 78.9 10.8 17.2 20.6 2,413 Greater Monrovia 88.8 21.0 15.8 11.0 3,361 83.0 16.1 21.7 16.3 1,433 Other urban 75.0 3.7 2.4 24.6 2,272 73.0 3.1 10.5 26.9 980 Rural 66.8 2.0 1.4 33.1 3,606 69.1 3.8 7.5 30.6 1,705 Region North Western 78.0 1.6 1.4 22.0 837 82.0 5.1 10.2 17.6 367 South Central 84.6 16.1 11.9 15.2 4,854 82.3 13.0 18.7 17.1 2,149 South Eastern A 56.9 2.3 2.3 42.8 483 59.5 3.4 7.0 40.2 254 South Eastern B 52.2 3.3 1.8 47.6 577 60.0 2.7 15.2 39.9 288 North Central 70.8 1.5 1.1 29.0 2,488 65.0 1.0 3.9 34.9 1,060 County Bomi 86.8 1.8 0.6 13.2 244 82.8 0.0 10.3 17.2 97 Bong 68.1 0.7 0.7 31.9 894 68.0 1.7 2.5 32.0 389 Gbarpolu 73.8 0.6 1.6 26.2 182 90.5 0.3 1.6 9.1 94 Grand Bassa 57.8 5.6 2.4 41.8 434 77.0 3.7 12.5 22.4 204 Grand Cape Mount 74.6 1.9 1.8 25.4 412 77.1 10.5 14.8 22.4 176 Grand Gedeh 59.6 1.5 1.1 40.2 167 67.2 3.1 5.5 32.6 82 Grand Kru 41.9 2.0 1.1 57.5 217 60.6 3.2 24.2 39.2 110 Lofa 50.6 0.6 0.9 49.4 447 60.5 0.2 2.4 39.5 219 Margibi 81.4 3.7 2.7 18.2 744 86.3 6.7 12.3 13.4 364 Maryland 61.2 5.1 2.8 38.6 257 66.3 3.3 12.6 33.7 123 Montserrado 88.4 19.9 14.8 11.4 3,675 82.1 15.7 21.0 17.3 1,582 Nimba 80.8 2.5 1.4 18.8 1,147 64.6 0.9 5.7 35.2 451 River Cess 64.8 1.2 1.0 35.2 135 61.6 3.8 5.0 37.8 64 River Gee 51.1 1.4 1.0 48.9 103 44.5 0.5 2.9 55.4 55 Sinoe 48.7 3.8 4.3 50.8 182 52.4 3.4 9.4 47.4 108 Education No education 65.7 2.8 0.7 34.3 3,066 62.2 1.1 0.7 37.8 533 Primary 75.4 6.6 2.6 24.3 2,875 62.4 3.0 2.3 37.6 1,202 Secondary and higher 88.4 17.8 16.3 11.3 3,298 83.9 12.0 21.4 15.4 2,383 Wealth quintile Lowest 55.6 0.9 0.8 44.3 1,581 63.3 2.5 4.9 36.6 749 Second 68.6 1.4 0.8 31.3 1,624 71.3 2.9 6.5 28.5 753 Middle 77.5 3.8 2.5 22.5 1,779 71.4 4.4 9.8 28.5 728 Fourth 86.4 9.3 7.1 13.3 2,047 80.4 7.7 15.5 19.5 864 Highest 88.7 25.8 19.0 11.0 2,207 83.7 18.4 24.5 15.1 1,024 Total 76.8 9.4 6.9 23.0 9,239 74.9 7.9 13.2 24.8 4,118 7.13 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS In the 2013 LDHS, women who were not using any contraceptive method were asked whether a fieldworker talked with them about family planning in the 12 months preceding the survey. This information is especially useful for determining whether family planning outreach programs reach nonusers. Nonusers were also asked if they had visited a health facility in the preceding 12 months for any reason, and if so, whether any Family Planning • 107 staff member at the facility had spoken to them about family planning. These questions help to assess the level of missed opportunities to inform women about contraception. The results shown in Table 7.13 indicate that 15 percent of nonusers reported discussing family planning when a fieldworker visited them. Forty-four percent of nonusers visited a health facility and discussed family planning, while 17 percent of the nonusers had visited a facility but did not discuss family planning. Table 7.13 Contact of nonusers with family planning providers Among women age 15-49 who are not using contraception, the percentage who during the past 12 months were visited by a fieldworker who discussed family planning, the percentage who visited a health facility and discussed family planning, the percentage who visited a health facility but did not discuss family planning, and the percentage who did not discuss family planning either with a fieldworker or at a health facility, by background characteristics, Liberia 2013 Background characteristic Percentage of women who were visited by fieldworker who discussed family planning Percentage of women who visited a health facility in the past 12 months and who: Percentage of women who did not discuss family planning either with fieldworker or at a health facility Number of women Discussed family planning Did not discuss family planning Age 15-19 11.5 31.3 15.2 64.0 1,723 20-24 17.1 49.7 16.5 43.8 1,173 25-29 15.6 53.1 18.6 43.6 1,180 30-34 17.4 51.0 18.9 44.2 897 35-39 14.9 46.2 19.2 49.5 924 40-44 14.9 42.6 14.9 53.1 673 45-49 11.9 37.7 16.2 57.2 663 Residence Urban 15.2 44.4 17.1 50.6 4,249 Greater Monrovia 12.0 40.2 19.6 55.1 2,404 Other urban 19.3 50.0 13.8 44.7 1,845 Rural 13.8 43.0 16.9 52.7 2,983 Region North Western 16.0 47.0 12.5 49.0 654 South Central 12.2 43.3 19.6 52.1 3,609 South Eastern A 16.9 36.2 17.2 58.1 377 South Eastern B 7.1 25.6 25.8 71.0 451 North Central 19.5 48.9 12.2 45.7 2,140 County Bomi 20.7 44.4 18.3 47.7 187 Bong 14.8 54.7 14.9 41.3 715 Gbarpolu 11.7 40.2 19.1 56.5 132 Grand Bassa 8.5 30.2 31.0 66.0 381 Grand Cape Mount 15.0 51.1 6.7 46.8 335 Grand Gedeh 26.5 37.1 15.0 55.7 129 Grand Kru 7.8 15.6 21.4 79.4 172 Lofa 9.1 39.0 16.7 59.3 394 Margibi 12.8 56.1 13.8 38.6 613 Maryland 5.4 26.9 30.5 71.0 205 Montserrado 12.5 42.2 19.2 53.3 2,615 Nimba 26.7 48.7 8.6 43.6 1,031 River Cess 10.3 50.9 15.1 46.7 110 River Gee 9.8 45.3 23.1 51.5 75 Sinoe 13.2 23.7 20.8 69.4 139 Education No education 13.4 45.8 16.3 50.4 2,595 Primary 14.5 40.9 14.3 54.1 2,359 Secondary and higher 16.1 44.6 20.6 49.8 2,278 Wealth quintile Lowest 12.1 39.0 18.2 56.8 1,361 Second 15.8 43.5 14.6 50.8 1,349 Middle 17.2 49.4 14.2 45.6 1,383 Fourth 16.4 47.2 13.9 47.9 1,500 Highest 11.9 40.2 23.3 55.7 1,639 Total 14.6 43.8 17.0 51.4 7,232 108 • Family Planning Variations in the percentage of nonusers who discussed family planning with either a fieldworker or at a health facility were greatest by county. For example, more than one in four nonusers in Grand Gedeh and Nimba (27 percent) discussed family planning with a field worker compared with one in 20 (5 percent) of nonusers in Maryland. Among nonusers, over half of those in Margibi (56 percent), Bong (55 percent), Grand Cape Mount (51 percent), and River Cess (51 percent) visited a health facility in the past 12 months and discussed family planning; in contrast, only one in six nonusers in Grand Kru (16 percent) visited a facility and discussed family planning. Overall, 51 percent of nonusers did not discuss family planning with a fieldworker or a staff member at a health facility. This represents a significant pool of potential users of family planning who could be targeted for family planning counseling. A more vigorous outreach program will be needed to reach these women. Infant and Child Mortality • 109 INFANT AND CHILD MORTALITY 8 nformation on levels, trends, and differentials in neonatal, infant, and child mortality is important in the demographic assessment of the population and the evaluation of health policies and programs. Estimates of infant and child mortality are used for population projections, particularly if the level of adult mortality is known from another source or can be inferred with reasonable confidence. Information on mortality of children serves the needs of agencies providing health services by identifying subgroups of the population at high risk of mortality. 8.1 BACKGROUND AND ASSESSMENT OF DATA QUALITY The rates of childhood mortality presented in this chapter are defined as follows: • Neonatal mortality: the probability of dying within the first month of life • Postneonatal mortality: the arithmetic difference between infant and neonatal mortality • Infant mortality: the probability of dying between birth and the first birthday • Child mortality: the probability of dying between the first and the fifth birthday • Under-5 mortality: the probability of dying between birth and the fifth birthday All rates are expressed as deaths per 1,000 live births, except child mortality, which is expressed as deaths per 1,000 children surviving to the first birthday. Information drawn from the questions asked in the birth history section of the Woman’s Questionnaire is used to calculate the mortality rates presented in this chapter. First, the respondents were asked a series of questions about their childbearing experience. In particular, they were asked to report the number of sons and daughters living with them, the number living elsewhere, and the number who have died. In the birth history, for each live birth, information was collected on sex; month and year of birth; survivorship status; and current age or, if the child has died, age at death. I Key Findings • The under-5 mortality rate in Liberia is 94 deaths per 1,000 live births. That is, about 1 in 11 Liberian children dies before they reach age 5. • The infant mortality rate, or deaths before the first birthday, is 54 deaths per 1,000 live births. About half of these occur in the first month of life. • Under-5 mortality has been cut in half over the 15 years prior to the 2013 LDHS; neonatal, postneonatal, infant, and child mortality all declined as well over this 15-year span. • Under-5 mortality is highest in South Eastern B and North Western regions and lowest in North Central region. • Survey data show that spacing births farther apart could have an enormous impact on reducing under-5 mortality in Liberia. 110 • Infant and Child Mortality The quality of mortality estimates calculated from retrospective birth histories depends on the mother’s ability to recall all of the children she has given birth to, as well as their birth dates and ages at death. Potentially the most serious data quality problem is the selective omission from the birth histories of those births that did not survive. If the problem of omission is serious, it can result in underestimation of childhood mortality. If selective omission of childhood deaths occurs, it is usually most severe for deaths early in infancy. Generally, if deaths are substantially underreported, the result is a low ratio of early neonatal deaths (deaths within the first week of life) to all neonatal deaths and a low ratio of neonatal deaths to infant deaths. An examination of the proportion of early neonatal deaths to all neonatal deaths (Appendix Table C.5) shows that early neonatal deaths represented 75 percent of all neonatal deaths for the five-year period prior to the 2013 LDHS.1 The percentage of early neonatal deaths was essentially equivalent during the period 5-19 years preceding the survey. In comparison, the proportion of early neonatal deaths for the five-year period prior to the 2007 LDHS was 79 percent. An examination of the proportion of neonatal deaths to infant deaths (Appendix Table C.6) shows that neonatal deaths represented 53 percent of infant deaths for the five-year period prior to the 2013 LDHS. This is higher than the proportion reported in the period 5-19 years before the survey, which ranged between 37 percent and 51 percent, and higher than the proportion reported for the five-year period prior to the 2007 LDHS (48 percent). Another potential data quality problem involves the displacement of birth dates, which may distort mortality trends. This can occur if an interviewer knowingly records a birth as occurring in a different year, which could happen if an interviewer were trying to cut down on his or her overall work load, because live births occurring during the five years preceding the interview are the subject of a lengthy set of additional questions. In the 2013 LDHS questionnaire, the cut-off year for these questions was 2008. Appendix Table C.4 shows evidence of clear transference of children from 2008 to earlier years. For example, there were 1,558 children born in 2007 compared with 1,155 born in 2008, a 35 percent increase. A third factor that affects childhood mortality estimates is the quality of reporting of age at death. Misreporting of the child’s age at death may distort the age pattern of mortality, especially if the net effect of the age misreporting is to transfer deaths from one age bracket to another. For example, a net transfer of deaths from under 1 month to a higher age will affect the estimates of neonatal and postneonatal mortality. To minimize errors in reporting age at death, LDHS interviewers were instructed to record age at death in days if the death took place in the month following the birth, in months if the child died before age 2, and in years if the child was at least age 2. They also were asked to probe for deaths reported at age 1 to determine a more precise age at death in terms of months. Appendix Table C.6 shows that, for the five years preceding the survey, the number of reported deaths at age 12 months is comparable to the number of deaths reported at 11 months and at 13 months, but is much greater than the number reported at 10 months, indicating distortion of the infant mortality rate. There were also a number of deaths reported to have occurred at age “1 year,” despite the instructions given to interviewers. It is likely that at least some of these deaths may have occurred before the child’s first birthday and thus should be classified as infant deaths. 1 There are no models for mortality patterns during the neonatal period. However, one review of data from several developing countries concluded that, at neonatal mortality levels of 20 per 1,000 or higher, approximately 70 percent of neonatal deaths occur within the first six days of life (Boerma, 1988). Infant and Child Mortality • 111 Finally, any method of measuring childhood mortality that relies on mothers’ reports (e.g., birth histories) assumes that female adult mortality is not high, or if it is high, that there is little or no correlation between the mortality risks of the mothers and those of their children. In countries like Liberia that have low rates of female adult mortality due to HIV (see Chapter 14), these assumptions are likely valid. 8.2 INFANT AND CHILD MORTALITY LEVELS AND TRENDS Table 8.1 presents childhood mortality rates for the three five-year periods before the 2013 LDHS. The data show that, for the five-year period immediately prior to the survey, under-5 mortality was 94 per 1,000 live births; that is, around 1 of every 11 Liberian children died before reaching their fifth birthday during the five-year period. The infant mortality rate was 54 deaths per 1,000 live births, and the neonatal mortality rate was 26 per 1,000 births. That is, nearly 60 percent of under-5 deaths occurred during infancy, with more than one-quarter taking place during the first month of life. Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under 5 mortality rates for five-year periods preceding the survey, Liberia 2013 Years preceding the survey Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) 0-4 26 28 54 42 94 5-9 41 44 84 52 132 10-14 43 70 113 81 185 1 Computed as the difference between the infant and neonatal mortality rates An examination of the mortality levels across the three successive five-year periods shown in Table 8.1 suggests that under-5 mortality has progressively declined over the 15 years prior to the 2013 LDHS: from 185 deaths per 1,000 live births during the period circa 1998 to 2002, to 132 deaths per 1,000 live births during the period circa 2003 to 2007, to 94 deaths per 1,000 live births during the period circa 2008 to 2012. Neonatal, postneonatal, infant, and child mortality all declined during this 15-year span. Trends in mortality in early childhood can also be explored by examining the mortality results from successive rounds of DHS surveys in Liberia. Figure 8.1 shows neonatal, postneonatal, infant, child, and under-5 mortality rates for the five-year periods preceding the 1986, 2007, and 2013 LDHS surveys. The overall pattern suggests that mortality levels have continued to decline over the past three decades.2 2 Data from the 1999/2000 LDHS are not shown due to methodological differences between that survey and other LDHS surveys. In the 1999/2000 LDHS, infant mortality was 117 deaths per 1,000 live births, child mortality was 90 deaths per 1,000 live births, and under-5 mortality was 194 deaths per 1,000 live births. Data for neonatal and postneonatal mortality were not reported in the 1999/2000 LDHS. 112 • Infant and Child Mortality Figure 8.1 Trends in childhood mortality 1981-2012 68 76 144 91 222 32 39 71 41 110 26 28 54 42 94 Neonatal mortality Post-neonatal mortality Infant mortality Child mortality Under-5 mortality Deaths per 1,000 live births 1986 LDHS (1981-1985) 2007 LDHS (2002-2006) 2013 LDHS (2008-2012) 8.3 SOCIOECONOMIC DIFFERENTIALS IN EARLY CHILDHOOD MORTALITY Table 8.2 shows differentials in infant and child mortality by residence, region, mother’s education, and wealth quintile. The mortality estimates are calculated for the 10-year period before the survey so that the rates are based on a sufficient number of cases in each category to ensure statistically reliable estimates. Under-5 mortality is higher in rural areas (120 deaths per 1,000 live births) than in urban areas (106 deaths per 1,000 live births). Child, infant, and postneonatal mortality are also higher in rural areas than in urban areas. However, neonatal mortality is higher in urban areas (37 deaths per 1,000 live births), especially in Greater Monrovia (41 deaths per 1,000 live births), than in rural areas (31 deaths per 1,000 live births). A mother’s education and the wealth quintile into which a child is born also relate to survival. The under-5 mortality rate is lower for children born to mothers with secondary and higher education (97 deaths per 1,000 live births) than for children with mothers with only primary education (111 deaths per 1,000 live births) or no education (122 deaths per 1,000 live births). The under-5 mortality rate is substantially lower in the highest wealth quintile (99 deaths per 1,000 live births) than in the lowest quintile (130 deaths per 1,000 live births). Infant and Child Mortality • 113 Table 8.2 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, by background characteristics, Liberia 2013 Background characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Residence Urban 37 29 66 42 106 Greater Monrovia 41 29 70 42 109 Other urban 33 29 62 43 102 Rural 31 42 73 51 120 Region North Western 39 54 93 53 141 South Central 39 34 73 42 112 South Eastern A 26 44 70 47 113 South Eastern B 50 36 86 62 143 North Central 22 30 52 47 97 Mother's education No education 34 41 75 50 122 Primary 35 33 68 46 111 Secondary and higher 32 28 60 40 97 Wealth quintile Lowest 38 41 79 55 130 Second 26 39 65 50 112 Middle 32 35 67 41 105 Fourth 41 30 71 44 112 Highest 32 30 62 40 99 1 Computed as the difference between the infant and neonatal mortality rates 8.4 DEMOGRAPHIC DIFFERENTIALS IN EARLY CHILDHOOD MORTALITY The relationship between early childhood mortality and various demographic variables is examined in Table 8.3. Mortality rates for male and female children are generally similar. The largest difference is in the neonatal mortality rate, with higher mortality for males (37 deaths per 1,000 live births) than for females (30 deaths per 1,000 live births). Studies have shown that a longer birth interval seems to increase a child’s chance of survival. Data from the 2013 LDHS support this observation. For example, under-5 mortality decreases from 190 deaths per 1,000 live births for children born less than two years after a preceding sibling to 60 deaths per 1,000 live births for children born four years or more after a preceding sibling. Child, infant, postneonatal, and neonatal mortality rates also generally decline as the interval between births increases. These findings point out the potential for mortality reduction that could result from successful efforts to promote birth spacing in Liberia. A child’s size at birth is an indicator of the risk of dying during infancy, particularly during the first months of life. In the 2013 LDHS, in addition to recording the actual birth weight, interviewers asked mothers whether each of their children born in the last five years were very small, small, average size, large, or very large at birth. This type of subjective assessment has been shown to correlate closely with actual birth weight. Survey results indicate that newborns perceived by their mothers to be very small or small were more likely to die in their first year than those perceived as average or larger in size; the differential is especially great during the neonatal period. 114 • Infant and Child Mortality Table 8.3 Early childhood mortality rates by demographic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, by demographic characteristics, Liberia 2013 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Child's sex Male 37 35 72 46 115 Female 30 37 67 48 111 Mother's age at birth <20 36 39 75 59 129 20-29 35 34 69 44 110 30-39 30 37 67 41 105 40-49 30 33 63 (59) (118) Birth order 1 35 35 70 50 117 2-3 28 28 57 42 97 4-6 33 43 75 43 115 7+ 48 42 90 63 148 Previous birth interval2 <2 years 64 70 134 65 190 2 years 31 37 67 50 114 3 years 19 28 46 45 89 4+ years 22 14 36 25 60 Birth size3 Small/very small 56 39 94 na na Average or larger 18 23 41 na na Note: Figures in parentheses are based on 250-499 unweighted person-years of exposure to the risk of death. na = Not applicable 1 Computed as the difference between the infant and neonatal mortality rates 2 Excludes first-order births 3 Rates for the five-year period before the survey 8.5 PERINATAL MORTALITY Pregnancy losses occurring after seven completed months of gestation (stillbirths) plus deaths of live births within the first seven days of life (early neonatal deaths) constitute perinatal deaths. The distinction between a stillbirth and an early neonatal death is recognized as a fine one, often depending on observing and then remembering sometimes faint signs of life after delivery. Furthermore, the causes of stillbirths and early neonatal deaths are closely linked, and examining just one or the other can understate the true level of mortality around delivery. For this reason, deaths around time of delivery are combined into the perinatal mortality rate. Information on stillbirths is available for the five years preceding the survey and was collected using the calendar at the end of the Woman’s Questionnaire. Table 8.4 indicates that the perinatal mortality for the country as a whole is 30 deaths per 1,000 pregnancies of seven or more months in duration. Differentials in perinatal mortality across selected background characteristics of the mothers vary widely. For example, perinatal mortality is particularly high in South Eastern B (53 deaths per 1,000 pregnancies) relative to other regions (21 to 37 deaths per 1,000 pregnancies). Perinatal mortality generally declines with age and the length of the preceding pregnancy interval. Infant and Child Mortality • 115 Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the five-year period preceding the survey, by background characteristics, Liberia 2013 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Number of pregnancies of 7+ months duration Mother's age at birth <20 17 28 33 1,375 20-29 32 75 33 3,229 30-39 18 23 24 1,697 40-49 3 3 21 270 Previous pregnancy interval in months4 First pregnancy 19 38 37 1,536 <15 6 22 40 698 15-26 8 27 27 1,327 27-38 10 18 25 1,101 39+ 27 24 26 1,910 Residence Urban 38 67 32 3,278 Greater Monrovia 14 28 26 1,635 Other urban 23 39 38 1,644 Rural 32 62 29 3,293 Region North Western 6 21 37 737 South Central 28 49 29 2,697 South Eastern A 2 8 21 495 South Eastern B 5 23 53 534 North Central 28 28 26 2,110 Mother's education No education 17 45 23 2,729 Primary 28 51 39 2,011 Secondary and higher 25 32 31 1,832 Wealth quintile Lowest 17 39 35 1,596 Second 13 14 19 1,466 Middle 17 27 32 1,384 Fourth 15 36 41 1,248 Highest 8 13 23 877 Total 70 129 30 6,572 1 Stillbirths are fetal deaths in pregnancies lasting seven or more months. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months' duration, expressed per 1,000. 4 Categories correspond to birth intervals of <24 months, 24-35 months, 36-47 months, and 48+ months. 8.6 HIGH-RISK FERTILITY BEHAVIOR Typically, infants and young children have a higher risk of dying if they are born to very young mothers or older mothers, if they are born after a short birth interval, or if their mothers have already had many children. In the following analysis, mothers are classified as at risk if they are younger than age 18 or older than age 35 at the time of childbirth. A short birth interval is defined as less than 24 months, and a high-order birth is defined as occurring after three or more previous births (i.e., birth order 4 or higher). A child may be at an elevated risk of dying due to a combination of factors. The first column of Table 8.5 shows the percentage of births in the five years before the survey classified by various risk categories. Overall, 55 percent of births involved at least one avoidable risk factor, with 37 percent involving a single risk factor and 19 percent involving multiple risk factors. 116 • Infant and Child Mortality The second column in Table 8.5 presents risk ratios, which represent the increased risk of mortality among births in various high-risk categories relative to births not having any high-risk characteristics. Among births involving a single risk factor, a birth interval less than 24 months (risk ratio = 1.48) and mother’s age less than 18 (risk ratio = 1.34) are the single factors most associated with increased risk of under-5 mortality in Liberia. Overall, the risk ratio for single risk factor births was 1.18. Multiple risk factor births were generally associated with higher risk ratios than single risk factor births, with an overall risk ratio of 1.31. The third column of Table 8.5 shows the distribution of currently married women by the risk category into which a birth conceived at the time of the survey would fall. The data in the table show that 20 percent of women are not in any high-risk category, and 3 percent are only at risk of having their first birth between ages 18 and 34, which is considered to be an unavoidable risk. Seventy-seven percent of currently married women in the 2013 LDHS have at least one avoidable risk factor, with 30 percent having a single risk factor and 47 percent having multiple risk factors. Table 8.5 High-risk fertility behavior Percent distribution of children born in the five years preceding the survey by category of elevated risk of mortality and risk ratio, and percent distribution of currently married women by category of risk if they were to conceive a child at the time of the survey, Liberia 2013 Risk category Births in the 5 years preceding the survey Percentage of currently married women1 Percentage of births Risk ratio Not in any high-risk category 28.7 1.00 19.7a Unavoidable risk category First-order births between ages 18 and 34 years 15.9 1.29 3.4 Single high-risk category Mother's age <18 9.5 1.34 0.5 Mother's age >34 1.1 0.00 4.5 Birth interval <24 months 4.6 1.48 7.7 Birth order >3 21.6 1.11 17.6 Subtotal 36.8 1.18 30.3 Multiple high-risk category Age <18 and birth interval <24 months2 0.5 (1.42) 0.3 Age >34 and birth interval <24 months 0.0 * 0.2 Age >34 and birth order >3 11.6 0.92 31.8 Age >34 and birth interval <24 months and birth order >3 1.5 2.26 4.7 Birth interval <24 months and birth order >3 5.0 1.92 9.6 Subtotal 18.6 1.31 46.6 In any avoidable high-risk category 55.4 1.23 76.8 Total 100.0 na 100.0 Number of births/women 6,502 na 5,386 Note: Risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. Ratios in parentheses are based on 25-49 unweighted births. An asterisk indicates that a ratio is based on fewer than 25 unweighted births and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilized women Maternal Health Care • 117 MATERNAL HEALTH CARE 9 he health care services that a mother receives during pregnancy, childbirth, and the immediate postnatal period are important for the survival and wellbeing of both the mother and the infant. The 2013 LDHS obtained information on the extent to which women in Liberia receive care during each of these stages. These results are important to those who design policy and implement programs to improve maternal and child health care services. 9.1 PRENATAL CARE Prenatal care from a skilled provider is important to monitor pregnancy and reduce the risks for both mother and child during pregnancy, at delivery and within the postnatal period (within 42 days after delivery). Prenatal care enables (1) screening and/or early detection of complications and prompt treatment (e.g., of sexually transmitted infections or anemia); (2) prevention of diseases through immunization and micronutrient supplementation; (3) birth preparedness and complication readiness; (4) health promotion and disease prevention through health messages; and (5) advice and counseling of pregnant women, including place of delivery and referral of mothers with complications. Collecting information on prenatal care is relevant for identifying subgroups of women who do not use such services and is useful in planning improvements in services provided. In the 2013 LDHS, women who had given birth in the five years preceding the survey were asked whether they had received prenatal care for their last live birth. If the respondent had received prenatal care for her last birth, she was then asked a series of questions T Key Findings • Ninety-six percent of women age 15-49 who gave birth in the five years preceding the survey received prenatal care from a skilled provider during pregnancy for their most recent birth. Two-thirds of women received prenatal care during their first trimester. • Eighty-four percent of the women who gave birth in the five years preceding the survey received two or more tetanus toxoid injections during pregnancy, ensuring that their most recent live birth was protected against neonatal tetanus. • Fifty-six percent of live births in the five years preceding the survey took place in a health facility, and 61 percent of live births were delivered by a skilled provider. • Among women who gave birth in the two years preceding the survey, 71 percent received a postnatal checkup within the first two days after birth, and 57 percent received the checkup from a skilled provider. • Among women who had a birth in the two years preceding the survey, 35 percent of their newborns received a postnatal check-up in the first two days after birth, and 30 percent received a check-up from a skilled provider. • Forty-seven percent of women report that getting money for treatment is a problem in accessing health care when they are sick; 40 percent of women indicate that distance to a health facility is a problem. 118 • Maternal Health Care about the care she received, such as the type of provider, number of visits made, stage of pregnancy at the time of the first visit, and services and information provided during these visits. For women with two or more live births during the five-year period preceding the survey, data refer to the most recent birth. Table 9.1 presents information about the type of provider from whom prenatal care services were received for the most recent birth, according to background characteristics. For women who reported more than one source of prenatal services, only the provider with the highest qualifications is presented in the table. Ninety-six percent of women age 15-49 who had a live birth in the five years preceding the survey received prenatal care from a skilled provider (doctor, nurse, midwife, or physician’s assistant) during their last pregnancy. This figure is markedly higher than that reported in the 2007 LDHS (79 percent). Eighteen percent of women received care from a doctor, 76 percent from a nurse or midwife, and 2 percent from a physician’s assistant. Only 2 percent of women received care from a traditional midwife or other unskilled provider, as compared with 17 percent of women in the 2007 LDHS. Two percent of women received no prenatal care, as compared with 4 percent in the 2007 LDHS. These improvements in the provision of prenatal care by skilled providers may be attributed to the increased number of, and geographic access to, health facilities and increased numbers of skilled providers across Liberia in recent years (MOHSW, 2011a). There are modest differences in the percentage of women who receive prenatal care from a skilled provider by place of residence. In urban areas, 98 percent of pregnant women age 15–49 receive prenatal care from skilled providers, while in rural areas, the corresponding percentage is 93 percent. Women in Greater Monrovia (25 percent) are more likely than either women from other urban areas (15 percent) or rural women (15 percent) to receive prenatal care from a doctor. By county, prenatal care coverage by a skilled provider is highest in Montserrado (99 percent) and lowest in Grand Kru (86 percent) and Sinoe (87 percent). There are modest educational and wealth status variations in the percentages of women who receive prenatal care from a skilled provider. For example, women with secondary and higher education are more likely to receive prenatal care services from a doctor (22 percent) than women with primary or no education (16 percent each). Women’s economic status also correlates with prenatal care provider type. Women in the highest wealth quintile (26 percent) are more likely to receive prenatal care from a doctor compared with those in the lower wealth quintiles (16 to 18 percent). Maternal Health Care • 119 Table 9.1 Prenatal care Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by prenatal care provider during pregnancy for the most recent birth and the percentage receiving prenatal care from a skilled provider for the most recent birth, according to background characteristics, Liberia 2013 Background characteristic Prenatal care provider No prenatal care Total Percentage receiving prenatal care from a skilled provider1 Number of women Doctor Nurse/ midwife Physician's Assistant Traditional midwife Other Mother's age at birth <20 20.0 74.5 2.2 1.3 0.0 2.0 100.0 96.7 971 20-34 16.6 77.7 1.7 1.6 0.1 2.3 100.0 96.0 3,031 35-49 20.0 73.8 0.8 1.9 0.2 3.2 100.0 94.6 768 Birth order 1 21.2 74.7 1.7 1.2 0.0 1.2 100.0 97.6 1,161 2-3 17.2 76.9 1.8 1.9 0.0 2.2 100.0 95.9 1,700 4-5 17.4 76.3 1.2 1.5 0.1 3.2 100.0 94.9 998 6+ 15.2 77.7 1.8 1.6 0.2 3.3 100.0 94.8 911 Residence Urban 20.1 76.9 1.1 0.6 0.0 1.2 100.0 98.0 2,555 Greater Monrovia 25.2 72.7 1.0 0.7 0.0 0.4 100.0 98.9 1,332 Other Urban 14.6 81.4 1.1 0.6 0.0 2.1 100.0 97.1 1,223 Rural 15.2 75.8 2.3 2.7 0.1 3.7 100.0 93.4 2,215 Region North Western 11.7 81.6 1.4 2.6 0.4 2.3 100.0 94.8 496 South Central 20.0 76.5 1.2 0.7 0.0 1.5 100.0 97.7 2,103 South Eastern A 17.6 72.5 2.6 2.7 0.1 4.3 100.0 92.7 328 South Eastern B 20.4 66.1 3.6 2.3 0.1 7.1 100.0 90.1 352 North Central 16.3 77.8 1.7 2.1 0.0 2.0 100.0 95.8 1,491 County Bomi 30.2 61.1 0.0 7.6 0.0 1.1 100.0 91.3 128 Bong 10.1 84.0 1.2 1.1 0.0 3.5 100.0 95.3 559 Gbarpolu 8.3 85.2 1.5 0.3 0.8 4.0 100.0 94.9 112 Grand Bassa 20.8 69.7 2.0 1.5 0.3 5.7 100.0 92.4 267 Grand Cape Mount 4.0 90.4 2.1 1.0 0.3 2.1 100.0 96.4 256 Grand Gedeh 22.8 70.5 2.1 1.3 0.2 2.3 100.0 95.3 112 Grand Kru 30.1 50.6 5.6 4.7 0.0 8.4 100.0 86.3 147 Lofa 41.6 45.8 3.4 8.3 0.0 0.7 100.0 90.8 262 Margibi 3.0 92.8 1.7 0.2 0.0 2.3 100.0 97.4 349 Maryland 10.6 80.0 1.5 0.3 0.2 7.4 100.0 92.1 141 Montserrado 23.9 73.9 0.9 0.7 0.0 0.6 100.0 98.7 1,487 Nimba 11.6 85.1 1.6 0.4 0.0 1.3 100.0 98.3 670 River Cess 5.3 87.8 3.7 0.9 0.0 2.3 100.0 96.8 92 River Gee 19.8 71.5 3.5 1.2 0.4 3.4 100.0 94.8 63 Sinoe 21.9 63.0 2.2 5.4 0.0 7.5 100.0 87.2 124 Education No education 16.3 75.1 1.9 2.0 0.1 4.4 100.0 93.3 1,862 Primary 15.7 79.5 1.7 1.4 0.1 1.6 100.0 96.8 1,428 Secondary and higher 21.9 75.1 1.3 1.2 0.0 0.5 100.0 98.3 1,479 Wealth quintile Lowest 16.5 72.6 2.6 2.9 0.3 5.2 100.0 91.6 1,052 Second 15.7 77.3 1.6 2.4 0.0 2.8 100.0 94.5 995 Middle 15.5 79.8 1.9 1.1 0.0 1.7 100.0 97.1 1,014 Fourth 18.2 78.6 1.4 0.7 0.0 1.0 100.0 98.2 972 Highest 25.6 73.0 0.5 0.4 0.0 0.4 100.0 99.1 736 Total 17.9 76.4 1.7 1.6 0.1 2.4 100.0 95.9 4,769 Note: If more than one source of prenatal care was mentioned, only the provider with the highest qualifications is considered in this tabulation. Total includes 4 cases for which information on prenatal care provider is missing. 1 Skilled provider includes doctor, nurse, midwife, and physician's assistant. 120 • Maternal Health Care 9.2 NUMBER AND TIMING OF PRENATAL VISITS Prenatal care is more effective in preventing adverse pregnancy outcomes when sought early in the pregnancy and continued through to delivery. Health professionals recommend that the first prenatal visit occur within 12 to 16 weeks of pregnancy. The second visit should occur at 28 weeks, the third visit at 32 weeks, and the fourth visit at 36 weeks. Under normal circumstances, WHO recommends that a woman without complications should have at least four visits. Women with complications, special needs, or conditions beyond the scope of basic care may require additional visits. In the 2013 LDHS, respondents were asked how many prenatal care visits they made during the pregnancy preceding their last live birth in the five years before the survey and how many months pregnant they were at the time of the first visit. Table 9.2 shows that among women who had a live birth in the five years preceding the survey, 78 percent had four or more prenatal care visits, 15 percent had two to three visits, and 2 percent had one visit only. Only 2 percent of women received no prenatal care, down from 4 percent in the 2007 LDHS. Urban women are more likely to receive four or more visits (83 percent) than rural women (72 percent). Table 9.2 also shows that the majority of women (67 percent) had their first visit at less than four months of pregnancy, as recommended. Twenty-four percent of women had their first visit in the fourth to the fifth month of pregnancy, 6 percent had their first visit in the sixth to the seventh month of pregnancy, and 1 percent had their first visit from the eighth month onwards. The median duration of pregnancy at the first visit was 3.3 months, down from 3.5 months in the 2007 LDHS. This is within the recommended period for the first prenatal care visit. 9.3 COMPONENTS OF PRENATAL CARE The content of prenatal care is an essential component of the quality of services. Apart from receiving basic care, every pregnant woman should be monitored for complications. Ensuring that pregnant women receive information on and undergo screening for complications should be a routine part of all prenatal care visits. To assess prenatal care services, respondents were asked whether they had been advised of complications or received certain screening tests during at least one of the prenatal care visits. Table 9.3 presents information on the content of prenatal services, including the percentages of women who took iron supplements, took drugs for intestinal parasites, were informed of the signs of pregnancy complications, and received selected routine services during prenatal care visits for their most recent birth in the past five years. Table 9.2 Number of prenatal care visits and timing of first visit Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by number of prenatal care visits for the most recent live birth, and by the timing of the first visit, and among women with prenatal care, median months pregnant at first visit, according to residence, Liberia 2013 Number and timing of prenatal visits Residence Total Urban Rural Number of prenatal care visits None 1.3 3.7 2.4 1 0.5 2.9 1.6 2-3 11.7 17.6 14.5 4+ 83.4 72.0 78.1 Don't know/missing 3.1 3.8 3.4 Total 100.0 100.0 100.0 Number of months pregnant at time of first prenatal care visit No prenatal care 1.3 3.7 2.4 <4 68.6 64.3 66.6 4-5 24.7 23.3 24.1 6-7 4.8 6.9 5.8 8+ 0.3 1.0 0.7 Don't know/missing 0.3 0.7 0.5 Total 100.0 100.0 100.0 Number of women 2,555 2,215 4,769 Median months pregnant at first visit (for those with prenatal care) 3.3 3.3 3.3 Number of women with prenatal care 2,523 2,132 4,655 Maternal Health Care • 121 Table 9.3 Components of prenatal care Among women age 15-49 with a live birth in the five years preceding the survey, the percentage who took iron tablets and drugs for intestinal worms during the pregnancy of the most recent birth, and among women receiving prenatal care for the most recent live birth in the five years preceding the survey, the percentage receiving specific prenatal services, according to background characteristics, Liberia 2013 Background characteristic Among women with a live birth in the past five years, the percentage who during the pregnancy of their last birth Number of women with a live birth in the past five years Among women who received prenatal care for their most recent birth in the past five years, the percentage with selected services Number of women with prenatal care for their most recent birth Took iron tablets Took drugs for intestinal worms Informed of signs of pregnancy complications Blood pressure measured Urine sample taken Blood sample taken Mother's age at birth <20 97.5 53.9 971 67.9 97.6 87.8 93.9 952 20-34 96.3 58.3 3,031 70.7 97.2 84.6 92.8 2,960 35-49 96.2 61.3 768 70.1 97.7 85.1 92.8 743 Birth order 1 97.5 55.0 1,161 71.0 97.9 89.0 94.8 1,147 2-3 97.1 60.5 1,700 70.5 97.1 86.3 93.9 1,663 4-5 95.4 57.3 998 68.9 97.2 85.4 92.0 965 6+ 95.4 57.3 911 69.2 97.2 78.8 90.1 879 Residence Urban 98.0 59.8 2,555 74.3 98.4 91.9 96.4 2,523 Greater Monrovia 99.3 60.4 1,332 81.6 100.0 97.3 98.3 1,327 Other urban 96.6 59.2 1,223 66.2 96.6 85.9 94.3 1,195 Rural 94.8 55.7 2,215 65.0 96.1 77.6 89.0 2,132 Region North Western 97.3 59.5 496 75.4 97.6 79.7 85.4 485 South Central 98.2 58.5 2,103 75.4 98.8 92.1 95.6 2,071 South Eastern A 92.8 56.6 328 66.4 94.9 83.5 92.6 314 South Eastern B 88.9 52.6 352 57.1 95.5 79.4 89.8 326 North Central 96.6 58.2 1,491 64.3 96.2 79.3 92.6 1,459 County Bomi 98.2 66.4 128 71.2 99.0 88.1 88.3 127 Bong 95.4 53.7 559 67.1 93.6 60.9 87.5 539 Gbarpolu 96.0 43.6 112 68.7 94.5 60.3 76.2 108 Grand Bassa 94.1 40.6 267 58.1 93.9 79.1 88.0 252 Grand Cape Mount 97.4 63.0 256 80.4 98.3 83.7 88.0 250 Grand Gedeh 96.2 62.0 112 73.6 96.3 92.2 97.3 109 Grand Kru 86.8 58.6 147 57.4 93.9 83.3 88.2 135 Lofa 96.5 59.5 262 49.4 97.9 84.3 94.3 259 Margibi 97.0 65.1 349 66.8 97.9 91.1 94.6 341 Maryland 91.2 44.0 141 53.9 96.3 79.8 90.4 131 Montserrado 99.2 60.1 1,487 80.4 99.8 94.6 97.2 1,478 Nimba 97.5 61.4 670 67.9 97.6 92.3 96.2 661 River Cess 96.8 58.3 92 69.7 98.2 80.7 94.1 90 River Gee 88.8 58.0 63 63.2 97.2 69.7 91.8 61 Sinoe 86.6 50.5 124 56.9 91.0 77.3 87.0 115 Education No education 94.2 57.1 1,862 66.9 96.2 79.2 89.9 1,778 Primary 96.9 57.3 1,428 69.3 96.9 84.1 93.2 1,405 Secondary and higher 99.0 59.6 1,479 74.7 99.2 94.0 96.6 1,472 Wealth quintile Lowest 93.1 52.5 1,052 65.5 94.7 75.1 87.3 997 Second 95.6 56.3 995 61.1 96.0 76.9 89.0 966 Middle 97.5 59.9 1,014 70.1 97.4 87.2 94.4 996 Fourth 98.7 59.8 972 76.1 99.4 93.7 97.6 962 Highest 98.5 62.8 736 80.1 100.0 96.9 98.2 733 Total 96.5 57.9 4,769 70.1 97.3 85.3 93.0 4,655 Overall, 97 percent of women took iron tablets during the pregnancy of their last birth. Variations by background characteristics are generally minor. 122 • Maternal Health Care As a component of prenatal care, the administration of drugs to treat intestinal worms is much less common than the administration of iron supplements. Overall, only 58 percent of women took drugs to treat intestinal worms during their last pregnancy. Women age 35-49 were more likely than women under age 20 to have taken drugs for intestinal parasites (61 percent and 54 percent, respectively). By county, prevalence of having taken drugs for intestinal parasites ranged from a low of 41 percent in Grand Bassa to a high of 66 percent in Bomi. Women in the lowest wealth quintile were less likely than women in the highest quintile to have taken drugs for intestinal parasites (53 percent and 63 percent, respectively). Seventy percent of the women who received prenatal care for their most recent live birth in the five years preceding the survey were informed of the signs of pregnancy complications. Women in Greater Monrovia (82 percent) were more likely to receive information than those in other urban areas (66 percent) or rural areas (65 percent). Differences are also reported by county; 80 percent of women in both Grand Cape Mount and Montserrado were informed of pregnancy complications compared to 49 percent of women in Lofa. Education and wealth quintile have a positive association with being informed of the signs of pregnancy complications. Seventy-five percent of women with at least some secondary education and 80 percent in the highest wealth quintile were informed of the signs of pregnancy complications compared with 67 percent of women with no education and 66 percent in the lowest quintile. Among the various other prenatal care services, overall, 97 percent of women who received prenatal care had their blood pressure measured, 85 percent had a urine sample taken, and 93 percent had a blood sample taken. By background characteristics, the likelihood of women receiving each of these prenatal care services increases with education level and wealth. In addition, women in urban areas were more likely than those in rural areas to receive each prenatal care service. 9.4 TETANUS TOXOID Tetanus toxoid injections are given during pregnancy to prevent neonatal tetanus, a leading cause of early infant death in many developing countries that is often due to poor hygiene during delivery. For full protection of her newborn baby, a pregnant woman should receive at least two injections of the vaccine during the pregnancy. If a woman has been vaccinated during a previous pregnancy, however, she may only require one or no doses for the current pregnancy. Five doses are considered to provide lifetime protection. Among women age 15-49 with a live birth in the five years preceding the survey, Table 9.4 presents the percentage whose last birth was protected against neonatal tetanus. Eighty-four percent of women received two or more tetanus toxoid injections during the pregnancy of their last live birth. This represents an increase from that reported in the 2007 LDHS (75 percent). Women in urban areas are more likely to have received two or more tetanus toxoid injections during the last pregnancy than women in rural areas (89 percent and 79 percent, respectively). By county, Grand Cape Mount, Lofa, and Montserrado have the highest proportion of women who received two or more tetanus toxoid injections during their last pregnancy (90 percent), while Grand Kru has the lowest proportion (52 percent). The proportion of women who received two or more tetanus toxoid injections during pregnancy varies by level of education and wealth. Eighty-eight percent of women with secondary and higher education received two or more tetanus toxoid injections during the last pregnancy compared with 81 percent of women with no education. Women in the highest wealth quintile were more likely than women in lowest wealth quintile to receive two or more tetanus toxoid injections (91 percent and 73 percent, respectively). Overall, 88 percent of women’s last births were protected against neonatal tetanus. Differences by background characteristics follow similar patterns to those reported for women who received two or more Maternal Health Care • 123 tetanus toxoid injections during the last pregnancy. The proportion of births protected against neonatal tetanus has increased since 2007 (88 percent compared with 78 percent). Table 9.4 Tetanus toxoid injections Among mothers age 15-49 with a live birth in the five years preceding the survey, the percentage receiving two or more tetanus toxoid injections during the pregnancy for the last live birth and the percentage whose last live birth was protected against neonatal tetanus, according to background characteristics, Liberia 2013 Background characteristic Percentage receiving two or more injections during last pregnancy Percentage whose last birth was protected against neonatal tetanus1 Number of mothers Mother's age at birth <20 81.5 85.9 971 20-34 85.3 89.1 3,031 35-49 83.0 85.5 768 Birth order 1 83.8 88.0 1,161 2-3 85.8 89.6 1,700 4-5 85.1 88.1 998 6+ 80.5 84.1 911 Residence Urban 89.0 92.3 2,555 Greater Monrovia 90.4 93.8 1,332 Other urban 87.4 90.8 1,223 Rural 78.6 82.7 2,215 Region North Western 85.6 87.8 496 South Central 87.0 90.6 2,103 South Eastern A 73.7 79.0 328 South Eastern B 63.1 69.4 352 North Central 86.9 90.2 1,491 County Bomi 89.3 91.3 128 Bong 82.3 86.4 559 Gbarpolu 71.8 76.8 112 Grand Bassa 67.5 73.5 267 Grand Cape Mount 89.8 90.9 256 Grand Gedeh 80.2 84.8 112 Grand Kru 51.5 58.7 147 Lofa 90.4 92.3 262 Margibi 87.9 91.1 349 Maryland 74.9 79.5 141 Montserrado 90.4 93.6 1,487 Nimba 89.3 92.7 670 River Cess 84.6 89.1 92 River Gee 63.8 71.5 63 Sinoe 59.8 66.3 124 Education No education 80.6 84.0 1,862 Primary 84.4 88.3 1,428 Secondary and higher 88.4 92.3 1,479 Wealth quintile Lowest 73.3 78.2 1,052 Second 81.4 85.5 995 Middle 88.3 90.9 1,014 Fourth 89.1 92.6 972 Highest 91.2 94.3 736 Total 84.2 87.8 4,769 1 Includes mothers with two injections during the pregnancy of her last birth, or two or more injections (the last within 3 years of the last live birth), or three or more injections (the last within 5 years of the last birth), or four or more injections (the last within 10 years of the last live birth), or five or more injections at any time prior to the last birth. 124 • Maternal Health Care 9.5 PLACE OF DELIVERY Increasing the proportion of women who deliver in health facilities is an important factor in reducing health risks to the mother and the newborn. Proper medical attention and hygienic conditions during delivery can reduce the risks of complications and infections that can cause morbidity and mortality to either the mother or the infant. Table 9.5 presents the percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics. Table 9.5 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery and percentage delivered in a health facility, according to background characteristics, Liberia 2013 Background characteristic Health facility Home Other Missing Total Percentage delivered in a health facility Number of births Public sector Private sector Mother's age at birth <20 47.8 12.2 39.2 0.6 0.1 100.0 60.1 1,358 20-34 42.6 11.8 45.1 0.4 0.1 100.0 54.3 4,217 35-49 40.4 16.0 43.1 0.3 0.2 100.0 56.4 927 Birth order 1 49.1 15.5 35.0 0.3 0.1 100.0 64.6 1,612 2-3 44.3 12.2 43.0 0.4 0.2 100.0 56.5 2,310 4-5 40.2 11.2 47.8 0.7 0.1 100.0 51.4 1,369 6+ 37.6 10.3 51.4 0.4 0.2 100.0 47.9 1,211 Prenatal care visits1 None 9.8 2.5 86.5 0.5 0.7 100.0 12.3 115 1-3 33.9 6.9 59.0 0.2 0.0 100.0 40.8 766 4+ 50.3 15.5 33.7 0.4 0.0 100.0 65.8 3,726 Don't know/missing 44.1 15.5 39.8 0.5 0.0 100.0 59.7 163 Residence Urban 47.5 18.7 33.6 0.2 0.0 100.0 66.2 3,241 Greater Monrovia 49.5 26.6 23.9 0.0 0.0 100.0 76.1 1,621 Other urban 45.4 10.9 43.4 0.3 0.1 100.0 56.2 1,620 Rural 39.3 6.2 53.5 0.7 0.2 100.0 45.5 3,261 Region North Western 42.8 4.1 51.0 1.9 0.2 100.0 47.0 731 South Central 41.5 23.3 34.9 0.1 0.1 100.0 64.8 2,668 South Eastern A 55.5 3.8 39.0 1.3 0.4 100.0 59.2 492 South Eastern B 48.4 4.2 47.0 0.1 0.3 100.0 52.6 529 North Central 41.8 5.6 52.3 0.3 0.0 100.0 47.4 2,082 County Bomi 56.4 7.7 35.3 0.6 0.0 100.0 64.1 177 Bong 32.5 2.1 65.2 0.2 0.0 100.0 34.6 792 Gbarpolu 46.5 1.2 52.0 0.3 0.0 100.0 47.7 161 Grand Bassa 26.2 14.0 59.1 0.7 0.0 100.0 40.2 366 Grand Cape Mount 35.2 3.8 57.7 3.1 0.3 100.0 39.0 392 Grand Gedeh 66.7 2.5 28.1 1.3 1.4 100.0 69.2 157 Grand Kru 47.8 3.3 48.5 0.0 0.4 100.0 51.1 235 Lofa 72.9 2.7 23.1 1.1 0.2 100.0 75.6 342 Margibi 24.5 26.8 47.9 0.2 0.6 100.0 51.3 478 Maryland 48.9 5.4 45.6 0.1 0.0 100.0 54.3 196 Montserrado 49.1 24.3 26.7 0.0 0.0 100.0 73.3 1,824 Nimba 38.4 9.7 52.0 0.0 0.0 100.0 48.0 949 River Cess 54.8 4.0 39.7 1.5 0.0 100.0 58.8 147 River Gee 49.0 3.7 46.4 0.4 0.5 100.0 52.7 97 Sinoe 46.7 4.6 47.5 1.1 0.0 100.0 51.3 189 Mother's education No education 37.4 7.9 54.0 0.5 0.2 100.0 45.3 2,713 Primary 44.4 11.3 43.5 0.7 0.0 100.0 55.7 1,983 Secondary and higher 51.2 20.5 28.0 0.1 0.1 100.0 71.7 1,807 Wealth quintile Lowest 37.4 3.2 58.6 0.7 0.2 100.0 40.6 1,580 Second 41.9 3.8 53.5 0.6 0.2 100.0 45.7 1,452 Middle 44.5 12.0 42.7 0.6 0.1 100.0 56.5 1,367 Fourth 47.9 22.1 30.0 0.0 0.1 100.0 70.0 1,234 Highest 48.4 30.9 20.5 0.1 0.0 100.0 79.3 870 Total 43.4 12.5 43.6 0.4 0.1 100.0 55.8 6,502 1 Includes only the most recent birth in the five years preceding the survey Maternal Health Care • 125 Table 9.5 shows that 56 percent of births occurred in health facilities. This figure is higher than that recorded in the 2007 LDHS (37 percent). Forty-three percent of births took place in public health facilities and 13 percent happened in private health facilities. Forty-four percent of live births in the five years preceding the survey occurred at home, compared with 61 percent in the 2007 LDHS. Women less than age 20 are slightly more likely to deliver in a health facility (60 percent) compared with women age 20-34 (54 percent) or age 35-49 (56 percent). There is a strong relationship between uptake of prenatal care and place of delivery. Only 12 percent of live births to women who received no prenatal care services took place in a health facility compared with 66 percent of live births to women who received four or more prenatal care visits. Place of delivery differs greatly by residence; 66 percent of births in urban areas were delivered in a health facility compared with 46 percent of births in rural areas. Among urban areas, the proportion of births that occurred in a health facility was larger in Greater Monrovia than other urban areas (76 percent and 56 percent, respectively). By county, the percentage of births delivered in a health facility ranges from a low of 35 percent in Bong to a high of 76 percent in Lofa. Conversely, home deliveries are most common in Bong (65 percent) and least common in Lofa (23 percent). There is a strong correlation between a mother’s education and place of delivery, and between household wealth and place of delivery. Births to mothers with secondary and higher education are much more likely to take place in a health facility than births to mothers with no education (72 percent compared with 45 percent). Likewise, births to women in the highest wealth quintile are nearly twice as likely to take place in a health facility as births to women in the lowest wealth quintile (79 percent and 41 percent, respectively). 9.6 ASSISTANCE DURING DELIVERY Obstetric care from a skilled provider (doctor, nurse, midwife, or physician’s assistant) during delivery is recognized as a critical element in the reduction of maternal and neonatal mortality. Births delivered at home are usually more likely to be delivered without assistance from a skilled provider, whereas births delivered at a health facility are more likely to be delivered by a trained health professional. Table 9.6 shows the percent distribution of live births in the five years preceding the survey by person providing assistance at delivery and the percentage of births delivered by Caesarean section (C-section), according to background characteristics. Sixty-one percent of live births in the five years preceding the survey were delivered by a skilled provider, with 8 percent of the deliveries assisted by a doctor, 52 percent by a nurse or midwife, and 1 percent by a physician’s assistant. Thirty-five percent of births were assisted by a traditional midwife, and 4 percent by relatives or others. Overall, the percentage of live births delivered by a skilled provider observed in the 2013 LDHS (61 percent) represents an increase from the figure reported in the 2007 LDHS (46 percent). The percentage of live births delivered by a skilled provider does not differ greatly by mother’s age at birth. In contrast, large variations occur by birth order, number of prenatal care visits, place of delivery, residence, region, county, education, and wealth quintile. First-order births are more likely to receive assistance from a skilled provider (70 percent) compared with higher-order births (54-61 percent). Births to mothers who had four or more prenatal care visits (71 percent) were much more likely than those with fewer visits (47 percent) or no prenatal care (16 percent) to be delivered by a skilled provider. Almost all births delivered in a health facility were delivered by a skilled provider (98 percent) compared with 15 percent of births that occurred elsewhere. Among births that occurred outside a health facility, 76 percent were assisted by a traditional midwife and 9 percent by relatives or others. 126 • Maternal Health Care Table 9.6 Assistance during delivery Percent distribution of live births in the five years preceding the survey by person providing assistance during delivery, percentage of births assisted by a skilled provider and percentage delivered by caesarean-section, according to background characteristics, Liberia 2013 Background characteristic Person providing assistance during delivery Percentage delivered by a skilled provider1 Percentage delivered by C- section Number of births Doctor Nurse/ midwife Physician's assistant Traditional midwife Relative/ friend/other No one Don't know/ missing Total Mother's age at birth <20 9.0 55.5 0.5 30.8 4.0 0.1 0.1 100.0 65.0 3.7 1,358 20-34 7.8 51.3 0.7 36.0 3.8 0.3 0.1 100.0 59.8 4.0 4,217 35-49 8.6 52.5 0.1 33.9 4.3 0.4 0.2 100.0 61.3 3.3 927 Birth order 1 9.5 60.1 0.4 26.6 3.3 0.1 0.0 100.0 70.0 5.4 1,612 2-3 8.9 51.5 0.8 35.1 3.5 0.1 0.2 100.0 61.1 3.7 2,310 4-5 7.3 48.8 0.5 38.8 4.1 0.3 0.1 100.0 56.6 3.5 1,369 6+ 6.2 47.8 0.5 39.5 5.2 0.6 0.2 100.0 54.4 2.6 1,211 Prenatal care visits2 None 1.9 12.8 1.1 62.5 18.8 1.4 1.5 100.0 15.8 3.4 115 1-3 7.9 38.3 1.2 44.2 7.8 0.6 0.0 100.0 47.4 3.1 766 4+ 9.6 60.6 0.4 26.5 2.7 0.1 0.0 100.0 70.7 4.6 3,726 Don't know/missing 8.9 51.8 0.3 37.9 1.1 0.0 0.0 100.0 61.0 3.8 163 Place of delivery Health facility 14.5 83.0 0.6 1.9 0.0 0.0 0.0 100.0 98.0 6.9 3,630 Elsewhere 0.3 13.7 0.5 76.2 8.8 0.6 0.0 100.0 14.5 0.0 2,863 Residence Urban 9.0 63.4 0.3 24.3 2.7 0.2 0.1 100.0 72.7 5.1 3,241 Greater Monrovia 10.6 72.7 0.6 13.2 2.8 0.1 0.0 100.0 83.9 5.9 1,621 Other urban 7.5 54.0 0.1 35.5 2.6 0.2 0.2 100.0 61.5 4.2 1,620 Rural 7.4 41.4 0.8 44.8 5.1 0.4 0.2 100.0 49.6 2.7 3,261 Region North Western 4.1 47.5 0.2 46.9 1.2 0.0 0.0 100.0 51.9 2.2 731 South Central 8.2 62.6 0.5 23.6 4.8 0.2 0.1 100.0 71.3 5.0 2,668 South Eastern A 8.3 56.2 0.9 29.3 4.4 0.5 0.4 100.0 65.3 2.5 492 South Eastern B 11.6 43.1 2.0 30.3 11.3 1.6 0.2 100.0 56.7 4.2 529 North Central 8.8 42.4 0.3 46.8 1.7 0.0 0.1 100.0 51.4 3.2 2,082 County Bomi 13.1 55.4 0.6 28.4 2.6 0.0 0.0 100.0 69.0 4.3 177 Bong 2.9 41.3 0.3 53.4 1.9 0.0 0.2 100.0 44.5 2.3 792 Gbarpolu 2.1 49.7 0.1 46.9 1.2 0.0 0.0 100.0 51.9 3.1 161 Grand Bassa 4.5 37.1 0.3 44.7 12.5 0.9 0.0 100.0 41.9 2.7 366 Grand Cape Mount 1.0 43.1 0.1 55.3 0.5 0.0 0.0 100.0 44.2 0.9 392 Grand Gedeh 12.3 59.9 1.1 22.8 2.5 0.0 1.4 100.0 73.4 4.1 157 Grand Kru 19.0 34.9 4.1 24.2 15.2 2.4 0.2 100.0 57.9 4.3 235 Lofa 31.4 39.6 0.8 24.9 3.1 0.0 0.2 100.0 71.8 5.9 342 Margibi 4.5 52.0 0.4 37.1 5.4 0.0 0.6 100.0 56.9 4.4 478 Maryland 5.9 49.0 0.0 35.7 8.8 0.7 0.0 100.0 54.8 5.1 196 Montserrado 9.9 70.5 0.6 15.8 3.1 0.1 0.0 100.0 81.0 5.6 1,824 Nimba 5.5 44.2 0.1 49.1 1.0 0.1 0.0 100.0 49.8 3.1 949 River Cess 2.7 60.3 0.4 35.2 1.4 0.0 0.0 100.0 63.4 2.2 147 River Gee 5.4 50.9 1.1 34.0 6.7 1.3 0.5 100.0 57.5 1.8 97 Sinoe 9.2 49.9 1.0 30.1 8.3 1.4 0.0 100.0 60.2 1.4 189 Mother's education No education 6.6 42.2 0.6 45.1 5.0 0.4 0.2 100.0 49.3 2.2 2,713 Primary 7.5 53.6 0.8 34.0 3.8 0.3 0.1 100.0 61.8 3.9 1,983 Secondary and higher 11.4 66.3 0.3 19.6 2.2 0.0 0.1 100.0 78.1 6.3 1,807 Wealth quintile Lowest 5.9 36.6 0.7 49.9 6.2 0.6 0.2 100.0 43.2 2.2 1,580 Second 8.2 41.7 0.6 44.9 4.3 0.1 0.2 100.0 50.5 3.1 1,452 Middle 8.2 53.6 0.3 34.8 2.8 0.2 0.1 100.0 62.2 3.3 1,367 Fourth 6.3 68.5 1.0 20.6 3.4 0.1 0.1 100.0 75.8 3.4 1,234 Highest 14.9 74.1 0.0 9.2 1.4 0.4 0.0 100.0 89.0 9.6 870 Total 8.2 52.4 0.6 34.6 3.9 0.3 0.1 100.0 61.1 3.9 6,502 Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. Total includes 8 cases for which information on place of delivery is missing. 1 Skilled provider includes doctor, nurse, midwife, and physician’s assistant. 2 Includes only the most recent birth in the five years preceding the survey Maternal Health Care • 127 In urban areas, 73 percent of births were assisted by a skilled provider compared with 50 percent in rural areas. By county, more than eight in ten deliveries in Montserrado (81 percent) were assisted by a skilled provider compared with four in 10 deliveries in Grand Bassa (42 percent), Grand Cape Mount (44 percent), and Bong (45 percent). Grand Cape Mount has the highest percentage of deliveries by traditional midwives (55 percent), and Montserrado has the lowest percentage (16 percent). Fifteen percent of live births in Grand Kru and 13 percent of live births in Grand Bassa were assisted during delivery by a relative, friend, or other unskilled person. Mother’s education is strongly related to the type of assistance at delivery. Births to women with secondary and higher education were much more likely to receive assistance from a skilled provider during delivery compared with births to women with no education (78 percent and 49 percent, respectively). Forty- five percent of births to women with no education and 34 percent of births to women with primary education only were assisted by a traditional midwife compared with 20 percent of births to women with secondary and higher education. Five percent of births to women with no education were assisted by a relative or friend compared with 2 percent of births to women with secondary and higher education. As with education, wealth quintile is strongly associated with type of assistance at delivery. Births to women in the highest wealth quintile were more likely to get assistance at delivery from a skilled provider (89 percent) compared with births to women in the lowest wealth quintile (43 percent). Furthermore, births to women in the highest wealth quintile were more than two times as likely as births to women in the lowest wealth quintile to be assisted by a doctor (15 percent and 6 percent, respectively). Respondents were also asked whether each of their live births in the five years preceding the survey were delivered by Caesarean (C-section). Four percent of births were delivered by C-section; this figure is unchanged from the one reported in the 2007 LDHS (4 percent). C-sections are most common among first births (5 percent), births in Greater Monrovia (6 percent) and in Lofa and Montserrado (6 percent each), births to women with secondary education and higher (6 percent), and births to women in the highest wealth quintile (10 percent). Figure 9.1 presents mother’s duration of stay in the health facility after giving birth. Approximately half (48 percent) of women that had a vaginal delivery spent one to two days at the health facility, but 22 percent stayed for less than six hours. For those mothers who had a Caesarean delivery, nearly nine in ten (87 percent) spent over three days at the health facility. 128 • Maternal Health Care Figure 9.1 Mother’s duration of stay in the health facility after giving birth 22 4 15 1 4 0 48 710 87 Vaginal birth Caesarean birth <6 hours 6-11 hours 12-23 hours 1-2 days 3+ days Percent LDHS 2013 9.7 POSTNATAL CARE FOR THE MOTHER A large proportion of maternal and neonatal deaths occur during the first 48 hours after delivery. Thus, prompt postnatal care (PNC) for both the mother and the child is important to treat any complications arising from the delivery, as well as to provide the mother with important information on how to care for herself and her child. Safe motherhood programs recommend that all women receive a check of their health within two days after delivery. Women who deliver at home should go to a health facility for postnatal care services within 24 hours, and subsequent visits (including those by women who deliver in a health facility) should be made at three days, seven days, and six weeks after delivery. It is also recommended that women who deliver in a health facility should be kept for at least 48 hours (up to 72 hours depending on the capacity of the institution) so the mothers and infants may be monitored by skilled personnel. To assess the extent of postnatal care utilization, respondents were asked, for the last birth in the two years preceding the survey, whether they had received a checkup after delivery, the timing of the first check- up, and the type of health provider performing the postnatal check-up. This information is presented according to background characteristics in Tables 9.7 and 9.8. Maternal Health Care • 129 Table 9.7 Timing of first postnatal checkup Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution of the mother's first postnatal check-up for the last live birth by time after delivery, and the percentage of women with a live birth in the two years preceding the survey who received a postnatal checkup in the first two days after giving birth, according to background characteristics, Liberia 2013 Background characteristic Time after delivery of mother's first postnatal checkup No postnatal checkup1 Total Percentage of women with a postnatal checkup in the first two days after birth Number of women Less than 4 hours 4-23 hours 1-2 days 3-6 days 7-41 days Don't know/ missing Mother's age at birth <20 58.5 6.0 7.9 1.5 1.0 3.3 21.8 100.0 72.5 574 20-34 55.1 6.7 8.2 1.5 1.6 1.5 25.4 100.0 70.0 1,704 35-49 56.6 9.0 6.3 1.0 0.7 1.9 24.5 100.0 71.9 372 Birth order 1 61.0 7.0 7.9 0.9 1.1 2.8 19.3 100.0 75.9 682 2-3 57.1 6.7 9.2 1.6 0.8 1.3 23.5 100.0 72.9 976 4-5 52.0 6.0 7.7 1.9 3.2 2.3 26.9 100.0 65.7 527 6+ 51.2 8.0 5.4 1.4 0.8 1.7 31.4 100.0 64.6 464 Place of delivery Health facility 69.6 9.5 8.2 0.7 0.4 2.9 8.8 100.0 87.3 1,622 Elsewhere 34.6 2.7 7.5 2.7 2.9 0.4 49.2 100.0 44.8 1,027 Residence Urban 62.0 6.3 8.5 1.4 1.1 2.0 18.6 100.0 76.9 1,351 Greater Monrovia 63.4 6.9 8.6 1.7 2.0 2.8 14.5 100.0 78.9 667 Other urban 60.7 5.8 8.4 1.1 0.2 1.2 22.6 100.0 74.9 684 Rural 49.8 7.4 7.2 1.5 1.6 1.9 30.6 100.0 64.5 1,299 Region North Western 51.1 9.9 9.0 1.8 1.6 3.1 23.5 100.0 70.0 288 South Central 58.2 6.0 7.5 1.4 2.1 1.9 22.8 100.0 71.7 1,109 South Eastern A 54.0 10.2 6.3 1.9 2.1 1.9 23.6 100.0 70.5 196 South Eastern B 42.3 8.8 6.2 1.9 1.8 2.1 36.9 100.0 57.3 197 North Central 58.5 5.7 8.7 1.1 0.0 1.6 24.2 100.0 73.0 860 County Bomi 59.6 8.1 5.0 0.0 0.9 8.3 18.1 100.0 72.7 68 Bong 44.4 7.2 6.6 1.5 0.1 1.1 39.1 100.0 58.1 318 Gbarpolu 33.9 13.3 14.9 1.3 1.3 4.7 30.4 100.0 62.2 64 Grand Bassa 19.5 6.0 6.8 1.3 5.2 0.6 60.7 100.0 32.3 149 Grand Cape Mount 54.6 9.2 8.3 2.8 2.0 0.2 23.0 100.0 72.1 155 Grand Gedeh 65.7 11.6 3.7 0.8 1.1 0.0 17.1 100.0 81.0 66 Grand Kru 34.0 14.5 7.8 1.8 0.4 3.5 38.0 100.0 56.3 80 Lofa 53.7 14.1 13.2 2.5 0.0 6.0 10.5 100.0 81.0 144 Margibi 74.7 0.8 4.7 1.2 0.8 0.4 17.5 100.0 80.1 214 Maryland 47.4 3.8 4.8 2.7 2.2 1.0 38.3 100.0 55.9 81 Montserrado 61.1 7.5 8.5 1.6 1.9 2.6 16.8 100.0 77.2 746 Nimba 71.7 1.5 8.9 0.3 0.0 0.4 17.3 100.0 82.0 398 River Cess 59.6 11.7 7.0 0.6 0.5 2.4 18.2 100.0 78.3 58 River Gee 49.0 7.6 6.1 0.5 3.8 1.6 31.3 100.0 62.7 36 Sinoe 39.0 7.8 7.9 3.8 4.2 3.3 33.8 100.0 54.8 73 Education No education 51.5 5.3 7.6 1.5 1.8 1.7 30.7 100.0 64.4 1,000 Primary 56.4 6.6 7.1 1.0 1.1 2.2 25.5 100.0 70.2 858 Secondary and higher 61.3 9.1 9.1 1.8 1.0 2.1 15.5 100.0 79.5 792 Wealth quintile Lowest 44.8 7.6 7.3 1.7 1.3 2.0 35.3 100.0 59.7 636 Second 51.1 5.6 8.2 1.1 1.7 1.4 30.9 100.0 64.9 567 Middle 59.9 7.1 8.0 0.9 1.8 1.6 20.7 100.0 75.1 551 Fourth 69.0 2.8 5.7 2.3 1.0 1.4 17.7 100.0 77.6 509 Highest 59.1 12.5 11.0 1.1 0.8 4.0 11.5 100.0 82.5 386 Total 56.0 6.9 7.9 1.4 1.4 2.0 24.5 100.0 70.8 2,650 1 Includes women who received a checkup after 41 days 130 • Maternal Health Care Table 9.8 Type of provider of first postnatal checkup for the mother Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution by type of provider of the mother's first postnatal health check in the two days after the last live birth, according to background characteristics, Liberia 2013 Background characteristic Type of health provider of mother's first postnatal checkup No postnatal checkup in the first two days after birth Total Number of women Doctor/ nurse/ midwife Physician's assistant Traditional midwife Other Mother's age at birth <20 56.4 2.3 12.8 1.0 27.5 100.0 574 20-34 54.2 2.0 13.6 0.1 30.0 100.0 1,704 35-49 54.6 2.5 14.2 0.6 28.1 100.0 372 Birth order 1 62.6 2.5 9.9 0.9 24.1 100.0 682 2-3 55.0 1.6 16.2 0.1 27.1 100.0 976 4-5 51.2 2.9 11.6 0.1 34.3 100.0 527 6+ 46.4 2.1 15.5 0.6 35.4 100.0 464 Place of delivery Health facility 83.1 3.0 1.1 0.1 12.7 100.0 1,622 Elsewhere 10.0 0.9 33.2 0.7 55.2 100.0 1,027 Residence Urban 63.0 2.1 11.4 0.3 23.1 100.0 1,351 Greater Monrovia 71.1 1.1 6.7 0.0 21.1 100.0 667 Other urban 55.2 3.1 15.9 0.6 25.1 100.0 684 Rural 46.1 2.2 15.8 0.4 35.5 100.0 1,299 Region North Western 50.6 2.3 16.5 0.5 30.0 100.0 288 South Central 59.3 1.1 10.7 0.6 28.3 100.0 1,109 South Eastern A 58.9 3.0 8.4 0.3 29.5 100.0 196 South Eastern B 46.5 2.0 8.3 0.6 42.7 100.0 197 North Central 51.1 3.4 18.6 0.0 27.0 100.0 860 County Bomi 60.9 0.0 11.8 0.0 27.3 100.0 68 Bong 43.2 1.3 13.6 0.0 41.9 100.0 318 Gbarpolu 45.7 2.8 11.3 2.4 37.8 100.0 64 Grand Bassa 26.3 0.0 6.0 0.0 67.7 100.0 149 Grand Cape Mount 48.1 3.2 20.8 0.0 27.9 100.0 155 Grand Gedeh 70.7 2.5 7.1 0.7 19.0 100.0 66 Grand Kru 48.1 0.8 6.7 0.7 43.7 100.0 80 Lofa 62.8 7.2 10.9 0.0 19.0 100.0 144 Margibi 48.2 2.1 26.8 3.1 19.9 100.0 214 Maryland 43.4 2.5 9.5 0.7 44.1 100.0 81 Montserrado 69.1 1.0 7.0 0.0 22.8 100.0 746 Nimba 53.1 3.6 25.3 0.0 18.0 100.0 398 River Cess 61.6 3.7 13.1 0.0 21.7 100.0 58 River Gee 50.0 3.7 9.0 0.0 37.3 100.0 36 Sinoe 46.0 2.8 6.0 0.0 45.2 100.0 73 Education No education 45.6 2.0 16.4 0.3 35.6 100.0 1,000 Primary 54.5 1.4 13.6 0.7 29.8 100.0 858 Secondary and higher 66.4 3.1 9.9 0.1 20.5 100.0 792 Wealth quintile Lowest 40.8 2.0 16.6 0.4 40.3 100.0 636 Second 48.0 1.7 15.0 0.2 35.1 100.0 567 Middle 53.2 4.3 17.5 0.1 24.9 100.0 551 Fourth 64.0 1.8 10.8 1.0 22.4 100.0 509 Highest 77.4 0.6 4.2 0.4 17.5 100.0 386 Total 54.7 2.2 13.5 0.4 29.2 100.0 2,650 Overall, 74 percent of mothers received a postnatal checkup within 41 days for the most recent birth in the two years preceding the survey. Fifty-six percent of mothers received a postnatal checkup within less than 4 hours after delivery, 7 percent within 4 to 23 hours, 8 percent within 1 to 2 days, 1 percent within 3 to 6 days, and 1 percent within 7 to 41 days after delivery. Twenty-five percent of the mothers had no postnatal checkup. In total, only 71 percent of women received a postnatal checkup within the first two days after delivery, the Maternal Health Care • 131 recommended time period. Nevertheless, this shows improvement from the 60 percent of women who received a postnatal checkup within the recommended interval reported in the 2007 LDHS. Although differences by mother’s age at birth were minor, women with six or more births were less likely to have a postnatal checkup within two days after delivery compared with women with one birth (65 percent compared with 76 percent). Women who delivered in a health facility, who resided in urban areas, who had higher levels of education, and who were in the highest wealth quintile were much more likely to receive a postnatal checkup within two days of delivery compared with other women. For instance, 87 percent of women who delivered at a health facility received a postnatal check-up within two days after birth compared with 45 percent who delivered elsewhere. Similarly, 77 percent of women living in urban areas had a postnatal checkup within two days compared with 65 percent of women living in rural areas. The postnatal care coverage for women who received a checkup within two days of delivery ranges from a low of 32 percent in Grand Bassa to a high of 82 percent in Nimba. Mothers with secondary education and higher are more likely to have had a postnatal checkup within two days of delivery than those with no education (80 percent and 64 percent, respectively). Also, mothers in the highest wealth quintile are more likely to have had a checkup within two days of delivery than those within the lowest wealth quintile (83 percent and 60 percent, respectively). Table 9.8 shows the type of provider of the mother’s first postnatal checkup that took place within two days after the last live birth: 57 percent of women received a postnatal checkup from a skilled provider (doctor, nurse, midwife, or physician’s assistant). Fourteen percent received a checkup from a traditional midwife. Differentials by background characteristics are similar to those observed for women who received a postnatal checkup within two days after delivery (Table 9.7). 9.8 POSTNATAL CARE FOR THE NEWBORN As mentioned, a significant proportion of neonatal deaths occur during the first few hours of life (48 hours) after delivery. The provision of postnatal care services for newborns should therefore start as soon as possible after the child is born. The timing of the postnatal checkup for the newborn is similar to that of the mother in that it should occur within two days after birth. Table 9.9 shows that 42 percent of last births in the two years preceding the survey received a postnatal checkup. Four percent of the newborns received a postnatal checkup less than 1 hour after birth, 16 percent within 1 to 3 hours, 3 percent within 4 to 23 hours, 12 percent within 1 to 2 days, and 7 percent within 3 to 6 days. Over half of newborns (57 percent) did not receive a postnatal checkup. Overall, 35 percent of births received a checkup in the first two days after birth. Place of delivery, residence, mother’s education level, and wealth quintile are closely linked to the timing of the first postnatal checkup for the newborn. Newborns whose mothers deliver in a health facility, live in urban areas, have at least some secondary education, and are in the highest wealth quintile have a greater chance of receiving a postnatal checkup within two days after birth when compared with those newborns whose mothers delivered elsewhere, reside in rural areas, are less educated, and are members of households in the lower wealth quintiles. For instance, 42 percent of newborns whose mothers delivered in a health facility received a checkup within 2 days compared with 23 percent whose mothers delivered elsewhere. Forty-five percent of newborns whose mothers reside in Greater Monrovia had a postnatal checkup within two days after birth compared with 33 percent of newborns whose mothers live in other urban areas and 30 percent whose mothers live in rural areas. Newborns whose mothers reside in Bomi (51 percent) were most likely to have a 132 • Maternal Health Care postnatal checkup within two days after birth, whereas those whose mothers live in Grand Bassa were the least likely (8 percent). Table 9.9 Timing of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by time after birth of first postnatal checkup, and the percentage of births with a postnatal checkup in the first two days after birth, according to background characteristics, Liberia 2013 Background characteristic Time after birth of newborn's first postnatal checkup No postnatal checkup1 Total Percentage of births with a postnatal checkup in the first two days after birth Number of births Less than 1 hour 1-3 hours 4-23 hours 1-2 days 3-6 days Don't know/ missing Mother's age at birth <20 2.2 17.7 2.4 12.8 6.2 0.5 58.2 100.0 35.1 574 20-34 4.0 16.2 3.2 11.9 7.9 0.6 56.2 100.0 35.3 1,704 35-49 3.1 13.0 3.1 11.2 7.1 1.3 61.2 100.0 30.7 372 Birth order 1 1.2 19.4 3.6 13.0 6.6 1.2 55.1 100.0 37.1 682 2-3 5.0 15.9 2.8 12.7 7.2 0.4 56.1 100.0 36.4 976 4-5 3.7 14.2 2.5 10.5 7.8 0.1 61.2 100.0 31.0 527 6+ 3.6 13.5 3.2 10.7 8.7 1.1 59.1 100.0 31.3 464 Place of delivery Health facility 4.3 21.8 3.6 12.0 5.8 0.9 51.6 100.0 41.8 1,622 Elsewhere 2.3 6.9 2.1 11.9 9.9 0.3 66.5 100.0 23.3 1,027 Residence Urban 3.8 18.7 2.9 13.2 7.8 0.6 52.9 100.0 38.7 1,351 Greater Monrovia 4.9 21.6 4.0 14.5 8.8 1.2 45.0 100.0 45.1 667 Other urban 2.8 15.8 1.9 12.0 6.7 0.1 60.7 100.0 32.5 684 Rural 3.2 13.3 3.1 10.7 7.1 0.7 62.0 100.0 30.3 1,299 Region North Western 0.7 17.5 4.0 15.6 10.1 0.6 51.5 100.0 37.8 288 South Central 4.0 15.3 3.1 11.5 7.9 0.8 57.4 100.0 33.9 1,109 South Eastern A 0.4 16.8 1.6 10.0 9.0 0.4 61.8 100.0 28.9 196 South Eastern B 4.1 9.4 4.2 6.4 4.8 1.8 69.4 100.0 24.0 197 North Central 4.4 17.9 2.6 13.1 6.1 0.4 55.5 100.0 38.2 860 County Bomi 0.6 38.4 4.1 7.6 7.1 2.4 39.9 100.0 50.7 68 Bong 10.4 17.7 3.6 6.2 4.4 0.2 57.5 100.0 37.8 318 Gbarpolu 1.3 17.3 2.5 10.4 3.5 0.0 65.0 100.0 31.5 64 Grand Bassa 0.0 4.2 0.8 3.3 4.1 0.5 87.1 100.0 8.3 149 Grand Cape Mount 0.5 8.4 4.6 21.3 14.2 0.0 51.0 100.0 34.8 155 Grand Gedeh 0.0 29.6 2.4 10.8 6.0 0.0 51.2 100.0 42.8 66 Grand Kru 0.0 6.0 8.1 5.4 3.5 3.5 73.6 100.0 19.4 80 Lofa 0.7 8.5 3.9 15.1 7.1 1.1 63.5 100.0 28.3 144 Margibi 2.0 5.2 0.0 7.4 6.9 0.0 78.5 100.0 14.6 214 Maryland 9.8 9.1 0.9 6.0 5.6 0.7 67.9 100.0 25.8 81 Montserrado 5.3 20.4 4.5 14.3 9.0 1.0 45.5 100.0 44.5 746 Nimba 1.0 21.5 1.4 17.9 7.1 0.3 51.0 100.0 42.0 398 River Cess 0.7 12.0 0.9 9.1 8.3 1.2 67.9 100.0 22.7 58 River Gee 0.0 17.3 3.0 9.8 5.9 0.4 63.5 100.0 30.1 36 Sinoe 0.7 9.0 1.5 10.0 12.3 0.0 66.5 100.0 21.2 73 Mother's education No education 3.5 13.5 2.3 9.9 8.0 0.4 62.4 100.0 29.2 1,000 Primary 3.9 12.7 3.5 12.7 6.4 0.7 60.2 100.0 32.9 858 Secondary and higher 3.1 22.8 3.4 13.8 7.8 1.0 48.0 100.0 43.2 792 Wealth quintile Lowest 3.7 13.6 2.7 8.8 5.3 0.8 65.1 100.0 28.8 636 Second 3.9 12.5 2.5 12.1 6.5 0.6 61.8 100.0 31.3 567 Middle 1.8 17.0 2.9 13.2 10.4 0.1 54.6 100.0 34.9 551 Fourth 1.6 18.4 2.2 12.4 8.2 1.5 55.7 100.0 34.6 509 Highest 7.7 20.8 5.5 14.7 7.0 0.3 44.1 100.0 48.7 386 Total 3.5 16.0 3.0 12.0 7.4 0.7 57.4 100.0 34.6 2,650 1 Includes newborns who received a checkup after the first week Maternal Health Care • 133 Newborns whose mothers have at least some secondary education are more likely to have a postnatal checkup within two days after birth when compared with their counterparts whose mothers have no education (43 percent and 29 percent, respectively). Newborns of mothers in the highest wealth quintile have a better chance of a checkup within two days after birth than those newborns whose mothers are part of the lowest wealth quintile (49 percent and 29 percent, respectively). Table 9.10 shows the type of provider of the newborn’s first postnatal checkup that took place within two days after birth: 30 percent of newborns received a postnatal checkup from a skilled provider (doctor, nurse, midwife, or physician’s assistant). Five percent of newborns received a postnatal checkup from a traditional midwife. Sixty-five percent of newborns did not receive a postnatal checkup within the first two days after birth. Differentials by background characteristics are similar to those observed for last births in the two years preceding the survey by time of newborn’s first postnatal checkup (Table 9.9). 134 • Maternal Health Care Table 9.10 Type of provider of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by type of provider of the newborn's first postnatal health check during the two days after the last live birth, according to background characteristics, Liberia 2013 Background characteristic Type of health provider of newborn's first postnatal checkup No postnatal checkup in the first two days after birth Total Number of births Doctor/ nurse/ midwife Physician's assistant Traditional midwife Other Mother's age at birth <20 29.8 1.4 3.8 0.1 64.9 100.0 574 20-34 29.2 1.0 5.0 0.1 64.7 100.0 1,704 35-49 25.7 0.6 4.4 0.0 69.3 100.0 372 Birth order 1 32.1 1.8 3.2 0.1 62.9 100.0 682 2-3 31.2 0.4 4.7 0.1 63.6 100.0 976 4-5 24.9 1.1 5.0 0.0 69.0 100.0 527 6+ 23.5 1.2 6.5 0.1 68.7 100.0 464 Place of delivery Health facility 39.5 1.5 0.8 0.0 58.2 100.0 1,622 Elsewhere 12.0 0.3 10.8 0.1 76.7 100.0 1,027 Residence Urban 34.8 0.8 3.0 0.0 61.3 100.0 1,351 Greater Monrovia 42.5 1.0 1.6 0.0 54.9 100.0 667 Other urban 27.3 0.6 4.5 0.0 67.5 100.0 684 Rural 22.5 1.3 6.3 0.1 69.7 100.0 1,299 Region North Western 31.2 2.7 3.9 0.1 62.2 100.0 288 South Central 31.3 0.7 1.8 0.0 66.1 100.0 1,109 South Eastern A 24.7 1.5 2.1 0.6 71.1 100.0 196 South Eastern B 18.9 0.8 4.2 0.1 76.0 100.0 197 North Central 27.9 0.9 9.4 0.0 61.8 100.0 860 County Bomi 42.9 0.0 7.8 0.0 49.3 100.0 68 Bong 27.7 0.0 10.1 0.0 62.2 100.0 318 Gbarpolu 24.5 0.7 5.8 0.5 68.5 100.0 64 Grand Bassa 5.9 0.0 2.4 0.0 91.7 100.0 149 Grand Cape Mount 28.8 4.6 1.4 0.0 65.2 100.0 155 Grand Gedeh 34.3 3.4 4.0 1.2 57.2 100.0 66 Grand Kru 15.2 0.0 4.2 0.0 80.6 100.0 80 Lofa 20.8 0.8 6.7 0.0 71.7 100.0 144 Margibi 12.1 0.8 1.7 0.0 85.4 100.0 214 Maryland 18.8 0.7 5.9 0.4 74.2 100.0 81 Montserrado 41.9 0.9 1.7 0.0 55.5 100.0 746 Nimba 30.7 1.5 9.7 0.0 58.0 100.0 398 River Cess 21.0 0.2 0.9 0.6 77.3 100.0 58 River Gee 27.4 2.8 0.0 0.0 69.9 100.0 36 Sinoe 19.1 0.8 1.3 0.0 78.8 100.0 73 Mother's education No education 21.5 1.2 6.5 0.1 70.8 100.0 1,000 Primary 28.3 0.8 3.8 0.1 67.1 100.0 858 Secondary and higher 38.6 1.2 3.3 0.1 56.8 100.0 792 Wealth quintile Lowest 19.8 1.1 7.7 0.1 71.2 100.0 636 Second 25.2 0.5 5.5 0.1 68.7 100.0 567 Middle 28.5 1.8 4.3 0.2 65.1 100.0 551 Fourth 29.9 0.9 3.7 0.0 65.4 100.0 509 Highest 47.9 0.8 0.0 0.0 51.3 100.0 386 Total 28.8 1.0 4.7 0.1 65.4 100.0 2,650 Maternal Health Care • 135 9.9 PROBLEMS IN ACCESSING HEALTH CARE Many factors can prevent women from accessing medical advice or treatment for themselves when they are sick. Information on such factors is particularly important in understanding and addressing the barriers women may face when seeking care during pregnancy, delivery, and the postnatal period. In the 2013 LDHS, women were asked whether each of the following factors would be an impediment (or not) in seeking medical care: getting permission to go for treatment, getting money for treatment, distance to a health facility, and not wanting to go alone. Table 9.11 shows that 62 percent of women reported at least one of these concerns as a hindrance when it came to accessing health care. The most common factor impeding women from accessing health care for themselves is getting money to pay for treatment; 47 percent of the women highlighted this concern. Distance to a health facility was cited by four in ten women as a big problem in accessing health care (40 percent). As expected, women residing in rural areas were more likely than those in urban areas to report distance as a big problem (63 percent compared with 26 percent). Eight percent of women reported getting permission to go and 25 percent reported not wanting to go alone as big problems in accessing health care. The percentage of women who reported each of these factors as big problems in seeking medical care generally decreased with increasing educational attainment and wealth quintile. To accomplish Millennium Development Goal (MDG) 5, intended to improve maternal health, the Ministry of Health and Social Welfare developed the Essential Package of Health Services (EPHS) with defined maternal health interventions at both the community and health facility levels. The EPHS is an assortment of health services that the Ministry is committed to providing at every health facility. Health interventions undertaken to improve maternal health in Liberia include prenatal care, delivery, postnatal services, intermittent preventive treatment of malaria during pregnancy, family planning, and tetanus toxoid immunization. Other support interventions include the construction of maternal waiting homes to facilitate institutional and skilled delivery, procurement of ambulances for referrals, and provision of insecticide-treated nets and a “mama and baby kit” to stimulate institutional delivery and prenatal care visits. The mama and baby starter kit is a package of assorted items such as a baby towel, soap, baby powder, and blanket provided to mothers upon delivery to encourage institutional delivery. 136 • Maternal Health Care Table 9.11 Problems in accessing health care Percentage of women age 15-49 who reported that they have serious problems in accessing health care for themselves when they are sick, by type of problem, according to background characteristics, Liberia 2013 Background characteristic Problems in accessing health care Getting permission to go for treatment Getting money for treatment Distance to health facility Not wanting to go alone At least one problem accessing health care Number of women Age 15-19 8.6 45.6 33.8 23.7 58.0 2,080 20-34 7.8 47.3 40.9 25.1 63.2 4,452 35-49 7.3 47.3 43.7 24.0 64.3 2,707 Number of living children 0 7.7 42.0 30.3 21.9 54.2 2,185 1-2 7.8 49.0 37.7 22.6 62.4 3,294 3-4 8.5 46.4 44.5 25.7 64.2 2,084 5+ 7.1 49.9 52.3 29.8 70.4 1,676 Marital status Never married 8.0 44.9 30.6 21.1 57.1 2,867 Married or living together 7.6 47.4 45.2 26.6 64.8 5,386 Divorced/separated/widowed 8.6 50.2 40.1 22.4 64.1 987 Employed past 12 months Not employed 8.5 46.9 35.3 20.4 60.2 3,944 Employed for cash 6.0 47.8 39.4 25.1 62.9 3,564 Employed not for cash 10.1 45.1 52.5 32.4 66.1 1,721 Residence Urban 6.9 45.7 25.5 16.3 54.8 5,633 Greater Monrovia 4.9 44.5 17.6 11.9 49.9 3,361 Other urban 9.9 47.6 37.1 22.9 61.9 2,272 Rural 9.2 48.7 63.0 37.1 74.2 3,606 Region North Western 8.3 40.8 57.1 34.2 67.5 837 South Central 6.1 44.2 25.5 16.0 53.4 4,854 South Eastern A 8.0 33.7 50.9 29.7 62.2 483 South Eastern B 10.2 47.2 49.1 34.1 68.4 577 North Central 10.5 56.7 58.8 34.3 76.6 2,488 County Bomi 5.5 47.8 51.9 20.4 64.2 244 Bong 5.7 51.3 59.9 37.9 73.6 894 Gbarpolu 8.4 33.9 45.6 24.4 54.8 182 Grand Bassa 6.3 52.6 60.2 44.1 73.0 434 Grand Cape Mount 10.0 39.7 65.4 46.7 75.0 412 Grand Gedeh 7.3 37.3 49.2 28.4 59.2 167 Grand Kru 8.2 52.1 50.6 35.9 70.1 217 Lofa 6.3 57.1 66.5 18.6 80.0 447 Margibi 13.4 42.4 38.1 17.7 59.3 744 Maryland 11.8 47.0 43.2 32.4 66.3 257 Montserrado 4.6 43.6 18.8 12.4 49.9 3,675 Nimba 15.9 60.7 55.0 37.6 77.7 1,147 River Cess 5.8 30.0 73.7 51.0 78.7 135 River Gee 10.3 37.7 60.3 34.6 70.3 103 Sinoe 10.2 33.2 35.6 15.3 52.7 182 Education No education 8.0 50.6 56.3 34.3 71.9 3,066 Primary 9.3 49.7 41.7 26.4 65.4 2,875 Secondary and higher 6.4 41.1 23.7 13.6 50.8 3,298 Wealth quintile Lowest 8.6 54.4 75.3 46.4 83.7 1,581 Second 9.6 49.3 59.0 34.4 70.7 1,624 Middle 9.3 49.9 44.1 24.9 66.0 1,779 Fourth 7.3 50.5 21.8 15.6 57.3 2,047 Highest 5.3 34.0 14.8 9.2 42.6 2,207 Total 7.8 46.9 40.1 24.5 62.3 9,239 Note: Total includes 9 cases for which information on employment status in past 12 months is missing. Child Health • 137 CHILD HEALTH 10 his chapter presents findings about child health and survival, including characteristics of the neonate (birth weight and size), the vaccination status of young children, and treatment practices—particularly contact with health services—among children suffering from three childhood illnesses: acute respiratory infection (ARI), fever, and diarrhea. Because appropriate sanitary practices can help prevent and reduce the severity of diarrheal disease, information is also provided on how children’s fecal matter is disposed of. These results from the 2013 LDHS are expected to assist policymakers and program managers as they formulate appropriate strategies and interventions to improve the health of children in Liberia. In particular, the results will be used to assess coverage of current strategies such as Integrated Management of Childhood Illness (IMCI), which seeks to prevent deaths from pneumonia, malaria, and diarrhea, and to plan for improvements in these initiatives. 10.1 CHILD’S WEIGHT AND SIZE AT BIRTH Birth weight is an important indicator when assessing a child’s health in terms of early exposure to childhood morbidity and mortality. Children who weigh less than 2.5 kilograms, or are reported to be “very small” or “smaller than average,” are considered to have a higher-than-average risk of early childhood death. In the 2013 LDHS, for births in the five years preceding the survey, birth weight was recorded in the Woman’s Questionnaire based on either a written record or the mother’s report. The mother’s estimate of the infant’s size at birth was also obtained because birth weight may be unknown for many infants. Although the mother’s estimate of size is subjective, it can be a useful proxy for the child’s weight. T Key Findings • By mothers’ estimates, 20 percent of all infants born alive in the five years preceding the survey were very small or smaller than average at birth. Among infants with a birth weight, 10 percent weighed less than 2.5 kg. • Fifty-five percent of children ages12-23 months were fully vaccinated at the time of the survey; 48 percent of this age group had received all basic vaccinations by age 12 months. • Seven percent of children under 5 experienced symptoms of an acute respiratory infection (ARI) in the two weeks preceding the survey. Among those with symptoms, advice or treatment from a health facility or provider was sought for half (51 percent), and slightly more than half (56 percent) received antibiotics. • Twenty-nine percent of children under 5 had a fever within the two weeks preceding the survey. Among those with a fever, 58 percent were taken to a health facility or provider for advice or treatment, 56 percent received antimalarial drugs, and 39 percent received antibiotics. • Twenty-two percent of children under 5 had diarrhea in the two weeks preceding the survey. Nearly one-half of the children with diarrhea (47 percent) were taken to a health facility or provider. Three in four (76 percent) of the children with diarrhea were treated with oral rehydration therapy (ORT) or increased fluids. Eight percent of children with diarrhea did not receive any type of treatment. 138 • Child Health Table 10.1 shows that birth weight is reported for 23 percent of the live births that occurred in the five years preceding the survey; 10 percent of these infants had low birth weights (less than 2.5 kg). Older mothers, age 35-49 (8 percent), are slightly less likely to have infants with low birth weight than mothers age 20-34 (10 percent) and mothers less than age 20 (11 percent). By birth order, women who have had six or more births (6 percent) are less likely than mothers with fewer births (9-12 percent) to have had a low birth weight baby. Birth weights in rural areas are slightly more likely than those in urban areas to be less than 2.5 kg (11 and 9 percent, respectively). There is no clear relationship between low birth weight and mother’s education or wealth quintile. Table 10.1 Child's size and weight at birth Percent distribution of live births in the five years preceding the survey by mother's estimate of baby's size at birth, percentage of live births in the five years preceding the survey that have a reported birth weight, and among live births in the five years preceding the survey with a reported birth weight, percentage less than 2.5 kg, according to background characteristics, Liberia 2013 Background characteristic Percent distribution of all live births by size of child at birth Percentage of all births that have a reported birth weight1 Number of births Births with a reported birth weight1 Very small Smaller than average Average or larger Don't know/ missing Total Percentage less than 2.5 kg Number of births Mother's age at birth <20 9.9 12.0 78.0 0.1 100.0 21.5 1,358 10.5 292 20-34 7.2 11.5 80.8 0.4 100.0 23.4 4,217 9.9 988 35-49 9.0 12.2 78.3 0.5 100.0 24.8 927 7.8 230 Birth order 1 9.3 11.5 79.1 0.1 100.0 27.2 1,612 12.2 438 2-3 7.6 11.1 80.9 0.4 100.0 23.1 2,310 9.3 533 4-5 6.4 12.9 80.0 0.7 100.0 21.8 1,369 9.9 299 6+ 8.9 11.9 78.8 0.3 100.0 19.7 1,211 5.8 239 Residence Urban 7.4 11.3 81.2 0.1 100.0 29.6 3,241 9.1 959 Greater Monrovia 6.1 10.9 83.0 0.0 100.0 35.2 1,621 9.7 571 Other urban 8.7 11.7 79.3 0.2 100.0 24.0 1,620 8.3 388 Rural 8.6 12.2 78.6 0.6 100.0 16.9 3,261 10.7 550 Region North Western 7.6 13.4 78.9 0.1 100.0 16.2 731 8.9 118 South Central 8.1 10.6 81.1 0.2 100.0 29.3 2,668 10.1 783 South Eastern A 10.7 14.0 74.8 0.5 100.0 17.8 492 7.2 88 South Eastern B 10.0 16.6 71.6 1.8 100.0 19.2 529 10.5 102 North Central 6.9 10.8 81.9 0.3 100.0 20.1 2,082 9.5 419 County Bomi 3.6 10.9 85.5 0.0 100.0 25.5 177 13.8 45 Bong 8.2 10.6 80.6 0.5 100.0 9.1 792 6.3 72 Gbarpolu 11.6 16.3 71.8 0.3 100.0 19.9 161 6.3 32 Grand Bassa 13.3 13.3 73.3 0.1 100.0 12.1 366 (14.2) 44 Grand Cape Mount 7.8 13.4 78.8 0.0 100.0 10.4 392 5.4 41 Grand Gedeh 10.1 10.9 77.6 1.4 100.0 32.8 157 7.5 51 Grand Kru 10.7 18.6 67.2 3.4 100.0 10.6 235 9.6 25 Lofa 7.1 8.1 84.2 0.5 100.0 46.3 342 12.2 158 Margibi 11.3 7.0 80.8 0.8 100.0 20.7 478 9.1 99 Maryland 10.8 16.2 72.7 0.3 100.0 27.1 196 9.0 53 Montserrado 6.3 10.9 82.8 0.0 100.0 35.1 1,824 10.0 640 Nimba 5.7 12.0 82.2 0.1 100.0 19.9 949 8.4 189 River Cess 12.8 9.4 77.8 0.0 100.0 16.7 147 8.7 25 River Gee 6.7 12.6 80.0 0.7 100.0 24.1 97 14.8 23 Sinoe 9.6 20.0 70.2 0.2 100.0 6.2 189 (2.7) 12 Mother's education No education 9.3 11.9 78.2 0.6 100.0 16.8 2,713 9.1 457 Primary 8.1 11.5 80.1 0.3 100.0 22.3 1,983 10.6 442 Secondary and higher 6.0 11.6 82.2 0.2 100.0 33.8 1,807 9.6 611 Wealth quintile Lowest 11.2 12.1 75.8 0.9 100.0 13.1 1,580 10.8 207 Second 6.7 11.0 82.0 0.3 100.0 18.9 1,452 11.7 275 Middle 8.5 12.8 78.5 0.2 100.0 24.7 1,367 7.7 338 Fourth 6.3 11.6 82.1 0.1 100.0 28.2 1,234 12.0 347 Highest 6.2 10.8 82.8 0.2 100.0 39.3 870 7.0 342 Total 8.0 11.7 79.9 0.4 100.0 23.2 6,502 9.7 1,509 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Based on either a written record or the mother's recall Child Health • 139 Table 10.1 also includes information on a mother’s estimate of her infant’s size at birth. Eight percent of births are reported as very small, 12 percent as smaller than average, and 80 percent as average or larger than average. Mothers with at least some secondary education report having had fewer very small babies than mothers with no education (6 percent and 9 percent, respectively). Mothers in the highest and fourth wealth quintiles report having had fewer very small babies than mothers in the lowest wealth quintile (6 percent, 6 percent, and 11 percent, respectively). 10.2 VACCINATION OF CHILDREN The induction of an immune response through vaccination is a widely accepted public health strategy for the prevention of vaccine-preventable infectious diseases. To enable evaluation of the Liberia Expanded Program of Immunization (LEPI), the 2013 LDHS collected information on vaccine coverage for all children born since January 2008. To be fully vaccinated, a child should have received one dose of BCG vaccine, three doses each of DPT and polio vaccines, and one dose of measles vaccine. BCG protects against tuberculosis, and DPT protects against diphtheria, pertussis (whooping cough), and tetanus. Since 2008, DPT has not been given to infants in Liberia as a stand-alone vaccine. Instead, it has been combined with other antigens that protect against hepatitis B and Haemophilus influenza type b (DPT-HB-Hib vaccine, also known as pentavalent vaccine). Thus, the 2013 LDHS report on DPT coverage includes coverage by DPT or pentavalent vaccines. Liberia has defined a schedule for the administration of all basic childhood vaccines. BCG should be given shortly after birth. DPT/pentavalent and polio vaccines require three vaccinations to be given at approximately age 3, 4, and 5 months, and measles vaccine should be given at or soon after reaching age 9 months. In addition, although not defined as a basic childhood vaccine, Liberian children should receive a yellow fever vaccine at age 9 months. Sources of Information In the survey, information on vaccination coverage was obtained in two ways – from child health cards and from mothers’ verbal reports. All mothers were asked to show the interviewer the child health cards in which immunization dates were recorded for all children born since January 2008. If a card was available, the interviewer recorded onto the questionnaire the dates of each vaccination received by the child. If a card indicated that the child was not fully vaccinated, the mother was then asked whether the child had received other vaccinations that were not recorded on the card, and they too were noted on the questionnaire. If a child never received a health card or if the mother was unable to show the card to the interviewer, the vaccination information for the child was based on the mother’s report. Questions were asked for each vaccine type. Mothers were asked to recall whether the child had received BCG, polio, DPT/pentavalent, measles, and yellow fever vaccinations. If the mother indicated that the child had received the polio or DPT/pentavalent vaccines, she was asked about the number of doses that the child received. The results presented here are based on both health card information and, for children without a card, information provided by the mother. Vaccination Coverage Table 10.2 shows vaccination coverage by source of information for children age 12-23 months, the age by which they should have received all vaccinations. Fifty-eight percent of mothers showed children’s vaccination cards to interviewers, while the remainder provided a self-report of children’s vaccination histories. Overall, 55 percent of children ages 12-23 months were fully vaccinated at the time of the survey. Ninety-four percent had received the BCG vaccination at any time before the survey. For DPT/pentavalent vaccine, 91 percent had received the first dose, 82 percent had received the second dose, and 71 percent had 140 • Child Health received the third dose. For polio vaccine, 96 percent had received the first dose, 87 percent had received the second dose, and 70 percent had received the third dose. Coverage for measles and yellow fever vaccines was 74 percent and 73 percent, respectively. Only 2 percent of children age 12-23 months had not received any vaccinations, compared with 12 percent in the 2007 LDHS. Table 10.2 Vaccinations by source of information Percentage of children age 12-23 months who received specific vaccines at any time before the survey, by source of information (vaccination card or mother's report), and percentage vaccinated 12 months of age, Liberia 2013 Source of information BCG DPT/ penta- valent 1 DPT/ penta- valent 2 DPT/ penta- valent 3 Polio 01 Polio 1 Polio 2 Polio 3 Measles Yellow Fever All basic vaccina- tions2 No vaccina- tions Number of children Vaccinated at any time before survey Vaccination card 57.5 56.9 53.2 49.9 53.3 57.5 53.5 50.7 44.5 43.4 43.0 0.0 743 Mother's report 36.4 34.4 28.9 21.5 27.1 38.4 33.2 19.2 29.7 29.4 11.8 1.5 529 Either source 93.9 91.3 82.1 71.4 80.4 95.9 86.7 69.9 74.2 72.8 54.8 1.5 1,272 Vaccinated by 12 months of age3 93.3 90.6 81.2 68.0 79.9 95.1 85.7 66.7 64.7 63.4 48.1 2.0 1,272 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles, and three doses each of DPT or pentavalent vaccine and polio vaccine (excluding polio vaccine given at birth and yellow fever vaccine) 3 For children whose information is based on the mother’s report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccination. Table 10.2 also shows vaccination coverage by age 12 months. The rates for each vaccination by the time the child reaches age 12 months is a measure of children that receive vaccines on time. Overall, 48 percent of children are fully immunized by 12 months, compared with 34 percent in the 2007 LDHS. Table 10.3 presents information on vaccine coverage among children age 12-23 months from vaccination cards and mothers’ reports, by background characteristics. Female children were slightly more likely to be fully immunized than male children (57 percent and 53 percent, respectively). Children in urban areas are more likely than rural children to have received all basic vaccinations (60 percent compared with 49 percent, respectively). At the regional level, full vaccination coverage ranges from a high of 68 percent in North Western, to a low of 38 percent in South Eastern A. Similarly, basic vaccination coverage varied widely at the county level; although 74 percent of children in Grand Cape Mount had received all basic vaccinations, only 33 percent of children in River Cess had basic vaccination coverage. The percentage of children who received no vaccinations also varies markedly at the county level: from 0 percent in Gbarpolu, Grand Cape Mount, Lofa, and Montserrado, to 10 percent in River Gee. A mother’s level of education relates to vaccination coverage; 66 percent of children whose mothers have at least some secondary education are fully vaccinated, compared with 48-51 percent of children whose mothers have only primary education or no education. Children in the highest wealth quintile are more likely to be fully vaccinated than those in the lowest (70 percent and 44 percent, respectively). Child Health • 141 Table 10.3 Vaccinations by background characteristics Percentage of children age 12-23 months who received specific vaccines at any time before the survey (according to a vaccination card or the mother's report), and percentage with a vaccination card, by background characteristics, Liberia 2013 Background characteristic BCG DPT/ penta- valent 1 DPT/ penta- valent 2 DPT/ penta- valent 3 Polio 01 Polio 1 Polio 2 Polio 3 Measles Yellow Fever All basic vaccina- tions2 No vaccina- tions Percen- tage with a vaccina- tion card seen Number of children Sex Male 93.1 90.1 82.9 69.2 79.2 94.9 85.9 68.8 73.8 72.4 52.9 2.2 55.6 658 Female 94.7 92.7 81.2 73.8 81.7 96.9 87.5 71.1 74.6 73.2 56.8 0.8 61.3 614 Birth order 1 97.6 95.0 89.4 79.9 85.8 97.7 90.9 75.6 82.8 81.8 64.0 0.8 58.3 309 2-3 95.7 93.3 81.2 71.9 84.5 96.0 84.8 67.8 73.1 71.9 52.0 1.2 57.9 484 4-5 90.8 88.7 79.1 65.8 75.0 95.6 87.2 69.0 70.8 69.8 50.2 2.7 56.7 263 6+ 88.2 84.9 77.1 65.1 69.8 93.2 84.2 67.6 68.4 65.3 53.6 2.0 61.6 216 Residence Urban 96.7 94.8 85.6 75.7 85.3 97.8 88.5 71.4 77.6 76.7 59.7 0.8 56.3 675 Greater Monrovia 100.0 98.8 86.2 80.0 89.0 99.3 87.8 71.5 78.8 78.6 60.2 0.0 51.1 337 Other urban 93.4 90.9 85.1 71.3 81.6 96.3 89.2 71.4 76.3 74.9 59.1 1.7 61.6 338 Rural 90.7 87.4 78.1 66.6 74.9 93.7 84.6 68.2 70.4 68.3 49.4 2.3 60.7 597 Region North Western 94.5 93.5 89.5 81.5 85.5 99.6 94.7 84.4 81.5 78.4 68.3 0.4 74.4 135 South Central 97.9 95.0 83.6 76.8 83.4 97.2 86.9 71.1 77.2 76.5 58.1 0.6 52.3 543 South Eastern A 89.4 88.0 77.9 58.6 72.4 93.9 83.6 60.0 66.7 67.3 37.6 2.8 49.6 85 South Eastern B 78.9 74.9 59.7 52.0 64.0 88.3 75.4 56.7 60.0 57.5 39.7 6.7 45.7 92 North Central 92.6 90.2 83.5 68.1 80.0 95.0 86.9 68.6 72.6 70.6 53.0 1.7 65.8 417 County Bomi 98.4 98.4 98.4 90.6 93.9 98.4 96.5 84.5 85.3 83.5 72.7 1.6 63.4 31 Bong 88.9 84.9 72.9 62.1 77.0 90.0 80.0 67.2 68.6 64.5 50.4 3.2 65.3 158 Gbarpolu 86.0 86.7 74.5 62.9 67.7 100.0 91.7 75.9 74.2 71.5 52.2 0.0 63.1 32 Grand Bassa 91.7 80.8 57.9 53.2 63.2 92.5 74.8 58.5 66.4 59.7 38.9 2.0 45.6 64 Grand Cape Mount 96.5 94.4 92.3 85.8 89.8 100.0 95.2 88.1 83.1 79.3 73.6 0.0 84.3 71 Grand Gedeh 92.4 93.4 87.1 62.0 85.7 96.4 85.8 61.2 79.0 81.3 44.0 2.1 44.8 26 Grand Kru 74.8 69.0 47.5 42.2 60.4 84.0 65.6 49.1 56.4 52.4 37.5 8.4 37.2 35 Lofa 98.9 96.4 94.6 80.9 92.9 98.5 92.1 77.1 80.0 77.2 63.7 0.0 76.0 67 Margibi 94.8 92.2 88.4 79.3 78.8 94.3 91.3 75.4 76.8 79.5 60.0 2.0 52.4 98 Maryland 83.5 79.0 66.5 58.4 62.8 92.8 81.2 62.2 62.7 59.8 40.3 3.7 46.4 40 Montserrado 99.8 98.1 86.7 80.1 88.0 98.8 87.8 72.2 79.1 78.5 60.9 0.0 53.3 380 Nimba 93.4 92.5 88.4 68.5 77.9 97.9 90.9 66.8 73.3 73.3 51.5 1.1 62.6 192 River Cess 92.4 95.2 80.9 60.6 70.7 98.6 91.7 64.9 57.4 58.0 33.1 1.0 60.2 27 River Gee 76.7 77.3 68.2 56.7 73.8 86.8 81.6 59.5 60.8 62.4 42.5 10.2 60.7 18 Sinoe 84.7 77.6 68.1 54.1 63.2 88.0 75.2 55.1 64.5 63.9 36.3 4.9 44.5 32 Mother's education No education 89.5 88.0 77.9 67.9 73.7 93.0 83.3 69.8 66.6 65.3 51.2 2.8 60.9 470 Primary 94.2 89.8 77.6 65.5 79.0 96.6 85.5 63.8 71.1 68.1 47.6 1.4 56.3 403 Secondary and higher 98.7 96.8 91.6 81.5 89.6 98.5 91.8 76.2 86.1 86.2 66.3 0.2 57.5 399 Wealth quintile Lowest 86.8 84.0 72.1 57.9 71.3 91.6 82.8 64.7 65.0 63.6 44.0 3.5 56.7 299 Second 92.6 89.7 81.5 71.7 74.7 96.1 86.2 74.4 74.1 71.1 56.6 1.6 68.3 268 Middle 95.9 93.4 87.4 73.6 80.7 96.0 87.9 71.1 73.0 71.2 53.6 1.9 61.2 240 Fourth 97.5 95.9 87.9 78.3 88.1 98.2 87.9 66.4 78.1 77.7 55.2 0.2 50.0 263 Highest 98.9 96.1 83.8 79.4 90.8 98.7 90.0 74.9 84.1 84.0 69.6 0.0 55.4 203 Total 93.9 91.3 82.1 71.4 80.4 95.9 86.7 69.9 74.2 72.8 54.8 1.5 58.4 1,272 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles, and three doses each of DPT/pentavalent and polio vaccine (excluding polio vaccine given at birth and yellow fever vaccine) Trends in Vaccination Coverage Figure 10.1 compares vaccination coverage from the 2007 and 2013 LDHS surveys for the first year of life among children age 12-23 months. Encouragingly, there has been marked improvement in vaccination coverage between the two surveys. Although only 34 percent of children ages 12-23 months were fully 142 • Child Health vaccinated by age 12 months in 2007, 48 percent were fully vaccinated in 2013. Between the 2007 and 2013 LDHS, vaccine coverage by age 12 months improved for BCG (from 77 percent to 93 percent), for three doses of DPT (from 47 percent to 68 percent), for three doses of polio (from 47 percent to 67 percent), and for measles (from 53 percent to 65 percent). Figure 10.1 Trends in vaccination coverage during the first year of life among children 12-23 months 34 77 75 63 47 57 82 69 47 53 13 48 93 91 81 68 80 95 86 67 65 2 All BCG DPT1 DPT2 DPT3 Polio 0 Polio 1 Polio 2 Polio 3 Measles None Percentage of children with specific vaccines 2007 LDHS 2013 LDHS Table 10.4 shows the percentage of children age 12-59 months who received specific vaccinations during the first year of life, according to age cohort. The data indicate that the proportion of children fully vaccinated by age 12 months has increased over the last several years from 32 percent of children 48-59 months to 48 percent 12-23 months. Thus, these data agree with the increase in coverage shown in Figure 10.1. Table 10.4 Vaccinations in first year of life Percentage of children age 12-59 months at the time of the survey who received specific vaccines by 12 months of age, and percentage with a vaccination card, by current age of child, Liberia 2013 Age in months BCG DPT/ penta- valent 1 DPT/ penta- valent 2 DPT/ penta- valent 3 Polio 01 Polio 1 Polio 2 Polio 3 Measles Yellow Fever All basic vaccina- tions2 No vaccina- tions Percentage with a vaccina- tion card seen Number of children 12-23 93.3 90.6 81.2 68.0 79.9 95.1 85.7 66.7 64.7 63.4 48.1 2.0 58.4 1,272 24-35 88.4 87.4 80.4 64.0 73.0 91.7 83.8 64.3 61.0 59.5 42.2 5.9 41.5 1,085 36-47 87.1 83.4 74.8 57.6 67.3 85.3 76.5 54.7 60.8 61.4 33.6 7.5 32.0 1,198 48-59 88.1 81.3 74.1 55.9 64.5 85.9 77.8 54.6 53.9 50.7 31.6 8.4 23.8 1,159 Total 89.7 86.2 78.2 61.8 71.6 90.1 81.5 60.5 61.6 60.4 39.6 5.5 39.3 4,714 Note: Information was obtained from the vaccination card or if there was no written record, from the mother. For children whose information is based on the mother's report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccinations. 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles, and three doses each of DPT/pentavalent and polio vaccine (excluding polio vaccine given at birth and yellow fever vaccine) Child Health • 143 10.3 PREVALENCE AND TREATMENT OF ACUTE RESPIRATORY INFECTION Acute respiratory infection (ARI) is among the leading causes of childhood morbidity and mortality throughout the world. Among acute respiratory diseases, pneumonia is the most serious for young children. Early diagnosis and treatment with antibiotics can prevent a large number of deaths caused by ARIs. In the 2013 LDHS, ARI prevalence was estimated by asking mothers whether their children under 5 had been ill with a cough accompanied by short, rapid breathing, which was chest-related, and/or by difficult breathing, which was chest- related, in the two weeks preceding the survey. It should be noted that these data collected are subjective in the sense that they are based on the mother’s perception of illness without validation by medical personnel. Table 10.5 shows the prevalence of ARI symptoms among children under 5 during the two-week period preceding the interview and the actions that mothers took in response to their children’s illness. Overall, 7 percent of children are reported to have had ARI symptoms in the two weeks preceding the survey. Mothers who reported that their children had had ARI symptoms were asked about the actions they had taken to treat the illness. Among children with ARI symptoms, advice or treatment was sought from a health facility or a health provider for 51 percent, and 56 percent received antibiotics. Differences are observed by background characteristics. Among the most striking finding is that whereas the percentages of male and female children that had symptoms of ARI was nearly identical (7 percent and 6 percent, respectively), as was the percentage of males and females with symptoms of ARI who received antibiotics (56 percent and 57 percent, respectively), male children were much more likely than female children to have had advice or treatment sought from a health facility or provider (57 percent and 44 percent, respectively). 144 • Child Health Table 10.5 Prevalence and treatment of symptoms of ARI Among children under 5, the percentage who had symptoms of acute respiratory infection (ARI) in the two weeks preceding the survey and among children with symptoms of ARI, the percentage for whom advice or treatment was sought from a health facility or provider and the percentage who received antibiotics as treatment, according to background characteristics, Liberia 2013 Background characteristic Among children under 5: Among children under 5 with symptoms of ARI: Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought from a health facility or provider2 Percentage who received antibiotics Number of children Age in months <6 5.6 603 (76.0) (75.9) 34 6-11 10.4 730 54.2 61.7 76 12-23 8.2 1,272 50.9 60.5 104 24-35 5.6 1,085 46.5 45.2 61 36-47 5.4 1,198 53.0 46.9 65 48-59 4.8 1,159 32.2 52.4 56 Sex Male 6.8 3,089 56.5 55.5 211 Female 6.2 2,957 44.0 57.2 184 Cooking fuel Electricity * 1 nc nc 0 Firecoal/charcoal 6.6 2,229 50.2 67.0 148 Wood 6.5 3,814 51.0 50.0 248 No food cooked in household * 2 nc nc 0 Residence Urban 5.4 3,013 49.4 62.3 164 Greater Monrovia 6.0 1,503 (38.2) (71.1) 91 Other Urban 4.8 1,510 63.2 51.4 73 Rural 7.6 3,034 51.7 52.1 232 Region North Western 7.6 663 53.0 69.8 50 South Central 6.6 2,485 47.8 64.6 165 South Eastern A 9.8 463 55.5 44.7 45 South Eastern B 8.9 466 52.6 35.9 42 North Central 4.7 1,970 51.4 49.0 93 County Bomi 5.7 160 * * 9 Bong 6.7 739 (58.2) (57.8) 50 Gbarpolu 6.0 149 (30.0) (42.2) 9 Grand Bassa 5.6 345 * * 19 Grand Cape Mount 9.1 355 (56.0) (71.9) 32 Grand Gedeh 7.4 146 (69.4) (43.9) 11 Grand Kru 11.5 203 (41.6) (30.4) 23 Lofa 4.2 323 * * 14 Margibi 8.7 448 (49.6) (57.5) 39 Maryland 5.2 175 * * 9 Montserrado 6.3 1,692 (46.5) (73.4) 107 Nimba 3.3 908 (38.7) (34.5) 30 River Cess 12.2 139 58.0 50.3 17 River Gee 10.4 88 (73.2) (52.3) 9 Sinoe 9.8 178 (44.5) (39.9) 17 Mother's education No education 6.9 2,508 46.6 53.4 172 Primary 6.5 1,846 53.8 53.8 120 Secondary and higher 6.1 1,693 53.9 64.2 103 Wealth quintile Lowest 7.8 1,469 48.3 37.0 115 Second 6.6 1,350 56.4 60.8 89 Middle 5.2 1,268 59.7 55.0 66 Fourth 5.7 1,132 (44.3) (58.4) 64 Highest 7.3 828 (44.0) (85.4) 61 Total 6.5 6,047 50.7 56.3 396 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Total includes 1 case for which information on type of cooking fuel used in household is missing. nc = no cases 1 Symptoms of ARI (cough accompanied by short, rapid breathing which was chest-related and/or by difficult breathing which was chest-related) is considered a proxy for pneumonia 2 Excludes pharmacy, shop, traditional practitioner, and black bagger/drug peddler Child Health • 145 10.4 PREVALENCE AND TREATMENT OF FEVER Fever is a symptom of malaria, but it may also accompany other illnesses including pneumonia, common colds, and influenza. Because malaria is a major cause of death in infancy and childhood in many developing countries, prior to 2010 the presumptive treatment of fever with antimalarial medication was advocated in many countries where malaria is endemic (WHO, 2010a). In Liberia, ideally all suspected malaria cases should be confirmed diagnostically before treatment; however, when parasitological diagnosis is not accessible, treatment may be based on clinical diagnosis (NMCP 2011 and PMI, 2013). Information relating to the prevention and treatment of malaria is discussed in detail in Chapter 12. In the 2013 LDHS, fever prevalence was estimated by asking mothers whether their children under 5 had been ill with fever in the two weeks preceding the survey. For children with fever, mothers were also asked about the actions they took to treat fever, including whether or not the child had been given any drug to treat the fever, and, if so, what drug the child was given. Table 10.6 shows that the percentage of children under 5 with fever during the two weeks preceding the survey was 29 percent. The prevalence of fever varies with children’s ages. Children age 6-11 months are more likely to be sick with fever (38 percent) than children in other age groups. Children in urban areas are slightly less likely than those in rural areas (26 percent and 31 percent, respectively) to have had fever. Among counties, 41 percent of children in River Gee had fever in the two weeks preceding the survey compared with 20 percent of children in Lofa. Advice or treatment was sought from a health facility or provider for 58 percent of the children with fever. Children with fever were more likely to have received an antimalarial drug than an antibiotic drug during the episode of the fever (56 percent versus 39 percent, respectively). Advice or treatment for fever was nearly as commonly sought for male children and female children (59 and 56 percent, respectively), but was more common for children in urban areas (62 percent) than for children in rural areas (54 percent). The percentages of children who took antimalarial and antibiotic drugs also varied by background characteristics. Most notably, antimalarial use generally increased with age, while antibiotic use generally decreased with age. 146 • Child Health Table 10.6 Prevalence and treatment of fever Among children under 5, the percentage who had a fever in the two weeks preceding the survey; and among children with fever, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage who took antimalarial drugs, and the percentage who received antibiotics as treatment, by background characteristics, Liberia 2013 Background characteristic Among children under 5: Among children under 5 with fever: Percentage with fever Number of children Percentage for whom advice or treatment was sought from a health facility or provider1 Percentage who took antimalarial drugs Percentage who took antibiotic drugs Number of children Age in months <6 18.7 603 67.2 27.9 48.9 113 6-11 38.1 730 58.7 48.2 54.5 278 12-23 33.7 1,272 61.9 60.3 42.1 429 24-35 28.5 1,085 52.0 53.8 33.3 309 36-47 27.3 1,198 56.1 61.8 34.1 327 48-59 23.6 1,159 53.3 62.4 28.6 273 Sex Male 30.4 3,089 58.8 56.9 39.8 938 Female 26.7 2,957 56.0 54.3 38.7 790 Residence Urban 26.3 3,013 61.7 57.3 41.4 793 Greater Monrovia 26.4 1,503 63.4 51.7 47.7 396 Other urban 26.2 1,510 59.9 62.9 35.1 396 Rural 30.8 3,034 54.0 54.4 37.6 935 Region North Western 36.1 663 54.8 63.9 50.7 240 South Central 28.4 2,485 60.6 52.8 44.7 706 South Eastern A 31.1 463 58.7 46.8 29.7 144 South Eastern B 36.7 466 58.3 53.2 32.6 171 North Central 23.7 1,970 53.7 59.5 30.8 467 County Bomi 30.9 160 68.1 71.2 61.6 49 Bong 28.1 739 57.1 57.4 38.0 208 Gbarpolu 40.2 149 49.8 55.7 21.1 60 Grand Bassa 35.1 345 45.5 43.1 22.9 121 Grand Cape Mount 36.8 355 52.1 64.9 60.2 131 Grand Gedeh 28.7 146 62.8 49.8 40.7 42 Grand Kru 33.7 203 49.1 47.2 23.3 68 Lofa 20.3 323 59.6 52.8 33.5 65 Margibi 22.8 448 56.4 62.1 48.5 102 Maryland 37.9 175 60.4 52.5 37.2 66 Montserrado 28.5 1,692 65.3 53.3 49.4 483 Nimba 21.4 908 48.1 64.2 22.2 194 River Cess 31.9 139 49.0 41.8 28.6 44 River Gee 41.3 88 71.6 65.8 41.7 36 Sinoe 32.4 178 63.2 48.5 22.5 58 Mother's education No education 26.7 2,508 56.5 53.2 35.9 670 Primary 29.2 1,846 54.2 58.2 41.2 540 Secondary and higher 30.6 1,693 62.3 56.4 41.8 518 Wealth quintile Lowest 31.4 1,469 50.6 51.8 33.3 460 Second 29.4 1,350 57.2 59.1 33.9 397 Middle 27.2 1,268 60.9 56.0 39.1 345 Fourth 27.0 1,132 61.2 55.6 47.0 306 Highest 26.6 828 62.2 57.5 51.4 220 Total 28.6 6,047 57.5 55.7 39.3 1,728 1 Excludes pharmacy, shop, traditional practitioner, and black bagger/drug peddler Child Health • 147 10.5 DIARRHEAL DISEASE Dehydration caused by severe diarrhea is a major cause of morbidity and mortality among young children. Exposure to diarrhea-causing agents frequently relates to the use of contaminated water and to unhygienic practices in food preparation and disposal of excreta. The 2013 LDHS obtained information on the prevalence of diarrhea among young children by asking mothers whether their children under 5 had had diarrhea during the two weeks preceding the survey. When a child was identified as having had diarrhea, information was collected on treatment and feeding practices during the diarrheal episode. The mother was also asked whether there was blood in the child’s stools. Diarrhea with blood in the stools indicates an infection that needs to be treated differently than diarrhea in which there is no blood in the stools. 10.5.1 Prevalence of Diarrhea Table 10.7 shows that 22 percent of children under 5 had a diarrheal episode in the two weeks preceding the survey and 4 percent had blood in the stool. The prevalence of diarrhea jumped from 10 percent among children less than age 6 months to 29 percent among children age 6-11 months, and peaked at 32 percent among children age 12-23 months. This observation is expected because children age 6 months and older are typically introduced to liquids in addition to breast milk and complementary foods. Diarrhea is somewhat more prevalent among children whose households do not have an improved source of drinking water (26 percent) compared with children from households that do (20 percent). Similarly, the prevalence of diarrhea is slightly higher among children whose households do not have an improved toilet facility (23 percent) or who share a facility with other households (22 percent) compared with households that have an improved, unshared toilet facility (19 percent). Rural children were slightly more likely to have had diarrhea than urban children (24 versus 20 percent, respectively.) The prevalence of diarrhea varies at the county level: it was highest in River Cess and River Gee (32 percent each) and lowest in Bomi and Lofa (12 percent and 14 percent, respectively). 148 • Child Health Table 10.7 Prevalence of diarrhea Percentage of children under 5 who had diarrhea in the two weeks preceding the survey, by background characteristics, Liberia 2013 Background characteristic Diarrhea in the two weeks preceding the survey Number of children All diarrhea Diarrhea with blood Age in months <6 9.8 0.3 603 6-11 28.7 3.0 730 12-23 32.0 5.7 1,272 24-35 24.7 5.5 1,085 36-47 19.3 3.8 1,198 48-59 13.5 3.2 1,159 Sex Male 22.1 3.9 3,089 Female 21.9 4.0 2,957 Source of drinking water1 Improved 20.3 3.3 4,084 Not improved 26.2 5.3 1,844 Toilet facility2 Improved, not shared 18.6 3.7 702 Shared3 21.6 3.3 1,522 Non-improved 22.8 4.2 3,821 Residence Urban 20.1 3.2 3,013 Greater Monrovia 19.5 2.3 1,503 Other urban 20.8 4.1 1,510 Rural 23.8 4.7 3,034 Region North Western 17.1 3.1 663 South Central 21.3 3.1 2,485 South Eastern A 27.5 5.1 463 South Eastern B 27.7 6.9 466 North Central 22.0 4.3 1,970 County Bomi 11.9 1.7 160 Bong 28.5 5.2 739 Gbarpolu 21.6 4.1 149 Grand Bassa 30.0 3.8 345 Grand Cape Mount 17.5 3.4 355 Grand Gedeh 22.2 4.6 146 Grand Kru 27.4 9.1 203 Lofa 13.7 2.6 323 Margibi 20.1 4.1 448 Maryland 25.6 4.2 175 Montserrado 19.8 2.7 1,692 Nimba 19.5 4.3 908 River Cess 32.1 6.5 139 River Gee 32.3 7.0 88 Sinoe 28.2 4.5 178 Mother's education No education 21.5 4.2 2,508 Primary 23.2 4.1 1,846 Secondary and higher 21.4 3.5 1,693 Wealth quintile Lowest 25.2 4.5 1,469 Second 22.8 5.1 1,350 Middle 19.4 3.9 1,268 Fourth 22.1 3.4 1,132 Highest 18.9 2.1 828 Total 22.0 3.9 6,047 Note: Total includes 119 cases for which information on source of drinking water is other/missing and 2 cases for which information on toilet facility type is missing. 1 See Table 2.1 for definition of categories 2 See Table 2.2 for definition of categories 3 Facilities that would be considered improved if they were not shared by two or more households Child Health • 149 10.5.2 Treatment of Diarrhea A simple and effective response to dehydration caused by diarrhea is oral rehydration therapy (ORT). Oral rehydration salt (ORS) packets are one source of rehydration therapy available in Liberia. Table 10.8 shows that advice or treatment was sought from a health facility or provider for 47 percent of children suffering from diarrhea. Advice and treatment were sought more often for children with bloody diarrhea than for those with non-bloody diarrhea (60 and 44 percent, respectively). Some form of ORT, either fluid from ORS packets or recommended home fluids (RHF), was used to treat the diarrhea in the majority of children (62 percent). Three percent of children suffering from diarrhea in the two weeks preceding the survey were given RHF, and 60 percent were given fluid from ORS packets. Thirty-nine percent of the children were given increased amounts of other fluids. Three out of four children (76 percent) were given either ORT or increased fluids. Other treatments given to children with diarrhea were principally antibiotics (13 percent) and anti-motility drugs (55 percent). Home remedies were used to treat 23 percent of children. Eight percent of children with diarrhea did not receive any treatment. 150 • Child Health Table 10.8 Diarrhea treatment Among children under 5 who had diarrhea in the two weeks preceding the survey, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage given oral rehydration therapy (ORT), the percentage given increased fluids, the percentage given ORT or increased fluids, and the percentage who were given other treatments, by background characteristics, Liberia 2013 Background characteristic Percentage of children with diarrhea for whom advice or treatment was sought from a health facility or provider1 Oral rehydration therapy (ORT) In- creased fluids ORT or in- creased fluids Other treatments Missing No treat- ment Number of children with diarrhea Fluid from ORS packets Recom- mended home fluids (RHF) Either ORS or RHF Antibiotic drugs Anti- motility drugs Zinc supple- ments Intra- venus solution Home remedy/ other Age in months <6 55.2 16.8 1.6 18.1 26.1 40.1 22.1 21.2 0.0 0.0 25.6 0.0 19.3 59 6-11 54.1 59.1 0.7 59.8 40.9 76.1 18.8 51.6 3.2 0.0 28.4 0.4 4.2 209 12-23 45.5 62.3 1.9 62.8 38.7 79.3 13.4 53.8 4.3 0.2 23.6 1.1 9.6 407 24-35 43.4 63.7 4.7 65.8 39.8 75.3 9.8 59.0 4.4 0.0 24.1 0.0 7.3 267 36-47 46.7 60.8 5.0 62.9 36.9 75.1 11.7 60.9 2.3 0.0 13.5 0.4 8.6 231 48-59 43.5 67.7 3.0 68.3 47.4 79.2 8.7 63.2 0.0 0.0 23.4 2.9 4.5 157 Sex Male 47.0 58.2 3.3 59.6 39.9 74.4 12.9 58.1 3.6 0.0 21.6 0.7 7.6 682 Female 46.7 62.8 2.6 63.7 38.9 76.7 13.2 52.5 2.6 0.1 23.9 1.0 8.3 648 Type of diarrhea Non-bloody 43.7 56.6 2.8 58.0 39.0 73.3 11.8 53.7 2.8 0.0 21.6 0.9 8.8 1,034 Bloody 60.1 74.9 3.7 75.6 42.7 84.8 18.4 60.6 3.3 0.3 24.0 0.0 3.7 239 Missing 48.8 68.2 1.7 68.2 32.7 75.9 12.8 64.0 7.3 0.0 37.4 1.9 10.5 58 Residence Urban 47.7 57.2 1.4 57.9 37.5 73.0 16.2 58.6 2.3 0.0 18.6 1.4 7.1 607 Greater Monrovia 48.1 51.1 0.0 51.1 33.6 69.3 18.5 56.8 2.1 0.0 13.0 2.8 7.6 293 Other urban 47.3 62.9 2.7 64.1 41.1 76.5 14.1 60.3 2.6 0.0 23.7 0.0 6.6 314 Rural 46.1 63.1 4.2 64.8 41.0 77.6 10.4 52.7 3.7 0.1 26.2 0.4 8.6 724 Region North Western 50.8 79.6 1.3 80.2 40.3 87.0 7.9 69.3 4.4 0.0 29.4 0.0 2.5 113 South Central 45.3 53.3 1.8 54.4 38.2 71.7 17.7 58.9 2.4 0.0 21.1 1.7 8.5 528 South Eastern A 46.2 54.1 3.4 55.4 44.5 75.0 10.3 46.4 1.8 0.1 18.7 1.2 11.5 127 South Eastern B 55.6 66.7 10.6 69.8 35.7 78.8 9.4 47.5 0.6 0.4 17.6 0.1 10.5 129 North Central 45.3 64.1 2.4 64.9 40.3 76.4 10.7 52.5 4.8 0.1 25.8 0.0 6.9 433 County Bomi (69.4) (69.9) (0.0) (69.9) (37.0) (81.5) (16.3) (84.5) (0.0) (0.0) (22.5) (0.0) (3.7) 19 Bong 42.0 62.1 1.1 62.1 36.1 73.9 13.0 46.2 8.9 0.0 34.9 0.0 7.8 211 Gbarpolu 44.2 70.6 4.5 72.7 44.8 80.5 0.6 59.9 0.6 0.0 34.1 0.0 6.6 32 Grand Bassa 33.5 48.2 5.1 50.4 38.1 72.2 16.9 53.8 0.0 0.0 35.1 0.0 7.8 104 Grand Cape Mount 48.5 87.2 0.0 87.2 39.0 92.1 9.2 69.5 7.6 0.0 29.2 0.0 0.0 62 Grand Gedeh 46.4 55.3 0.0 55.3 30.7 70.0 13.2 43.0 0.0 0.4 9.5 0.0 14.5 32 Grand Kru 52.7 64.9 11.0 65.7 30.0 72.5 10.1 44.0 0.0 0.0 16.2 0.2 10.0 56 Lofa 54.0 73.4 6.4 75.6 35.5 84.3 10.0 56.0 0.0 0.7 13.1 0.0 6.8 44 Margibi 41.5 59.4 2.5 61.9 53.5 74.6 17.0 64.9 4.7 0.0 22.8 0.9 13.6 90 Maryland 55.1 70.4 8.7 73.9 35.8 84.9 6.6 51.9 1.1 0.7 16.0 0.0 11.2 45 Montserrado 50.0 53.2 0.5 53.7 34.1 70.7 18.1 58.8 2.5 0.0 16.2 2.5 7.3 335 Nimba 47.0 64.3 2.9 65.6 46.4 77.3 8.1 59.2 1.0 0.0 18.0 0.0 5.9 177 River Cess 44.9 51.3 1.2 51.9 51.8 73.0 11.1 53.6 5.2 0.0 32.2 2.9 11.2 45 River Gee 62.4 64.2 12.7 71.6 46.9 81.6 12.6 47.3 1.0 0.5 22.8 0.0 10.4 28 Sinoe 47.3 55.9 7.6 58.6 47.0 80.0 7.7 42.3 0.0 0.0 12.5 0.6 9.9 50 Mother's education No education 44.9 59.9 3.6 61.4 40.3 74.0 12.6 53.2 3.9 0.2 26.9 0.4 10.1 539 Primary 44.1 64.5 2.5 65.1 41.4 80.0 11.0 54.9 2.3 0.0 22.2 0.1 6.2 428 Secondary and higher 52.9 56.4 2.5 57.7 35.7 72.4 16.1 59.2 2.9 0.0 17.3 2.3 6.7 363 Wealth quintile Lowest 43.2 56.8 3.1 58.5 39.7 73.5 10.5 45.3 3.7 0.2 26.2 0.7 10.9 370 Second 46.8 66.1 6.0 68.1 41.6 78.6 9.9 58.5 3.5 0.1 27.4 0.0 7.2 307 Middle 53.6 70.4 2.6 71.4 37.4 80.2 11.6 60.3 3.0 0.0 20.1 0.0 4.1 246 Fourth 44.2 59.3 0.9 59.5 39.7 77.5 19.1 58.3 3.1 0.0 18.0 0.0 9.1 251 Highest 49.2 44.1 0.2 44.3 37.4 63.7 17.9 60.8 0.9 0.0 17.1 5.3 6.8 157 Total 46.8 60.4 2.9 61.6 39.4 75.5 13.1 55.4 3.1 0.1 22.7 0.8 7.9 1,330 Note: ORT includes fluid prepared from oral rehydration salt (ORS) packets and recommended home fluids (RHF). Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes pharmacy, shop, traditional practitioner, and black bagger/drug peddler Child Health • 151 10.5.3 Feeding Practices during Diarrhea When a child has diarrhea, mothers are encouraged to continue feeding their child the same amount of food as they would if the child did not have diarrhea, and they are also encouraged to increase the child’s fluid intake. These practices help to reduce dehydration and minimize the adverse consequences of diarrhea on the child’s nutritional status. In the 2013 LDHS, mothers were asked whether they gave their child with diarrhea less, the same amount of, or more fluids and food than usual. Table 10.9 shows, by feeding practices, the percent distribution of children under 5 who had diarrhea in the two weeks preceding the survey, according to background characteristics. Twenty-six percent of the children with diarrhea were given the same amount of liquids as usual, and 39 percent were given more. It is of concern that 15 percent of the children were given somewhat less and 18 percent were given much less to drink during the diarrhea episode. Thirty-one percent of children were given the same amount of food as usual, 10 percent were given more food, 21 percent were given somewhat less food, and 24 percent were given much less food. Seven percent of children were not given any food during the diarrhea episode. Overall, only 23 percent of children had increased fluid intake and continued feeding. Forty-six percent of children were given ORT and/or increased fluids, and continued feeding. 152 • Child Health Table 10.9 Feeding practices during diarrhea Percent distribution of children under 5 who had diarrhea in the two weeks preceding the survey, by amount of liquids and food offered compared with normal practice, the percentage of children given increased fluids and continued feeding during the diarrhea episode, and the percentage of children who continued feeding and were given ORT and/or increased fluids during the episode of diarrhea, by background characteristics, Liberia 2013 Background characteristic Amount of liquids given Amount of food given Percentage given increased fluids and continued feeding1 Percentage who continued feeding and were given ORT and/or increased fluids1 Number of children with diarrhea More Same as usual Some- what less Much less None Don't know/ mis- sing Total More Same as usual Some- what less Much less None Never gave food Don't know/ mis- sing Total Age in months <6 26.1 33.4 17.5 16.2 6.8 0.0 100.0 1.9 39.6 6.6 6.4 6.0 39.4 0.0 100.0 9.0 17.7 59 6-11 40.9 22.5 13.4 20.7 2.2 0.4 100.0 4.5 22.5 20.2 25.1 9.0 18.3 0.4 100.0 19.1 35.4 209 12-23 38.7 25.9 14.3 18.8 1.2 1.1 100.0 11.1 31.8 18.1 25.0 8.1 4.6 1.2 100.0 21.9 47.7 407 24-35 39.8 29.8 11.0 16.3 2.8 0.3 100.0 10.4 36.5 21.7 25.9 4.4 0.5 0.6 100.0 27.1 51.3 267 36-47 36.9 23.3 17.5 21.6 0.6 0.2 100.0 12.9 26.5 28.2 26.6 5.3 0.4 0.1 100.0 24.4 51.6 231 48-59 47.4 21.0 18.1 10.4 0.1 3.0 100.0 12.7 30.0 22.6 22.6 8.8 0.1 3.0 100.0 30.7 52.7 157 Sex Male 39.9 26.3 12.8 18.4 1.7 0.9 100.0 10.6 32.3 19.6 25.7 5.2 5.7 0.9 100.0 25.2 46.9 682 Female 38.9 24.6 16.5 17.5 1.6 0.8 100.0 9.4 28.6 22.4 23.0 8.8 6.8 1.0 100.0 21.5 46.0 648 Type of diarrhea Non-bloody 39.0 27.3 14.0 16.7 2.0 1.0 100.0 10.3 33.0 19.7 23.0 6.1 6.9 1.0 100.0 23.5 46.3 1,034 Bloody 42.7 16.8 18.6 21.1 0.7 0.0 100.0 9.9 21.5 28.0 28.0 8.9 3.2 0.5 100.0 25.1 50.3 239 Missing 32.7 27.8 9.5 27.9 0.7 1.4 100.0 5.4 23.6 14.4 33.1 15.5 6.4 1.4 100.0 14.4 32.9 58 Residence Urban 37.5 22.8 17.0 20.0 1.3 1.4 100.0 11.5 29.8 26.2 23.3 4.8 3.1 1.4 100.0 27.4 51.8 607 Greater Monrovia 33.6 21.0 21.5 21.1 0.0 2.8 100.0 15.9 27.1 35.7 11.6 5.8 0.9 2.8 100.0 30.1 59.5 293 Other Urban 41.1 24.6 12.8 18.9 2.5 0.1 100.0 7.4 32.2 17.3 34.2 3.8 5.1 0.0 100.0 24.8 44.6 314 Rural 41.0 27.7 12.6 16.3 2.0 0.4 100.0 8.8 31.1 16.5 25.2 8.9 8.9 0.6 100.0 20.1 41.9 724 Region North Western 40.3 25.4 19.0 13.8 1.0 0.5 100.0 4.9 34.3 23.2 22.6 10.0 4.6 0.5 100.0 19.5 53.0 113 South Central 38.2 21.2 18.1 19.5 1.4 1.6 100.0 13.0 26.3 28.6 20.6 6.2 3.6 1.6 100.0 26.3 50.7 528 South Eastern A 44.5 25.0 12.3 17.2 0.7 0.2 100.0 11.2 24.9 19.1 20.3 16.2 8.1 0.2 100.0 21.6 38.9 127 South Eastern B 35.7 28.9 15.4 15.4 2.8 1.8 100.0 16.0 30.5 12.7 26.9 5.2 6.3 2.5 100.0 21.2 46.3 129 North Central 40.3 29.8 9.7 18.1 2.1 0.0 100.0 5.6 36.3 14.0 29.8 5.0 9.4 0.0 100.0 22.2 41.7 433 County Bomi (37.0) (47.7) (4.3) (11.1) (0.0) (0.0) 100.0 (0.0) (49.6) (8.7) (30.6) (2.3) (8.8) (0.0) 100.0 (15.0) (45.4) 19 Bong 36.1 38.7 13.3 11.4 0.6 0.0 100.0 4.1 44.3 14.3 14.6 7.1 15.5 0.0 100.0 19.6 43.4 211 Gbarpolu 44.8 24.5 18.2 9.7 1.1 1.7 100.0 12.0 23.7 48.2 8.7 1.9 3.8 1.7 100.0 38.3 67.0 32 Grand Bassa 38.1 25.4 17.1 18.6 0.9 0.0 100.0 9.8 29.1 20.3 29.4 5.3 6.1 0.0 100.0 16.7 39.2 104 Grand Cape Mount 39.0 19.0 24.0 16.7 1.3 0.0 100.0 2.7 35.2 14.6 27.3 16.5 3.7 0.0 100.0 11.2 48.0 62 Grand Gedeh 30.7 25.8 21.3 22.2 0.0 0.0 100.0 3.8 32.6 18.1 35.9 5.4 4.3 0.0 100.0 13.6 37.6 32 Grand Kru 30.0 26.5 21.9 14.2 3.9 3.6 100.0 12.7 28.5 16.9 25.6 7.5 3.1 5.7 100.0 12.7 39.5 56 Lofa 35.5 33.1 13.9 15.6 1.9 0.0 100.0 7.9 48.3 13.9 18.2 7.9 3.7 0.0 100.0 25.2 58.4 44 Margibi 53.5 18.5 5.4 17.0 5.6 0.0 100.0 6.0 21.0 22.3 34.2 9.8 6.6 0.0 100.0 27.0 37.7 90 Maryland 35.8 31.8 13.6 17.0 1.3 0.6 100.0 26.6 33.3 9.3 21.8 0.0 9.1 0.0 100.0 29.5 61.0 45 Montserrado 34.1 20.6 21.8 20.5 0.4 2.5 100.0 15.9 26.9 32.9 14.2 5.6 2.0 2.5 100.0 29.0 57.8 335 Nimba 46.4 18.5 4.3 26.7 4.0 0.0 100.0 6.7 23.7 13.7 50.7 1.8 3.4 0.0 100.0 24.5 35.5 177 River Cess 51.8 18.7 9.8 19.3 0.5 0.0 100.0 13.1 19.2 17.6 11.8 25.4 12.8 0.0 100.0 21.2 31.6 45 River Gee 46.9 29.0 5.6 15.2 3.3 0.0 100.0 5.9 30.0 9.8 37.6 8.7 8.0 0.0 100.0 24.6 36.4 28 Sinoe 47.0 30.1 8.8 12.2 1.4 0.6 100.0 14.1 25.0 21.1 17.9 15.0 6.3 0.6 100.0 27.1 46.3 50 Mother's education No education 40.3 26.0 16.1 14.9 2.4 0.3 100.0 8.1 30.5 20.4 22.2 10.5 7.8 0.4 100.0 22.1 42.8 539 Primary 41.4 26.2 12.3 18.7 1.2 0.2 100.0 8.6 34.3 17.3 27.0 6.5 6.1 0.3 100.0 25.2 49.6 428 Secondary and higher 35.7 23.8 15.2 21.7 1.1 2.4 100.0 14.6 26.0 26.2 24.4 2.4 4.0 2.4 100.0 23.3 48.1 363 Wealth quintile Lowest 39.7 29.1 13.2 16.4 1.0 0.6 100.0 9.1 32.1 16.2 22.1 9.2 10.4 0.9 100.0 19.6 40.9 370 Second 41.6 26.2 14.3 16.5 1.6 0.0 100.0 10.6 31.1 19.1 26.8 6.2 6.2 0.0 100.0 23.9 46.1 307 Middle 37.4 25.3 8.7 24.9 3.4 0.3 100.0 6.5 29.3 15.1 38.0 5.9 4.9 0.3 100.0 20.2 40.2 246 Fourth 39.7 23.3 21.5 14.0 1.5 0.0 100.0 9.0 34.1 28.2 21.0 3.4 4.3 0.0 100.0 26.5 56.4 251 Highest 37.4 19.2 17.1 20.0 0.9 5.5 100.0 18.1 21.7 33.5 8.7 11.0 1.7 5.3 100.0 31.6 53.9 157 Total 39.4 25.5 14.6 18.0 1.7 0.9 100.0 10.0 30.5 21.0 24.4 7.0 6.2 0.9 100.0 23.4 46.4 1,330 Note: It is recommended that children should be given more liquids to drink during diarrhea and that food should not be reduced. Figures in parentheses are based on 25-49 unweighted cases. 1 Continued feeding practices include children who were given more, the same as usual, or somewhat less food during the diarrhea episode. Child Health • 153 10.6 Knowledge of ORS Packets To ascertain respondents’ knowledge of ORS in Liberia, women were asked whether they had heard of a special product called an ORS packet that can be used to treat diarrhea. Table 10.10 presents information on the percentage of mothers with a birth in the five years preceding the survey who had heard of ORS packets. Knowledge was nearly universal (96 percent). Variations in knowledge of ORS packets according to background characteristics were generally minor. Table 10.10 Knowledge of ORS packets Percentage of women age 15-49 with a live birth in the five years preceding the survey who know about ORS packets for treatment of diarrhea by background characteristics, Liberia 2013 Background characteristic Percentage of women who know about ORS packets Number of women Age 15-19 96.2 532 20-24 96.3 1,182 25-34 95.5 1,987 35-49 96.2 1,069 Residence Urban 97.7 2,555 Greater Monrovia 99.4 1,332 Other Urban 95.8 1,223 Rural 93.9 2,215 Region North Western 98.6 496 South Central 99.1 2,103 South Eastern A 90.1 328 South Eastern B 92.2 352 North Central 92.8 1,491 County Bomi 100.0 128 Bong 94.6 559 Gbarpolu 96.6 112 Grand Bassa 98.1 267 Grand Cape Mount 98.8 256 Grand Gedeh 88.9 112 Grand Kru 85.0 147 Lofa 97.4 262 Margibi 98.3 349 Maryland 98.5 141 Montserrado 99.4 1,487 Nimba 89.4 670 River Cess 92.1 92 River Gee 94.9 63 Sinoe 89.7 124 Education No education 95.1 1,862 Primary 94.7 1,428 Secondary and higher 98.2 1,479 Wealth quintile Lowest 92.5 1,052 Second 94.1 995 Middle 97.2 1,014 Fourth 97.7 972 Highest 99.4 736 Total 95.9 4,769 ORS = Oral rehydration salts 154 • Child Health 10.7 DISPOSAL OF CHILDREN’S STOOLS The proper disposal of children’s feces is important in preventing the spread of disease. If feces are left uncontained, disease may spread by direct contact or through animal contact. The safe disposal of children’s feces is of particular importance because they are more likely to be the cause of fecal contamination in the household environment than adult feces. This occurs because they are often not disposed of properly and may be mistakenly considered less harmful than adult feces. Children’s stools are considered to be safely disposed of if the child uses a toilet or latrine, the child’s stool is put or rinsed into a toilet or latrine, or the stool is buried. Table 10.11 presents information on the disposal of fecal matter of children under 5, according to background characteristics. Overall, 32 percent of children had their last stool disposed of safely. Access to an improved toilet or latrine is clearly a factor in determining whether or not fecal matter was safely disposed of. For example, 53 percent of children who had access to an improved, non-shared toilet facility had their last stool disposed of safely compared with 21 percent of children who did not have such access. Children in urban areas were more likely than those in rural areas to have had their last stool safely disposed of (40 and 23 percent, respectively). At the county level, the proportion of children whose last stool was properly disposed of ranged broadly: 59 percent of children in Maryland had their stools disposed of safely, making it the county with best stool disposal practices. In contrast, only 7 percent of children from Bong had their stools disposed of safely, ranking it last among all counties. The proportion of children whose last stool was disposed of safely rose with the mother’s education and the wealth quintile. Child Health • 155 Table 10.11 Disposal of children's stools Percent distribution of youngest children under 5 living with the mother by the manner of disposal of the child's last fecal matter, and percentage of children whose stools are disposed of safely, according to background characteristics, Liberia 2013 Background characteristic Manner of disposal of children's stools Total Percentage of children whose stools are disposed of safely1 Number of children Child used toilet or latrine Put/rinsed into toilet or latrine Buried Put/rinsed into drain or ditch Thrown into garbage Left in the open/ bush/field Other Missing Age in months <6 0.6 25.3 0.5 40.8 15.1 16.9 0.5 0.4 100.0 26.4 590 6-11 0.3 19.0 1.5 37.2 18.7 22.7 0.4 0.1 100.0 20.8 699 12-23 0.8 23.3 4.2 22.9 24.7 23.5 0.0 0.5 100.0 28.3 1,184 24-35 1.0 21.8 13.2 8.3 28.2 27.3 0.2 0.1 100.0 35.9 769 36-47 6.9 19.5 14.5 3.9 23.0 31.8 0.0 0.3 100.0 40.9 615 48-59 10.5 18.7 15.4 1.6 18.2 35.0 0.3 0.4 100.0 44.6 451 Toilet facility2 Improved, not shared 12.1 35.7 4.9 14.0 26.2 6.4 0.4 0.2 100.0 52.8 541 Shared3 1.8 35.8 8.5 18.7 19.1 15.6 0.0 0.5 100.0 46.1 1,102 Non-improved 1.1 12.8 7.6 22.0 22.5 33.6 0.2 0.3 100.0 21.4 2,663 Residence Urban 3.8 28.6 7.6 18.6 23.0 18.0 0.1 0.3 100.0 40.0 2,269 Greater Monrovia 6.2 32.6 7.9 21.4 20.4 11.6 0.0 0.0 100.0 46.6 1,171 Other urban 1.1 24.4 7.4 15.7 25.8 24.8 0.2 0.6 100.0 32.9 1,097 Rural 1.4 13.7 7.4 21.8 21.1 33.9 0.3 0.3 100.0 22.5 2,040 Region North Western 0.1 11.5 4.3 35.5 22.3 25.9 0.2 0.1 100.0 15.9 443 South Central 4.8 30.3 9.1 19.4 18.9 17.3 0.2 0.0 100.0 44.2 1,877 South Eastern A 2.0 10.9 10.0 25.6 21.9 28.1 0.9 0.6 100.0 23.0 291 South Eastern B 3.6 23.2 9.1 12.2 23.8 27.4 0.0 0.6 100.0 35.9 308 North Central 0.4 14.8 5.5 16.9 26.0 35.7 0.0 0.7 100.0 20.7 1,389 County Bomi 0.4 9.0 1.8 35.0 34.0 19.9 0.0 0.0 100.0 11.1 113 Bong 0.5 5.3 0.6 12.7 32.1 47.5 0.0 1.2 100.0 6.5 519 Gbarpolu 0.0 19.1 2.8 26.4 11.1 40.4 0.2 0.0 100.0 22.0 102 Grand Bassa 2.6 25.0 15.8 16.4 3.7 36.2 0.3 0.0 100.0 43.4 243 Grand Cape Mount 0.0 9.3 6.3 39.8 21.5 22.4 0.3 0.2 100.0 15.6 228 Grand Gedeh 3.2 17.6 7.8 20.3 24.6 26.0 0.3 0.4 100.0 28.6 97 Grand Kru 0.0 5.4 15.9 9.7 19.7 48.4 0.0 0.9 100.0 21.3 127 Lofa 0.3 13.5 0.6 10.9 23.9 50.2 0.0 0.7 100.0 14.4 240 Margibi 3.3 32.8 6.8 16.7 28.2 11.1 1.0 0.0 100.0 43.0 324 Maryland 6.5 46.1 6.1 11.7 21.8 7.6 0.1 0.2 100.0 58.7 126 Montserrado 5.6 30.7 8.4 20.6 19.5 15.3 0.0 0.0 100.0 44.7 1,309 Nimba 0.4 23.1 11.5 22.6 21.7 20.3 0.1 0.3 100.0 34.9 630 River Cess 1.7 0.4 16.4 41.0 20.0 20.0 0.0 0.4 100.0 18.5 85 River Gee 5.0 12.2 0.6 19.2 37.9 24.3 0.0 0.9 100.0 17.8 56 Sinoe 1.2 13.3 7.0 18.1 20.9 36.4 2.1 0.9 100.0 21.6 108 Mother's education No education 1.5 17.3 7.4 18.6 21.2 33.4 0.3 0.4 100.0 26.2 1,731 Primary 1.1 20.8 7.1 21.2 20.6 28.6 0.2 0.3 100.0 29.0 1,296 Secondary and higher 5.7 28.1 8.1 21.2 24.9 11.9 0.1 0.1 100.0 41.9 1,281 Wealth quintile Lowest 0.6 8.5 6.8 21.9 19.8 41.9 0.2 0.3 100.0 15.9 972 Second 1.2 17.5 6.9 19.1 21.1 33.4 0.2 0.5 100.0 25.6 918 Middle 1.7 21.3 7.4 20.1 23.1 25.9 0.4 0.1 100.0 30.4 920 Fourth 1.7 32.7 11.4 21.2 21.9 10.4 0.1 0.5 100.0 45.8 849 Highest 10.1 32.6 4.5 17.6 25.8 9.2 0.0 0.1 100.0 47.3 650 Total 2.6 21.6 7.5 20.1 22.1 25.5 0.2 0.3 100.0 31.7 4,308 Note: Total includes 2 cases for which information on toilet facility type is missing. 1 Children's stools are considered to be disposed of safely if the child used a toilet or latrine, if the fecal matter was put or rinsed into a toilet or latrine, or if it was buried. 2 See Table 2.2 for definition of categories. 3 Facilities that would be considered improved if they were not shared by two or more households Nutrition of Children and Adults • 157 NUTRITION OF CHILDREN AND ADULTS 11 his chapter, which focuses on the nutritional status of children and adults, complements other recent surveys on nutrition that have been conducted in Liberia (LISGIS, 2011b). The chapter describes the nutritional status of children under 5; infant and young child feeding practices, including breastfeeding and feeding with solid/semisolid foods; diversity of foods fed and frequency of feeding; and micronutrient status, supplementation, and fortification. The discussion also covers the nutritional status of women and men age 15-49. 11.1 NUTRITIONAL STATUS OF CHILDREN The anthropometric data on height and weight collected in the 2013 LDHS permit the measurement and evaluation of the nutritional status of young children in Liberia. This evaluation allows identification of subgroups of the child population that are at increased risk of faltered growth, disease, impaired mental development, and death. Marked differences, especially with regard to height-for-age, weight-for-height, and weight-for-age, are often seen among subgroups of children within the country. T Key Findings • Among Liberian children under age 5 at the time of the survey, 32 percent were stunted (short for their age), 6 percent were wasted (thin for their height), and 15 percent were underweight (thin for their age). Only 3 percent of children were overweight (heavy for their height). • Almost all children (98 percent) are breastfed at some point in their life. Fifty-five percent of children under 6 months are exclusively breastfed. Less than half (44 percent) of children age 6-8 months are breastfeeding and consuming complementary foods. • The median duration for breastfeeding is 19.6 months. Exclusive breastfeeding, in contrast, is relatively short, with a median duration of 2.7 months. • Feeding practices of only 4 percent of children age 6-23 months meet the minimum standards set by three core infant and young child feeding (IYCF) practices. • Sixty percent of Liberian children age 6-59 months received vitamin A supplements in the 6 months prior to the survey, 27 percent received iron supplements in the 7 days beforehand, 56 percent received deworming medication in the preceding 6 months, and 99 percent live in households with iodized salt. • Overall, 66 percent of women and 80 percent of men have a body mass index (BMI) in the normal range. One in four women and fewer than 1 in 10 men are overweight or obese. • Among women age 15-49 with a child born in the past five years, 62 percent received a vitamin A dose postpartum; during the pregnancy of their last birth, 21 percent of women took iron tablets for the recommended period of time, and 58 percent took deworming medication. 158 • Nutrition of Children and Adults 11.1.1 Measurement of Nutritional Status among Young Children The 2013 LDHS collected data on the nutritional status of children by measuring the height and weight of children under 5. Data came from the subsample of households selected for the male survey and biomarker collection, regardless of whether the children’s mothers were interviewed in the survey. Data were collected to calculate three indices: height-for-age, weight-for-height, and weight-for-age. Weight measurements were obtained using a SECA 874 digital scale, designed for weighing children and adults. Height measurements were carried out using a Shorr Productions measuring board. Children younger than 24 months were measured lying down on the board (recumbent length), and standing height was measured for older children. For the 2013 LDHS, the nutritional status of children was calculated using growth standards published by WHO in 2006. These standards were generated through data collected in the WHO Multicentre Growth Reference Study (WHO, 2006). That study, which involved a sample of 8,440 children drawn from six countries across the world, was designed to describe how children should grow under optimal conditions. The WHO child growth standards can therefore be used to assess children all over the world, regardless of ethnicity, social and economic influences, and feeding practices. Each of the three nutritional status indicators described below is expressed in standard deviation units from the median of the Multicentre Growth Reference Study sample. Each of these indices—height-for-age, weight-for-height, and weight-for-age—provides different information about growth and body composition that can be used to assess nutritional status. The height-for- age index is an indicator of linear growth retardation and cumulative growth deficits. Children whose height- for-age Z-score is below minus two standard deviations (-2 SD) from the median of the reference population are considered short for their age (stunted), or chronically malnourished. Children who are below minus three standard deviations (-3 SD) are considered severely stunted. Stunting reflects failure to receive adequate nutrition over a long period and is also affected by recurrent and chronic illness. Height-for age, therefore, represents the long-term effects of malnutrition (specifically, undernutrition) in a population and is not sensitive to recent, short-term changes in dietary intake. The weight-for-height index measures body mass in relation to body height or length and describes current nutritional status. Children whose Z-scores are below -2 SD from the median of the reference population are considered thin (wasted), or acutely malnourished. Wasting represents the failure to receive adequate nutrition in the period immediately preceding the survey. It may result from inadequate food intake or a recent episode of illness causing loss of weight and the onset of malnutrition. Children whose weight-for-height is below -3 SD are considered severely wasted. Overweight and obesity are other forms of malnutrition that are becoming concerns for some children in developing countries. Children whose Z-score values are +2 SD above the median for weight-for-height are considered overweight. Weight-for-age is a composite index of height-for-age and weight-for-height. It takes into account both acute and chronic malnutrition. Children whose weight-for-age is below -2 SD from the median of the reference population are classified as underweight. Children whose weight-for-age is below -3 SD from the median are considered severely underweight. Z-score means are also calculated as summary statistics representing the nutritional status of children in a population. These mean scores describe the nutritional status of the entire population without the use of a cutoff. A mean Z-score of less than 0 (i.e., a negative value for stunting, wasting, or underweight) suggests that the distribution of an index has shifted downward and, on average, children in the population are less well- nourished than children in the WHO Multicentre Growth Reference Study. Nutrition of Children and Adults • 159 11.1.2 Data Collection Height and weight measurements were obtained for 3,706 children under age 5 who were present in the LDHS sample households at the time of the survey. The following analysis focuses on the 3,520 children (95 percent) for whom complete and credible anthropometric and age data were collected. 11.1.3 Levels of Child Malnutrition Table 11.1 and Figure 11.1 show the percentage of children under 5 classified as malnourished according to the three anthropometric indices of nutritional status (height-for-age, weight-for-height, and weight-for-age). Overall, at the time of the 2013 LDHS, 32 percent of children were stunted, 6 percent were wasted, 15 percent were underweight, and 3 percent were overweight. The percentage of stunting initially increases with a child’s age, with prevalence peaking in the age range of 36-47 months (42 percent), before declining somewhat as children approach their fifth birthday (35 percent of children age 48-59 months are stunted). Seventeen percent of Liberian children age 24-35 months are severely stunted. The prevalence of wasting is highest among children age 6-8 months (15 percent), and children age 9-11 months are most likely to be underweight (23 percent). Table 11.1 Nutritional status of children Percentage of children under age 5 classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for- height, and weight-for-age, by background characteristics, Liberia 2013 Background characteristic Height-for-age1 Weight-for-height Weight-for-age Number of children Per- centage below -3 SD Per- centage below -2 SD2 Mean Z- score (SD) Per- centage below -3 SD Per- centage below -2 SD2 Per- centage above +2 SD Mean Z- score (SD) Per- centage below -3 SD Per- centage below -2 SD2 Per- centage above +2 SD Mean Z- score (SD) Age in months <6 1.3 8.6 0.0 2.4 6.7 6.3 -0.1 0.6 5.7 2.6 -0.2 282 6-8 5.1 17.5 -0.1 3.6 15.3 2.4 -0.8 5.7 16.9 2.3 -0.8 208 9-11 7.0 19.6 -0.5 5.0 13.7 4.2 -0.6 5.8 22.9 3.3 -0.8 213 12-17 5.9 24.4 -0.9 4.2 10.4 1.8 -0.6 4.8 14.5 1.4 -0.9 362 18-23 15.1 34.6 -1.4 2.8 7.5 2.4 -0.3 4.8 19.4 1.7 -0.9 360 24-35 17.4 36.7 -1.6 1.5 4.6 1.0 0.0 6.5 16.1 0.5 -0.9 651 36-47 16.1 42.2 -1.7 0.8 2.5 2.3 0.1 4.1 15.0 0.3 -0.9 731 48-59 13.9 35.0 -1.5 0.9 2.6 4.3 0.0 3.0 12.9 0.0 -0.9 713 Sex Male 13.7 34.0 -1.3 2.4 6.4 2.6 -0.2 5.0 16.6 1.2 -0.9 1,886 Female 10.8 28.8 -1.1 1.6 5.6 3.2 -0.2 3.7 13.2 0.8 -0.8 1,634 Birth interval in months3 First birth4 11.2 28.4 -1.1 3.1 7.0 2.2 -0.3 3.9 16.6 0.8 -0.8 677 <24 15.0 39.5 -1.5 1.5 5.2 2.0 -0.2 4.9 15.1 0.6 -1.0 315 24-47 13.5 32.7 -1.3 2.1 6.3 2.7 -0.2 5.5 17.4 0.7 -0.9 1,186 48+ 9.0 23.4 -0.9 1.8 6.7 4.2 -0.1 2.6 9.4 1.9 -0.6 731 Size at birth3 Very small 23.7 36.7 -1.6 5.6 16.9 2.6 -0.7 10.1 28.4 0.5 -1.4 219 Small 14.9 38.0 -1.6 2.6 10.5 1.8 -0.5 7.0 23.5 0.5 -1.2 313 Average or larger 10.5 28.5 -1.1 1.8 4.9 3.1 -0.1 3.4 12.6 1.2 -0.7 2,373 Mother's interview status Interviewed 12.0 30.1 -1.2 2.2 6.4 2.9 -0.2 4.3 15.0 1.0 -0.8 2,910 Not interviewed but in household 13.6 43.0 -1.4 0.0 3.5 3.8 -0.1 6.2 17.8 0.4 -0.8 68 Not interviewed and not in the household5 14.1 38.2 -1.3 1.3 4.1 2.7 0.0 4.5 15.1 0.9 -0.8 543 …Continued 160 • Nutrition of Children and Adults Table 11.1 Nutritional status of children—Continued Background characteristic Height-for-age1 Weight-for-height Weight-for-age Number of children Per- centage below -3 SD Per- centage below -2 SD2 Mean Z- score (SD) Per- centage below -3 SD Per- centage below -2 SD2 Per- centage above +2 SD Mean Z- score (SD) Per- centage below -3 SD Per- centage below -2 SD2 Per- centage above +2 SD Mean Z- score (SD) Mother's nutritional status6 Thin -BMI<18.5 23.6 43.1 -1.9 7.0 14.3 4.5 -0.7 12.8 36.4 0.0 -1.5 157 Normal -BMI 18.5- 24.9 12.1 31.1 -1.2 2.4 6.7 2.5 -0.3 4.5 15.0 1.2 -0.9 1,778 Overweight/ obese –BMI ≥ 25 8.0 21.9 -0.9 1.1 5.1 2.8 0.0 1.9 8.1 0.7 -0.5 620 Residence Urban 10.5 30.0 -1.1 2.0 5.9 3.0 -0.2 4.3 13.4 1.3 -0.8 1,791 Greater Monrovia 6.8 27.0 -0.9 1.0 5.5 3.7 -0.2 2.0 8.5 1.5 -0.6 885 Other urban 14.2 32.9 -1.3 2.9 6.3 2.3 -0.2 6.5 18.2 1.2 -0.9 906 Rural 14.2 33.3 -1.4 2.1 6.1 2.8 -0.2 4.5 16.7 0.7 -0.9 1,729 Region North Western 10.8 29.0 -1.3 2.2 5.9 3.8 -0.1 2.7 13.3 0.4 -0.8 406 South Central 9.3 29.4 -1.0 2.3 6.6 3.0 -0.2 3.5 11.7 1.4 -0.7 1,447 South Eastern A 14.0 32.6 -1.3 1.7 7.1 2.5 -0.2 4.5 16.8 0.6 -0.9 237 South Eastern B 14.9 34.1 -1.3 1.9 4.2 3.1 -0.1 4.0 19.1 1.1 -0.8 248 North Central 15.7 34.5 -1.4 1.7 5.5 2.5 -0.2 6.2 18.6 0.8 -1.0 1,182 County Bomi 15.3 33.1 -1.4 3.4 8.8 6.5 -0.2 4.0 19.7 0.0 -0.9 110 Bong 14.6 34.7 -1.3 2.9 7.2 2.8 -0.2 6.2 17.4 1.2 -0.9 434 Gbarpolu 6.9 25.1 -1.0 4.8 6.5 1.7 -0.2 1.8 10.8 0.4 -0.8 92 Grand Bassa 17.5 38.1 -1.6 4.6 8.6 2.1 -0.3 8.4 19.7 1.3 -1.1 197 Grand Cape Mount 10.2 28.5 -1.3 0.4 4.1 3.2 0.0 2.4 11.0 0.7 -0.8 204 Grand Gedeh 13.4 31.4 -1.3 0.9 5.9 2.4 -0.0 5.3 15.5 0.4 -0.8 80 Grand Kru 11.2 31.4 -1.2 1.7 3.7 2.0 -0.1 3.5 18.6 0.9 -0.8 100 Lofa 8.8 28.5 -1.1 2.4 6.8 4.6 -0.1 3.8 14.8 0.5 -0.8 189 Margibi 10.5 31.4 -1.2 2.8 5.4 1.8 -0.2 3.5 14.6 1.2 -0.8 259 Maryland 15.9 33.4 -1.3 1.9 3.3 3.3 0.0 3.9 17.3 1.1 -0.8 105 Montserrado 7.4 27.1 -0.9 1.8 6.5 3.4 -0.2 2.5 9.3 1.4 -0.6 992 Nimba 18.9 36.4 -1.6 0.5 3.9 1.6 -0.1 6.9 20.7 0.6 -1.1 559 River Cess 15.5 35.4 -1.5 2.0 8.6 1.5 -0.4 6.7 21.0 0.5 -1.1 69 River Gee 21.1 42.6 -1.7 2.2 7.8 5.0 -0.1 5.6 25.0 1.7 -1.0 43 Sinoe 13.4 31.5 -1.2 2.1 7.0 3.4 -0.2 1.9 14.6 0.9 -0.8 88 Mother's education7 No education 14.1 32.9 -1.3 2.0 6.4 3.1 -0.2 5.0 16.0 1.0 -0.9 1,268 Primary 12.3 28.3 -1.2 1.7 5.9 2.6 -0.2 3.8 14.6 1.3 -0.8 881 Secondary and higher 8.6 28.8 -1.0 2.9 6.8 3.0 -0.2 4.1 14.0 0.9 -0.8 828 Wealth quintile Lowest 15.9 35.3 -1.4 2.6 6.1 3.1 -0.1 5.4 18.3 0.6 -0.9 838 Second 16.3 35.2 -1.4 2.1 6.2 2.2 -0.2 5.7 18.8 0.7 -1.0 813 Middle 12.7 35.3 -1.3 2.0 6.4 3.0 -0.1 4.3 15.1 1.4 -0.8 683 Fourth 7.7 27.7 -1.0 1.6 6.8 2.1 -0.2 2.0 11.3 1.7 -0.7 681 Highest 5.9 19.9 -0.7 1.7 3.9 4.4 -0.2 3.8 8.5 0.6 -0.6 506 Total 12.3 31.6 -1.2 2.0 6.0 2.9 -0.2 4.4 15.0 1.0 -0.8 3,520 Note: Table is based on children who stayed in the household on the night before the interview. Each of the indices is expressed in standard deviation units (SD from the median of the WHO Child Growth Standards adopted in 2006. Table is based on children with valid dates of birth (month and year) and valid measurement of both height and weight. Total includes 5 cases for which information on size at birth is missing. 1 Recumbent length is measured for children under age 2, or in the few cases when the age of the child is unknown and the child is less than 85 cm; standing height is measured for all other children. 2 Includes children who are below -3 standard deviations (SD) from the WHO Child Growth standards population median 3 Excludes children whose mothers were not interviewed 4 First-born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval. 5 Includes children whose mothers are deceased 6 Excludes children whose mothers were not weighed and measured, children whose mothers were not interviewed, and children whose mothers are pregnant or gave birth within the preceding 2 months. Mother's nutritional status in terms of BMI (body mass index) is presented in Table 11.9.1. 7 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. As can be seen in Table 11.1, boys are more likely to be malnourished than girls across all indices. Proportions of stunting, wasting, and underweight are higher among children reported as very small and small Nutrition of Children and Adults • 161 at birth than among children reported as average or larger at birth. In addition, the prevalence of stunting, wasting, and underweight is higher among children born to underweight mothers than among those born to normal-weight or overweight mothers. Malnutrition levels vary little by residence; by county, River Gee has the highest prevalence of stunting (43 percent) and underweight (25 percent), while Bomi, Grand Bassa, and River Cess have the highest prevalence of wasting (9 percent). The prevalence of stunting, wasting, and underweight is inversely correlated with wealth quintile. Children in the highest wealth quintile are less likely to suffer from malnutrition than those in lower wealth quintiles. The prevalence of overweight children varies little by background characteristics. The mean stunting, wasting, and underweight Z-scores for children under 5 are -1.2, -0.2, and -0.8, respectively. Scores of less than zero on these indices suggest that nutritional status is poorer on average than that of the reference population. Figure 11.1 Nutritional status of children by age 0 5 10 15 20 25 30 35 40 45 50 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Percent Age (months) Stunted Wasted Underweight Note: Stunting reflects chronic malnutrition; wasting reflects acute malnutrition; underweight reflects chronic or acute malnutrition or a combination of both. Plotted values are smoothed by a five-month moving average. LDHS 2013 11.1.4 Trends in Child Malnutrition Figure 11.2 shows trends in the nutritional status of children in Liberia using anthropometric measurements from the 2007 LDHS and 2013 LDHS. The results show that stunting, wasting, underweight, and overweight decreased in Liberia between 2007 and 2013. 162 • Nutrition of Children and Adults Figure 11.2 Trends in nutritional status of children under 5 39 8 19 4 32 6 15 3 Stunting (height-for-age) Wasting (weight-for-height) Underweight (weight-for-age) Overweight (weight-for-height) Percent 2007 LDHS 2013 LDHS Note: The data for both surveys are based on the WHO child growth standards adopted in 2006. 11.2 BREASTFEEDING LDHS data can be used to evaluate infant feeding practices, including breastfeeding duration, introduction of complementary weaning foods, and use of feeding bottles. The pattern of infant feeding has important influences on both the child and the mother. Feeding practices are the principal determinants of a child’s nutritional status. Poor nutritional status in young children exposes them to greater risks of morbidity. Biologically, breastfeeding suppresses the mother’s return to fertile status and affects the length of the birth interval as well as the level of fertility. These effects are influenced by both the duration and frequency of breastfeeding and the age at which the child receives foods and liquids to complement breast milk. 11.2.1 Initiation of Breastfeeding Early breastfeeding practices determine the successful establishment and duration of breastfeeding. Moreover, during the first three days after delivery, colostrum, an important source of nutrition and protection for the newborn, is produced and should be given to the newborn while awaiting the letdown of regular breast milk. Thus, it is recommended that children be put to the breast immediately or within one hour after birth and that prelacteal feeding (i.e., feeding newborns anything other than breast milk before breast milk is regularly given) be discouraged. Table 11.2 shows that 98 percent of last-born children who were born in the two years preceding the survey were breastfed at some point in their life. Differences by background characteristics were small. Sixty-one percent of infants were breastfed within one hour of birth, and 87 percent began breastfeeding within one day of birth. The proportion of children breastfed within one hour of birth was no higher among those delivered in a health facility (61 percent) than among those born at home (62 percent). The likelihood of an infant breastfeeding within one hour of birth varied markedly by county, ranging from a low of 24 percent in Grand Kru to a high of 80 percent in Bong. Nutrition of Children and Adults • 163 The practice of giving prelacteal feeds limits the frequency of suckling by the infant and exposes the baby to the risk of infection. Table 11.2 shows that 10 percent of newborns received prelacteal feeds, with the practice being most common among infants whose delivery was assisted by someone other than a health professional or traditional birth attendant (22 percent). Infants of mothers with secondary and higher education and those in the highest wealth quintile were more likely to receive a prelacteal feed than other infants. Table 11.2 Initial breastfeeding Among last-born children who were born in the two years preceding the survey, the percentage who were ever breastfed and the percentages who started breastfeeding within one hour and within one day of birth; and among last-born children born in the two years preceding the survey who were ever breastfed, the percentage who received a prelacteal feed, by background characteristics, Liberia 2013 Background characteristic Among last-born children born in the past two years: Among last-born children born in the past two years who were ever breastfed: Percentage ever breastfed Percentage who started breastfeeding within 1 hour of birth Percentage who started breastfeeding within 1 day of birth1 Number of last-born children Percentage who received a prelacteal feed2 Number of last-born children ever breastfed Sex Male 97.8 58.8 85.6 1,394 9.8 1,364 Female 98.3 64.0 89.2 1,255 10.7 1,233 Assistance at delivery Health professional3 97.9 61.2 87.0 1,736 11.0 1,700 Traditional birth attendant 98.3 62.0 89.1 807 7.0 793 Other 97.6 57.9 78.6 101 22.2 99 No one * * * 5 * 5 Place of delivery Health facility 97.8 61.0 86.9 1,622 11.4 1,587 At home 98.4 61.9 88.1 1,012 8.4 996 Other * * * 15 * 14 Residence Urban 98.0 62.9 89.1 1,351 11.8 1,323 Greater Monrovia 97.5 61.3 87.8 667 16.3 650 Other urban 98.4 64.6 90.4 684 7.4 673 Rural 98.1 59.5 85.4 1,299 8.6 1,274 Region North Western 96.3 60.0 88.9 288 7.3 277 South Central 97.7 61.3 86.3 1,109 14.7 1,084 South Eastern A 98.7 47.8 80.6 196 16.1 194 South Eastern B 96.6 41.1 72.8 197 10.6 190 North Central 99.1 69.3 92.8 860 3.9 852 County Bomi 94.7 72.2 91.8 68 6.2 64 Bong 98.5 79.8 92.5 318 2.1 314 Gbarpolu 98.1 67.6 91.6 64 6.1 63 Grand Bassa 98.3 61.1 80.4 149 15.0 146 Grand Cape Mount 96.3 51.5 86.6 155 8.4 150 Grand Gedeh 98.3 42.2 84.8 66 18.7 65 Grand Kru 96.7 23.6 62.5 80 8.2 77 Lofa 100.0 74.7 91.7 144 2.8 144 Margibi 98.7 57.8 86.6 214 7.3 211 Maryland 95.8 56.2 80.5 81 14.1 78 Montserrado 97.4 62.4 87.4 746 16.8 726 Nimba 99.3 58.9 93.4 398 5.8 395 River Cess 99.3 50.5 77.9 58 10.0 58 River Gee 98.4 45.4 78.2 36 8.4 36 Sinoe 98.7 50.7 78.9 73 18.7 72 Mother's education No education 98.5 64.1 88.6 1,000 8.7 985 Primary 98.2 62.4 87.6 858 8.4 842 Secondary and higher 97.3 56.4 85.3 792 14.1 770 Wealth quintile Lowest 98.1 58.6 84.2 636 9.3 624 Second 98.8 66.2 89.5 567 5.3 560 Middle 98.2 61.0 89.2 551 7.1 541 Fourth 97.7 61.3 88.8 509 12.0 497 Highest 97.1 58.7 84.4 386 21.3 375 Total 98.0 61.2 87.3 2,650 10.2 2,597 Note: Total includes 1 case for which information about assistance during delivery is missing. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes children who started breastfeeding within one hour of birth 2 Children given something other than breast milk during the first three days of life 3 Doctor, nurse/midwife, or physician’s assistant 164 • Nutrition of Children and Adults 11.2.2 Breastfeeding Status by Age Breast milk contains all of the nutrients needed by children in the first six months of life and is an uncontaminated nutritional source. Therefore, complementing breast milk before age 6 months is discouraged as the likelihood of contamination and resulting risk of diarrheal disease are high. Early initiation of complementary feeding also reduces breast milk output because the production and release of breast milk is modulated by the frequency and intensity of suckling. Table 11.3 shows breastfeeding practices by child’s age.1 Fifty-five percent of infants under 6 months are exclusively breastfed, which is a 26 percentage point increase from the figure reported in the 2007 LDHS (29 percent). Contrary to the recommendation that children under 6 months be exclusively breastfed, 28 percent of infants consume plain water, 3 percent consume non-milk liquids, 6 percent consume other milk, and 7 percent consume complementary foods in addition to breast milk. Forty-four percent of children age 6-8 months receive timely complementary foods, and half of children age 18-23 months have been weaned. Feeding children using a bottle with a nipple is discouraged and remains a relatively uncommon practice in Liberia; 17 percent of children below age 6 months are fed using a bottle with a nipple. The prevalence of bottle-feeding is highest among children age 4-5 months (21 percent). These figures are somewhat higher than those reported in the 2007 LDHS when 13 percent of children below 6 months were bottle-fed and the prevalence of bottle-feeding was highest among children 2-3 months (15 percent). Table 11.3 Breastfeeding status by age Percent distribution of youngest children under age 2 who are living with their mother, by breastfeeding status, the percentage currently breastfeeding; and the percentage of all children under age 2 using a bottle with a nipple, according to age in months, Liberia 2013 Age in months Not breast- feeding Breastfeeding status Total Percentage currently breast- feeding Number of youngest child under two years living with their mother Percentage using a bottle with a nipple Number of all children under age 2 Exclusively breastfed Breast- feeding and consuming plain water only Breast- feeding and consuming non-milk liquids1 Breast- feeding and consuming other milk Breast- feeding and consuming comple- mentary foods 0-1 0.9 76.4 16.2 2.3 2.8 1.4 100.0 99.1 173 13.9 175 2-3 1.6 59.8 27.5 5.3 3.7 2.1 100.0 98.4 211 15.6 213 4-5 2.5 32.6 37.1 1.5 9.7 16.5 100.0 97.5 206 21.2 215 6-8 3.5 9.7 38.8 1.4 3.2 43.5 100.0 96.5 349 12.6 361 9-11 3.0 2.4 16.3 2.6 2.1 73.6 100.0 97.0 351 9.9 369 12-17 14.6 0.3 5.4 1.0 0.1 78.5 100.0 85.4 627 8.1 655 18-23 48.5 0.0 4.8 0.0 0.0 46.6 100.0 51.5 556 3.1 617 0-3 1.3 67.3 22.4 3.9 3.3 1.8 100.0 98.7 384 14.9 388 0-5 1.7 55.2 27.5 3.1 5.5 6.9 100.0 98.3 590 17.1 603 6-9 3.6 9.1 34.6 2.0 2.5 48.3 100.0 96.4 449 11.3 467 12-15 12.5 0.5 6.9 1.3 0.1 78.6 100.0 87.5 427 9.3 442 12-23 30.5 0.2 5.2 0.5 0.0 63.5 100.0 69.5 1,184 5.6 1,272 20-23 55.8 0.1 2.7 0.0 0.0 41.5 100.0 44.2 366 3.8 408 Note: Breastfeeding status refers to a "24-hour" period (yesterday and last night). Children who are classified as breastfeeding and consuming plain water only consumed no liquid or solid supplements. The categories of not breastfeeding, exclusively breastfed, breastfeeding and consuming plain water, non-milk liquids, other milk, and complementary foods (solids and semi-solids) are hierarchical and mutually exclusive, and their percentages add to 100 percent. Thus children who receive breast milk and non-milk liquids and who do not receive other milk and who do not receive complementary foods are classified in the non-milk liquid category even though they may also get plain water. Any children who get complementary food are classified in that category as long as they are breastfeeding as well. 1 Non-milk liquids include juice, juice drinks, clear broth, or other liquids 1 When comparing the results of the 2013 LDHS with previous LDHS surveys, note that the 2013 table on breastfeeding status by age is restricted to the youngest children and all children under age 2 living with their mothers, instead of the youngest children and all children under age 3 living with their mothers (as in the 2007 LDHS and 1999/2000 LDHS). Nutrition of Children and Adults • 165 Figure 11.3 depicts the transition of feeding practices among children up to age 2. The rapid drop in exclusive breastfeeding from 76 percent among infants under 2 months to 33 percent among children age 4-5 months demands attention. Figure 11.3 Infant feeding practices by age 0.0 20.0 40.0 60.0 80.0 100.0 <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 Percent Age group in months Not breastfeeding Complementary foods Other milk Non-milk liquids/juice Plain water only Exclusively breastfed LDHS 2013 Figure 11.4 presents 2013 LDHS results on infant and young child feeding (IYCF) indicators related to breastfeeding status. Detailed descriptions of these indicators can be found in WHO publications (WHO, 2008, and WHO, 2010b). 166 • Nutrition of Children and Adults Figure 11.4 IYCF Indicators on breastfeeding status 55 33 88 46 44 60 86 10 Exclusive breastfeeding under age 6 months Exclusive breastfeeding at age 4-5 months Continued breastfeeding at 1 year Introduction of solid, semi-solid, or soft foods (6-8 months) Continued breastfeeding at 2 years Age-appropriate breastfeeding (0-23 months) Predominant breastfeeding (0-5 months) Bottle feeding (0-23 months) Percentage of children LDHS 2013 11.2.3 Median Duration of Breastfeeding Table 11.4 shows that the median duration of any breastfeeding (i.e., the length of time in months for which half of children are breastfed) is 19.6 months. Children are breastfed one and a half months longer on average in rural areas (20.6 months) than in urban areas (18.9 months). Median durations of any breastfeeding are shorter for children with mothers who have at least some secondary education (19.0 months) than for children of mothers with no education (20.8). Large differences are observed by region, with median duration of any breastfeeding being highest in North Central region (21.4 months) and lowest in South Central (16.9 months). The median duration of breastfeeding generally declines by mother’s wealth quintile. Overall, the median duration of exclusive breastfeeding for Liberian children is 2.7 months, whereas the median duration of predominant breastfeeding (i.e., the period in which an infant receives only water or other non-milk liquids in addition to breast milk) is just over six months (6.4 months). Comparisons of duration of exclusive breastfeeding by background characteristics are not possible because in several categories there are too few children. Differences in median duration of predominant breastfeeding are generally small; the median duration of predominant breastfeeding decreases with rising education level of the mother and wealth quintile. Median durations of exclusive and predominant breastfeeding have increased from those reported in 2007; according to the 2007 LDHS, the median duration of exclusive breastfeeding was 0.6 months and the median duration of predominant breastfeeding was 4.8 months. Nutrition of Children and Adults • 167 Table 11.4 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey, by background characteristics, Liberia 2013 Background characteristic Median duration (months) of breastfeeding among children born in the past three years1 Any breastfeeding Exclusive breast- feeding Predominant breastfeeding2 Sex Male 19.3 2.5 6.4 Female 20.1 2.9 6.4 Residence Urban 18.9 (2.1) 5.8 Greater Monrovia (16.1) * (3.6) Other urban 20.2 2.9 7.4 Rural 20.6 3.2 7.0 Region North Western 20.5 3.4 6.8 South Central 16.9 (2.0) 4.9 South Eastern A 19.7 (1.5) 7.9 South Eastern B 19.1 2.8 6.5 North Central 21.4 3.8 7.3 Mother's education No education 20.8 3.2 7.0 Primary 19.1 2.8 6.5 Secondary and higher 19.0 (1.6) 5.1 Wealth quintile Lowest 20.1 3.2 7.3 Second 21.1 3.6 7.4 Middle 20.8 3.1 6.4 Fourth (18.9) * 5.8 Highest (15.9) * (3.6) Total 19.6 2.7 6.4 Mean for all children 19.3 4.8 8.6 Note: Median and mean durations are based on the distributions at the time of the survey of the proportion of births by months since birth. Includes children living and deceased at the time of the survey. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 It is assumed that non-last-born children and last-born children not currently living with the mother are not currently breastfeeding. 2 Either exclusively breastfed or received breast milk and plain water, and/or non-milk liquids only 11.3 DIETARY DIVERSITY AMONG YOUNG CHILDREN In the 2013 LDHS, women who had at least one child living with them who was born in 2011 or later were asked questions about the types of liquids and foods the child had consumed during the day or night preceding the interview. Mothers who had more than one child born in 2011 or later were asked questions about the youngest child living with them. Mothers were also asked about the number of times the child had eaten solid or semi-solid food during the period. The results from these data are subject to a number of limitations. For example, they do not apply to the full universe of young children. Unlike previous LDHS surveys, the information in Table 11.5 is restricted to the youngest children under age 22 living with their mother at the time of the survey. The dietary data on children are subject to recall errors on the mother’s part. In addition, the mother may not be able to report fully 2 In earlier surveys, the table comparable to Table 11.5 was restricted to the youngest children under age 3 who were living with their mothers at the time of the survey. 168 • Nutrition of Children and Adults on the child’s intake of food and liquids if the child was fed by other individuals during the period. Despite these problems, the information collected in the 2013 LDHS on the types of foods and liquids consumed by young children is useful in assessing the diversity of children’s diets. Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview Percentage of youngest children under age 2 who are living with the mother by type of foods consumed in the day or night preceding the interview, according to breastfeeding status and age, Liberia 2013 Age in months Liquids Solid or semi-solid foods Any solid or semi- solid food Number of children Infant formula Other milk1 Other liquids2 Fortified baby foods Food made from grains3 Fruits and vege- tables rich in vitamin A4 Other fruits and vege- tables Food made from roots and tubers Food made from legumes and nuts Meat, fish, poultry Eggs Cheese, yogurt, other milk product BREASTFEEDING CHILDREN 0-1 3.0 1.0 2.3 1.1 0.2 0.0 0.0 0.1 0.0 0.0 0.0 0.0 1.5 171 2-3 2.7 3.0 5.4 1.8 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.1 2.1 208 4-5 6.6 9.0 5.8 8.2 7.0 2.8 0.0 3.1 0.8 1.3 0.0 1.2 17.0 201 6-8 12.7 13.6 7.8 16.2 27.4 15.5 1.8 6.9 0.9 11.8 2.0 3.4 45.2 337 9-11 6.5 6.0 13.6 9.6 67.9 53.5 3.3 17.7 4.1 39.1 8.4 4.4 76.1 340 12-17 1.8 5.7 19.4 7.0 86.5 73.0 6.8 27.8 5.9 45.7 9.5 4.1 92.1 536 18-23 0.5 3.9 17.6 3.4 84.0 74.5 6.4 31.5 4.2 55.6 13.0 4.9 90.8 287 6-23 5.0 7.2 15.1 8.9 68.5 56.0 4.8 21.5 4.0 38.5 8.3 4.2 77.7 1,499 Total 4.8 6.5 12.2 7.5 50.1 40.6 3.5 15.8 3.0 27.9 6.0 3.2 58.0 2,079 NONBREASTFEEDING CHILDREN 0-11 (57.3) (33.7) (41.4) (51.8) (37.0) (30.2) (0.0) (1.5) (2.4) (20.0) (1.5) (0.0) (60.4) 33 12-17 17.2 18.8 29.5 12.0 82.7 65.3 9.3 19.0 1.2 54.5 13.6 6.2 88.7 92 18-23 1.3 6.6 25.6 4.4 95.9 85.9 9.0 41.6 7.7 55.3 15.8 7.2 98.7 270 6-23 8.4 11.6 27.7 9.7 90.2 78.4 8.5 33.8 5.9 53.5 14.4 6.5 94.9 385 Total 9.7 11.7 27.8 10.2 87.9 76.4 8.3 33.0 5.8 52.2 14.1 6.4 93.2 395 Note: Breastfeeding status and food consumed refer to a 24-hour period (yesterday and last night). Figures in parentheses are based on 25-49 unweighted cases. 1 Other milk includes fresh, tinned, and powdered cow or other animal milk 2 Doesn't include plain water 3 Includes fortified baby food 4 Includes pumpkin, squash, carrots, yellow or orange sweet potatoes, potato greens, bitter leaf, or any dark green leafy vegetables, mangoes, pawpaws, and red palm soup. 11.3.1 Foods and Liquids Consumed by Infants and Young Children Appropriate nutrition includes feeding children a variety of foods to ensure that nutrient requirements are met. Fruits and vegetables rich in vitamin A should be consumed daily. Although eating a range of fruits and vegetables, especially those rich in vitamin A, is important, studies have shown that plant-based complementary foods by themselves are insufficient to meet the needs for certain micronutrients. Therefore, it has been recommended that meat, poultry, fish, or eggs be eaten daily or as often as possible (WHO, 1998). Table 11.5 is based on information from mothers about the foods and liquids consumed by their youngest child during the day or night preceding the interview. As expected, the proportions of children consuming foods or liquids included in the various food groups generally increase with age. Children who are still breastfed are less likely than children who are not being breastfed to consume other types of liquids and solid/semi-solid foods. For example, 90 percent of nonbreastfeeding children age 6-23 months consumed foods made from grains the day or night preceding the interview, compared with 69 percent of breastfeeding children in that age group. Similarly, 78 percent of nonbreastfeeding children age 6-23 months consumed foods rich in vitamin A, as compared with 56 percent of breastfeeding children in the same age group. Half of nonbreastfeeding children (54 percent) and 39 percent of breastfeeding children age 6-23 months consumed Nutrition of Children and Adults • 169 meat, fish, and poultry. Differences between nonbreastfeeding and breastfeeding children age 6-23 months in the consumption of eggs, foods made from legumes and nuts, or cheese, yogurt, and other milk products were smaller, although the proportion of nonbreastfeeding children consuming each food group was higher than breastfeeding children. 11.3.2 Infant and Young Child Feeding (IYCF) Practices Appropriate IYCF practices include breastfeeding through age 2, introduction of solid and semisolid foods at age 6 months, and gradual increases in the amount of food given and frequency of feeding as the child gets older. The minimum frequencies for feeding children in developing countries are based on the energy output of complementary foods. The energy needs of children are based on age-specific total daily energy requirements plus 2 SD (to cover almost all children), minus the average energy intake from breast milk. Infants with low breast milk intake need to be fed more frequently than those with high breast milk intake. However, care should be taken that feeding frequencies do not exceed the recommended input from complementary foods because excessive feeding can result in displacement of breast milk (PAHO/WHO, 2003). According to recommendations, breastfed children age 6-23 months should receive animal-source foods and vitamin A-rich fruits and vegetables daily (PAHO/WHO, 2003). Because first foods almost always include a grain- or tuber-based staple, it is unlikely that young children who eat food from less than three groups will receive both an animal-source food and a vitamin A-rich fruit or vegetable. Therefore, three food groups are considered the minimum number appropriate for breastfed children (Arimond and Ruel, 2004). Breastfed infants age 6-8 months should receive complementary foods two to three times a day, with one or two snacks; breastfed children age 9-23 months should receive meals three to four times a day, with one or two snacks (PAHO/WHO, 2003; WHO, 2008; and WHO, 2010b). Nonbreastfed children age 6-23 months should receive milk or milk products two or more times a day to ensure that their calcium needs are met. In addition, they need animal-source foods and vitamin A-rich fruits and vegetables. Four food groups are considered the minimum number appropriate for nonbreastfed young children. Nonbreastfed children age 12-23 months should be fed meals four to five times each day, with one or two snacks (WHO, 2005; WHO, 2008; and WHO, 2010b). The results presented in Table 11.6 indicate that 83 percent of Liberian children age 6-23 months living with their mother received breast milk or breast milk substitutes during the day or night preceding the interview. Eleven percent of children had an adequately diverse diet—that is, they had been given foods from the appropriate number of food groups—and 30 percent had been fed the minimum number of times appropriate for their age. The feeding practices of only 4 percent of Liberian children age 6-23 months meet the minimum standards with respect to all three IYCF practices. The IYCF indicators for minimum acceptable diet by breastfeeding status among Liberian children age 6-23 months are summarized in Figure 11.5. Children in Greater Monrovia (8 percent) are more likely to be fed according to the recommended IYCF guidelines than children in other urban areas (3 percent) or in rural areas (3 percent). Variation in the percentage of children fed according to the recommended IYCF feeding practices is also observed at the county level, but these results should be interpreted with caution because of the small number of children reported on in the different counties. As expected, children in the highest two wealth quintiles (7-8 percent) are more likely to be fed according to the recommended three IYCF practices than children in lower wealth quintiles (2-3 percent). 170 • Nutrition of Children and Adults Table 11.6 Infant and young child feeding (IYCF) practices Percentage of youngest children age 6-23 months living with their mother who are fed according to three IYCF feeding practices based on breastfeeding status, number of food groups, and times they are fed during the day or night preceding the survey, by background characteristics, Liberia 2013 Background characteristic Among breastfed children 6-23 months, percentage fed: Among non-breastfed children 6-23 months, percentage fed: Among all children 6-23 months, percentage fed: 4+ food groups1 Minimum meal fre- quency2 Both 4+ food groups and minimum meal frequency Number of breastfed children 6-23 months Milk or milk products3 4+ food groups1 Minimum meal fre- quency4 With 3 IYCF practices5 Number of non- breastfed children 6-23 months Breast milk, milk, or milk products6 4+ food groups1 Minimum meal fre- quency7 With 3 IYCF practices Number of all children 6-23 months Age in months 6-8 0.8 32.3 0.5 337 * * * * 12 99.2 2.2 34.0 0.5 349 9-11 11.1 23.8 5.3 340 * * * * 11 97.9 10.7 24.0 5.2 351 12-17 11.5 36.7 6.5 536 33.1 19.3 32.5 3.3 92 90.2 12.6 36.1 6.0 627 18-23 13.7 28.5 4.7 287 5.4 18.5 21.2 2.6 270 54.1 16.0 25.0 3.7 556 Sex Male 9.8 28.2 4.2 761 14.2 18.7 24.2 1.0 221 80.7 11.8 27.3 3.5 982 Female 9.0 34.4 4.9 738 16.2 19.0 28.4 4.8 163 84.8 10.8 33.3 4.9 901 Residence Urban 10.4 36.1 6.2 725 20.1 24.4 31.7 2.8 246 79.8 14.0 35.0 5.3 971 Greater Monrovia 14.5 44.2 10.0 303 29.7 31.9 35.9 4.0 162 75.5 20.6 41.3 7.9 465 Other urban 7.5 30.3 3.5 422 1.5 10.0 23.7 0.4 84 83.7 7.9 29.2 3.0 506 Rural 8.5 26.7 3.0 774 6.1 8.9 15.9 2.4 139 85.7 8.5 25.1 2.9 913 Region North Western 6.5 25.6 4.3 165 0.0 11.8 11.5 0.0 33 83.4 7.4 23.2 3.5 198 South Central 11.6 35.5 6.6 562 23.4 27.3 29.6 2.9 221 78.4 16.0 33.9 5.6 783 South Eastern A 8.5 17.9 2.9 108 3.4 6.2 14.9 1.5 23 83.0 8.1 17.3 2.7 131 South Eastern B 10.5 34.4 1.9 107 12.4 10.3 18.4 8.4 27 82.5 10.5 31.2 3.2 134 North Central 8.1 30.6 3.4 556 2.7 4.8 27.7 1.3 81 87.7 7.7 30.2 3.1 637 County Bomi 3.2 19.4 0.0 34 * * * * 10 77.8 3.7 19.3 0.0 44 Bong 8.6 29.4 1.9 201 * * * * 34 85.9 7.3 30.0 1.7 235 Gbarpolu 7.4 40.2 4.8 37 * * * * 5 87.6 6.5 37.7 4.2 42 Grand Bassa 5.3 24.0 0.0 90 * * * * 17 84.0 4.5 22.0 0.0 107 Grand Cape Mount 7.3 22.0 5.6 93 * * * * 18 84.0 9.2 19.3 4.7 111 Grand Gedeh 8.6 22.1 5.0 31 * * * * 8 79.2 8.3 21.8 4.0 39 Grand Kru 18.9 29.5 2.6 38 * * * * 14 78.8 18.4 26.2 6.2 52 Lofa 9.5 31.9 4.3 83 * * * * 13 86.3 8.9 27.5 3.7 96 Margibi 10.4 23.1 3.0 123 (9.9) (21.9) (14.6) (0.0) 30 82.5 12.7 21.4 2.4 153 Maryland 5.0 43.1 1.3 45 * * * * 11 81.6 4.1 38.9 1.0 55 Montserrado 13.6 42.9 9.6 350 27.9 30.9 34.0 3.7 174 76.0 19.3 39.9 7.6 524 Nimba 7.3 31.0 4.1 273 (3.1) (9.5) (33.0) (3.1) 33 89.5 7.5 31.2 4.0 306 River Cess 6.8 13.8 0.9 38 * * * * 6 87.8 5.9 14.1 0.7 43 River Gee 7.5 26.3 2.0 24 * * * * 2 91.6 8.4 25.2 1.8 26 Sinoe 10.0 18.4 3.3 39 (5.7) (9.0) (9.6) (3.6) 10 81.7 9.8 16.7 3.4 49 Mother's education No education 9.2 28.3 3.9 587 5.1 4.5 16.7 0.0 112 84.8 8.4 26.4 3.2 699 Primary 9.7 33.9 4.6 496 10.3 19.2 21.1 2.3 111 83.6 11.4 31.5 4.2 607 Secondary and higher 9.4 32.3 5.4 415 25.2 28.4 35.8 4.6 162 79.0 14.8 33.3 5.2 577 Wealth quintile Lowest 8.3 24.9 2.9 390 4.5 4.9 10.9 3.3 68 85.8 7.8 22.9 3.0 458 Second 5.4 30.5 2.0 344 5.2 6.8 22.8 0.0 61 85.7 5.6 29.4 1.7 406 Middle 9.3 29.7 3.8 323 10.5 13.1 29.4 0.6 62 85.6 9.9 29.7 3.3 385 Fourth 15.3 34.8 8.6 259 16.4 28.3 20.2 4.6 96 77.3 18.8 30.8 7.5 355 Highest 11.1 43.6 8.3 183 (30.4) (30.5) (42.3) (3.1) 97 76.0 17.8 43.2 6.5 280 Total 9.4 31.2 4.5 1,499 15.1 18.8 26.0 2.6 385 82.7 11.3 30.2 4.1 1,883 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Food groups: a. infant formula, milk other than breast milk, cheese or yogurt or other milk products; b. foods made from grains, roots, and tubers, including porridge and fortified baby food from grains; c. vitamin A-rich fruits and vegetables (and red palm oil); d. other fruits and vegetables; e. eggs; f. meat, poultry, fish, and shellfish (and organ meats); g. legumes and nuts. 2 For breastfed children, minimum meal frequency is receiving solid or semi-solid food at least twice a day for infants 6-8 months and at least three times a day for children 9-23 months 3 Includes two or more feedings of commercial infant formula; fresh, tinned, and powdered animal milk; and yogurt 4 For non-breastfed children age 6-23 months, minimum meal frequency is receiving solid or semi-solid food or milk feeds at least four times a day 5 Non-breastfed children age 6-23 months are considered to be fed with a minimum standard of three Infant and Young Child Feeding Practices if they receive other milk or milk products at least twice a day, receive the minimum meal frequency, and receive solid or semi-solid foods from at least four food groups, not including the milk or milk products food group. 6 Breastfeeding, or not breastfeeding and receiving two or more feedings of commercial infant formula; fresh, tinned, and powdered animal milk; and yogurt 7 Children are fed the minimum recommended number of times per day according to their age and breastfeeding status as described in footnotes 2 and 4. Nutrition of Children and Adults • 171 In the period between the 2007 LDHS and the 2013 LDHS, the definition of standard IYCF indicators changed to reflect more restrictive requirements. In order to compare the IYCF results presented here with results from the 2007 LDHS, the 2013 data were recalculated according to the definitions used in 2007. This comparison indicates that the percentage of children age 6-23 months fed with an adequate diet (i.e., with all three IYCF practices) has declined from 25 percent in 2007 to 12 percent in 2013 (data not shown). However, this result should be interpreted with caution because the difference could be mostly due to methodological differences in data collection between the two surveys. Figure 11.5 IYCF indicators on minimum acceptable diet 9 31 5 19 26 3 11 30 4 IYCF 5: Minimum dietary diversity IYCF 6: Minimum meal frequency IYCF 7: Minimum acceptable diet Percent Breastfed children Non-breastfed children All children 6-23 months LDHS 2013 11.4 MICRONUTRIENT INTAKE AND SUPPLEMENTATION AMONG CHILDREN Micronutrient deficiency is a major contributor to childhood morbidity and mortality. Micronutrients are available in foods and can also be provided through direct supplementation. Breastfeeding children benefit from supplements given to the mother. Iron deficiency is one of the primary causes of anemia, which has serious health consequences for both women and children. Vitamin A is an essential micronutrient for the immune system and plays an important role in maintaining the epithelial tissue in the body. Severe vitamin A deficiency (VAD) can cause eye damage and is the leading cause of childhood blindness. VAD also increases the severity of infections such as measles and diarrheal disease in children and slows recovery from illness. VAD is common in dry environments where fresh fruits and vegetables are not readily available. Vitamin A supplementation is an important tool in preventing VAD among young children. Information was collected on food consumption during the day and night preceding the interview among the youngest children under age 2 living with their mothers; these data are useful in assessing the extent to which children are consuming food groups rich in two key micronutrients—vitamin A and iron—in their daily diet. In addition, the LDHS included questions designed to ascertain whether young children had received vitamin A supplements or deworming medication in the six months preceding the survey or iron supplements in the seven days preceding the survey. 172 • Nutrition of Children and Adults Table 11.7 shows the intake of foods rich in vitamin A and iron by the youngest children age 6-23 months living with their mother and recent vitamin A supplementation among all children age 6-59 months. Sixty-seven percent of children consumed vitamin A-rich foods in the 24 hours preceding the interview, and 45 percent consumed iron-rich foods. As expected, intake of both vitamin A-rich and iron-rich foods increases as children are weaned. Non-breastfeeding children are more likely to consume foods rich in vitamin A and iron than breastfeeding children. Intake of these two micronutrients varies considerably by county. Sixty percent of children age 6-59 months received a vitamin A supplement in the six months preceding the survey. The likelihood of a child being given a vitamin A dose rose with a mother’s education and with wealth quintile. Over one in four children (27 percent) received iron supplements in the previous seven days. Fifty-six percent of children age 6-59 months received deworming medication in the six months preceding the survey. Ninety-nine percent of children age 6-59 months live in households using iodized salt. The overall proportion of children who were reported to have received micronutrient supplements or deworming medication was higher in the 2013 LDHS than the 2007 LDHS. For example, vitamin A supplementation increased from 43 percent to 60 percent, iron supplementation increased from 17 percent to 27 percent, and deworming medication increased from 45 percent to 56 percent. Nutrition of Children and Adults • 173 Table 11.7 Micronutrient intake among children Among youngest children age 6-23 months who are living with their mother, the percentages who consumed vitamin A-rich and iron-rich foods in the day or night preceding the survey, and among all children 6-59 months, the percentages who were given vitamin A supplements in the six months preceding the survey, who were given iron supplements in the past seven days, and who were given deworming medication in the six months preceding the survey, and among all children age 6-59 months who live in households that were tested for iodized salt, the percentage who live in households with iodized salt, by background characteristics, Liberia 2013 Background characteristic Among youngest children age 6-23 months living with the mother: Among all children age 6-59 months: Among children age 6-59 months living in house-holds tested for iodized salt Percentage who consumed foods rich in vitamin A in past 24 hours1 Percentage who con- sumed foods rich in iron in past 24 hours2 Number of children Percentage given vitamin A supplements in past 6 months Percentage given iron supplements in past 7 days Percentage given deworming medication in past 6 months3 Number of children Percentage living in households with iodized salt4 Number of children Age in months 6-8 20.3 14.5 349 55.5 23.5 20.2 361 97.0 349 9-11 58.8 41.2 351 62.9 37.6 40.1 369 98.2 351 12-17 78.6 50.6 627 64.4 31.4 57.4 655 99.4 629 18-23 86.7 59.7 556 64.4 34.3 61.7 617 98.7 581 24-35 na na na 59.5 26.0 60.6 1,085 98.2 1,042 36-47 na na na 61.1 23.0 60.0 1,198 98.7 1,139 48-59 na na na 55.9 21.9 60.2 1,159 99.4 1,110 Sex Male 66.6 43.7 982 60.2 26.9 55.0 2,773 98.6 2,646 Female 66.4 46.1 901 60.2 26.5 57.1 2,671 98.7 2,556 Breastfeeding status Breastfeeding 61.7 41.3 1,499 62.0 30.9 46.1 1,614 98.4 1,556 Not breastfeeding 85.0 58.6 385 59.7 25.0 60.6 3,803 98.8 3,619 Mother's age at birth 15-19 64.3 47.2 259 56.9 29.9 46.7 446 98.4 431 20-29 66.5 42.4 961 60.8 27.6 55.4 2,780 98.2 2,639 30-39 65.1 44.2 571 61.2 25.9 59.3 1,745 99.3 1,677 40-49 80.5 68.5 92 56.6 21.1 57.1 473 99.3 453 Residence Urban 65.8 45.4 971 65.5 31.4 59.3 2,723 98.6 2,597 Greater Monrovia 64.0 42.9 465 72.5 35.9 66.4 1,356 98.8 1,302 Other urban 67.4 47.6 506 58.6 27.0 52.3 1,367 98.4 1,294 Rural 67.3 44.3 913 54.9 21.9 52.8 2,721 98.8 2,605 Region North Western 64.1 41.6 198 67.9 30.7 66.4 598 99.9 566 South Central 61.5 42.0 783 67.2 30.9 62.3 2,236 99.2 2,151 South Eastern A 64.8 39.8 131 49.2 18.0 46.0 410 98.4 387 South Eastern B 64.8 42.5 134 35.0 18.7 47.4 424 98.5 406 North Central 74.0 50.9 637 57.4 23.8 49.1 1,777 97.7 1,692 County Bomi 48.9 29.4 44 63.6 29.7 67.1 144 100.0 137 Bong 75.6 52.5 235 64.5 19.1 54.3 667 99.5 647 Gbarpolu 74.6 42.5 42 71.2 20.9 64.7 131 99.7 118 Grand Bassa 53.5 34.5 107 36.5 18.2 50.6 314 99.7 308 Grand Cape Mount 66.1 46.0 111 68.4 35.2 66.7 322 100.0 311 Grand Gedeh 63.2 37.7 39 50.4 22.0 46.1 125 96.0 115 Grand Kru 66.0 55.7 52 28.6 22.4 47.4 185 98.7 176 Lofa 68.3 33.8 96 41.9 22.2 42.5 281 98.6 270 Margibi 60.1 44.8 153 67.8 20.5 52.6 393 100.0 373 Maryland 64.0 30.6 55 33.4 13.7 44.4 158 98.9 153 Montserrado 63.6 42.7 524 73.4 36.2 67.2 1,528 98.9 1,471 Nimba 74.6 55.1 306 57.0 28.2 47.2 828 95.8 774 River Cess 66.3 40.1 43 51.1 15.5 47.8 125 100.0 118 River Gee 64.2 41.5 26 52.7 20.1 53.3 81 97.2 77 Sinoe 64.6 41.2 49 46.9 16.8 44.4 160 98.9 154 Mother's education No education 68.2 44.5 699 57.0 23.2 54.6 2,264 98.6 2,179 Primary 68.5 47.3 607 61.5 26.2 56.0 1,652 98.3 1,572 Secondary and higher 62.2 42.6 577 63.7 32.3 58.3 1,528 99.2 1,450 Wealth quintile Lowest 68.1 42.2 458 50.8 19.4 48.7 1,321 98.3 1,243 Second 69.5 46.3 406 58.0 23.1 53.5 1,217 99.1 1,162 Middle 66.1 45.1 385 61.2 31.4 57.1 1,136 98.0 1,100 Fourth 69.7 48.2 355 67.4 30.0 62.2 1,026 98.5 982 Highest 55.9 42.5 280 69.2 33.4 63.4 745 100.0 714 Total 66.5 44.8 1,883 60.2 26.7 56.1 5,444 98.7 5,201 Note: Information on vitamin A is based on both mother's recall and the immunization card (where available). Information on iron supplements and deworming medication is based on the mother's recall. Totals for children 6-59 months include 26 cases for which information on breastfeeding status is missing. na = Not applicable 1 Includes meat (and organ meat), fish, poultry, eggs, pumpkin, squash, carrots, yellow or orange sweet potatoes, dark green leafy vegetables, mango, pawpaw, red palm soup, red palm oil, or palm butter. 2 Includes meat (including organ meat), fish, poultry, and eggs 3 Deworming for intestinal parasites is commonly done for helminths and for schistosomiasis. 4 Excludes children in households in which salt was not tested. 174 • Nutrition of Children and Adults 11.5 Presence of Iodized Salt in Households Salt is used for several purposes in a household. It plays a role in cooking and food preservation. In line with food and drug regulations, household salt should be fortified with iodine sufficient to ensure concentration is at least 15 parts per million (ppm) when consumed. Iodine is an essential micronutrient, and iodized salt prevents goiter among children and adults. The 2013 LDHS tested household salt for iodine in 92 percent of households (Table 11.8). Among households in which salt was tested, 99 percent were consuming iodized salt, which is indicative of universal salt iodization. There were only small variations in the percentages of households with iodized salt by residence, region, county, and wealth quintile. It should be noted that household salt was tested for the presence or absence of iodine only; the iodine level in the salt was not measured. Table 11.8 Presence of iodized salt in household Among all households, the percentage with salt tested for iodine content and the percentage with no salt in the household; and among households with salt tested, the percentage with iodized salt, according to background characteristics, Liberia 2013 Background characteristic Among all households, the percentage Among households with tested salt: With salt tested With no salt in the household Number of households Percentage with iodized salt Number of households Residence Urban 91.5 8.5 5,289 98.2 4,839 Greater Monrovia 91.6 8.4 3,060 99.0 2,804 Other urban 91.3 8.7 2,229 97.1 2,036 Rural 92.7 7.3 4,044 98.9 3,750 Region North Western 92.4 7.6 909 99.9 839 South Central 92.3 7.7 4,645 99.3 4,288 South Eastern A 91.7 8.3 573 97.6 526 South Eastern B 94.2 5.8 571 97.9 538 North Central 91.0 9.0 2,634 97.0 2,398 County Bomi 92.4 7.6 295 99.7 273 Bong 91.8 8.2 1,118 99.5 1,026 Gbarpolu 89.9 10.1 216 99.6 194 Grand Bassa 94.5 5.5 584 99.8 552 Grand Cape Mount 94.0 6.0 420 99.9 395 Grand Gedeh 91.7 8.3 198 95.4 182 Grand Kru 93.3 6.7 201 97.2 188 Lofa 89.8 10.2 501 99.3 450 Margibi 91.6 8.4 699 99.9 640 Maryland 95.4 4.6 261 98.6 249 Montserrado 92.0 8.0 3,329 99.1 3,062 Nimba 90.6 9.4 1,019 93.2 923 River Cess 88.5 11.5 150 98.8 133 River Gee 94.6 5.4 118 98.3 112 Sinoe 94.3 5.7 223 98.8 211 Wealth quintile Lowest 91.1 8.9 2,008 98.7 1,830 Second 92.0 8.0 1,785 98.7 1,642 Middle 94.1 5.9 1,738 96.8 1,636 Fourth 91.0 9.0 2,024 98.8 1,843 Highest 92.2 7.8 1,777 99.7 1,638 Total 92.0 8.0 9,333 98.5 8,589 Nutrition of Children and Adults • 175 11.6 ADULT NUTRITIONAL STATUS 11.6.1 Nutritional Status of Women The 2013 LDHS collected anthropometric data on height and weight for 99 percent of the women age 15-49 who were interviewed in the survey and were eligible for biomarker collection. These data were used to assess low maternal height and body mass index (BMI). Maternal height is an outcome of genetics combined with the effects of nutrition during childhood and adolescence. It helps to predict a risk of difficult delivery because small stature is frequently associated with small pelvic size. The risk of low birth weight babies is also higher for short women. The cutoff point—that is, the height below which a woman is considered to be at risk for poor birth outcomes and obstetric complications—is defined as 145 centimeters. Table 11.9.1 shows that 2 percent of Liberian women age 15-49 measure below this height. Information on BMI is also presented in Table 11.9.1. BMI is calculated by dividing weight in kilograms by height in meters squared (kg/m2). Pregnant women and women who had a birth in the two months preceding the survey were excluded from the calculation of BMI. A BMI cutoff point of 18.5 has been recommended for assessing chronic energy deficiency among nonpregnant women. At the other end of the BMI scale, women are considered overweight if their BMI falls between 25.0 and 29.9 and obese if their BMI is 30.0 or greater. Overall, 66 percent of women have a BMI in the normal range, 7 percent are thin, and 26 percent are overweight or obese. Six percent of women are classified as mildly thin and 2 percent are moderately or severely thin. Nine percent of women in Liberia are classified as obese. Hence, among women of reproductive age, overweight and obesity may be more of a concern than underweight in Liberia. Women in the 15-19 age group are more likely than other women to be thin (BMI below 18.5). The proportion of women who are overweight or obese increases with age and wealth quintile. For example, only 7 percent of women age 15-19 are overweight or obese compared with 45 percent of women age 40-49. Thirty percent of urban Liberian women are overweight or obese, compared with 22 percent of rural women. Montserrado (33 percent) has the highest proportion of overweight or obese women and Lofa (16 percent) the lowest. 176 • Nutrition of Children and Adults Table 11.9.1 Nutritional status of women Among women age 15-49, the percentage with height under 145 cm, the mean BMI, and the percentages with specific BMI levels (normal, thin, and overweight), by background characteristics, Liberia 2013 Background characteristic Height Body Mass Index1 Mean Body Mass Index (BMI) Normal Thin Overweight/obese Number of women Percent- age below 145 cm Number of women 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (mod- erately and severely thin) ≥25.0 (total overweight or obese) 25.0-29.9 (over- weight) ≥30.0 (obese) Age 15-19 3.8 1,000 21.0 77.9 15.0 9.9 5.2 7.1 6.8 0.3 892 20-29 1.8 1,653 22.8 74.4 4.8 4.4 0.5 20.8 15.9 4.9 1,438 30-39 1.6 1,146 24.5 58.0 4.5 3.3 1.2 37.5 25.2 12.3 1,034 40-49 1.9 769 25.5 47.8 7.1 5.8 1.4 45.1 24.8 20.3 746 Residence Urban 2.0 2,737 23.7 63.5 6.9 5.1 1.9 29.6 19.0 10.6 2,487 Greater Monrovia 1.6 1,646 24.1 60.6 6.7 4.6 2.1 32.7 20.2 12.6 1,514 Other urban 2.7 1,091 23.1 68.0 7.3 5.7 1.6 24.7 17.1 7.6 973 Rural 2.4 1,832 22.8 70.3 8.1 6.3 1.8 21.6 16.2 5.4 1,623 Region North Western 2.0 420 23.7 63.0 6.2 5.7 0.5 30.9 21.8 9.1 372 South Central 2.1 2,364 23.8 62.0 7.4 5.1 2.3 30.7 19.8 10.9 2,164 South Eastern A 2.4 241 23.2 69.5 6.7 4.7 1.9 23.8 17.0 6.8 213 South Eastern B 3.1 296 23.2 68.9 5.0 3.4 1.5 26.1 20.1 6.0 259 North Central 2.1 1,247 22.4 74.3 8.6 7.1 1.4 17.2 12.4 4.7 1,102 County Bomi 3.1 121 23.5 60.9 6.9 5.9 1.1 32.2 23.1 9.1 106 Bong 1.8 447 22.3 71.9 10.6 9.5 1.1 17.5 13.0 4.5 394 Gbarpolu 2.2 98 23.1 63.0 10.9 10.1 0.8 26.1 17.4 8.7 88 Grand Bassa 4.3 213 22.6 69.8 9.4 7.3 2.1 20.8 15.0 5.8 193 Grand Cape Mount 1.3 201 24.1 64.1 3.4 3.4 0.0 32.5 23.2 9.3 178 Grand Gedeh 4.4 81 23.3 70.1 5.9 4.8 1.1 24.0 17.3 6.7 74 Grand Kru 2.3 118 23.4 67.7 3.9 3.3 0.6 28.5 22.5 6.0 101 Lofa 1.6 230 22.3 75.6 8.3 6.8 1.5 16.2 11.2 4.9 205 Margibi 1.9 355 23.0 65.2 9.5 6.0 3.5 25.4 18.1 7.2 321 Maryland 3.8 131 23.0 69.8 5.4 2.8 2.6 24.8 18.4 6.4 115 Montserrado 1.9 1,796 24.1 60.4 6.7 4.6 2.1 32.9 20.7 12.2 1,650 Nimba 2.4 571 22.5 75.6 7.1 5.4 1.7 17.3 12.5 4.9 503 River Cess 2.9 69 22.1 75.7 7.7 5.3 2.4 16.5 11.0 5.5 61 River Gee 2.9 47 23.1 69.4 6.4 5.3 1.1 24.3 19.0 5.2 43 Sinoe 0.3 92 23.8 64.1 6.6 4.2 2.4 29.4 21.4 7.9 77 Education No education 3.0 1,528 23.7 63.4 7.1 5.8 1.3 29.5 19.5 10.0 1,357 Primary 2.8 1,372 22.5 69.6 10.7 7.3 3.4 19.7 14.0 5.7 1,210 Secondary and higher 0.9 1,668 23.7 65.9 5.0 4.0 1.1 29.0 19.4 9.6 1,543 Wealth quintile Lowest 3.1 818 22.3 72.1 10.0 7.9 2.1 17.9 14.6 3.4 718 Second 1.9 836 22.6 70.2 9.1 6.9 2.2 20.7 15.0 5.7 739 Middle 2.7 838 23.0 70.5 6.1 4.5 1.5 23.4 16.6 6.8 727 Fourth 2.2 1,036 23.9 64.3 5.1 4.0 1.2 30.5 20.5 10.0 973 Highest 1.2 1,041 24.4 57.2 7.4 5.1 2.3 35.4 20.8 14.6 954 Total 2.2 4,569 23.3 66.2 7.4 5.5 1.8 26.4 17.9 8.6 4,110 Note: The body mass index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). 1 Excludes pregnant women and women with a birth in the preceding two months Figure 11.6 compares the nutritional status among women age 15-49 in 2007 and 2013. The percentage of women who are thin has declined in the last five years from 10 percent to 7 percent. In contrast, the proportion of women who are overweight or obese has increased in the past five years from 21 percent to 26 percent. Nutrition of Children and Adults • 177 Figure 11.6: Trends in nutritional status of women age 15-49 10 21 7 26 Undernutrition (chronic energy deficiency) Overnutrition (overweight/ obese) 2007 LDHS 2013 LDHS Percent 11.6.2 Nutritional Status of Men For the first time in an LDHS, anthropometric data on height and weight were collected for men age 15-49. Overall, this information was successfully collected for 99 percent of the men interviewed during the survey. These data are useful in the calculation of BMI, which can be used as a measure of chronic energy deficiency among men (BMI calculations and cutoff points are the same for men and women). In addition, BMI can be used to measure overweight and obesity, risk factors for nutrition-related chronic diseases such as diabetes mellitus and cardiovascular disease. Table 11.9.2 shows BMI information for Liberian men. Overall, 80 percent of men age 15-49 have a BMI in the normal range, 11 percent are thin, and 9 percent are overweight or obese. Men age 40-49 (15 percent) are more likely to be thin than younger men (9-11 percent), and men with primary education are more likely than all other men to be thin (18 percent versus 7-9 percent). The prevalence of overweight or obesity is higher among urban (12 percent) than rural (6 percent) men, and is higher among men in Grand Kru (16 percent) and Montserrado (14 percent) than among men in the other counties (3-9 percent). Overweight and obesity among men increase with wealth. Overall, however, the prevalence of overweight or obesity among men is strikingly lower than the prevalence among women (9 percent versus 26 percent, respectively). 178 • Nutrition of Children and Adults Table 11.9.2 Nutritional status of men Among men age 15-49, mean body mass index (BMI), and the percentages with specific BMI levels (normal, thin, and overweight), by background characteristics, Liberia 2013 Background characteristic Body Mass Index Mean Body Mass Index (BMI) Normal Thin Overweight/obese Number of men 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (mod- erately and severely thin) ≥25.0 (total overweight or obese) 25.0-29.9 (over- weight) ≥30.0 (obese) Age 15-19 21.4 79.0 11.2 7.4 3.8 9.8 8.4 1.4 1,013 20-29 21.8 80.2 8.6 6.8 1.7 11.2 10.5 0.8 1,566 30-39 21.4 81.7 11.0 8.5 2.5 7.3 5.7 1.6 1,031 40-49 21.1 77.8 15.3 11.0 4.3 6.9 5.5 1.4 439 Residence Urban 21.7 76.9 11.0 8.3 2.7 12.1 10.4 1.8 2,357 Greater Monrovia 22.0 74.9 10.2 8.8 1.4 14.9 12.7 2.2 1,393 Other urban 21.3 79.6 12.2 7.4 4.7 8.2 7.0 1.1 964 Rural 21.3 84.5 9.9 7.3 2.6 5.6 5.2 0.4 1,692 Region North Western 21.5 81.9 10.9 7.5 3.5 7.2 6.5 0.6 363 South Central 21.7 76.6 11.0 8.9 2.1 12.3 10.5 1.8 2,106 South Eastern A 21.4 87.3 7.9 6.2 1.6 4.8 4.5 0.3 250 South Eastern B 21.9 83.1 7.2 5.6 1.7 9.6 8.3 1.3 284 North Central 21.1 83.6 11.0 6.8 4.2 5.3 5.0 0.3 1,046 County Bomi 21.3 79.3 13.7 10.8 2.9 6.9 5.9 1.1 95 Bong 21.4 87.2 7.0 6.0 1.0 5.8 5.4 0.4 384 Gbarpolu 21.6 84.7 8.5 6.4 2.1 6.8 5.5 1.4 94 Grand Bassa 20.6 80.2 15.9 12.1 3.9 3.9 3.9 0.0 201 Grand Cape Mount 21.5 81.9 10.6 6.2 4.4 7.5 7.5 0.0 175 Grand Gedeh 21.3 82.5 10.7 9.2 1.5 6.8 6.8 0.0 80 Grand Kru 22.5 78.1 6.1 5.4 0.6 15.8 12.5 3.3 108 Lofa 21.1 84.3 10.5 7.7 2.7 5.2 4.3 0.9 211 Margibi 21.3 77.8 12.9 9.2 3.7 9.3 7.5 1.8 364 Maryland 21.4 84.9 8.7 6.2 2.4 6.5 6.3 0.1 122 Montserrado 22.0 75.9 9.9 8.5 1.5 14.2 12.1 2.1 1,541 Nimba 20.8 80.3 14.7 7.1 7.6 5.0 5.0 0.0 451 River Cess 21.1 87.9 8.9 7.5 1.4 3.2 3.2 0.0 63 River Gee 21.6 89.3 6.4 4.4 2.0 4.3 4.3 0.0 54 Sinoe 21.8 90.6 5.1 3.3 1.9 4.3 3.6 0.7 107 Education No education 21.6 81.2 9.4 8.0 1.4 9.4 8.9 0.5 527 Primary 20.7 76.7 18.4 11.7 6.6 4.9 4.2 0.7 1,188 Secondary and higher 21.9 81.4 6.8 5.8 1.0 11.7 10.1 1.6 2,334 Wealth quintile Lowest 21.3 85.4 10.1 6.6 3.5 4.5 3.8 0.7 741 Second 21.3 84.7 9.7 7.4 2.3 5.6 5.2 0.4 748 Middle 21.2 81.4 10.8 7.9 2.9 7.8 7.7 0.2 718 Fourth 21.7 75.2 12.4 9.4 3.0 12.4 11.3 1.1 850 Highest 22.0 75.7 9.8 7.7 2.1 14.5 11.5 3.0 992 Total 21.5 80.0 10.6 7.9 2.7 9.4 8.2 1.2 4,049 Note: The body mass index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). 11.7 MICRONUTRIENT INTAKE AMONG MOTHERS Adequate micronutrient intake by women has important benefits for both women and their children. Table 11.10 includes a number of measures that are useful in assessing women’s intake of vitamin A and iron. Breastfeeding children benefit from the micronutrient supplementation that mothers receive, especially vitamin A. The LDHS included questions to ascertain whether mothers had received iron supplements during pregnancy and vitamin A supplements within two months postpartum. Table 11.10 includes measures of vitamin A and iron supplementation among mothers of young children and also presents the proportion of women who took deworming medication while pregnant and who live in households with iodized salt. Nutrition of Children and Adults • 179 Table 11.10 Micronutrient intake among mothers Among women age 15-49 with a child born in the past five years, the percentage who received a vitamin A dose in the first two months after the birth of the last child, the percent distribution by number of days they took iron tablets during the pregnancy of the last child, and the percentage who took deworming medication during the pregnancy of the last child; and among women age 15-49 with a child born in the past five years and who live in households that were tested for iodized salt, the percentage who live in households with iodized salt, by background characteristics, Liberia 2013 Background characteristic Among women with a child born in the past five years: Among women with a child born in the last five years, who live in households that were tested for iodized salt Percentage who received vitamin A dose postpartum1 Number of days women took iron tablets during pregnancy of last birth Percentage of women who took deworming medication during preg- nancy of last birth Number of women None <60 60-89 90+ Don't know/ missing Total Percentage living in house- holds with iodized salt2 Number of women Age 15-19 60.8 2.7 51.8 15.4 17.2 12.9 100.0 52.0 532 97.7 514 20-29 62.6 3.5 43.2 14.6 22.0 16.8 100.0 58.2 2,350 98.1 2,225 30-39 62.4 3.2 44.1 16.9 19.8 16.0 100.0 59.3 1,466 99.4 1,410 40-49 62.6 4.7 45.8 10.8 26.8 11.9 100.0 58.9 421 99.4 406 Residence Urban 67.1 1.9 40.8 16.0 23.8 17.5 100.0 59.8 2,555 98.4 2,436 Greater Monrovia 69.4 0.7 33.6 16.0 29.1 20.6 100.0 60.4 1,332 99.2 1,279 Other urban 64.6 3.3 48.7 15.9 18.0 14.1 100.0 59.2 1,223 97.6 1,157 Rural 56.8 5.1 49.1 14.0 18.2 13.6 100.0 55.7 2,215 98.8 2,119 Region North Western 64.5 2.7 45.1 19.3 26.5 6.4 100.0 59.5 496 99.9 469 South Central 64.4 1.8 37.8 15.4 25.2 19.7 100.0 58.5 2,103 99.4 2,025 South Eastern A 57.5 6.9 50.4 8.2 21.5 13.1 100.0 56.6 328 97.4 309 South Eastern B 45.5 10.9 47.9 9.9 12.9 18.4 100.0 52.6 352 98.5 338 North Central 63.8 3.3 52.1 15.7 15.8 13.0 100.0 58.2 1,491 97.2 1,414 County Bomi 72.6 1.8 24.0 14.8 46.4 13.0 100.0 66.4 128 100.0 122 Bong 65.1 4.4 46.5 10.5 15.4 23.2 100.0 53.7 559 99.7 538 Gbarpolu 49.1 4.0 59.0 6.2 26.3 4.5 100.0 43.6 112 99.7 101 Grand Bassa 57.2 5.9 58.5 4.9 6.9 23.7 100.0 40.6 267 99.6 260 Grand Cape Mount 67.2 2.6 49.5 27.4 16.5 4.0 100.0 63.0 256 100.0 246 Grand Gedeh 68.2 3.5 63.8 12.9 16.6 3.2 100.0 62.0 112 94.4 105 Grand Kru 40.0 13.2 56.1 5.7 13.8 11.2 100.0 58.6 147 98.4 140 Lofa 48.8 3.3 65.8 10.7 11.2 9.0 100.0 59.5 262 98.8 251 Margibi 47.5 3.0 34.6 22.5 31.7 8.1 100.0 65.1 349 100.0 336 Maryland 48.9 8.8 37.9 14.3 9.7 29.3 100.0 44.0 141 99.0 137 Montserrado 69.6 0.8 34.8 15.7 26.9 21.7 100.0 60.1 1,487 99.3 1,429 Nimba 68.5 2.5 51.5 22.1 17.8 6.1 100.0 61.4 670 94.4 624 River Cess 67.5 3.1 40.7 9.4 29.4 17.5 100.0 58.3 92 99.5 85 River Gee 50.4 10.4 51.5 9.9 17.7 10.6 100.0 58.0 63 97.9 61 Sinoe 40.4 12.7 45.4 3.0 20.1 18.8 100.0 50.5 124 98.6 119 Education No education 56.9 5.6 47.7 15.3 17.0 14.4 100.0 57.1 1,862 98.8 1,794 Primary 63.5 3.0 47.7 13.4 20.5 15.3 100.0 57.3 1,428 98.0 1,359 Secondary and higher 68.0 1.0 37.9 16.2 27.2 17.7 100.0 59.6 1,479 98.8 1,402 Wealth quintile Lowest 54.6 6.9 49.5 9.7 16.7 17.2 100.0 52.5 1,052 98.6 990 Second 58.1 4.2 52.8 16.0 14.9 12.1 100.0 56.3 995 98.9 946 Middle 68.1 2.4 48.1 17.4 20.8 11.4 100.0 59.9 1,014 96.9 980 Fourth 64.3 1.3 37.6 18.8 28.3 13.9 100.0 59.8 972 98.9 938 Highest 68.7 1.5 31.4 13.2 27.3 26.6 100.0 62.8 736 100.0 701 Total 62.3 3.4 44.6 15.0 21.2 15.7 100.0 57.9 4,769 98.6 4,555 1 In the first two months after delivery of last birth 2 Excludes women in households where salt was not tested Table 11.10 shows that 62 percent of women with a child born in the five years before the survey received a vitamin A dose in the first two months after the birth of their last child. Supplementation rates were highest among urban women (67 percent), women living in Bomi (73 percent), women with secondary education and higher (68 percent), and women in the highest wealth quintile (69 percent). 180 • Nutrition of Children and Adults As mentioned earlier, pregnant women are more likely to be anemic than other women. Iron status among pregnant women can be improved by means of iron supplements as well as by increased consumption of iron-rich foods and control of parasites and malaria. Table 11.10 shows the percent distribution of women who gave birth during the five years prior to the survey by the number of days they took iron tablets during the pregnancy for their last-born child. Only 3 percent of women did not take iron supplements at all. The majority of women who took supplements took them for less than 60 days (45 percent). One in five women (21 percent) took iron supplements for the recommended period of time (90 days or more). Women living in Grand Bassa were least likely to have taken iron tablets during their last pregnancy for the recommended period of time (7 percent), and women in Bomi were most likely to have done so (46 percent). Nearly six in 10 of women (58 percent) took deworming medication during their last pregnancy. Ninety-nine percent of women with a child born in the past five years live in households using iodized salt. Malaria • 181 MALARIA 12 alaria is one of the leading causes of death in sub-Saharan Africa. Although preventable and curable, the disease remains a major public health problem in Liberia, where it takes its greatest toll on young children and pregnant women. Hospital records suggest that at least 33 percent of all inpatient deaths and 41 percent of inpatient deaths among children under 5 are attributable to malaria (NMCP, 2009). The 2013 LDHS obtained data on a number of topics related to the prevention and treatment of malaria. These include the percentage of households that owned mosquito nets by net type, the percentage of households that received indoor residual spraying (IRS), and the percentages of children under 5 and pregnant women who slept under a net the night before the survey. For women who gave birth in the two years preceding the survey, data also show the percentage who took any SP/Fansidar during pregnancy as part of prenatal care, and the percentage who took two or more doses of SP/Fansidar and received at least one dose from a prenatal care visit. Additionally, for children under 5 who experienced an episode of fever in the two weeks preceding the survey, information is provided on whether they received timely treatment with recommended antimalarial drugs (the same day or the day following onset of fever). According to Liberia’s National Malaria Strategic Plan 2010-15, the current target is for at least 80 percent of patients with uncomplicated malaria to receive early diagnosis and prompt, effective treatment (NMCP, 2011). M Key Findings • Over half (55 percent) of Liberian households own at least one insecticide-treated net (ITN). Only 40 percent of households in Greater Monrovia own at least one ITN compared with 64 percent of other urban households and 61 percent of rural households. • Fifty-four percent of households own at least one long-lasting insecticidal net (LLIN). • Sixty-one percent of households in Grand Bassa, 34 percent in Bong, and 21 percent in Margibi reported that they had received indoor residual spraying during the past 12 months. • Thirty-seven percent of Liberians have access to ITNs; this means that over one-third of the household population could sleep under an ITN if each ITN in the household were used by up to two people. • Overall, 32 percent of the household population slept under an ITN the night before the survey. Among households that owned at least one ITN, 56 percent slept under an ITN the night before the survey. • Among children under age 5 and pregnant women, 38 percent and 37 percent, respectively, slept under an ITN the night before the survey. • Forty-eight percent of women who had their last birth in the two years preceding the survey received intermittent preventive treatment during their pregnancy, that is, they took two or more doses of SP/Fansidar and received at least one during a prenatal care visit. • Among children with fever in the two weeks before the survey, advice and treatment were sought for 71 percent; one in four children (24 percent) was given an artemisinin-combination therapy (ACT), the first- line treatment for uncomplicated malaria in Liberia. 182 • Malaria 12.1 OWNERSHIP OF MOSQUITO NETS The use of insecticide-treated mosquito nets (ITNs) is a primary health intervention designed to reduce malaria transmission in Liberia. An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment, or (2) a net that has been soaked with insecticide within the past 12 months. Long-lasting insecticidal nets (LLINs) are a subset of ITNs. An LLIN is a factory-treated mosquito net made with netting material that has insecticide incorporated within or bound around the fibers. The current generation of LLINs lasts three to five years, after which the net should be replaced. All households in the 2013 LDHS were asked whether they owned mosquito nets, and if so, how many. Table 12.1 shows the household ownership of nets by type (any, ITN, and LLIN) and the average number of nets per household, by background characteristics. Among all households in Liberia, 58 percent possess at least one mosquito net, 55 percent own at least one ITN, and 54 percent own at least one LLIN. Table 12.1 Household possession of mosquito nets Percentage of households with at least one mosquito net (treated or untreated), insecticide-treated net (ITN), and long-lasting insecticidal net (LLIN); average number of nets, ITNs, and LLINs per household; and percentage of households with at least one net, ITN, and LLIN per two persons who stayed in the household last night, by background characteristics, Liberia 2013 Background characteristic Percentage of households with at least one mosquito net Average number of nets per household Number of households Percentage of households with at least one net for every two persons who stayed in the household last night1 Number of households with at least one person who stayed in the household last night Any mosquito net Insecticide- treated mosquito net (ITN)2 Long- lasting insecticidal net (LLIN) Any mosquito net Insecticide- treated mosquito net (ITN)2 Long- lasting insecticidal net (LLIN) Any mosquito net Insecticide- treated mosquito net (ITN)2 Long- lasting insecticidal net (LLIN) Residence Urban 53.1 49.7 49.4 1.0 0.9 0.9 5,289 21.1 19.6 19.6 5,268 Greater Monrovia 42.5 39.5 39.1 0.7 0.6 0.6 3,060 16.3 15.2 15.2 3,051 Other urban 67.6 63.7 63.5 1.3 1.3 1.3 2,229 27.7 25.6 25.5 2,217 Rural 63.8 61.1 60.8 1.2 1.2 1.2 4,044 26.8 25.4 25.3 4,028 Region North Western 71.0 69.3 69.3 1.4 1.3 1.3 909 28.2 27.3 27.3 906 South Central 50.2 47.5 47.2 0.9 0.8 0.8 4,645 20.2 19.2 19.2 4,630 South Eastern A 48.4 45.2 44.9 0.8 0.8 0.8 573 18.1 16.7 16.5 571 South Eastern B 47.9 45.6 45.4 0.9 0.8 0.8 571 15.6 14.7 14.5 568 North Central 70.6 66.1 65.7 1.4 1.3 1.3 2,634 30.9 28.4 28.1 2,620 County Bomi 74.0 70.7 70.7 1.5 1.4 1.4 280 33.5 31.8 31.8 279 Bong 69.4 66.0 66.0 1.4 1.3 1.3 1,118 34.7 32.4 32.4 1,116 Gbarpolu 66.0 64.8 64.7 1.2 1.1 1.1 212 26.7 26.2 26.1 212 Grand Bassa 64.1 60.8 60.6 1.1 1.0 1.0 588 28.9 27.4 27.4 585 Grand Cape Mount 71.5 70.7 70.7 1.4 1.4 1.4 417 25.4 24.8 24.8 415 Grand Gedeh 55.9 54.0 53.7 1.0 1.0 1.0 196 22.2 21.1 20.8 195 Grand Kru 41.1 39.5 39.2 0.8 0.7 0.7 206 10.8 9.9 9.5 206 Lofa 78.2 74.6 74.5 1.7 1.6 1.6 498 36.3 33.5 33.5 495 Margibi 55.7 55.3 55.3 1.0 1.0 1.0 694 20.7 20.2 20.2 691 Maryland 46.9 44.1 44.0 0.8 0.8 0.8 249 14.4 13.8 13.6 248 Montserrado 46.7 43.6 43.2 0.8 0.7 0.7 3,363 18.6 17.5 17.5 3,354 Nimba 68.1 62.1 61.2 1.4 1.3 1.3 1,018 24.2 21.5 20.8 1,009 River Cess 51.7 50.4 50.3 0.9 0.8 0.8 152 14.5 13.9 13.8 151 River Gee 62.2 59.4 59.4 1.2 1.2 1.2 116 26.9 25.5 25.5 114 Sinoe 39.6 34.1 33.6 0.7 0.6 0.6 225 17.1 14.7 14.5 225 Wealth quintile Lowest 55.7 53.1 52.9 1.0 0.9 0.9 2,008 23.7 22.7 22.6 2,000 Second 67.1 64.2 64.0 1.3 1.3 1.3 1,785 28.0 26.3 26.2 1,778 Middle 65.9 61.2 61.0 1.3 1.2 1.2 1,738 26.9 24.5 24.4 1,727 Fourth 54.0 51.8 51.6 0.9 0.8 0.8 2,024 19.6 18.8 18.8 2,015 Highest 47.0 43.4 42.9 0.9 0.9 0.8 1,777 20.3 18.7 18.6 1,776 Total 57.7 54.6 54.3 1.1 1.0 1.0 9,333 23.6 22.1 22.0 9,295 1 De facto household members 2 An insecticide-treated net (ITN) is a factory-treated net that does not require any further treatment (LLIN) or a net that has been soaked with insecticide within the past 12 months. Malaria • 183 Ownership of nets differs markedly by residence, with 50 percent of urban households owning at least one ITN compared with 61 percent of rural households. Households in Greater Monrovia were much less likely to own an ITN compared with other urban regions (40 percent and 64 percent, respectively). Large differences in the percentage of households that own at least one ITN are observed by region and county. Coverage of mosquito nets in Liberia has improved modestly in the last several years. For example, between the 2009 LMIS and the 2013 LDHS, ownership of at least one ITN increased from 47 to 55 percent (Figure 12.1). Figure 12.1 Trends in ITN ownership 47 50 55 2009 LMIS 2011 LMIS 2013 LDHS Percent Although mosquito net ownership is a key indicator of the success of malaria control measures, it is also important to determine if a household has a sufficient number of nets for those sleeping within the home. Households in Liberia own, on average, 1.0 ITNs, nearly all of which are LLINs (1.0 LLIN per household). By assuming that each net is shared by two people in the household, universal net coverage within the population can be measured. Table 12.1 also shows the percentage of households with at least one mosquito net for every two persons who stayed in the household the night before interview. One in five Liberian households has reached universal ITN coverage; that is, 22 percent of households have at least one ITN for every two people who slept in the household the previous night. Rural households (25 percent) are more likely than urban households (20 percent) to own at least one ITN for every two persons who stayed in the household the night before the survey. Differences are also observed by region, county, and wealth quintile. 12.2 INDOOR RESIDUAL SPRAYING Indoor residual spraying (IRS) is part of the National Malaria Control Program’s strategy for Integrated Vector Management (IVM). IRS is the spraying of the interior walls and ceilings of a dwelling with long-lasting insecticide. It reduces the transmission of malaria by killing adult female mosquitoes when they rest on the walls of the dwelling after feeding. In Liberia, IRS implementation started in 2009 and has been incrementally rolled out into select areas. IRS target areas include Mamba-Kaba district in Margibi County; all districts in Grand Bassa except Buchanan City; Careysburg district in Montserrado County; Fuamah, Kokoyah, and Panta-Kpaai districts in Bong 184 • Malaria County; and the Arcelor Mittal concession area in Yekepa, Nimba County. To obtain information on the prevalence of indoor residual spraying, all households interviewed in the 2013 LDHS were asked whether the interior walls of their dwelling had been sprayed during the 12-month period before the survey and, if so, who had sprayed the dwelling. Nationally, 11 percent of households reported receiving IRS in the 12 months before the survey (Table 12.2) compared with 9 percent of Liberian households in the 2011 LMIS. Among all households, 59 percent have received IRS in the past 12 months and/or had at least one ITN. Table 12.2 Indoor residual spraying against mosquitoes Percentage of households in which someone has come into the dwelling to spray the interior walls against mosquitoes (IRS) in the past 12 months, the percentage of households with at least one ITN and/or IRS in the past 12 months, and the percentage of households with at least one ITN for every two persons and/or IRS in the past 12 months, by background characteristics, Liberia 2013 Background characteristic Percentage of households with IRS1 in the past 12 months Percentage of households with at least one ITN2 and/or IRS in the past 12 months Percentage of households with at least one ITN2 for every two persons and/or IRS in the past 12 months Number of households Residence Urban 8.2 53.0 25.6 5,289 Greater Monrovia 1.8 40.5 16.6 3,060 Other urban 17.1 70.2 37.9 2,229 Rural 13.9 66.3 35.6 4,044 Region North Western 0.1 69.3 27.2 909 South Central 12.8 52.4 28.8 4,645 South Eastern A 0.6 45.4 17.0 573 South Eastern B 0.2 45.6 14.7 571 North Central 15.0 72.1 39.0 2,634 County Bomi 0.0 70.7 31.7 280 Bong 34.4 79.8 56.9 1,118 Gbarpolu 0.5 64.8 26.2 212 Grand Bassa 60.6 81.7 70.9 588 Grand Cape Mount 0.0 70.7 24.7 417 Grand Gedeh 0.9 54.0 21.5 196 Grand Kru 0.4 39.6 9.9 206 Lofa 0.1 74.6 33.2 498 Margibi 21.0 65.9 37.0 694 Maryland 0.1 44.1 13.7 249 Montserrado 2.8 44.6 19.7 3,363 Nimba 1.0 62.3 22.2 1,018 River Cess 1.2 50.9 14.6 152 River Gee 0.0 59.4 25.1 116 Sinoe 0.0 34.1 14.7 225 Wealth quintile Lowest 16.9 60.5 35.3 2,008 Second 13.4 68.6 36.0 1,785 Middle 11.6 65.5 32.6 1,738 Fourth 6.5 54.0 23.4 2,024 Highest 4.9 45.8 22.6 1,777 Total 10.7 58.8 29.9 9,333 1 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or nongovernmental organization. 2 An insecticide-treated net (ITN) is a factory-treated net that does not require any further treatment (LLIN) or a net that has been soaked with insecticide within the past 12 months. The prevalence of IRS varies by residence. Rural households were more likely than urban households to report receiving IRS (14 percent and 8 percent, respectively). However, among urban households, a further Malaria • 185 distinction emerges: households in Greater Monrovia are far less likely to receive IRS than those in other urban areas (2 percent and 17 percent, respectively). IRS is inversely correlated with wealth quintile: households in the lowest wealth quintile (17 percent) were more likely to have been sprayed than households in the highest wealth quintile (5 percent). An examination of the prevalence of IRS by geographical areas confirms that the recent IRS campaigns in Liberia reached the targeted areas. By region, the prevalence of IRS was highest in South Central (13 percent) and North Central (15 percent). By county, households in Grand Bassa (61 percent) have the highest IRS coverage, followed by Bong (34 percent) and Margibi (21 percent). Among households that received IRS, spraying was conducted principally by government workers (56 percent) and nongovernmental organizations (26 percent) (data not shown). 12.3 ACCESS TO MOSQUITO NETS The 2013 LDHS presents the proportion of the population that could sleep under an ITN if each ITN in the household were used by up to two people. This population is referred to as having access to an ITN. Coupled with mosquito net usage, ITN access can provide useful information on the magnitude of the behavioral gap between ITN ownership and use, or, in other words, the population with access to an ITN but not using it. If the difference between these indicators is substantial, the program may need to focus on behavior change and how to identify the main drivers/barriers to ITN use in order to design an appropriate intervention. This analysis helps ITN programs determine whether they need to achieve higher ITN coverage, promote ITN use, or both. Table 12.3 shows the percent distribution of the de facto household population by the number of ITNs that the household owns, according to the number of persons who stayed in the household the night before the survey. Table 12.3 Access to an insecticide-treated net (ITN) Percent distribution of the de facto household population by number of ITNs that the household owns, according to number of persons who stayed in the household the night before the survey, Liberia 2013 Number of ITNs Number of persons who stayed in the household the night before the survey Total 1 2 3 4 5 6 7 8+ 0 55.3 49.9 46.5 45.3 41.9 41.0 44.7 41.1 43.3 1 35.5 35.0 33.2 28.0 22.1 19.6 14.3 10.7 19.7 2 7.4 11.9 13.9 17.8 22.4 20.8 19.4 16.1 17.6 3 1.7 3.0 6.1 7.7 12.2 17.2 18.9 22.8 15.3 4 0.0 0.1 0.2 0.8 0.9 0.9 2.0 4.1 1.9 5 0.0 0.1 0.0 0.1 0.3 0.3 0.6 2.7 1.0 6 0.0 0.0 0.1 0.3 0.2 0.2 0.2 2.3 0.9 7+ 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.2 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,006 2,108 3,876 5,638 6,315 6,257 5,358 14,485 45,042 Percent with access to an ITN1 44.7 50.1 42.5 40.8 40.4 39.0 34.1 30.4 37.0 1 Percentage of the de facto household population who could sleep under an ITN if each ITN in the household were used by up to two people Nationally, 37 percent of the Liberian population has access to ITNs. In general, ITN access tends to decrease as household size increases. For example, 50 percent of persons who stayed in households where two people stayed the night before the survey had access to an ITN, whereas 30 percent of persons who stayed in households where eight or more people stayed the night before the survey had access to an ITN. Figure 12.2 presents the percentage of the population with access to an ITN in the household, by select background characteristics. The percentage of the urban population with access to an ITN in the household is 186 • Malaria lower than the percentage of the rural population (33 percent and 42 percent, respectively). Among regions, the percentage of the population with access to an ITN is highest in North Western (49 percent) and lowest in South Eastern B (27 percent). The percentage of the population with access to ITNs also varies by wealth quintile, with those in the highest wealth quintile having the least access to an ITN (29 percent). Figure 12.2 Percentage of the de facto population with access to an ITN in the household 37 33 24 43 42 49 31 28 27 47 36 44 42 34 29 TOTAL RESIDENCE Urban Greater Monrovia Other urban Rural REGION North Western South Central South Eastern A South Eastern B North Central WEALTH QUINTILE Lowest Second Middle Fourth Highest Percent LDHS 2013 12.4 USE OF MOSQUITO NETS Community level protection against malaria helps reduce the spread of the disease and offers an additional level of protection against malaria for those most vulnerable: children under 5 and pregnant women. This section describes use of mosquito nets among all persons in the household, among children under age 5, and among pregnant women. 12.4.1 Use of Mosquito Nets by Persons in the Household Mosquito net coverage of the entire population is necessary to accomplish large reductions in the malaria burden. Although vulnerable groups, such as children under 5 and pregnant women, should still be prioritized, the communal benefits of wide-scale ITN use by older children and adults should be promoted and evaluated by national malaria control programs (Killeen et al., 2007). Malaria • 187 As shown in Table 12.4, overall, 34 percent of the household population slept under a mosquito net the night before the survey; 32 percent slept under an ITN and 32 percent slept under an LLIN. Those age 35 and older report the highest use of ITNs (39 percent), followed by children under 5 (38 percent). Differences by sex are small (33 percent of females slept under an ITN compared with 31 percent of males). More substantial differences are observed by residence, region, and county. For example, although 55 percent of the household population in Lofa slept under an ITN the night before the survey, only 17 percent of the household population in Sinoe and 18 percent of the household population in Grand Kru and Maryland did likewise. Table 12.4 Use of mosquito nets by persons in the household Percentage of the de facto household population who slept the night before the survey under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among the de facto household population in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Liberia 2013 Background characteristic Household population Household population in households with at least one ITN1 Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number Percentage who slept under an ITN1 last night Number Age (in years) <5 40.3 38.1 37.7 44.0 7,261 63.2 4,375 5-14 25.6 24.0 23.9 31.6 13,375 43.0 7,475 15-34 31.9 30.4 29.9 35.6 13,630 55.5 7,454 35-49 41.5 38.6 38.4 45.1 5,905 68.4 3,333 50+ 41.0 39.0 38.8 45.5 4,865 66.0 2,879 Sex Male 32.4 30.7 30.5 37.6 22,317 53.8 12,757 Female 34.8 32.7 32.5 38.7 22,725 58.3 12,760 Residence Urban 30.3 28.1 27.8 33.3 25,438 54.4 13,153 Greater Monrovia 23.2 21.3 20.7 22.9 13,960 53.5 5,555 Other urban 39.1 36.4 36.4 45.8 11,478 55.0 7,598 Rural 37.9 36.4 36.2 44.4 19,604 57.8 12,364 Region North Western 44.2 43.1 43.1 43.2 4,388 60.1 3,150 South Central 27.7 26.2 25.7 34.6 21,487 53.5 10,510 South Eastern A 26.3 24.5 24.4 24.9 2,820 53.0 1,305 South Eastern B 21.7 21.1 21.0 21.1 3,144 44.3 1,495 North Central 44.1 41.1 40.9 49.0 13,203 59.9 9,058 County Bomi 45.5 43.9 43.9 43.9 1,341 61.2 961 Bong 44.6 42.9 42.9 63.4 4,845 61.6 3,374 Gbarpolu 42.1 41.2 41.2 41.2 980 64.3 628 Grand Bassa 33.8 31.8 31.4 71.7 2,371 50.0 1,506 Grand Cape Mount 44.0 43.5 43.5 43.7 2,128 58.4 1,584 Grand Gedeh 37.0 35.2 35.0 36.8 952 63.6 527 Grand Kru 17.9 17.5 17.4 17.6 1,183 40.7 510 Lofa 56.8 54.8 54.8 55.0 2,426 70.0 1,900 Margibi 31.2 31.1 31.1 44.1 3,582 53.9 2,068 Maryland 18.5 18.0 18.0 18.0 1,399 39.8 632 Montserrado 26.0 24.1 23.6 26.7 15,462 54.0 6,911 Nimba 38.1 33.8 33.4 34.5 5,942 53.2 3,778 River Cess 23.7 23.3 23.3 23.9 746 43.5 400 River Gee 38.4 36.7 36.7 36.7 563 58.7 352 Sinoe 19.4 16.6 16.6 16.6 1,121 48.3 386 Wealth quintile Lowest 32.5 31.1 31.0 41.6 8,909 57.2 4,841 Second 40.2 38.5 38.3 45.4 8,923 59.5 5,775 Middle 41.2 38.1 38.0 44.4 8,962 59.6 5,725 Fourth 30.6 29.6 29.5 33.9 9,115 53.2 5,070 Highest 23.9 21.7 20.8 25.7 9,133 48.2 4,106 Total 33.6 31.7 31.5 38.1 45,042 56.0 25,517 Note: Total includes several cases for which information on the age of a household member is missing. 1 An insecticide-treated net (ITN) is a factory-treated net that does not require any further treatment (LLIN) or a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or nongovernmental organization 188 • Malaria Among households with at least one ITN, more than half of the household population (56 percent) slept under the ITN the previous night. Net usage among the population that owns at least one ITN is markedly higher than that of the general population (56 percent and 32 percent, respectively), indicating that ITN ownership increases the likelihood of net usage. Variations in ITN use among those households that own at least one ITN are generally similar to those within the general population. Figure 12.3 presents ownership of, coverage with, access to, and use of ITNs in Liberia. As shown in column 1, 55 percent of households own at least one ITN. However, only 22 percent of households have enough ITNs to cover their entire household population, assuming one ITN is used by two persons (column 2). Among the household population, 37 percent of individuals have access to an ITN (column 3), and 32 percent slept under a mosquito net the night before the survey (column 4). A comparison of columns 1 and 2 indicates that Liberian households do not have a sufficient number of ITNs to cover the population sleeping in the household. A comparison of columns 3 and 4, on the other hand, suggests that ITN access is generally similar to usage. Figure 12.3 Ownership of, access to, and use of ITNs 55 22 37 32 Percentage of households with at least one ITN Percentage of households with at least one ITNs for every two persons who stayed in the household last night* Percentage of the household population with access to an ITN within their household* Percentage of the household population who slept under an ITN Percent LDHS 2013 * Assuming one ITN covers two persons 12.4.2 Use of Existing Mosquito Nets Table 12.5 shows use of existing ITNs. Of all ITNs distributed to households in Liberia, 67 percent were used the night prior to the survey. Variations by background characteristics were generally minor. Malaria • 189 Table 12.5 Use of existing ITNs Percentage of insecticide-treated nets (ITNs) that were used by anyone the night before the survey, by background characteristics, Liberia 2013 Background characteristic Percentage of existing ITNs1 used the night before the survey Number of ITNs1 Residence Urban 67.9 4,695 Greater Monrovia 70.8 1,893 Other urban 65.9 2,803 Rural 66.9 4,769 Region North Western 67.0 1,220 South Central 66.9 3,789 South Eastern A 68.0 444 South Eastern B 63.1 478 North Central 68.6 3,534 County Bomi 64.8 406 Bong 63.6 1,458 Gbarpolu 75.6 234 Grand Bassa 57.9 590 Grand Cape Mount 65.5 590 Grand Gedeh 80.3 193 Grand Kru 64.7 149 Lofa 81.8 777 Margibi 70.9 690 Maryland 59.3 192 Montserrado 67.7 2,498 Nimba 66.3 1,295 River Cess 55.0 123 River Gee 67.1 137 Sinoe 63.1 132 Wealth quintile Lowest 67.0 1,856 Second 68.5 2,251 Middle 68.5 2,135 Fourth 69.3 1,711 Highest 62.6 1,512 Total 67.4 9,464 1 An insecticide-treated net (ITN) is a factory-treated net that does not require any further treatment (LLIN) or a net that has been soaked with insecticide within the past 12 months. 12.4.3 Use of Mosquito Nets by Children Under 5 Malaria is endemic in Liberia. Those living in areas of high malaria transmission acquire immunity to the disease over time (Doolan et al., 2009). Acquired immunity is not the same as sterile immunity—that is, acquired immunity does not prevent infection but rather protects against severe disease and death. Age is an important factor in determining levels of acquired immunity to malaria. For about six months following birth, antibodies acquired from the mother during pregnancy protect children born in areas of endemic malaria. This immunity gradually disappears, and children start to develop their own immunity to malaria. The pace at which immunity develops depends on the exposure to malarial infection, and in high malaria-endemic areas, children are thought to attain a high level of immunity by their fifth birthday. Such children may experience episodes of illness but usually do not suffer from severe, life-threatening malaria. Immunity in areas of low malaria transmission is acquired more slowly. Malaria affects all age groups of the population. 190 • Malaria According to the 2011 LMIS, the prevalence of malaria in children 6-59 months is 45 percent as measured by rapid diagnostic test (RDT) or 28 percent as measured by analysis of blood smears by microscopy. Prevalence among children by county was not estimated in the 2011 LMIS but, by region, prevalence was much lower in Greater Monrovia than elsewhere. The region with the highest prevalence of malaria was South Eastern B (71 percent as measured by RDT and 49 percent as measured by blood smears). These findings imply that the highest malaria transmission areas are in the most rural regions of the country. The National Malaria Control Strategic Plan recognizes that children under 5 and pregnant women are high- risk groups and recommends that they be protected by sleeping under insecticide-treated nets. Table 12.6 shows that overall, only 40 percent of children under 5 slept under a mosquito net the night before the survey, and 38 percent slept under an ITN. Among those in households owning at least one ITN, 63 percent of children under 5 slept under an ITN the night before the survey. The percentage of children who slept under an ITN gradually decreased with increasing age; for example, 48 percent of children under age 1 slept under an ITN compared with 35 percent of children age 4. Differences in the percentages of children who slept under an ITN were observed by residence, region, and county. Notably, only 23 percent of children under 5 residing in South Eastern B region slept under an ITN the night before the survey. Among counties, the percentage of children under 5 who slept under an ITN ranged from a high of 55 percent in Lofa to a low of 16 percent in Sinoe. Malaria • 191 Table 12.6 Use of mosquito nets by children Percentage of children under 5 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among children under 5 in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Liberia 2013 Background characteristic Children under 5 in all households Children under 5 in households with at least one ITN1 Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of children Percentage who slept under an ITN1 last night Number of children Age (in years) <1 50.7 48.4 48.2 54.0 1,448 74.9 935 1 39.7 37.6 37.5 42.8 1,445 65.8 826 2 39.3 36.6 36.3 43.3 1,296 62.6 758 3 36.0 33.6 33.0 40.0 1,531 57.3 898 4 35.9 34.5 34.1 40.4 1,541 55.5 958 Sex Male 41.1 38.7 38.2 44.5 3,767 63.3 2,305 Female 39.3 37.4 37.2 43.6 3,494 63.0 2,070 Residence Urban 39.7 36.7 36.2 41.0 3,617 64.0 2,072 Greater Monrovia 31.0 28.3 27.5 29.8 1,769 62.5 802 Other urban 48.0 44.6 44.6 51.7 1,847 64.9 1,270 Rural 40.8 39.5 39.2 47.1 3,645 62.5 2,302 Region North Western 52.2 51.2 51.2 51.2 813 70.1 594 South Central 36.0 33.8 33.2 42.5 2,950 62.6 1,595 South Eastern A 29.2 27.5 27.3 27.9 516 56.1 253 South Eastern B 23.3 23.1 23.1 23.1 546 45.8 275 North Central 47.6 44.4 44.2 51.6 2,436 65.3 1,657 County Bomi 51.3 49.5 49.5 49.5 213 69.3 153 Bong 48.3 47.1 47.1 66.2 899 68.3 620 Gbarpolu 49.5 48.0 48.0 48.0 177 74.4 114 Grand Bassa 41.5 38.8 37.8 74.5 401 59.8 260 Grand Cape Mount 53.9 53.4 53.4 53.4 423 69.1 327 Grand Gedeh 43.5 42.3 41.9 42.8 166 70.3 100 Grand Kru 18.0 17.9 17.9 18.0 227 39.0 104 Lofa 57.9 55.3 55.3 55.3 389 72.3 298 Margibi 38.5 38.5 38.5 50.4 541 64.3 324 Maryland 22.3 22.2 22.2 22.2 213 45.3 105 Montserrado 34.2 31.6 30.8 34.0 2,009 62.7 1,011 Nimba 43.4 38.5 38.0 38.8 1,147 59.7 738 River Cess 27.4 26.7 26.6 27.5 153 50.3 81 River Gee 37.4 36.7 36.7 36.7 104 57.3 67 Sinoe 19.3 16.4 16.4 16.4 198 44.5 73 Wealth quintile Lowest 35.6 33.8 33.7 43.5 1,752 61.7 961 Second 43.6 42.0 41.6 48.4 1,626 63.6 1,074 Middle 49.5 46.7 46.6 52.0 1,514 70.2 1,007 Fourth 38.7 37.0 37.0 40.7 1,330 60.9 807 Highest 31.3 27.8 26.4 30.8 1,040 55.1 525 Total 40.3 38.1 37.7 44.0 7,261 63.2 4,375 Note: Table is based on children who stayed in the household the night before the interview. 1 An insecticide-treated net (ITN) is a factory-treated net that does not require any further treatment (LLIN) or a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or nongovernmental organization. 192 • Malaria 12.4.4 Use of Mosquito Nets by Pregnant Women In malaria-endemic areas, adults usually have acquired some degree of immunity to severe, life- threatening malaria. However, pregnancy leads to a depression of the immune system so that pregnant women, especially those in their first pregnancy, have a higher risk of malarial infection. Moreover, malaria among pregnant women may be asymptomatic. Malaria during pregnancy is a major contributor to low birth weight, maternal anemia, infant mortality, spontaneous abortion, and stillbirth. Pregnant women can reduce the risk of these adverse effects of malaria by sleeping under insecticide-treated mosquito nets. Table 12.7 shows the use of mosquito nets by pregnant women, by background characteristics. Overall, 40 percent of pregnant women age 15-49 slept under a mosquito net the night before the survey, and 37 percent slept under an ITN. Among pregnant women in households owning at least one ITN, 63 percent slept under an ITN the night before the survey. Differentials in the percentage of pregnant women who slept under an ITN the night before the survey are similar to those described for children under 5. Use of an ITN by pregnant women does not correlate with either education level or wealth quintile. Malaria • 193 Table 12.7 Use of mosquito nets by pregnant women Percentages of pregnant women age 15-49 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls had been sprayed against mosquitoes (IRS) in the past 12 months; and among pregnant women age 15-49 in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Liberia 2013 Background characteristic Among pregnant women age 15-49 in all households: Among pregnant women age 15- 49 in households with at least one ITN1: Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under a LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of pregnant women Percentage who slept under an ITN1 last night Number of pregnant women Residence Urban 37.5 34.0 34.0 38.6 422 62.5 230 Greater Monrovia 31.6 30.5 30.5 30.5 235 (68.4) 105 Other urban 45.0 38.5 38.5 48.9 187 57.6 125 Rural 42.1 40.3 40.2 48.5 394 63.8 249 Region North Western 45.7 45.2 45.2 45.2 93 61.5 68 South Central 36.6 35.2 35.2 41.5 350 65.5 188 South Eastern A 32.5 30.6 30.6 30.6 48 67.7 22 South Eastern B 25.6 24.1 22.8 24.1 55 47.9 28 North Central 45.9 40.5 40.5 51.4 270 63.2 173 County Bomi 34.7 34.7 34.7 34.7 31 (48.9) 22 Bong 50.3 47.0 47.0 72.2 113 (78.4) 68 Gbarpolu (64.0) (64.0) (64.0) (64.0) 15 (75.3) 13 Grand Bassa 42.7 39.0 39.0 77.3 46 (55.2) 32 Grand Cape Mount 47.2 46.2 46.2 46.2 47 (64.6) 33 Grand Gedeh (26.6) (25.2) (25.2) (25.2) 13 * 7 Grand Kru (17.3) (17.3) (14.5) (17.3) 23 * 9 Lofa 61.8 57.1 57.1 57.1 43 68.6 36 Margibi (36.0) (36.0) (36.0) (42.7) 45 (55.1) 29 Maryland 25.5 25.5 25.5 25.5 22 (48.3) 12 Montserrado 35.6 34.4 34.4 35.0 260 70.4 127 Nimba 35.6 27.8 27.8 28.7 114 45.6 70 River Cess (34.5) (34.5) (34.5) (34.5) 15 * 8 River Gee (47.2) (37.6) (37.6) (37.6) 9 * 6 Sinoe 35.0 31.2 31.2 31.2 19 * 7 Education No education 39.7 38.4 38.4 48.6 304 66.8 175 Primary 40.0 35.7 35.7 40.7 290 59.3 175 Secondary and higher 39.4 37.0 36.7 39.7 222 63.6 129 Wealth quintile Lowest 35.8 32.0 32.0 45.2 173 64.7 86 Second 47.0 45.9 45.6 52.1 185 70.7 120 Middle 43.8 38.7 38.7 44.7 184 57.9 123 Fourth 52.3 52.1 52.1 54.1 128 71.3 94 Highest 19.2 16.5 16.5 19.0 146 (42.7) 56 Total 39.7 37.1 37.0 43.4 816 63.2 479 Note: Table is based on women who stayed in the household the night before the interview. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 An insecticide-treated net (ITN) is a factory-treated net that does not require any further treatment (LLIN) or a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or nongovernmental organization 12.5 INTERMITTENT PREVENTIVE TREATMENT OF MALARIA IN PREGNANCY As explained, in areas of high malaria transmission, by the time an individual reaches adulthood, she or he has acquired immunity that protects against severe disease. However, pregnant women—especially those pregnant for the first time—frequently regain their susceptibility to malaria. Although malaria in pregnant 194 • Malaria women may not manifest itself as either febrile illness or severe disease, it is frequently the cause of mild to severe anemia. In addition, malaria during pregnancy can interfere with the maternal-fetal exchange that occurs at the placenta, leading to the delivery of low birth weight infants. In Liberia, NMCP Malaria in Pregnancy policy and guidelines require that pregnant women receive intermittent preventive treatment for malaria in pregnancy (IPTp). Specifically, IPTp is preventive treatment with the antimalarial combination drug SP/Fansidar given once at the beginning of the second trimester of pregnancy and once at the beginning of the third trimester. It is preferable that women receive IPTp during routine prenatal care. Pregnant women who take medicine only to treat an existing case of malaria are not considered to have received IPTp. The NMCP National Malaria Strategic Plan for 2010-2015 highlights the Roll Back Malaria (RBM) goal of achieving IPTp among 80 percent of all pregnant Liberian women by 2010 (NMCP, 2011). Women in the 2013 LDHS who had a live birth in the two years preceding the survey were asked whether they took any antimalarial medications during the pregnancy leading to their most recent birth, and if so, which ones. Women were also asked whether the drugs they took were received during a prenatal care visit. It should be noted that obtaining information about drugs can be difficult because some respondents may not know or remember the name or the type of drug that they received. Table 12.8 shows that 65 percent of women with a live birth in the two years preceding the survey reported taking at least one dose of SP/Fansidar during a prenatal care visit, and 48 percent reported taking two or more doses of SP/Fansidar at least one of which was received during a prenatal care visit. A higher proportion of women in urban areas received two doses of SP/Fansidar, with at least one dose received during a prenatal care visit, when compared with women in rural areas (50 percent and 45 percent, respectively). Differences in IPTp coverage were observed by region and county also. Although the percentage of women who received at least one dose of SP/Fansidar during a prenatal care visit increased with either increasing level of educational attainment (from 61 percent to 67 percent) or increasing wealth quintile (from 58 percent to 71 percent), patterns of coverage were less distinct with two or more doses. There is little difference between the percentage of women who took two or more doses of SP/Fansidar, at least one of which was received during a prenatal care visit, in the 2013 LDHS (48 percent) and the 2011 LMIS (50 percent). Malaria • 195 Table 12.8 Use of intermittent preventive treatment (IPTp) by women during pregnancy Percentage of women age 15-49 with a live birth in the two years preceding the survey who, during the pregnancy preceding the last birth, received any SP/Fansidar during a prenatal care visit, and who took at least two doses of SP/Fansidar and received at least one dose during a prenatal care visit, by background characteristics, Liberia 2013 Background characteristic Percentage who received any SP/Fansidar during a prenatal care visit Percentage who took 2+ doses of SP/Fansidar and received at least one during a prenatal care visit Number of women with a live birth in the two years preceding the survey Residence Urban 67.0 49.9 1,351 Greater Monrovia 68.3 49.1 667 Other urban 65.7 50.7 684 Rural 62.5 45.2 1,299 Region North Western 66.0 50.9 288 South Central 67.4 46.9 1,109 South Eastern A 47.9 35.9 196 South Eastern B 59.5 41.2 197 North Central 66.1 51.5 860 County Bomi 70.1 52.4 68 Bong 68.0 52.1 318 Gbarpolu 47.9 33.5 64 Grand Bassa 58.1 35.6 149 Grand Cape Mount 71.6 57.5 155 Grand Gedeh 49.8 35.1 66 Grand Kru 55.6 32.9 80 Lofa 53.2 39.7 144 Margibi 68.8 45.0 214 Maryland 56.9 45.5 81 Montserrado 68.9 49.7 746 Nimba 69.3 55.3 398 River Cess 47.6 37.3 58 River Gee 74.0 49.9 36 Sinoe 46.4 35.5 73 Education No education 61.4 45.6 1,000 Primary 66.4 49.6 858 Secondary and higher 67.4 48.0 792 Wealth quintile Lowest 58.1 42.1 636 Second 64.9 47.7 567 Middle 67.7 52.8 551 Fourth 65.3 46.5 509 Highest 71.0 50.8 386 Total 64.8 47.6 2,650 12.6 PREVALENCE, DIAGNOSIS, AND PROMPT TREATMENT OF FEVER AMONG CHILDREN In moderate to high-endemic areas of malaria in sub-Saharan Africa, acute clinical disease is almost always confined to young children who suffer high parasite densities. If untreated, this condition can progress very rapidly to severe malaria, which can result in death. The diagnosis of malaria is based on clinical criteria (clinical diagnosis) and supplemented by the detection of parasites in the blood (parasitological or confirmatory diagnosis). Fever is a major manifestation of malaria in young children, although it also accompanies other illnesses. In Liberia, the artemisinin-based combination therapy (ACT) artesunate plus amodiaquine (ASAQ) is the recommended first-line antimalarial drug for uncomplicated malaria. 196 • Malaria In the 2013 LDHS, for each child under 5, mothers were asked if the child had experienced an episode of fever in the two weeks preceding the survey, and if so, whether treatment and advice was sought. Information was also collected about the type and timing of the treatment given. Table 12.9 shows the percentage of children under 5 who had fever in the two weeks preceding the survey. Also shown, among those children under 5 with fever, are the percentage for whom advice or treatment was sought from a health facility, provider, or pharmacy; the percentage of such children who had a drop of blood taken from a finger- or heel-prick (presumably for a malaria test); the percentage who took ACT or any antimalarial drugs; and the percentage who took drugs on the same or next day. Twenty-nine percent of children under 5 had a fever during the two weeks preceding the survey. Prevalence of fever differed little by sex and residence. Children age 6-11 months (38 percent) and those residing in South Eastern B and North Western (37 percent and 36 percent, respectively) are more likely than other children to have had recent fever. Among children with fever, advice or treatment was sought for 71 percent, 42 percent had blood taken from a finger or heel for testing, 24 percent took ACT, 17 percent took ACT the same or next day after the start of the fever, 56 percent took any antimalarial, and 43 percent took an antimalarial the same or next day after the start of the fever. In general, younger children were more likely than older children to be taken to a health facility, provider, or pharmacy for treatment or advice. The percentage of children in urban areas for whom advice or treatment was sought was much higher than the percentage in rural areas (79 percent compared with 64 percent). Treatment-seeking behavior increased with mother’s education level and wealth. With the exception of children under age 6 months, the proportion of children who had blood taken for testing did not vary greatly by age; in contrast, the percentage of children who took ACT increased with age. For example, only 17 percent of children 6-11months took ACT compared with 30 percent of children 36-59 months in age. There is no formulation of ACT made for children under age 6 months; instead, children under 6 months of age (or 5.0 kg) should receive quinine (NMCP, 2011). Accordingly, the proportion of children less than 6 months with fever who took ACT is low (8 percent). Malaria • 197 Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever Percentage of children under 5 with fever in the two weeks preceding the survey; and among children under 5 with fever, the percentage for whom advice or treatment was sought, the percentage who had blood taken from a finger or heel, the percentage who took any artemisinin- based combination therapy (ACT), the percentage who took ACT the same or next day following the onset of fever, the percentage who took antimalarial drugs, and the percentage who took the drugs the same or next day following the onset of fever, by background characteristics, Liberia 2013 Background characteristic Among children under 5: Among children under 5 with fever: Percentage with fever in the two weeks preceding the survey Number of children Percentage for whom advice or treatment was sought1 Percentage who had blood taken from a finger or heel for testing Percentage who took any ACT Percentage who took any ACT the same or next day Percentage who took antimalarial drugs Percentage who took antimalarial drugs the same or next day Number of children Age (in months) <6 18.7 603 76.4 23.9 8.3 6.2 27.9 21.0 113 6-11 38.1 730 72.6 48.4 17.2 10.5 48.2 38.2 278 12-23 33.7 1,272 74.5 46.5 23.4 17.2 60.3 46.1 429 24-35 28.5 1,085 67.1 36.6 24.0 14.4 53.8 39.3 309 36-47 27.3 1,198 71.5 38.5 30.3 20.8 61.8 44.9 327 48-59 23.6 1,159 65.3 45.9 30.1 24.2 62.4 52.1 273 Sex Male 30.4 3,089 72.0 43.0 25.9 18.2 56.9 43.1 938 Female 26.7 2,957 69.8 40.8 21.5 14.9 54.3 42.2 790 Residence Urban 26.3 3,013 79.0 47.1 20.6 14.9 57.3 45.9 793 Greater Monrovia 26.4 1,503 83.0 46.7 15.7 10.7 51.7 39.2 396 Other urban 26.2 1,510 74.9 47.5 25.5 19.1 62.9 52.6 396 Rural 30.8 3,034 64.2 37.6 26.7 18.2 54.4 39.9 935 Region North Western 36.1 663 69.9 32.5 41.1 23.9 63.9 41.8 240 South Central 28.4 2,485 75.3 45.6 16.8 11.9 52.8 41.8 706 South Eastern A 31.1 463 65.2 48.4 23.5 16.1 46.8 32.5 144 South Eastern B 36.7 466 68.8 46.8 30.1 22.8 53.2 41.2 171 North Central 23.7 1,970 67.7 37.5 23.6 18.2 59.5 48.2 467 County Bomi 30.9 160 82.0 40.7 53.2 47.3 71.2 61.4 49 Bong 28.1 739 66.9 36.9 26.4 24.2 57.4 52.5 208 Gbarpolu 40.2 149 57.6 35.3 8.1 3.2 55.7 38.6 60 Grand Bassa 35.1 345 52.2 35.4 12.7 9.4 43.1 33.7 121 Grand Cape Mount 36.8 355 70.9 28.0 51.6 24.5 64.9 35.8 131 Grand Gedeh 28.7 146 66.4 53.4 22.4 11.1 49.8 31.1 42 Grand Kru 33.7 203 61.0 45.4 15.9 12.3 47.2 35.6 68 Lofa 20.3 323 68.0 33.5 29.4 14.5 52.8 33.9 65 Margibi 22.8 448 66.8 42.5 21.8 11.8 62.1 47.8 102 Maryland 37.9 175 71.4 37.4 34.7 24.6 52.5 38.8 66 Montserrado 28.5 1,692 82.9 48.8 16.8 12.6 53.3 42.5 483 Nimba 21.4 908 68.4 39.6 18.6 13.0 64.2 48.3 194 River Cess 31.9 139 58.4 43.2 25.1 17.6 41.8 27.3 44 River Gee 41.3 88 78.6 66.7 48.2 39.3 65.8 56.4 36 Sinoe 32.4 178 69.5 48.8 23.2 18.5 48.5 37.5 58 Mother's education No education 26.7 2,508 65.8 39.0 24.0 16.6 53.2 41.7 670 Primary 29.2 1,846 71.0 41.7 27.4 18.5 58.2 43.3 540 Secondary and higher 30.6 1,693 77.6 46.1 20.1 14.9 56.4 43.2 518 Wealth quintile Lowest 31.4 1,469 59.9 35.2 25.7 18.8 51.8 38.5 460 Second 29.4 1,350 67.7 42.9 28.1 17.8 59.1 44.4 397 Middle 27.2 1,268 72.9 45.6 23.8 15.0 56.0 39.4 345 Fourth 27.0 1,132 83.2 47.3 18.3 13.1 55.6 44.2 306 Highest 26.6 828 80.1 41.3 20.4 18.0 57.5 51.3 220 Total 28.6 6,047 71.0 41.9 23.9 16.7 55.7 42.7 1,728 1 Excludes traditional practitioner and drug peddler/black bagger. 198 • Malaria Table 12.10 shows the sources of advice or treatment for children under 5 with fever in the two weeks preceding the survey. The public sector was the principal source for advice or treatment (41 percent), followed by the private sector (29 percent) and other sources (12 percent). Government health clinics (26 percent) and government hospitals (12 percent) were the primary public sources of advice or treatment. Private hospitals and clinics (14 percent) and pharmacies (13 percent) were the primary private sources of advice or treatment. Drug peddlers/black baggers were the primary other source of advice or treatment (7 percent). Table 12.10 Source of advice or treatment for children with fever Percentage of children under 5 with fever in the two weeks preceding the survey for whom advice or treatment was sought from specific sources; and among children under 5 with fever in the two weeks preceding the survey for whom advice or treatment was sought, the percentage for whom advice or treatment was sought from specific sources, Liberia 2013 Source Percentage for whom advice or treatment was sought from each source: Among children with fever Among children with fever for whom advice or treatment was sought Any public sector source 41.0 51.8 Government hospital 11.5 14.5 Government health center 3.0 3.8 Government health clinic 26.4 33.3 Government community health volunteer 0.1 0.1 Other 0.1 0.2 Any private sector source 28.9 36.5 Private hospital/clinic 14.4 18.2 Pharmacy 12.5 15.7 Private doctor 1.6 2.0 Mobile clinic 0.6 0.7 Other private medical sector 0.1 0.1 Any other source 11.5 14.5 Shop 2.2 2.8 Traditional practitioner 1.7 2.1 Drug peddler/Black bagger 7.4 9.4 Other 0.4 0.5 Number of children 1,728 1,368 As mentioned above, ACT is the first line treatment for uncomplicated malaria. Not all children with fever should necessarily take an ACT because not all have malaria. However, among children with fever who do take an antimalarial, the antimalarial they should receive is ACT. Table 12.11 shows how effectively this policy is being implemented. Among children under 5 with fever in the two weeks preceding the survey who took antimalarial medication, 43 percent took an ACT. Use of ACT generally increased with age, ranging from about one-third of children 6-11 months (36 percent) to about half of children age 36-47 months and age 48-59 months (49 percent and 48 percent, respectively). Males (46 percent) were more likely to receive ACT, as compared with females (40 percent); rural children (49 percent) were more likely than their urban counterparts (36 percent) to receive ACT. By county, ACT usage among children under 5 with fever in the two weeks preceding the survey who took antimalarial medication varied substantially, ranging from 15 percent in Gbarpolu to 80 percent in Grand Cape Mount. Malaria • 199 Table 12.11 Type of antimalarial drugs used Among children under 5 with fever in the two weeks preceding the survey who took any antimalarial medication, the percentages who took specific antimalarial drugs, by background characteristics, Liberia 2013 Background characteristic Percentage of children who took drug: Number of children with fever who took anti- malarial drug Any ACT Quinine SP/ Fansidar Chloroquine Amodiaquine Other anti- malarial Age (in months) <6 (29.7) (24.0) (21.0) (27.6) (30.5) (0.0) 31 6-11 35.7 12.4 5.9 11.4 41.1 0.5 134 12-23 38.8 7.2 6.0 10.8 46.1 0.1 258 24-35 44.6 4.9 2.1 11.4 40.5 1.0 166 36-47 49.0 2.6 6.7 6.2 40.5 0.4 202 48-59 48.3 3.6 3.4 9.0 42.6 0.3 170 Sex Male 45.5 6.9 5.5 8.7 40.6 0.3 534 Female 39.7 6.0 5.5 12.1 44.1 0.4 429 Residence Urban 36.0 6.4 5.6 10.1 47.6 0.0 454 Greater Monrovia 30.4 6.1 7.0 9.7 50.6 0.0 205 Other urban 40.6 6.6 4.4 10.4 45.2 0.1 249 Rural 49.0 6.6 5.4 10.4 37.3 0.7 508 Region North Western 64.3 4.0 3.3 5.4 29.0 0.0 153 South Central 31.9 7.5 6.8 13.5 50.8 0.4 373 South Eastern A 50.3 8.2 4.7 11.1 30.9 2.2 67 South Eastern B 56.5 9.1 5.6 11.0 26.0 0.7 91 North Central 39.6 5.3 5.1 8.2 45.8 0.0 278 County Bomi 74.8 7.3 1.2 1.2 15.5 0.0 35 Bong 46.1 4.4 10.8 5.1 42.8 0.0 119 Gbarpolu 14.5 6.4 13.8 19.2 72.0 0.0 33 Grand Bassa 29.5 20.1 20.0 38.5 50.0 0.0 52 Grand Cape Mount 79.5 1.7 0.0 1.7 17.7 0.0 85 Grand Gedeh 44.9 5.2 0.0 14.9 36.3 0.8 21 Grand Kru 33.8 20.7 15.9 14.7 37.7 2.0 32 Lofa (55.7) (3.1) (0.0) (6.3) (34.9) (0.0) 35 Margibi 35.1 4.5 0.9 13.9 46.7 2.5 63 Maryland 66.2 4.6 0.0 7.5 22.2 0.0 35 Montserrado 31.6 5.6 5.6 8.2 52.0 0.0 257 Nimba 29.0 6.7 1.1 11.6 51.6 0.0 125 River Cess 60.0 6.3 0.0 6.8 26.9 7.0 19 River Gee 73.2 0.0 0.0 10.8 15.9 0.0 24 Sinoe 47.9 11.6 11.4 11.2 29.5 0.0 28 Mother's education No education 45.2 7.0 6.8 10.2 40.6 0.6 356 Primary 47.0 4.9 3.2 10.0 42.8 0.4 314 Secondary and higher 35.6 7.5 6.4 10.6 43.4 0.1 292 Wealth quintile Lowest 49.6 9.1 6.0 11.5 33.9 0.8 239 Second 47.5 4.9 6.1 9.5 40.5 0.7 235 Middle 42.5 2.6 3.4 7.7 47.4 0.1 193 Fourth 32.9 7.4 4.0 11.2 53.9 0.0 170 Highest 35.5 9.2 8.7 11.7 37.0 0.0 127 Total 42.9 6.5 5.5 10.2 42.2 0.4 963 Note: Figures in parentheses are based on 25-49 unweighted cases. ACT = Artemisinin-based combination therapy It is noteworthy that 42 percent of children under 5 with fever in the two weeks preceding the survey who took antimalarial medication reportedly received the antimalarial amodiaquine. In Liberia, ASAQ is colloquially referred to as amodiaquine, making it difficult to distinguish use of the single drug and the combination therapy. Thus, it is possible that many of the children who reportedly received amodiaquine 200 • Malaria actually received ASAQ. If so, this would affect the estimate of children with fever who received ACT. Indeed, if all of the children who were reported to have received amodiaquine actually received ASAQ, among children with fever who took an antimalarial, the proportion who took an ACT would double from 43 percent to 85 percent. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 201 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR 13 iberia has a generalized HIV epidemic with a low prevalence of infection among the adult population. Results from the Estimates and Projection Package and the Spectrum (EPP/Spectrum) model indicate that as of July 2013 an estimated 20,120 Liberians (adults and children), out of a total population of about 3.5 million, are living with the virus. Of these, 68 percent (13,740 persons) are estimated to require antiretroviral therapy (MOHSW and NACP, unpublished results). L Key Findings • Knowledge of AIDS is nearly universal in Liberia. Ninety-seven percent of women and 96 percent of men age 15-49 have heard of AIDS. • Comprehensive knowledge about AIDS is low in Liberia: 37 percent of women and 34 percent of men know that use of condoms and having just one uninfected faithful partner can reduce the chances of getting HIV, know that a healthy-looking person can have HIV, and reject the two most common local misconceptions about HIV transmission or prevention. • Seventy-one percent of women and 52 percent of men age 15-49 know that HIV can be transmitted by breastfeeding. In addition, 58 percent of women and 35 percent of men know that the risk of mother-to-child transmission can be reduced by a mother taking special drugs during pregnancy. • Seven percent of women and 18 percent of men had two or more sexual partners during the 12 months preceding the survey. Among respondents who had two or more partners in the past 12 months, 20 percent of women and 24 percent of men reported using a condom during their most recent sexual intercourse. • The mean number of sexual partners in the lifetime of Liberian women and men age 15 – 49 is 4.3 and 13.1, respectively. • Point prevalence and cumulative prevalence of concurrent sexual partners among women were 3 percent and 6 percent respectively; among men, point prevalence was 8 percent and cumulative prevalence was 15 percent. • Five percent of men had paid for sexual intercourse in the past 12 months; among these men, 61 percent reported using a condom during their most recent paid sexual intercourse. • Seventy-six percent of women and 62 percent of men know where to get an HIV test. Forty-five percent of women and 23 percent of men have ever been tested for HIV and received the results of their last test. • Fifty percent of women and 17 percent of men reported having a sexually transmitted infection (STI) or symptoms of an STI in the 12 months preceding the survey. 202 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior In Liberia, the main routes of HIV transmission are heterosexual contact and transmission from mother to child during pregnancy, childbirth, and breastfeeding. The prevention of mother-to-child transmission (PMTCT) is a priority in the fight against HIV/AIDS in children. The program seeks primary prevention among childbearing women, including prevention of unintended pregnancies, prevention in children through a single-dose nevirapine regimen, and provision of care and follow-up psychosocial support of women. Tracked through prenatal care HIV sentinel surveillance surveys, the HIV prevalence among pregnant women peaked at 5.6 percent in 2006 and declined to 2.6 percent in 2011 (NAC, 2012). The future course of Liberia’s AIDS epidemic depends on many variables: levels of HIV/AIDS- related knowledge among the general population, social stigmatization, risk behavior modification, access to high-quality services for sexually transmitted infections (STIs), provision and uptake of HIV counseling and testing, and access to care and antiretroviral therapy (ART), including prevention and treatment of opportunistic infections. The principal objective of this chapter is to establish the prevalence of relevant knowledge, perceptions, and behaviors at the national level and also within geographic and socioeconomic subpopulations. In so doing, the National AIDS Control Program in Liberia will be able to better target those groups of individuals most in need of information and most at risk of HIV infection. This chapter begins by focusing on the 15-49 age group; it concludes with a discussion of findings about young people age 15-24. 13.1 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS The 2013 LDHS included a series of questions that addressed respondents’ knowledge about HIV and AIDS, their awareness of modes of HIV transmission, and their behaviors to prevent the spread of HIV. Table 13.1 provides information on overall AIDS knowledge in Liberia. The table shows that AIDS awareness is nearly universal in Liberia: 97 percent of women and 96 percent of men have heard of AIDS. This represents an increase in the proportion of adults who have heard of AIDS; according to the 2007 LDHS, slightly lower percentages (89 percent of women and 93 percent of men) had heard of AIDS. Awareness of AIDS varies only modestly by background characteristics such as residence, region, county, education, and wealth quintile. For example, whereas 99 percent of women and 98 percent of men living in urban areas have heard of AIDS, 95 percent of women and 94 percent of men living in rural areas have heard of AIDS. In addition, women and men from Grand Kru (85 percent and 82 percent, respectively) and Lofa (84 percent and 77 percent, respectively) are less likely than those from other counties to have heard of AIDS. The percentages increase with a rising level of education and wealth. HIV/AIDS prevention programs in Liberia focus their messages and efforts on three important aspects of behavior: use of condoms, limiting the number of sexual partners or staying faithful to one partner, and preventing maternal transmission and delaying onset of sexual debut among young people (i.e., abstinence). Table 13.2 shows that 75 percent of both women and men age 15-49 know that consistent use of condoms is a means of preventing the spread of HIV. Seventy-nine percent of women and 78 percent of men know that limiting sexual intercourse to one faithful and uninfected partner can reduce the chances of contracting HIV. The proportion knowing that both those using condoms and limiting sexual intercourse to one uninfected partner reduces risk is 68 percent among both women and men. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 203 Table 13.1 Knowledge of AIDS Percentage of women and men age 15-49 who have heard of AIDS, by background characteristics, Liberia 2013 Background characteristic Women Men Has heard of AIDS Number of women Has heard of AIDS Number of men Age 15-24 97.1 3,722 92.8 1,587 15-19 96.8 2,080 89.3 890 20-24 97.4 1,642 97.4 696 25-29 97.9 1,611 97.0 673 30-39 97.5 2,378 98.8 1,044 40-49 96.9 1,528 98.6 814 Marital status Never married 97.6 2,867 92.7 1,749 Ever had sex 98.3 2,230 97.3 1,171 Never had sex 95.3 637 83.4 578 Married/Living together 97.0 5,386 98.7 2,218 Divorced/Separated/Widowed 97.9 987 98.5 151 Residence Urban 99.1 5,633 97.5 2,413 Greater Monrovia 99.7 3,361 99.0 1,433 Other urban 98.1 2,272 95.4 980 Rural 94.6 3,606 94.3 1,705 Region North Western 98.2 837 98.7 367 South Central 99.3 4,854 98.8 2,149 South Eastern A 94.0 483 94.2 254 South Eastern B 91.3 577 91.7 288 North Central 95.2 2,488 91.5 1,060 County Bomi 97.5 244 97.7 97 Bong 98.2 894 96.7 389 Gbarpolu 97.9 182 100.0 94 Grand Bassa 95.0 434 97.9 204 Grand Cape Mount 98.8 412 98.5 176 Grand Gedeh 97.3 167 97.4 82 Grand Kru 85.4 217 81.9 110 Lofa 83.9 447 76.9 219 Margibi 99.9 744 98.9 364 Maryland 96.8 257 97.6 123 Montserrado 99.7 3,675 99.0 1,582 Nimba 97.2 1,147 94.2 451 River Cess 93.5 135 97.2 64 River Gee 90.0 103 98.1 55 Sinoe 91.2 182 89.9 108 Education No education 94.9 3,066 92.1 533 Primary 97.0 2,875 92.3 1,202 Secondary and higher 99.9 3,298 99.0 2,383 Wealth quintile Lowest 92.5 1,581 93.0 749 Second 94.8 1,624 93.6 753 Middle 98.2 1,779 95.1 728 Fourth 99.7 2,047 99.1 864 Highest 99.7 2,207 98.7 1,024 Total 97.3 9,239 96.2 4,118 Table 13.2 also presents differences in the levels of knowledge of prevention methods by background characteristics. Differences in knowledge by age among women are minor; however young men age 15-19 have markedly lower levels of knowledge than those in older age groups. By marital status, women who have never been married and have never had sex are least likely to know that using condoms and limiting sexual intercourse to one uninfected partner reduces the risk of HIV transmission (55 percent); women who have never been married but have had sex are the most likely to know that using condoms and limiting sexual 204 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior intercourse to one uninfected partner reduces the risk of HIV transmission (72 percent). Among men, those who have never been married and never had sex are least likely to be aware that using condoms and limiting sexually intercourse to one uninfected partner reduces the risk of HIV transmission (36 percent); men who have been married previously are most likely to be aware of HIV prevention methods (84 percent). Table 13.2 Knowledge of HIV prevention methods Percentage of women and men age 15-49 who, in response to prompted questions, say that people can reduce the risk of getting HIV by using condoms every time they have sexual intercourse, and by having one sex partner who is not infected and has no other partners, by background characteristics, Liberia 2013 Background characteristic Women Men Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Number of women Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Number of men Age 15-24 73.2 77.7 66.6 3,722 66.9 70.7 59.3 1,587 15-19 70.6 77.3 64.7 2,080 57.3 62.6 49.1 890 20-24 76.4 78.3 69.1 1,642 79.2 81.1 72.4 696 25-29 80.3 82.5 73.0 1,611 81.1 84.3 75.5 673 30-39 76.0 79.1 68.1 2,378 79.3 80.7 71.9 1,044 40-49 72.7 78.3 65.7 1,528 80.4 85.4 75.8 814 Marital status Never married 74.7 79.1 68.3 2,867 69.1 72.4 61.5 1,749 Ever had sex 77.9 81.9 72.2 2,230 82.2 81.6 74.0 1,171 Never had sex 63.6 69.3 54.5 637 42.8 53.7 36.3 578 Married/Living together 74.9 78.8 67.6 5,386 78.6 82.6 72.8 2,218 Divorced/Separated/ Widowed 77.2 79.9 69.1 987 91.4 85.1 84.3 151 Residence Urban 78.7 82.2 72.0 5,633 78.1 82.1 71.9 2,413 Greater Monrovia 81.4 84.5 75.0 3,361 80.6 86.1 75.5 1,433 Other urban 74.7 78.8 67.4 2,272 74.3 76.3 66.5 980 Rural 69.4 74.1 61.7 3,606 70.8 73.0 63.5 1,705 Region North Western 72.5 72.7 61.7 837 87.5 87.3 82.7 367 South Central 79.1 82.6 72.8 4,854 77.1 81.4 70.7 2,149 South Eastern A 70.6 71.2 60.8 483 78.3 79.0 71.5 254 South Eastern B 64.9 73.2 59.1 577 66.0 68.6 58.4 288 North Central 71.2 77.0 64.2 2,488 68.2 71.5 60.7 1,060 County Bomi 80.0 90.9 78.8 244 85.7 83.4 77.3 97 Bong 78.5 86.5 72.2 894 69.8 72.0 62.4 389 Gbarpolu 69.8 72.6 59.1 182 86.9 89.6 84.4 94 Grand Bassa 52.6 56.7 42.0 434 58.2 63.3 49.0 204 Grand Cape Mount 69.2 61.9 52.8 412 88.8 88.1 84.7 176 Grand Gedeh 70.5 66.4 57.5 167 77.0 79.5 67.4 82 Grand Kru 56.3 69.1 50.9 217 49.2 55.8 44.7 110 Lofa 65.1 76.2 63.5 447 48.8 55.4 40.9 219 Margibi 85.8 91.6 81.7 744 83.7 84.6 75.6 364 Maryland 70.3 76.6 66.0 257 73.3 74.5 62.4 123 Montserrado 80.9 83.9 74.6 3,675 78.0 83.0 72.4 1,582 Nimba 67.9 70.0 58.1 1,147 76.2 78.8 68.8 451 River Cess 77.7 81.0 71.6 135 89.6 92.3 87.6 64 River Gee 69.4 73.3 59.2 103 83.2 80.9 76.9 55 Sinoe 65.3 68.3 56.0 182 72.5 70.6 65.0 108 Education No education 67.5 73.3 60.1 3,066 62.0 62.6 52.6 533 Primary 73.2 77.2 66.1 2,875 64.9 69.6 56.9 1,202 Secondary and higher 83.7 86.0 76.9 3,298 83.1 86.3 77.7 2,383 Wealth quintile Lowest 64.4 69.7 56.2 1,581 66.5 69.6 59.8 749 Second 71.2 75.7 63.4 1,624 72.9 75.3 65.6 753 Middle 73.4 78.2 66.0 1,779 72.6 75.0 63.5 728 Fourth 78.8 80.9 71.3 2,047 79.0 81.1 72.2 864 Highest 83.4 87.1 78.2 2,207 81.2 87.1 77.1 1,024 Total 75.1 79.0 68.0 9,239 75.0 78.3 68.4 4,118 1 Using condoms every time they have sexual intercourse 2 Partner who has no other partners HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 205 By residence, women living in Greater Monrovia are more likely to be knowledgeable about HIV prevention methods than their counterparts residing in either other urban areas or rural areas. The same pattern is true for men. Knowledge that using condoms and limiting sexual intercourse to one uninfected partner are both HIV prevention methods varies across counties, with the lowest percentages in Grand Bassa for women (42 percent) and Lofa for men (41 percent). Better educated and wealthier respondents are generally more knowledgeable of HIV prevention methods than other respondents. Knowledge of HIV prevention methods among women has increased since 2007. According to the 2007 LDHS, 44 percent of women knew that HIV could be prevented by using a condom and by limiting sexual partners; this compares with 68 percent in 2013. Among men, the percentage has remained stable (66 percent in 2007 compared with 68 percent in 2013). As part of the effort to assess HIV/AIDS knowledge, the 2013 LDHS also obtained information on several common misconceptions about HIV transmission. Respondents were asked whether they think it is possible for a healthy-looking person to have HIV and whether people can get HIV from mosquito bites, by supernatural means, or from sharing food with a person who has AIDS. The latter question is especially important because in a recent study among persons living with HIV/AIDS in Liberia, many respondents who had experienced stigma or discrimination believed this occurred because people feared getting infected through casual contact and/or because they do not know the modes of HIV transmission (NAC, 2014). Tables 13.3.1 and 13.3.2 show the proportions of women and men who know that a healthy-looking person can have HIV and who reject common misconceptions about HIV/AIDS transmission. Seventy-three percent of women and 75 percent of men agreed that a healthy-looking person can have HIV. Regarding misconceptions about avenues of infection, only 66 percent of women and 58 percent of men said that HIV cannot be transmitted by mosquito bites. Seventy-nine percent of women and men knew that HIV cannot be transmitted by supernatural means. Also, 75 percent of women and 73 percent of men said a person cannot become infected by sharing food with a person who has AIDS. Two composite measures of HIV/AIDS knowledge are included in Tables 13.3.1 and 13.3.2. The first measure indicates that under half of women (46 percent) and men (43 percent) know that the two most common misconceptions about HIV/AIDS (i.e., HIV can be transmitted by mosquito bites or by sharing food with a person who has AIDS) are incorrect and also are aware that a healthy-looking person can have HIV. The second measure shows that about a third of Liberian women (37 percent) and men (34 percent) have what can be considered comprehensive knowledge of HIV/AIDS prevention and transmission; that is, they know that both condom use and limiting sexual intercourse to one uninfected partner can prevent HIV, they are aware that a healthy-looking person can have HIV, and they reject the two most common local misconceptions (that HIV can be transmitted through mosquitoes and that a person can become infected with HIV by sharing food with a person who has AIDS). 206 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.3.1 Comprehensive knowledge about AIDS: Women Percentage of women age 15-49 who say that a healthy-looking person can have HIV and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of HIV, and the percentage with a comprehensive knowledge about AIDS, by background characteristics, Liberia 2013 Background characteristic Percentage of women who say that: Percentage who say that a healthy looking person can have HIV and who reject the two most common local misconceptions1 Percentage with a comprehensive knowledge about AIDS2 Number of women A healthy- looking person can have HIV HIV cannot be transmitted by mosquito bites HIV cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has AIDS Age 15-24 72.1 66.6 79.8 74.2 45.2 35.7 3,722 15-19 68.0 67.4 78.4 70.8 43.3 34.6 2,080 20-24 77.4 65.7 81.5 78.5 47.5 37.1 1,642 25-29 77.4 69.0 80.9 80.4 51.0 41.5 1,611 30-39 73.2 65.5 78.2 74.6 45.2 36.6 2,378 40-49 67.1 63.3 74.9 69.6 41.1 33.6 1,528 Marital status Never married 73.6 69.4 81.5 75.6 48.2 39.2 2,867 Ever had sex 77.4 71.6 84.2 78.4 51.4 42.4 2,230 Never had sex 60.4 61.9 72.1 65.8 37.1 27.9 637 Married/Living together 71.2 64.4 77.6 74.1 43.9 34.9 5,386 Divorced/Separated/ Widowed 75.8 66.3 76.9 74.7 46.7 38.3 987 Residence Urban 80.4 71.3 82.1 80.6 53.5 43.1 5,633 Greater Monrovia 85.4 74.0 84.4 85.5 60.9 50.0 3,361 Other urban 72.8 67.3 78.6 73.4 42.7 32.8 2,272 Rural 60.1 58.3 73.6 65.3 33.1 26.5 3,606 Region North Western 68.5 57.5 74.2 68.0 38.9 29.6 837 South Central 78.9 71.9 83.0 80.7 54.3 45.1 4,854 South Eastern A 63.4 61.8 76.9 72.1 39.5 29.3 483 South Eastern B 60.2 63.8 75.7 67.8 37.2 29.8 577 North Central 65.8 59.5 73.1 67.1 33.8 25.3 2,488 County Bomi 83.9 70.2 83.4 79.0 57.3 49.7 244 Bong 62.0 62.7 73.9 70.5 34.3 25.7 894 Gbarpolu 57.5 57.9 69.8 65.2 31.5 21.9 182 Grand Bassa 45.9 63.8 71.7 64.7 28.3 20.3 434 Grand Cape Mount 64.2 49.8 70.7 62.8 31.3 21.0 412 Grand Gedeh 68.9 71.5 83.3 76.7 46.0 30.1 167 Grand Kru 55.1 63.6 71.0 59.1 34.7 27.9 217 Lofa 60.1 56.0 74.7 64.8 38.8 35.2 447 Margibi 71.0 67.6 83.0 68.3 41.0 38.3 744 Maryland 62.8 67.7 82.0 77.0 41.8 34.9 257 Montserrado 84.4 73.7 84.3 85.1 60.0 49.4 3,675 Nimba 71.0 58.3 71.9 65.3 31.5 21.2 1,147 River Cess 61.2 54.7 76.4 74.3 35.7 32.2 135 River Gee 64.5 54.5 69.7 63.0 30.8 21.2 103 Sinoe 60.0 58.3 71.3 66.2 36.5 26.4 182 Education No education 59.7 57.5 70.4 63.2 32.4 24.6 3,066 Primary 68.7 62.7 77.8 71.3 38.7 30.5 2,875 Secondary and higher 87.6 77.4 87.3 88.1 63.8 53.0 3,298 Wealth quintile Lowest 52.3 54.8 68.9 60.2 27.2 21.2 1,581 Second 62.6 61.6 74.1 68.2 34.6 27.5 1,624 Middle 74.0 65.1 77.5 73.5 43.6 33.0 1,779 Fourth 78.6 70.8 84.1 79.6 52.7 41.7 2,047 Highest 87.2 74.4 85.3 85.9 61.7 52.4 2,207 Total 72.5 66.2 78.8 74.6 45.5 36.6 9,239 1 Two most common local misconceptions: HIV can be transmitted by mosquito bites and by sharing food with a person who has AIDS. 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about AIDS transmission or prevention. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 207 Table 13.3.2 Comprehensive knowledge about AIDS: Men Percentage of men age 15-49 who say that a healthy-looking person can have HIV and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of HIV, and the percentage with a comprehensive knowledge about AIDS, by background characteristics, Liberia 2013 Background characteristic Percentage of men who say that: Percentage who say that a healthy looking person can have HIV and who reject the two most common local misconceptions1 Percentage with a comprehensive knowledge about AIDS2 Number of men A healthy- looking person can have HIV HIV cannot be transmitted by mosquito bites HIV cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has AIDS Age 15-24 70.3 58.7 77.3 70.0 40.8 28.5 1,587 15-19 61.2 53.2 70.2 61.5 32.2 19.0 890 20-24 81.9 65.6 86.4 80.9 51.8 40.6 696 25-29 79.6 61.9 84.7 78.3 49.0 41.9 673 30-39 77.0 55.9 78.9 75.3 42.4 35.5 1,044 40-49 77.6 57.8 78.9 72.5 42.8 36.4 814 Marital status Never married 70.6 58.9 78.2 71.4 42.7 31.3 1,749 Ever had sex 78.8 63.2 87.0 81.5 49.8 40.0 1,171 Never had sex 54.1 50.1 60.2 50.9 28.5 13.5 578 Married/Living together 77.7 57.5 79.7 74.2 42.6 35.4 2,218 Divorced/Separated/ Widowed 85.7 63.3 84.2 78.5 50.5 45.1 151 Residence Urban 81.1 67.8 83.0 79.6 52.8 41.8 2,413 Greater Monrovia 85.3 75.9 86.6 81.4 60.6 49.6 1,433 Other urban 74.9 56.0 77.7 77.1 41.3 30.5 980 Rural 66.3 44.9 74.0 64.1 29.0 22.9 1,705 Region North Western 74.1 57.0 80.7 71.1 42.4 38.5 367 South Central 82.8 67.2 84.4 78.5 52.2 40.9 2,149 South Eastern A 67.1 54.5 81.5 71.8 37.6 31.0 254 South Eastern B 65.9 43.1 71.1 59.9 29.2 22.7 288 North Central 63.8 45.8 70.0 67.1 29.3 22.3 1,060 County Bomi 81.9 54.7 78.5 76.8 43.9 38.8 97 Bong 70.2 40.8 65.3 65.4 28.3 22.8 389 Gbarpolu 76.6 63.3 77.3 72.1 46.7 42.3 94 Grand Bassa 70.1 42.8 77.8 68.5 27.4 13.9 204 Grand Cape Mount 68.5 54.9 83.7 67.5 39.4 36.3 176 Grand Gedeh 74.5 66.4 89.4 82.5 46.8 34.3 82 Grand Kru 52.1 32.6 61.2 48.8 19.7 13.4 110 Lofa 49.7 31.8 64.8 53.1 19.7 12.5 219 Margibi 79.2 50.1 79.1 71.8 35.8 29.9 364 Maryland 76.2 50.5 74.4 63.9 34.4 26.6 123 Montserrado 85.2 74.3 86.5 81.3 59.2 46.9 1,582 Nimba 65.1 56.9 76.5 75.3 34.9 26.8 451 River Cess 69.5 55.7 86.7 76.9 36.3 34.9 64 River Gee 70.0 47.5 83.6 73.3 36.4 32.4 55 Sinoe 60.0 44.7 72.4 60.6 31.3 26.2 108 Education No education 57.9 38.6 58.8 52.4 22.7 16.5 533 Primary 62.6 45.8 66.9 59.0 25.6 18.8 1,202 Secondary and higher 85.0 69.1 90.0 85.0 56.2 45.6 2,383 Wealth quintile Lowest 60.1 40.9 69.8 59.6 24.7 18.9 749 Second 69.0 45.1 75.6 65.4 29.5 24.0 753 Middle 73.6 55.3 77.8 75.5 40.2 30.1 728 Fourth 81.9 70.0 82.1 80.9 54.0 41.9 864 Highest 85.4 73.0 87.5 80.7 58.8 48.6 1,024 Total 75.0 58.3 79.2 73.2 42.9 34.0 4,118 1 Two most common local misconceptions: HIV can be transmitted by mosquito bites and by sharing food with a person who has AIDS. 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about AIDS transmission or prevention. 208 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Male respondents age 15-19 and female and male respondents who have never been married and never had sex are less likely to have comprehensive knowledge of HIV/AIDS than older male respondents, never- married women and men who have had sex, and those who have been married. Women and men in Greater Monrovia are more likely than those in other urban areas or rural areas to have comprehensive knowledge. By county, comprehensive knowledge is highest among women in Bomi (50 percent) and Montserrado (49 percent) and among men in Montserrado (47 percent). Conversely, comprehensive knowledge is particularly low among women in Gbarpolu, Grand Bassa, Grand Cape Mount, Nimba, and River Gee (20-22 percent) and men residing in Lofa (13 percent), Grand Kru (13 percent), and Grand Bassa (14 percent). Among both women and men, comprehensive knowledge of HIV/AIDS rises steadily with increasing education level and wealth quintile. Although comprehensive knowledge of HIV/AIDS is relatively low in Liberia, a comparison with the 2007 LDHS reveals a slight improvement. According to the 2007 LDHS, comprehensive knowledge among women and men was 19 percent and 32 percent, compared with 37 and 34 percent in 2013, respectively. 13.2 KNOWLEDGE ABOUT MOTHER-TO-CHILD TRANSMISSION In Liberia, a program aimed at preventing mother-to-child-transmission of HIV (PMTCT) has been in place since 2004. With support from the Global Fund and other partners, efforts to strengthen the program kicked off in 2008. The National AIDS Control Program (NACP) dramatically increased the number of sites offering PMTCT services, from 29 in 2008 to 335 in September 2012. Now nearly half of all health facilities providing prenatal care services offer PMTCT services. With these interventions in place, the recent PMTCT impact study estimated the maternal transmission rate among a cohort of HIV/AIDS positive mothers at below 14 percent. In the absence of these interventions, the transmission rate was estimated at 31 percent (NACP and MOHSW, 2013). In accordance with the increase in the availability of PMTCT services, increasing the level of general knowledge about HIV transmission and reducing the risk of transmission using antiretroviral drugs are critical in reducing mother-to-child transmission of HIV (MTCT). To assess knowledge, respondents were asked whether HIV can be transmitted from a mother to a child through breastfeeding and whether a mother with HIV can reduce the risk of transmission to her baby by taking certain drugs during pregnancy. Table 13.4 shows that women are more aware than men that HIV can be transmitted through breastfeeding (71 percent versus 52 percent) and that the risk of MTCT can be reduced by taking special drugs (58 percent versus 35 percent). Overall, 51 percent of women and 27 percent of men are aware both that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs. According to the 2007 LDHS, only 12 percent of women and 14 percent of men were aware both that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs; thus, there has been a substantial increase in knowledge about MTCT in Liberia since 2007. By age, MTCT knowledge levels are highest among women age 20-24 and men age 25-29. Although knowledge levels are higher among women and men who have ever had sex or were ever married than those who never had sex, little difference in knowledge is seen among women who are currently pregnant versus women who are not pregnant. MTCT knowledge is higher among both women and men who live in urban areas compared with those who live in rural areas. Knowledge also varies widely by county, and generally increases with educational attainment and wealth quintile. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 209 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV Percentage of women and men age 15-49 who know that HIV can be transmitted from mother to child by breastfeeding and that the risk of mother-to-child transmission (MTCT) of HIV can be reduced by the mother taking special drugs during pregnancy, by background characteristics, Liberia 2013 Background characteristic Women Men Percentage who know that: Number of women Percentage who know that: Number of men HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy Age 15-24 69.3 56.1 50.7 3,722 46.5 29.1 23.6 1,587 15-19 62.9 47.8 42.4 2,080 40.4 20.4 17.3 890 20-24 77.4 66.6 61.2 1,642 54.3 40.1 31.6 696 25-29 74.1 64.9 56.6 1,611 57.9 44.4 34.4 673 30-39 73.1 58.4 51.8 2,378 54.4 36.0 27.0 1,044 40-49 68.2 53.8 46.5 1,528 56.2 34.9 27.0 814 Marital status Never married 66.8 56.4 49.3 2,867 47.2 32.5 25.9 1,749 Ever had sex 70.3 62.4 54.3 2,230 56.6 42.1 33.0 1,171 Never had sex 54.8 35.3 32.0 637 28.2 12.9 11.4 578 Married/Living together 72.7 58.1 52.2 5,386 56.0 35.6 27.4 2,218 Divorced/Separated/ Widowed 73.3 60.9 52.6 987 56.8 42.2 31.0 151 Currently pregnant Pregnant 73.0 58.9 51.8 765 na na na na Not pregnant or not sure 70.8 57.7 51.3 8,474 na na na na Residence Urban 75.1 65.2 57.8 5,633 54.6 41.0 31.6 2,413 Greater Monrovia 76.7 68.4 59.4 3,361 54.1 44.5 34.7 1,433 Other urban 72.6 60.3 55.3 2,272 55.2 36.0 27.0 980 Rural 64.5 46.4 41.3 3,606 49.0 25.2 20.3 1,705 Region North Western 67.6 45.1 40.5 837 53.7 29.5 24.5 367 South Central 75.3 64.6 57.6 4,854 54.2 39.5 31.3 2,149 South Eastern A 67.0 46.5 41.0 483 48.2 35.3 25.7 254 South Eastern B 60.3 48.1 40.4 577 51.5 31.6 26.5 288 North Central 66.7 53.5 47.4 2,488 49.1 26.6 19.1 1,060 County Bomi 68.8 57.5 50.0 244 56.0 26.2 21.1 97 Bong 64.1 44.7 39.8 894 52.5 27.3 22.9 389 Gbarpolu 61.8 34.4 31.9 182 59.6 51.2 39.4 94 Grand Bassa 64.7 37.1 35.4 434 63.8 29.7 23.2 204 Grand Cape Mount 69.6 42.4 38.8 412 49.3 19.7 18.3 176 Grand Gedeh 72.5 58.7 52.6 167 51.7 51.0 33.5 82 Grand Kru 41.5 41.1 25.8 217 48.6 28.7 26.2 110 Lofa 49.4 47.9 34.4 447 37.4 12.7 10.8 219 Margibi 75.2 65.0 62.0 744 47.7 27.5 23.9 364 Maryland 72.5 55.5 51.9 257 56.2 39.6 30.6 123 Montserrado 76.6 67.7 59.3 3,675 54.5 43.5 34.1 1,582 Nimba 75.5 62.5 58.3 1,147 51.7 32.8 19.9 451 River Cess 66.1 30.6 27.7 135 56.3 19.4 17.3 64 River Gee 69.8 44.3 42.4 103 47.0 19.1 17.6 55 Sinoe 62.7 47.2 40.1 182 40.7 32.9 24.8 108 Education No education 65.4 48.7 43.6 3,066 41.1 18.3 12.5 533 Primary 66.6 52.0 45.7 2,875 46.2 22.4 18.6 1,202 Secondary and higher 79.8 71.4 63.4 3,298 57.8 44.2 34.3 2,383 Wealth quintile Lowest 58.2 38.8 33.3 1,581 48.9 23.5 19.0 749 Second 64.9 48.2 43.5 1,624 50.8 28.1 21.0 753 Middle 73.4 59.5 54.0 1,779 53.2 31.2 25.1 728 Fourth 79.2 69.2 62.7 2,047 48.5 34.9 27.5 864 Highest 74.8 66.7 57.3 2,207 58.3 49.2 37.8 1,024 Total 70.9 57.8 51.3 9,239 52.3 34.5 26.9 4,118 na = Not applicable 210 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior 13.3 ATTITUDES TOWARD PEOPLE LIVING WITH HIV/AIDS Widespread stigma and discrimination against people living with HIV/AIDS can adversely affect both people’s willingness to be tested for HIV and their adherence to antiretroviral therapy (ART). Indeed, HIV/AIDS- related stigma and discrimination undermine HIV prevention efforts by making people afraid to seek out information about how to reduce their risk of exposure to HIV and to adapt safer behavior, in case the inquiry itself raises suspicion about their HIV status. Since 2005, a number of organizations in Liberia have campaigned against stigma and discrimination and fought for improved rights for people living with HIV (NAC, 2014). The reduction of stigma and discrimination in the population is thus an important indicator of the success of programs targeting HIV/AIDS prevention and control. In the 2013 LDHS, respondents who had heard of AIDS were asked a number of questions to assess the level of stigma associated with HIV/AIDS. Respondents were asked about their willingness or unwillingness to buy vegetables from an infected shopkeeper or vendor, to let others know the HIV status of family members, and to take care of a member of their family with AIDS in their own household. They were also asked whether an HIV-positive female teacher who is not sick should be allowed to continue teaching. Tables 13.5.1 and 13.5.2 present results for women and men, respectively. Women and especially men tend to express more accepting attitudes toward HIV-infected relatives than toward shopkeepers or teachers. Sixty-nine percent of women and 74 percent of men would be willing to care for a relative with AIDS in their home. In contrast, only 44 percent of women and 50 percent of men indicate they would buy vegetables from a shopkeeper with HIV, and 49 percent of women and 52 percent of men agreed that a female teacher with HIV should be allowed to continue teaching. Four in ten women (43 percent) and six in ten men (57 percent) indicated that they would not want to keep secret that a family member was infected with HIV. Overall, only 7 percent of women and 14 percent of men expressed accepting attitudes with regard to all four situations (i.e., they would care for a family member with AIDS in their own home, would buy fresh vegetables from a shopkeeper with HIV, would allow an HIV-positive female teacher to continue teaching, and would not want to keep the HIV-positive status of a family member a secret). In contrast, according to the 2007 LDHS, 13 percent of women and 22 percent of men expressed accepting attitudes regarding these same four situations. Thus, since 2007, there has been no measurable improvement, and stigma associated with HIV has perhaps increased. This is of concern because, as previously discussed, stigma prevents or delays persons getting tested for HIV and, among those living with HIV, stigma prevents them from seeking care and treatment services (NACP and MOHSW, 2014). There were associations between stigma levels and most of the background characteristics shown in Tables 13.5.1 and 13.5.2. Accepting attitudes were more common among urban than rural residents. There were marked differences by region and county in the proportions of women and men expressing accepting attitudes. Accepting attitudes on three indicators (i.e., they would care for a family member with AIDS in their own home, would buy fresh food from a shopkeeper with HIV, and would allow an HIV-positive female teacher to continue teaching) generally increased with increasing education level and wealth quintile. The exception was in the percentages of women and men who would not want to keep the HIV-positive status of a family member a secret, which generally was highest among those with no education and those in the lowest two wealth quintiles. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 211 Table 13.5.1 Accepting attitudes toward those living with HIV/AIDS: Women Among women age 15-49 who have heard of AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Liberia 2013 Background characteristic Percentage of women who: Percentage expressing acceptance attitudes on all four indicators Number of respondents who have heard of AIDS Are willing to care for a family member with AIDS in the respondent's home Would buy fresh vegetables from shopkeeper who has HIV Say that a female teacher who has HIV but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with HIV Age 15-24 69.7 43.4 51.3 41.4 6.5 3,614 15-19 67.0 41.0 49.4 40.9 6.2 2,014 20-24 73.1 46.6 53.7 41.9 6.9 1,599 25-29 70.9 48.5 48.4 40.4 6.6 1,577 30-39 68.0 44.5 49.4 43.3 7.7 2,320 40-49 65.7 41.4 42.0 46.0 4.8 1,480 Marital status Never married 69.4 46.3 53.1 39.8 7.6 2,799 Ever had sex 70.9 49.3 54.1 39.6 7.8 2,192 Never had sex 64.0 35.6 49.5 40.9 6.8 607 Married/Living together 68.0 42.5 46.4 44.6 6.3 5,226 Divorced/Separated/Widowed 71.5 47.7 49.0 38.7 5.1 966 Residence Urban 74.0 49.5 55.3 37.7 6.8 5,580 Greater Monrovia 78.4 54.8 60.8 30.9 7.0 3,351 Other urban 67.3 41.7 47.0 47.9 6.5 2,229 Rural 60.4 35.6 38.2 50.2 6.1 3,411 Region North Western 59.9 38.8 41.2 52.3 7.1 822 South Central 76.2 51.7 57.7 33.4 7.1 4,820 South Eastern A 72.2 42.9 51.9 35.1 4.0 454 South Eastern B 71.6 38.1 43.4 46.5 7.7 526 North Central 55.6 32.7 33.9 58.1 5.4 2,368 County Bomi 68.9 60.6 62.9 47.4 11.7 238 Bong 56.4 35.8 31.7 49.8 5.2 878 Gbarpolu 63.7 36.6 37.8 53.2 7.0 178 Grand Bassa 79.5 40.3 34.2 31.1 4.1 412 Grand Cape Mount 52.9 27.1 29.9 54.7 4.4 407 Grand Gedeh 72.1 51.2 60.9 35.2 6.2 162 Grand Kru 59.2 27.4 28.6 61.2 6.6 185 Lofa 50.4 37.4 38.0 61.3 7.4 375 Margibi 64.4 44.9 60.1 44.3 9.2 743 Maryland 79.0 42.8 52.1 38.4 8.4 248 Montserrado 78.3 54.3 59.9 31.4 7.1 3,664 Nimba 56.7 28.7 34.2 63.5 4.9 1,115 River Cess 76.3 41.3 49.0 24.7 0.4 126 River Gee 76.7 47.0 49.5 38.5 8.1 93 Sinoe 69.3 36.0 45.4 42.8 4.6 166 Education No education 59.7 31.4 33.2 51.1 4.5 2,908 Primary 62.9 37.5 42.6 47.0 5.4 2,789 Secondary and higher 81.9 61.4 67.8 31.0 9.4 3,294 Wealth quintile Lowest 60.2 33.5 34.2 49.1 4.5 1,462 Second 60.0 33.5 36.0 53.9 5.8 1,539 Middle 62.3 39.0 42.3 48.1 6.2 1,747 Fourth 73.8 49.7 56.8 38.8 7.0 2,042 Highest 81.2 58.1 65.1 28.9 8.3 2,201 Total 68.8 44.3 48.8 42.5 6.6 8,991 212 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men Among men age 15-49 who have heard of HIV/AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Liberia 2013 Background characteristic Percentage of men who: Percentage expressing acceptance attitudes on all four indicators Number of respondents who have heard of AIDS Are willing to care for a family member with AIDS in the respondent's home Would buy fresh vegetables from shopkeeper who has HIV Say that a female teacher who has HIV but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with HIV Age 15-24 72.3 43.8 47.0 54.1 10.3 1,473 15-19 68.7 37.7 40.6 54.6 8.2 795 20-24 76.5 51.1 54.5 53.6 12.8 679 25-29 76.8 55.5 64.1 55.3 18.7 652 30-39 72.6 49.3 50.9 61.3 15.5 1,032 40-49 77.8 55.1 54.5 55.6 16.8 803 Marital status Never married 73.4 45.6 50.7 51.9 10.5 1,622 Ever had sex 78.5 51.9 58.2 49.4 11.8 1,139 Never had sex 61.3 30.9 33.1 57.8 7.7 482 Married/Living together 74.4 51.7 53.0 59.9 17.0 2,189 Divorced/Separated/Widowed 80.7 59.0 61.0 56.0 17.2 149 Residence Urban 79.6 54.5 60.0 50.7 15.0 2,353 Greater Monrovia 82.1 56.4 67.6 46.8 16.3 1,418 Other urban 75.9 51.5 48.6 56.6 13.1 935 Rural 66.4 42.1 41.2 64.9 13.4 1,607 Region North Western 69.4 45.4 48.2 74.8 21.3 362 South Central 78.0 57.0 63.4 48.9 16.0 2,125 South Eastern A 80.6 53.6 55.6 57.3 17.6 239 South Eastern B 77.1 42.3 44.3 52.7 8.8 264 North Central 65.4 35.4 31.2 67.0 8.9 970 County Bomi 78.0 39.1 57.0 79.9 22.8 95 Bong 50.7 30.7 24.1 65.6 7.1 376 Gbarpolu 81.1 49.1 47.8 59.8 18.6 94 Grand Bassa 68.7 51.7 46.8 62.5 15.1 199 Grand Cape Mount 58.3 46.8 43.6 80.1 22.0 174 Grand Gedeh 81.5 65.1 62.3 51.6 18.4 80 Grand Kru 83.9 30.1 36.1 52.2 7.7 90 Lofa 80.4 36.7 53.9 63.2 11.8 169 Margibi 67.7 58.2 58.2 53.2 17.5 360 Maryland 79.0 53.0 54.1 47.6 10.1 121 Montserrado 81.6 57.4 66.7 46.2 15.8 1,566 Nimba 72.5 39.0 28.4 69.7 9.4 425 River Cess 72.0 54.6 61.8 62.4 22.0 62 River Gee 61.2 38.7 36.2 64.8 8.0 54 Sinoe 85.4 43.5 46.0 58.8 14.2 97 Education No education 54.6 27.6 30.4 68.5 7.6 491 Primary 64.3 34.5 34.3 63.7 10.1 1,110 Secondary and higher 83.0 61.1 65.4 50.6 17.8 2,360 Wealth quintile Lowest 63.4 36.2 36.6 71.5 12.6 697 Second 69.9 40.2 36.6 63.1 11.7 704 Middle 71.7 49.0 49.1 58.7 14.7 692 Fourth 76.4 58.1 60.3 48.2 13.9 856 Highest 84.5 58.2 69.8 47.0 17.6 1,011 Total 74.2 49.5 52.4 56.5 14.4 3,960 HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 213 13.4 ATTITUDES TOWARD NEGOTIATING FOR SAFER SEXUAL RELATIONS WITH HUSBANDS Knowledge about HIV transmission and ways to prevent it is of little use if people feel powerless to negotiate safer sex practices with their partners. The high levels of sexual transmission of HIV make negotiating for safer sex indispensable, especially in marital unions where women’s status is compromised by societal expectations, thereby increasing their vulnerability to HIV transmission. Therefore, in the 2013 LDHS, women and men were asked if they thought that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women or in asking that he use condoms if she knows that he has a sexually transmitted infection (STI). Table 13.6 shows that three in four women (75 percent) and men (74 percent) believe that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with women other than his wives. Eighty-three percent of both women and men believe a woman has a right to ask her husband to use a condom if she knows he has an STI. Differences by background characteristics are generally small. Program designers should therefore take advantage of this acceptance of women as negotiators of safer sex with their husbands. It affords an opportunity to expand and further strengthen messages and interventions that promote preventive practices such as the use of male and female condoms. Table 13.6 Attitudes toward negotiating safer sexual relations with husband Percentage of women and men age 15-49 who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows that he has sexual intercourse with other women, and percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has a sexually transmitted infection (STI), by background characteristics, Liberia 2013 Background characteristic Women Men Woman is justified in: Number of women Woman is justified in: Number of men Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Age 15-24 73.8 81.8 3,722 64.8 73.8 1,587 15-19 72.1 79.2 2,080 57.9 65.1 890 20-24 75.8 85.2 1,642 73.7 84.8 696 25-29 76.5 85.9 1,611 80.8 89.7 673 30-39 74.9 82.8 2,378 79.4 87.3 1,044 40-49 75.0 81.0 1,528 77.7 87.1 814 Marital status Never married 74.8 82.1 2,867 65.4 75.4 1,749 Ever had sex 78.2 87.3 2,230 74.8 87.0 1,171 Never had sex 62.7 63.9 637 46.2 52.1 578 Married/Living together 74.6 83.1 5,386 79.6 87.4 2,218 Divorced/Separated/Widowed 75.3 82.0 987 83.3 90.5 151 Residence Urban 75.8 84.4 5,633 74.2 83.3 2,413 Greater Monrovia 75.1 85.8 3,361 75.5 84.0 1,433 Other Urban 76.9 82.3 2,272 72.3 82.3 980 Rural 73.1 80.0 3,606 73.0 81.2 1,705 Region North Western 67.0 79.6 837 82.1 89.8 367 South Central 78.6 87.0 4,854 77.8 86.2 2,149 South Eastern A 71.6 84.3 483 77.8 88.3 254 South Eastern B 73.4 74.5 577 68.3 79.4 288 North Central 70.8 76.9 2,488 62.9 71.6 1,060 …Continued 214 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.6 Attitudes toward negotiating safer sexual relations with husband—Continued Background characteristic Women Men Woman is justified in: Number of women Man is justified in: Number of men Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI County Bomi 60.6 73.1 244 75.2 83.3 97 Bong 75.0 83.0 894 62.3 72.8 389 Gbarpolu 72.2 80.7 182 89.1 95.2 94 Grand Bassa 79.6 80.0 434 84.5 90.2 204 Grand Cape Mount 68.5 83.0 412 82.1 90.5 176 Grand Gedeh 69.0 83.7 167 78.3 90.0 82 Grand Kru 69.3 61.3 217 70.6 82.5 110 Lofa 64.2 69.6 447 49.4 53.8 219 Margibi 88.2 94.0 744 84.8 93.5 364 Maryland 76.5 80.4 257 69.0 79.1 123 Montserrado 76.5 86.4 3,675 75.3 84.1 1,582 Nimba 70.1 75.0 1,147 70.0 79.3 451 River Cess 78.8 94.6 135 84.3 95.6 64 River Gee 74.3 87.4 103 62.0 74.0 55 Sinoe 68.7 77.3 182 73.6 82.6 108 Education No education 71.0 77.3 3,066 65.3 70.0 533 Primary 74.3 80.2 2,875 64.5 74.3 1,202 Secondary and higher 78.6 89.8 3,298 80.2 89.3 2,383 Wealth quintile Lowest 72.5 77.3 1,581 70.0 76.7 749 Second 72.7 78.8 1,624 71.8 82.9 753 Middle 73.3 80.0 1,779 72.3 82.4 728 Fourth 77.2 87.0 2,047 75.1 81.3 864 Highest 76.7 87.6 2,207 77.6 87.3 1,024 Total 74.7 82.7 9,239 73.7 82.5 4,118 13.5 ATTITUDES TOWARD CONDOM EDUCATION FOR YOUNG PEOPLE Condom use is one of the main strategies for combating the spread of HIV. However, educating young people about condoms is sometimes controversial, with some saying it promotes early sexual experimentation. To gauge attitudes toward condom education, 2013 LDHS respondents were asked whether they thought that children age 12-14 should be taught about using a condom to avoid getting AIDS. Because the focus is on adults’ opinions, results are tabulated for respondents age 18-49. As shown in Table 13.7, 74 percent of women and 62 percent of men support teaching children age 12- 14 about condoms. Among women but not men, younger respondents age 18-24 are more likely than older respondents to support education about condom use. Support for teaching children about condoms is higher in urban areas than rural areas, and varies widely by region and county. Support generally increases with level of education and wealth status. For example, 61 percent of women and 43 percent of men with no education support education of children about condoms; this compares with 86 percent of women and 70 percent of men with secondary education and higher. The level of support for teaching children about condoms has increased from that reported in the 2007 LDHS (60 percent among women age 18-49 and 57 percent among men age 18-49). HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 215 Table 13.7 Adult support of education about condom use to prevent AIDS Percentage of women and men age 18-49 who agree that children age 12-14 years should be taught about using a condom to avoid AIDS, by background characteristics, Liberia 2013 Background characteristic Women Men Percentage who agree Number of women Percentage who agree Number of men Age 18-24 78.1 2,411 60.0 1,000 18-19 77.2 769 52.6 304 20-24 78.5 1,642 63.2 696 25-29 74.3 1,611 64.2 673 30-39 71.8 2,378 64.2 1,044 40-49 69.0 1,528 61.6 814 Marital status Never married 81.8 1,649 61.7 1,164 Married or living together 70.7 5,306 62.5 2,216 Divorced/separated/widowed 76.2 974 66.5 151 Residence Urban 81.2 4,737 66.2 2,049 Greater Monrovia 84.0 2,788 69.2 1,221 Other urban 77.3 1,949 61.9 828 Rural 62.5 3,191 57.0 1,483 Region North Western 69.2 721 60.0 315 South Central 81.4 4,030 67.8 1,811 South Eastern A 66.2 439 65.0 226 South Eastern B 55.5 514 61.3 261 North Central 66.9 2,225 52.2 919 County Bomi 72.3 207 62.9 80 Bong 60.4 817 56.0 354 Gbarpolu 66.6 157 62.2 85 Grand Bassa 52.8 385 68.1 183 Grand Cape Mount 68.6 357 57.2 150 Grand Gedeh 74.9 152 54.6 72 Grand Kru 35.7 202 59.7 101 Lofa 54.6 402 47.0 186 Margibi 86.3 592 61.1 292 Maryland 71.5 219 69.3 108 Montserrado 84.0 3,053 69.2 1,336 Nimba 77.0 1,006 51.1 379 River Cess 72.0 122 73.2 59 River Gee 60.8 94 47.5 51 Sinoe 53.8 165 67.8 95 Education No education 61.4 2,999 42.6 514 Primary 73.7 2,036 54.8 838 Secondary and higher 86.4 2,893 70.0 2,180 Wealth quintile Lowest 56.5 1,440 53.3 675 Second 65.2 1,437 55.5 662 Middle 74.2 1,538 62.5 621 Fourth 82.8 1,762 70.2 726 Highest 85.1 1,752 68.2 847 Total 18-49 73.7 7,928 62.4 3,531 13.6 MULTIPLE SEXUAL PARTNERS Given that most HIV infections in Liberia are contracted through heterosexual contact, information on sexual behavior is important in designing and monitoring intervention programs to control the spread of the epidemic. The 2013 LDHS included questions on respondents’ sexual partners during their lifetimes and over the 12 months preceding the survey. Men were also asked whether they paid for sex during the 12 months 216 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior preceding the interview. In addition, information was collected on women’s and men’s use of condoms during their most recent sexual intercourse with each type of partner. These questions are sensitive, and it is recognized that some respondents may have been reluctant to provide information on recent sexual behavior. Tables 13.8.1 and 13.8.2 show the percentages of women and men, respectively, who had two or more partners in the 12 months preceding the survey. Among those with two or more partners in the past 12 months, the tables also show the percentage that used a condom during their last sexual intercourse. Finally, the tables provide information on the mean number of lifetime sexual partners among those who have ever had sexual intercourse. Seven percent of women had two or more partners in the 12 months before the survey. The proportion of women who had two or more partners is inversely correlated with age: 9 percent of women age 15-24 had two or more partners compared with 3 percent of women age 40-49. Those who were never married (10 percent) or divorced, separated, or widowed (8 percent) were more likely to have multiple partners in the past 12 months than those who were married (5 percent). By residence, women in urban areas, those in South Central, and women in Montserrado, were more likely than their counterparts to have multiple partners. The proportion of women with two or more partners increases with level of educational attainment and generally with wealth. A larger proportion of men than women reported having had more than one sexual partner (18 percent and 7 percent, respectively) at some time in the past 12 months. Men age 20-39, those divorced, separated, and widowed, and those with secondary education and higher were more likely than their counterparts to have had more than one sexual partner in the past 12 months. As would be expected, the proportion of men with multiple sexual partners in the past 12 months was exceptionally high among those in polygynous unions (70 percent). By residence, men in rural areas, those in South Eastern A and B regions, and those in Grand Bassa, River Cess, and River Gee were more likely to have had more than one sexual partner than men living in other areas. Although the likelihood of having more than one sexual partner generally decreased with wealth quintile, the pattern was not uniform. Among respondents who had more than one sexual partner in the past 12 months, men were slightly more likely to report using a condom during their last sexual intercourse than women (24 percent and 20 percent, respectively). On average, men had had 13.1 sexual partners over their lifetimes, and women had had 4.3 partners. Among those with more than one sexual partner in the past 12 months, never-married men were much more likely to report condom use during their most recent sexual intercourse than those who were married (41 percent and 16 percent, respectively). Urban men (30 percent) were also more likely to report using a condom during their last sexual intercourse than rural men (17 percent). Condom use among men during last sexual intercourse varied by region and county, and generally increased with education level and wealth. The mean number of lifetime sexual partners increases with age, with men age 40-49 reporting an average of 17.0 lifetime partners. Among men, those in a polygynous union (19.1 partners), those living in South Eastern A region (19.4), and those living in Grand Gedeh (22.9) had the highest average numbers of lifetime sexual partners. Among women, mean number of lifetime sexual partners also increases with age, with women age 25- 39 reporting an average of 5.0 partners. Among women, those divorced, separated, or widowed and those living in Nimba had the most lifetime partners (5.7 and 6.4, respectively). HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 217 Table 13.8.1 Multiple sexual partners: Women Among all women age 15-49, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse; and the mean number of sexual partners during their lifetime for women who ever had sexual intercourse, by background characteristics, Liberia 2013 Background characteristic All women Among women who had 2+ partners in the past 12 months: Among women who ever had sexual intercourse1: Percentage who had 2+ partners in the past 12 months Number of women Percentage who reported using a condom during last sexual intercourse Number of women Mean number of sexual partners in lifetime Number of women Age 15-24 8.6 3,722 25.6 320 3.3 3,063 15-19 8.6 2,080 27.1 179 2.6 1,449 20-24 8.6 1,642 23.6 142 4.0 1,614 25-29 7.2 1,611 14.2 116 5.0 1,580 30-39 5.1 2,378 14.8 121 5.0 2,321 40-49 2.6 1,528 (2.1) 39 4.7 1,467 Marital status Never married 9.7 2,867 27.3 279 3.8 2,198 Married or living together 4.5 5,386 6.0 241 4.3 5,280 Divorced/separated/widowed 7.8 987 34.6 77 5.7 954 Residence Urban 8.1 5,633 22.9 459 4.8 5,060 Greater Monrovia 9.3 3,361 27.5 313 4.8 2,982 Other urban 6.4 2,272 13.2 146 4.7 2,079 Rural 3.8 3,606 8.6 138 3.7 3,372 Region North Western 3.6 837 10.9 30 3.7 761 South Central 7.9 4,854 26.2 383 4.5 4,317 South Eastern A 2.9 483 (16.5) 14 4.3 468 South Eastern B 3.9 577 16.6 23 3.0 539 North Central 5.9 2,488 5.2 148 4.5 2,347 County Bomi 2.9 244 * 7 2.8 227 Bong 6.0 894 (3.0) 54 3.2 846 Gbarpolu 5.4 182 (23.6) 10 5.6 167 Grand Bassa 3.9 434 * 17 3.7 413 Grand Cape Mount 3.2 412 * 13 3.4 367 Grand Gedeh 4.6 167 * 8 5.8 163 Grand Kru 2.6 217 * 6 3.0 207 Lofa 1.4 447 * 6 2.2 415 Margibi 3.5 744 (15.0) 26 3.7 637 Maryland 4.2 257 (26.8) 11 2.7 234 Montserrado 9.2 3,675 (27.5) 340 4.8 3,267 Nimba 7.6 1,147 6.1 87 6.4 1,086 River Cess 2.1 135 * 3 3.7 130 River Gee 6.0 103 * 6 3.6 98 Sinoe 1.9 182 * 3 3.5 175 Education No education 3.8 3,066 9.1 116 3.9 2,961 Primary 6.3 2,875 12.6 182 4.3 2,420 Secondary and higher 9.1 3,298 28.0 299 4.7 3,050 Wealth quintile Lowest 3.2 1,581 3.2 50 3.9 1,502 Second 4.1 1,624 5.8 67 4.0 1,527 Middle 6.1 1,779 11.3 109 4.6 1,641 Fourth 8.9 2,047 17.3 182 4.7 1,858 Highest 8.5 2,207 36.1 188 4.3 1,904 Total 6.5 9,239 19.6 597 4.3 8,432 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Means are calculated excluding respondents who gave non-numeric responses. 218 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.8.2 Multiple sexual partners: Men Among all men age 15-49, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse; and the mean number of sexual partners during their lifetime for men who ever had sexual intercourse, by background characteristics, Liberia 2013 Background characteristic All men Among men who had 2+ partners in the past 12 months: Among men who ever had sexual intercourse1: Percentage who had 2+ partners in the past 12 months Number of men Percentage who reported using a condom during last sexual intercourse Number of men Mean number of sexual partners in lifetime Number of men Age 15-24 12.1 1,587 32.4 193 6.8 967 15-19 4.4 890 (21.6) 39 3.6 359 20-24 22.1 696 35.2 154 8.7 608 25-29 23.5 673 31.4 158 13.1 598 30-39 22.6 1,044 15.6 236 16.7 908 40-49 17.1 814 16.0 139 17.0 687 Marital status Never married 11.6 1,749 41.1 203 8.2 1,102 Married or living together 21.3 2,218 15.9 472 15.5 1,918 Divorced/separated/widowed 33.7 151 (25.6) 51 17.8 139 Type of union In polygynous union 69.7 126 5.9 88 19.1 106 In non-polygynous union 18.4 2,092 18.2 385 15.3 1,813 Not currently in union 13.4 1,900 38.0 254 9.2 1,241 Residence Urban 15.7 2,413 29.7 379 11.8 1,811 Greater Monrovia 13.2 1,433 30.6 189 9.6 1,083 Other urban 19.4 980 28.8 190 15.1 728 Rural 20.4 1,705 16.9 347 14.7 1,349 Region North Western 16.1 367 16.3 59 13.6 284 South Central 16.6 2,149 27.6 357 11.6 1,664 South Eastern A 21.8 254 21.8 55 19.4 203 South Eastern B 20.9 288 21.2 60 11.5 229 North Central 18.4 1,060 19.8 195 14.8 780 County Bomi 12.3 97 * 12 5.9 63 Bong 23.2 389 22.4 90 16.4 255 Gbarpolu 10.5 94 (11.4) 10 11.8 71 Grand Bassa 27.4 204 23.9 56 16.0 176 Grand Cape Mount 21.1 176 15.4 37 17.7 150 Grand Gedeh 15.6 82 (27.6) 13 22.9 70 Grand Kru 21.5 110 19.3 24 8.4 79 Lofa 6.6 219 * 14 6.6 149 Margibi 18.7 364 24.3 68 15.7 284 Maryland 17.6 123 (27.4) 22 11.9 107 Montserrado 14.8 1,582 29.4 233 10.0 1,203 Nimba 19.9 451 15.6 90 17.0 376 River Cess 29.5 64 21.1 19 16.0 55 River Gee 27.4 55 15.1 15 15.9 43 Sinoe 21.8 108 19.3 24 18.5 78 Education No education 17.7 533 11.8 95 13.6 433 Primary 14.1 1,202 16.2 170 12.9 771 Secondary and higher 19.4 2,383 28.7 462 13.0 1,955 Wealth quintile Lowest 20.7 749 17.6 155 15.1 614 Second 17.7 753 17.6 133 14.8 584 Middle 18.8 728 14.6 137 12.7 541 Fourth 17.4 864 31.8 150 13.5 626 Highest 14.7 1,024 35.1 151 10.0 795 Total 17.6 4,118 23.6 726 13.1 3,160 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Means are calculated excluding respondents who gave non-numeric responses. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 219 Point prevalence and cumulative prevalence of concurrent sexual partners are new concepts that were incorporated for the first time in the 2013 LDHS. The point prevalence of concurrent sexual partners is defined as the percentage of respondents who had two (or more) sexual partners concurrently at the point in time six months before the survey. The cumulative prevalence of concurrent sexual partners is defined as the percentage of respondents who had two (or more) sexual partners concurrently at any time during the 12 months preceding the survey. Table 13.9 shows the point prevalence and cumulative prevalence of concurrent sexual partners among all respondents during the 12 months before the survey. It also shows the percentage of respondents who had concurrent sexual partners among those who had multiple sexual partners during the 12 months before the survey. Among women, point prevalence and cumulative prevalence were 3 and 6 percent respectively; among men, point prevalence was 8 percent and cumulative prevalence was 15 percent. Among female respondents, point prevalence and cumulative prevalence were higher in urban areas than rural areas; in contrast, among male respondents point prevalence and cumulative prevalence were higher in rural areas than urban areas. Men in polygynous unions had the highest cumulative prevalence (66 percent), and those not currently in a union had the lowest (10 percent). Not surprisingly, cumulative prevalence rates were much higher among respondents who reported having multiple partners during the 12 months before the survey than those who did not report multiple partners (86 percent versus 6 percent among women and 83 percent versus 15 percent among men). 220 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.9 Point prevalence and cumulative prevalence of concurrent sexual partners Percentage of all women and men age 15-49 who had concurrent sexual partners six months before the survey (point prevalence1), and percentage of all women and all men age 15-49 who had any concurrent sexual partners during the 12 months before the survey (cumulative prevalence2), and among women and men age 15-49 who had multiple sexual partners during the 12 months before the survey, percentage who had concurrent sexual partners, by background characteristics, Liberia 2013 Background characteristic Among all respondents: Among all respondents who had multiple partners during the 12 months before the survey: Point prevalence of concurrent sexual partners1 Cumulative prevalence of concurrent sexual partners2 Number of respondents Percentage who had concurrent sexual partners2 Number of respondents WOMEN Age 15-24 3.3 6.8 3,722 79.5 320 15-19 2.7 6.5 2,080 75.8 179 20-24 4.2 7.2 1,642 84.1 142 25-29 4.8 6.9 1,611 96.7 116 30-39 3.6 4.7 2,378 91.1 121 40-49 1.6 2.4 1,528 (92.5) 39 Marital status Never married 4.4 8.1 2,867 83.0 279 Married or living together 2.6 4.2 5,386 92.9 241 Divorced/separated/widowed 4.5 5.9 987 75.7 77 Residence Urban 4.6 7.1 5,633 87.7 459 Greater Monrovia 5.7 8.4 3,361 90.6 313 Other urban 3.0 5.2 2,272 81.3 146 Rural 1.5 3.1 3,606 80.7 138 Total 3.4 5.6 9,239 86.0 597 MEN Age 15-24 3.8 9.0 1,587 74.2 193 15-19 0.7 3.2 890 (72.4) 39 20-24 7.7 16.5 696 74.7 154 25-29 9.0 18.9 673 80.5 158 30-39 11.8 19.3 1,044 85.1 236 40-49 10.6 15.9 814 93.2 139 Marital status Never married 3.7 8.7 1,749 75.5 203 Married or living together 11.5 18.7 2,218 87.7 472 Divorced/separated/widowed 7.2 22.5 151 (66.5) 51 Type of union In polygynous union 58.4 65.8 126 94.4 88 In non-polygynous union 8.6 15.8 2,092 86.2 385 Not currently in union 4.0 9.8 1,900 73.7 254 Residence Urban 6.4 12.8 2,413 81.4 379 Greater Monrovia 5.4 10.6 1,433 80.3 189 Other urban 7.9 16.0 980 82.4 190 Rural 10.3 17.2 1,705 84.4 347 Total 8.0 14.6 4,118 82.8 726 Note: Two sexual partners are considered to be concurrent if the date of the most recent sexual intercourse with the earlier partner is after the date of the first sexual intercourse with the later partner. Figures in parentheses are based on 25-49 unweighted cases. 1 The percentage of respondents who had two (or more) sexual partners that were concurrent at the point in time 6 months before the survey 2 The percentage of respondents who had two (or more) sexual partners that were concurrent anytime during the 12 months preceding the survey 13.7 PAID SEX The act of paying for sex introduces an uneven negotiating ground for safer sexual intercourse. Condom use is an important indicator in efforts to ascertain the level of risk associated with sexual intercourse involving payments. Table 13.10 presents information on the extent to which men ever engaged in paid sex, HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 221 engaged in paid sex in the 12-month period before the survey, and used a condom during the last paid sexual intercourse in the 12-month period before the survey. Table 13.10 Payment for sexual intercourse and condom use at last paid sexual intercourse Percentage of men age 15-49 who ever paid for sexual intercourse and percentage reporting payment for sexual intercourse in the past 12 months, and among them, the percentage reporting that a condom was used the last time they paid for sexual intercourse, by background characteristics, Liberia 2013 Background characteristic Among all men: Among men who paid for sex in the past 12 months: Percentage who ever paid for sexual intercourse Percentage who paid for sexual intercourse in the past 12 months Number of men Percentage reporting condom use at last paid sexual intercourse Number of men Age 15-24 7.1 4.6 1,587 63.2 73 15-19 2.6 1.7 890 * 15 20-24 12.8 8.3 696 69.4 58 25-29 13.9 7.2 673 (58.8) 48 30-39 11.9 4.7 1,044 67.7 49 40-49 8.3 3.0 814 (46.3) 24 Marital status Never married 7.9 5.2 1,749 68.1 91 Married or living together 10.4 4.3 2,218 54.8 94 Divorced/separated/widowed 18.5 6.1 151 * 9 Residence Urban 10.3 4.6 2,413 69.7 112 Greater Monrovia 10.2 4.0 1,433 * 58 Other urban 10.5 5.5 980 57.8 54 Rural 8.7 4.9 1,705 49.7 83 Region North Western 9.5 4.8 367 (51.5) 18 South Central 10.5 4.1 2,149 75.3 88 South Eastern A 11.6 8.9 254 55.6 23 South Eastern B 11.0 6.3 288 (40.1) 18 North Central 7.2 4.6 1,060 (49.5) 48 County Bomi 10.9 6.0 97 * 6 Bong 4.2 3.2 389 * 12 Gbarpolu 7.4 5.2 94 * 5 Grand Bassa 13.1 5.4 204 * 11 Grand Cape Mount 9.9 4.0 176 * 7 Grand Gedeh 10.0 8.9 82 * 7 Grand Kru 12.2 9.9 110 * 11 Lofa 1.7 0.9 219 * 2 Margibi 9.3 3.1 364 * 11 Maryland 9.6 4.1 123 * 5 Montserrado 10.4 4.1 1,582 (78.4) 66 Nimba 12.5 7.5 451 * 34 River Cess 10.6 7.1 64 * 5 River Gee 11.5 3.9 55 * 2 Sinoe 13.5 9.9 108 (60.8) 11 Education No education 7.0 4.3 533 (51.1) 23 Primary 6.8 3.3 1,202 47.4 40 Secondary and higher 11.7 5.5 2,383 67.1 131 Wealth quintile Lowest 8.5 5.0 749 41.4 38 Second 8.5 5.2 753 48.2 39 Middle 8.0 4.5 728 (48.7) 33 Fourth 11.0 4.1 864 (83.9) 36 Highest 11.3 4.8 1,024 (78.4) 49 Total 9.6 4.7 4,118 61.2 195 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 222 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Ten percent of men reported ever paying for sex; 5 percent reported paying for sex at least once during the 12 months preceding the survey. Men age 25-29 (14 percent), divorced/separated/widowed men (19 percent), and men living in Sinoe (14 percent) were most likely to have ever paid for sex. Payment for sexual intercourse was higher among men with secondary and higher education and men in the fourth and highest wealth quintiles relative to men with no education or primary education and those in lower wealth quintiles, although differences are small. Men from Sinoe (10 percent) had the highest rate of paid sex during the 12 months preceding the survey. Sixty-one percent of men who had engaged in paid sex in the past 12 months used a condom the last time they paid for sex. A comparison of the 2007 and 2013 LDHS results suggests that while there has been a minor increase in the percentage of men who paid for sex in the 12 months preceding the interview, those who did engage in paid sex were more likely to use a condom. Specifically, in 2007, 3 percent of men had paid for sex in the preceding 12 months and 48 percent of them reported condom use, whereas in 2013, 5 percent of men paid for sex in the last 12 months and 61 percent used a condom the last time they paid for sex. Although the number of men paying for sex has increased, the increase in condom use among them is encouraging. 13.8 COVERAGE OF HIV TESTING SERVICES Knowledge of HIV status helps HIV-negative individuals make specific decisions to reduce risk and increase safer sex practices so that they can remain disease-free. Among those who are HIV infected, knowledge of their status allows them to take action to protect their sexual partners, to access treatment, and to plan for the future. To assess awareness and coverage of HIV testing services, 2013 LDHS respondents were asked whether they had ever been tested for HIV. If they said that they had been tested, they were asked whether they had received the results of their last test and where they had been tested. If they had never been tested, they were asked whether they knew a place where they could go to be tested. Tables 13.11.1 and 13.11.2 show that the majority of respondents (76 percent of women and 62 percent of men) knew of a place where they could get an HIV test. Younger respondents (age 15-19) were less likely than those age 20-49 to know a place where they could go to be tested. Never-married respondents who had never had sex were less likely than others to know a place to get an HIV test. Knowledge of a place to get an HIV test increased with both increasing education and wealth quintile and was more common among urban than rural residents. Differences among regions and counties are also observed. Tables 13.11.1 and 13.11.2 also show the coverage of HIV testing services. A larger proportion of men (74 percent) than women (49 percent) had never been tested. Most of those who had been tested said that they had received the results of the last test they took. Overall, 45 percent of women and 23 percent of men had been tested and had received the results of the last test. Among women, the likelihood of having ever had an HIV test and receiving the results was highest in the 25-29 age group (60 percent); among men rates were highest among those age 40-49 (32 percent). Not surprisingly, the percentages of women and men who had ever had an HIV test and received the results was much lower among those who were never married and never had sex (4 percent of women and 1 percent of men) than among those who were ever married or were never married but ever had sex. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 223 Table 13.11.1 Coverage of prior HIV testing: Women Percentage of women age 15-49 who know where to get an HIV test, percent distribution of women age 15-49 by testing status and by whether they received the results of the last test, the percentage of women ever tested, and the percentage of women age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Liberia 2013 Background characteristic Percentage who know where to get an HIV test Percent distribution of women by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 71.3 37.6 4.0 58.4 100.0 41.6 18.3 3,722 15-19 62.2 24.0 2.9 73.1 100.0 26.9 13.1 2,080 20-24 82.8 54.9 5.3 39.8 100.0 60.2 24.9 1,642 25-29 86.2 59.5 7.8 32.6 100.0 67.4 26.0 1,611 30-39 80.6 52.4 7.5 40.1 100.0 59.9 19.8 2,378 40-49 70.6 36.7 5.0 58.3 100.0 41.7 12.6 1,528 Marital status Never married 69.9 31.3 3.3 65.4 100.0 34.6 15.2 2,867 Ever had sex 77.7 39.2 4.2 56.6 100.0 43.4 18.7 2,230 Never had sex 42.8 3.5 0.3 96.2 100.0 3.8 3.1 637 Married/Living together 78.9 52.0 6.9 41.2 100.0 58.8 21.6 5,386 Divorced/Separated/Widowed 79.2 47.7 6.6 45.7 100.0 54.3 16.7 987 Residence Urban 82.4 49.1 4.8 46.1 100.0 53.9 19.9 5,633 Greater Monrovia 85.3 50.8 4.3 44.9 100.0 55.1 19.7 3,361 Other urban 78.1 46.5 5.4 48.0 100.0 52.0 20.2 2,272 Rural 66.4 38.8 7.3 53.9 100.0 46.1 17.9 3,606 Region North Western 72.7 44.2 6.9 48.9 100.0 51.1 22.6 837 South Central 80.9 47.5 4.4 48.1 100.0 51.9 19.0 4,854 South Eastern A 75.0 49.6 7.7 42.8 100.0 57.2 24.6 483 South Eastern B 55.3 29.9 8.4 61.7 100.0 38.3 16.1 577 North Central 73.1 43.2 7.0 49.8 100.0 50.2 17.7 2,488 County Bomi 76.7 52.4 4.9 42.7 100.0 57.3 27.1 244 Bong 70.0 41.8 9.6 48.6 100.0 51.4 14.3 894 Gbarpolu 66.2 32.4 8.2 59.4 100.0 40.6 14.9 182 Grand Bassa 55.2 30.4 6.3 63.3 100.0 36.7 14.3 434 Grand Cape Mount 73.2 44.5 7.4 48.0 100.0 52.0 23.5 412 Grand Gedeh 82.6 60.0 5.6 34.4 100.0 65.6 31.5 167 Grand Kru 45.7 27.0 5.1 67.9 100.0 32.1 13.2 217 Lofa 57.8 30.8 7.6 61.6 100.0 38.4 18.5 447 Margibi 78.0 46.3 3.2 50.5 100.0 49.5 20.3 744 Maryland 63.5 32.5 11.6 55.9 100.0 44.1 19.3 257 Montserrado 84.5 49.8 4.4 45.8 100.0 54.2 19.3 3,675 Nimba 81.6 49.2 4.7 46.1 100.0 53.9 20.0 1,147 River Cess 76.5 50.8 9.1 40.1 100.0 59.9 23.1 135 River Gee 55.1 29.7 7.4 63.0 100.0 37.0 14.3 103 Sinoe 67.0 39.1 8.6 52.4 100.0 47.6 19.3 182 Education No education 67.4 38.5 7.4 54.1 100.0 45.9 15.8 3,066 Primary 70.9 41.5 5.3 53.2 100.0 46.8 17.4 2,875 Secondary and higher 88.9 54.4 4.5 41.1 100.0 58.9 23.7 3,298 Wealth quintile Lowest 60.0 35.1 7.5 57.5 100.0 42.5 15.9 1,581 Second 69.0 38.0 8.4 53.6 100.0 46.4 15.8 1,624 Middle 76.6 47.1 5.9 47.1 100.0 52.9 23.0 1,779 Fourth 84.4 51.3 4.2 44.5 100.0 55.5 20.4 2,047 Highest 84.9 50.1 3.9 46.1 100.0 53.9 19.5 2,207 Total 76.2 45.1 5.7 49.2 100.0 50.8 19.1 9,239 1 Includes “don't know/missing” 224 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.11.2 Coverage of prior HIV testing: Men Percentage of men age 15-49 who know where to get an HIV test, percent distribution of men age 15-49 by testing status and by whether they received the results of the last test, the percentage of men ever tested, and the percentage of men age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Liberia 2013 Background characteristic Percentage who know where to get an HIV test Percent distribution of men by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 50.8 11.1 1.6 87.3 100.0 12.7 6.2 1,587 15-19 37.1 4.3 1.2 94.5 100.0 5.5 3.6 890 20-24 68.3 19.7 2.1 78.2 100.0 21.8 9.6 696 25-29 73.1 28.0 5.2 66.8 100.0 33.2 15.9 673 30-39 66.2 31.3 4.0 64.8 100.0 35.2 17.3 1,044 40-49 67.3 31.8 3.0 65.2 100.0 34.8 15.3 814 Marital status Never married 53.6 14.1 1.5 84.4 100.0 15.6 7.9 1,749 Ever had sex 67.1 20.6 2.0 77.4 100.0 22.6 11.4 1,171 Never had sex 26.5 1.0 0.6 98.5 100.0 1.5 0.8 578 Married/Living together 66.9 29.3 4.2 66.5 100.0 33.5 15.4 2,218 Divorced/Separated/Widowed 75.5 35.6 3.8 60.6 100.0 39.4 20.8 151 Residence Urban 68.5 27.4 2.3 70.3 100.0 29.7 15.9 2,413 Greater Monrovia 71.4 29.4 1.7 68.9 100.0 31.1 15.9 1,433 Other urban 64.3 24.5 3.1 72.4 100.0 27.6 15.8 980 Rural 51.8 16.9 4.2 78.9 100.0 21.1 7.6 1,705 Region North Western 62.4 18.1 4.0 77.9 100.0 22.1 9.6 367 South Central 67.8 27.6 2.2 70.2 100.0 29.8 14.8 2,149 South Eastern A 60.0 22.2 4.4 73.3 100.0 26.7 11.5 254 South Eastern B 48.6 14.5 4.5 80.9 100.0 19.1 7.9 288 North Central 52.7 18.0 3.7 78.3 100.0 21.7 10.0 1,060 County Bomi 58.3 19.8 5.3 74.9 100.0 25.1 12.3 97 Bong 46.7 19.0 2.4 78.6 100.0 21.4 8.8 389 Gbarpolu 66.3 15.3 4.7 79.9 100.0 20.1 8.2 94 Grand Bassa 56.0 25.9 2.3 71.8 100.0 28.2 17.1 204 Grand Cape Mount 62.6 18.6 3.0 78.4 100.0 21.6 8.8 176 Grand Gedeh 75.1 31.3 4.5 64.1 100.0 35.9 16.7 82 Grand Kru 36.8 17.7 3.6 78.8 100.0 21.2 10.3 110 Lofa 41.2 13.3 3.8 82.9 100.0 17.1 4.8 219 Margibi 64.0 23.7 3.8 72.5 100.0 27.5 11.9 364 Maryland 57.8 11.9 6.3 81.9 100.0 18.1 6.1 123 Montserrado 70.2 28.7 1.8 69.4 100.0 30.6 15.2 1,582 Nimba 63.4 19.4 4.9 75.7 100.0 24.3 13.6 451 River Cess 62.1 23.3 3.7 73.0 100.0 27.0 8.3 64 River Gee 51.2 14.3 2.6 83.1 100.0 16.9 7.3 55 Sinoe 47.3 14.7 4.8 80.5 100.0 19.5 9.5 108 Education No education 38.3 12.8 2.7 84.5 100.0 15.5 6.3 533 Primary 41.8 10.9 2.4 86.8 100.0 13.2 5.6 1,202 Secondary and higher 76.8 31.5 3.5 65.0 100.0 35.0 17.3 2,383 Wealth quintile Lowest 44.0 14.9 3.3 81.9 100.0 18.1 7.6 749 Second 52.2 14.7 4.2 81.2 100.0 18.8 6.8 753 Middle 59.6 21.4 3.5 75.1 100.0 24.9 11.7 728 Fourth 68.8 28.2 2.9 68.9 100.0 31.1 17.3 864 Highest 76.7 32.1 1.9 66.0 100.0 34.0 16.5 1,024 Total 61.6 23.1 3.1 73.9 100.0 26.1 12.4 4,118 1 Includes “don't know/missing” By residence, those living in urban areas (49 percent of women and 27 percent of men) were more likely than those living in rural areas (39 percent of women and 17 percent of men) to have been tested for HIV HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 225 and to have received the results of the last test. By county, the percentage of women who were tested for HIV and received the results of the last test varied from a low of 30 percent in Grand Bassa and River Gee to a high of 60 percent in Grand Gedeh, while the percentage among men ranged from a low of 12 percent in Maryland to a high of 31 percent in Grand Gedeh. Among women, testing coverage also increased with increasing educational attainment, from 39 percent among those with no education to 54 percent among those with secondary and higher education. Testing coverage among women also generally increased by wealth quintile. Results by education level and wealth quintile were generally similar among men. Nineteen percent of women and 12 percent of men had been tested in the 12 month period preceding the survey and had received the results of the last test. Overall, relative to the data reported in the 2007 LDHS, the proportion of respondents who know where to get an HIV test and the proportion who have ever been tested and received results have increased dramatically. For instance, the proportion of respondents who know where to get an HIV test increased from 24 percent to 76 percent among women and from 33 percent to 62 percent among men. Likewise, the proportion of respondents who have ever been tested for HIV and have received their test results has increased from 3 percent to 45 percent among women and from 5 to 23 percent among men. Screening for HIV in pregnant women is a key intervention in reducing transmission of HIV from a mother to her child. The Ministry of Health and Social Welfare (MOHSW) through the National AIDS Control Program (NACP) has expanded the number of facilities offering Prevention of Mother-To-Child Transmission (PMTCT) services from 29 in 2008 to 335 in September 2012 (NACP and MOHSW, 2013). Table 13.12 shows that 66 percent of women who gave birth during the two years preceding the survey received HIV counseling during prenatal care. Forty-five percent of women who gave birth during the two years preceding the survey were tested for HIV, received the test results, and received post-test counseling, while 18 percent of women were tested and received the test results but did not receive post-test counseling. Fifty-three percent of women reported that they had both received counseling about HIV and had been offered, accepted, and received the results of an HIV test during prenatal care. Sixty-four percent of women had an HIV test either during prenatal care or during labor and received their test results. Women were more likely to have been both counseled about HIV and tested for HIV during prenatal care, and to have received the results of their test, if they lived in an urban area (64 percent), particularly Greater Monrovia (72 percent), had at least some secondary education (71 percent), or were in the highest wealth quintile (74 percent). Women were least likely to report receiving the full range of voluntary counseling and testing services during prenatal care if they lived in rural areas (41 percent), had no education (40 percent), or were in the lowest wealth quintile (38 percent). 226 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.12 Pregnant women counseled and tested for HIV Among all women age 15-49 who gave birth in the two years preceding the survey, the percentage who received counseling on HIV during prenatal care, the percentage who received an HIV test during prenatal care for their most recent birth by whether they received their results and post-test counseling, and the percentage who received an HIV test during prenatal care or labor for their most recent birth by whether they received their test results, according to background characteristics, Liberia 2013 Background characteristic Percentage who received counseling on HIV during prenatal care1 Percentage who were tested for HIV during prenatal care and who: Percentage who received counseling on HIV and an HIV test during prenatal care, and the results Percentage who had an HIV test during prenatal care or labor and who:2 Number of women who gave birth in the past two years3 Received results and: Did not receive results Received post-test counseling Did not receive post- test counseling Received results Did not receive results Age 15-24 67.6 44.3 19.4 6.8 53.9 64.4 7.1 1,147 15-19 63.0 42.9 20.2 7.4 49.8 63.6 7.7 422 20-24 70.3 45.2 18.9 6.4 56.3 64.8 6.7 725 25-29 66.6 49.3 18.3 7.3 55.6 68.0 7.5 627 30-39 63.0 43.6 16.3 8.4 49.8 60.8 8.6 750 40-49 55.8 36.3 15.6 9.1 44.6 52.5 9.3 126 Marital status Never married 70.7 43.4 24.0 8.6 57.0 67.4 9.0 558 Married or living together 64.1 44.9 17.2 7.0 51.8 62.8 7.2 1,893 Divorced/separated/widowed 64.3 49.6 10.2 8.6 48.9 61.6 8.6 199 Residence Urban 75.6 53.0 20.1 6.1 64.0 73.7 6.3 1,351 Greater Monrovia 83.3 60.9 18.7 5.5 72.2 79.6 5.5 667 Other urban 68.1 45.2 21.6 6.6 56.1 67.9 7.0 684 Rural 55.0 36.5 15.9 8.9 40.9 53.3 9.2 1,299 Region North Western 65.3 43.6 14.3 10.4 49.8 58.4 11.1 288 South Central 76.6 53.9 17.8 5.5 63.4 72.3 5.6 1,109 South Eastern A 59.2 47.8 12.9 9.1 48.0 61.6 9.3 196 South Eastern B 46.7 28.7 13.4 8.9 31.2 43.5 9.5 197 North Central 56.9 36.9 21.9 8.4 45.9 59.4 8.5 860 County Bomi 72.9 67.2 4.6 5.3 64.4 71.8 5.3 68 Bong 55.1 38.9 14.0 14.4 41.9 53.8 14.4 318 Gbarpolu 49.1 23.8 17.1 14.3 34.9 41.6 15.3 64 Grand Bassa 52.8 27.2 11.9 6.1 30.9 41.9 6.7 149 Grand Cape Mount 68.7 41.6 17.4 11.0 49.6 59.5 11.9 155 Grand Gedeh 70.9 64.2 11.8 3.8 63.6 77.3 4.5 66 Grand Kru 36.6 26.8 17.9 2.2 29.3 45.7 3.3 80 Lofa 37.9 43.5 4.4 7.2 26.6 47.9 7.2 144 Margibi 76.9 57.6 19.5 3.4 65.4 77.1 3.4 214 Maryland 56.5 29.4 12.2 13.5 34.8 43.1 13.7 81 Montserrado 81.2 58.1 18.5 6.0 69.3 76.9 6.0 746 Nimba 65.3 32.8 34.6 4.0 56.1 68.1 4.3 398 River Cess 62.6 47.8 9.2 12.1 49.1 57.5 12.3 58 River Gee 47.0 31.6 6.4 13.4 27.5 39.7 13.9 36 Sinoe 45.9 32.9 16.9 11.4 32.9 50.7 11.4 73 Education No education 55.4 35.2 14.9 9.1 40.2 51.0 9.4 1,000 Primary 62.3 43.4 19.0 7.1 50.6 62.9 7.2 858 Secondary and higher 81.7 58.9 21.1 5.9 70.7 80.4 6.1 792 Wealth quintile Lowest 51.7 36.5 11.2 9.0 37.7 48.3 9.3 636 Second 53.3 35.7 16.9 11.2 38.2 53.5 11.3 567 Middle 67.3 42.9 21.2 6.1 56.1 65.0 6.5 551 Fourth 78.1 52.0 26.1 4.5 68.2 78.6 4.7 509 Highest 86.7 65.9 16.3 5.4 73.6 82.4 5.6 386 Total 65.5 44.9 18.1 7.5 52.7 63.7 7.7 2,650 1 In this context, "counseling on HIV" means that someone talked with the respondent about all three of the following topics: 1) babies getting HIV from their mother, 2) preventing the virus, and 3) getting tested for the virus 2 Women are asked whether they received an HIV test during labor only if they were not tested for HIV during prenatal care 3 Denominator for percentages includes women who did not receive prenatal care for their last birth in the past two years HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 227 13.9 MALE CIRCUMCISION Circumcision is a common practice in many parts of sub-Saharan Africa for traditional, health, and other reasons. Male circumcision has been associated with a lower risk of HIV transmission from women to men (Williams et al., 2006; WHO and UNAIDS, 2007). To examine the practice of circumcision at the national level, men interviewed in the 2013 LDHS were asked whether they had been circumcised and when they were circumcised. The results are presented in Table 13.13. Male circumcision is universal in Liberia (99 percent).The proportion of men who have been circumcised is high across all background characteristics. Table 13.13 Male circumcision Percentage of men age 15-49 who report having been circumcised, by background characteristics, Liberia 2013 Background characteristic Percentage circumcised Number of men Age 15-24 98.6 1,587 15-19 97.8 890 20-24 99.5 696 25-29 99.2 673 30-39 99.6 1,044 40-49 99.8 814 Residence Urban 99.3 2,413 Greater Monrovia 99.2 1,433 Other urban 99.4 980 Rural 99.0 1,705 Region North Western 99.2 367 South Central 99.4 2,149 South Eastern A 99.1 254 South Eastern B 98.3 288 North Central 98.8 1,060 Religion Christian 99.3 3,387 Muslim 98.8 529 Traditional religion 96.8 54 No religion 99.2 130 Total 99.2 4,118 Note: Total includes 16 men for whom information on religion is missing. 13.10 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS In the 2013 LDHS, respondents who had ever had sex were asked whether they had had a sexually transmitted infection or symptoms of an STI (a bad-smelling, abnormal discharge from the vagina/penis or a genital sore or ulcer) in the 12 months preceding the survey. Table 13.14 shows the self-reported prevalence of STIs and STI symptoms among both men and women. Women were much more likely than men to report having had an STI or having experienced STI symptoms. Among women, in the 12 months preceding the survey, 30 percent reported that they had an STI; 38 percent had a bad-smelling, abnormal discharge; and 34 percent had a genital sore or ulcer. Among men, 13 percent reported that they had an STI; 12 percent had a bad-smelling, abnormal discharge; and 8 percent had a genital sore or ulcer. In total, 50 percent of women and 17 percent of men reported having an STI or STI symptoms. 228 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.14 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms Among women and men age 15-49 who ever had sexual intercourse, the percentage reporting having an STI and/or symptoms of an STI in the past 12 months, by background characteristics, Liberia 2013 Background characteristic Women Men Percentage of women who reported having in the past 12 months: Number of women who ever had sexual intercourse Percentage of men who reported having in the past 12 months: Number of men who ever had sexual intercourseSTI Bad smelling/ abnormal genital discharge Genital sore/ulcer STI/genital discharge/ sore or ulcer STI Bad smelling/ abnormal discharge from penis Genital sore/ulcer STI/ abnormal discharge from penis/ sore or ulcer Age 15-24 30.9 42.7 37.1 53.7 3,085 13.8 14.1 8.4 19.0 1,019 15-19 25.6 38.3 33.2 49.6 1,456 8.9 10.5 7.3 14.2 366 20-24 35.6 46.6 40.7 57.4 1,630 16.6 16.0 8.9 21.6 652 25-29 33.2 41.8 36.1 54.9 1,611 21.0 16.3 12.2 23.4 670 30-39 29.8 37.1 31.3 48.9 2,376 11.7 10.6 7.9 15.0 1,042 40-49 26.5 28.0 26.7 40.2 1,528 6.4 7.8 4.5 10.6 809 Marital status Never married 30.9 42.4 35.4 53.0 2,230 14.5 13.9 9.3 18.8 1,171 Married or living together 30.6 37.0 32.7 49.5 5,384 12.1 11.2 7.6 15.7 2,217 Divorced/separated/ widowed 26.9 36.6 33.4 47.5 987 11.3 9.7 6.4 15.2 151 Residence Urban 33.0 42.9 37.6 55.2 5,165 13.5 12.9 8.2 17.0 2,047 Greater Monrovia 33.1 46.3 40.1 56.8 3,048 12.4 11.4 7.5 14.9 1,232 Other urban 32.8 37.9 34.1 53.0 2,117 15.1 15.1 9.1 20.1 816 Rural 26.0 31.6 27.2 42.6 3,436 12.0 10.9 8.0 16.4 1,492 Region North Western 25.8 30.6 25.0 42.8 783 11.9 11.1 7.4 13.9 326 South Central 33.3 44.1 39.1 55.5 4,415 12.4 10.6 7.4 15.3 1,830 South Eastern A 24.0 28.3 26.1 41.4 473 16.2 18.8 12.7 25.4 226 South Eastern B 16.2 25.3 20.5 33.3 548 9.0 9.3 8.3 14.8 259 North Central 30.5 35.2 30.2 48.4 2,381 14.4 14.5 8.4 19.0 898 County Bomi 26.0 31.2 20.6 40.3 227 17.8 18.5 13.8 22.6 85 Bong 27.0 33.6 24.3 42.8 865 14.3 11.3 7.3 15.1 345 Gbarpolu 19.2 33.2 28.8 42.6 171 9.1 8.8 6.9 10.8 85 Grand Bassa 41.8 46.6 42.0 59.6 417 11.9 8.8 8.6 15.2 181 Grand Cape Mount 28.7 29.0 25.9 44.4 385 10.3 8.3 4.1 10.8 156 Grand Gedeh 31.3 32.9 29.5 45.7 164 29.9 29.3 21.0 36.2 73 Grand Kru 13.4 19.2 14.6 30.0 211 11.3 12.8 10.5 20.6 100 Lofa 14.4 19.3 8.5 24.0 418 10.4 14.4 9.3 18.9 174 Margibi 25.1 28.6 27.5 43.0 658 11.5 6.5 5.4 15.1 296 Maryland 20.0 34.6 27.9 40.0 238 8.6 8.0 9.3 13.4 110 Montserrado 33.8 46.9 41.1 57.5 3,340 12.7 11.7 7.7 15.3 1,353 Nimba 39.4 42.6 43.2 62.1 1,098 16.4 17.4 9.1 22.7 379 River Cess 28.3 31.6 28.5 49.3 132 10.7 8.0 9.4 15.8 59 River Gee 12.9 16.0 15.4 24.2 100 5.3 4.8 1.9 6.2 49 Sinoe 14.0 21.5 21.1 31.4 177 9.0 17.4 8.5 23.0 95 Education No education 27.6 33.9 29.0 44.3 3,036 8.7 9.0 7.0 11.8 495 Primary 30.1 38.1 33.1 50.6 2,463 13.0 12.8 8.8 17.0 853 Secondary and higher 32.8 42.9 38.2 55.7 3,102 13.7 12.4 8.1 17.7 2,191 Wealth quintile Lowest 24.1 31.6 25.1 41.3 1,527 11.9 10.8 8.7 15.2 673 Second 25.4 31.1 27.4 42.0 1,549 13.4 13.6 8.0 17.9 662 Middle 29.8 37.2 36.4 49.7 1,669 15.5 13.3 8.1 18.8 606 Fourth 38.4 48.7 40.8 60.4 1,898 15.4 13.8 8.7 19.6 723 Highest 31.3 40.3 35.2 54.2 1,958 9.2 9.4 7.1 13.1 876 Total 30.2 38.4 33.5 50.2 8,601 12.9 12.0 8.1 16.7 3,539 Variations in the self-reported prevalence of STIs or STI symptoms by background characteristics are also presented in Table 13.14. The prevalence of STIs or STI symptoms was slightly higher among never- married women and men compared with ever-married women and men. Prevalence of STIs or STI symptoms HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 229 was also higher among women living in urban areas (55 percent) than among women in rural areas (43 percent); similarly large differences were not observed for men. Differences are also seen by region and county. For example, the proportion of women reporting an STI or STI symptoms ranged from a high of 62 percent in Nimba to a low of 24 percent in both Lofa and River Gee. For men, the proportion reporting an STI or STI symptoms ranged from 36 percent in Grand Gedeh to 6 percent in River Gee. For women and men, the prevalence of STIs or STI symptoms increases with educational attainment and wealth, although for the latter, prevalence peaks among those in the fourth wealth quintile. As shown in Figure 13.1, more than eight in ten women (86 percent) and men (81 percent) who had an STI or STI symptoms sought advice or treatment from a clinic, hospital, private doctor, or other health professional. Few women or men sought advice or treatment from either a shop or pharmacy (1 percent of women and 4 percent of men) or any other source (5 percent of women and 4 percent of men). One in ten women (10 percent) and men (11 percent) did not seek any treatment when they had an STI or STI symptoms. Figure 13.1 Women and men seeking treatment for STIs 86 1 5 10 81 4 4 11 Clinic/hospital/private doctor/other health professional Advice or medicine from shop/pharmacy Advice or treatment from any other source No advice or treatment Percentage Women Men LDHS 2013 13.11 INJECTIONS Injection overuse in a health care setting can contribute to the transmission of blood-borne pathogens because it amplifies the effect of unsafe practices such as reuse of injection equipment. To measure the potential risk of transmission of HIV associated with medical injections, LDHS respondents were asked whether they had received any injections from a health worker in the 12 months preceding the survey and, if so, whether their last injection was administered with a syringe from a new, unopened package. It should be noted that self- administered medical injections (e.g., insulin injections for diabetes) were not included in the calculations. 230 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.15 shows the reported prevalence of injections and of safe injection practices. Forty percent of women and 41 percent of men report receiving an injection from a health worker during the 12 months preceding the survey. Among women and men, the prevalence of injections was lowest in those age 15-19 (31 and 34 percent, respectively) and those who were never married and never had sex (23 and 30 percent, respectively) compared with those in other age groups and those who have ever had sex. Women and men in rural areas were less likely than those in urban areas to have reported receiving an injection, although the difference was greater for women (35 and 43 percent, respectively) than men (39 and 43 percent, respectively). Considerable variation was reported by county of residence; among women, injection prevalence was highest in Grand Gedeh and Nimba (51 percent, each) and lowest in Lofa (23 percent). Among men, injection prevalence was highest in Grand Kru (63 percent) and lowest in River Gee (22 percent). For both women and men, the reported prevalence of injections in the past 12 months is highest among those with at least some secondary education; on the other hand, variations by wealth quintile do not follow a clear pattern. In the past 12 months, the average number of medical injections per woman or man was less than two. Ninety-eight percent of recent injections among both women and men were administered with a syringe taken from a newly opened package. Table 13.15 Prevalence of medical injections Percentage of women and men age 15-49 who received at least one medical injection in the past 12 months, the average number of medical injections per person in the past 12 months, and among those who received a medical injection, the percentage of last medical injections for which the syringe and needle were taken from a new, unopened package, by background characteristics, Liberia 2013 Background characteristic Women Men Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of women For last injection, syringe and needle taken from a new, unopened package Number of women receiving medical injections in the past 12 months Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of men For last injection, syringe and needle taken from a new, unopened package Number of men receiving medical injections in the past 12 months Age 15-24 39.0 1.3 3,722 98.1 1,451 36.9 1.4 1,587 98.1 586 15-19 31.4 1.0 2,080 97.1 652 34.1 1.2 890 98.7 303 20-24 48.6 1.7 1,642 99.0 798 40.6 1.6 696 97.5 283 25-29 44.5 1.8 1,611 98.8 717 46.4 2.1 673 97.0 312 30-39 40.9 1.7 2,378 97.9 973 43.2 1.8 1,044 96.8 451 40-49 34.9 1.6 1,528 99.4 533 42.8 1.8 814 98.9 349 Marital status Never married 37.8 1.4 2,867 98.0 1,084 38.3 1.4 1,749 97.6 669 Ever had sex 42.0 1.5 2,230 98.6 938 42.3 1.6 1,171 98.3 495 Never had sex 23.0 0.7 637 94.1 147 30.1 1.0 578 95.7 174 Married or living together 40.7 1.6 5,386 98.5 2,192 44.0 1.9 2,218 97.9 976 Divorced/separated/ widowed 40.3 1.9 987 98.8 398 35.2 1.7 151 96.4 53 Residence Urban 42.6 1.8 5,633 98.3 2,402 42.8 1.7 2,413 98.9 1,033 Greater Monrovia 44.4 1.8 3,361 98.5 1,491 44.5 1.9 1,433 99.4 638 Other urban 40.1 1.7 2,272 98.0 910 40.3 1.5 980 97.9 395 Rural 35.3 1.2 3,606 98.5 1,272 39.0 1.6 1,705 96.0 665 Region North Western 36.8 1.2 837 99.5 308 41.3 1.7 367 97.5 152 South Central 41.3 1.7 4,854 98.2 2,003 42.5 1.8 2,149 98.5 914 South Eastern A 42.9 1.6 483 98.9 207 45.6 2.0 254 97.9 116 South Eastern B 33.1 1.1 577 96.9 191 41.9 1.5 288 98.6 120 North Central 38.8 1.5 2,488 98.7 965 37.4 1.4 1,060 95.8 396 …Continued HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 231 Table 13.15 Prevalence of medical injections—Continued Background characteristic Women Men Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of women For last injection, syringe and needle taken from a new, unopened package Number of women receiving medical injections in the past 12 months Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of men For last injection, syringe and needle taken from a new, unopened package Number of men receiving medical injections in the past 12 months County Bomi 34.7 1.2 244 100.0 85 47.7 1.8 97 100.0 46 Bong 31.2 1.1 894 97.3 279 36.3 1.3 389 95.6 141 Gbarpolu 36.5 1.2 182 99.0 66 39.1 1.4 94 98.6 37 Grand Bassa 35.4 1.1 434 96.2 154 50.4 1.8 204 97.0 103 Grand Cape Mount 38.2 1.3 412 99.4 157 38.9 1.8 176 95.3 69 Grand Gedeh 51.4 2.3 167 100.0 86 52.4 1.8 82 97.1 43 Grand Kru 30.1 1.0 217 97.9 65 62.6 2.3 110 100.0 69 Lofa 23.2 0.9 447 100.0 104 41.2 1.7 219 98.8 90 Margibi 28.9 1.2 744 97.1 215 27.9 1.1 364 94.6 101 Maryland 33.3 1.1 257 96.2 85 32.2 1.2 123 97.6 40 Montserrado 44.5 1.9 3,675 98.5 1,634 44.9 1.9 1,582 99.3 710 Nimba 50.7 2.0 1,147 99.0 582 36.4 1.4 451 94.3 164 River Cess 36.3 1.2 135 97.3 49 27.9 1.0 64 100.0 18 River Gee 39.0 1.2 103 96.6 40 22.2 0.8 55 93.6) 12 Sinoe 39.9 1.3 182 98.7 73 51.0 2.7 108 97.8 55 Education No education 32.6 1.2 3,066 98.1 1,000 38.1 1.6 533 96.0 203 Primary 36.3 1.3 2,875 98.2 1,043 35.6 1.3 1,202 96.5 428 Secondary and higher 49.5 2.1 3,298 98.7 1,631 44.8 1.9 2,383 98.6 1,067 Wealth quintile Lowest 32.0 1.2 1,581 96.9 505 40.2 1.5 749 96.2 301 Second 33.7 1.3 1,624 98.9 548 38.7 1.5 753 94.7 291 Middle 41.0 1.5 1,779 98.7 730 41.9 1.8 728 98.6 305 Fourth 46.5 1.8 2,047 99.2 952 43.2 1.8 864 99.0 373 Highest 42.6 1.9 2,207 97.8 940 41.7 1.7 1,024 99.2 427 Total 39.8 1.6 9,239 98.4 3,674 41.2 1.7 4,118 97.7 1,698 Note: Medical injections are those given by a doctor, nurse, pharmacist, dentist, or other health worker 13.12 HIV/AIDS-RELATED KNOWLEDGE AND BEHAVIOR AMONG YOUNG PEOPLE This section addresses HIV/AIDS-related knowledge among Liberian young people age 15-24 and also assesses the extent to which Liberian young people are engaged in behaviors that may place them at risk of contracting HIV. 13.12.1 Knowledge about HIV/AIDS and Source for Condoms Knowledge of how HIV is transmitted is crucial to enabling people to avoid HIV infection, and this is especially true for young people, who are often at greater risk because they may have shorter relationships with more partners or engage in other risky behaviors. Table 13.16 shows the level of comprehensive knowledge of HIV/AIDS among young people and the percentage of young people who know a source for condoms. As discussed earlier in the chapter, comprehensive knowledge of HIV/AIDS is defined as knowing that both condom use and limiting sexual intercourse to one uninfected partner are HIV prevention methods, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission. Table 13.16 shows that 36 percent of young women and 29 percent of young men have comprehensive knowledge of HIV/AIDS. The proportion of young women and men age 15-19 with comprehensive knowledge of AIDS is lower than the proportion of young women and men age 20-24. Urban young people, especially 232 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior those living in Greater Monrovia, are more likely than rural young people to have comprehensive knowledge of HIV/AIDS. Among both sexes, the proportion with comprehensive knowledge increases with educational attainment. Table 13.16 Comprehensive knowledge about AIDS and of a source of condoms among youth Percentage of young women and young men age 15-24 with comprehensive knowledge about AIDS and percentage with knowledge of a source of condoms, by background characteristics, Liberia 2013 Background characteristic Women age 15-24 Men age 15-24 Percentage with comprehensive knowledge of AIDS1 Percentage who know a condom source1 Number of women Percentage with comprehensive knowledge of AIDS1 Percentage who know a condom source1 Number of men Age 15-19 34.6 63.6 2,080 19.0 53.8 890 15-17 31.7 55.7 1,311 17.5 45.4 587 18-19 39.5 77.1 769 21.9 70.1 304 20-24 37.1 81.1 1,642 40.6 86.8 696 20-22 37.0 79.0 998 41.9 86.3 466 23-24 37.2 84.4 644 38.0 87.7 231 Marital status Never married 36.2 68.4 2,426 28.3 65.7 1,407 Ever had sex 39.1 79.2 1,790 38.1 86.6 839 Never had sex 27.9 37.8 636 13.8 34.9 568 Ever married 34.8 76.8 1,295 30.0 88.6 179 Residence Urban 39.9 74.3 2,467 34.4 74.4 1,030 Greater Monrovia 45.6 76.7 1,504 40.9 80.7 631 Other urban 31.2 70.6 962 24.0 64.4 399 Rural 27.3 65.4 1,255 17.6 57.0 556 Education No education 21.5 65.2 495 5.3 42.3 86 Primary 26.8 59.3 1,640 14.9 44.6 585 Secondary and higher 49.4 85.7 1,586 39.3 85.9 916 Total 15-24 35.7 71.3 3,722 28.5 68.3 1,587 1 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about AIDS transmission or prevention of HIV. The components of comprehensive knowledge are presented in Tables 13.2, 13.3.1 and 13.3.2. 2 For this table, the following responses are not considered a source for condoms: friends, family members, and home. Although only a minority of young women and men have a comprehensive knowledge of HIV/AIDS, knowledge of a source for condoms is relatively common. Seventy-one percent of young women and 68 percent of young men know a place where they can obtain a condom. 13.12.2 First Sex Age at first sex is an important indicator of exposure to risk of pregnancy and sexually transmitted infections. Young people who initiate sex at an early age are typically at higher risk of becoming pregnant or contracting an STI than young people who delay the onset of sexual activity. Consistent condom use can reduce such risks. In Liberia, 23 percent of young women and 9 percent of young men in the 15-24 age group report having sex before age 15 (Table 13.17). Among those age 18-24, 85 percent of young women and 58 percent of young men report having had sex before age 18. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 233 Table 13.17 Age at first sexual intercourse among young people Percentage of young women and young men age 15-24 who had sexual intercourse before age 15 and percentage of young women and young men age 18-24 who had sexual intercourse before age 18, by background characteristics, Liberia 2013 Background characteristic Women age 15-24 Women age 18-24 Men age 15-24 Men age 18-24 Percentage who had sexual intercourse before age 15 Number of women Percentage who had sexual intercourse before age 18 Number of women Percentage who had sexual intercourse before age 15 Number of men Percentage who had sexual intercourse before age 18 Number of men Age 15-19 23.3 2,080 na na 8.9 890 na na 15-17 24.5 1,311 na na 8.1 587 na na 18-19 21.3 769 88.9 769 10.5 304 63.3 304 20-24 22.9 1,642 82.8 1,642 9.4 696 55.4 696 20-22 23.5 998 81.6 998 9.8 466 58.8 466 23-24 21.8 644 84.7 644 8.7 231 48.4 231 Marital status Never married 18.0 2,426 80.3 1,208 9.0 1,407 57.0 822 Ever married 32.7 1,295 89.3 1,203 10.2 179 61.3 178 Knows condom source1 Yes 24.0 2,654 85.2 1,925 11.3 1,084 62.8 817 No 20.9 1,067 83.0 487 4.5 503 35.2 183 Residence Urban 19.8 2,467 82.9 1,571 7.9 1,030 59.8 666 Greater Monrovia 17.5 1,504 81.5 932 6.7 631 62.1 419 Other urban 23.6 962 85.0 640 9.9 399 55.8 247 Rural 29.6 1,255 88.2 840 11.3 556 53.8 335 Education No education 35.9 495 88.9 428 9.6 86 46.0 67 Primary 27.5 1,640 85.5 801 8.2 585 50.5 221 Secondary and higher 14.6 1,586 82.8 1,181 9.7 916 61.1 713 Total 23.1 3,722 84.8 2,411 9.1 1,587 57.8 1,000 na = Not applicable 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. As expected, the proportion of young women initiating sexual intercourse by age 15 is higher among those who have ever been married than among those who were not yet married at the time of the survey. Rural young women are more likely than their urban counterparts to have initiated sex before age 15 (30 percent and 20 percent, respectively). Initiation of sexual intercourse before age 15 varies slightly according to knowledge of a condom source. Differences by education level are much more marked: among young women with no education, 36 percent have had sex before age 15 compared to 15 percent of those with secondary and higher education. There are several notable differences between the age of initiation of sexual intercourse between young men and young women. First, the proportion of young men age 15-24 and 18-24 who had sex before age 15 or age 18 was much higher among men who knew a condom source than those who did not, whereas differences were minimal among young women. For example, among young men age 18-24, 63 percent who knew a source of condoms initiated sex before age 18, compared with 35 percent of men who did not know a condom source. Second, the proportion of young men age 15-24 who initiated sexual intercourse by age 15 showed no correlation by educational status whereas among young women, those with more education were less likely to have initiated sexual intercourse by age 15. Among young men age 18-24, those with no education (46 percent) were less likely than those with primary education (51 percent) or at least some secondary education (61 percent) to have had sexual intercourse before age 18; among women age 18-24, the 234 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior correlation was in the opposite direction, although overall differences in the proportion of women who had sex by age 18 were small. Figure 13.2 examines trends in age at first sexual intercourse among young people. The percentage of young women age 15-19 who have had sex by age 15 has increased slightly since 2007 (from 19 percent to 23 percent). In contrast, no change is observed in the proportion of young men age 15-19 who had sex by age 15 (9 percent in both the 2007 and 2013 LDHS). The percentage of women 18-19 and men 18-19 who had sex before age 18 has also held steady between the two surveys: 88 percent of young women and 63 percent of young men had sex before age 18 according to the 2007 LDHS compared with 89 percent of young women and 63 percent of young men according to the 2013 LDHS. Figure 13.2 Trends in age of first sexual intercourse 19 9 88 63 23 9 89 63 Percentage of women 15-19 who had sexual intercourse before exact age 15 Percentage of men 15-19 who had sexual intercourse before exact age 15 Percentage of women 18-19 who had sexual intercourse before exact age 18 Percentage of men 18-19 who had sexual intercourse before exact age 18 Percent 2007 LDHS 2013 LDHS 13.12.3 Premarital Sex The period between first sex and marriage is often a time of sexual experimentation. Table 13.18 presents information on the patterns of sexual activity among never-married young people age 15-24 in Liberia, including the percentage who have never had sexual intercourse, the percentage who engaged in sexual intercourse in the 12 months before the survey, and, among those who had sexual intercourse in the past 12 months, the percentage who used a condom during their most recent sexual encounter. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 235 Table 13.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth Among never-married women and men age 15-24, the percentage who have never had sexual intercourse, the percentage who had sexual intercourse in the past 12 months, and, among those who had premarital sexual intercourse in the past 12 months, the percentage who used a condom at the last sexual intercourse, by background characteristics, Liberia 2013 Background characteristic Never-married women age 15-24 Never-married men age 15-24 Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of never married women Women who had sexual intercourse in the past 12 months Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of never married men Men who had sexual intercourse in the past 12 months Percentage who used a condom at last sexual intercourse Number of women Percentage who used a condom at last sexual intercourse Number of men Age 15-19 35.6 60.2 1,752 23.6 1,055 59.8 37.2 877 36.6 326 15-17 48.0 49.3 1,218 24.2 601 75.4 21.9 585 33.2 128 18-19 7.3 85.0 534 22.8 454 28.5 67.9 292 38.8 198 20-24 1.8 88.6 674 20.2 598 8.3 88.2 531 51.3 468 20-22 2.2 89.9 436 21.5 392 10.6 86.4 377 49.7 326 23-24 1.2 86.2 238 17.8 205 2.8 92.7 154 54.9 142 Knows condom source1 Yes 14.5 79.7 1,659 23.9 1,323 21.5 74.3 925 48.9 688 No 51.6 43.0 767 16.0 330 76.6 22.2 483 21.4 107 Residence Urban 26.7 68.6 1,753 26.1 1,203 37.7 58.8 954 53.1 561 Greater Monrovia 28.1 68.8 1,113 33.2 766 33.9 61.5 595 59.3 366 Other urban 24.2 68.4 639 13.6 438 44.2 54.2 358 41.5 194 Rural 25.1 66.7 674 12.4 449 45.9 51.5 454 26.3 234 Education No education 18.2 67.1 158 4.8 106 46.1 53.9 72 (29.0) 39 Primary 37.0 57.8 1,111 16.2 642 64.7 33.4 532 20.4 178 Secondary and higher 17.0 78.1 1,157 28.8 904 23.7 71.9 804 54.0 578 Total 15-24 26.2 68.1 2,426 22.3 1,652 40.4 56.4 1,407 45.2 794 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. Never-married young women age 15-24 are much less likely than never-married young men age 15-24 to report that they have never engaged in sexual intercourse (26 percent and 40 percent, respectively). The percentage of never-married young people who have never had sex declines rapidly with age; 48 percent of young women and 75 percent of young men age 15-17 report that they have not yet had sexual intercourse compared with 1 percent of women age 23-24 and 3 percent of men age 23-24. Never-married young women and men who know a condom source are considerably more likely than those who do not to have ever had sexual intercourse: 15 percent of young women who know a condom source have never had sexual intercourse compared with 52 percent of young women who do not know a condom source. Similarly, 22 percent of young men who know a condom source have never had sexual intercourse, compared with 77 percent of young men who do not know a condom source. Variations in the percentages of young people who had sexual intercourse in the past 12 months by knowledge of a condom source are even more striking: 80 percent of young women and 74 percent of young men who know of a condom source had sexual intercourse in the past 12 months, compared with only 43 percent of young women and 22 percent of young men who do not know of a condom source. 236 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Overall, 56 percent of never-married young men reported that they had sexual intercourse during the 12 months preceding the survey, compared with 68 percent of never-married young women. Among never- married young people who had intercourse in the past 12 months, condom use at last sexual intercourse was more common among young men than young women (45 percent and 22 percent, respectively). There are large differentials by background characteristics in the percentages of never-married young people using condoms during their most recent sexual intercourse in the past 12 months. Condom use at last sexual intercourse increases with education and, not surprisingly, is more common among those who know a condom source. Condom use at last sexual intercourse is also more common among never-married young women and young men in Greater Monrovia (33 percent and 59 percent, respectively) than among those in other urban areas (14 percent and 42 percent, respectively) or rural areas (12 percent and 26 percent, respectively). 13.12.4 Multiple Sexual Partners The most common means of transmission of HIV in Liberia is through unprotected sex with an infected person. To prevent HIV transmission, it is important that young people practice safe sex. Tables 13.19.1 and 13.19.2 present data on the percentage of young people who had engaged in sexual intercourse with more than one partner in the 12 months before the survey and the rate of condom use at last sex. Table 13.19.1 Multiple sexual partners in the past 12 months among young people: Women Among all young women age 15-24, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months, and among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse, by background characteristics, Liberia 2013 Background characteristic Women age 15-24 Women age 15-24 who had 2+ partners in the past 12 months Percentage who had 2+ partners in the past 12 months Number of women Percentage who reported using a condom at last intercourse Number of women Age 15-19 8.6 2,080 27.1 179 15-17 6.1 1,311 17.6 80 18-19 12.9 769 34.8 99 20-24 8.6 1,642 23.6 142 20-22 9.1 998 22.6 91 23-24 7.9 644 (25.4) 51 Marital status Never married 9.5 2,426 29.0 229 Ever married 7.0 1,295 16.8 91 Knows condom source1 Yes 10.4 2,654 28.5 277 No 4.1 1,067 (6.6) 43 Residence Urban 10.3 2,467 29.2 255 Greater Monrovia 10.8 1,504 37.4 163 Other urban 9.5 962 14.6 92 Rural 5.2 1,255 11.6 65 Education No education 5.7 495 (24.3) 28 Primary 7.0 1,640 17.4 115 Secondary and higher 11.1 1,586 31.1 177 Total 15-24 8.6 3,722 25.6 320 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 237 Table 13.19.2 Multiple sexual partners in the past 12 months among young people: Men Among all young men age 15-24, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months, and among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse, by background characteristics, Liberia 2013 Background characteristic Men age 15-24 Men age 15-24 who had 2+ partners in the past 12 months Percentage who had 2+ partners in the past 12 months Number of men Percentage who reported using a condom at last intercourse Number of men Age 15-19 4.4 890 (21.6) 39 15-17 1.8 587 * 10 18-19 9.3 304 (25.3) 28 20-24 22.1 696 35.2 154 20-22 21.2 466 40.7 99 23-24 23.9 231 25.4 55 Marital status Never married 9.6 1,407 37.4 135 Ever married 32.2 179 20.8 58 Knows condom source1 Yes 16.8 1,084 34.4 182 No 2.2 503 * 11 Residence Urban 11.7 1,030 38.5 121 Greater Monrovia 8.6 631 * 54 Other urban 16.7 399 33.0 67 Rural 12.9 556 22.2 72 Education No education 13.6 86 * 12 Primary 6.6 585 29.9 39 Secondary and higher 15.5 916 33.8 142 Total 15-24 12.1 1,587 32.4 193 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. Young men were somewhat more likely than young women to report having multiple sexual partners in the 12 months preceding the survey (12 percent and 9 percent, respectively). Among young people who had ever been married, only 7 percent of young women reported having had sexual intercourse with more than one partner in the previous 12 months, compared with 32 percent of young men. The percentage of young men, but not young women, who reported having sexual intercourse with more than one partner in the past 12 months increased with increasing age. Among young men who had multiple partners in the past 12 months, 32 percent reported that they used a condom during their most recent sexual intercourse. The proportion of young women who had multiple partners in the last 12 months and who used a condom during their last sexual intercourse was 26 percent. 13.12.5 Age-mixing in Sexual Relationships In many societies, young women have sexual relationships with men who are considerably older than they are. This practice can contribute to the spread of HIV and other STIs because if a younger, uninfected partner has sex with an older, infected partner, this can introduce the virus into a younger, uninfected cohort. To investigate this practice, women age 15-19 who had a sexual partner in the 12 months preceding the survey were asked the age of the partner. Table 13.20 shows that in the year preceding the survey, 11 percent of young women age 15-19 who had sexual intercourse had sex with a man 10 or more years older. 238 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Similarly, young men age 15-19 who reported that they had a sexual partner in the past 12 months were asked the age of the partner. Less than 1 percent reported having a partner 10 or more years older. Table 13.20 Age-mixing in sexual relationships among women and men age 15-19 Among women and men age 15-19 who had sexual intercourse in the past 12 months, percentage who had sexual intercourse with a partner who was 10 or more years older than themselves, by background characteristics, Liberia 2013 Background characteristic Women age 15-19 who had sexual intercourse in the past 12 months Men age 15-19 who had sexual intercourse in the past 12 months Percentage who had sexual intercourse with a man 10+ years older Number of women Percentage who had sexual intercourse with a woman 10+ years older Number of men Age 15-17 10.0 681 0.0 129 18-19 11.5 671 0.6 210 Marital status Never married 8.2 1,055 0.4 326 Ever married 19.6 298 * 13 Knows condom source1 Yes 11.4 1,024 0.5 272 No 8.8 328 0.0 68 Residence Urban 10.4 882 0.6 212 Greater Monrovia 11.3 527 (0.0) 127 Other urban 9.0 355 1.5 85 Rural 11.4 470 0.0 128 Education No education 17.4 103 * 17 Primary 9.6 689 0.3 124 Secondary and higher 10.9 561 0.5 199 Total 15-19 10.7 1,352 0.4 340 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 13.12.6 Coverage of HIV Testing Services Seeking an HIV test may be more difficult for young people than adults because many young people lack experience in accessing health services for themselves and because there are often barriers to young people obtaining services. Table 13.21 presents data on the percentage of sexually active young people being tested and receiving the results within the past year. Overall, young women are much more likely than young men to have been tested for HIV and to have received the results of the test (21 percent and 10 percent, respectively). Coverage of HIV testing services among young people has improved dramatically over the last six years. In the 2007 LDHS, only 2 percent of young women and men were tested for HIV and received their results in the 12 months preceding the survey. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 239 Table 13.21 Recent HIV tests among youth Among young women and young men age 15-24 who have had sexual intercourse in the past 12 months, the percentage who were tested for HIV in the past 12 months and received the results of the last test, by background characteristics, Liberia 2013 Background characteristic Women age 15-24 who have had sexual intercourse in the past 12 months: Men age 15-24 who have had sexual intercourse in the past 12 months: Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Age 15-19 17.0 1,352 8.1 340 15-17 12.4 681 6.8 129 18-19 21.8 671 8.8 210 20-24 24.8 1,485 10.5 632 20-22 23.3 898 10.9 413 23-24 27.0 586 9.8 218 Marital status Never married 17.0 1,652 10.0 794 Ever married 26.8 1,185 7.9 177 Knows condom source1 Yes 23.0 2,243 10.5 844 No 14.0 595 4.3 127 Residence Urban 20.7 1,862 12.2 637 Greater Monrovia 19.9 1,135 11.6 403 Other urban 21.9 727 13.2 235 Rural 21.8 975 4.8 334 Education No education 19.4 409 0.5 52 Primary 19.8 1,121 3.2 230 Secondary and higher 22.7 1,307 12.5 689 Total 15-24 21.1 2,837 9.7 971 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIV Prevalence • 241 HIV PREVALENCE 14 nformation on national HIV prevalence in Liberia typically comes from sentinel surveillance of HIV among pregnant women attending prenatal clinics. Other sources of information derive from routine hospital-based surveys and focused surveillance of special populations, such as the recently completed Integrated Bio-Behavioral Surveillance Survey (IBBSS) carried out among Liberia’s most at-risk population by the National AIDS Control Program (NACP) of the Ministry of Health and Social Welfare in collaboration with the National AIDS Commission (MOHSW and NAC, 2014). Together, these surveys provide information on HIV prevalence among special groups. However, such surveillance data do not provide an estimate of the HIV prevalence among the general Liberian population. As part of the 2007 LDHS, it was therefore decided to test a representative sample of women and men age 15-49 for HIV. The 2007 LDHS provided, for the first time, direct estimates of HIV prevalence among the general adult female and male populations in Liberia. Also available were details of HIV prevalence by age, residence, region, and other socioeconomic characteristics. In addition, HIV prevalence was analyzed according to demographic characteristics and sexual behavior to identify factors associated with the epidemic. I Key Findings • Only 1.9 percent of Liberian adults age 15-49 are infected with HIV. In the 2007 LDHS, the HIV prevalence rate for adults was 1.5 percent. However, the difference in the estimates of HIV prevalence between the two surveys is not statistically significant. • The HIV prevalence rate among women age 15-49 is 2.0 percent and among men age 15-49 is 1.7 percent. Among women, HIV prevalence peaks at 3.6 percent in the 25-29 age group; among men, HIV prevalence peaks at 3.6 percent in the 40-44 age group. • Among women and men combined, HIV prevalence is higher in urban areas (2.6 percent) than in rural areas (0.8 percent). And among urban dwellers, HIV prevalence is higher in Greater Monrovia (3.2 percent) than in other urban areas (1.7 percent). • HIV prevalence is higher among women age 15-49 who are pregnant (4.6 percent) than among those who are not pregnant or are not sure (1.8 percent). • One percent of young people age 15-24 are infected with HIV. HIV prevalence among women age 15-24 is 1.4 percent; HIV prevalence among men age 15-24 is 0.5 percent. • Over half (55 percent) of women and men who are infected with HIV have not previously been tested or have been tested but have not received the result. • Nearly 1,600 cohabiting couples were tested for HIV in the 2013 LDHS, and in 96.8 percent, both partners were HIV negative. In 0.5 percent of couples, both partners were HIV positive. Just under 3 percent (2.8 percent) of couples were discordant, that is, one partner was infected with HIV and the other was not. 242 • HIV Prevalence Given that large population-based surveys such as the LDHS cannot be repeated each year, the 2007 results were used to calibrate estimates based on the sentinel surveillance system in order to monitor the epidemic over time on a regular basis. To obtain a new estimate of HIV prevalence among the general population and provide updated information on the characteristics of the epidemic, it was decided to repeat HIV testing in the 2013 LDHS. Test results will be used to refine HIV prevalence estimates based on the sentinel surveillance system and allow better monitoring of the epidemic. The 2013 LDHS HIV prevalence estimates will also be used to project the future path of the HIV epidemic in Liberia, and to identify interventions to stall its spread. The methodology for HIV testing is described in detail in the first chapter. This chapter addresses the results of the testing and provides information on HIV testing coverage rates among eligible survey respondents. It also compares HIV prevalence estimates from the 2007 LDHS and 2013 LDHS and discusses levels and differentials in HIV prevalence among those tested. 14.1 COVERAGE RATES FOR HIV TESTING Table 14.1 shows the distribution of women and men age 15-49 eligible for HIV testing by testing outcome. Overall, 90 percent of LDHS respondents who were eligible for testing were both interviewed and tested. Testing coverage rates were higher among women than among men (92 percent and 88 percent, respectively). Among all respondents eligible for testing, 7 percent refused to provide blood and 2 percent were absent at the time of blood collection. Among both women and men, refusal was a larger component of nonresponse than absence. A comparison of the 2007 LDHS and 2013 LDHS indicates that HIV coverage rates have improved, from 87 percent to 92 percent among women and from 80 percent to 88 percent among men. By residence, coverage of HIV testing among all eligible respondents was higher in rural areas (92 percent) than in urban areas (88 percent). Among urban areas, coverage was lower in Greater Monrovia (86 percent) than other urban areas (89 percent). Among the regions, coverage rates were generally high and ranged from a low of 86 percent in South Eastern A and South Eastern B to a high of 95 percent in North Western. HIV Prevalence • 243 Table 14.1 Coverage of HIV testing by residence and region Percent distribution of women and men age 15-49 eligible for HIV testing by testing status, according to residence and region (unweighted), Liberia 2013 Residence and region Testing status Total Number DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed WOMEN Residence Urban 89.8 0.3 7.4 0.9 0.2 1.1 0.1 0.2 100.0 1,870 Greater Monrovia 87.9 0.0 10.4 1.0 0.3 0.2 0.0 0.2 100.0 577 Other urban 90.6 0.5 6.1 0.8 0.2 1.5 0.2 0.2 100.0 1,293 Rural 93.1 0.4 4.2 0.7 0.2 1.1 0.1 0.1 100.0 2,897 Region North Western 96.1 0.1 3.3 0.1 0.0 0.4 0.0 0.0 100.0 800 South Central 90.5 0.0 8.2 0.5 0.1 0.4 0.0 0.2 100.0 1,374 South Eastern A 88.0 0.6 6.8 1.4 0.4 2.3 0.1 0.4 100.0 725 South Eastern B 88.2 0.9 6.3 1.2 0.5 2.4 0.5 0.0 100.0 765 North Central 95.3 0.5 2.3 0.7 0.2 0.9 0.0 0.1 100.0 1,103 Total 91.8 0.4 5.5 0.7 0.2 1.1 0.1 0.1 100.0 4,767 MEN Residence Urban 85.6 0.4 8.5 1.8 0.2 2.9 0.5 0.2 100.0 1,680 Greater Monrovia 84.4 0.4 9.0 3.7 0.4 0.6 1.2 0.2 100.0 487 Other urban 86.1 0.4 8.2 1.0 0.1 3.9 0.2 0.2 100.0 1,193 Rural 89.7 0.4 5.5 1.3 0.1 2.2 0.5 0.3 100.0 2,638 Region North Western 94.5 0.0 3.7 0.3 0.0 1.0 0.3 0.1 100.0 677 South Central 87.8 0.2 8.3 1.8 0.2 0.8 0.6 0.3 100.0 1,231 South Eastern A 83.8 0.4 7.6 1.9 0.3 4.7 1.3 0.0 100.0 749 South Eastern B 82.7 1.1 8.0 2.1 0.1 5.5 0.1 0.4 100.0 729 North Central 91.5 0.5 4.8 1.2 0.0 1.6 0.0 0.3 100.0 932 Total 88.1 0.4 6.6 1.5 0.1 2.5 0.5 0.3 100.0 4,318 TOTAL Residence Urban 87.8 0.4 7.9 1.3 0.2 2.0 0.3 0.2 100.0 3,550 Greater Monrovia 86.3 0.2 9.8 2.3 0.4 0.4 0.6 0.2 100.0 1,064 Other urban 88.5 0.4 7.1 0.9 0.1 2.7 0.2 0.2 100.0 2,486 Rural 91.5 0.4 4.8 1.0 0.2 1.6 0.3 0.2 100.0 5,535 Region North Western 95.4 0.1 3.5 0.2 0.0 0.7 0.1 0.1 100.0 1,477 South Central 89.3 0.1 8.3 1.1 0.2 0.6 0.3 0.3 100.0 2,605 South Eastern A 85.9 0.5 7.2 1.6 0.3 3.5 0.7 0.2 100.0 1,474 South Eastern B 85.5 1.0 7.1 1.6 0.3 3.9 0.3 0.2 100.0 1,494 North Central 93.6 0.5 3.4 0.9 0.1 1.2 0.0 0.2 100.0 2,035 Total 90.1 0.4 6.0 1.1 0.2 1.8 0.3 0.2 100.0 9,085 1 Includes all dried blood samples (DBS) tested at the lab and for which there is a result, i.e., positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes (1) other results of blood collection (e.g., technical problem in the field), (2) lost specimens, (3) noncorresponding bar codes, and (4) lab results such as blood not tested for a technical reason, not enough blood to complete the algorithm, etc. Table 14.2 shows coverage of HIV testing by background characteristics. Coverage rates for HIV testing among women were 91 percent or above across all age groups with the exception of the age group 40- 44 with an 88 percent rate. Among men, coverage rates for HIV testing were similarly high across all age groups (87-91 percent). 244 • HIV Prevalence Table 14.2 Coverage of HIV testing by selected background characteristics Percent distribution of women age 15-49 and men age 15-49 eligible for HIV testing by testing status, according to selected background characteristics (unweighted), Liberia 2013 Background characteristic Testing status Total Number DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed WOMEN Age 15-19 92.9 0.2 3.8 0.8 0.2 1.8 0.0 0.2 100.0 963 20-24 93.0 0.2 4.9 0.7 0.5 0.6 0.0 0.1 100.0 824 25-29 92.0 0.2 6.4 0.1 0.0 1.0 0.1 0.1 100.0 830 30-34 91.4 0.2 6.2 1.3 0.0 0.8 0.2 0.0 100.0 627 35-39 91.0 0.5 6.1 0.6 0.2 1.3 0.0 0.3 100.0 624 40-44 88.3 1.0 7.6 1.0 0.6 1.0 0.4 0.0 100.0 489 45-49 92.4 0.7 4.1 0.7 0.2 1.2 0.2 0.2 100.0 410 Education No education 91.5 0.6 5.2 1.1 0.2 1.0 0.2 0.2 100.0 1,931 Primary 93.8 0.1 4.3 0.5 0.1 1.1 0.1 0.0 100.0 1,617 Secondary and higher 90.7 0.4 6.8 0.3 0.4 1.3 0.0 0.3 100.0 1,135 Wealth quintile Lowest 92.0 0.6 4.5 1.1 0.3 1.2 0.1 0.1 100.0 1,394 Second 94.6 0.3 3.4 0.2 0.2 1.1 0.2 0.0 100.0 1,209 Middle 92.3 0.4 4.9 0.7 0.2 1.3 0.1 0.1 100.0 960 Fourth 91.0 0.1 7.2 0.6 0.0 0.7 0.1 0.1 100.0 670 Highest 85.0 0.2 11.6 1.1 0.4 1.1 0.0 0.6 100.0 534 Total 91.8 0.4 5.5 0.7 0.2 1.1 0.1 0.1 100.0 4,767 MEN Age 15-19 87.9 0.8 6.2 1.5 0.2 2.8 0.4 0.2 100.0 894 20-24 87.2 0.6 6.9 1.2 0.1 3.2 0.3 0.4 100.0 682 25-29 87.6 0.1 7.2 1.6 0.0 2.7 0.6 0.1 100.0 671 30-34 87.9 0.2 7.5 1.3 0.2 2.2 0.6 0.2 100.0 627 35-39 87.5 0.7 7.4 1.6 0.2 2.1 0.4 0.2 100.0 570 40-44 89.5 0.0 5.7 2.0 0.0 2.0 0.6 0.4 100.0 512 45-49 90.6 0.3 5.2 1.4 0.3 1.7 0.3 0.3 100.0 362 Education No education 86.9 0.8 5.4 2.5 0.0 3.4 0.3 0.8 100.0 647 Primary 90.0 0.4 5.9 1.3 0.1 1.9 0.3 0.1 100.0 1,458 Secondary and higher 87.6 0.3 6.9 1.3 0.2 2.8 0.6 0.2 100.0 2,012 Wealth quintile Lowest 90.2 0.3 4.7 1.5 0.2 2.3 0.5 0.3 100.0 1,226 Second 89.9 0.4 4.6 1.4 0.1 3.0 0.5 0.2 100.0 1,103 Middle 88.3 0.9 6.1 0.8 0.0 3.3 0.1 0.4 100.0 849 Fourth 84.7 0.0 11.9 1.0 0.2 1.4 0.9 0.0 100.0 582 Highest 83.2 0.4 10.2 3.2 0.4 1.8 0.5 0.4 100.0 558 Total 88.1 0.4 6.6 1.5 0.1 2.5 0.5 0.3 100.0 4,318 1 Includes all dried blood samples (IDBS) tested at the lab for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes (1) other results of blood collection (e.g. technical problem in the field), (2) lost specimens, (3) noncorresponding bar codes, and (4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. By education level, testing coverage levels were higher for women and men with only primary education than for those who had no education or some secondary education. Women in the highest wealth quintile and men in the two highest wealth quintiles had lower coverage rates than those in lower wealth quintiles. HIV Prevalence • 245 Additional tables describing the relationship between participation in HIV testing and characteristics related to HIV risk are presented in Appendix A (see Tables A.7-A.10). Overall, the results in Tables A.7-A.10 do not show a systematic relationship between participation in testing and variables associated with a higher risk of HIV infection. 14.2 HIV PREVALENCE 14.2.1 HIV Prevalence by Age and Sex The HIV-1 prevalence observed in the 2013 LDHS among adults age 15-49 is 1.9 percent (Table 14.3). HIV-1 prevalence is comparable between women and men age 15-49 (2.0 and 1.7 percent, respectively). Among women, peak prevalence occurs in the 25-29 age group (3.6 percent); among men, prevalence is highest among those age 40-44 (3.6 percent). There is no consistent pattern of HIV-1 prevalence by age among either women or men; rather, the prevalence fluctuates by age group. Table 14.3 HIV prevalence by age Among the de facto women age 15-49 and men age 15-49 who were interviewed and tested, the percentage HIV positive, by age, Liberia 2013 Age Women Men Total Percent- age HIV-1 positive Percent- age HIV-2 positive Percent- age HIV-1 or HIV-2 positive Number Percent- age HIV-1 positive Percent- age HIV-2 positive Percent- age HIV-1 or HIV-2 positive Number Percent- age HIV-1 positive Percent- age HIV-2 positive Percent- age HIV-1 or HIV-2 positive Number 15-19 0.2 0.0 0.2 996 0.6 0.4 1.0 825 0.4 0.2 0.6 1,820 20-24 2.9 0.0 2.9 822 0.5 0.0 0.5 642 1.8 0.0 1.8 1,464 25-29 3.6 0.3 4.0 765 2.2 0.0 2.2 620 3.0 0.2 3.2 1,386 30-34 1.8 0.0 1.8 545 2.8 0.0 2.8 505 2.3 0.0 2.3 1,050 35-39 2.6 0.2 2.8 551 2.1 0.0 2.1 429 2.4 0.1 2.5 979 40-44 0.2 3.3 3.5 391 3.6 0.0 3.6 452 2.0 1.5 3.6 843 45-49 3.1 0.0 3.1 328 1.5 0.1 1.6 312 2.3 0.0 2.3 640 Total 2.0 0.4 2.4 4,397 1.7 0.1 1.8 3,785 1.9 0.3 2.1 8,182 Only a tiny fraction of women and men age 15-49 are infected with HIV-2 (0.3 percent). No women or men were observed to be infected with both HIV-1 and HIV-2 (data not shown). In the remainder of this chapter, results are presented only for HIV-1 infection. Consequently, in Tables 14.4-14.11 and in the rest of the text of this chapter, HIV infection refers only to those individuals infected with HIV-1. Liberia is characterized by the UNAIDS classification scheme as having a low-level generalized HIV epidemic with an HIV prevalence that consistently exceeds 1 percent among pregnant women (NAC, 2010). The 2013 LDHS HIV prevalence estimates are consistent with this classification, and are also in line with other recent estimates. For example, based on data collected from the prenatal clinic surveillance system in 2011, the HIV prevalence was estimated to be 2.6 percent among prenatal clinic attendees1 (MOHSW and NACP, 2011). A comparison of the 2007 LDHS and 2013 LDHS HIV prevalence estimates indicates that HIV prevalence for all adults age 15-49 increased from 1.5 percent to 1.9 percent. Prevalence among women age 15-49 shifted from 1.8 to 2.0 percent, and prevalence among men age 15-49 increased from 1.2 percent to 1.7 1 Prevalence estimates by HIV type were as follows: 1.4 percent HIV-1 only, 0.1 percent HIV-2 only, and 1.1 percent both HIV-1 and HIV-2. Prevalence estimates ranged from 0.3 percent to 6.3 percent, depending on the sentinel site analyzed. 246 • HIV Prevalence percent. Note, however, that the differences between the 2007 and 2013 estimates of HIV prevalence are not statistically significant. As shown in Figure 14.1, the confidence intervals (CIs) for the 2007 and 2013 HIV prevalence estimates for all adults age 15-49 overlap (1.3-1.8 and 1.3-2.5, respectively). Similarly, by sex, there are no statistically significant changes in HIV prevalence among women or men between the two surveys. For women, the confidence interval is 1.4-2.7 compared with 1.4-2.2 reported in 2007. For men, the confidence interval is 1.0-2.5 compared with 0.8-1.5 reported in 2007 LDHS. Thus, the small differences in HIV prevalence observed between the two surveys are not large enough to be statistically significant with the sample sizes of the surveys. Figure 14.1 HIV prevalence among all adults age 15-49, and by sex, Liberia 2007 and 2013 1.5 1.9 1.8 2.0 1.2 1.7 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Total 2007 LDHS Total 2013 LDHS Women 2007 LDHS Women 2013 LDHS Men 2007 LDHS Men 2013 LDHS Percent Midpoint of Confidence Interval LDHS 2013 The HIV prevalence estimate for the 15-19 age group is assumed to represent new infections and therefore serves as a proxy for HIV incidence among young people. A comparison of HIV prevalence estimates in the 15-19 age group between the 2007 LDHS (0.9 percent) and the 2013 LDHS (0.4 percent) reveals prevalence has remained stable or slightly declined among this age group. This is an encouraging finding in terms of the prospects of achieving the Millennium Development Goal (MDG) 6, which calls for halting and beginning to reverse the spread of HIV/AIDS by 2015. 14.2.2 HIV Prevalence by Socioeconomic Characteristics Table 14.4 shows the variation in HIV prevalence among women and men age 15-49 by socioeconomic characteristics. Differences by socioeconomic characteristic are small. Nevertheless, several observations warrant attention. Among women and men combined, HIV prevalence is higher in urban areas (2.6 percent) than in rural areas (0.8 percent). Among urban areas, prevalence is higher in Greater Monrovia (3.2 percent) than in other urban areas (1.7 percent). The higher prevalence in Greater Monrovia relative to other geographic areas may reflect the fact that Monrovia is the largest city in Liberia; because of the diverse opportunities it affords, Monrovia continues to attract migrants, both those displaced as a result of the civil HIV Prevalence • 247 conflict and those seeking new economic opportunities. Such persons may be separated from their spouses or regular sexual partners, putting them at increased risk of engaging in transactional sex, finding new sexual partners, or both, which may increase their risk of contracting HIV. Table 14.4 HIV prevalence by socioeconomic characteristics Percentage HIV positive among women and men age 15-49 who were tested, by socioeconomic characteristics, Liberia 2013 Socioeconomic characteristic Women Men Total Percentage HIV positive1 Number Percentage HIV positive1 Number Percentage HIV positive1 Number Religion Christian 2.2 3,748 1.8 3,097 2.0 6,845 Muslim 1.4 512 2.2 498 1.8 1,010 Traditional religion * 23 0.0 51 0.0 75 No religion 0.0 107 0.0 123 0.0 230 Other * 1 nc 0 * 1 Employment (past 12 months ) Not employed 2.6 1,954 1.5 981 2.3 2,935 Employed 1.5 2,443 1.8 2,803 1.7 5,247 Residence Urban 2.7 2,653 2.5 2,218 2.6 4,871 Greater Monrovia 3.0 1,605 3.4 1,311 3.2 2,917 Other urban 2.3 1,048 1.1 907 1.7 1,955 Rural 1.0 1,744 0.7 1,567 0.8 3,311 Region North Western 1.2 396 0.4 338 0.9 734 South Central 2.6 2,293 2.9 1,975 2.7 4,268 South Eastern A 1.1 231 1.5 233 1.3 465 South Eastern B 2.7 283 0.8 264 1.8 547 North Central 1.2 1,194 0.2 974 0.7 2,168 Education No education 2.3 1,461 2.1 487 2.3 1,947 Primary 1.5 1,335 1.4 1,119 1.5 2,454 Secondary and higher 2.2 1,602 1.8 2,179 2.0 3,781 Wealth quintile Lowest 0.7 780 0.8 702 0.8 1,482 Second 0.8 810 0.5 703 0.7 1,513 Middle 1.5 815 0.9 673 1.2 1,488 Fourth 3.5 1,010 2.3 768 3.0 1,778 Highest 3.0 982 3.5 939 3.3 1,921 Total 2.0 4,397 1.7 3,785 1.9 8,182 Note: For women, the total includes 8 cases for which information on religion is missing. For men, the total includes 13 cases for which information on religion is missing and 1 case for which information on employment is missing. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. nc = No cases 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. There is no clear correlation between education level and HIV prevalence; however, prevalence generally increases with increasing wealth quintile. For women, HIV prevalence increases from 0.7 percent among those in the lowest wealth quintile to 3.5 and 3.0 percent among those in the highest two wealth quintiles, respectively. For men, HIV prevalence increases from 0.8 percent among those in the lowest wealth quintile to 3.5 percent among those in the highest. 14.2.3 HIV Prevalence by Other Sociodemographic and Health Characteristics Table 14.5 shows HIV prevalence by demographic characteristics. Marital status and HIV prevalence are related, with the highest infection rates among widowed women (9.0 percent) and divorced or separated men (5.1 248 • HIV Prevalence percent). Those who have never been married have a lower HIV prevalence than those who are married (1.1 percent and 2.1 percent, respectively). HIV prevalence among men and women in non-polygynous unions differed little (2.3 percent and 2.1 percent, respectively). However, women in polygynous unions were more likely than men in polygynous unions to be infected with HIV (2.6 percent and 0.0 percent, respectively). Table 14.5 HIV prevalence by demographic characteristics Percentage HIV positive among women and men age 15-49 who were tested, by demographic characteristics, Liberia 2013 Demographic characteristic Women Men Total Percentage HIV positive1 Number Percentage HIV positive1 Number Percentage HIV positive1 Number Marital status Never married 1.3 1,434 1.0 1,617 1.1 3,051 Ever had sexual intercourse 1.6 1,143 1.5 1,089 1.5 2,232 Never had sexual intercourse 0.0 291 0.1 528 0.1 819 Married/living together 2.1 2,541 2.1 2,025 2.1 4,566 Divorced or separated 2.3 315 5.1 121 3.1 436 Widowed 9.0 107 * 22 7.4 129 Type of union In polygynous union 2.6 338 0.0 238 1.5 576 In non-polygynous union 2.1 2,149 2.3 1,966 2.2 4,115 Not currently in union 1.9 1,856 1.3 1,544 1.6 3,401 In union, polygyny status unknown or missing 0.0 54 (0.0) 35 0.0 89 Currently pregnant Pregnant 4.6 372 na na na na Not pregnant or not sure 1.8 4,026 na na na na Prenatal care for last birth in the last 3 years Prenatal care provided by the public sector 1.6 1,436 na na na na Prenatal care provided by other than the public sector 3.1 313 na na na na No prenatal care/No birth in last 3 years 2.1 2,645 na na na na Male circumcision Circumcised na na 1.8 3,754 na na Not circumcised na na (0.0) 25 na na Total 2.0 4,397 1.7 3,785 1.9 8,182 Note: For women, total includes 3 cases for which information on prenatal care is missing. For men, total includes 5 cases for which information on circumcision is missing. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = not applicable 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. Women who were pregnant at the time of the survey had a higher HIV prevalence rate than those who were not pregnant or who were unsure of their pregnancy status (4.6 percent and 1.8 percent, respectively). This correlates with the three previous ANC survey results that show higher HIV prevalence among pregnant women than other women (MOHSW and NACP, 2011). HIV prevalence varied little by whether or not women received prenatal care for their last birth in the three-year period preceding the survey or by source of prenatal care (public sector or another source) among those who received it. Male circumcision is assumed to reduce the risk of HIV infection, in part because of physiological differences that decrease the susceptibility to HIV infection among circumcised men. Several recent studies in HIV Prevalence • 249 sub-Saharan Africa, including clinical trials conducted in South Africa, Kenya, and Uganda (Auvert et al., 2005; NIAID, 2006), have documented that the protective effect of male circumcision is significant. Table 14.5 also presents data on the relationship between HIV prevalence and male circumcision among men age 15-49 who were tested for HIV in the survey and who responded to the question about their circumcision status. However, as male circumcision in Liberia is nearly universal (see Table 13.13), there are too few cases of uncircumcised men to allow for a robust comparison of circumcision status on HIV prevalence. 14.2.4 HIV Prevalence by Sexual Risk Behavior Chapter 13 of the 2013 LDHS has shown that HIV knowledge in the general population is relatively high, yet risky behaviors, including high numbers of sexual partners and a lack of condom use, are common and therefore remain a significant public health concern. Table 14.6 presents HIV prevalence rates by sexual behavior characteristics among respondents who have ever had sexual intercourse. In reviewing these results, it is important to remember that responses about sexual risk behaviors may be subject to reporting bias. Also, sexual behavior in the 12 months preceding the survey may not adequately reflect lifetime sexual risk. Nor is it possible to know the sequence of events (e.g., whether any reported condom use occurred before or after HIV transmission). Table 14.6 shows no clear relationship between HIV prevalence with increasing age at sexual debut among women or men who ever had sex. The association of HIV prevalence with multiple sexual partners and partner concurrency was also examined in the 2013 LDHS. A respondent was considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. Among men, this included those who had overlapping sexual partnerships with two or more, or polygynous, wives. Among women, HIV prevalence was higher among those who had no sexual partners (3.1 percent) or two or more sexual partners (2.9 percent) in the past 12 months than among those who had only one partner in the past 12 months (2.0 percent). Women who had concurrent partners were less likely than those who had no concurrent partners to be infected with HIV (1.9 percent and 3.8 percent, respectively). Among men, there was no difference in prevalence among those who had no partners in the past 12 months compared with those who had one or more. However, as with women, prevalence was lower among men who had concurrent partners (0.9 percent) than among those who did not (2.3 percent). Among both women and men, there is no clear correlation between HIV prevalence and number of lifetime partners. For example, only 0.7 percent of women who had one partner were HIV positive compared with 2.8 percent who had three to nine partners and 1.9 percent who had 10 or more. For men, prevalence is lower among those who have had three to four or five to nine partners than among those who have had fewer or more lifetime partners. Table 14.6 also shows no clear correlation between condom use at last sexual intercourse and HIV status among women or men. The HIV prevalence among women who used a condom during their most recent sexual intercourse in the 12-month period before the survey varied little from those who did not use a condom during their last sexual intercourse (2.3 percent and 2.0 percent, respectively). In contrast, men who used a condom during their most recent sexual intercourse in the 12-month period before the survey were slightly less likely to be infected than men who did not use a condom (1.3 percent and 2.2 percent, respectively). 250 • HIV Prevalence Table 14.6 HIV prevalence by sexual behavior Percentage HIV positive among women and men age 15-49 who ever had sex and were tested for HIV, by sexual behavior characteristics, Liberia 2013 Sexual behavior characteristic Women Men Total Percentage HIV positive1 Number Percentage HIV positive1 Number Percentage HIV positive1 Number Age at first sexual intercourse <16 2.5 2,001 2.0 756 2.4 2,757 16-17 1.1 1,362 2.0 943 1.5 2,305 18-19 4.0 480 1.6 945 2.4 1,425 20+ 1.6 125 2.8 594 2.6 719 Missing 1.4 138 (0.0) 19 1.2 156 Multiple sexual partners and partner concurrency in past 12 months 0 3.1 395 2.0 93 2.9 488 1 2.0 3,402 2.1 2,489 2.0 5,890 2+ 2.9 308 1.6 673 2.0 981 Had concurrent partners2 1.9 142 0.9 309 1.2 451 None of the partners were concurrent 3.8 165 2.3 365 2.7 530 Condom use at last sexual intercourse in past 12 months Used condom 2.3 363 1.3 659 1.7 1,023 Did not use condom 2.0 3,345 2.2 2,503 2.1 5,848 No sexual intercourse in last 12 months 3.1 396 2.0 95 2.9 491 Number of lifetime partners 1 0.7 640 2.0 159 0.9 798 2 2.0 986 2.6 297 2.1 1,283 3-4 2.8 1,382 1.1 485 2.3 1,868 5-9 2.8 737 1.4 752 2.1 1,489 10+ 1.9 259 2.0 1,209 2.0 1,468 Don't know/Missing 1.9 101 4.0 355 3.5 456 Paid for sexual intercourse in past 12 months Yes na na 2.6 183 na na Used condom na na 0.6 111 na na Did not use condom na na 5.6 72 na na No (No paid sexual intercourse/no sexual intercourse in last 12 months) na na 2.0 3,073 na na Total 2.2 4,105 2.0 3,257 2.1 7,362 Note: Figures in parentheses are based on 25-49 unweighted cases. Total includes 2 women and 1 man for whom information on multiple sexual partners and partner concurrency is missing. na = Not applicable 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. 2 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). The HIV prevalence estimate among men involved in a paid sexual encounter during the 12 months before the survey is 2.6 percent. The prevalence among men who paid for sex and did not use a condom is higher than for those who did use a condom (5.6 percent and 0.6 percent, respectively). In summary, the results presented in Table 14.6 do not demonstrate a consistent relationship between sexual risk behavior and HIV prevalence. Additional analysis may be necessary to understand these relationships because they are often confounded by other factors that are associated with both behavioral HIV Prevalence • 251 measures and HIV prevalence such as age, marital status, and residence. In addition, because HIV prevalence rates are low overall, even when differences in prevalence are linked with behavior, they may not be possible to parse. 14.3 HIV PREVALENCE AMONG YOUNG PEOPLE Young people in the 15-24 age range are an important group to monitor for reduction of HIV incidence in the population. This was specified in the United Nations General Assembly Special Session (UNGASS) on HIV and AIDS. Table 14.7 shows that HIV prevalence among those age 15-24 is low (1.0 percent); 1.4 percent of young women and 0.5 percent of young men are HIV positive. Young people living in Greater Monrovia (1.8 percent) are somewhat more likely to be infected than those in other urban areas (0.6 percent) or rural areas (0.4 percent). Although the overall HIV prevalence among young women and men is similar, comparison by background characteristics reveals some important distinctions. HIV prevalence is higher among young women who are married (2.7 percent) or divorced, separated, or widowed (4.6 percent) than among those who have never married (0.7 percent). These distinctions are not observed among young men. Although the overall differences are small, there does appear to be an inverse correlation between education level and HIV prevalence – young adults with at least some education have lower HIV prevalence than those with no education. Young women who are currently pregnant are more likely to be HIV positive than those who are not (5.3 percent and 1.0 percent, respectively), and this relatively high prevalence is of great concern. Combined with the evidence of high teen sexuality (see Chapter 13) and childbearing (see Chapter 5), and low levels of HIV testing (Chapter 13), young women are at repeated risk of exposure to HIV. This is an issue not only for themselves, but also for the children born to them. 252 • HIV Prevalence Table 14.7 HIV prevalence among young people by background characteristics Percentage HIV-positive among women and men age 15-24 who were tested for HIV, by background characteristics, Liberia 2013 Background characteristic Women Men Total Percentage HIV positive1 Number Percentage HIV positive1 Number Percentage HIV positive1 Number Age 15-19 0.2 996 0.6 825 0.4 1,820 15-17 0.1 613 0.4 534 0.2 1,147 18-19 0.5 382 1.0 291 0.7 673 20-24 2.9 822 0.5 642 1.8 1,464 20-22 3.3 510 0.5 428 2.0 938 23-24 2.2 312 0.4 214 1.5 526 Marital status Never married 0.7 1,204 0.5 1,298 0.6 2,503 Ever had sex 0.9 914 0.8 779 0.9 1,693 Never had sex 0.0 290 0.1 520 0.1 810 Married/Living together 2.7 541 0.8 154 2.3 695 Divorced/Separated/Widowed 4.6 72 * 14 3.8 86 Currently pregnant Pregnant 5.3 169 na na na na Not pregnant or not sure 1.0 1,649 na na na na Residence Urban 1.9 1,219 0.7 958 1.3 2,177 Greater Monrovia 2.3 777 1.0 582 1.8 1,360 Other urban 1.1 441 0.1 376 0.6 817 Rural 0.5 599 0.3 508 0.4 1,108 Region North Western 0.9 141 0.3 93 0.6 234 South Central 2.0 1,052 0.8 835 1.5 1,887 South Eastern A 0.2 81 0.3 86 0.2 167 South Eastern B 1.5 104 0.3 98 0.9 202 North Central 0.5 440 0.1 354 0.3 794 Education No education 3.2 230 0.0 77 2.4 307 Primary 1.5 782 0.0 539 0.9 1,320 Secondary and higher 0.9 807 0.9 851 0.9 1,658 Wealth quintile Lowest 0.7 236 0.4 201 0.6 437 Second 0.5 287 0.3 234 0.4 521 Middle 0.8 331 0.2 244 0.5 574 Fourth 1.5 469 0.0 325 0.9 794 Highest 2.7 495 1.3 463 2.0 959 Total 15-24 1.4 1,818 0.5 1,467 1.0 3,285 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. Table 14.8 shows HIV prevalence among young people by sexual behavior. As was the case for women and men age 15-49 who had ever had sex, the variations in HIV prevalence according to the measures of sexual behavior included in Table 14.8 are difficult to interpret. Among young women who had ever had sex, those who had no concurrent partners in the past 12 months were more likely to be HIV positive than those who had concurrent partners, although the latter value was based on a small number of cases. The opposite was true for young men. Condom use also has an inconsistent relationship with HIV prevalence among young people. HIV Prevalence • 253 Table 14.8 HIV prevalence among young people by sexual behavior Percentage HIV-positive among women and men age 15-24 who have ever had sex and were tested for HIV, by sexual behavior characteristics, Liberia 2013 Sexual behavior characteristic Women Men Total Percentage HIV positive1 Number Percentage HIV positive1 Number Percentage HIV positive1 Number Multiple sexual partners and partner concurrency in past 12 months 0 2.3 132 (0.0) 40 1.7 172 1 1.4 1,236 0.9 725 1.2 1,961 2+ 3.5 159 0.6 182 2.0 341 Had concurrent partners2 (0.0) 45 2.0 57 1.1 102 None of the partners were concurrent 4.8 115 0.0 125 2.3 239 Condom use at last sexual intercourse in past 12 months Used condom 2.6 257 0.4 349 1.4 606 Did not use condom 1.4 1,139 1.1 558 1.3 1,696 No sexual intercourse in last 12 months 2.3 132 (0.0) 40 1.7 172 Total 15-24 1.7 1,527 0.8 947 1.4 2,474 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. 2 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). 14.4 HIV PREVALENCE BY OTHER CHARACTERISTICS RELATED TO HIV RISK Table 14.9 presents HIV prevalence by other characteristics related to HIV risk among women and men age 15-49 who have ever had sex. The table shows that women and men with a history of a sexually transmitted infection (STI) or STI symptoms differ little with regard to HIV prevalence when compared with those with no history or symptoms. Table 14.9 HIV prevalence by other characteristics Percentage HIV positive among women and men age 15-49 who ever had sex and were tested for HIV, by whether had an STI in the past 12 months and by prior testing for HIV, Liberia 2013 Characteristic Women Men Total Percentage HIV positive1 Number Percentage HIV positive1 Number Percentage HIV positive1 Number Sexually transmitted infection in past 12 months Had STI or STI symptoms 2.3 2,006 1.9 567 2.2 2,574 No STI, no symptoms 2.0 2,089 2.0 2,675 2.0 4,765 Don't know/missing * 9 * 14 (1.2) 23 Prior HIV testing Ever tested 2.6 2,177 3.0 961 2.7 3,138 Received results 2.2 1,949 3.1 841 2.5 2,790 Did not receive results 5.3 228 2.5 121 4.3 348 Never tested 1.7 1,920 1.6 2,295 1.6 4,216 Total 2.2 4,105 2.0 3,257 2.1 7,362 Note: Total includes 8 women for whom information on prior HIV testing is missing. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. 254 • HIV Prevalence The table also shows that individuals who had been tested for HIV previously were more likely to be HIV positive than those who had never been tested (2.7 percent and 1.6 percent, respectively). Among women but not men who had been tested previously, the HIV infection rate was higher among those who reported that they had not received the result from their last test than among those who reported that they had received the result. Table 14.10 provides further information about the relationship between prior HIV testing and the actual HIV status of respondents. The results show that less than half (45 percent) of individuals who are HIV positive have been tested previously and received the result of their last test. This represents a vast increase from the 2007 LDHS, in which only 9 percent of respondents who had been previously tested reported that they had received the result of their last test. However, a majority of HIV-positive respondents have either never been tested (45 percent) or have not received the results of their last test (10 percent) and therefore do not know that they can transmit HIV if they have unprotected sex. Table 14.10 Prior HIV testing by current HIV status Percent distribution of women and men age 15-49 who tested HIV positive and who tested HIV negative by HIV testing status prior to the survey, Liberia 2013 Women Men Total HIV testing prior to the survey HIV positive1 HIV negative HIV positive1 HIV negative HIV positive1 HIV negative Previously tested Received result of last test 49.2 44.2 (39.7) 22.1 45.1 33.9 Did not receive result of last test 13.6 5.3 (4.5) 3.2 9.7 4.3 Not previously tested 37.3 50.3 (55.8) 74.7 45.2 61.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 89 4,308 66 3,719 155 8,027 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. 14.5 HIV PREVALENCE AMONG COUPLES A total of 1,593 cohabiting couples were tested for HIV in the 2013 LDHS. The results shown in Table 14.11 indicate that, among 96.8 percent of cohabiting couples, both partners tested negative for HIV. Both partners were HIV positive in 0.5 percent of cohabiting couples, while 2.8 percent of couples were discordant, that is, one partner was infected and the other was not. In 1.7 percent of couples, the male partner was infected and the woman was not, while in 1.1 percent of couples, the woman was infected and the man was not. Differences in HIV prevalence among couples were small with one exception: in only 86.1 percent of cohabitating couples in which the man was 15 or more years older than his partner were both partners HIV negative. Both partners were HIV positive in 7.0 percent of these intergenerational couples; the man was positive and woman was HIV negative in 5.2 percent of these couples, and the woman was positive and the man negative in 1.6 percent of these couples. Table 14.11 HIV prevalence among couples Percent distribution of couples living in the same household, both of whom were tested for HIV, by HIV status, according to background characteristics, Liberia 2013 Background characteristic Both HIV positive1 Man HIV positive, woman HIV negative1 Woman HIV positive, man HIV negative1 Both HIV negative1 Total Number Woman's age 15-19 0.0 1.6 2.0 96.4 100.0 110 20-29 1.1 2.4 1.6 94.9 100.0 689 30-39 0.0 1.4 0.5 98.0 100.0 579 40-49 0.0 0.2 0.3 99.6 100.0 215 …Continued HIV Prevalence • 255 Table 14.11 HIV prevalence among couples—Continued Background characteristic Both HIV positive1 Man HIV positive, woman HIV negative1 Woman HIV positive, man HIV negative1 Both HIV negative1 Total Number Man's age 15-19 * * * * 100.0 10 20-29 0.0 1.8 0.9 97.3 100.0 441 30-39 0.4 2.4 0.5 96.7 100.0 618 40-49 1.0 0.8 1.9 96.3 100.0 524 Age difference between partners Woman older 0.0 0.2 0.2 99.6 100.0 168 Same age/man older by 0-4 years 0.0 1.3 0.4 98.2 100.0 630 Man older by 5-9 years 0.4 2.8 1.3 95.5 100.0 515 Man older by 10-14 years 0.0 0.0 3.0 97.0 100.0 203 Man older by 15+ years 7.0 5.2 1.6 86.1 100.0 76 Type of union Non-polygynous 0.5 1.8 1.2 96.5 100.0 1,417 Polygynous 0.0 0.3 0.4 99.3 100.0 154 Don't know/missing * * * * 100.0 21 Multiple partners in past 12 months2 Both no 0.5 1.6 1.0 96.9 100.0 1,182 Man yes, woman no 0.4 2.3 1.1 96.2 100.0 333 Woman yes, man no 0.0 0.0 2.3 97.7 100.0 73 Both yes * * * * 100.0 3 Either missing * * * * 100.0 2 Concurrent sexual partners in past 12 months3 Both no 0.5 1.9 1.0 96.6 100.0 1,350 Man yes, woman no 0.8 0.5 1.9 96.8 100.0 197 Woman yes, man no (0.0) (0.0) (0.0) (100.0) 100.0 45 Both yes * * * * 100.0 1 Residence Urban 0.9 2.4 1.2 95.5 100.0 826 Greater Monrovia 1.2 3.6 1.5 93.7 100.0 465 Other urban 0.7 1.0 0.7 97.7 100.0 361 Rural 0.0 0.9 1.0 98.2 100.0 767 Region North Western 0.0 0.5 1.3 98.2 100.0 167 South Central 0.9 2.9 1.5 94.7 100.0 739 South Eastern A 0.1 3.1 1.2 95.6 100.0 94 South Eastern B 0.8 0.3 1.9 97.1 100.0 105 North Central 0.0 0.4 0.2 99.5 100.0 488 Woman's education No education 0.8 1.9 0.6 96.7 100.0 705 Primary 0.3 1.9 0.4 97.4 100.0 482 Secondary and higher 0.2 1.0 2.6 96.2 100.0 405 Man's education No education 0.0 0.5 0.7 98.8 100.0 295 Primary 1.4 2.0 0.9 95.7 100.0 427 Secondary and higher 0.2 2.0 1.3 96.6 100.0 872 Wealth quintile Lowest 0.0 1.0 0.7 98.3 100.0 376 Second 0.0 0.9 0.6 98.5 100.0 348 Middle 0.5 0.4 0.4 98.7 100.0 315 Fourth 0.3 4.9 2.4 92.4 100.0 297 Highest 2.1 1.6 1.5 94.8 100.0 258 Total 0.5 1.7 1.1 96.8 100.0 1,593 Note: The table is based on couples for which a valid test result (positive or negative) is available for both partners. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Total includes two cases for which information on multiple partners in the past 12 months is missing. 1 HIV positive refers only to individuals infected with HIV-1. Individuals infected with HIV-2 only are not counted as HIV positive when calculating the numerator of the percentages. 2 A respondent is considered to have had multiple sexual partners in the past 12 months if he or she had sexual intercourse with two or more people during this time period. (Respondents with multiple partners include polygynous men who had sexual intercourse with two or more wives.) 3 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). Women’s Empowerment and Demographic and Health Outcomes • 257 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 15 his chapter explores women’s empowerment in terms of earnings, control over earnings, and magnitude of earnings relative to those of their partners. In addition, responses to specific questions are used to define two different indicators of women’s empowerment: women’s participation in household decision making and women’s attitudes towards wife beating. The extent to which women’s empowerment influences maternal health, contraceptive use, and child mortality is also examined. 15.1 WOMEN’S AND MEN’S EMPLOYMENT Table 15.1 shows, by type of earnings received, the percent distribution of currently married women and men age 15-49 who were employed in the 12 months preceding the survey. Employment is assumed to go hand-in-hand with payment for work. However, not all women and men receive earnings for the work they do, and among those who do receive earnings, not all receive cash. Sixty-six percent of currently married women reported being employed at any time in the 12 months preceding the survey. Of the employed women, 57 percent received cash earnings only, 11 percent received T Key Findings • Sixty-six percent of currently married women and 94 percent of currently married men were employed at some point in time in the 12 months preceding the survey. • Fifty-four percent of married women who receive cash earnings report jointly deciding with their husbands how their own earnings will be used; 30 percent say they decide on their own how to use their earnings. • The majority of women report that they do not own a house (70 percent). Nineteen percent of women say that they own a house jointly with someone else, 8 percent own their house alone, and 3 percent own a house both jointly and alone. • The majority of currently married women (58-61 percent) report that each of three household decisions is made jointly with their husbands. Sixteen percent of women report that they alone make decisions about their own health care; 19 percent make their own decisions to visit their families and relatives, and 24 percent make their own decisions about major household purchases. • Forty-three percent of women believe that a husband is justified in beating his wife for at least one of five specified reasons (if she burns the food, if she goes out without telling him, if she neglects the children, if she argues with him, or if she refuses to have sexual intercourse with him). Conversely, only 24 percent of men believe that a husband is justified in beating his wife for at least one of these same five specified reasons. • Half of all women who have heard of the Sande society are members. Among members of the Sande society, 39 percent think it should disband. 258 • Women’s Empowerment and Demographic and Health Outcomes both cash and in-kind earnings, and 2 percent received in-kind earnings only. Thirty percent did not receive any form of earnings for their work. The percentage of currently married women who are employed increases with age, from 42 percent of those ages 15-19 to a peak of 78 percent in the age groups 40-44 and 45-49. Ninety-four percent of currently married men age 15-49 were employed during the 12 months preceding the survey. Among the men employed, 66 percent received cash only, 13 percent received a combination of cash and in-kind earnings, and 1 percent received in-kind earnings only for the work they did. Twenty-one percent of men did not get paid for their work. Table 15.1 Employment and cash earnings of currently married women and men Percentage of currently married women and men age 15-49 who were employed at any time in the past 12 months and the percent distribution of currently married women and men employed in the past 12 months by type of earnings, according to age, Liberia 2013 Age Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Total Number of respondents Percentage employed in past 12 months Number of respondents Cash only Cash and in- kind In-kind only Not paid WOMEN 15-19 42.4 299 46.3 13.6 8.1 32.0 100.0 127 20-24 53.3 862 56.1 12.7 2.5 28.7 100.0 459 25-29 62.2 1,168 60.6 8.1 1.6 29.6 100.0 727 30-34 68.2 957 59.5 10.5 2.1 27.7 100.0 652 35-39 73.4 924 55.8 14.2 1.7 28.2 100.0 679 40-44 77.6 619 53.5 11.8 2.5 32.2 100.0 480 45-49 78.4 557 53.9 11.7 2.4 31.9 100.0 437 Total 66.1 5,386 56.6 11.4 2.3 29.6 100.0 3,560 MEN 15-19 56.6 13 * * * * * 8 20-24 86.5 152 60.7 10.7 1.4 27.2 100.0 131 25-29 89.5 434 70.7 9.6 0.4 19.2 100.0 388 30-34 94.5 475 64.4 12.9 1.4 21.3 100.0 449 35-39 98.1 421 61.4 16.0 0.2 22.4 100.0 413 40-44 94.6 422 64.5 15.6 0.4 19.5 100.0 399 45-49 96.5 302 71.7 9.3 0.8 18.1 100.0 291 Total 93.7 2,218 65.7 12.8 0.7 20.7 100.0 2,079 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Totals include 9 women and 2 men for whom information on type of earnings is missing. 15.2 WOMEN’S CONTROL OVER THEIR OWN EARNINGS AND RELATIVE MAGNITUDE OF WOMEN’S EARNINGS To assess women’s autonomy, currently married women who earned cash for their work in the 12 months preceding the survey were asked who the main decision maker is with regard to the use of their earnings. This information allows the assessment of women’s control over their own earnings. Women who earned cash for their work were also asked the relative magnitude of their earnings compared with those of their husband. It is probable that employment and earnings are more likely to empower women if women themselves control their own earnings and perceive them as significant relative to those of their husband. Table 15.2.1 shows the degree of control women have over the use of their earnings, and their perception of the magnitude of their earnings relative to those of their husband, by background characteristics. Thirty percent of currently married women who receive cash earnings report that they alone mainly decide how their earnings are used, while 54 percent say they decide jointly with their husband. Only 15 percent of women report that their husband mainly decides how their earnings will be used. Women’s Empowerment and Demographic and Health Outcomes • 259 Table 15.2.1 Control over women's cash earnings and relative magnitude of women's cash earnings Percent distribution of currently married women age 15-49 who received cash earnings for employment in the 12 months preceding the survey by person who decides how wife's cash earnings are used and by whether she earned more or less than her husband, according to background characteristics, Liberia 2013 Person who decides how the wife's cash earnings are used: Total Wife's cash earnings compared with husband's cash earnings: Total Number of women Background characteristic Mainly wife Wife and husband jointly Mainly husband Other Missing More Less About the same Husband has no earnings Don't know/ missing Age 15-19 37.3 44.4 17.5 0.0 0.8 100.0 8.8 65.8 24.6 0.0 0.8 100.0 76 20-24 33.1 50.0 15.4 0.0 1.5 100.0 7.9 71.3 17.0 1.9 1.9 100.0 316 25-29 31.4 49.6 17.3 0.0 1.6 100.0 12.3 65.0 15.0 4.8 2.9 100.0 499 30-34 25.7 58.5 14.8 0.7 0.3 100.0 11.6 65.7 18.7 3.2 0.8 100.0 456 35-39 32.5 51.0 13.7 0.3 2.4 100.0 13.0 56.9 19.6 4.3 6.2 100.0 476 40-44 26.5 62.3 10.7 0.4 0.0 100.0 17.8 59.4 17.4 3.4 1.9 100.0 313 45-49 26.8 57.0 14.9 0.2 1.0 100.0 21.9 48.1 19.9 7.0 3.1 100.0 287 Number of living children 0 30.9 53.2 14.4 0.0 1.4 100.0 7.2 73.8 14.2 0.4 4.3 100.0 107 1-2 28.7 56.9 12.9 0.1 1.5 100.0 12.6 65.6 15.7 3.4 2.7 100.0 875 3-4 34.3 48.0 16.0 0.6 1.1 100.0 16.0 59.4 18.0 4.5 2.0 100.0 819 5+ 25.2 57.8 15.8 0.2 1.0 100.0 12.4 57.0 22.1 4.6 3.9 100.0 622 Residence Urban 32.3 53.6 12.7 0.3 1.2 100.0 14.4 63.1 14.6 4.6 3.4 100.0 1,521 Greater Monrovia 37.1 51.5 9.2 0.5 1.6 100.0 14.6 65.1 11.1 5.1 4.1 100.0 964 Other urban 23.9 57.1 18.6 0.0 0.5 100.0 14.0 59.6 20.6 3.7 2.0 100.0 557 Rural 25.6 54.7 18.3 0.2 1.2 100.0 12.0 59.3 23.9 2.9 2.0 100.0 902 Region North Western 25.4 47.6 26.5 0.0 0.6 100.0 8.8 62.9 22.9 3.8 1.6 100.0 275 South Central 33.3 56.3 8.8 0.4 1.2 100.0 15.4 62.2 14.9 4.1 3.4 100.0 1,362 South Eastern A 18.5 61.8 14.8 0.5 4.3 100.0 16.9 47.7 22.6 5.2 7.6 100.0 69 South Eastern B 29.5 51.0 17.7 0.0 1.8 100.0 19.9 58.5 14.7 3.5 3.4 100.0 84 North Central 25.4 51.4 22.0 0.2 1.0 100.0 10.2 61.9 22.6 3.7 1.6 100.0 633 County Bomi 40.3 49.3 10.4 0.0 0.0 100.0 12.7 45.3 32.3 9.7 0.0 100.0 47 Bong 25.9 56.3 17.2 0.5 0.0 100.0 6.6 71.7 17.9 3.0 0.8 100.0 188 Gbarpolu 29.7 48.7 21.0 0.0 0.6 100.0 9.7 70.5 14.0 2.3 3.5 100.0 66 Grand Bassa 34.6 53.1 11.8 0.6 0.0 100.0 24.1 53.1 18.0 2.3 2.5 100.0 126 Grand Cape Mount 19.2 46.6 33.4 0.0 0.8 100.0 7.3 65.0 23.8 2.7 1.3 100.0 161 Grand Gedeh 20.5 57.7 10.7 0.0 11.1 100.0 16.5 44.8 24.3 4.5 9.8 100.0 27 Grand Kru 24.2 54.2 16.9 0.0 4.7 100.0 11.1 64.6 16.4 0.3 7.6 100.0 32 Lofa 34.4 54.2 11.4 0.0 0.0 100.0 12.2 55.9 28.2 2.2 1.5 100.0 111 Margibi 12.7 81.8 4.6 0.0 0.9 100.0 13.5 55.7 27.3 2.3 1.2 100.0 159 Maryland 33.3 43.4 23.2 0.0 0.0 100.0 27.9 54.2 13.2 4.7 0.0 100.0 37 Montserrado 36.1 52.8 9.1 0.5 1.4 100.0 14.6 64.2 12.7 4.6 3.8 100.0 1,077 Nimba 22.1 47.7 28.3 0.0 1.9 100.0 11.6 58.4 23.4 4.5 2.1 100.0 335 River Cess 16.9 70.2 12.9 0.0 0.0 100.0 16.2 47.4 24.4 7.9 4.2 100.0 21 River Gee 31.8 62.9 5.3 0.0 0.0 100.0 19.4 56.1 14.6 7.2 2.7 100.0 15 Sinoe 17.5 58.7 22.1 1.8 0.0 100.0 18.0 51.6 18.7 3.4 8.2 100.0 21 Education No education 28.4 52.7 17.7 0.4 0.8 100.0 12.2 59.4 22.9 3.1 2.3 100.0 1,029 Primary 25.8 59.0 14.2 0.2 0.8 100.0 14.6 61.6 18.5 3.3 2.0 100.0 619 Secondary and higher 34.8 51.6 11.4 0.2 2.0 100.0 14.3 64.7 11.3 5.6 4.2 100.0 775 Wealth quintile Lowest 27.6 50.2 20.5 0.3 1.4 100.0 8.8 57.4 27.6 3.7 2.5 100.0 399 Second 24.3 55.0 19.5 0.0 1.2 100.0 13.8 56.9 25.5 2.1 1.8 100.0 400 Middle 24.1 53.0 20.6 0.9 1.5 100.0 13.0 59.9 19.6 4.4 3.1 100.0 480 Fourth 37.7 55.1 6.4 0.0 0.8 100.0 14.7 66.0 11.8 5.3 2.2 100.0 585 Highest 31.8 55.5 11.0 0.3 1.4 100.0 15.7 65.2 11.2 3.7 4.3 100.0 559 Total 29.8 54.0 14.8 0.3 1.2 100.0 13.5 61.7 18.1 4.0 2.8 100.0 2,423 Younger women are generally more likely than older women to make independent decisions on their earnings. There is a modest difference in control over women’s cash earnings by residence: 32 percent of urban and 26 percent of rural, currently married women report that they mainly decide how to spend their 260 • Women’s Empowerment and Demographic and Health Outcomes earnings. However, the county data vary greatly in the way decisions are made on how women’s earnings are used. The percentage of women who mainly decide for themselves how their earnings will be spent ranges from a low of 13 percent in Margibi to a high of 40 percent in Bomi. Twenty-eight percent of women with no education decide independently how to spend their earnings compared with 35 percent of women with secondary and higher education. Only 11 percent of women with secondary and higher education report that their husband mainly makes decisions about how their cash earnings will be spent; in contrast, 18 percent of women with no education report that their husband mainly decides how their earnings will be used. Only trifling differences are observed between the lowest, second, and middle wealth quintiles (20-21 percent); however, substantially lower proportions of married women in the fourth (6 percent) and fifth (11 percent) wealth quintiles reported that their husbands mainly control their earnings. Regarding the comparative magnitude of women’s earnings with those of their husbands, 14 percent report that they earn more than their husband, 62 percent earn less than their husband, and 18 percent earn about the same as their husband. Four percent of women report that their husband has no earnings. Older women, women with 3-4 children, women who live in Maryland, and women in the highest wealth quintile are more likely than other women to report that they earn more than their husbands. Table 15.2.2 shows who decides how a husband’s cash earnings are used, as reported independently by currently married men and women age 15-49. Among men, 10 percent report that their wife mainly decides how their earnings are used, 67 percent say that they and their wife jointly make the decision, and 24 percent report they mainly make the decision on their own. In comparison, 10 percent of women report that they mainly decide how their husband’s earnings are used, 65 percent say that they and their husband jointly make the decision, and 25 percent report that their husband mainly decides. Overall, there is remarkable agreement among men and women regarding who decides how a husband’s cash earnings are used. Cross-tabulations by the person in the household who decides how the wife’s cash earnings are used and how the husband’s cash earnings are used, by the woman’s earnings relative to her husband’s are presented in Table 15.3; they provide some insight into a woman’s empowerment in the family and the extent of her control over decision making in the household. Women’s Empowerment and Demographic and Health Outcomes • 261 Table 15.2.2 Control over men's cash earnings Percent distributions of currently married men age 15-49 who receive cash earnings and of currently married women age 15-49 whose husbands receive cash earnings, by person who decides how husband's cash earnings are used, according to background characteristics, Liberia 2013 Background characteristic Men Women Person who decides how husband’s cash earnings are used: Total Number of men Person who decides how husband’s cash earnings are used: Total Number of women Mainly wife Husband and wife jointly Mainly husband Other Missing Mainly wife Husband and wife jointly Mainly husband Other Missing Age 15-19 * * * * * 100.0 5 11.2 57.1 31.1 0.2 0.4 100.0 284 20-24 8.5 62.7 27.8 0.0 1.0 100.0 94 10.5 60.2 28.9 0.0 0.4 100.0 839 25-29 8.5 58.5 32.8 0.2 0.0 100.0 312 9.1 63.8 27.0 0.0 0.2 100.0 1,130 30-34 5.9 68.9 24.5 0.4 0.3 100.0 347 10.6 66.2 23.2 0.0 0.0 100.0 926 35-39 11.1 71.1 17.8 0.0 0.0 100.0 319 9.0 69.0 21.2 0.2 0.6 100.0 893 40-44 12.2 69.1 18.6 0.1 0.0 100.0 320 9.0 67.4 22.2 0.0 1.4 100.0 598 45-49 10.8 66.4 22.8 0.0 0.0 100.0 236 10.3 67.9 21.2 0.5 0.1 100.0 527 Number of living children 0 13.5 52.7 33.3 0.0 0.5 100.0 89 10.6 60.0 29.3 0.0 0.1 100.0 290 1-2 7.4 64.0 28.0 0.3 0.3 100.0 585 9.3 62.7 27.7 0.0 0.3 100.0 1,907 3-4 8.0 70.0 21.9 0.2 0.0 100.0 499 10.6 64.7 23.6 0.2 0.9 100.0 1,629 5+ 13.0 69.0 18.0 0.0 0.0 100.0 461 9.2 69.7 20.9 0.1 0.1 100.0 1,370 Residence Urban 7.7 70.0 22.1 0.1 0.0 100.0 953 9.0 65.0 25.4 0.1 0.4 100.0 2,794 Greater Monrovia 7.7 68.6 23.7 0.0 0.0 100.0 541 7.5 64.7 27.3 0.3 0.3 100.0 1,547 Other urban 7.7 72.0 19.9 0.3 0.1 100.0 411 11.0 65.4 23.1 0.0 0.5 100.0 1,246 Rural 12.1 61.9 25.7 0.1 0.2 100.0 680 10.7 65.0 23.9 0.0 0.4 100.0 2,403 Region North Western 15.4 61.9 22.3 0.1 0.3 100.0 184 7.4 67.1 25.5 0.1 0.0 100.0 551 South Central 6.8 71.4 21.5 0.1 0.1 100.0 853 7.8 67.5 24.3 0.2 0.3 100.0 2,397 South Eastern A 15.7 64.6 19.7 0.0 0.0 100.0 93 14.1 62.5 22.7 0.2 0.5 100.0 335 South Eastern B 11.6 54.2 34.2 0.0 0.0 100.0 91 12.3 52.7 33.7 0.0 1.2 100.0 348 North Central 10.6 62.0 26.9 0.3 0.1 100.0 412 12.2 63.8 23.5 0.0 0.5 100.0 1,565 County Bomi 8.4 75.0 16.6 0.0 0.0 100.0 39 5.2 74.9 20.0 0.0 0.0 100.0 140 Bong 13.8 37.0 49.2 0.0 0.0 100.0 126 13.9 66.0 19.8 0.0 0.3 100.0 613 Gbarpolu 37.5 53.4 8.0 0.3 0.8 100.0 56 17.1 44.5 38.1 0.3 0.0 100.0 120 Grand Bassa 4.6 77.1 16.2 0.8 1.2 100.0 91 10.0 65.6 24.5 0.0 0.0 100.0 285 Grand Cape Mount 4.5 61.7 33.8 0.0 0.0 100.0 89 4.5 72.6 22.9 0.0 0.0 100.0 291 Grand Gedeh 8.3 81.2 10.5 0.0 0.0 100.0 32 17.1 58.2 24.3 0.2 0.2 100.0 110 Grand Kru 18.9 45.4 35.6 0.0 0.0 100.0 44 17.0 33.9 46.4 0.0 2.8 100.0 133 Lofa 30.8 44.9 24.3 0.0 0.0 100.0 69 4.3 64.5 31.2 0.0 0.0 100.0 288 Margibi 5.3 77.8 16.9 0.0 0.0 100.0 156 5.6 77.0 16.8 0.0 0.6 100.0 400 Maryland 4.5 59.0 36.5 0.0 0.0 100.0 31 11.6 60.9 27.0 0.0 0.5 100.0 142 Montserrado 7.5 68.9 23.6 0.0 0.0 100.0 606 7.9 65.5 26.0 0.2 0.3 100.0 1,712 Nimba 2.3 81.9 14.9 0.7 0.2 100.0 217 14.1 61.3 23.6 0.0 0.9 100.0 664 River Cess 8.5 65.0 26.5 0.0 0.0 100.0 17 7.6 75.4 17.0 0.0 0.0 100.0 95 River Gee (5.4) (69.4) (25.2) (0.0) (0.0) 100.0 16 5.4 71.2 23.4 0.0 0.0 100.0 73 Sinoe 24.1 52.1 23.8 0.0 0.0 100.0 43 16.1 56.7 25.6 0.4 1.2 100.0 131 Education No education 14.6 54.4 30.7 0.1 0.2 100.0 261 10.4 64.9 24.1 0.1 0.5 100.0 2,337 Primary 9.7 66.0 23.6 0.2 0.4 100.0 354 9.6 63.4 26.6 0.1 0.3 100.0 1,394 Secondary and higher 8.1 70.0 21.8 0.1 0.0 100.0 1,018 8.9 66.7 23.8 0.2 0.5 100.0 1,466 Wealth quintile Lowest 13.5 60.1 25.8 0.1 0.6 100.0 279 12.6 60.9 25.8 0.1 0.6 100.0 1,079 Second 13.6 64.3 21.9 0.0 0.2 100.0 275 11.4 64.1 24.1 0.0 0.3 100.0 1,065 Middle 8.9 69.9 20.5 0.6 0.0 100.0 356 8.7 67.1 23.7 0.0 0.5 100.0 1,047 Fourth 5.0 67.9 27.0 0.0 0.0 100.0 371 8.3 66.4 24.6 0.1 0.5 100.0 1,063 Highest 8.4 69.0 22.6 0.0 0.0 100.0 352 7.6 66.7 25.4 0.3 0.0 100.0 942 Total 9.5 66.6 23.6 0.1 0.1 100.0 1,633 9.8 65.0 24.7 0.1 0.4 100.0 5,197 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 262 • Women’s Empowerment and Demographic and Health Outcomes Table 15.3 shows that currently married women who earn more than their husband are more likely to decide by themselves how their own earnings are used (38 percent) than those who earn less (31 percent) or the same as their husband (15 percent). Currently married women who earn more than their husbands are also more likely to decide for themselves how their husband’s cash earnings are used (19 percent) than those women who earn less than their husband (10 percent) or the same as their husband (5 percent). Women who earn the same as their husband are most likely to make joint decisions on how their earnings (72 percent) and their husband’s earnings (82 percent) are used. Table 15.3 Women's control over their own earnings and over those of their husbands Percent distribution of currently married women age 15-49 with cash earnings in the last 12 months by person who decides how the wife's cash earnings are used and percent distribution of currently married women age 15-49 whose husbands have cash earnings by person who decides how the husband's cash earnings are used, according to the relation between wife's and husband's cash earnings, Liberia 2013 Women's earnings relative to husband's earnings Person who decides how the wife's cash earnings are used: Total Number Person who decides how husband's cash earnings are used: Total Number of women Mainly wife Wife and husband jointly Mainly husband Other Missing Mainly wife Wife and husband jointly Mainly husband Other Missing More than husband 37.7 49.4 12.9 0.0 0.0 100.0 327 19.0 58.3 21.4 1.3 0.0 100.0 327 Less than husband 31.1 51.8 16.7 0.4 0.0 100.0 1,494 9.9 62.4 27.7 0.0 0.0 100.0 1,494 Same as husband 14.9 72.2 12.9 0.0 0.0 100.0 437 4.5 81.5 13.9 0.0 0.0 100.0 437 Husband has no cash earnings or did not work 38.8 51.4 8.7 0.7 0.3 100.0 96 na na na na na na 0 Woman worked but has no cash earnings na na na na na na 0 12.1 67.1 20.4 0.0 0.3 100.0 1,085 Woman did not work na na na na na na 0 7.8 63.9 27.6 0.0 0.7 100.0 1,785 Total 29.8 54.0 14.8 0.3 1.2 100.0 2,423 9.8 65.0 24.7 0.1 0.4 100.0 5,197 Note: Total includes 30 cases where information on whether a woman earned more or less than her husband is missing, and 39 cases where a woman does not know whether she earned more or less than her husband. na = Not applicable 15.3 WOMEN’S OWNERSHIP OF ASSETS The 2013 LDHS asked respondents questions regarding the ownership of houses. Ownership of a house is considered a measure of women’s empowerment, and to this effect, the government of Liberia gives equal opportunity of owning property to everyone regardless of sex. Table 15.4.1 shows the percentages of women age 15-49 who reported owning a house alone, jointly, both alone and jointly, and the percentage who do not own a house, according to background characteristics. Overall, 8 percent of women own a house alone. Nineteen percent of women report that they own a house jointly with someone. Three percent of women own a house both alone and jointly. Seventy percent of women report that they do not own a house. Ownership of a home alone or jointly increases with age, with younger women much less likely to own a house, either alone or jointly, compared with older women. Rural women in Liberia are twice as likely as urban women to own a house alone (12 percent and 6 percent, respectively) or jointly (28 percent and 14 percent, respectively). By county, the percentage of women who do not own a house is highest in Montserrado (81 percent) and lowest in Grand Gedeh (48 percent). Interestingly, home ownership among women is inversely correlated with education level and wealth quintile. Whereas 80 percent of women with at least some secondary education do not own a house, only 53 percent of women with no education do not own a house. Women’s Empowerment and Demographic and Health Outcomes • 263 And while 80-83 percent of women in the highest two wealth quintiles do not own a house, only 49 percent of women in the lowest wealth quintile do not own a house. Table 15.4.1 Ownership of assets: Women Percent distribution of women age 15-49 by ownership of housing, according to background characteristics, Liberia 2013 Background characteristic Percentage who own a house: Total Number Alone Jointly Alone and jointly Percentage who do not own a house Age 15-19 1.2 2.3 1.0 95.5 100.0 2,080 20-24 3.7 10.2 2.1 84.0 100.0 1,642 25-29 6.9 17.7 3.1 72.2 100.0 1,611 30-34 9.7 26.1 3.3 60.9 100.0 1,199 35-39 14.6 29.9 4.6 50.9 100.0 1,179 40-44 15.2 38.8 4.3 41.7 100.0 812 45-49 24.0 38.7 3.5 33.8 100.0 716 Residence Urban 6.0 13.5 2.4 78.1 100.0 5,633 Greater Monrovia 5.4 10.2 2.2 82.2 100.0 3,361 Other urban 7.0 18.4 2.6 71.9 100.0 2,272 Rural 12.2 27.7 3.4 56.6 100.0 3,606 Region North Western 15.3 22.7 1.7 60.2 100.0 837 South Central 6.1 12.5 2.5 78.9 100.0 4,854 South Eastern A 15.7 29.7 1.8 52.6 100.0 483 South Eastern B 10.7 24.8 3.5 61.0 100.0 577 North Central 8.7 27.2 3.7 60.4 100.0 2,488 County Bomi 4.3 20.1 4.3 71.3 100.0 244 Bong 5.1 27.8 3.3 63.8 100.0 894 Gbarpolu 6.1 29.4 0.9 63.6 100.0 182 Grand Bassa 9.9 27.0 2.6 60.4 100.0 434 Grand Cape Mount 25.8 21.4 0.6 52.2 100.0 412 Grand Gedeh 16.0 32.9 2.9 48.2 100.0 167 Grand Kru 13.4 34.3 3.3 49.1 100.0 217 Lofa 10.3 30.2 10.4 49.0 100.0 447 Margibi 6.2 10.3 3.8 79.6 100.0 744 Maryland 5.4 20.1 3.3 71.2 100.0 257 Montserrado 5.6 11.2 2.2 80.9 100.0 3,675 Nimba 10.9 25.5 1.4 62.2 100.0 1,147 River Cess 22.3 23.3 0.4 53.4 100.0 135 River Gee 18.5 16.4 4.3 60.7 100.0 103 Sinoe 10.5 31.6 1.9 55.9 100.0 182 Education No education 12.8 30.5 4.1 52.6 100.0 3,066 Primary 6.0 15.3 2.3 76.4 100.0 2,875 Secondary and higher 6.6 11.7 2.0 79.7 100.0 3,298 Wealth quintile Lowest 14.6 32.8 4.0 48.6 100.0 1,581 Second 11.0 27.0 3.2 58.8 100.0 1,624 Middle 7.7 19.0 2.8 70.4 100.0 1,779 Fourth 5.1 10.2 1.8 82.8 100.0 2,047 Highest 5.9 11.5 2.5 80.1 100.0 2,207 Total 8.4 19.0 2.8 69.7 100.0 9,239 Note: Total includes 1 case for which information on housing ownership is missing. Table 15.4.2 shows ownership of housing by men age 15-49, according to background characteristics. Seventy-four percent of men do not own a house, which is comparable to the proportion of women who do not own a house (70 percent). Seventeen percent own a house alone, 8 percent jointly own a house, and 1 percent own a house alone and jointly. Ownership of a home alone or jointly increases with age, with younger men 264 • Women’s Empowerment and Demographic and Health Outcomes much less likely to own a house, either alone or jointly, compared with older men. Rural men in Liberia are more than twice as likely as urban men to own a house on their own (26 percent and 11 percent, respectively) or jointly with someone else (12 percent and 5 percent, respectively). By county, the percentage of men who do not own a house is highest in Montserrado (89 percent) and lowest in Grand Kru (47 percent). Like women, home ownership among men is inversely correlated with education level and wealth quintile. Whereas 78 percent of men with at least some secondary education do not own a house, only 60 percent of men with no education do not own a house. And while 90 percent of men in the highest wealth quintile do not own a house, only 49 percent of men in the lowest wealth quintile do not own a house. Table 15.4.2 Ownership of assets: Men Percent distribution of men age 15-49 by ownership of housing, according to background characteristics, Liberia 2013 Background characteristic Percentage who own a house: Alone Jointly Alone and jointly Percentage who do not own a house Total Number Age 15-19 0.4 0.1 0.0 99.4 100.0 890 20-24 5.6 2.1 0.4 91.8 100.0 696 25-29 15.2 6.4 0.2 78.2 100.0 673 30-34 20.3 10.7 1.0 67.8 100.0 575 35-39 27.2 17.0 1.1 54.7 100.0 469 40-44 36.9 14.6 1.6 47.0 100.0 482 45-49 40.8 17.5 0.8 40.9 100.0 332 Residence Urban 10.9 5.0 0.3 83.9 100.0 2,413 Greater Monrovia 6.6 3.5 0.0 89.9 100.0 1,433 Other urban 17.2 7.1 0.6 75.1 100.0 980 Rural 25.8 12.2 1.1 60.8 100.0 1,705 Region North Western 22.7 10.5 2.3 64.3 100.0 367 South Central 10.6 5.0 0.1 84.2 100.0 2,149 South Eastern A 26.6 12.3 0.8 60.3 100.0 254 South Eastern B 26.2 12.6 0.7 60.5 100.0 288 North Central 23.5 10.8 1.0 64.8 100.0 1,060 County Bomi 18.2 3.7 2.4 75.1 100.0 97 Bong 20.6 11.8 0.7 66.9 100.0 389 Gbarpolu 16.5 18.8 0.4 64.3 100.0 94 Grand Bassa 16.5 18.9 0.4 64.1 100.0 204 Grand Cape Mount 28.4 9.8 3.3 58.5 100.0 176 Grand Gedeh 30.0 13.2 0.3 56.5 100.0 82 Grand Kru 32.0 19.4 1.2 47.4 100.0 110 Lofa 39.6 3.7 0.0 56.7 100.0 219 Margibi 20.0 2.6 0.4 76.6 100.0 364 Maryland 22.0 2.3 0.2 75.5 100.0 123 Montserrado 7.6 3.8 0.0 88.6 100.0 1,582 Nimba 18.2 13.3 1.7 66.8 100.0 451 River Cess 33.3 3.4 0.8 62.5 100.0 64 River Gee 24.1 22.1 0.9 52.9 100.0 55 Sinoe 20.1 16.9 1.2 61.8 100.0 108 Education No education 26.5 12.9 0.7 59.6 100.0 533 Primary 17.5 7.0 1.0 74.5 100.0 1,202 Secondary and higher 14.7 7.3 0.4 77.5 100.0 2,383 Wealth quintile Lowest 32.4 17.2 0.9 49.3 100.0 749 Second 24.4 10.0 1.2 64.2 100.0 753 Middle 17.3 6.6 0.7 75.3 100.0 728 Fourth 9.8 4.7 0.4 85.1 100.0 864 Highest 6.3 3.4 0.0 90.2 100.0 1,024 Total 17.1 8.0 0.6 74.3 100.0 4,118 Note: Total includes 2 cases for which information on housing ownership is missing. Women’s Empowerment and Demographic and Health Outcomes • 265 15.4 WOMEN’S AND MEN’S PARTICIPATION IN DECISION MAKING Decision making can be a complex process, and the ability of women and men to make decisions that affect the circumstances of their own lives is essential to their status in the household and in society. The number of decisions in which a woman either alone or jointly with her husband has the final say is assumed to be directly related to the woman’s empowerment and reflects the degree of decision making control the woman is able to exercise in areas that affect her life and environment. To assess women’s decision making autonomy, the 2013 LDHS sought information on women’s participation in three types of household decisions: the respondent’s own health care; making major household purchases; and visits to family or relatives. Similarly, men were asked about their participation in two types of household decisions: the respondent’s health care and making major household purchases. Table 15.5 shows the percent distribution of currently married women and men according to the person in the household who usually makes decisions concerning these matters. Women and men are considered to participate in decision making if they make decisions alone or jointly with their spouse. Table 15.5 Participation in decision making Percent distribution of currently married women and currently married men age 15-49 by person who usually makes decisions about various issues, Liberia 2013 Decision Mainly wife Wife and husband jointly Mainly husband Someone else Other Missing Total Number of women WOMEN Own health care 16.2 61.0 22.1 0.3 0.0 0.3 100.0 5,386 Major household purchases 24.3 57.9 17.1 0.2 0.0 0.4 100.0 5,386 Visits to her family or relatives 18.6 60.3 20.6 0.0 0.1 0.3 100.0 5,386 MEN Man’s own health care 12.7 57.2 29.3 0.5 0.2 0.0 100.0 2,218 Major household purchases 16.8 58.2 24.6 0.3 0.0 0.0 100.0 2,218 The strength of the role of women in decision making varies with the type of decision. In Liberia, the majority of currently married women (58-61 percent) report that each of three household decisions is made jointly by husband and wife. Sixteen percent of currently married women report that they alone make the decisions about their own health care, 24 percent say that they mainly make decisions about major household purchases, and 19 percent say that they mainly decide on visiting their families and relatives. Nearly six in 10 men report that they make decisions jointly with their wives with regard to their own health care (57 percent) and on major household purchases (58 percent). Approximately 13 percent of men stated that decisions about their own health care are made mainly by their wife. Seventeen percent of men indicated that it is mainly the responsibility of their wife to make decisions on major household purchases. Table 15.6.1 shows the percentage of currently married women who report that they usually make specific household decisions either by themselves or jointly with their husbands, according to background characteristics. The majority of Liberian women make decisions either by themselves or jointly with their husbands for matters pertaining to their own health care (77 percent), making major household purchases (82 percent), and visiting their family or relatives (79 percent). Variations by background characteristics are generally relatively minor. 266 • Women’s Empowerment and Demographic and Health Outcomes Table 15.6.1 Women's participation in decision making by background characteristics Percentage of currently married women age 15-49 who usually make specific decisions either by themselves or jointly with their husband, by background characteristics, Liberia 2013 Background characteristic Specific decisions All three decisions None of the three decisions Number of women Woman's own health care Making major household purchases Visits to her family or relatives Age 15-19 67.3 74.6 73.5 53.4 11.4 299 20-24 72.1 79.3 80.6 63.3 11.1 862 25-29 77.3 81.9 77.0 64.1 8.6 1,168 30-34 80.3 82.4 79.5 66.8 8.0 957 35-39 79.3 85.4 80.9 71.1 8.9 924 40-44 75.6 83.9 78.0 66.4 8.7 619 45-49 83.3 84.6 80.1 70.0 7.5 557 Employment (past 12 months) Not employed 72.9 78.3 76.5 62.5 11.9 1,825 Employed for cash 79.9 85.2 80.9 69.3 7.3 2,423 Employed not for cash 78.3 82.5 78.5 64.1 7.9 1,134 Number of living children 0 69.3 78.4 76.3 56.2 10.9 300 1-2 76.7 81.1 79.5 65.4 9.0 1,973 3-4 75.6 81.0 77.6 64.4 9.7 1,688 5+ 81.5 86.1 80.3 70.6 7.9 1,424 Residence Urban 77.3 83.3 79.1 65.8 8.1 2,898 Greater Monrovia 78.9 84.7 80.9 67.4 7.0 1,614 Other urban 75.4 81.4 76.7 63.7 9.6 1,283 Rural 77.0 81.1 78.8 66.1 10.0 2,488 Region North Western 77.8 80.7 76.3 65.0 10.6 580 South Central 80.7 86.0 82.9 70.4 6.1 2,481 South Eastern A 78.6 83.2 78.3 64.7 6.8 348 South Eastern B 69.1 72.7 73.0 57.2 16.1 358 North Central 73.1 79.0 75.3 61.6 11.8 1,619 County Bomi 80.7 83.1 75.3 70.2 13.0 145 Bong 76.4 83.7 84.1 69.3 7.6 635 Gbarpolu 67.7 74.7 70.9 52.8 11.9 123 Grand Bassa 83.5 88.3 85.4 74.4 3.5 294 Grand Cape Mount 80.4 82.0 79.0 67.4 8.9 312 Grand Gedeh 78.9 87.3 76.4 65.5 5.3 113 Grand Kru 55.1 59.8 62.9 41.9 25.5 135 Lofa 71.3 69.5 71.0 62.8 22.3 291 Margibi 84.8 87.7 86.0 77.8 6.5 407 Maryland 74.6 77.2 75.9 63.4 13.1 148 Montserrado 79.3 85.2 81.7 68.1 6.5 1,780 Nimba 70.9 78.8 69.1 53.9 11.2 694 River Cess 87.8 86.7 89.7 78.4 4.4 100 River Gee 83.3 87.0 85.8 72.8 5.1 74 Sinoe 71.4 77.1 71.3 53.8 9.9 135 Education No education 77.3 81.0 78.6 67.3 10.5 2,417 Primary 74.0 81.4 76.3 60.8 9.3 1,446 Secondary and higher 80.0 85.1 81.9 68.7 6.4 1,523 Wealth quintile Lowest 77.5 81.9 78.5 65.8 9.2 1,133 Second 75.4 80.1 77.6 64.4 10.6 1,094 Middle 75.4 81.2 77.4 64.8 11.1 1,082 Fourth 79.1 82.9 79.9 68.7 8.2 1,108 Highest 78.7 85.5 81.5 66.0 5.6 968 Total 77.2 82.3 78.9 65.9 9.0 5,386 Note: Total includes 3 cases for which information on employment for cash or not for cash is missing. Women’s Empowerment and Demographic and Health Outcomes • 267 The total number of decisions in which a woman participates is one simple measure of her empowerment. Figure 15.1 shows the distribution of currently married women according to the number of decisions in which they participate either alone or jointly with their husband. Sixty-six percent of currently married women participate in all three household decisions, and 16 percent participate in two decisions. Ten percent of women participate in one decision, and 9 percent do not participate in any decisions. Figure 15.1 Number of decisions in which currently married women participate 9 10 16 66 0 1 2 3 Number of decisions Percent of women LDHS 2013 Table 15.6.2 shows the percentage of currently married men who report that they alone or jointly with their wives participate in specific household decisions, according to background characteristics. The majority of Liberian men make decisions either by themselves or jointly with their wives for matters pertaining to their own health care (87 percent) and making major household purchases (83 percent). Eighty percent of men make both types of decisions either by themselves or jointly with their wives, while 10 percent do not participate in either type of decision. 268 • Women’s Empowerment and Demographic and Health Outcomes Table 15.6.2 Men's participation in decision making by background characteristics Percentage of currently married men age 15-49 who usually make specific decisions either alone or jointly with their wife, by background characteristics, Liberia 2013 Background characteristic Specific decisions Both decisions Neither of the two decisions Number of men Man's own health Making major household purchases Age 15-19 * * * * 13 20-24 92.1 89.5 89.2 7.6 152 25-29 85.3 86.7 82.1 10.1 434 30-34 87.8 84.8 81.1 8.5 475 35-39 86.5 78.5 75.1 10.1 421 40-44 84.3 79.2 76.4 12.8 422 45-49 88.1 83.1 81.0 9.8 302 Employment (past 12 months) Not employed 74.1 72.8 72.8 25.9 139 Employed for cash 88.9 84.0 81.0 8.1 1,633 Employed not for cash 81.8 81.8 76.8 13.2 445 Number of living children 0 82.0 75.5 72.8 15.4 129 1-2 86.7 85.1 82.0 10.3 774 3-4 88.7 83.0 80.0 8.2 670 5+ 84.9 81.5 77.7 11.3 644 Residence Urban 86.3 82.3 78.8 10.2 1,150 Greater Monrovia 88.2 82.3 80.9 10.4 623 Other urban 84.0 82.3 76.3 9.9 526 Rural 86.7 83.4 80.5 10.3 1,068 Region North Western 82.5 83.5 80.8 14.9 236 South Central 90.5 85.0 82.8 7.3 1,033 South Eastern A 86.1 78.5 75.2 10.6 147 South Eastern B 88.7 82.0 78.9 8.3 158 North Central 81.1 80.4 75.2 13.7 644 County Bomi 86.5 89.1 85.4 9.9 55 Bong 67.0 67.8 58.1 23.3 247 Gbarpolu 60.7 58.2 56.7 37.8 63 Grand Bassa 94.0 82.5 80.1 3.6 140 Grand Cape Mount 92.2 94.3 91.5 5.0 118 Grand Gedeh 95.0 78.1 76.6 3.6 44 Grand Kru 81.8 70.6 69.7 17.2 65 Lofa 78.9 78.6 77.8 20.2 124 Margibi 94.5 94.1 90.2 1.5 194 Maryland 91.4 86.3 79.8 2.1 58 Montserrado 88.7 82.9 81.3 9.7 699 Nimba 94.8 92.6 89.4 2.0 273 River Cess 93.6 87.4 85.9 4.9 41 River Gee 97.0 95.8 94.6 1.8 35 Sinoe 75.0 72.9 67.1 19.2 62 Education No education 85.2 81.9 78.1 11.1 375 Primary 84.0 84.0 79.3 11.2 569 Secondary and higher 88.0 82.6 80.2 9.6 1,274 Wealth quintile Lowest 86.6 81.8 80.0 11.5 489 Second 82.1 81.6 76.2 12.5 463 Middle 84.9 82.7 78.3 10.8 433 Fourth 89.2 82.7 80.1 8.3 447 Highest 90.4 86.0 84.2 7.8 387 Total 86.5 82.8 79.6 10.3 2,218 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Women’s Empowerment and Demographic and Health Outcomes • 269 15.5 ATTITUDES TOWARD WIFE BEATING The critical problems that women face are many and diverse. One of these, and among the most serious, is the issue of violence against women. It is described as the most serious because it concerns the personal security of women, and the right of personal security is fundamental to all other rights. If violence against women is tolerated and accepted in a society, its eradication is made more difficult. To assess women’s and men’s attitudes towards wife beating, respondents were asked whether a husband is justified in hitting or beating his wife in each of the following five situations: if she burns the food; if she argues with him; if she goes out without telling him; if she neglects the children; and if she refuses to have sexual intercourse with him. A woman’s responses to these five situations are used to generate the women’s empowerment indicator; “Number of reasons wife beating is justified,” described below (see section 15.6). The results of this series of questions for women and men are summarized in Tables 15.7.1 and 15.7.2, respectively. Table 15.7.1 shows attitudes toward wife beating by the percentage of all women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, according to background characteristics. Seven percent of women report that a husband is justified in hitting or beating his wife if she burns the food, 33 percent if she argues with him, 29 percent if she goes out without telling him, 32 percent if she neglects the children, and 11 percent if she refuses to have sexual intercourse with him. Forty-three percent of women believe that a husband is justified in hitting or beating his wife for at least one of the five specified reasons. Rural women were more likely than urban women (49 percent and 39 percent, respectively), women with no education were more likely than women with at least some secondary education, (46 percent and 35 percent, respectively), and women in the lowest three wealth quintiles were more likely than women in the highest wealth quintile (48-49 percent and 29 percent, respectively) to agree with at least one specified reason that a husband is justified in hitting or beating his wife. Table 15.7.2 shows attitudes toward wife beating by the percentage of all men age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, according to background characteristics. Three percent of men report that a husband is justified in hitting or beating his wife if she burns the food, 18 percent if she argues with him, 14 percent if she goes out without telling him, 15 percent if she neglects the children, and 4 percent if she refuses to have sexual intercourse with him. Twenty-four percent of men believe that a husband is justified in hitting or beating his wife for at least one of the five specified reasons. Younger men were more likely than older men to agree with at least one specified reason that a husband is justified in hitting or beating his wife, decreasing from 29 percent among men age 15-19 to 17 percent among men age 45-49. Rural men were more likely than urban men (30 percent and 21 percent, respectively), men with no education were more likely than men with at least some secondary education, (28 percent and 21 percent, respectively), and men in the lowest wealth quintile were more likely than men in the highest wealth quintile (33 percent and 17 percent, respectively) to agree with at least one specified reason that a husband is justified in hitting or beating his wife. 270 • Women’s Empowerment and Demographic and Health Outcomes Table 15.7.1 Attitude toward wife beating: Women Percentage of all women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Liberia 2013 Background characteristic Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Number of women Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Age 15-19 9.2 35.2 28.8 35.2 8.8 45.1 2,080 20-24 6.1 32.9 29.8 33.7 12.1 43.2 1,642 25-29 6.5 31.8 27.9 30.5 10.4 41.4 1,611 30-34 8.6 33.9 28.7 31.9 11.8 42.2 1,199 35-39 6.6 31.4 26.5 28.1 10.1 38.8 1,179 40-44 6.7 32.7 28.5 33.2 11.0 41.8 812 45-49 7.4 32.7 28.7 30.5 12.7 42.9 716 Employment (past 12 months) Not employed 8.0 34.3 29.6 33.3 12.3 43.4 3,944 Employed for cash 6.8 31.1 28.2 31.3 9.9 39.7 3,564 Employed not for cash 7.4 34.6 26.4 31.9 8.8 46.4 1,721 Number of living children 0 7.4 32.2 27.0 32.3 8.1 41.9 2,185 1-2 7.0 32.8 29.1 32.0 11.3 42.2 3,294 3-4 7.3 33.7 28.2 32.0 12.5 42.2 2,084 5+ 8.3 34.3 29.6 32.9 10.9 44.2 1,676 Marital status Never married 7.6 32.4 26.5 31.3 8.7 41.6 2,867 Married or living together 7.6 34.0 30.0 33.5 11.8 43.5 5,386 Divorced/separated/widowed 5.8 30.6 25.7 27.9 10.9 39.5 987 Residence Urban 6.1 30.4 26.8 29.9 9.4 38.6 5,633 Greater Monrovia 4.1 23.1 21.8 23.6 8.0 30.1 3,361 Other urban 9.0 41.2 34.1 39.3 11.4 51.2 2,272 Rural 9.5 37.3 31.1 35.8 12.8 48.5 3,606 Region North Western 5.5 25.3 21.3 24.7 9.5 32.8 837 South Central 4.8 27.3 24.9 27.2 8.0 35.6 4,854 South Eastern A 11.2 40.3 32.8 36.1 10.6 53.2 483 South Eastern B 12.9 38.9 28.3 35.6 16.2 53.5 577 North Central 11.2 44.4 37.0 43.1 15.1 54.6 2,488 County Bomi 9.2 29.5 22.3 24.8 16.5 35.6 244 Bong 7.7 27.5 17.7 26.2 5.0 37.4 894 Gbarpolu 6.1 33.3 26.8 32.5 11.9 43.7 182 Grand Bassa 7.6 38.0 32.8 33.5 15.0 47.3 434 Grand Cape Mount 3.1 19.3 18.4 21.2 4.2 26.2 412 Grand Gedeh 10.4 46.2 34.0 35.5 10.3 60.0 167 Grand Kru 13.0 40.2 29.3 31.6 25.5 53.6 217 Lofa 12.0 38.9 33.8 35.2 25.3 45.9 447 Margibi 5.7 44.3 37.2 41.6 5.9 55.4 744 Maryland 12.1 34.0 23.8 35.4 10.6 49.1 257 Montserrado 4.2 22.6 21.5 23.5 7.6 30.2 3,675 Nimba 13.6 59.8 53.4 59.4 19.0 71.3 1,147 River Cess 4.8 37.1 39.7 41.4 5.1 51.2 135 River Gee 14.7 48.6 37.7 44.2 10.9 64.0 103 Sinoe 16.5 37.1 26.8 32.7 15.0 48.3 182 Education No education 8.6 35.0 30.7 34.5 13.4 45.8 3,066 Primary 8.4 38.8 31.5 37.1 11.6 47.8 2,875 Secondary and higher 5.4 26.4 23.7 25.9 7.4 34.8 3,298 Wealth quintile Lowest 10.4 37.2 29.9 35.5 12.7 48.3 1,581 Second 8.7 38.3 30.6 35.8 12.8 48.9 1,624 Middle 10.2 39.6 34.8 38.9 12.8 49.0 1,779 Fourth 5.4 32.0 28.6 31.9 8.7 41.3 2,047 Highest 4.0 22.3 20.7 22.2 7.9 29.4 2,207 Total 7.4 33.1 28.5 32.2 10.7 42.5 9,239 Note: Total includes 9 cases for which information on employment for cash or not for cash is missing. Women’s Empowerment and Demographic and Health Outcomes • 271 Table 15.7.2 Attitude toward wife beating: Men Percentage of all men age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Liberia 2013 Background characteristic Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Number of men Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Age 15-19 5.7 22.2 16.7 19.4 6.0 29.2 890 20-24 2.0 19.8 15.9 16.3 4.4 26.8 696 25-29 2.5 22.3 16.6 14.9 3.8 28.7 673 30-34 2.4 15.7 11.6 11.1 3.2 22.6 575 35-39 0.7 13.4 9.8 11.9 3.0 18.3 469 40-44 1.1 12.8 10.5 12.2 3.3 18.1 482 45-49 1.3 13.3 12.9 10.9 3.1 16.7 332 Employment (past 12 months) Not employed 3.7 15.4 11.4 11.0 4.1 19.3 958 Employed for cash 1.4 16.9 14.5 14.8 4.2 23.2 2,396 Employed not for cash 5.2 25.2 15.9 18.5 3.8 33.8 761 Number of living children 0 4.1 21.0 15.8 17.2 5.4 27.5 1,634 1-2 1.8 17.7 13.3 13.7 3.2 23.4 1,083 3-4 1.0 14.4 12.2 12.4 3.0 21.1 728 5+ 2.2 15.7 12.8 12.2 3.3 21.1 673 Marital status Never married 4.0 21.5 16.6 17.5 5.5 28.0 1,749 Married or living together 1.5 15.3 11.9 12.1 3.2 21.1 2,218 Divorced/separated/widowed 3.2 19.5 14.7 17.3 0.9 26.5 151 Residence Urban 2.0 16.3 12.3 12.4 3.0 20.5 2,413 Greater Monrovia 1.5 13.7 11.8 12.1 1.9 17.2 1,433 Other urban 2.7 20.1 13.1 13.0 4.5 25.3 980 Rural 3.5 20.7 16.4 17.6 5.6 29.5 1,705 Region North Western 0.6 13.2 11.4 12.0 2.1 19.2 367 South Central 2.4 17.2 13.3 13.9 2.4 22.1 2,149 South Eastern A 1.9 17.2 12.3 14.2 2.9 27.2 254 South Eastern B 11.7 26.2 20.4 23.4 13.7 42.5 288 North Central 1.5 19.6 15.2 14.6 5.7 24.6 1,060 County Bomi 0.0 9.2 4.4 7.0 1.1 9.6 97 Bong 2.4 31.3 27.4 28.1 11.5 37.3 389 Gbarpolu 2.5 21.0 17.8 19.9 2.8 27.7 94 Grand Bassa 5.6 27.9 22.0 28.5 5.3 40.1 204 Grand Cape Mount 0.0 11.2 11.7 10.6 2.4 20.0 176 Grand Gedeh 1.0 12.6 9.0 12.4 4.3 24.1 82 Grand Kru 13.9 20.6 22.5 25.1 8.2 37.1 110 Lofa 2.2 9.2 6.2 6.2 1.9 13.2 219 Margibi 2.9 22.7 11.2 10.1 1.7 25.9 364 Maryland 14.4 36.5 22.5 26.0 22.0 54.8 123 Montserrado 1.9 14.6 12.6 12.9 2.2 19.0 1,582 Nimba 0.4 14.6 9.0 7.2 2.6 19.0 451 River Cess 2.3 26.1 21.9 22.4 4.3 39.1 64 River Gee 1.2 14.3 11.6 14.1 5.8 25.5 55 Sinoe 2.4 15.4 9.2 10.7 1.0 22.4 108 Education No education 1.9 21.2 17.8 18.7 8.7 28.0 533 Primary 3.9 23.4 16.2 18.1 5.3 30.0 1,202 Secondary and higher 2.1 14.7 12.1 11.9 2.4 20.5 2,383 Wealth quintile Lowest 3.8 23.2 18.9 20.4 7.7 32.7 749 Second 3.2 21.1 15.6 16.0 5.9 29.1 753 Middle 2.3 17.4 13.5 13.6 4.9 24.0 728 Fourth 1.4 17.4 14.1 14.2 1.3 21.2 864 Highest 2.6 13.2 9.7 10.3 1.7 17.2 1,024 Total 2.6 18.1 14.0 14.6 4.1 24.2 4,118 Note: Total includes 2 cases for which information on employment for cash or not for cash is missing. 272 • Women’s Empowerment and Demographic and Health Outcomes 15.6 WOMEN’S EMPOWERMENT INDICATORS Two sets of empowerment indicators, namely, women’s participation in making household decisions and women’s attitudes towards wife beating can be summarized in two indices. The first index shows the number of decisions (see Table 15.6.1 for the list of decisions) in which women participate either alone or jointly with their husbands. This index ranges from 0 to 3 and reflects the degree of decision-making control that women are able to exercise in areas that affect their own lives and the level of women’s empowerment in a society. The second index, which ranges from 0 to 5, is the number of reasons (see Table 15.7.1 for a list of reasons) for which a woman thinks that a husband is justified in beating his wife. A low score on this indicator is interpreted as reflecting a higher status of women in the household and society. Table 15.8 shows how the two indices relate to each other. The findings indicate that women who participate in all three household decisions asked about are slightly more likely to disagree with all five reasons justifying wife beating than women who participate in fewer or no household decisions. Similarly, women who do not believe that wife beating is justified for any reason are somewhat more likely to participate in all household decision making than women who believe there are reasons for which wife beating is justified. Table 15.8 Indicators of women's empowerment Percentage of currently married women age 15-49 who participate in all decision making and the percentage who disagree with all of the reasons justifying wife beating, by value on each of the indicators of women's empowerment, Liberia 2013 Empowerment indicator Percentage who participate in all decision making Percentage who disagree with all the reasons justifying wife-beating Number of women Number of decisions in which women participate1 0 na 54.2 485 1-2 na 50.9 1,350 3 na 59.0 3,551 Number of reasons for which wife- beating is justified2 0 68.8 na 3,043 1-2 62.3 na 982 3-4 62.1 na 1,192 5 62.6 na 168 na = Not applicable 1 See Table 15.6.1 for the list of decisions. 2 See Table 15.7.1 for the list of reasons. 15.7 CURRENT USE OF CONTRACEPTION BY WOMEN’S EMPOWERMENT A woman’s desire and ability to control her fertility and her choice of contraceptive method are in part affected by her status in the household and her own sense of empowerment. A woman who feels that she is unable to control her life may be less likely to feel she can make and carry out decisions about her fertility. Table 15.9 presents the distribution of currently married women by contraceptive method use, according to the two empowerment indicators. There is generally a positive relationship between women’s empowerment and use of contraception, although differences are not great. Women who participate in one or more household decisions are more likely Women’s Empowerment and Demographic and Health Outcomes • 273 to use any method of contraception than women who do not participate in any household decisions (19-22 percent and 11 percent, respectively). Likewise, women who believe that wife beating is not justified for any reason are more likely than other women to use any method of contraception (23 percent and 9-17 percent, respectively). Conversely, the percentage of women not currently using any method is highest among those women who justified all five reasons for wife beating (92 percent) and those women who do not take part in any decision making (89 percent). Table 15.9 Current use of contraception by women's empowerment Percent distribution of currently married women age 15-49 by current contraceptive method, according to selected indicators of women's status, Liberia 2013 Empowerment indicator Any method Modern methods Any traditional method Not currently using Total Number of women Any modern method Female sterilization Temporary modern female methods1 Male condom Number of decisions in which women participate2 0 11.3 11.2 0.4 10.4 0.4 0.1 88.7 100.0 485 1-2 19.2 18.7 0.4 17.7 0.6 0.5 80.8 100.0 1,350 3 21.9 20.4 0.2 19.8 0.4 1.5 78.1 100.0 3,551 Number of reasons for which wife- beating is justified3 0 23.2 21.5 0.4 20.5 0.6 1.7 76.8 100.0 3,043 1-2 17.0 16.4 0.1 16.0 0.3 0.7 83.0 100.0 982 3-4 17.0 16.8 0.3 16.5 0.0 0.2 83.0 100.0 1,192 5 8.5 8.5 0.0 8.5 0.0 0.0 91.5 100.0 168 Total 20.2 19.1 0.3 18.4 0.4 1.1 79.8 100.0 5,386 Note: If more than one method is used, only the most effective method is considered in this tabulation. 1 Pill, IUD, injectables, implants, female condom, diaphragm, foam/jelly, and lactational amenorrhea method 2 See Table 15.6.1 for the list of decisions. 3 See Table 15.7.1 for the list of reasons. 15.8 IDEAL FAMILY SIZE AND UNMET NEED BY WOMEN’S EMPOWERMENT A woman’s fertility preference—for example, her preference for an ideal number of children—is typically lower than that of her husband (see Chapter 6, Table 6.3). As a woman becomes more empowered to negotiate fertility decision making, she has more control over her ability to access and use contraceptives to space and limit her family size. Women who have a desire to space or limit their births but who are not using family planning are defined as having an unmet need for family planning. Table 15.10 shows how women’s ideal family size and their unmet need for family planning vary by the two empowerment indicators. Currently married women who participate in none of the empowerment indicator-specified household decisions have a higher ideal number of children than women who participate in one to three decisions (5.6 children versus 5.3 children). The unmet need for family planning is only slightly lower among women who participate in all three decisions (30 percent) compared to women who participate in zero to two decisions (31- 35 percent). Desired family size increases with the number of reasons a woman thinks that wife beating is justified, increasing from 4.7 children among women who do not agree with any of the reasons justifying wife beating to 5.3 children among women who agree with all five reasons justifying wife beating. The unmet need for family planning is lower among women who do not agree with any of the reasons justifying wife beating (30 percent) compared to women who agree with all five reasons justifying wife beating (38 percent). 274 • Women’s Empowerment and Demographic and Health Outcomes Table 15.10 Ideal number of children and unmet need for family planning by women's empowerment Mean ideal number of children for women 15-49 and the percentage of currently married women age 15-49 with an unmet need for family planning, by indicators of women's empowerment, Liberia 2013 Empowerment indicator Mean ideal number of children1 Number of women Percentage of currently married women with an unmet need for family planning2 Number of women For spacing For limiting Total Number of decisions in which women participate3 0 5.6 458 22.9 8.1 31.0 485 1-2 5.3 1,301 25.9 9.3 35.2 1,350 3 5.3 3,329 20.4 9.1 29.6 3,551 Number of reasons for which wife-beating is justified4 0 4.7 5,075 21.3 9.0 30.3 3,043 1-2 4.9 1,634 24.8 8.0 32.8 982 3-4 5.1 1,881 21.0 9.9 30.9 1,192 5 5.3 260 26.7 11.1 37.8 168 Total 4.8 8,849 22.0 9.1 31.1 5,386 1 Mean excludes respondents who gave non-numeric responses. 2 See Chapter 7 and Bradley et al., 2012 for the definition of unmet need for family planning. 3 Restricted to currently married women. See Table 15.6.1 for the list of decisions. 4 See Table 15.7.1 for the list of reasons. 15.9 WOMEN’S EMPOWERMENT AND REPRODUCTIVE HEALTH CARE Table 15.11 shows women’s use of prenatal, delivery, and postnatal care services from health care workers by level of empowerment, as measured by the two empowerment indicators. Theoretically, increased empowerment of women is likely to increase their ability to seek out and use health services, enabling them to better meet their reproductive health goals, including safe motherhood. However, the results in Table 15.11 show that, overall, in Liberia there is no correlation between women’s empowerment and reproductive health care. That is, no differences are seen in the proportions of women who received prenatal care, delivery assistance, or postnatal care from health personnel, with respect to the levels of either of the empowerment indicators. Table 15.11 Reproductive health care by women's empowerment Percentage of women age 15-49 with a live birth in the five years preceding the survey who received prenatal care, delivery assistance, and postnatal care from health personnel for the most recent birth, by indicators of women's empowerment, Liberia 2013 Empowerment indicator Percentage receiving prenatal care from a skilled provider1 Percentage receiving delivery care from a skilled provider1 Received postnatal care from health personnel within the first two days since delivery2 Number of women with a child born in the last five years Number of decisions in which women participate3 0 95.4 62.3 70.3 320 1-2 96.5 64.9 66.7 869 3 95.3 61.9 70.8 2,294 Number of reasons for which wife- beating is justified4 0 96.4 66.8 71.3 2,628 1-2 96.1 62.9 67.5 916 3-4 94.6 63.3 72.6 1,077 5 96.0 67.8 74.3 149 Total 95.9 65.3 70.9 4,769 1 “Skilled provider” includes doctor, nurse, midwife, or physician’s assistant 2 Includes women who received a postnatal checkup from a doctor, nurse, midwife, physician’s assistant, community health worker, or traditional birth attendant (TBA) in the first two days after the birth. Includes women who gave birth in a health facility and those who did not give birth in a health facility. 3 Restricted to currently married women. See Table 15.6.1 for the list of decisions. 4 See Table 15.7.1 for the list of reasons. Women’s Empowerment and Demographic and Health Outcomes • 275 15.10 DIFFERENTIALS IN INFANT AND CHILD MORTALITY BY WOMEN’S EMPOWERMENT The abilities of women to access information, make decisions, and act effectively in their own interest, or in the interest of those who depend on them, are essential aspects of the empowerment of women. If women, the primary caretakers of children, are empowered, the health and survival of their infants will be enhanced. In fact, maternal empowerment fits into Mosley and Chen’s framework on child survival as an individual-level variable that affects child survival through proximate determinants (Mosley, W.H., and L.C. Chen, 1984). However, Table 15.12 suggests that in Liberia there is no clear correlation between women’s empowerment and infant, child, or under-5 mortality rates. For example, infant mortality is similar for women who participate in three household decisions and women who participate in no household decisions, and is actually lowest among women who participate in one to two household decisions. Moreover, infant mortality is highest among women who do not agree with any of the reasons justifying wife beating and is lowest among women who agree with five reasons justifying wife beating. Child and under-5 mortality also show unremarkable or unclear differences with respect to empowerment indicator categories. Table 15.12 Early childhood mortality rates by women's status Infant, child, and under 5 mortality rates for the 10-year period preceding the survey, by indicators of women's empowerment, Liberia 2013 Empowerment indicator Infant mortality (1q0) Child mortality (4q1) Under 5 mortality (5q0) Number of decisions in which women participate1 0 71 48 116 1-2 57 46 101 3 70 47 114 Number of reasons for which wife- beating is justified2 0 74 45 116 1-2 69 55 120 3-4 60 45 103 5 49 (34) (82) Note: Figures in parentheses are based on 250-499 unweighted person-years of exposure to the risk of death. 1 Restricted to currently married women. See Table 15.6.1 for the list of decisions. 2 See Table 15.7.1 for the list of reasons. 15.11 FEMALE GENITAL CUTTING Female genital cutting (FGC)—also called female circumcision and female genital mutilation— involves cutting some part of the clitoris or labia, usually as part of a traditional ceremony or rite of passage into adolescence. In Liberia, FGC is usually implemented through bush societies or the Sande society, which refer to bush schools for young girls. Girls are taken to the bush where they are taught local customs, sex education, feminine hygiene, and housekeeping skills. They also undergo FGC, which in Liberia usually consists of removing some of or the entire clitoris. Because of the secretive nature of the bush society and the sensitivity of direct questions about FGC, women interviewed in the 2013 LDHS were asked if they had ever heard of a bush society like the Sande society and, if so, whether they were a member of the Sande society or a woman’s bush society. They were further asked whether they thought that this society should continue or should stop. As shown in Table 15.13, 89 percent of women said they had heard of a bush society like the Sande society. Among those who had heard of bush societies, 50 percent said they were members of the Sande society or a woman’s bush society. Among women who are members, 39 percent think that the society should stop. 276 • Women’s Empowerment and Demographic and Health Outcomes Table 15.13 Female genital cutting Percentage of women age 15-49 who have heard of the Sande bush society, and among those, the percentage who are members of the society, and among those, the percentage who think the society should stop, according to background characteristics, Liberia 2013 Background characteristic All women Women who have heard of Sande society Women who are members of Sande society Percentage who have heard of Sande society Number of women Percentage who are members Number of women Percentage who think Sande society should stop Number of women Age 15-19 85.0 2,080 31.1 1,768 41.4 550 20-24 89.9 1,642 39.8 1,476 38.4 588 25-29 89.4 1,611 50.1 1,439 38.4 721 30-34 89.4 1,199 60.3 1,072 38.3 646 35-39 92.1 1,179 60.3 1,085 40.9 654 40-44 91.8 812 63.3 746 37.3 473 45-49 91.3 716 72.4 654 40.1 473 Residence Urban 91.4 5,633 40.8 5,146 36.0 2,099 Greater Monrovia 91.5 3,361 31.9 3,075 30.0 982 Other urban 91.2 2,272 53.9 2,071 41.3 1,117 Rural 85.8 3,606 64.8 3,095 42.7 2,006 Region North Western 94.3 837 72.0 789 48.7 568 South Central 92.6 4,854 39.1 4,497 30.3 1,757 South Eastern A 60.7 483 22.7 293 25.6 67 South Eastern B 58.7 577 5.4 339 31.4 18 North Central 93.3 2,488 73.0 2,323 46.1 1,695 County Bomi 96.3 244 67.2 235 53.1 158 Bong 94.7 894 82.3 847 40.0 697 Gbarpolu 95.5 182 73.2 174 38.7 127 Grand Bassa 94.5 434 65.3 410 19.1 268 Grand Cape Mount 92.5 412 74.3 381 50.7 283 Grand Gedeh 55.1 167 15.4 92 (40.9) 14 Grand Kru 50.9 217 7.5 111 * 8 Lofa 91.7 447 80.8 410 69.2 332 Margibi 94.5 744 50.4 703 40.1 355 Maryland 70.1 257 2.7 180 * 5 Montserrado 92.1 3,675 33.5 3,383 29.8 1,134 Nimba 92.9 1,147 62.6 1,065 40.9 667 River Cess 76.4 135 40.5 103 17.1 42 River Gee 46.9 103 10.9 48 * 5 Sinoe 54.3 182 10.9 99 (38.3) 11 Religion Christian 89.5 7,945 46.9 7,109 35.1 3,333 Muslim 87.5 1,001 68.6 876 55.8 600 Traditional religion (86.1) 42 (89.2) 36 * 32 No religion 87.3 227 67.8 198 65.9 134 Other * 1 nc 0 nc 0 Education No education 88.6 3,066 71.2 2,715 45.6 1,934 Primary 86.6 2,875 48.9 2,489 40.5 1,217 Secondary and higher 92.1 3,298 31.4 3,037 24.8 954 Wealth quintile Lowest 84.0 1,581 69.5 1,328 43.2 924 Second 86.1 1,624 65.2 1,398 44.0 912 Middle 90.3 1,779 56.8 1,606 45.1 912 Fourth 93.5 2,047 40.6 1,914 33.1 777 Highest 90.3 2,207 29.1 1,994 24.7 580 Total 89.2 9,239 49.8 8,241 39.3 4,105 Note: Membership in the Sande society is a proxy for female genital cutting. Total includes a small number of women with information missing on religion. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. nc = no cases Women’s Empowerment and Demographic and Health Outcomes • 277 The prevalence of membership in the Sande society is higher among older women, increasing from 31 percent among women age 15-19 to 72 percent among women age 45-49. Membership is also more common among rural women (65 percent) than urban women (41 percent). Society membership is more common among women in the North Central (73 percent) and North Western (72 percent) regions, as compared with the South Central (39 percent), South Eastern A (23 percent), and South Eastern B (5 percent) regions. Membership in the society is inversely correlated with both level of education and wealth quintile, ranging from 71 percent of women with no education to 31 percent of women with a secondary and higher education, and from 70 percent of women in the lowest wealth quintile to 29 percent of women in the highest. Among women who are members of the Sande society, differences in the percentages who think the society should stop generally do not vary substantially by age or residence, but members do show differences by county, religion, education, and wealth. 15.12 ATTITUDES TOWARD CHILD BEATING Child beating is a common practice in Liberia that is passed from generation to generation. As Liberians learn more about life outside the country, opportunities arise to adapt behavior. For example, behaviour change education provides information to children and parents alike about prevailing human rights issues, including child beating. Respondents in the 2013 LDHS were asked questions about whether or not parents are justified in hitting or beating their children for five specific reasons. Tables 15.14.1 and 15.14.2 show results for women and men, respectively, age 15-49. Fifty-six percent of women and 35 percent of men agree that parents are justified in hitting or beating their children if they go out without telling them. Similarly, 56 percent of women and 35 percent of men report that parents are justified in hitting or beating their children if they do not want to do housework. If children speak when grown-ups are talking, 61 percent of women and 31 percent of men believe that parents are justified in hitting or beating their children; and if children do not study well at school, 51 percent of women and 35 percent of men agree that parents are justified in hitting or beating their children. Only 2 percent of women and 1 percent of men report that parents are justified in hitting or beating their children if they ask for clothes or toys. Overall, 73 percent of women and 51 percent of men agree that at least one of the specified reasons is justification for parents to hit or beat their children. 278 • Women’s Empowerment and Demographic and Health Outcomes Table 15.14.1 Attitude toward child beating: Women Percentage of all women age 15-49 who agree that parents are justified in hitting or beating their children for specific reasons, according to background characteristics, Liberia 2013 Background characteristic Parents are justified in hitting or beating their children if: Percentage who agree with at least one specified reason Number of women They go out without telling them They do not want to do housework They speak when grown-ups are talking They do not study well at school They ask for clothes or toys Age 15-19 57.2 58.4 62.1 54.1 3.4 74.9 2,080 20-24 53.6 55.4 58.0 51.8 1.7 72.4 1,642 25-29 55.0 55.3 61.1 52.5 1.9 73.9 1,611 30-34 58.1 55.7 61.1 49.2 1.2 71.8 1,199 35-39 52.4 53.0 58.0 47.8 1.5 70.6 1,179 40-44 61.2 58.1 62.5 52.5 2.3 75.2 812 45-49 54.9 51.1 62.0 46.8 2.2 74.5 716 Employment (past 12 months) Not employed 56.9 56.8 59.6 53.0 3.0 73.6 3,944 Employed for cash 53.8 53.5 58.7 48.5 1.2 70.4 3,564 Employed not for cash 57.8 57.8 66.8 53.1 1.8 78.9 1,721 Number of living children 0 53.8 55.5 59.2 50.3 3.0 72.0 2,185 1-2 55.4 54.5 58.7 51.8 1.5 72.1 3,294 3-4 56.6 56.3 62.5 51.0 1.7 74.6 2,084 5+ 58.5 57.5 63.4 51.9 2.6 75.9 1,676 Marital status Never married 55.2 56.5 60.3 52.3 2.7 73.0 2,867 Married or living together 56.6 55.8 60.8 50.6 1.9 73.7 5,386 Divorced/separated/widowed 53.5 53.0 59.8 51.9 1.5 72.3 987 Residence Urban 55.9 56.0 60.4 49.5 1.6 72.3 5,633 Greater Monrovia 51.9 51.8 55.8 47.0 0.5 68.0 3,361 Other urban 61.9 62.1 67.2 53.3 3.2 78.6 2,272 Rural 55.7 55.2 60.8 54.0 2.9 74.9 3,606 Region North Western 45.8 43.4 50.9 42.7 2.2 63.6 837 South Central 54.6 54.2 59.7 49.8 0.7 71.2 4,854 South Eastern A 59.2 57.4 66.1 54.8 2.8 78.1 483 South Eastern B 56.9 62.0 59.8 64.1 3.3 82.2 577 North Central 60.7 61.0 64.6 53.3 4.4 77.8 2,488 County Bomi 40.3 36.0 43.5 48.8 1.7 60.6 244 Bong 55.5 52.8 60.8 53.1 2.4 76.7 894 Gbarpolu 58.4 58.9 67.6 56.6 1.6 77.7 182 Grand Bassa 65.6 64.5 69.7 66.0 2.9 82.3 434 Grand Cape Mount 43.6 40.8 47.9 33.0 2.8 59.1 412 Grand Gedeh 62.1 60.0 67.6 50.5 0.3 78.8 167 Grand Kru 49.2 59.0 48.3 65.0 4.3 80.2 217 Lofa 43.4 48.0 43.6 47.0 1.5 63.8 447 Margibi 64.6 63.7 69.9 52.3 0.6 78.5 744 Maryland 62.3 66.0 66.5 61.8 2.0 83.4 257 Montserrado 51.3 51.0 56.4 47.4 0.5 68.4 3,675 Nimba 71.4 72.5 75.8 55.9 7.0 84.0 1,147 River Cess 60.8 57.7 65.1 51.3 0.8 76.9 135 River Gee 59.3 58.6 67.6 67.6 4.7 83.4 103 Sinoe 55.3 54.9 65.5 61.2 6.5 78.3 182 Education No education 58.2 57.6 62.5 50.1 1.9 75.9 3,066 Primary 57.4 58.1 63.0 54.9 3.2 75.0 2,875 Secondary and higher 52.3 51.8 56.6 49.2 1.4 69.5 3,298 Wealth quintile Lowest 57.0 56.4 59.6 52.9 2.5 75.5 1,581 Second 55.7 58.1 62.2 52.5 2.6 75.5 1,624 Middle 62.0 60.9 66.3 57.4 3.2 78.4 1,779 Fourth 57.5 57.6 62.4 49.2 1.5 74.1 2,047 Highest 48.7 47.4 53.7 46.1 1.1 65.4 2,207 Total 55.8 55.7 60.6 51.3 2.1 73.3 9,239 Note: Total includes 9 cases for which information on employment for cash or not for cash is missing. Women’s Empowerment and Demographic and Health Outcomes • 279 Table 15.14.2 Attitude toward child beating: Men Percentage of all men age 15-49 who agree that parents are justified in hitting or beating their children for specific reasons, according to background characteristics, Liberia 2013 Background characteristic Parents are justified in hitting or beating their children if: They go out without telling them They do not want to do housework They speak when grown-ups are talking They do not study well at school They ask for clothes or toys Percentage who agree with at least one specified reason Number of men Age 15-19 35.8 39.7 32.6 38.1 1.9 53.1 890 20-24 31.9 33.0 28.0 36.0 0.5 50.4 696 25-29 37.6 33.7 29.3 30.6 0.9 50.8 673 30-34 35.5 35.9 31.3 34.4 1.0 50.8 575 35-39 31.3 34.2 32.9 35.7 0.6 49.9 469 40-44 34.7 32.7 28.3 35.2 0.3 48.7 482 45-49 38.8 35.7 32.7 32.7 0.6 51.9 332 Employment (past 12 months) Not employed 26.6 31.0 23.7 30.8 1.3 43.9 958 Employed for cash 35.6 34.5 29.6 32.3 0.8 49.9 2,396 Employed not for cash 43.6 43.2 42.6 48.8 0.9 63.4 761 Number of living children 0 35.5 36.8 31.0 36.1 1.3 51.3 1,634 1-2 33.8 32.0 28.2 31.7 0.5 49.9 1,083 3-4 31.5 32.0 30.4 33.0 1.1 46.3 728 5+ 39.4 40.4 34.2 39.5 0.5 57.1 673 Marital status Never married 35.7 37.0 30.9 36.2 1.3 52.0 1,749 Married or living together 34.1 34.0 30.6 34.0 0.6 50.0 2,218 Divorced/separated/widowed 39.1 35.0 29.0 35.0 1.0 53.3 151 Residence Urban 33.4 32.8 28.3 31.0 0.8 47.6 2,413 Greater Monrovia 31.0 27.6 21.9 25.7 0.5 40.0 1,433 Other urban 37.1 40.3 37.8 38.8 1.4 58.7 980 Rural 37.2 38.8 33.9 40.5 1.0 55.8 1,705 Region North Western 30.7 32.1 22.8 32.0 0.0 40.5 367 South Central 36.0 33.2 28.5 29.8 1.0 48.4 2,149 South Eastern A 34.7 37.2 31.1 41.5 0.5 56.1 254 South Eastern B 39.9 42.4 41.1 53.2 3.0 66.2 288 North Central 33.2 38.2 34.8 39.9 0.6 54.4 1,060 County Bomi 11.6 15.2 11.6 16.8 0.0 20.9 97 Bong 50.5 54.4 52.2 48.6 1.2 65.3 389 Gbarpolu 45.0 40.7 38.2 35.5 0.0 51.9 94 Grand Bassa 43.8 38.5 41.6 42.2 1.2 63.4 204 Grand Cape Mount 33.7 36.7 20.8 38.4 0.0 45.2 176 Grand Gedeh 19.3 20.4 21.0 30.9 0.0 45.0 82 Grand Kru 38.8 38.9 47.9 54.6 1.1 64.4 110 Lofa 20.1 21.5 25.7 21.3 0.2 35.3 219 Margibi 45.1 48.3 42.5 33.4 2.8 66.5 364 Maryland 44.9 51.6 35.2 59.7 5.9 74.5 123 Montserrado 32.8 29.1 23.6 27.4 0.6 42.3 1,582 Nimba 24.8 32.3 24.2 41.3 0.3 54.3 451 River Cess 47.9 48.7 44.4 52.8 0.9 68.2 64 River Gee 30.8 28.6 40.7 35.8 0.5 51.1 55 Sinoe 38.4 43.0 30.8 42.9 0.8 57.4 108 Education No education 36.7 37.7 32.6 34.2 0.8 50.8 533 Primary 36.9 40.3 33.5 40.0 1.7 56.1 1,202 Secondary and higher 33.6 32.2 28.8 32.6 0.5 48.4 2,383 Wealth quintile Lowest 38.5 39.8 37.1 40.5 0.7 56.0 749 Second 39.9 43.5 36.5 47.6 1.0 60.2 753 Middle 34.5 37.0 28.5 35.3 1.1 52.4 728 Fourth 33.9 33.1 29.7 31.5 1.2 49.4 864 Highest 30.1 26.6 24.0 24.3 0.7 40.8 1,024 Total 35.0 35.3 30.7 35.0 0.9 51.0 4,118 Note: Total includes 2 cases for which information on employment for cash or not for cash is missing. Adult and Maternal Mortality • 281 ADULT AND MATERNAL MORTALITY 16 dult and maternal mortality rates are key indicators of the health status of a population. In Liberia, maternal mortality is a core indicator of national health performance. Estimation of mortality rates requires comprehensive and accurate reporting of adult deaths, including maternal deaths. The maternal mortality module included in the 2013 LDHS gathers the valuable information that is needed to determine maternal mortality. This chapter includes results based on collection of sibling history data in the Sibling Survival Module (commonly referred to as the “Maternal Mortality Module”) of the 2013 LDHS Woman’s Questionnaire. In addition to adult mortality rates for five-year age groups, this chapter includes a summary measure (35q15) that represents the probability of dying between exact ages 15 and 50. In order to compare this measure with the 2007 LDHS, the adult mortality probabilities (35q15) for the 2007 LDHS have been calculated and presented in Table 16.2. The term maternal mortality, used in this chapter and in previous LDHS surveys, corresponds to the term pregnancy-related mortality, as defined in the latest version of the International Classification of Diseases (ICD-10). The ICD-10 definition of a pregnancy-related death is “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death” (WHO, 2011c). In keeping with this definition, the Sibling Survival Module used in the DHS surveys measures only the timing of deaths and not the cause of death. The data collected in the LDHS questionnaire are based on information about deaths that occur during the two months following a birth rather than the 42 days following a birth. 16.1 ASSESSMENT OF DATA QUALITY To obtain a sibling history, the 2013 LDHS first asked each female respondent to list all children born to her biological mother, starting with the firstborn. The survey then asked the respondent whether each of these siblings was still alive. For living siblings, the interviewer asked the current age of each sibling. For deceased siblings, the age at death and the number of years since death were recorded. When a respondent could not provide precise information on age at death or years since death, approximate but quantitative answers were accepted. For sisters who died at age 12 or older, the LDHS asked three questions to determine A Key Findings • Adult mortality is slightly higher among women than men (4.9 female deaths and 4.1 male deaths per 1,000 population, respectively). • Between age 15 and age 50, approximately 176 women per 1,000 and 151 men per 1,000 are likely to die. • Maternal deaths account for 38 percent of all deaths to women age 15- 49. The maternal mortality rate for the seven-year period preceding the survey was 1.7 maternal deaths per 1,000 woman-years of exposure. • The maternal mortality ratio was 1,072 maternal deaths per 100,000 live births for the seven-year period preceding the survey. Although this ratio is higher than the ratio reported in the 2007 LDHS (994), the difference is not statistically significant. 282 • Adult and Maternal Mortality whether the death was maternal: “Was [NAME] pregnant when she died?” and, if the response was negative, “Did she die during childbirth?” and, if negative again, “Did she die within two months after the end of a pregnancy or childbirth?” Table C.7 in Appendix C shows that in the 2013 LDHS, a total of 48,190 siblings were recorded in the sibling histories, with nearly 40,000 reported as living and over 8,000 reported as deceased. Survival status was not reported for 14 siblings. Among surviving siblings, current age was not reported for less than 1 percent. Among deceased siblings, both age at death (AD) and years since death (YSD) were reported for more than 99 percent. The sex ratio of the enumerated siblings (the ratio of brothers to sisters x 100) is 98.3 (see Table C.8), which is lower than the expected value of 100.2 (LISGIS, 2009), a difference that suggests sisters may be over-reported. 16.2 ESTIMATES OF ADULT MORTALITY One way to assess the quality of data used to estimate maternal mortality is to evaluate the plausibility and stability of adult mortality estimates. If the overall estimated rates of adult mortality are implausible, rates based on a subset of deaths—maternal mortality, in particular—are likely to have serious problems. Moreover, levels and trends in overall adult mortality have important implications for health and social welfare programs in Liberia, especially with regard to the potential impact of limited access to health care services, an inadequately qualified and skilled health work force, and the emergence of infectious and non-communicable diseases. The direct estimation of adult mortality uses the reported ages at death and years since the death of the respondents’ brothers and sisters. Mortality rates are calculated by dividing the number of deaths in each age group of women and men by the total person-years of exposure to the risk of dying in that age group during a specified period prior to the survey. To have a sufficiently large number of adult deaths to generate a robust estimate, the rates are calculated for the seven-year period preceding the survey (approximately 2006 to 2013). Nevertheless, the age- specific mortality rates obtained in this manner are subject to considerable sampling variation. Table 16.1 and Figure 16.1 show age- specific mortality rates (ASMR) for women and men age 15-49 for the seven-year period preceding the survey. Overall, the level of adult mortality is slightly higher among women (4.9 deaths per 1,000 population) than among men (4.1 deaths per 1,000 population). Age-specific mortality rates appear to be higher for women than for men in most age groups. Generally, ASMRs show the expected increases with age, for both women and men. The confidence intervals for many of the five-year mortality rates overlap and can be found in Appendix Table B.27. Relative to the 2013 LDHS, adult mortality rates for both males and females were distinctly different in the 2007 LDHS. Overall, mortality was higher among men than women in the 2007 LDHS (5.4 deaths per 1,000 population for men versus 4.9 deaths per 1,000 population for women), whereas mortality was lower among men than women in the 2013 LDHS (4.1 deaths per 1,000 population for men and 4.9 deaths per 1,000 population for Table 16.1 Adult mortality rates Direct estimates of female and male mortality rates for the seven years preceding the survey, by five-year age groups, Liberia 2013 Age Deaths Exposure years Mortality rates1 FEMALE 15-19 54 18,616 2.92 20-24 82 21,948 3.72 25-29 103 21,254 4.83 30-34 79 17,638 4.47 35-39 72 12,880 5.56 40-44 69 8,184 8.41 45-49 42 4,753 8.73 15-49 500 105,273 4.87a MALE 15-19 56 18,322 3.06 20-24 69 19,961 3.46 25-29 55 20,226 2.71 30-34 72 16,161 4.44 35-39 56 11,983 4.64 40-44 56 7,349 7.69 45-49 30 4,446 6.68 15-49 393 98,447 4.14a 1 Expressed per 1,000 population a Age-adjusted rate Adult and Maternal Mortality • 283 women). Female mortality rates exceed male rates at all ages except for age 15-19 in the 2013 LDHS, but differences in age-specific mortality between women and men were more variable in the 2007 LDHS. Figure 16.1 Age specific mortality rates by sex 0 1 2 3 4 5 6 7 8 9 10 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Deaths per 1,000 population Age group Females Males LDHS 2013 Table 16.2 shows a summary measure of the risk of dying between the exact ages of 15 and 50 (35q15). That is, 35q15 represents the risk of a 15-year-old man or woman dying before age 50. According to the 2013 LDHS, 176 of 1,000 Liberian women age 15, and 151 of 1,000 Liberian men age 15, are likely to die before reaching age 50. In the 2007 LDHS, the probability of dying between the ages of 15 and 50 (35q15) was lower for women (164 deaths per 1,000 persons who reached age 15) and higher for men (186 deaths per 1,000 persons who reached age 15), as compared with the 2013 LDHS. The confidence limits for the 35q15 estimates for the 2013 LDHS can be found in Appendix Table B.27. Table 16.2 Adult mortality probabilities The probability of dying between the ages of 15 and 50 for women and men for the seven years preceding the survey, Liberia 2013 Survey Female Male 35q151 35q151 2013 LDHS 176 151 2007 LDHS 164 186 1 The probability of dying between exact ages 15 and 50, expressed per 1,000 persons who reached age 15 16.3 ESTIMATES OF MATERNAL MORTALITY In this survey, maternal deaths are defined as any deaths that occur during pregnancy, childbirth, or within two months after the birth or termination of a pregnancy. Estimates of maternal mortality are therefore 284 • Adult and Maternal Mortality based solely on the timing of the death in relationship to the pregnancy1. Maternal mortality in Liberia and other developing countries can be estimated using two procedures: the indirect sisterhood method (Graham et al., 1989) or a direct estimation variant of the sisterhood method (Rutenberg and Sullivan, 1991). In this report, the direct estimation variant is used to estimate maternal mortality. Table 16.3 presents direct estimates of maternal mortality for the seven-year period preceding the survey. The maternal mortality rate among women age 15-49 is 1.7 maternal deaths per 1,000 woman-years of exposure, which is essentially unchanged since the 2007 LDHS. By five-year age groups, the maternal mortality rate is highest among women 40-44 (3.1), followed by those age 25-29 (2.2) and 30-34 (2.1). The confidence limits for the maternal mortality rates can be found in Appendix Table B.27. Table 16.3 Maternal mortality Direct estimates of maternal mortality rates for the seven years preceding the survey, by five-year age groups, Liberia 2013 Age Percentage of female deaths that are maternal Maternal deaths Exposure years Maternal mortality rate1 15-19 31.6 17 18,616 0.92 20-24 39.2 32 21,948 1.46 25-29 45.3 47 21,254 2.19 30-34 47.8 38 17,638 2.14 35-39 28.2 20 12,880 1.56 40-44 37.1 26 8,184 3.12 45-49 20.2 8 4,753 1.77 Total 15-49 37.5 188 105,273 1.74 General fertility rate (GFR)2 162a Maternal mortality ratio (MMR)3 1,072 CI: (776-1,368) Lifetime risk of maternal death4 0.053 2007 LDHS Maternal mortality ratio (MMR)3 994 CI: (678-1,310) CI: Confidence interval 1 Expressed per 1,000 woman-years of exposure 2 Expressed per 1,000 women age 15-49 3 Expressed per 100,000 live births; calculated as the age-adjusted maternal mortality rate times 100 divided by the age-adjusted general fertility rate 4 Calculated as 1-(1-MMR)TFR where TFR represents the total fertility rate for the seven years preceding the survey a Age-adjusted rate In the 2013 LDHS, maternal deaths represent 38 percent of all deaths to women age 15-49, compared with 35 percent in the 2007 LDHS. Also, the percentage of female deaths that are maternal varies by age and ranges from 20 percent of all deaths among women 45-49 to 48 percent of all deaths among women 30-34 years. The maternal mortality rate can be converted to a maternal mortality ratio (expressed as deaths per 100,000 live births) by dividing the total maternal mortality rate (1.7) by the general fertility rate (GFR) of 162 that prevailed during the same time period, and multiplying the result by 100,000. This procedure produces a 1 This time-dependent definition includes all deaths that occurred during pregnancy and two months after pregnancy, even if the death was due to non-maternal causes. However, this definition is unlikely to result in over-reporting of maternal deaths because most deaths to women during the two-month period are due to maternal causes. Adult and Maternal Mortality • 285 maternal mortality ratio (MMR) of 1,072 deaths per 100,000 live births during the seven-year period preceding the survey. In other words, for every 1,000 live births in Liberia during the seven years preceding the 2013 LDHS, about 11 women died during pregnancy, or during childbirth, or within two months of childbirth. The lifetime risk of maternal death (0.053) indicates that about 5 percent of women die during pregnancy, during childbirth, or within two months of childbirth. These figures should be viewed with caution because the number of female deaths occurring during pregnancy, at delivery, or within two months of delivery is small (188). As a result, the maternal mortality estimates are subject to larger sampling errors than the adult mortality estimates. Confidence limits are presented in Appendix Table B.27. The 2013 MMR estimate (1,072) is higher than the 2007 LDHS (994) by 8 percent. Important to note, however, is that the difference between the 2013 and 2007 estimates of the MMR is not statistically significant. As shown in Table 16.3 and Figure 16.2, the confidence interval for the 2013 MMR estimate spans the point estimate of the MMR in the 2007 DHS and vice versa. The confidence interval for the 2007 MMR of 994 deaths per 100,000 live births is 678-1,310 deaths, while the confidence interval for the 2013 LDHS MMR of 1,072 is 776-1,368. Any change that may have occurred between the two surveys was not large enough to be significant with the sample sizes of the surveys. Figure 16.2 Maternal mortality ratio (MMR) with confidence intervals for the seven years preceding the 2007 Liberia DHS and the 2013 Liberia DHS 994 1072 0 200 400 600 800 1000 1200 1400 Seven years preceding the 2007 LDHS Seven years preceding the 2013 LDHS Maternal deaths per 100,000 live births Midpoint of MMR LDHS 2013 An MMR was also estimated as part of the 1999/2000 LDHS (578 maternal deaths per 100,000 live births). The 1999/2000 LDHS included questions similar to those asked of respondents in the 2007 and 2013 LDHS. However, there were several key methodological differences that complicate the comparison of the 1999/2000 LDHS estimate with either the 2007 or 2013 LDHS estimate. First, the 2000 survey asked questions related to sibling mortality of both male and female respondents, and responses from both were used to produce the estimate. However, the 2007 and 2013 LDHS surveys included questions on siblings for female respondents only. Second, maternal deaths were defined as any deaths that occurred during pregnancy, childbirth, or within six weeks after the birth or termination of a pregnancy rather than deaths that occurred during pregnancy, childbirth, or within two months after the birth or termination of a pregnancy. Third, the 286 • Adult and Maternal Mortality MMR reported in the 1999/2000 LDHS was based on the indirect estimation procedure rather than the direct estimation method used in the 2007 and 2013 LDHS. Finally, the 1999/2000 LDHS estimate was based on the 12 to 13 years preceding the survey (roughly 1987-2000) rather than the seven-year period preceding the 2007 survey (roughly 2000-2007) or the seven-year period preceding the 2013 survey (roughly 2006-2013). Differences between the three surveys could be due to variations in estimation, differences in analysis, and large sampling errors. Thus, although the absolute difference in the MMR for the 1999/2000 LDHS and either the 2007 or 2013 LDHS suggests an increase in maternal mortality in the last 25 years, validating this conclusion will require additional analysis. It is important to remember that the sample sizes implemented in these three surveys do not allow for precise estimates of maternal mortality. The sampling errors around these estimates are large and, consequently, differences need to be interpreted with caution. A large increase in the maternal mortality ratio is not supported by the trends in related indicators, such as prenatal care coverage, delivery in health facilities, and medical assistance at delivery, all of which have improved over the last seven years. The main health factors contributing to the high level of maternal mortality include the acute shortage of skilled health workers, inadequate emergency obstetric care facilities, inefficient and limited referral systems, poor nutritional status of pregnant women, high fertility rates, and extremely high number of teenage pregnancies, coupled with low access to family planning services. Moreover, four in ten births are delivered by traditional midwives or other unskilled attendants. The health and social welfare sector is determined to reduce the MMR in Liberia. In an effort to reduce maternal and newborn deaths and achieve the Millennium Development Goals 4 and 52, the Government of Liberia has developed a roadmap for maternal mortality reduction, adopted the Reach Every Pregnant Woman (REP) Strategy, and made compulsory the reporting of maternal deaths by health workers to keep up surveillance on maternal deaths. The National Roadmap has a resource mobilization tool highlighting simple, cost-effective interventions that would accelerate the reduction of maternal and newborn mortality over the next ten years beginning in 2011. The Roadmap has been costed for the first five years (2011-2015), during which period the MOHSW plans to reduce the maternal mortality rate by at least 25 percent from a baseline of 994/100,000, and 50 percent by 2021 (497/100,000). The five-year rough cost estimate of implementing maternal mortality reduction interventions is approximately 145 million USD (MOHSW, 2011b; MOHSW, 2012). 2 MDG 4 is to reduce child mortality; target 4A is to reduce by two-thirds, between 1990 and 2015, the under-5 mortality rate. MDG 5 is to improve maternal health; target 5A is to reduce by three-quarters, between 1990 and 2015, the maternal mortality ratio. References • 287 REFERENCES African Economic Outlook. Liberia: Overview. http://www.africaneconomicoutlook.org/en/countries/west- africa/liberia (accessed March 11, 2014). Arimond, M., and M. T. Ruel. 2004. “Dietary Diversity Is Associated with Child Nutritional Status: Evidence from 11 Demographic and Health Surveys.” Journal of Nutrition 134:2579-2585. Auvert, B., D. Taljaard, E. Lagarde, J. Sobngwi-Tambekou, R. Sitta, and A. Puren. 2005. “Randomized, Controlled Intervention Trial of Male Circumcision for Reduction of HIV Infection Risk: The ANRS 1265 Trial.” PLoS Med 2(11): e298. doi:10.1371/journal.pmed.0020298. Bishai, David M., Nirali M. Shah, Damian G. Walker, William Brieger, David Peters. 2008. “Social Franchising to Improve Quality and Access in Private Health Care in Developing Countries.” Harvard Health Policy Review. 9(1):184-196. Boerma, T. 1988. “Monitoring and Evaluation of Health Interventions: Age- and Cause-Specific Mortality and Morbidity in Childhood.” In Research and Interventions Issues Concerning Infant and Child Mortality and Health, 195-218. Proceedings of the East Africa Workshop, International Development Research Center, Manuscript Report 200e. Ottawa, Canada. Chieh-Johnson, D., A. Cross, A. Way, and J. Sullivan. 1988. Liberia Demographic and Health Survey 1986. Columbia, Maryland, USA, and Monrovia, Liberia: Bureau of Statistics, Ministry of Planning and Economic Affairs, and Institute for Resource Development/Westinghouse. Doolan, D. L., C. Dobaño, and J. K. Baird. 2009. “Acquired Immunity to Malaria.” Clinical Microbiology Review 22(1):13-36. doi: 10.1128/CMR.00025-08. Graham, W., W. Brass, and R. W. Snow. 1989. “Indirect Estimation of Maternal Mortality: The Sisterhood Method.” Studies in Family Planning 20(3): 125-135. doi:10.2307/1966567. Guannu, Joseph Saye. 2010. Liberian History Up to 1847. Fourth Edition. Monrovia, Liberia: Star Books, Sedco Longman, pp 17-26. Killeen, G. F., T. A. Smith, H. M. Ferguson, H. Mshinda, S. Abdulla, C. Lengeler, S. P. Kachur. 2007. “Preventing Childhood Malaria in Africa by Protecting Adults from Mosquitoes with Insecticide-Treated Nets.” PLoS Medicine 4(7):e229. doi: 10.1371/journal.pmed.0040229. Liberia Institute of Statistics and Geo-Information Services (LISGIS). 2009. 2008 National Population and Housing Census, Final Results. Monrovia, Liberia: LISGIS. Liberia Institute of Statistics and Geo-Information Services (LISGIS). 2011a. 2008 National Population and Housing Census: Analytical report on Mortality. Monrovia, Liberia: LISGIS. Liberia Institute of Statistics and Geo-Information Services (LISGIS). 2011b. Liberia National Micronutrient Survey 2011: Summary of Key Findings. Monrovia, Liberia: LISGIS Liberia Institute of Statistics and Geo-Information Services (LISGIS), Ministry of Health and Social Welfare (MOHSW), National AIDS Control Program, and Macro International Inc. 2008. Liberia Demographic and Health Survey 2007. Monrovia, Liberia: Liberia Institute of Statistics and Geo-Information Services (LISGIS) and Macro International Inc. 288 • References Ministry of Health (MOH). 2001. Roll Back Malaria Situation Analysis, Liberia. Monrovia, Liberia: MOH. Ministry of Health and Social Welfare (MOHSW). 2011a. Country Situational Analysis Report. Monrovia, Liberia: MOHSW. Ministry of Health and Social Welfare (MOHSW). 2011b. Road Map for Accelerating Reduction of Maternal and Newborn Mortality and Morbidity (2011-2015). Monrovia, Liberia: MOHSW. Ministry of Health and Social Welfare (MOHSW). 2012. Accelerated Action Plan to Reduce Maternal and Neonatal Mortality. Monrovia, Liberia: MOHSW. Ministry of Health and Social Welfare (MOHSW) and National AIDS Commission (NAC). 2014. Integrated bio-Behavioural Surveillance Survey (IBBSS) among Most at Risk Populations (MARPs) in Liberia. Monrovia, Liberia: MOHSW and NAC. Ministry of Health and Social Welfare (MOHSW) and National AIDS Control Program (NACP). 2011. NACP Sentinel Survey Report. Monrovia, Liberia: MOHSW and NACP. Ministry of Health and Social Welfare (MOHSW) and National AIDS Control Program (NACP). Unpublished results. Personal communication by David Logan. Ministry of Planning and Economic Affairs (MPEA), University of Liberia, and United Nations Population Fund (UNFPA). 2000. Liberia Demographic and Health Survey: 1999/2000. Analytical Report. No. 3. Monrovia, Liberia: MPEA. Mosley, W. H., and L. C. Chen. 1984. “An Analytical Framework for the Study of Child Survival in Developing Countries.” Population and Development Review 10 (supplement):25-45. National AIDS Commission (NAC), 2010. National HIV Strategic Framework Framework II: 2010-2014. Monrovia, Liberia: NAC. National AIDS Commission (NAC). 2012. United Nations General Assembly Special Session on HIV and AIDS: Country Progress Report, 2012. Liberia: NAC. http://www.unaids.org/en/dataanalysis/ knowyourresponse/countryprogressreports/2012countries/ce_LR_Narrative_Report[1].pdf National AIDS Commission (NAC). 2014. Final Liberia Stigma Index Report, 2014. Monrovia, Liberia: National AIDS Commission. National AIDS Control Program (NACP) and Ministry of Health & Social Welfare (MOHSW). 2013. Prevention of Mother-to-Child Transmission of HIV: Impact Evaluation of PMTCT Programme in Liberia, 2012. Monrovia, Liberia: NACP and MOHSW. National AIDS Control Program (NACP) and Ministry of Health & Social Welfare (MOHSW). 2014. Retention, Reasons for Loss to Follow Up and Adherence of HIV-Positive Person Enrolled into Care and Treatment in Liberia – A Three-Year Cohort Study. Preliminary Report. Monrovia, Liberia: NACP and MOHSW. National Institute of Allergy and Infectious Diseases (NIAID). 2006. Adult Male Circumcision Significantly Reduces Risk of Acquiring HIV. Press Release. Washington, DC, USA: NIAID. http://www.nih.gov/news/pr/dec2006/niaid-13.htm. National Malaria Control Program (NMCP), Ministry of Health and Social Welfare (MOHSW). 2009. Health Facility Survey. Monrovia, Liberia: MOHSW. References • 289 National Malaria Control Program (NMCP), Ministry of Health and Social Welfare (MOHSW). 2011. National Malaria Strategic Plan 2010-2015. Monrovia, Liberia: Sabanoh Printing Press. National Malaria Control Program (NMCP), Ministry of Health and Social Welfare (MOHSW), Liberia Institute of Statistics and Geo-Information Services (LISGIS), and ICF Macro. 2009. Liberia Malaria Indicator Survey 2009. Monrovia, Liberia: MOHSW, LISGIS, and ICF Macro. National Malaria Control Program (NMCP), Ministry of Health and Social Welfare (MOHSW), Liberia Institute of Statistics and Geo-Information Services (LISGIS), and ICF International. 2012. Liberia Malaria Indicator Survey 2011. Monrovia, Liberia: MOHSW, LISGIS, and ICF International. Pan American Health Organization (PAHO) and World Health Organization (WHO). 2003. Guiding Principles for Complementary Feeding of the Breastfed Child. Washington, DC, USA, and Geneva, Switzerland: PAHO and WHO. President’s Malaria Initiative (PMI). 2013. Liberia Malaria Operational Plan FY 2013. http://www.pmi.gov/countries/mops/fy13/liberia_mop_fy13.pdf. Rutenberg, N., and J. Sullivan. 1991. “Direct and Indirect Estimates of Maternal Mortality from the Sisterhood Method.” In Proceedings of the Demographic and Health Surveys World Conference, 3: 1669-1696. Columbia, Maryland, USA: IRD/Macro International Inc. Rutstein, S., and K. Johnson. 2004. The DHS Wealth Index. DHS Comparative Reports No. 6. Calverton, Maryland: ORC Macro. Rutstein, S. 2008. The DHS Wealth Index: Approaches for Rural and Urban Areas. DHS Working Papers. Calverton, Maryland: Macro International. United Nations Children’s Fund (UNICEF). 2006. Child Protection Information Sheets. New York: UNICEF. United Nations Development Program (UNDP). 2013. Human Development Report 2013. The Rise of the South: Human Progress in a Diverse World. New York: United Nations Development Program. http://hdr.undp.org/sites/default/files/reports/14/hdr2013_en_complete.pdf. United Nations General Assembly. 2002. Road Map towards the Implementation of the United Nations Millennium Declaration: Report of the Secretary-General. New York: United Nations, General Assembly. A/56/326. US Department of Health and Human Services. 2006. The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta, GA, USA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Coordinating Center for Health Promotion, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. Williams, B. G., J. O. Lloyd-Smith, E. Gouws, C. Hankins, W. M. Getz, J. Hargrove, I. de Zoysa, C. Dye, B. Auvert. 2006. “The Potential Impact of Male Circumcision on HIV in Sub-Saharan Africa.” PLoS Med 3(7):e262. doi:10.1371/journal.pmed.0030262. Windham, G. C., A. Eaton, and B. Hopkins. 1999. “Evidence for an Association between Environmental Tobacco Smoke Exposure and Birth Weight: A Meta-Analysis and New Data.” Paediatric and Perinatal Epidemiology 13:35-37. World Bank, 2012. Liberia Poverty Note: Tracking the Dimensions of Poverty. World Bank, 2012 https://openknowledge.worldbank.org/bitstream/handle/10986/12320/NonAsciiFileName0.pdf?sequence=1. 290 • References World Health Organization (WHO). 1998. Complementary Feeding of Young Children in Developing Countries: A Review of Current Scientific Knowledge. Geneva, Switzerland: WHO. World Health Organization (WHO). 2005. Guiding Principles for Feeding Nonbreastfed Children 6 to 24 Months of Age. Geneva, Switzerland: WHO. World Health Organization (WHO). 2008. Indicators for Assessing Infant and Young Child Feeding Practices. Part I: Definitions. Conclusions of a Consensus Meeting held 6-8 November 2007 in Washington, DC, USA. http://whqlibdoc.who.int/publications/2008/9789241596664_eng.pdf. World Health Organization (WHO). 2010a. Guidelines for the treatment of malaria. Second edition. Geneva, Switzerland: WHO. http://whqlibdoc.who.int/publications/2010/9789241547925_eng.pdf World Health Organization (WHO). 2010b. Indicators for Assessing Infant and Young Child Feeding Practices. Part II: Measurement. Geneva, Switzerland: WHO. http://whqlibdoc.who.int/publications/2010/ 9789241599290_eng.pdf. World Health Organization (WHO). 2011a. Indoor Air Pollution and Health. Fact sheet N°292. Geneva, Switzerland: WHO. http://www.who.int/mediacentre/factsheets/fs292/en. World Health Organization (WHO). 2011b. WHO Report on the Global Tobacco Epidemic, 2011: Warning about the Dangers of Tobacco. Geneva, Switzerland: WHO. World Health Organization (WHO). 2011c. International Statistical Classification of Diseases and Related Health Problems – 10th revision, 2010 edition. Geneva, Switzerland: WHO. http://www.who.int/ classifications/icd/ICD10Volume2_en_2010.pdf?ua=1. World Health Organization (WHO) and Joint United Nations Program on HIV/AIDS (UNAIDS). 2007. New Data on Male Circumcision and HIV Prevention: Policy and Programme Implications. Geneva, Switzerland: WHO and UNAIDS. Accessed 13 February 2014. http://libdoc.who.int/publications/ 2007/9789241595988_eng.pdf. World Health Organization (WHO) Multicentre Growth Reference Study Group. 2006. WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Height and Body Mass Index-for Age: Methods and Development. Geneva, Switzerland: WHO. WHO and UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation. 2012a. Progress on Drinking Water and Sanitation: 2012 Update. Geneva and New York: WHO/UNICEF. http://www.wssinfo.org/fileadmin/user_upload/resources/JMP-report-2012-en.pdf. WHO and UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation. 2012b. Types of Drinking-Water Sources and Sanitation. http://www.wssinfo.org/definitions-methods/watsan-categories (accessed 10 February 2014). Appendix A • 291 SAMPLE DESIGN Appendix A A.1 INTRODUCTION he 2013 Liberia Demographic and Health Survey (2013 LDHS), which is the fourth DHS to be conducted in Liberia, follows other surveys carried out in 1986, 1999/2000, and 2007. The 2013 LDHS was designed to provide up-to-date information on key indicators needed to track progress in Liberia’s population and health programs. These indicators include fertility, fertility preferences, and contraceptive use; child and maternal mortality, utilization of maternal and child health services, women’s and children’s nutrition status; and knowledge, attitudes and behaviors relating to HIV/AIDS and other sexually transmitted diseases. In addition, the 2013 LDHS includes two biomarkers: anthropometry and HIV testing. To obtain these data, a nationally representative sample of households was selected. All women age 15-49 who were usual residents of the sampled households or who slept in the households on the night before the interview were eligible for interviewing. In addition, in every second household, all men age 15-49 who were usual residents of the household or slept in the household on the night before the interview were eligible for interviewing. In the subsample of households selected for the male survey, blood specimens for HIV testing were collected from all eligible women and men age 15-49 who voluntarily consented to the testing. Height and weight measurements were recorded for children age 0-59 months and women and men age 15-49. In Liberia, there are 15 counties, grouped to form five geographical regions (with each region consisting of three counties). The survey estimates are reported for the country as a whole, for all urban areas, for the capital city of Greater Monrovia, for the other urban areas, for all the rural areas, and for each of the five geographical regions. In total, there are nine report domains, with domain composition as follows: • All urban areas of Liberia • The urban capital city of Greater Monrovia • Urban areas of Liberia other than Greater Monrovia • The rural areas of Liberia • North Western: Bomi, Grand Cape Mount, Gbarpolu • South Central: Montserrado, Margibi, Grand Bassa • North Central: Bong, Nimba, Lofa • South Eastern A: River Cess, Sinoe, Grand Gedeh • South Eastern B: River Gee, Grand Kru, Maryland The survey will also produce separate representative results for most key indicators of the 15 counties. A.2 SAMPLE FRAME The 2013 LDHS sample was selected using a stratified, two-stage cluster design. The frame used for the first stage of the selection of the 2013 LDHS sample was based on an updated version of the 2008 Liberia National Population and Housing Census (2008 LPHC) in which the classification of localities as urban or rural was updated T 292 • Appendix A through the application of standardized definitions. Administratively, Liberia is divided into 15 counties; each county is sub-divided into a number of districts, and each district into clans. There are 138 districts and 854 clans. For the 2008 LPHC, each of the clans was subdivided into smaller enumeration areas (EAs), typically including about 100 households. The small size of the EAs and the availability of sketch maps and other materials to delimit their geographic boundaries made the census EA ideal for use as the first-stage sampling unit of the LDHS sample. Households were the units for second-stage sampling. Table A.1 shows the distribution of households and population as described in the updated 2008 census frame, by the geographic domains of interest for the LDHS, i.e., county by urban-rural residence. Table A.2 presents the distribution of enumeration areas and their average size in number of households in the sample frame by county and residence. Table A.1 Households and population Distribution of residential households and population in the sampling frame, by county and by type of residence, Liberia 2013 County Household distribution Population distribution Urban Rural County Urban Rural County Bomi 0.172 0.828 0.031 0.172 0.828 0.024 Bong 0.374 0.626 0.104 0.388 0.612 0.096 Gbarpolu 0.155 0.845 0.022 0.149 0.851 0.023 Grand Bassa 0.312 0.688 0.071 0.321 0.679 0.063 Grand Cape Mount 0.064 0.936 0.036 0.073 0.927 0.037 Grand Gedeh 0.446 0.554 0.027 0.416 0.584 0.036 Grand Kru 0.057 0.943 0.013 0.053 0.947 0.017 Lofa 0.363 0.637 0.074 0.359 0.641 0.080 Margibi 0.465 0.535 0.067 0.497 0.503 0.060 Maryland 0.487 0.513 0.029 0.457 0.543 0.039 Montserrado 0.936 0.064 0.347 0.943 0.057 0.323 Nimba 0.593 0.407 0.120 0.599 0.401 0.133 River Gee 0.291 0.709 0.015 0.302 0.698 0.019 River Cess 0.035 0.965 0.021 0.032 0.968 0.020 Sinoe 0.164 0.836 0.024 0.131 0.869 0.029 Liberia 0.562 0.438 1.000 0.554 0.446 1.000 Table A.2 Enumeration areas and households Number of enumeration areas and average number of households per EA in the sampling frame, by county and type of residence, Liberia 2013 County Number of EAs Average EA size Urban Rural County Urban Rural County Bomi 46 227 273 77 75 75 Bong 326 601 927 80 73 75 Gbarpolu 21 127 148 107 97 98 Grand Bassa 152 316 468 97 103 101 Grand Cape Mount 17 261 278 90 86 87 Grand Gedeh 83 93 176 97 108 103 Grand Kru 7 123 130 72 69 69 Lofa 170 331 501 106 95 99 Margibi 168 263 431 125 92 105 Maryland 73 98 171 129 101 113 Montserrado 2,101 149 2,250 104 101 104 Nimba 434 347 781 110 95 103 River Gee 29 79 108 99 88 91 River Cess 5 147 152 97 92 92 Sinoe 23 195 218 113 68 73 Liberia 3,655 3,357 7,012 103 88 96 Appendix A • 293 A.3 SAMPLE DESIGN AND IMPLEMENTATION The sample for LDHS 2013 was a stratified sample selected in two stages. In the first stage, 322 EAs were selected with a stratified probability proportional to size selection from the sampling frame. The EA size is the number of households residing in the EA recorded in the updated 2008 LPHC frame. Stratification was achieved by separating every county into urban and rural areas. The urban area in each county mainly consisted of the county’s capital. Therefore the 15 counties were stratified into 30 sampling strata: 15 rural strata and 15 urban strata. Samples were selected independently in each stratum, with a predetermined number of EAs to be selected. Implicit stratification was achieved at each of the lower administrative unit levels by sorting the sampling frame according to districts and clans within each sampling stratum and by using a probability-proportional-to-size selection procedure. After the selection of EAs and before the main survey, a household listing operation was carried out in all selected EAs. The resulting lists of households served as the sampling frame for the selection of households in the second stage. If an EA was too large to be a DHS cluster (>200 households), the EA was segmented into smaller segments following specified guidelines, and one of the resulting segments was selected with probability proportional to size. The household listing was conducted only in the selected segment, and the listing of the segment was then used to help select the final household sample. So, an LDHS 2013 cluster was either an EA or a segment of an EA. In the second stage of selection, a fixed number of 30 households were selected in every urban and rural cluster, by an equal probability systematic sampling. A spreadsheet indicating the selected household numbers for each cluster was prepared. The survey interviewers were asked to interview only the pre-selected households. To prevent bias, replacements and changes of the pre-selected households were not allowed. Table A.3 shows the sample allocation of clusters and households by report domain and by type of residence. The number of interviews with women and men that were expected to be completed based on the sample design is shown by county and residence in Table A.4. The sample allocation was a power allocation with a small adjustment, which took into account the county population and their urban-rural distribution. A proportional allocation was not applied because of the great disparity among the county sizes. Among the 322 clusters selected, 119 clusters were in urban areas, and 203 clusters were in rural areas. The total number of households selected in the 2013 LDHS was 9,660; 3,570 exist in urban areas and 6,090 are from rural areas. Because many of the counties are rural and have small populations, rural areas were oversampled relative to urban areas. Table A.3 Sample allocation of clusters and households Sample allocation of clusters and households by region, according to residence, Liberia 2013 County Allocation of clusters Allocation of households Urban Rural Total Urban Rural Total Bomi 5 12 17 150 360 510 Bong 9 16 25 270 480 750 Gbarpolu 4 14 18 120 420 540 Grand Bassa 7 15 22 210 450 660 Grand Cape Mount 4 16 20 120 480 600 Grand Gedeh 7 12 19 210 360 570 Grand Kru 3 13 16 90 390 480 Lofa 8 15 23 240 450 690 Margibi 9 12 21 270 360 630 Maryland 7 12 19 210 360 570 Montserrado 36 8 44 1,080 240 1,320 Nimba 8 18 26 240 540 780 River Gee 5 11 16 150 330 480 River Cess 2 15 17 60 450 510 Sinoe 5 14 19 150 420 570 Liberia 119 203 322 3,570 6,090 9,660 294 • Appendix A Table A.4 Sample allocation of completed interviews with women and men Sample allocation of expected number of completed interviews with women and men, by county, according to residence, Liberia 2013 Region Women 15-49 Men 15-49 Urban Rural Total Urban Rural Total Bomi 154 308 462 65 134 199 Bong 277 410 687 118 178 296 Gbarpolu 124 359 483 53 156 209 Grand Bassa 216 385 601 92 168 260 Grand Cape Mount 124 410 534 53 178 231 Grand Gedeh 216 308 524 92 134 226 Grand Kru 92 333 425 39 145 184 Lofa 246 385 631 105 168 273 Margibi 277 308 585 118 134 252 Maryland 216 308 524 92 134 226 Montserrado 1,108 205 1,313 473 89 562 Nimba 246 462 708 105 201 306 River Gee 154 282 436 65 123 188 River Cess 62 385 447 26 168 194 Sinoe 154 359 513 65 156 221 Liberia 3,666 5,207 8,873 1,561 2,266 3,827 The allocations presented in Table A.4 were based on the results obtained from LDHS 2007, in which the overall household gross response rate was 91 percent. There were 1.20 women age 15-49 per household in urban areas and 1.00 woman age 15-49 per household in rural areas; the response rate for women was 95 percent for urban areas and 96 percent for rural areas. There were 1.07 men age 15-49 per household in urban areas and 0.87 men age 15-49 per household in rural areas; the response rate for men was 90 percent in urban areas and 95 percent in rural areas. An examination of response rates for the 2013 LDHS indicates that the survey was successfully implemented. Table A.5 and Table A.6 present the interview response rates in the 2013 LDHS for women and men, respectively, by urban and rural area and region. Overall, the number of completed interviews is similar to the expected number for both women and men. The coverage of HIV testing was slightly higher in the 2013 LDHS relative to the 2007 survey. Tables A.7-A.10 present response rates for the HIV testing by background characteristics. A.4 SAMPLE PROBABILITIES AND SAMPLING WEIGHTS Due to the nonproportional allocation of the sample across domains and urban-rural areas, and the differential response rates, sampling weights must be calculated using all analyses of the LDHS results to ensure that survey results are representative at both the national and domain level. Since the LDHS sample is a two-stage stratified cluster sample, sampling weights are based on sampling probabilities calculated separately for each sampling stage and for each cluster where: P1hi: first-stage sampling probability of the ith cluster in stratum h P2hi: second-stage sampling probability within the ith cluster (households) The following describes the calculation of these probabilities: Let ah be the number of clusters selected in stratum h, Mhi the number of households according to the sampling frame in the ith cluster, and M hi∑ the total number of households in the stratum. The probability of selecting the ith cluster in the 2013 LDHS sample is calculated as follows: Appendix A • 295 M M a hi hih ∑ Let hib be the proportion of households in the selected cluster compared with the total number of households in cluster i in stratum h if the cluster is segmented, otherwise 1=hib . Then the probability of selecting cluster i in the sample is: hi hi hih 1hi b M M a = P × ∑ Let hiL be the number of households listed in the household listing operation in cluster i in stratum h, and let hig be the number of households selected in the cluster. The second stage’s selection probability for each household in the cluster is calculated as follows: hi hi hi L gP =2 The overall selection probability of each household in cluster i of stratum h is therefore the product of the two stages of selection probabilities: hihihi PPP 21 ×= The design weight for each household in cluster i of stratum h is the inverse of its overall selection probability: hihi PW /1= Next, the design weight is adjusted for household non-response and individual non-response to get the sampling weights for households and for women and men, respectively. Non-response is adjusted at the sampling stratum level. For the household sampling weight, the household design weight is multiplied by the inverse of the household response rate, by stratum. For the women’s individual sampling weight, the household sampling weight is multiplied by the inverse of the women’s individual response rate, by stratum. For the men’s individual sampling weight, the household sampling weight for the male sub-sample is multiplied by the inverse of the men’s individual response rate, by stratum. After adjusting for non-response, the sampling weights are normalized to get the final standard weights that appear in the data files. The normalization process is done to obtain a total number of un- weighted cases equal to the total number of weighted cases at the national level, for the total number of households, women, and men. Normalization is done by multiplying the sampling weight by the estimated sampling fraction obtained from the survey for the household weight, the individual woman’s weight, and the individual man’s weight. The normalized weights are relative weights that are valid for estimating means, proportions, ratios, and rates, but they are not valid for estimating population totals or pooled data. The sampling weights for HIV testing are calculated in a similar way, but the normalization of the HIV weights is different. The individual HIV testing 296 • Appendix A weights are normalized at the national level for women and men together so that HIV prevalence estimates calculated for women and men together are valid. Table A.5 Sample implementation: Women Percent distribution of households and eligible women by results of the household and individual interviews, and household, eligible women and overall women response rates, according to urban-rural residence and region (unweighted), Liberia 2013 Result Residence Region Total Urban Rural North Western South Central South Eastern A South Eastern B North Central Total urban Greater Monrovia Other urban Selected households Completed (C) 96.5 98.2 95.8 96.4 97.8 98.2 94.1 93.8 96.9 96.4 Household present but no competent respondent at home (HP) 0.1 0.1 0.2 0.2 0.0 0.1 0.4 0.5 0.2 0.2 Refused (R) 0.2 0.2 0.2 0.1 0.0 0.2 0.5 0.1 0.0 0.2 Dwelling not found (DNF) 0.2 0.0 0.3 0.2 0.0 0.0 0.4 0.5 0.2 0.2 Household absent (HA) 1.3 0.4 1.7 1.5 0.7 0.6 3.0 2.4 1.2 1.4 Dwelling vacant/address not a dwelling (DV) 1.1 1.1 1.1 0.8 0.8 0.7 0.6 1.8 0.9 0.9 Dwelling destroyed (DD) 0.5 0.0 0.7 0.7 0.7 0.2 1.0 0.9 0.5 0.6 Other (O) 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.1 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of sampled households 3,576 990 2,586 6,101 1,658 2,609 1,651 1,531 2,228 9,677 Household response rate (HRR)1 99.5 99.7 99.4 99.4 100.0 99.7 98.7 98.9 99.5 99.4 Eligible women Completed (EWC) 97.8 99.0 97.2 97.6 99.2 99.0 95.0 95.7 97.9 97.6 Not at home (EWNH) 1.2 0.2 1.6 1.3 0.3 0.3 3.1 2.5 1.0 1.2 Postponed (EWP) 0.0 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 Refused (EWR) 0.6 0.8 0.5 0.4 0.1 0.4 1.0 0.5 0.3 0.5 Partly completed (EWPC) 0.1 0.0 0.1 0.1 0.0 0.0 0.2 0.2 0.1 0.1 Incapacitated (EWI) 0.3 0.0 0.5 0.3 0.1 0.3