Eritrea - Demographic and Health Survey - 2003

Publication date: 2003

Eritrea Demographic and Health Survey 2002 E r i t r e a 2 0 0 2 D e m o g r a p h i c a n d H e a l t h S u r v e y World Summit for Children Indicators World Summit for Children Indicators by zoba, Eritrea 2002 Zoba Total Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash- Barka Debub Childhood mortality Infant mortality rate (per 1,000 live births) 48 122 39 77 37 66 58 Under-five mortality rate (per 1,000 live births) 93 187 60 154 73 123 111 Percent stunted (children under 5 years) 37.6 37.4 23.0 41.9 40.5 44.8 38.7 Childhood undernutrition Percent wasted (children under 5 years) 12.6 13.8 6.1 18.0 15.6 16.9 9.8 Percent underweight (children under 5 years) 39.6 41.1 23.4 51.2 46.7 49.6 34.6 Clean water supply Percent of households within 15 minutes of safe water supply1 67.4 83.7 91.5 62.6 56.3 70.3 51.9 Sanitary excreta disposal Percent of households with flush toilet, pit toilet/latrine2 25.6 56.7 58.4 24.1 19.2 10.3 10.0 Basic education Proportion entering primary school3 14.4 14.4 39.5 9.2 9.5 7.7 9.4 Net primary school attendance rate3 61.2 52.7 87.5 42.7 53.3 40.4 71.1 Children in especially difficult situations Percent of children who do not live with either biological parent3 5.7 6.6 6.6 4.3 5.3 5.4 5.9 Percent of children with at least one parent dead3 9.8 12.0 11.7 9.8 8.1 12.2 8.0 Percent of children age 10-14 that are working 2.2 9.9 0.8 2.2 1.4 4.3 1.7 Family planning Contraceptive prevalence rate (any method, currently married women) 8.0 7.1 19.6 5.1 4.4 1.9 7.9 Contraceptive prevalence rate (any method, all women) 5.8 6.2 10.5 4.0 3.2 1.8 5.7 Antenatal care Percent of women who received antenatal care from a health professional4 70.4 68.0 89.1 74.1 68.6 64.0 62.1 Delivery care Percent of births in the 5 years preceding the survey attended by a health professional 28.3 41.9 71.9 22.5 15.4 11.0 20.5 Low birth weight Percent of births in the 5 years preceding the survey at low birth weight5 11.3 17.1 9.8 16.4 12.4 7.5 4.8 Iodized salt intake Percent of households that use iodized salt6 68.0 51.0 79.1 48.7 70.2 57.1 75.6 Vitamin A supplements Percent of children age 6-59 months who received a vitamin A dose in the 6 months preceding the survey 38.0 22.1 51.7 36.0 37.3 32.2 35.8 Percent of women age 15-49 who received a vitamin A dose in the 2 months after delivery4 13.4 10.7 25.8 12.7 12.7 11.4 8.0 Night blindness Percent of women age 15-49 who suffered from night blindness during pregnancy4, 7 11.6 19.2 3.4 11.9 9.9 13.7 15.4 Exclusive breastfeeding Percent of children under 6 months who are exclusively breastfed 52.0 26.1 55.7 44.9 58.3 48.8 54.4 Continued breastfeeding Percent of all children age 12-15 months still breastfeeding 91.0 77.3 (85.6) 89.3 90.3 91.6 97.6 Percent of all children age 20-23 months still breastfeeding 58.0 (28.5) (58.7) (54.9) 53.4 (65.2) 60.8 (Continued on inside back cover) World Summit for Children Indicators (Continued from inside front cover) Zoba Total Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash- Barka Debub Timely complementary feeding Percent of children age 6-9 months receiving breast milk and complementary foods 42.5 28.2 62.5 38.3 39.9 34.4 42.8 Vaccinations Percent of children whose mothers received at least 2 tetanus toxoid vaccinations4 34.6 50.0 40.7 37.1 34.6 32.7 29.3 Percent of children age 12-23 months with at least 3 DPT vaccinations 82.8 76.5 95.0 78.8 94.8 73.5 75.8 Percent of children age 12-23 months with at least 3 polio vaccinations 83.3 75.6 91.9 79.8 93.0 75.6 79.0 Percent of children age 12-23 months with measles vaccination 84.2 70.2 96.1 80.3 93.8 75.7 78.7 Percent of children age 12-23 months with BCG vaccination 91.4 90.8 97.9 89.1 97.9 87.1 86.8 Diarrhea control Percent of children with diarrhea in preceding 2 weeks who received ORS or RHF 55.7 47.1 75.8 64.4 51.3 57.7 47.1 Home management of diarrhea Percent of children age 0-59 months with diarrhea in the past 2 weeks who took more fluids than usual and continued eating somewhat less, the same, or more food 30.4 27.1 41.3 29.4 39.9 42.5 20.1 Treatment of ARI Percent of children age 0-59 months with acute respiratory infection (ARI) in past 2 weeks who were taken to a health facility or provider 43.6 41.1 61.5 40.3 32.7 57.2 36.0 Malaria control Percent of children age 0-59 months who slept under an insecticide-treated mosquito net on the previous night8 4.2 2.1 0.7 8.1 4.5 3.0 5.4 Percent of children age 0-59 months with fever in the past 2 weeks who were treated with antimalarial drugs 3.6 0.0 5.8 0.7 4.4 5.6 2.8 HIV/AIDS Percent of women age 15-49 who correctly state two ways of avoiding HIV infection9 51.5 46.3 71.2 29.2 42.4 31.0 61.3 Percent of women age 15-49 who correctly identify two misconceptions about AIDS10 46.3 36.5 72.4 30.8 42.3 24.2 45.9 Percent of women age 15-49 who believe that AIDS can be transmitted from mother to child during pregnancy, delivery, and breastfeeding 60.2 57.8 63.7 54.1 65.9 44.1 67.7 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Piped water or protected well water from covered well or tanker 2 In household or shared with others 3 Based on de jure children 4 For the last live birth in the five years preceding the survey 5 For children without a reported birth weight, the proportion with low birth weight is assumed to be the same as the proportion with low birth weight in each birth size category among children who have a reported birth weight 6 15 parts per million or more 7 Includes women who report night blindness and difficulty with vision during the day 8 Mosquito net bought or treated with insecticide within 6 months before the interview 9 Having sex with only one partner who has no other partners and using a condom every time they have sex 10 They said that AIDS cannot be transmitted through mosquito bites and that a healthy-looking person can have the AIDS virus Eritrea Demographic and Health Survey 2002 National Statistics and Evaluation Office Asmara, Eritrea ORC Macro Calverton, Maryland, USA May 2003 National Statistics and Evaluation Office ORC Macro This report summarizes the findings of the 2002 Eritrea Demographic and Health Survey (EDHS) carried out by the National Statistics and Evaluation Office. Financial support for the survey was provided by the U.S. Agency for International Development (USAID) and the Ministry of Health through the Technical Assistance and Support Contract (TASC) with John Snow, Inc. ORC Macro provided technical assistance for the survey through the USAID-funded MEASURE DHS+ project, which is designed to assist developing countries to collect data on fertility, family planning, and maternal and child health. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Agency for International Development. Additional information about the EDHS may be obtained from the National Statistics and Evaluation Office P.O. Box 5838, Asmara, Eritrea (telephone: 291-1-202940/119507; e-mail: seo12@eol.com.er). Additional information about the MEASURE DHS+ project may be obtained by contacting: MEASURE DHS+, ORC Macro, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705 (telephone: 301-572-0200; fax: 301-572-0999; e-mail: reports@orcmacro.com; internet: www.measuredhs.com). Suggested citation: National Statistics and Evaluation Office (NSEO) [Eritrea] and ORC Macro. 2003. Eritrea Demographic and Health Survey 2002. Calverton, Maryland, USA: National Statistics and Evaluation Office and ORC Macro. Contents | iii CONTENTS Contents. iii Tables and Figures . vii Preface . xiii Summary of Findings . xv Map of Eritrea. xxii CHAPTER 1 INTRODUCTION 1.1 Geography, History, and the Economy.1 1.2 Population.2 1.3 Health Services and Programs.3 1.4 Objectives of the Survey .5 1.5 Organization of the Survey .5 1.6 Sample Design.5 1.7 Questionnaires .6 1.9 Data Processing .7 1.10 Coverage and Response Rates.7 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS 2.1 Household Population by Age, Residence, and Sex .9 2.2 Household Composition .11 2.3 Fosterhood And Orphanhood.12 2.4 Education Levels of the Household Population .14 2.5 Marital Status.20 2.6 Employment Status of Household Population .22 2.7 Housing Characteristics.24 2.8 Household Possessions .28 2.9 Mosquito Nets .29 CHAPTER 3 WOMEN’S CHARACTERISTICS AND STATUS 3.1 Characteristics of Survey Respondents .31 3.2 Women’s Migration .33 3.3 Educational Attainment by Background Characteristics .36 3.4 Reasons for Leaving School.39 3.5 Access to Mass Media .40 3.6 Employment Status .42 3.7 Occupation .44 3.8 Earnings, Employers and Continuity of Employment.44 3.9 Child Care While Working.48 3.10 Decision on Use of Earnings .49 3.11 Measures of Women’s Empowerment.51 iv | Contents CHAPTER 4 FERTILITY 4.1 Current Fertility .55 4.2 Fertility Differentials.58 4.3 Fertility Trends.59 4.4 Children Ever Born and Living .61 4.5 Birth Intervals .63 4.6 Age at First Birth .65 4.7 Adolescent Fertility .66 CHAPTER 5 FERTILITY REGULATION 5.1 Knowledge of Contraceptive Methods and Sources.71 5.2 Exposure to Family Planning Information .75 5.3 Acceptability of Use of Electronic Media to Disseminate Family Planning Messages .77 5.4 Interpersonal Communication About Family Planning.79 5.5 Attitudes of Couples Toward Family Planning .80 5.6 Ever Use of Contraceptive Methods .83 5.7 Current Use of Contraceptive Methods.84 5.8 Source of Modern Family Planning Methods.89 5.9 Reasons for Nonuse of Contraception .90 5.10 Intention to Use Family Planning Among Nonusers .92 5.11 Reasons for Not Intending to Use a Contraceptive Method in the Future .92 5.12 Preferred Method of Contraception for Future Use .93 5.13 Contact of Nonusers with Health Care Providers.94 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6.1 Current Marital Status .97 6.2 Polygyny.98 6.3 Age at First Marriage . 100 6.4 Median Age at First Marriage . 101 6.5 Age at First Sexual Intercourse . 102 6.6 Median Age at First Intercourse. 102 6.7 Recent Sexual Activity. 103 6.8 Postpartum Amenorrhea, Abstinence, and Insusceptibility . 105 6.9 Median Duration of Postpartum Insusceptibility by Background Characteristics. 106 6.10 Menopause . 108 CHAPTER 7 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING 7.1 Reproductive Preferences . 109 7.2 Desire To Limit Childbearing by Background Characteristics . 110 7.3 Need for Family Planning Services . 111 7.4 Ideal Family Size. 113 7.5 Ideal Family Size, Unmet Need, and Status of Women . 115 7.6 Fertility Planning . 116 Contents | v 7.7 Attitudes toward Unplanned Pregnancy. 119 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Assessment of Data Quality. 121 8.2 Early Childhood Mortality Rates: Levels and Trends . 122 8.3 Differentials in Mortality . 123 8.4 Early Childhood Mortality by Women’s Status. 127 8.5 High-Risk Fertility Behavior. 128 CHAPTER 9 MATERNAL AND CHILD HEALTH 9.1 Pregnancy Care . 131 9.2 Delivery Care . 136 9.3 Postnatal Care . 142 9.4 Reproductive Health Care by Women’s Status. 142 9.5 Use of Mosquito Nets by Women. 144 9.6 Childhood Vaccination . 146 9.7 Acute Respiratory Infections . 149 9.8 Fever . 151 9.9 Diarrheal Diseases . 151 9.10 Women’s Status and Child Health Care . 156 9.11 Use of Mosquito Nets by Children . 158 9.12 Women’s Perception of Problems in Accessing Health Care. 158 CHAPTER 10 INFANT FEEDING AND NUTRITIONAL STATUS OF CHILDREN AND WOMEN 10.1 Breastfeeding and Complementary Feeding . 161 10.2 Age Pattern of Breastfeeding . 163 10.3 Duration and Frequency of Breastfeeding . 164 10.4 Types of Complementary Foods Consumed. 166 10.5 Frequency of Foods Consumed by Children in the Past Day and Night . 167 10.6 Frequency of Foods Consumed by Children in the Past Seven Days. 169 10.7 Micronutrient Supplementation . 171 10.8 Nutritional Status of Children under Age Five. 176 10.9 Nutritional Status of Women . 182 CHAPTER 11 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS 11.1 Knowledge of HIV/AIDS and Its Prevention. 186 11.2 Knowledge of Other AIDS-Related Issues. 189 11.3 Social Aspects of HIV/AIDS Prevention and Mitigation . 191 11.4 Knowledge of Signs and Symptoms of Sexually Transmitted Infections . 194 11.5 Knowledge of Source and Use of Condoms . 195 CHAPTER 12 FEMALE CIRCUMCISION 12.1 Circumcision of EDHS Respondents. 197 vi | Contents 12.2 Circumcision Experience of Daughters. 201 12.3 Objections to Daughter’s Circumcision . 204 12.4 Attitudes Toward Female Circumcision . 206 12.5 Women’s Perceptions of Their Husband’s Attitude Toward Female Circumcision . 208 12.6 Perceived Benefits of Female Circumcision . 208 12.7 Perceived Benefits of Girls Not Being Circumcised. 211 12.8 Beliefs about Circumcision. 213 12.9 Problems Associated with Female Circumcision . 214 References . 217 Appendix A SAMPLE DESIGN . 219 Appendix B SAMPLING ERRORS . 225 Appendix C DATA QUALITY TABLES . 239 Appendix D SURVEY PERSONNEL. 245 Appendix E QUESTIONNAIRES . 251 Tables and Figures | vii TABLES AND FIGURES CHAPTER 1 INTRODUCTION Table 1.1 Results of the household and individual interviews and response rates.7 Table 1.2 Sample implementation.8 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS Table 2.1 Household population by age, residence and sex .10 Table 2.2 Household composition according to residence and zoba.12 Table 2.3 Children’s living arrangements and orphanhood .13 Table 2.4 Educational attainment of the household population .15 Table 2.5.1 Primary school attendance ratios .16 Table 2.5.2 Middle school attendance ratios .17 Table 2.5.3 Secondary school attendance ratios .18 Table 2.6 Marital status of the de facto household population .21 Table 2.7.1 Employment status: women.22 Table 2.7.2 Employment status: men .23 Table 2.8 Household characteristics .25 Table 2.9 Household durable goods.28 Table 2.10 Household ownership of a house, animals and cropland.29 Table 2.11 Household possession of mosquito nets .30 Figure 2.1 Population Pyramid .10 Figure 2.2 Distribution of DeFacto Household Population by Single Year of Age and Sex .11 Figure 2.3 Age Specific Attendance Rates .19 Figure 2.4 Access to Clean Water .27 CHAPTER 3 WOMEN’S CHARACTERISTICS AND STATUS Table 3.1 Background characteristics of respondents .32 Table 3.2 Reasons for migration by background characteristics .34 Table 3.3 Reasons for migration by type of migration .35 Table 3.4 Zoba in-migration and out-migration, and immigration from abroad.35 Table 3.5 Educational attainment by background characteristics.37 Table 3.6 Reason for leaving school by zoba .39 Table 3.7 Exposure to mass media .41 Table 3.8 Employment status.43 Table 3.9 Occupation .45 Table 3.10 Employment characteristics.46 Table 3.11 Childcare while working .48 Table 3.12 Decision on use of earnings .50 Table 3.13 Women’s participation in decisionmaking .51 Table 3.14 Women’s participation in decisionmaking by background characteristics .52 Table 3.15 Women’s attitude toward wife beating .54 viii | Tables and Figures Figure 3.1 In-Migration and Out-Migration by Zoba .36 Figure 3.2 Employment Status of Women.42 Figure 3.3 Type of Earnings Among Employed Women .47 Figure 3.4 Type of Employer Among Employed Women .47 CHAPTER 4 FERTILITY Table 4.1 Current fertility .56 Table 4.2 Fertility by background characteristics.58 Table 4.3 Trends in fertility.60 Table 4.4 Trends in age-specific fertility rates .61 Table 4.5 Children ever born and living.62 Table 4.6 Birth intervals.64 Table 4.7 Age at first birth .65 Table 4.8 Median age at first birth by background characteristics.66 Table 4.9 Teenage pregnancy and motherhood .68 Figure 4.1 Total Fertility Rates, Etritrea Compared with Other Sub-Saharan Countries .56 Figure 4.2 Age-Specific Fertility Rates by Residence.57 Figure 4.3 Total Fertility Rates by Background Characteristics .59 Figure 4.4 Trends in Age-Specific Fertility Rates.60 Figure 4.5 Trends in Adolescent Fertility by Age and Residence.69 CHAPTER 5 FERTILITY REGULATION Table 5.1 Knowledge of contraceptive methods .72 Table 5.2 Knowledge of fertile period.73 Table 5.3 Knowledge of contraceptive methods by background characteristics.74 Table 5.4 Exposure to family planning messages.76 Table 5.5 Acceptability of media messages on family planning .78 Table 5.6 Discussion of family planning with husband.80 Table 5.7 Discussion of family planning with persons other than husband .81 Table 5.8 Attitudes toward family planning.82 Table 5.9 Ever use of contraception .84 Table 5.10 Current use of contraception .85 Table 5.11 Current use of contraception by background characteristics .86 Table 5.12 Current use of contraception by women's status.88 Table 5.13 Number of children at first use of contraception .88 Table 5.14 Source of contraception.90 Table 5.15 Reasons for not using family planning .91 Table 5.16 Future use of contraception .92 Table 5.17 Reasons for not intending to use contraception in the future.93 Table 5.18 Preferred method of contraception for future use .94 Table 5.19 Contact of nonusers with family planning providers .95 Figure 5.1 Trends in Knowledge of Family Planning Methods Among Currently Married Women, 1995 EDHS and 2002 EDHS.73 Tables and Figures | ix Figure 5.2 Exposure to Family Planning Messages on Radio, Women Age 15-49, 1995 EDHS and 2002 EDHS .77 Figure 5.3 Trends in Acceptability of Family Planning Messages on Radio, Women Age 15-49 Years, 1995 EDHS and 2002 EDHS.79 Figure 5.4 Trends in Approval of Family Planning, Women Age 15-49, 1995 EDHS and 2002 EDHS .83 Figure 5.5 Contraceptive Use by Background Characteristics, Currently Married Women 15-49 .87 Figure 5.6 Distribution of Current Users of Modern Contraceptive Methods by Source of Supply .89 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status.97 Table 6.2 Number of co-wives .99 Table 6.3 Age at first marriage . 100 Table 6.4 Median age at first marriage. 101 Table 6.5 Age at first sexual intercourse. 102 Table 6.6 Median age at first sexual intercourse . 103 Table 6.7 Recent sexual activity. 104 Table 6.8 Postpartum amenorrhea, abstinence and insusceptibility . 106 Table 6.9 Median duration of postpartum insusceptibility by background characteristics . 107 Table 6.10 Menopause . 108 Figure 6.1 Current Marital Status .98 Figure 6.2 Median Duration of Postpartum Insusceptibility by Background Characteristics. 108 CHAPTER 7 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING Table 7.1 Fertility preferences by number of living children. 109 Table 7.2 Desire to limit childbearing by background characteristics . 111 Table 7.3 Need for family planning . 112 Table 7.4 Ideal number of children . 114 Table 7.5 Mean ideal number of children by background characteristics . 115 Table 7.6 Ideal number of children and unmet need by women’s status. 116 Table 7.7 Fertility planning status . 117 Table 7.8 Wanted fertility rates . 118 Table 7.9 Attitudes of nonusers toward mistimed and unwanted pregnancies. 120 Figure 7.1 Fertility Preferences of Currently Married Women . 110 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates. 123 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 125 Table 8.3 Early childhood mortality rates by demographic characteristics . 126 Table 8.4 Early childhood mortality rates by women’s status indicators. 128 Table 8.5 High-risk fertility behavior. 129 x | Tables and Figures Figure 8.1 Trends in Childhood Mortality . 124 Figure 8.2 Under-five Mortality by Background Characteristics . 125 CHAPTER 9 MATERNAL AND CHILD HEALTH Table 9.1 Antenatal care . 132 Table 9.2 Number of antenatal care visits and timing of first visit . 134 Table 9.3 Components of antenatal care . 135 Table 9.4 Tetanus toxoid injections . 137 Table 9.5 Place of delivery . 139 Table 9.6 Assistance during delivery . 140 Table 9.7 Delivery characteristics . 141 Table 9.8 Postnatal care by background characteristics. 143 Table 9.9 Reproductive health care by women’s status. 144 Table 9.10 Use of mosquito nets by all women and pregnant women . 145 Table 9.11 Vaccinations by source of information . 147 Table 9.12 Vaccinations by background characteristics. 148 Table 9.13 Prevalence and treatment of symptoms of acute respiratory infection (ARI) . 150 Table 9.14 Prevalence and treatment of fever . 152 Table 9.15 Prevalence of diarrhea . 153 Table 9.16 Knowledge of ORS packets . 154 Table 9.17 Diarrhea treatment . 155 Table 9.18 Children’s health care by women’s status. 157 Table 9.19 Use of mosquito nets by children. 158 Table 9.20 Problems in accessing health care . 159 Figure 9.1 Percentage of Children Age 12-23 Months Who Have Received Specific Vaccinations, 1995 EDHS and 2002 EDHS. 147 Figure 9.2 Feeding Practices During Diarrhea Compared to Normal Practice. 156 CHAPTER 10 INFANT FEEDING AND NUTRITIONAL STATUS OF CHILDREN AND WOMEN Table 10.1 Initial breastfeeding . 162 Table 10.2 Breastfeeding status by child’s age . 164 Table 10.3 Median duration of breastfeeding . 165 Table 10.4 Foods consumed by children in the day or night preceding the interview . 166 Table 10.5 Frequency of foods consumed by children in the day and night preceding the interview . 168 Table 10.6 Frequency of foods consumed by children in preceding seven days . 170 Table 10.7 Iodization of household salt . 172 Table 10.8 Micronutrient intake among children . 173 Table 10.9 Micronutrient intake among mothers . 175 Table 10.10 Nutritional status of children by child’s characteristics . 179 Table 10.11 Nutritional status of children by mother’s characteristics . 180 Table 10.12 Nutritional status of women by background characteristics. 183 Tables and Figures | xi Figure 10.1 Frequency of Meals Consumed by Children Under 36 Months of Age Living with Their Mother. 169 Figure 10.2 Nutritional Status of Children Under Age Five. 178 Figure 10.3 Percentage of Children Under Age Five that Are Underweight (weight-for-age below -2 SD) by Background Characteristics . 181 Figure 10.4 Trends in Levels of Undernutrition among Children Under Age Three, 1995 and 2002. 182 Figure 10.5 Percentage of Women Age 15-49 with Low Body Mass Index (BMI < 18.5) by Background Characteristics . 184 CHAPTER 11 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Table 11.1 Knowledge of HIV/AIDS . 186 Table 11.2 Knowledge of ways to avoid HIV/AIDS . 187 Table 11.3 Knowledge of programmatically important ways to avoid HIV/AIDS. 188 Table 11.4 Knowledge of HIV/AIDS-related issues. 190 Table 11.5 Discussion of HIV/AIDS with partner . 192 Table 11.6 Social aspects of HIV/AIDS . 193 Table 11.7 Knowledge of symptoms of STIs. 195 Table 11.8 Knowledge of source and use of condoms . 196 Figure 11.1 Percentage of Women Who Know at Least Two Programatically Important Ways to Avoid HIV/AIDS, by Zoba and Education . 189 Figure 11.2 Percentage of Women Who Know at Least One Symptom of Sexually Transmitted Infections (STIs) in Men . 194 CHAPTER 12 FEMALE CIRCUMCISION Table 12.1 Knowledge and prevalence of female circumcision . 198 Table 12.2 Age at circumcision . 200 Table 12.3 Person who performed female circumcision . 201 Table 12.4 Daughter’s circumcision experience and type of circumcision. 202 Table 12.5 Person who performed daughter’s circumcision. 204 Table 12.6 Objections to daughter’s circumcision . 205 Table 12.7 Attitudes toward female circumcision by background characteristics . 207 Table 12.8 Women’s perception of their husband’s attitude toward circumcision. 209 Table 12.9 Perceived benefits of female circumcision. 210 Table 12.10 Perceived benefits of not undergoing female circumcision . 212 Table 12.11 Beliefs about female circumcision . 214 Table 12.12 Problems associated with female circumcision . 215 Figure 12.1 Distribution of Circumcised Women by Type of Circumcision . 199 Figure 12.2 Daughter’s Age at Circumcision . 203 Figure 12.3 Perceived Benefits of Female Circumcision . 211 Figure 12.4 Perceived Benefits of Not Undergoing Female Circumcision . 213 xii | Tables and Figures APPENDIX A SAMPLE DESIGN Table A.1 Proportional and square root allocations of clusters. 220 Table A.2 Expected number of selected households to reach the target of completed interviews . 220 Table A.3 Final allocation of women 15-49 with completed interviews and clusters in each zoba. 220 Table A.4 Sample implementation. 223 APPENDIX B SAMPLING ERRORS Table B.1 List of selected variables for sampling errors . 227 Table B.2 Sampling errors for selected variables, total sample . 228 Table B.3 Sampling errors for selected variables, urban sample. 229 Table B.4 Sampling errors for selected variables, Asmara sample . 230 Table B.5 Sampling errors for selected variables, other towns sample . 231 Table B.6 Sampling errors for selected variables, rural sample. 232 Table B.7 Sampling errors for selected variables, zoba Debubawi Keih Bahri sample . 233 Table B.8 Sampling errors for selected variables, zoba Maekel sample . 234 Table B.9 Sampling errors for selected variables, Zoba Semenawi Keih Bahri sample. 235 Table B.10 Sampling errors for selected variables, zoba Anseba sample . 236 Table B.11 Sampling errors for selected variables, zoba Gash-Barka sample. 237 Table B.12 Sampling errors for selected variables, zoba Debub sample. 238 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution. 239 Table C.2 Age distribution of eligible and interviewed women. 240 Table C.3 Completeness of reporting . 240 Table C.4 Births by calendar years . 241 Table C.5 Reporting of age at death in days . 242 Table C.6 Reporting of age at death in months . 243 Preface | xiii PREFACE The 2002 Eritrea Demographic and Health Survey (EDHS) is the second National Demographic and Health Survey (DHS) in the series that started in 1995. The National Statistics and Evaluation Office (NSEO), Office of the President conducted the survey under the aegis of the Ministry of Health (MOH). ORC Macro furnished technical assistance to the survey as part of the MEASURE DHS+ program, while funding was provided by the U.S Agency for International Development (USAID). The United Nations Population Fund (UNFPA) and the Canada International Development Agency (CIDA) supported the survey by supplying 20 field vehicles. The fieldwork for the 2002 EDHS was carried out between the last week of March and the first week of July 2002. The major objective of this survey, similar to the first survey, was to collect and analyze data on fertility, mortality, family planning, and health. Compared with the 1995 EDHS, the present survey was expanded in scope to include a malaria module and questions on gender issues. Moreover, geographic coordinates were taken for the selected sample points to allow analysis based on the geographic information system (GIS). Thus, the 2002 EDHS will not only update the information from the 1995 EDHS, but also will provide findings on some new topics of interest. The findings of the 2002 EDHS presented in this report provide up-to-date and reliable information on a number of key topics of interest to planners, policymakers, program managers, and researchers that will guide the planning, implementation, monitoring, and evaluation of population and health programs in Eritrea. In addition to the estimates at the national level, estimates for key indicators relating to fertility, mortality, and health are provided for all six zobas and for urban and rural areas. The 2002 EDHS results present evidence of a decline in fertility and early childhood mortality as well as a substantial increase in the level of child immunization coverage since the 1995 EDHS survey. Knowledge of HIV/AIDS remains high in Eritrea. There is, however, still a wide gap between knowledge and use of family planning. The National Statistics and Evaluation Office (NSEO) acknowledges the efforts of a number of organizations and individuals who contributed immensely to the successful completion of the 2002 EDHS and the timely publication of this report. NSEO is particularly thankful to USAID for funding the survey, to ORC Macro for providing technical assistance, and to UNFPA and CIDA for supporting field vehicles. The office would like to express its gratitude to the Ministry of Health (MOH) for close cooperation in the whole operation and for their significant technical and logistical inputs. The office is grateful for the endeavors of government officials at all levels of administration that supported the survey. High appreciation and commendation go to all the 2002 EDHS field personnel for commitment to high-quality work in difficult working conditions. We acknowledge with gratitude the NSEO staff, who made the survey successful through commitment and a spirit of team work. Last but not least, special gratitude goes to all of the respondents who generously gave their valuable time to provide information that forms the basis of this report Dr. Georgis Teclemichael National Statistics and Evaluation Office (Head) May 2003 Summary of Findings | xv SUMMARY OF FINDINGS The 2002 Eritrea Demographic and Health Sur- vey (2002 EDHS) is a nationally representative sample survey covering 9,389 households and 8,754 women age 15-49. The survey provides up-to-date information on fertility, early childhood mortality, fertility pref- erences, knowledge and use of family planning, maternal and child health and nutrition, aware- ness and behavior regarding HIV/AIDS and other sexually transmitted infections, malaria control program indicators, and female genital cutting (female circumcision). It was designed as follow- on to the 1995 EDHS survey. As most of the in- formation collected in the two surveys is similar, it is possible to examine trends in the different indicators over the intervening period of six and a half years. The major findings are considered at the national level, by urban-rural residence, and by region (the six zobas). The National Statistics and Evaluation Office (NSEO) was responsible for implementing the survey. Fourteen survey teams conducted inter- views from the last week of March to the first week of July 2002. FERTILITY Fertility Trends: Fertility has declined sharply since 1995; the total fertility rate has dropped from 6.1 children per woman to 4.8 children, a decline of 21 percent. Because of this decline, at current fertility levels, the average Eritrean woman will give birth to five children instead of six children by the end of her reproductive years. The decline is more rapid among rural women and younger women (below age 35), and is most notable among adolescents (15-19). Fertility Differentials: Similar to the pattern that exists in all sub-Saharan countries, fertility among urban women in Eritrea is substantially lower than fertility among rural women. The total fertility rate among rural women is 5.7 children per women, compared with 3.2 children in urban areas. By zoba, fertility ranges from a high of 5.7 children per woman in zoba Debub to a low of 3.4 children in zoba Maekel. Fertility levels are related to various socioeco- nomic characteristics of women. Education, for example, has a negative relationship with fertil- ity. The total fertility rate decreases from 5.5 children among women with no education to 3.1 children among women who have at least some secondary education. Birth Intervals: The length of interval between births influences overall fertility, as well as the health status of mother and child. The interval between births in Eritrea has increased from 31.3 months in 1995 to 33.6 months in 2002. The op- timal interval between births is at least 36 months. In Eritrea, 43 percent of births occur with the optimal birth interval, compared with 35 percent in 1995. Nuptiality: Women’s age at marriage has been increasing. For example, the proportion of women age 15-19 still single has increased from 62 percent in1995, to 69 percent in 2002. In 1995, almost six in ten women were married by age 18, compared with less than half in 2002. These results indicate that the rising age at mar- riage is an important factor in fertility decline in Ertirea. The proportion of never-married women who reported that they had sex in the year before the survey is less than 3 percent. Childbearing at Young Ages: Fourteen percent of adolescent women (15-19) are either already mothers (11 percent) or are currently pregnant with their first child (3 percent). The rate for ado- lescent women has declined substantially since 1995 (23 percent). The decline is mainly attribut- able to lower teenage childbearing among rural women. In 1995, one in three rural teenagers had started childbearing, compared with one in five in 2002, a decline of more than 40 percent. xvi | Summary of Findings Unplanned Fertility: The 2002 EDHS data indi- cate that one-fourth of all births in the five years preceding the survey were unplanned; 6 percent were unwanted and 20 percent were mistimed (wanted later). The proportion of mistimed births has increased from 14 percent in the 1995 EDHS to 20 percent in 2002, while the proportion of unwanted births increased only slightly from 5 percent to 6 percent. If all births associated with unwanted pregnancy were avoided, the total fer- tility rate in Eritrea would be 4.4 children per woman, which is roughly one-half child lower than the observed total fertility rate. Ideal Family Size: Eritrean women want to have large families; the mean ideal number of children for all women is 5.8. Overall, only one in ten women wants less than four children, while more than one-fourth want seven or more. One in ten women considers 10 or more children to be the ideal family size. FAMILY PLANNING Knowledge of Family Planning Methods: Al- most nine in ten women know of at least one modern method of family planning. The pill, male condoms, and injectables are the most widely known modern methods among all sub- groups. Knowledge of family planning methods has increased since 1995. The mean number of methods known by all women increased by al- most two methods from 2.6 in 1995 to 4.4. in 2002. Mass media are important sources of information on family planning. A majority of women (55 percent) heard or saw a family planning message on the radio, on television, in a newspaper/ magazine, or on a poster in the 12 months before the survey. Half of all women have heard a fam- ily planning message on the radio, which is the major medium for all subgroups. Women’s expo- sure to all other media is much lower. Nineteen percent of women reported seeing a family plan- ning message on television, and the same propor- tion saw a family planning message on a poster. Only 16 percent saw a family planning message in newspapers or magazines. Trends in Contraceptive Use: Contraceptive use remains low in Eritrea; there has been no increase since 1995. The 2002 EDHS results show that only 8 percent of currently married women re- ported using contraception at the time of the sur- vey, with 5 percent depending on modern meth- ods and 3 percent relying on traditional methods. Currently, the most widely used methods among married women are injectables (3 percent), lacta- tional amenorrhea method (LAM) (2 percent), and the pill (1 percent). Differentials in Family Planning Use: There are marked differences by background characteristics in current use of family planning methods among currently married women. Urban women are more than four times as likely to use a method of contraception as rural women (17 versus 4 per- cent). Among zobas, use of contraception is high- est in zoba Maekel (20 percent) and lowest in zoba Gash-Barka (2 percent). One-fifth of women with some secondary education reported using a method, compared with only 4 percent of women with no education. Source of Family Planning Methods: The sur- vey results show that public facilities remain the major source for modern contraceptive methods in Eritrea, providing family planning methods to nearly three-fourths (74 percent) of current users. Fifteen percent of users get their methods from private medical sources, and 8 percent get their methods from other private sources (mainly shops). As in 1995, three-fourth of pill users and more than 90 percent of users of injectables rely on the public sector. The Family Reproductive Health Association of Eritrea (previously the Planned Parenthood Federation of Eritrea) remains the major source for pills, while government hospi- tals are the predominant source for injectables users. Unmet Need for Family Planning: Currently married women who either do not want any more children or want to wait two or more years before having another child, and are not using contra- ception, are considered to have an unmet need for family planning. The total unmet need for family planning in Eritrea is 27 percent — 21 percent for Summary of Findings | xvii spacing and 6 percent for limiting births. Because unmet need has remained unchanged since 1995, no progress has been made in satisfying women’s need for family planning. Among currently mar- ried women, less than one-fourth of the total de- mand for family planning is being satisfied. CHILD HEALTH AND SURVIVAL Early Childhood Mortality: The 2002 EDHS data indicate that early childhood mortality in Eritrea has declined sharply since 1995. The in- fant mortality rate has declined from 72 per 1000 live births in the 1995 EDHS survey (1991-1995) to 48 in the 2002 EDHS survey (1997-2001). The under-five mortality rate was 136 per 1000 live births in the period 1991-1995, compared with 93 per 1000 for the period 1997-2001. Factors that have contributed to the decline in child mortality are increasing urbanization, major gains in child immunization, improved nutrition and increasing education among women. Marked differentials in early childhood mortality exist in Eritrea. Infant mortality ranges from a low of 37 deaths per 1,000 live births in zoba An- seba to a high of 122 in zoba Debubawi Keih Bahri. Living in rural areas, low maternal educa- tion, and young age of mothers at birth are factors associated with higher infant and childhood mor- tality. Vaccination Coverage: The 2002 EDHS results show that three-fourths of children age 12-23 months are fully vacinated. This represents a sub- stantial increase from the 41 percent fully vacci- nated in 1995. Although urban children are more likely to be fully vaccinated, the urban-rural gap has narrowed. It is encouraging to note that the proportion of fully vaccinated children among uneducated mothers has doubled since 1995. Zoba Anseba (92 percent) has the highest propor- tion of children fully immunized and zoba De- bubawi Keih Bahri has the lowest (60 percent). Childhood Illnesses: The survey provides data on some of the more common childhood illnesses and their treatment. One in five children under five had a cough accompanied by short, rapid breathing—signs of acute respiratory infection (ARI)—in the two weeks before the survey. Of these, 44 percent were taken to a health facility for treatment. Thirteen percent of children under age five were reported to had experienced diar- rhea some time in the two weeks preceding the survey. Overall, more than two-thirds of these children received some type of oral rehydration therapy, i.e., solution prepared from packets of oral rehydration salts (ORS), homemade sugar- salt water solution, or increased fluids. Although almost all mothers who had a birth in the five years preceding the survey reported knowing about ORS packets, only 45 percent of children with diarrhea received ORS. Breastfeeding Practices: The 2002 EDHS data indicate that almost all children under one year of age are breastfed. Despite the universal preva- lence of breastfeeding of newborns in Eritrea, the majority of infants are not fed in compliance with WHO/UNICEF recommendations. Exclusive breastfeeding is common but not universal in early infancy in Eritrea. The prevalence of exclu- sive breastfeeding would be higher except for the early supplementation of breast milk with plain water. Overall, the median duration of any breast- feeding is 22 months; the median duration of ex- clusive breastfeeding is 2.5 months. Patterns of Feeding in Early Childhood: Dur- ing the period when complementary foods should be introduced, at age 6-9 months, only 54 percent of Eritrean infants in this age group received solid or semi-solid foods the day and night pre- ceding the survey and the variety of foods given was limited. These children mainly received foods made from grain and milk, (cheese or yo- gurt), and to a lesser extent received animal prod- ucts (meats, poultry, fish, or eggs), and fruits and vegetables, and infant formula. Micronutrient Supplements: The 2002 EDHS data show that only 38 percent of children age 6- 59 months received a vitamin A supplement in the six months preceding the survey. The survey also measured the iodine content of salt used in the household. The results show that over two- thirds (68 percent) of children under age five live in households that use adequately iodized salt. Nutritional Status of Children: Overall, 38 per- cent of children under age five are chronically xviii | Summary of Findings malnourished or stunted (short for their age), 13 percent are wasted (thin for their height), and 40 percent are underweight (low weight-for-age). Rural children are more than one and a half times as likely to be stunted and wasted as urban chil- dren. Among zobas, malnutrition is more preva- lent in Gash-Barka, Anseba, and Semenawi Keih Bahri than in other zobas. The prevalence of se- vere malnutrition among children in these zobas is also higher than in other zobas. A comparison of children under three years in 1995 and 2002 indicates a slight improvement in the nutritional status. WOMEN’S HEALTH Maternal Health: The 2002 EDHS findings in- dicate that there has been a substantial improve- ment in antenatal care coverage since 1995. Seven in ten women with births in the five years before the survey received antenatal care services for the last birth from a health professional (doc- tor, trained nurse, midwife or auxiliary midwife), compared with only half of mothers in 1995. Forty-one percent of women with a birth in the five years preceding the survey had four or more antenatal care visit, though only 22 percent made the first visit in the first trimester. Half of women who had a live birth in the five years preceding the survey received at least one tetanus toxoid injection during pregnancy for the most recent birth; 32 percent received multivitamin or vita- min C tablets. Four in ten mothers received iron tablets for the last birth in the five years preced- ing the survey but almost all took the tablets for less than 60 days. Delivery under hygienic conditions and where medical assistance is available decreases the risk of maternal morbidity and mortality. Overall, one-fourth of births—compared with 17 percent in 1995—occurred in health facilities, almost all of them public facilities. More than nine in ten women with deliveries outside health facilities do not receive any postnatal checkup. Three percent of births in the five years preceding the survey were delivered by caesarean section (C-section), indicating a slight increase from 1995. A C-section rate below 5 percent is gener- ally thought to be a reflection of limited access to maternal health services and potentially life- saving emergency obstetrical care. Female Genital Cutting: Results from the 2002 EDHS show that knowledge of female circumci- sion is universal among Eritrean women, with almost all respondents (99 percent) having heard of female genital cutting. Nine in ten women (89 percent) reported that they had been circumcised, indicating a slight decline in the proportion of women circumcised in 1995 (95 percent). Among circumcised women, 39 percent had their vaginal area sewn closed (the most severe form of cir- cumcision), 4 percent had some flesh removed, and 46 percent were nicked and no flesh was re- moved. Younger women (age 15-19) are less likely to be circumcised than older women. Sixty- three percent of women with living daughters indicated that at least one daughter was circum- cised. Attitudes of Eritrean women toward female cir- cumcision are evenly divided: the proportion of women who support continuation of the practice is the same as the proportion who want it to be discontinued (49 percent). As expected, women who are not circumcised are more likely to want the practice discontinued (86 percent) than those who are circumcised (44 percent). Seven percent of circumcised women say they have had prob- lems during sexual relations; one in ten reported having problems during delivery and one in twenty-five reported problems during both sexual relations and delivery. Constraints to Use of Health Services: Many different factors can be barriers to women seek- ing health care for themselves. Seventy-two per- cent of women reported at least one issue or cir- cumstance they regarded as a big problem in seeking health care. The major constraints to women’s access to health services are lack of money, distance to health facilities, and having to take transportation. Almost four in ten women mentioned the problem of waiting in line at the health facility as a big problem. Eleven percent of women in Eritrea do not know where to go for health care. Nutritional Status of Women: The 2002 EDHS collected information on the height and weight of Summary of Findings | xix all women age 15-49. Overall, 2 percent of women are shorter than 145 cm, the cutoff point below which a woman is identified as at risk of delivering a baby with low birth weight. The findings also indicate that more than half of women age 15-49 have a body mass index (BMI)—a measure of a woman’s weight relative to her height—in the normal range, and 37 per- cent have a low BMI (less than 18.5), indicating chronic energy deficiency. Rural women and women with no education are more likely to have a low BMI than urban women and women with some education. In addition, 9 percent of Eritrean women are overweight, including 2 percent that are severely overweight or obese. WOMEN’S CHARACTERISTICS AND STATUS Residence and Education: Almost six in ten (57 percent) of the survey respondents live in rural areas. Over half of women age six and over have never been to school. Women’s Migration: More than half of women in Eritrea can be considered migrants because they are not living in the area in which they were born. Women’s Status and Empowerment: Only one in five women is currently working. Two-thirds (65 percent) of these women work for cash. Nearly three-fourths (73 percent) of working women who receive cash earnings report that they are solely responsible for decisions on the use of their earnings. To assess women’s attitudes toward wife beating, women interviewed in the EDHS were asked whether a husband would be justified in beating his wife for specific reasons. Seven in ten women believe that a husband is justified in beating his wife for at least one of the reasons. MALARIA CONTROL PROGRAM INDICATORS Mosquito nets: The use of insecticide-treated mosquito nets has been proven to reduce malaria transmission. The 2002 EDHS found that 34 per- cent of households owned at least one mosquito net. Possession of mosquito nets is more common in rural areas (37 percent) than urban areas (28 percent), but it is most common in small towns (45 percent). Mosquito nets are least prevalent in zoba Maekel, where malaria prevalence is low. Women: Seven percent of all women and preg- nant women slept under a mosquito net the night before the interview; however, only 3 percent used an insecticide-treated net. Use of antimalari- als by pregnant women is low. Only five percent of women who had at least one birth in the five years preceding the survey reported that they re- ceived antimalarial treatment for the last birth. Children: Twelve percent of children under five slept under a mosquito net the night before the interview. However, only 4 percent of children under five slept under an insecticide-treated net. (Note: the survey was conducted in the dry sea- son, when mosquito net use is lower than aver- age). Fever is a major manifestation of malaria in chil- dren. Thirty percent of children under five had a fever in the two weeks preceding the survey. Fe- ver was most prevalent among children age 6-23 months. Among febrile children, only 4 percent were treated with antimalarial medication, mostly chloroquine. HIV/AIDS AND OTHER STIS Knowledge of HIV/AIDS and Prevention Methods: The 2002 EDHS results indicate that awareness of HIV/AIDS is nearly universal among women in Eritrea, with 96 percent of women reporting that they have heard of AIDS. The ways to prevent HIV/AIDS mentioned most frequently by respondents were staying faithful to one partner (72 percent), using condoms (54 per- cent), and abstaining (47 percent). Almost eight in ten women know two or more programmati- cally important ways to avoid getting infected with HIV. Knowledge of ways that HIV can be transmitted is important in preventing the spread of the dis- ease. More than seven in ten women recognize that the HIV virus can be transmitted from mother to child during pregnancy (80 percent), xx | Summary of Findings during delivery (72 percent), and through breast- feeding (70 percent). Three-fourths of women know that a healthy-looking person can have the AIDS virus. Knowledge of Condoms and Use of Condoms: One of the main objectives of the National HIV/ AIDS Control Programme is to encourage consis- tent and correct use of condoms, especially among high-risk groups. The 2002 EDHS data show that 54 percent of women know a source for condoms. However, use of condoms is negligible, with only 2 percent of women having used con- doms during the last sexual intercourse in the past year. Social Aspects of HIV/AIDS Prevention and Mitigation: Discussion of HIV/AIDS with a with spouse or partner is an important first step in pre- vention of HIV/AIDS and the control of the epi- demic. The 2002 EDHS survey results show that only 37 percent of women have had such discus- sions with their partners. One-fourth of women say that they would not be willing to take care of a relative who had HIV/AIDS Knowledge of Signs and Symptoms of Sexually Transmitted Infections (STIs): Sexually trans- mitted infections (STIs) are believed to be impor- tant predisposing factors in HIV/AIDS transmis- sion. Fifty-eight percent of women in Eritrea have no knowledge of STIs other than HIV. Among those who have heard of STIs, one in ten women was unable to mention any symptoms of STIs in a man and a woman. ERITREA xxii | Map of Eritrea DEBUBAWI KEIH BAHRI SEMENAWI KEIH BAHRI ANSEBA GASH-BARKA DEBUB MAEKEL Asmara Ethiopia Djibouti Sudan R E D S E A Saudi Arabia Republic of Yemen Note: This is not the official and political map of Eritrea. Introduction | 1 INTRODUCTION 1 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY Geography Eritrea is situated in the Horn of Africa and lies north of the equator between latitudes 12o22' N and 18o02' N, and longitudes 36o26'21" E and 43o13' E. It has an area of 122,000 square kilometers. To the east, the country is bordered by the Red Sea, extending about 1,212 kilometers from Ras Kasar in the north to Dar Elwa in the southeast. Djibouti borders Eritrea in the southeast, Ethiopia in the south, and the Sudan in the north and west. Administratively, the country is divided into six zobas (regions): Anseba, Debub, Debubawi Keih Bahri, Gash Barka, Maekel, and Semenawi Keih Bahri (see map). Eritrea is a land of contrasts with land rising from below sea level to 3,000 meters above sea level. There are three major physiographic zones: the Western Lowlands, the Central and Northern Highlands, and the Eastern Lowlands (also referred to as the Coastal Plains). Temperature varies with altitude: the mean annual temperature ranges from 16o-18oC in the Highlands to 28oC in the Lowlands to more than 30oC in the Coastal Plains (Ministry of Land, Water and Environment, 1997). Most of the Western Lowlands and Coastal Plains are associated with hot and dry climatic conditions, while the Highlands are relatively cool. The presence of flat land, relatively fertile soil, and a milder climate makes the Central Highlands a center of rain-fed agricultural activity. Several of the major urban centers of Eritrea, including the capital city, Asmara, are located in the Central Highlands zone. During good rains the Western Lowlands have a potential for cultivation and agro-pastoralism. The Coastal Plains is the location of the two major port towns of Eritrea, Massawa and Assab. In general, the Central Highlands is the most densely populated part of the country, while the Lowlands are sparsely populated. Rainfall in Eritrea ranges from less than 200 mm per annum in the Eastern Lowlands to about 1,000 mm per annum in a small pocket of the Escarpment; the annual rainfall in the Highlands ranges from 450 mm to 600 mm. The southern part of the Western Lowlands receives 600-800 mm per annum, but rainfall decreases substantially as one moves northward. The extremely low rainfall in the Eastern Lowlands causes aridity and a hostile environment for agriculture, grazing, and industry. There are two major periods of precipitation in Eritrea. One, from June to September, covers both the Western Lowlands and the Highlands. The second comes between October and March and covers the Eastern Lowlands. History Because of Eritrea’s strategic position on the Red Sea, it has fallen victim to many invaders and colonizers. The Ottoman Turks controlled the northern and coastal areas from the middle of the sixteenth century to the second half of the nineteenth century, when Egypt evicted them from their last stronghold, Massawa, in 1872. With the opening of the Suez Canal in 1869, the European colonizers became interested in the Red Sea and Horn of Africa. Italy, after establishing a foothold at Assab through a maritime company, Compagnia Maritimma Rubattino, extended its control, and declared Eritrea its first African colony in 1890. In 1941, Italy was defeated by the Allied forces, and Britain took over the administration of Eritrea. In 1952, after 10 years of British colonial rule, Eritrea was federated with Ethiopia by the United Nations against the will of the Eritrean people. A decade later, Ethiopia abrogated the federal arrangement of the United Nations and annexed Eritrea as one of its provinces. This led to the Eritrean struggle for self-determination, which resulted in a destructive war lasting from 1961 to 1991. 2 | Introduction Two years after the end of the war, a United Nations supervised referendum was held to determine Eritrea’s political status; 99.8 percent of the voters chose independence in that referendum. Independence was formally declared in May 1993. Thereafter, Eritrea became a member of the United Nations and many other international and regional organizations. Economy Agriculture and pastoralism are the main sources of livelihood for about 80 percent of Eritrea’s population. The agricultural sector depends mainly on rain, with less than 10 percent of the arable land currently irrigated. Consequently, productivity is low and the agricultural sector, including livestock and fisheries, accounts for only one-fifth of the gross domestic product (GDP). Eritrea is one of the poorest countries in the world, with GDP per capita of about US$ 200, well below the average US$ 270 for less developed countries (UNDP, 2001). The war for liberation destroyed most of Eritrea’s infrastructure and devastated its economy and environment. This compelled Eritrea to reconstruct its social, economic and physical infrastructure entirely. In an effort to place the economy on a path of sustainable development, the government had targeted the period 1998-2000 to complete the transitional phase of rehabilitation and reconstruction. Nonetheless, in May 1998, under the pretext of a border dispute, Ethiopia declared war against Eritrea and occupied some parts of zobas Gash Barka and Debub. As a result of this war, Eritrean villages, towns, bridges, power plants and public and private buildings were destroyed systematically through aerial and artillery bombardment. The impact of the war on the economy of Eritrea is more visible in the destruction of infrastructure, which had been painfully built in the seven years of peace. Although growth in GDP had reached about 7 percent over the period 1994-1997 (University of Asmara, 2000), it fell to about 3 percent in 1999 due to the border conflict. Government development efforts not only concentrated on rebuilding and rehabilitating war- damaged and destroyed economic and social infrastructures, but also on formulating numerous national economic and social development strategies and policies. Among these was the Macro Policy of 1994, which mapped out short-, medium-, and long-term reconstruction and development programs. In the Macro Policy, human capital formation through education and health was identified as the main strategy for long-term national development. Eritrea’s Macro Policy advocated adequate and sustainable economic growth and social development to reduce poverty and create a basis for all of Eritrea’s citizens to provide a better life for themselves and their children. Eritrea has abundant natural resources including arable land (26 percent of the total area) of which only about 4 percent is under cultivation (World Food Programme, 2002). Although surface water is inadequate in Eritrea, there are adequate supplies of ground water, particularly in the Western Lowlands and in some parts of the Coastal Plains, that can be used for both household and industrial purposes. Eritrea is also believed to have varied and extensive mineral resources including copper, gold, iron, nickel, silica, sulfur and potash. Good quality marble and granite also exist in large quantities (Ministry of Land, Water and Environment, 1997). The Red Sea offers opportunities for the fishing industry, for expanding salt extraction industry, tourism, and possibly extraction of oil and gas. At present, most of these natural resources have not been fully exploited. 1.2 POPULATION No population census has ever been carried out in Eritrea. As a result, there are no reliable estimates of the population currently residing in Eritrea or the population of Eritreans living abroad, many of whom are potential returnees. However, based on a population count, the Ministry of Local Government estimated the total population of Eritrea to be about 3.2 million as of 2001. As there is no Introduction | 3 reliable information about population size, the population growth rate is not known with precision. The population is essentially rural with about 80 percent of the people living in the countryside. The urban population is characterized by rapid growth, partly as the result of returning refugees from the neighboring and other countries, and partly due to high rural-urban migration. The population of Eritrea is not uniformly distributed throughout the country. About 50-60 percent of the population lives in the Highlands. The age distribution is typical of high fertility regimes in which a larger proportion of the population is to be found in the younger age groups than in the older age groups. Eritrea is a multi-ethnic society with nine different ethnic groups speaking nine different languages and professing two major religions, namely, Christianity and Islam. Great efforts have been made by the National Statistics and Evaluation Office (NSEO) to collect demographic, health, and socioeconomic information through surveys. The first nationally representative survey conducted by the NSEO was the 1995 Eritrea Demographic and Health Survey (1995 EDHS) (National Statistics Office and Macro International, 1997). The 2002 Eritrea Demographic and Health Survey (2002 EDHS) was carried out by the same office. These surveys provide detailed information on fertility, infant and child mortality, health and nutritional status of women and children, breastfeeding, and contraceptive use, among other topics. 1.3 HEALTH SERVICES AND PROGRAMS The introduction of modern health services into Eritrea is relatively recent. The first hospital was established in Asmara by the Italians at the end of the nineteenth century. In the period prior to federation with Ethiopia, Eritrea had a relatively advanced health care system at least by the standards of the time. However, during the three decades of the war for independence, almost all existing health facilities were destroyed, medical supplies were disrupted, and health professionals abandoned their posts. Since independence, the Ministry of Health (MOH) has made significant progress in ensuring access to health care services through restoration of health facilities damaged during the war, the provision of adequate supplies of drugs and equipment, the expansion of available health services to communities where they are lacking, through the construction of new facilities and the training of qualified health personnel. Health services in Eritrea focus on primary health care (PHC) and are available to everyone. The PHC strategy emphasizes the development of basic health services at the local level to reach more people and to strengthen preventive public health activities including the prevention and control of endemic diseases such as HIV/AIDS, malaria, tuberculosis, and sexually transmitted infections (STIs). The major objectives of the PHC program are to: • Reduce infant and maternal mortality and increase life expectancy through the provision of adequate and equitable maternal and child health services, promotion of adequate nutrition, and control of communicable diseases, • Ensure that health services are available and accessible to all urban and rural communities, • Sensitize the community to common preventable health problems and design appropriate activities through genuine community involvement, • Promote awareness among the relevant offices and the community at large that health problems can only be solved through multi-sectoral cooperation, • Create awareness among the community that responsibility for one’s health rests with the individual, as an integral part of the family, and 4 | Introduction • Move towards self-sufficiency in manpower by training cadres required at all levels (WHO, 2002a). Since effective implementation of PHC depends on approaches that coordinate and make use of various sectors, and not simply health care activities, the MOH has put more emphasis on an integrated program of PHC that incorporates cross-cutting issues. This is because the causes of ill health are related to both health factors and non-health factors. The important cross-cutting issues include community participation, intersectoral collaboration, decentralization of health services, information, education and communication (IEC), monitoring and supervision of programs and capacity-building (mainly research and training). Currently, the MOH is operating 23 hospitals, 52 health centers, and 225 health stations, most of which are government owned (WHO, 2002a). When compared with the data at independence, these figures indicate a significant increase in health services; the number of hospitals grew by about 50 percent, while health stations and health centers grew by more than 100 percent. The substantial growth in the number of health stations and health centers indicates a great effort on the part of MOH to develop and expand basic health care services at the local level, particularly to people living in rural areas. In terms of health manpower, significant improvements have been made in both recruitment and training. For example, between 1995 and 2000, the number of physicians and nurses increased by 60 percent and 107 percent, respectively. Another area of concern to MOH since independence is maternal and child health and family planning (MCH/FP). Before 1992, family planning services were provided at locations where MCH services were delivered. In 1992, the Planned Parenthood Association of Eritrea (PPAE) was established to promote family planning services, particularly among women and youth. About seven years later, the name of the association was changed to Family Reproductive Health Association of Eritrea (FRHAE), to encompass a broader area of activities. The FRHAE has the following objectives (FRHAE, 2000): • To contribute to the advancement of family welfare by establishing health facilities, social services and other delivery systems for the purpose of advising and counseling couples, youth, and interested individuals regarding responsible parenthood, • To assist families to solve problems of infertility and sub-fertility by providing them with appropriate preventive and remedial social and psychological services, • To promote public awareness and understanding about the marriage relationship, sexual life, reproductive health, and related matters through educational programs, and • To conduct research on and compile and disseminate information about child feeding and rearing practices, quality of life, and reproductive and sexual activity. Although significant efforts have been made to improve the health care system since independence, there remain some deficiencies both in coverage and quality. Health care services are still not adequate for the population, a problem common to most African countries. There is, for example, a shortage of skilled medical personnel, medications, and equipment. In 2000, the ratio of population per physician was 13,144, while the ratio of population per nurse was 2,804 (WHO, 2002a). Another problem is the uneven distribution of medical facilities. There is a high concentration of health facilities in urban areas, especially in the capital city, Asmara. Traditional healers are still consulted in Eritrea, especially in the rural areas. In this respect, although the MOH has made efforts to improve the health situation through educational campaigns directed to eradicate harmful traditional practices, such as female circumcision, it Introduction | 5 appears that there are still problems in this area. Also, the health system of Eritrea provides only limited services on reproductive health and family planning. 1.4 OBJECTIVES OF THE SURVEY The major aim of the 2002 EDHS was to provide up-to-date information on: fertility and childhood mortality levels, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, breastfeeding practices, nutritional status of mothers and young children, and awareness and behavior regarding HIV/AIDS and other sexually transmitted infections. It was designed as a follow-on to the 1995 EDHS survey. However, compared with the 1995 survey, the 2002 EDHS is significantly expanded in scope and coverage. More specifically, the 2002 EDHS survey was designed to: • Collect data at the national level that allow the calculation of demographic rates, particularly fertility and childhood mortality rates; • Assess the health status of mothers and children under age five in Eritrea, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, use of immunization services, and malaria prevention activities; • Measure the levels and patterns of knowledge and behavior of women about sexually transmitted infections, HIV/AIDS, and female circumcision; • Provide information on changes in fertility and contraceptive prevalence and the factors that have contributed to these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding practices, and other important socioeconomic factors; and • Assess gender issues. 1.5 ORGANIZATION OF THE SURVEY The 2002 EDHS survey is a comprehensive survey that involved several agencies. The NSEO, which is a part of the Office of the President, had the major responsibility for conducting this survey. The various departments of the Ministry of Health collaborated with NSEO in all phases of the survey and provided valuable technical help. Financial support for the survey was provided by the U.S. Agency for International Development (USAID) and the Ministry of Health through the Technical Assistance and Support Contract (TASC) with John Snow, Inc. The United Nations Population Fund and the Canadian International Development Agency supported the 2002 EDHS by supplying all the field vehicles. Technical assistance was provided by ORC Macro. 1.6 SAMPLE DESIGN The objectives of the 2002 Eritrea survey are similar to those of the 1995 EDHS survey, with major findings considered at the national level, by urban-rural residence, and by region (the six zobas). The sample for the 2002 EDHS survey is a nationally representative sample of households and is self-weighted in each of the six zobas but not proportionally distributed among the zobas. The sample was designed using information provided by the Ministry of Local Government on the total number of households in various administrative units, mainly villages (in rural areas) and towns (in urban areas). It is a two-stage cluster design in rural areas and a three-stage cluster design in urban areas. 6 | Introduction A national sample of 368 clusters was selected, with 249 in rural areas and 119 in urban areas. A complete household listing operation was carried out in all the selected clusters to provide a frame for the final systematic selection of households. Twenty-five households were selected from each cluster in urban and rural areas in all zobas except one. In zoba Debubawi Keih Bahri, 40 households were selected in each cluster because this zoba contains less than 4 percent of the national population, and has transportation problems, so it was decided to select fewer, larger clusters in this zoba. Around 9,800 households were selected from the 368 clusters to provide an expected sample of 8,500 eligible women. A detailed sample design description is presented in Appendix A. 1.7 QUESTIONNAIRES Two kinds of questionnaires were used in the 2002 EDHS survey: the Household Questionnaire and the Women’s Questionnaire. The contents of the questionnaires were based on the MEASURE DHS+ Model “B”, which was developed for countries with low levels of contraceptive use. The NSEO held several meetings with experts and professionals from partner ministries, most importantly the Ministry of Health, to discuss the questionnaires. The MOH, the Ministry of Education, the Ministry of Labor and Human Welfare, and other concerned institutions in Eritrea actively participated in reviewing and modifying the questionnaires to address Eritrean concerns. Both questionnaires, which were originally prepared in English, were translated into and printed in seven local languages: Tigrigna, Tigre, Bilen, Saho, Afar, Kunama, and Nara. A pretest of the questionnaires was conducted in December 2002. The Household Questionnaire was used to list all of the usual members and visitors who spent the night before the interview in the selected households. Basic background information on each listed person was collected, including age, sex, marital status, educational level attained, occupation, and relationship to the head of the household. The information on age was used to identify women eligible for the individual interview and children less than five years of age whose height and weight would be measured. The Household Questionnaire also obtained information on selected socioeconomic indicators such as number of rooms in the dwelling, type of floor material, source of drinking water, type of toilet facilities, and ownership of various durable goods. Information on the household’s possession of mosquito nets was collected, and a test was conducted by interviewers to assess whether the household used cooking salt fortified with iodine. The Women’s Questionnaire was used to collect information from all women age 15-49. Respondents were asked questions on the following topics: background characteristics; reproductive history; contraceptive knowledge and use; antenatal, delivery and postnatal care; infant feeding practices; child immunization, health and nutrition; marriage and sexual activity; and fertility preferences. In addition, respondents were asked questions about their husband’s background characteristics. Data on female circumcision and on knowledge, attitudes and behavior related to HIV/AIDS and other sexually transmitted infections were collected. Training and Fieldwork Training of the field staff, namely interviewers, supervisors and field editors for the main survey was conducted over a three-week period from February to March 2002. The training was conducted following the standard DHS training procedures, including class presentations, mock interviews, field practice and tests. There was a detailed review of items on the questionnaires and interviewer instructions, and the trainees practiced weighing and measuring women and children. The trainers included NSEO staff, guest lecturers from various departments of the Ministry of Health and the ORC Macro country manager. Introduction | 7 A total of 123 female field staff were trained, of which 98 with good performance were selected to form 14 teams for the fieldwork. The remaining 25 trainees were assigned as data processing staff. Following the training, the fieldwork for the survey was conducted from the last week of March to the first week of July 2002. 1.9 DATA PROCESSING All completed questionnaires for the EDHS survey were brought to the NSEO in Asmara for data processing, which consisted of office editing, coding of open-ended questions, data entry, and secondary editing. A team of 14 data entry clerks, one questionnaire administrator, 14 office editors, two data entry supervisors, six secondary editors, and two data processing experts from ORC Macro were involved in the data processing. Data entry and editing were completed between April 16 and July 26, 2002. 1.10 COVERAGE AND RESPONSE RATES Table 1.1 presents the results of household and individual interviews and response rates for Eritrea as a whole and by urban-rural residence. A total of 9,824 households were selected in the sample, of which 9,512 households were occupied. Of the total occupied households, 9,389 were interviewed successfully, giving a household response rate of 99 percent. In general, response rates for households were not influenced by urban-rural residence. As Table 1.2 indicates, the major reason for not completing household interviews was that no competent respondent was found at home1 (1 percent). Table 1.1 Results of the household and individual interviews and response rates Number of households and interviews and response rates, according to residence, Eritrea 2002 —————————————————————————————————————————————— Urban ———————————————— Result Asmara Other towns Total Rural Total —————————————————————————————————————————————— Household interviews Households selected 1,076 2,169 3,245 6,579 9,824 Households occupied 1,043 2,134 3,177 6,335 9,512 Households interviewed 1,023 2,104 3,127 6,262 9,389 Household response rate 98.1 98.6 98.4 98.8 98.7 Individual interviews Number of eligible women 1,205 2,138 3,343 5,753 9,096 Number of eligible women interviewed 1,123 2,057 3,180 5,574 8,754 Eligible woman response rate 93.2 96.2 95.1 96.9 96.2 From the interviewed households, 9,096 women eligible were identified for the individual interview, of whom 8,754 were successfully interviewed. The women’s response rate for the 2002 EDHS was 96 percent (Table 1.1). Nonresponse among women was mainly due to the absence of women at home at the time of interview, despite repeated visits to the household. The women’s response rate is higher in rural areas than in urban areas (Table 1.2). Details of the fieldwork and sample design are presented in Appendix A. 1An absent household is considered not occupied. 8 | Introduction Table 1.2 Sample implementation Percent distribution of households and eligible women by results of the household and individual interviews, and household and eligible women response rates, according to residence, Eritrea 2002 —————————————————————————————————————————————— Urban ———————————————— Result Asmara Other towns Total Rural Total —————————————————————————————————————————————— Selected households Completed 95.1 97.0 96.4 95.2 95.6 Household present but no competent respondent at home 1.7 1.3 1.4 1.1 1.2 Refused 0.2 0.1 0.1 0.0 0.0 Household absent 2.0 1.2 1.5 3.1 2.6 Dwelling vacant/address not a dwelling 0.9 0.3 0.5 0.4 0.4 Dwelling destroyed 0.1 0.1 0.1 0.2 0.1 Total 100.0 100.0 100.0 100.0 100.0 Number of sampled households 1,076 2,169 3,245 6,579 9,824 Household response rate 98.1 98.6 98.4 98.8 98.7 Eligible women Completed 93.2 96.2 95.1 96.9 96.2 Not at home 3.9 2.3 2.9 1.8 2.2 Postponed 0.2 0.0 0.1 0.1 0.1 Refused 0.4 0.4 0.4 0.1 0.2 Partly completed 0.1 0.1 0.1 0.1 0.1 Incapacitated 0.8 0.7 0.7 1.0 0.9 Other 1.4 0.1 0.6 0.1 0.3 Total 100.0 100.0 100.0 100.0 100.0 Number of women 1,205 2,138 3,343 5,753 9,096 Eligible woman response rate 93.2 96.2 95.1 96.9 96.2 Characteristics of Households and Household Members | 9 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS 2 The purpose of this chapter is to provide a descriptive summary of some socioeconomic and demographic characteristics of the population in sampled households. These characteristics include age, sex, place of residence, educational status, marital status, household economic status (the wealth index), and children’s living arrangements. The chapter also discusses household facilities and housing characteristics such as source of drinking water, electricity, sanitation facilities, flooring materials, and ownership of household durable goods. Information on the characteristics of the surveyed population is essential because it provides a more complete picture of the household population and gives a wider perspective for interpreting the survey findings in subsequent chapters. For the purpose of the 2002 EDHS survey, a household is defined as a person or a group of related or unrelated persons who usually live in the same dwelling unit and who have common cooking and eating arrangements. A member of the household is any person who usually lives in the household and a visitor is someone who is not a member of the household, but who stayed in the household the night preceding the interview. The Household Questionnaire in the survey collected information from all usual residents of the selected household (de jure population) and visitors who stayed in the selected household the night before the interview. The de facto population includes all persons who stayed in the household the night before the interview. The inclusion of both populations in the household survey allows the analysis of either the de jure or the de facto population. 2.1 HOUSEHOLD POPULATION BY AGE, RESIDENCE, AND SEX The percent distribution of the de facto household population in the 2002 EDHS is shown in Table 2.1 by five-year age groups, according to sex and residence. Of the total household population sampled, 62 percent were living in rural areas and 38 percent in urban areas. Forty-five percent of the household population were males and 55 percent were females. The proportion of males in the sampled households is slightly lower than in 1995. Overall, the age distribution in Table 2.1 shows the expected pattern. The proportion in each five-year age group generally decreases with increasing age. An important exception is the age group 0-4 years, in which the proportions are lower than the next age group (i.e., 5- 9). The lower proportions at age 0-4 years are partly due to a recent decline in fertility (see Chapter 3). Figure 2.1 shows the age-sex structure of the household population more clearly in a population pyramid. The pyramid is broad at the base with the next adjacent bar slightly wider. This is a pattern of a youthful population with high but recently declining fertility. The distribution of the male and female household population by single year of age is presented in Figure 2.2. The figure shows noticeable heaping at ages ending with 0 and 5 for both sexes. Ages ending with 1 and 9 are underreported. 10 | Characteristics of Households and Household Members Table 2.1 Household population by age, residence and sex Percent distribution of the de facto household population by five-year age group, according to sex and residence, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban Rural Total ––––––––––––––––––––– –––––––––––––––––––– ––––––––––––––––––––– Age Male Female Total Male Female Total Male Female Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– <5 14.8 11.8 13.1 18.2 14.5 16.2 17.0 13.4 15.0 5-9 17.5 12.5 14.7 20.4 17.4 18.7 19.3 15.5 17.2 10-14 15.7 13.6 14.5 17.7 14.7 16.0 16.9 14.2 15.5 15-19 13.7 11.7 12.6 10.4 8.6 9.5 11.6 9.8 10.6 20-24 4.8 7.9 6.5 3.8 6.4 5.2 4.2 7.0 5.7 25-29 4.3 8.9 6.9 2.2 6.5 4.5 3.0 7.5 5.4 30-34 3.7 5.3 4.6 2.3 5.1 3.8 2.8 5.2 4.1 35-39 2.8 5.7 4.5 2.2 4.7 3.5 2.4 5.1 3.9 40-44 3.2 3.7 3.5 2.9 4.0 3.5 3.0 3.9 3.5 45-49 3.2 3.3 3.3 2.3 3.6 3.0 2.6 3.5 3.1 50-54 3.6 4.3 4.0 3.6 3.0 3.3 3.6 3.5 3.5 55-59 2.7 3.0 2.9 2.7 2.8 2.7 2.7 2.8 2.8 60-64 3.4 2.9 3.1 3.4 3.3 3.3 3.4 3.2 3.3 65-69 2.3 1.7 2.0 2.3 1.8 2.1 2.3 1.8 2.0 70-74 1.7 1.7 1.7 2.4 1.9 2.1 2.1 1.8 2.0 75-79 1.3 0.8 1.0 1.3 0.6 0.9 1.3 0.7 1.0 80 + 1.2 1.2 1.2 1.9 1.1 1.4 1.6 1.1 1.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 6,504 8,423 14,929 11,362 13,281 24,644 17,865 21,703 39,573 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Totals include a small number of people with age or sex not known. EDHS 2002 Figure 2.1 Population Pyramid 85+ 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 Age 0 2 4 6 8 10-2-4-6-8-10 Percent Male Female Characteristics of Households and Household Members | 11 EDHS 2002 Figure 2.2 Distribution of the De Facto Household Population by Single Year of Age and Sex 0 20 40 60 80 100 Age 0 1 2 3 4 5 Pe rc e n t Male Female 2.2 HOUSEHOLD COMPOSITION Table 2.2 presents the distribution of de jure households in the 2002 EDHS sample by sex of head of household and by number of household members. These characteristics are important because they are often associated with socioeconomic differences between households. In addition, the size and composition of households affect the allocation of financial and other resources among household members, which in turn influences the well-being of these individuals. Household size is related to crowding, which can lead to unfavorable health conditions. Since 1995, the proportion of households in Eritrea headed by females has increased. Slightly more than half (53 percent) of household heads are males, indicating a substantial decrease since 1995 (69 percent). The proportion of female-headed households is higher in urban areas (52 percent) than in rural areas (43 percent). All zobas except zoba Debub, have predominantly male-headed households. Forty-three percent of households have 2-4 members. Large households (9 or more members) account for 8 percent of all households and single-person households account for 7 percent. The proportion of single- person households is higher in urban areas (9 percent) than in rural areas (6 percent). Large households are most common in rural areas. The average household size is 4.8 persons, which is larger than the household size observed in both urban areas and rural areas in 1995 (4.4). Since 1995, the mean household size has increased more in rural areas (4.9) than in urban areas (4.7). In the 2002 EDHS, information was collected on the displacement status of household members due to the recent war between Eritrea and Ethiopia. Respondents to the Household Questionnaire were asked whether there were any members in the household who had been displaced from their usual place of residence due to the recent war. According to Table 2.2, 7 percent of households have at least one displaced person—11 percent of urban households and 4 percent of rural households. By zoba, the proportion of households with displaced persons is higher in zobas Maekel (11 percent) and Gash-Barka (8 percent) than in other zobas. The average number of displaced persons (in households with displaced persons) is 3.5. Zoba Gash-Barka has the highest mean number of displaced persons (4.6). 12 | Characteristics of Households and Household Members Table 2.2 Household composition according to residence and zoba Percent distribution of households by sex of head of household and household size, and percentage of households with displaced persons, according to residence and zoba, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Zoba ––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Debubawi Semenawi –––––––––––– Keih Keih Gash- Characteristic Urban Rural Bahri Maekel Bahri Anseba Barka Debub Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Sex of head of household Male 47.8 56.8 54.5 50.6 61.6 59.8 59.3 45.1 53.3 Female 52.2 43.2 45.5 49.4 38.4 40.2 40.7 54.9 46.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of usual members 1 8.8 6.2 9.2 8.8 6.0 4.8 6.8 7.6 7.2 2 11.9 12.3 17.1 12.3 13.3 10.2 13.8 10.8 12.2 3 14.8 15.1 18.4 13.2 15.4 14.5 17.8 14.1 15.0 4 16.9 15.1 16.1 16.3 15.8 16.0 15.1 15.6 15.8 5 13.7 13.3 13.8 11.7 15.2 12.8 14.4 13.6 13.4 6 11.9 12.9 10.8 11.9 12.7 13.3 11.8 13.3 12.5 7 8.6 9.8 6.4 9.7 9.6 9.8 8.5 9.8 9.4 8 5.8 6.8 4.4 6.5 5.7 8.9 5.8 6.3 6.4 9+ 7.6 8.5 3.7 9.7 6.3 9.8 6.0 9.0 8.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Mean size 4.7 4.9 4.1 4.9 4.7 5.1 4.6 4.9 4.8 Percentage of households with displaced persons 10.6 4.0 3.4 10.9 0.9 1.2 8.1 7.4 6.6 Number of households 3,634 5,755 328 2,122 1,195 1,181 1,800 2,763 9,389 Mean number of displaced persons per household1 3.4 3.5 2.6 3.2 * * 4.6 3.1 3.5 Number of households with displaced persons 384 225 11 227 10 15 144 203 610 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Based on households with displaced persons 2.3 FOSTERHOOD AND ORPHANHOOD Foster children are children under 15 years of age who are not living with either of their biological parents. Orphaned children are children under 15 years of age who have lost one or both of their biological parents. To measure the prevalence of child fostering and orphanhood, four questions were asked in the Household Questionnaire on the survival status and residence of the parents of children under 15 years of age. Information on children’s living arrangements and orphanhood is presented in Table 2.3. In Eritrea, 76 percent of children under age 15 live with both parents. The proportion of children living with both parents decreases with increasing age. Rural children are more likely to live with both parents than urban children. By residence, the percentage of children who live with both parents is lowest in Asmara and, among zobas, in zoba Maekel. Eighteen percent of children live with only one parent— Characteristics of Households and Household Members | 13 15 percent with their mothers and 3 percent with their fathers. Seven percent of children live with only one parent because the other parent is dead. The proportion of children living with their father only because their mother is dead is higher in zoba Gash-Barka than in other zobas. Foster children—children not living with either parent—account for 6 percent of children under age 15 and orphaned children— children who have lost one or both parents—account for 10 percent. Among children age 10-14, one in six is an orphan. A comparison of the last two rows in Table 2.3 shows that the proportion of children under 15 years who live with both of their parents has increased from 72 percent in 1995 to 76 percent in 2002. The proportion who live with their mothers only declined from 18 to 15 percent, and those who live with their fathers only decreased from 4 to 3 percent. The proportion of orphaned children decreased from 12 percent to 10 percent. Table 2.3 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 15 by children’s living arrangements and survival status of parents, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Living Living with mother with father Not living with but not father but not mother either parent Missing Living –––––––––––––– ––––––––––––––– ––––––––––––––––––––––––– informa- with Only Only tion on Number Background both Father Father Mother Mother Both father mother Both father/ of characteristic parents alive dead alive dead alive alive alive dead mother Total children –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age <2 84.9 13.4 0.8 0.0 0.1 0.4 0.1 0.0 0.0 0.3 100.0 2,274 2-4 82.7 11.8 1.9 0.2 0.6 1.3 0.9 0.1 0.1 0.4 100.0 3,790 5-9 77.3 9.9 4.0 0.8 1.9 3.0 1.6 0.4 0.7 0.5 100.0 7,026 10-14 67.3 8.4 10.2 1.2 3.0 4.2 1.8 1.5 1.6 0.9 100.0 6,343 Sex Male 76.7 10.3 5.0 0.7 1.8 2.5 1.2 0.5 0.8 0.5 100.0 9,849 Female 75.2 10.1 5.4 0.7 1.8 3.0 1.5 0.7 0.8 0.7 100.0 9,582 Residence Total urban 67.6 16.1 6.2 1.2 1.3 3.5 1.2 1.1 1.0 0.9 100.0 6,462 Asmara 63.9 16.7 7.9 1.2 1.8 3.3 1.2 1.5 1.0 1.5 100.0 2,594 Other towns 70.1 15.6 5.0 1.2 1.0 3.7 1.2 0.8 1.0 0.4 100.0 3,868 Rural 80.1 7.3 4.8 0.5 2.1 2.4 1.4 0.4 0.6 0.5 100.0 12,970 Zoba Debubawi Keih Bahri 71.3 11.7 7.1 1.1 1.8 3.5 1.2 0.9 1.0 0.5 100.0 550 Maekel 69.1 13.5 7.2 1.1 1.4 3.3 1.0 1.2 0.8 1.4 100.0 3,654 Semenawi Keih Bahri 78.4 9.4 5.0 0.6 1.9 1.5 1.7 0.5 0.6 0.3 100.0 2,527 Anseba 82.4 6.2 3.2 0.5 2.3 2.7 1.5 0.5 0.6 0.1 100.0 2,836 Gash-Barka 77.1 8.0 5.9 0.5 2.8 1.9 2.3 0.2 1.0 0.2 100.0 3,626 Debub 75.8 11.5 4.5 0.8 1.2 3.4 0.9 0.6 0.7 0.6 100.0 6,241 Total 2002 76.0 10.2 5.2 0.7 1.8 2.8 1.4 0.6 0.8 0.6 100.0 19,433 Total 1995 71.8 11.8 6.4 1.0 2.7 2.8 1.1 0.8 0.7 0.9 100.0 11,269 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes two children with missing information on sex. 14 | Characteristics of Households and Household Members 2.4 EDUCATION LEVELS OF THE HOUSEHOLD POPULATION Education is a key determinant of the lifestyle and status an individual enjoys in society. It affects many aspects of life, including health, employment, marriage, and demographic behaviors. Studies have consistently shown that education has a strong effect on reproductive behavior, fertility, childhood mortality, morbidity, and contraceptive use, as well as attitudes and awareness related to family health and hygiene. Educational Attainment of the Household Population In the 2002 EDHS survey, information on educational attainment was collected for every member of the household age six years and above. Primary education in Eritrea starts at 7 years of age and continues until age 11; it is followed by two years for middle school, and an additional four years for secondary education. Table 2.4 shows the distribution of the de facto male and female household populations age six years and over by educational level, according to age, residence, and zoba. Educational attainment at each age is higher for males than for females. Fifty-two percent of female household members have never attended school, compared with 39 percent of males. However, among the population with any schooling, about one-fourth of males as well females have completed at least primary school. The median number of years of schooling is 0.7 for males and 0.0 for females because the majority of women have never attended school. Rapid increases in educational attainment for both sexes can be seen from the declining proportion without any formal education in successively younger age groups. For example, the proportion of women with no education decreases from 95 percent at age 65 and above to 21 percent at age 10-14. The higher proportions uneducated among those age 6-9 years for both sexes (51 percent and 54 percent for boys and girls, respectively) is mostly due to the inclusion of children age six in the age group; those children have not yet attended school. Officially, the minimum age for attending school in Eritrea is 7 years. There have been marked improvements since the 1995 EDHS in educational attainment among both males and females, but the differentials in 2002 show the same patterns by zoba, residence, and sex as in the past. For example, in 1995, the proportions of boys and girls age 10-14 who had never attended school were 32 percent and 40 percent, respectively, compared with 15 percent and 21 percent, respectively, in 2002. Urban areas have a wide lead over rural areas in level of education attained. For example, 82 percent of males and 70 percent of females in urban areas have some education, compared with less than half of males (48 percent) and one-third of females in rural areas. Asmara, the most urbanized area in the country, has the highest proportion of males and females with some education (88 percent and 77 percent, respectively). The median number of years of schooling for urban males and urban females is 4.1 and 2.6, respectively, and 0.0 for both males and females in rural areas. By residence, the difference in the median number of years of schooling between males and females is highest in other towns (the median is 2.8 years for males and 1.1 years for females). Educational attainment varies widely among zobas. The proportion of males and females with some education is lowest in zoba Gash-Barka (38 and 26 percent, respectively) and highest in zoba Maekel (86 and 76 percent, respectively). The median number of years of schooling for males is 4.7 years in zoba Maekel, much lower in zobas Debubawi Keih Bahri and Debub, and 0.0 in all other zobas. The median number of years for schooling is one year lower for females (3.7 years) than for males in zoba Maekel, and is 0.0 for females in all other zobas. To determine the literacy level in the country, for each person age six and above, the question was asked if the person could read and write in any language without difficulty. More than half Characteristics of Households and Household Members | 15 Table 2.4 Educational attainment of the household population Percent distribution of the de facto household populations age six and over by highest level of education attended or completed, median number of years of schooling, and percentage literate, by sex, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Highest level of schooling attended or completed Median ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– number More of years Some than Don’t of Percent- Background No Some Completed second- Completed second- know/ school- age characteristic education primary primary1 ary secondary2 ary missing Total Number ing literate ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MALE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 6-9 50.8 47.7 0.0 0.0 0.0 0.0 1.5 100.0 2,940 0.0 31.5 10-14 14.7 80.6 1.1 3.4 0.0 0.1 0.1 100.0 3,024 2.0 79.5 15-19 12.3 47.4 3.2 33.7 1.9 1.4 0.1 100.0 2,072 5.3 86.7 20-24 20.1 27.1 3.8 30.2 9.5 8.5 0.7 100.0 751 6.3 81.4 25-29 19.7 25.1 1.5 21.0 19.7 12.3 0.7 100.0 528 7.0 81.4 30-34 37.8 21.0 2.9 11.6 17.5 8.4 0.8 100.0 503 3.9 67.1 35-39 47.0 22.3 3.0 10.5 10.8 6.2 0.2 100.0 430 1.6 60.8 40-44 54.5 20.6 1.9 7.3 7.6 7.1 1.0 100.0 536 0.0 54.7 45-49 49.6 25.3 3.0 7.6 7.2 6.6 0.7 100.0 473 0.0 59.6 50-54 58.8 20.3 2.2 6.9 4.8 5.6 1.4 100.0 648 0.0 49.6 55-59 63.1 19.5 1.3 5.5 4.2 5.3 1.0 100.0 480 0.0 46.3 60-64 74.2 15.8 1.5 2.2 3.1 1.7 1.6 100.0 605 0.0 34.5 65+ 82.4 12.9 0.3 1.1 0.8 0.7 1.7 100.0 1,319 0.0 31.4 Residence Total urban 18.2 45.4 2.8 18.0 8.1 6.3 1.3 100.0 5,370 4.1 80.7 Asmara 10.4 42.2 2.6 18.9 12.3 11.5 2.1 100.0 2,420 5.5 88.9 Other towns 24.6 48.1 2.9 17.2 4.6 2.0 0.6 100.0 2,950 2.8 73.9 Rural 51.6 40.7 0.8 5.0 0.8 0.5 0.6 100.0 8,951 0.0 46.7 Zoba Debubawi Keih Bahri 37.6 37.8 2.8 9.8 8.4 2.5 1.0 100.0 410 1.7 60.0 Maekel 13.8 45.3 2.4 18.0 9.6 9.0 2.0 100.0 3,186 4.7 85.0 Semenawi Keih Bahri 52.7 37.6 2.2 4.7 1.4 0.8 0.7 100.0 1,893 0.0 48.1 Anseba 45.7 44.2 1.3 5.6 2.5 0.4 0.4 100.0 2,028 0.0 52.3 Gash-Barka 61.7 30.4 1.2 4.7 0.8 0.6 0.5 100.0 2,700 0.0 37.5 Debub 34.4 50.1 0.8 11.6 1.6 1.0 0.4 100.0 4,105 0.7 62.8 Total 39.1 42.5 1.6 9.9 3.5 2.7 0.8 100.0 14,321 0.7 59.4 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– FEMALE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 6-9 53.8 44.6 0.1 0.0 0.0 0.0 1.5 100.0 2,825 0.0 28.7 10-14 21.3 74.0 1.1 3.5 0.0 0.0 0.2 100.0 3,092 1.9 73.4 15-19 21.5 47.2 2.7 24.4 3.0 1.0 0.1 100.0 2,136 4.6 77.1 20-24 41.5 27.9 3.0 16.4 8.8 2.1 0.2 100.0 1,515 2.1 57.9 25-29 46.4 26.3 1.8 12.9 9.7 2.7 0.2 100.0 1,618 1.2 53.5 30-34 65.7 19.1 0.9 5.4 7.4 1.2 0.4 100.0 1,130 0.0 35.6 35-39 65.5 20.4 1.2 4.8 6.3 1.7 0.1 100.0 1,105 0.0 34.4 40-44 72.8 15.7 1.1 3.7 3.8 2.7 0.3 100.0 845 0.0 27.0 45-49 79.5 14.9 1.4 1.5 1.7 0.5 0.5 100.0 753 0.0 20.5 50-54 78.7 12.7 0.5 1.6 1.2 1.3 4.0 100.0 750 0.0 19.6 55-59 85.4 10.0 0.0 1.7 0.5 0.4 2.0 100.0 616 0.0 12.1 60-64 91.0 4.7 0.2 0.9 0.0 0.3 2.9 100.0 684 0.0 5.9 65+ 95.0 2.1 0.3 0.2 0.2 0.0 2.3 100.0 1,178 0.0 3.3 Residence Total urban 30.2 41.8 2.3 14.7 7.3 2.3 1.4 100.0 7,259 2.6 65.6 Asmara 20.6 38.3 2.7 20.7 11.7 3.6 2.3 100.0 3,525 4.7 75.3 Other towns 39.2 45.1 1.9 9.0 3.2 1.0 0.6 100.0 3,734 1.1 56.4 Rural 67.0 29.8 0.5 1.9 0.3 0.0 0.5 100.0 10,994 0.0 28.9 Zoba Debubawi Keih Bahri 54.8 28.9 2.5 8.3 4.1 0.4 1.0 100.0 567 0.0 41.6 Maekel 23.9 41.0 2.5 18.1 9.3 2.9 2.3 100.0 4,506 3.7 72.0 Semenawi Keih Bahri 69.2 26.4 1.0 1.9 1.1 0.1 0.3 100.0 2,216 0.0 28.0 Anseba 60.2 34.2 0.7 3.5 1.0 0.0 0.5 100.0 2,368 0.0 36.6 Gash-Barka 74.2 23.1 0.6 1.5 0.4 0.1 0.1 100.0 3,179 0.0 22.0 Debub 52.7 40.0 0.7 4.5 1.1 0.6 0.5 100.0 5,417 0.0 41.9 Total 52.4 34.5 1.2 7.0 3.1 0.9 0.9 100.0 18,253 0.0 43.5 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 8 females and 13 males with missing information on age, who are not shown separately. 1 Completed 5 grade at the primary level 2 Completed 11 grades at the secondary level 16 | Characteristics of Households and Household Members (51 percent) of the population are literate. There is a significant difference in the literacy level by sex. Overall, 59 percent of males and 44 percent of females are literate. There are marked differentials in the literacy level by residence. Eight in ten males and almost two-thirds of females in urban areas are literate, compared with less than half (47 percent) of males and less than one-third (29 percent) of females in rural areas. School Attendance Ratios Information on the net attendance ratio (NAR), gross attendance ratio (GAR), and gender parity index (GPI) by school level, according to sex, residence, zoba, and wealth index is shown in Tables 2.5.1- 2.5.3. The NAR indicates participation in primary schooling for the population age 7-11, in middle schooling for the population age 12-13, and in secondary schooling for the population age 14-17. The GAR measures participation at each level of schooling among population age 6-24. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. The GPI at a given school level is defined as the ratio of the GAR for females to the GAR for males, and indicates the magnitude of the gender gap in attendance ratios. If there is no gender difference, the GPI will be equal to 1, whereas the wider the disparity in favor of males, the closer the gap will be to zero. If the gender gap favors females, the GPI exceeds 1. Table 2.5.1 Primary school attendance ratios Primary school net attendance ratios (NAR), gross attendance ratios (GAR), and the gender parity index for the de jure household population age 7-11, by sex, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Net attendance ratio 1 Gross attendance ratio 2 Gender Background –––––––––––––––––––––––––– ––––––––––––––––––––––––– parity characteristic Male Female Total Male Female Total index 3 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 79.4 80.6 80.0 112.3 121.4 116.6 1.08 Asmara 86.9 89.3 88.1 114.7 119.2 116.9 1.04 Other towns 75.1 75.0 75.1 110.9 122.9 116.5 1.11 Rural 54.7 49.7 52.3 103.0 82.3 92.9 0.80 Zoba Debubawi Keih Bahri 57.2 47.7 52.7 84.0 71.0 77.9 0.84 Maekel 85.4 89.6 87.5 117.8 121.5 119.7 1.03 Semenawi Keih Bahri 46.7 38.3 42.7 89.2 69.2 79.6 0.78 Anseba 57.2 49.3 53.3 111.9 85.7 98.8 0.77 Gash-Barka 42.7 37.8 40.4 84.7 70.9 78.1 0.84 Debub 72.4 69.8 71.1 118.9 110.3 114.8 0.93 Wealth index Lowest 43.6 33.8 39.0 93.6 63.9 79.4 0.68 Second 52.8 46.6 49.8 96.4 79.7 88.4 0.83 Middle 64.1 64.9 64.5 114.3 104.9 109.6 0.92 Fourth 81.9 81.6 81.7 120.9 120.2 120.6 0.99 Highest 85.3 86.4 85.8 113.5 121.3 117.0 1.07 Total 62.8 59.4 61.2 106.1 94.6 100.5 0.89 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Percentage of the primary-school-age (7-11 years) population that is attending primary school 2 Total number of primary school students, expressed as a percentage of the official primary-school-age population. 3 The gender parity index for primary school is the ratio of the primary school GAR for females to the GAR for males. Characteristics of Households and Household Members | 17 Table 2.5.2 Middle school attendance ratios Middle school net attendance ratios (NAR), gross attendance ratios (GAR), and the gender parity index for the de jure household population age 12-13, by sex, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Net attendance ratio1 Gross attendance ratio 2 Gender Background –––––––––––––––––––––––––– ––––––––––––––––––––––––– parity characteristic Male Female Total Male Female Total index 3 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 40.0 38.1 39.0 116.2 106.6 111.0 0.92 Asmara 49.6 54.7 52.3 121.1 133.6 127.7 1.10 Other towns 33.1 27.1 29.8 112.7 88.8 99.5 0.79 Rural 13.6 9.1 11.2 58.9 34.0 45.9 0.58 Zoba Debubawi Keih Bahri 31.8 28.1 29.8 76.3 63.7 69.5 0.84 Maekel 48.4 49.0 48.7 115.9 121.5 118.8 1.05 Semenawi Keih Bahri 14.3 10.7 12.3 92.4 29.9 57.0 0.32 Anseba 15.2 12.0 13.5 64.7 42.5 53.2 0.66 Gash-Barka 6.4 1.9 4.0 35.6 17.6 25.9 0.50 Debub 20.6 17.4 19.0 79.6 67.2 73.2 0.84 Wealth index Lowest 4.6 4.2 4.4 38.6 18.5 27.6 0.48 Second 9.4 5.5 7.4 59.4 30.5 44.3 0.51 Middle 19.8 12.2 15.8 83.4 42.3 61.6 0.51 Fourth 34.3 32.1 33.2 95.0 106.9 101.2 1.12 Highest 51.5 52.2 51.9 129.0 124.4 126.6 0.96 Total 22.7 19.6 21.1 78.6 60.4 68.9 0.77 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Percentage of the middle-school-age (12-13 years) population that is attending middle school 2 Total number of middle school students, expressed as a percentage of the official middle-school-age population. 3 The gender parity index for middle school is the ratio of the middle school GAR for females to the GAR for males. Table 2.5.1 shows that more than six in ten (61 percent) primary-school-age children are currently attending primary school. Only one in five (21 percent) middle-school-age children is attending middle school (Table 2.5.2), while one in four (23 percent) secondary-school-age youths is attending secondary school (Table 2.5.3). The NAR is slightly higher among males than among females at each level. Attendance ratios are much lower in rural areas than in urban areas at all three levels of schooling. Regarding variations by zoba, the NAR in zoba Maekel is the same for boys and girls at the middle-school level and the secondary-school level, but higher for girls than for boys at the primary- school level. In the other zobas, it is consistently higher for boys than for girls at each level. Net attendance ratios are lowest in zoba Gash-Barka and highest in zoba Maekel, followed by zoba Debub. There is a positive correlation between the wealth index1 and attendance ratios for both sexes at each school level. The GAR has a pattern similar to that of the NAR. The GAR is higher among males than females, at 106 and 95, respectively, at the primary level; 79 and 60, respectively, at the middle-school level; and 1 The wealth index used in this analysis is discussed on page 19. 18 | Characteristics of Households and Household Members 50 and 35, respectively, at the secondary-school level. The GPI for these levels is 0.89, 0.77, and 0.71, respectively, indicating that the deficit of females increases with level of education. Table 2.5.3 Secondary school attendance ratios Secondary school net attendance ratios (NAR), gross attendance ratios (GAR), and the gender parity index for the de jure household population age 14-17, by sex, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Net attendance ratio 1 Gross attendance ratio 2 Gender Background –––––––––––––––––––––––––– ––––––––––––––––––––––––– parity characteristic Male Female Total Male Female Total Index 3 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 44.4 36.6 40.4 87.1 61.1 73.6 0.70 Asmara 48.3 45.4 46.6 86.5 80.7 83.2 0.93 Other towns 41.9 28.0 35.3 87.4 42.0 65.9 0.48 Rural 13.4 8.4 11.3 27.2 12.4 20.9 0.46 Zoba Debubawi Keih Bahri 42.5 24.3 33.7 57.7 37.8 48.1 0.66 Maekel 42.6 42.6 42.6 78.6 72.3 75.2 0.92 Semenawi Keih Bahri 14.2 8.4 11.9 27.1 13.7 21.9 0.51 Anseba 16.1 13.2 15.0 33.8 21.5 28.8 0.64 Gash-Barka 9.4 4.8 7.4 29.3 7.2 19.9 0.25 Debub 28.6 16.3 22.9 56.5 24.3 41.7 0.43 Wealth index Lowest 7.0 2.0 5.1 14.5 4.4 10.7 0.30 Second 8.4 4.9 6.9 22.1 6.4 15.2 0.29 Middle 18.2 11.6 15.2 36.2 15.0 26.7 0.41 Fourth 45.2 29.4 37.4 91.9 46.5 69.4 0.51 Highest 47.5 45.2 46.3 85.4 78.3 81.6 0.92 Total 25.1 21.6 23.5 49.7 35.3 43.0 0.71 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Percentage of the secondary-school-age (14-17 years) population that is attending secondary school 2 Total number of secondary school students, expressed as a percentage of the official secondary-school- population. 3 The gender parity index for secondary school is the ratio of the secondary school GAR for females to the GAR for males. The differentials in GAR and GPI by residence and zoba are small at the primary school level but become more pronounced as the level of education increases. At the middle school level, the total GAR is lower in rural areas than in urban areas and in zobas Semenawi Keih Bahri, Anseba, and Gash Barka than in other zobas. The lowest GAR is in zoba Gash-Barka (26). The GPI at the middle-school level ranges from 0.32 in zoba Semenawi Keih Bahri to 1.10 in Asmara, indicating that there is a huge deficit of females in the zoba, while females have a slight edge in school attendance in Asmara. The GAR and GPI at the secondary-school level are generally lower than at the middle-school level. The GPI is lowest for zoba Gash-Barka (0.25) and deficit of females is evident for all subgroups. The female deficit observed at the secondary-school level could be partly due to young women getting married and dropping out of school, especially in rural areas. At the primary school level, for different levels of the wealth index the GAR varies from 79 to 117 and the GPI varies from 0.68 to 1.07. The differences by sex are small at the primary-school level. At higher levels of schooling, there is greater variation in the GAR and the GPI by wealth index. At the middle-school level, the total GAR increases from 28 to 127 going from the lowest to the highest quintile. The GPI is around 0.50 for the three lowest quintiles of the wealth index. Females from households in the Characteristics of Households and Household Members | 19 fourth quintile of the wealth index have a slight edge over males, and the deficit of females at the secondary-school level is even greater for the three lowest quintiles. The wealth index used here is one recently developed and tested in a large number of countries in relation to inequities in household income, use of health services, and health outcomes (Rutstein, Johnson, and Gwatkin, 2000). It is an indicator of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The wealth index was constructed using household asset data (including country-specific assets) and principal components analysis. The asset information was collected through the 2002 EDHS Household Questionnaire, and covers information on household ownership of a number 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 material used in flooring. Each asset was assigned a weight (factor score) generated through principal components analysis, and the resulting asset scores were standardized in relation to a standard normal distribution with a mean of zero and a standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the total score of the household in which they resided. The sample was then divided into population quintiles; each quintile was designated a rank, from one (lowest) to five (highest). Current School Attendance The age-specific attendance rates (ASARs) for the population age 6-24 by single year and sex are shown in Figure 2.3. The ASAR indicates school attendance at any level, from primary to higher levels of education. Although the minimum age for schooling in Eritrea is 7 years, there are some children attending school at younger ages. A majority of children are not attending school at age 7. The peak attendance is at age 11 when 86 percent of boys and 82 percent of girls are currently attending school. The male-female disparity in attending school is small at younger ages (in favor of males). However, EDHS 2002 Figure 2.3 Age-Specific Attendance Rates Note: Figure shows percentage of the de jure house- hold population age 6-24 years attending school. 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age 0 20 40 60 80 100 Percent Male Female 20 | Characteristics of Households and Household Members differentials by sex in school attendance become wider beginning at age 17. For example, one in five males age 24 is attending school, compared with only one in 50 females. 2.5 MARITAL STATUS The 2002 EDHS includes information on the marital status of all household members age 15 and above. Table 2.6 shows the current marital status of the de facto household population by age, sex, and residence. In this report, ‘‘marriage’’ refers to both formal and informal unions. An informal union is one in which the man and woman live together for some time, intending to have a lasting relationship, but do not have a formal civil, cultural or religious marriage ceremony. Among females age 15 and above, 62 percent are currently married and 19 percent have never been married. The proportion never married is much higher among males (39 percent) than among females (19 percent), and is higher in urban areas (46 percent for males and 28 percent for females) than in rural areas (34 percent for males and 12 percent for females). Percentages currently divorced and separated are generally small, regardless of age, sex, and place of residence. One in eight women age 15 and above in urban areas and rural areas is currently widowed, compared with 2-3 percent of men. By age group, the percentage of women widowed is small except at older ages (age 40 and above). For example, among women age 50 and above in both urban areas and rural areas, more than two in ten women are widowed. The higher percentage of older woman than men who are widowed reflects sex differentials in age at marriage, longevity, and remarriage rates. A discussion of marital patterns among women age 15-49 is contained in Chapter 6. Characteristics of Households and Household Members | 21 Table 2.6 Marital status of the de facto household population Percent distribution of the de facto household population age 15 and above by marital status, according to age, residence and sex, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Current marital status –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number Never Living Not living of Characteristic married Married together Widowed Divorced together Missing Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– URBAN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Male 15-19 98.0 0.5 0.0 0.0 0.0 0.0 1.5 100.0 889 20-24 92.4 3.7 1.2 0.0 1.0 0.0 1.7 100.0 315 25-29 73.0 24.1 1.8 0.0 1.0 0.0 0.0 100.0 277 30-34 38.7 55.6 3.9 0.0 0.8 0.0 1.0 100.0 243 35-39 21.0 70.8 4.1 0.8 2.2 1.1 0.0 100.0 184 40-44 8.1 85.0 3.1 2.4 0.7 0.1 0.5 100.0 209 45-49 4.4 90.3 3.0 1.0 1.4 0.0 0.0 100.0 207 50+ 1.6 90.6 1.6 2.1 2.3 0.0 1.7 100.0 240 Total 45.6 48.8 1.4 1.8 1.3 0.2 0.9 100.0 3,386 Female 15-19 88.5 10.0 0.5 0.0 0.7 0.2 0.1 100.0 988 20-24 48.9 42.0 3.1 0.4 3.4 2.1 0.0 100.0 662 25-29 21.8 63.3 5.0 2.4 5.5 1.8 0.2 100.0 749 30-34 9.2 68.3 4.5 4.5 9.1 3.7 0.7 100.0 447 35-39 4.4 76.1 3.5 4.2 9.4 2.1 0.2 100.0 481 40-44 2.5 71.6 2.6 12.1 5.1 6.2 0.0 100.0 313 45-49 1.5 61.1 4.5 14.8 15.0 2.7 0.4 100.0 280 50+ 4.2 59.0 0.5 21.1 13.1 1.7 0.3 100.0 360 Total 28.0 48.7 2.5 12.0 6.4 2.0 0.4 100.0 5,234 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– RURAL ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Male 15-19 96.3 2.3 0.1 0.1 0.2 0.0 1.0 100.0 1,183 20-24 80.4 17.9 0.0 0.4 0.7 0.0 0.6 100.0 436 25-29 47.8 47.3 2.1 0.9 0.9 0.5 0.4 100.0 250 30-34 12.1 82.1 1.3 1.2 3.3 0.0 0.0 100.0 260 35-39 7.0 86.3 2.0 1.2 2.9 0.0 0.5 100.0 245 40-44 2.5 92.3 0.0 2.3 2.0 0.0 1.0 100.0 326 45-49 2.6 91.5 0.5 3.8 1.6 0.0 0.0 100.0 266 50+ 1.0 93.2 0.7 3.0 2.1 0.1 0.0 100.0 415 Total 33.9 60.6 0.6 3.1 1.3 0.1 0.4 100.0 4,971 Female 15-19 52.7 43.5 0.5 0.0 2.1 0.4 0.8 100.0 1,148 20-24 14.2 77.4 0.9 1.0 4.5 1.5 0.5 100.0 853 25-29 4.9 83.2 1.8 0.9 7.7 1.0 0.4 100.0 868 30-34 2.2 85.9 1.6 3.3 5.7 1.3 0.0 100.0 682 35-39 1.6 83.0 2.9 5.1 5.7 1.8 0.0 100.0 624 40-44 0.4 84.8 0.9 9.4 4.1 0.4 0.0 100.0 532 45-49 0.6 79.0 1.8 10.9 6.4 1.3 0.0 100.0 473 50+ 0.8 67.9 0.8 22.3 7.4 0.3 0.5 100.0 394 Total 11.5 68.2 1.1 12.8 5.2 0.9 0.3 100.0 7,103 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– TOTAL ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Male 15-19 97.0 1.5 0.1 0.1 0.1 0.0 1.2 100.0 2,072 20-24 85.4 11.9 0.5 0.2 0.9 0.0 1.0 100.0 751 25-29 61.1 35.1 2.0 0.4 1.0 0.2 0.2 100.0 528 30-34 25.0 69.3 2.6 0.6 2.1 0.0 0.5 100.0 503 35-39 13.0 79.7 2.9 1.0 2.6 0.5 0.3 100.0 430 40-44 4.7 89.4 1.2 2.4 1.5 0.0 0.8 100.0 536 45-49 3.4 91.0 1.6 2.6 1.5 0.0 0.0 100.0 473 50+ 1.2 92.2 1.0 2.7 2.2 0.0 0.6 100.0 655 Total 38.6 55.8 0.9 2.6 1.3 0.1 0.6 100.0 8,357 Female 15-19 69.3 28.0 0.5 0.0 1.4 0.3 0.5 100.0 2,136 20-24 29.4 61.9 1.9 0.7 4.1 1.7 0.3 100.0 1,515 25-29 12.8 74.0 3.3 1.6 6.7 1.4 0.3 100.0 1,618 30-34 5.0 79.0 2.7 3.7 7.0 2.3 0.3 100.0 1,130 35-39 2.8 80.0 3.2 4.7 7.3 1.9 0.1 100.0 1,105 40-44 1.2 79.9 1.5 10.4 4.5 2.5 0.0 100.0 845 45-49 1.0 72.4 2.8 12.4 9.6 1.8 0.1 100.0 753 50+ 2.4 63.7 0.7 21.7 10.1 1.0 0.4 100.0 754 Total 18.5 59.9 1.7 12.5 5.7 1.4 0.4 100.0 12,337 22 | Characteristics of Households and Household Members 2.6 EMPLOYMENT STATUS OF HOUSEHOLD POPULATION Tables 2.7.1 and 2.7.2 show the distribution of household populations of females and males age 10 and above by employment status and type of earnings, according to background characteristics. Sixty- nine percent of males and 16 percent of females age 15 years and above were employed in the month before the survey and are considered currently employed. The proportions for males and females age 15- 64 employed are 72 percent and 17 percent, respectively. The proportion currently employed peaks at age 30-34 for males (93 percent) and at age 25-29 for females (26 percent). For both sexes, there is a moderate decline in employment at age 60 and above. However, remarkably, almost half of males age 65 and above were employed the month before the survey. Tables 2.7.1 and 2.7.2 show that overall, the vast majority of children age 10-14 attend school, and only a small proportion were employed in the month before the survey. Children’s employment varies by sex; boys are more likely to be employed than girls (4 percent and 1 percent, respectively). Around four in ten persons age 10-14 are not paid for their work. Table 2.7.1 Employment status: women Percent distribution of the de jure female household population age 10 and over by employment status and type of earnings, according to background charac- teristics, Eritrea 2002 Employment status Type of earnings Background characteristic Not em- ployed, in school Not em- ployed in past month Employed in past month Missing Total Number of women Cash In-kind Both cash and in-kind Not paid Missing Total Total employed women Age 10-14 69.7 24.2 1.3 4.9 100.0 3,185 40.5 7.0 2.3 39.4 10.8 100.0 41 15-19 43.2 47.0 9.1 0.7 100.0 2,247 80.1 3.6 0.7 12.9 2.7 100.0 205 20-24 7.2 69.5 22.7 0.6 100.0 1,660 86.0 1.4 0.7 11.0 0.8 100.0 377 25-29 0.0 73.5 25.7 0.8 100.0 1,719 86.6 1.1 1.0 8.6 2.7 100.0 442 30-34 0.0 80.8 18.7 0.4 100.0 1,172 81.8 2.4 2.5 12.2 1.2 100.0 220 35-39 0.0 77.8 21.7 0.5 100.0 1,135 81.7 3.5 4.5 10.2 0.0 100.0 247 40-44 0.0 82.8 16.8 0.3 100.0 878 81.2 3.4 2.2 9.5 3.7 100.0 148 45-49 0.0 80.8 19.0 0.2 100.0 783 76.7 3.2 7.0 13.0 0.0 100.0 149 50-54 0.0 83.3 16.2 0.5 100.0 796 79.9 5.7 4.4 8.9 1.0 100.0 129 55-59 0.0 88.5 10.5 1.0 100.0 650 78.3 6.3 5.8 9.7 0.0 100.0 68 60-64 0.0 92.5 5.9 1.6 100.0 715 75.0 2.7 5.3 17.0 0.0 100.0 42 65+ 0.0 93.4 5.4 1.2 100.0 1,220 75.8 8.5 5.6 8.5 1.6 100.0 66 Residence1 Urban 14.1 57.5 27.5 0.9 100.0 5,072 89.5 1.6 0.6 6.8 1.4 100.0 1,394 Asmara 13.7 52.7 32.3 1.3 100.0 2,596 90.4 0.6 0.1 7.2 1.6 100.0 840 Other towns 14.5 62.6 22.4 0.6 100.0 2,476 88.1 3.2 1.4 6.2 1.1 100.0 554 Rural 5.7 84.4 9.5 0.4 100.0 6,684 67.7 4.9 6.6 19.2 1.6 100.0 634 Zoba1 Debubawi Keih Bahri 7.4 58.1 34.4 0.2 100.0 409 58.8 0.6 0.3 40.2 0.1 100.0 141 Maekel 13.6 55.3 30.0 1.1 100.0 3,202 89.0 1.2 0.3 7.5 1.9 100.0 961 Semenawi Keih Bahri 5.5 84.1 9.4 0.9 100.0 1,458 84.4 4.5 1.3 9.8 0.0 100.0 138 Anseba 10.8 82.2 6.9 0.1 100.0 1,421 76.8 4.0 13.3 4.9 1.0 100.0 98 Gash-Barka 3.5 83.9 11.9 0.7 100.0 2,012 81.9 1.6 5.2 9.1 2.3 100.0 239 Debub 9.9 76.0 13.8 0.3 100.0 3,255 77.6 6.1 4.5 10.6 1.1 100.0 451 Population age 10+ 20.5 64.8 13.2 1.5 100.0 16,170 81.6 2.9 2.6 11.2 1.7 100.0 2,134 Population age 15+ 8.4 74.8 16.1 0.7 100.0 12,986 82.4 2.9 2.6 10.6 1.5 100.0 2,093 Population age 10-64 22.1 62.5 13.8 1.6 100.0 14,941 81.8 2.8 2.5 11.3 1.7 100.0 2,068 Population age 15-64 9.3 72.8 17.2 0.6 100.0 11,756 82.7 2.7 2.5 10.7 1.5 100.0 2,028 Note: The populations age 10 and over and age 15 and over include 9 women with missing information on age. 1 Based on women age 15-64 Characteristics of Households and Household Members | 23 Table 2.7.2 Employment status: men Percent distribution of the de jure male household population age 10 and over by employment status and type of earnings, according to background charac- teristics, Eritrea 2002 Employment status Type of earnings Background characteristic Not em- ployed, in school Not em- ployed in past month Employed in past month Missing Total Number of men Cash In-kind Both cash and in-kind Not paid Missing Total Total employed men Age 10-14 76.7 15.5 3.9 3.9 100.0 3,158 31.2 13.1 7.8 43.8 4.1 100.0 122 15-19 63.2 13.4 23.0 0.5 100.0 2,416 60.4 5.1 11.8 21.2 1.5 100.0 555 20-24 19.7 11.4 68.5 0.4 100.0 1,539 76.9 1.1 6.0 13.3 2.8 100.0 1,054 25-29 0.0 10.5 89.2 0.3 100.0 1,424 77.4 1.3 4.5 14.3 2.5 100.0 1,270 30-34 0.0 6.7 93.2 0.1 100.0 1,166 79.2 1.4 8.4 9.8 1.2 100.0 1,087 35-39 0.0 8.0 91.9 0.1 100.0 910 79.6 1.5 9.6 8.3 1.0 100.0 836 40-44 0.0 8.5 91.4 0.1 100.0 898 72.2 4.5 12.7 8.4 2.1 100.0 821 45-49 0.0 10.0 90.0 0.0 100.0 704 71.9 5.3 13.3 8.3 1.2 100.0 633 50-54 0.0 12.9 87.1 0.0 100.0 814 61.8 7.3 21.3 8.3 1.4 100.0 709 55-59 0.0 13.9 86.1 0.0 100.0 567 54.3 11.2 21.8 11.6 1.0 100.0 489 60-64 0.0 24.8 75.2 0.0 100.0 673 47.0 11.3 27.7 11.9 2.1 100.0 506 65+ 0.0 52.2 47.5 0.3 100.0 1,427 36.3 14.9 32.2 13.7 2.8 100.0 678 Residence1 Urban 19.2 10.9 69.6 0.3 100.0 4,568 85.0 0.9 1.3 11.0 1.7 100.0 3,179 Asmara 14.6 12.2 72.7 0.5 100.0 2,217 82.2 0.3 0.0 14.9 2.6 100.0 1,613 Other towns 23.5 9.6 66.6 0.2 100.0 2,352 88.0 1.5 2.7 7.1 0.7 100.0 1,566 Rural 14.6 12.2 73.1 0.1 100.0 6,542 61.5 6.0 18.8 11.7 1.9 100.0 4,781 Zoba1 Debubawi Keih Bahri 10.7 11.9 77.2 0.2 100.0 345 77.7 0.1 0.2 21.4 0.7 100.0 266 Maekel 16.2 12.1 71.4 0.4 100.0 2,810 80.4 0.9 0.4 15.4 2.9 100.0 2,005 Semenawi Keih Bahri 16.5 12.9 70.3 0.3 100.0 1,327 67.7 6.1 15.9 8.7 1.6 100.0 933 Anseba 18.5 11.0 70.5 0.0 100.0 1,436 64.7 0.8 30.3 3.1 1.1 100.0 1,013 Gash-Barka 11.5 13.3 74.9 0.2 100.0 2,150 59.1 5.7 22.9 10.1 2.1 100.0 1,611 Debub 19.9 9.9 70.1 0.2 100.0 3,042 74.5 6.6 5.2 12.7 1.0 100.0 2,131 Population age 10+ 27.1 16.2 55.8 1.0 100.0 15,710 67.7 5.0 13.4 12.1 1.9 100.0 8,765 Population age 15+ 14.6 16.3 68.9 0.2 100.0 12,552 68.2 4.8 13.5 11.6 1.9 100.0 8,642 Population age 10-64 29.8 12.5 56.6 1.0 100.0 14,268 70.3 4.1 11.8 11.9 1.8 100.0 8,082 Population age 15-64 16.5 11.7 71.6 0.2 100.0 11,110 70.9 4.0 11.9 11.5 1.8 100.0 7,960 Note: The populations age 10 and over and age 15 and over include 15 men with missing information on age. 1 Based on men age 15-64 Differentials in employment status by residence and zoba are examined for persons age 15-64, the age considered economically active in Eritrea. There is a slight difference in the level of current employment for males by urban-rural residence, with rural males more likely to be employed than urban males. However, rural males and males living in Asmara have the same level of employment (73 percent). In contrast, females are almost three times as likely to be employed in urban areas as in rural areas. However, females are also most likely to be employed in Asmara than in other areas. By zoba, the highest levels of both female and male employment are in zoba Debubawi Keih Bahri (34 percent and 77 percent, respectively). The differentials by zoba in male employment are small; at least 70 percent of males are employed in all zobas. The differentials in female employment are marked: one-third of females in Debubawi Keih Bahri are currently employed, compared with only 7 percent in Anseba. A substantial majority of employed females and males age 15-64 reported that they earn only cash (83 percent and 71 percent, respectively), and 3 percent of females and 12 percent of males reported that they receive cash 24 | Characteristics of Households and Household Members plus some payment in kind. Men and women employed in rural areas and in zobas Anseba and Gash- Barka are more likely to be paid in cash and in-kind than other men and women. Thus, there are only small differences in the proportion of employed persons receiving some cash by residence and zoba. 2.7 HOUSING CHARACTERISTICS In the Household Questionnaire, respondents were asked about characteristics of their households, including access to electricity, source of drinking water, time to water source, time at water source, type of toilet facilities, fuel used for cooking, main flooring material, and number of rooms used for sleeping. Table 2.8 summarizes this information by residence. In Eritrea, 32 percent of the households have electricity, a substantial increase from 23 percent in 1995. However, there has been almost no increase in households with electricity in rural areas. Only 3 percent of rural households have electricity, compared with 78 percent of urban households—almost all households in Asmara and 61 percent of households in other towns. Information on a household’s source of drinking water is important because potentially fatal diseases including typhoid, cholera, and dysentery are prevalent in unprotected water sources. Sources of water expected to be relatively free of these diseases are piped water, water drawn from protected wells, and water delivered by tanker trucks. Piped water is mainly accessible in urban areas; seven in ten households in Asmara, more than six in ten in other towns, and 18 percent (all from public tap) in rural areas use piped water. Around one-fourth of households in Asmara and other towns depend on tanker trucks to deliver water. More than half of households in rural areas have access to public wells (half of them protected and the other half unprotected) and 17 percent use spring water. Overall, half of rural households have access to clean water. The accessibility to water is reflected by the time required to get to the water source. At least 50 percent of urban households have water available in the dwelling or yard and 69 percent are within 15 minutes of a water source. In contrast, only 8 percent of rural households are within 15 minutes to a water source, and more than half spend at least an hour to reach water. Respondents were asked about the waiting time at the source of water, excluding the time to go to and come back from the water source. For 57 percent of households there is no wait at the water source. But one in nine households in urban areas and almost one in four households in rural areas wait at least an hour at the water source. Access to adequate sanitation facilities is an important determinant of health conditions. Three- fourths of households in Eritrea, and almost all households in rural areas (96 percent) have no toilet facility. Half of the households in other towns and slightly more than one-fourth of those in Asmara also do not have any toilet facility. Figure 2.4 shows that since 1995 access to flush toilets in Eritrea has increased from 12 percent to 17 percent, mainly because of better toilet facilities in other towns. Several types of fuel are used for cooking in Eritrea. More than half of the households (59 percent) use wood or straw for cooking, 28 percent use kerosene, and 5 percent each depend on animal dung cakes and gas. Regarding urban-rural variation, wood or straw is more commonly used for cooking in rural areas (82 percent) than in urban areas (23 percent). In Asmara, most households use either kerosene (70 percent) or gas (22 percent) as fuel for cooking. The type of material used for flooring is an indicator of the economic standing of the household as well as the potential exposure of household members to disease-causing agent. According to Table 2.8, two-thirds of households in Eritrea live in structures with floors made of earth, sand or dung, 20 percent have floors made of cement, and 13 percent have ceramic tile floors. The flooring material differs considerably by place of residence. Rural houses have poorer quality floors than urban houses (89 percent Characteristics of Households and Household Members | 25 Table 2.8 Household characteristics Percent distribution of households by household characteristics, according to resi- dence, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban –––––––––––––––––––––– Total Other Characteristic urban Asmara towns Rural Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Electricity Yes 78.3 98.7 60.9 3.0 32.2 No 21.7 1.3 39.1 96.9 67.8 Total 100.0 100.0 100.0 100.0 100.0 Source of drinking water Piped into residence/yard/plot 41.9 56.9 29.0 0.1 16.3 Public tap 25.1 15.1 33.8 18.1 20.8 Unprotected well in dwelling/ yard/plot 0.1 0.0 0.2 0.6 0.4 Unprotected public well 2.1 0.0 3.9 24.7 15.9 Protected well in dwelling/ yard/plot 0.3 0.0 0.5 0.4 0.4 Protected public well 4.2 0.2 7.6 26.3 17.8 Spring 0.3 0.0 0.6 17.2 10.7 River, stream 0.2 0.0 0.3 4.8 3.0 Pond, lake 0.1 0.0 0.1 1.4 0.9 Dam 0.1 0.0 0.2 2.3 1.5 Tanker truck 25.5 27.7 23.6 3.8 12.2 Total 100.0 100.0 100.0 100.0 100.0 Time to water source Percentage <15 minutes 68.7 80.9 58.3 8.2 31.6 Median time to source 0.0 0.0 0.0 59.7 29.9 Normal wait at water source None 72.5 81.1 65.2 47.9 57.4 <5 min 0.4 0.6 0.3 0.0 0.2 5-14 min 3.7 2.7 4.7 4.2 4.0 15-29 min 5.4 3.1 7.5 7.8 6.9 30-44 min 6.3 4.1 8.1 15.4 11.9 45-59 min 0.6 0.4 0.7 0.7 0.7 60+ min 11.1 8.1 13.6 23.8 18.9 Total 100.0 100.0 100.0 100.0 100.0 Sanitation facility Own flush toilet 23.0 32.2 15.1 0.4 9.1 Shared flush toilet 18.8 29.6 9.5 0.3 7.5 Traditional pit toilet 15.6 8.4 21.7 1.3 6.8 Ventilated improved pit latrine 3.2 2.7 3.6 1.5 2.2 No facility, bush, field 39.4 27.0 50.1 96.4 74.3 Other 0.0 0.0 0.1 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 Fuel used for cooking Gas 11.9 21.9 3.3 0.2 4.7 Electricity 1.6 3.0 0.4 0.0 0.6 Kerosene 58.2 70.3 47.9 8.9 28.0 Charcoal/coal 3.0 0.4 5.2 0.9 1.7 Wood, straw 23.4 3.0 41.0 82.1 59.4 Animal dung cakes 1.2 0.8 1.5 7.7 5.2 Other 0.5 0.4 0.6 0.1 0.2 Missing 0.2 0.3 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 continued 26 | Characteristics of Households and Household Members Table 2.8 Household characteristics (cont.) Percent distribution of households by household characteristics, according to resi- dence, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban –––––––––––––––––––––– Total Other Characteristic urban Asmara towns Rural Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Flooring material Earth, sand 31.6 12.6 47.9 75.4 58.5 Dung 1.3 0.3 2.1 13.5 8.7 Wood planks 0.1 0.1 0.0 0.0 0.0 Parquet, polished wood 0.1 0.1 0.0 0.0 0.0 Vinyl, asphalt strips 0.6 1.2 0.2 0.0 0.2 Ceramic tiles 30.6 50.1 13.9 1.2 12.6 Cement 35.3 35.3 35.4 9.8 19.7 Carpet 0.4 0.3 0.5 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 Persons per room <3 40.8 46.5 36.0 26.0 31.7 3-4 32.7 28.6 36.3 33.8 33.4 5-6 16.7 15.1 18.1 22.5 20.3 7+ 9.7 9.8 9.6 17.7 14.6 Total 100.0 100.0 100.0 100.0 100.0 Mean number of persons per room 3.4 3.2 3.5 4.2 3.9 Persons per sleeping room <3 31.8 36.3 27.9 21.8 25.7 3-4 36.5 34.6 38.2 33.3 34.6 5-6 20.0 18.0 21.8 24.4 22.7 7+ 11.7 11.2 12.1 20.4 17.0 Total 100.0 100.0 100.0 100.0 100.0 Mean number of persons per sleeping room 3.8 3.6 3.9 4.5 4.2 Farm animals in living area 1.1 0.7 1.4 5.9 4.1 Wealth index Lowest 0.8 0.0 1.4 26.1 16.3 Second 3.2 0.0 5.9 31.3 20.4 Middle 9.6 0.1 17.7 29.4 21.7 Fourth 35.3 25.9 43.4 12.6 21.4 Highest 51.1 74.0 31.6 0.5 20.1 Total 100.0 100.0 100.0 100.0 100.0 Number of households 3,634 1,678 1,956 5,755 9,389 Characteristics of Households and Household Members | 27 EDHS 2002 Figure 2.4 Access to Clean Water and Flush Toilet 22 12 37 17 Clean water supply (piped) Flush toilet 0 10 20 30 40 50 Percentage of households 1995 2002 EDHS 1995 and EDHS 2002 of rural households have earth, sand or dung floors, while 66 percent of urban houses have cement or ceramic tile floors). In Asmara, floors in half the households are made of ceramic tiles, one-third have cement floors, and one in ten has flooring made of lesser quality materials. Compared with the quality of flooring in 1995, some improvement is evident. For example, the proportion of households with floors made of earth or sand decreased from 69 to 59 percent, the proportion of households with floors made of ceramic tiles increased from 9 to 13 percent, and the proportion of households with cement floors more than doubled from 9 percent to 20 percent. The increase in households with floors made of cement is almost entirely due to improvement in housing in rural areas. Information on the total number of rooms (excluding toilets and kitchens) and sleeping rooms was collected to measure household crowding. Overall, one-third of households have less than 3 persons per room and the same proportion have 3-4 persons per room. Crowding is more common in rural areas than urban areas. For example, 10 percent of the households in urban areas have 7 or more persons per room, compared with 18 percent in rural areas. The mean number of persons per room and per sleeping room in rural areas is 4.2 and 4.5, respectively; in urban areas, it is 3.4 and 3.8, respectively. The presence of farm animals in the living area increases crowding, pollutes the living area, and exposes household members to disease-causing agents. In Eritrea, farm animals in the living area are not common; only 4 percent of households have farm animals in their living areas. The problem is more common among rural households (6 percent) than urban households (1 percent). The wealth index is discussed in Section 2.4 (page 19). Table 2.8 shows that the proportion of households in the lowest quintile is 16 percent and the proportion of households in the other quintiles is nearly the same, 20-22 percent. Regarding differences by residence, more than half of urban households (51 percent) are in the highest quintile of the wealth index, compared with only 1 percent of rural households. This difference in wealth is a result of rural areas not having access to many of the amenities common in urban areas, such as electricity and piped water. In contrast, only 4 percent of urban households are in the two lowest quintiles of the wealth index. All households in Asmara are in the higher quintiles of the wealth indexthree-fourths in the highest quintile and the remaining in the fourth 28 | Characteristics of Households and Household Members quintile. This is not surprising because of the concentration of amenities in the city (Table 2.8). Households in Asmara are also most likely to own various durable goods and transportation vehicles (Table 2.9). 2.8 HOUSEHOLD POSSESSIONS Information on household possession of durable goods and means of transportation is presented in Table 2.9. Combined with other indicators, information on ownership of durable goods can be used to generate a wealth index that acts as a proxy estimate for the socioeconomic status of a household. Ownership of a radio or television is a measure of access to mass media; telephone ownership measures access to efficient communications; refrigerator ownership indicates a capacity for more hygienic storage. Bicycle, motorcycle, car, and donkey cart ownership reflects access to means of transportation. In general, ownership of these items has a bearing on the households’ access to health information and services. Possession of the durable goods mentioned above is not common in Eritrea. Six in ten households in Eritrea own a radio–81 percent of urban households and 43 percent of rural households. Radio ownership is almost universal in Asmara and very high in zoba Maekel. Less than half the households in zobas Anseba, Gash-Barka, and Semenawi Keih Bahri have radios. A household in zoba Gash-Barka is even less likely to have a radio than a household in rural areas. Basically, television is only in urban areas (34 percent), and zobas Maekel (46 percent) and Debubawi Keih Bahri (18 percent). Fifty-seven percent of households in Asmara have television. Overall, four in ten households in Eritrea have no television or radio. Four percent of households have a telephone and 7 percent own a refrigerator. These amenities are almost exclusively in urban areas and zobas Maekel and Debubawi Keih Bahri. Regarding ownership of any means of transportation, 87 percent of the households do not own any means of transportation. Table 2.9 Household durable goods Percentage of households possessing various durable consumer goods and transport vehicles, by residence and zoba, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Zoba –––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––––– Debubawi Semenawi Durable Total Other Keih Keih Gash- goods/vehicles urban Asmara towns Rural Bahri Maekel Bahri Anseba Barka Debub Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Durable consumer goods Radio 81.3 93.4 71.0 42.9 50.5 89.3 43.8 46.7 36.7 58.8 57.8 Television 33.6 57.4 13.2 0.3 17.6 46.2 4.5 4.6 0.6 3.0 13.2 Telephone 11.3 18.5 5.1 0.1 4.6 14.7 1.6 3.1 0.3 1.0 4.4 Refrigerator 18.2 25.7 11.8 0.1 35.2 20.4 4.5 2.5 0.8 0.9 7.1 No mass media1 18.1 6.0 28.6 57.1 47.9 10.1 56.0 53.2 63.2 41.2 42.0 Transport vehicles Donkey cart 1.9 1.4 2.3 0.4 0.6 1.6 0.2 0.2 2.4 0.3 1.0 Bicycle 19.4 29.0 11.2 4.9 6.2 29.6 2.4 3.8 2.4 8.0 10.5 Motorcycle 0.5 0.8 0.2 0.0 0.0 0.7 0.1 0.0 0.0 0.1 0.2 Car/truck 7.9 14.5 2.3 0.4 3.0 11.8 1.8 0.8 0.4 0.6 3.3 None of the above 73.9 60.7 85.2 94.6 90.6 62.0 95.9 95.6 95.7 91.3 86.6 Total 3,634 1,678 1,956 5,755 328 2,122 1,195 1,181 1,800 2,763 9,389 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 No radio or television Characteristics of Households and Household Members | 29 Bicycles are the most common means of transportation; one in ten households owns a bicycle. Only 3 percent of households own a car or a truck. Not surprisingly, households in urban areas, in Asmara, and zoba Maekel are more likely to own durable consumer goods and means of transportation. Ownership of durable consumer goods and means of transportation has increased since 1995. For example, the proportion of households with radios has increased from 40 to 58 percent and the proportion of households that have a bicycle has increased from 7 to 11 percent. Respondents to the Household Questionnaire were asked whether they owned the house they lived in, whether they owned animals and cropland, and whether they grew cash crops. Seven in ten households own a house, 56 percent own cropland, and almost half of the households own animals (Table 2.10). Possession of livestock, a house, and cropland is more concentrated in rural areas than urban areas. For example, nine in ten rural households own a house, compared with only two in five urban households. Two-thirds of rural households own animals, half own horses, mules, or donkeys, four in ten own sheep or goats, and the same proportion own cattle or camels. Four percent of households in rural areas and 2 percent in other towns grow cash crop. Table 2.10 Household ownership of a house, animals and cropland Percentage of households owning a house, animals, and cropland, and percentage of households that grow cash crops, by residence, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Total Other Ownership urban Asmara towns Rural Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– House 42.2 28.8 53.7 88.2 70.4 Any animals 12.6 1.2 22.4 68.8 47.0 Cattle or camel 5.2 0.9 9.0 41.6 27.5 Horse, mule, or donkey 7.4 0.8 13.0 49.5 33.2 Sheep or goat 6.9 0.3 12.6 38.9 26.6 Cropland 17.6 4.4 28.9 80.8 56.4 Grow cash crops 1.1 0.2 1.8 3.8 2.7 Total 3,634 1,678 1,956 5,755 9,389 2.9 MOSQUITO NETS Malaria is endemic and is a major public health problem in Eritrea. Use of mosquito nets is one of the methods to prevent malaria. The global Roll Back Malaria (RBM) movement, which Eritrea endorsed, has set the framework within which the country is implementing malaria control. In the 2002 EDHS, information on the possession of mosquito nets by households was collected in the Household Questionnaire. Table 2.11 shows the distribution of households by number of mosquito nets, according to household characteristics. One-third of households reported owning at least one mosquito net. The likelihood of possessing at least two mosquito nets increases with household size. For example, one-fifth of large households (nine members or more) have at least two mosquito nets, compared with only 8 percent of households with three members. 30 | Characteristics of Households and Household Members Table 2.11 Household possession of mosquito nets Percent distribution of households by number of mosquito nets present in household, percentage with at least one net, and mean number of nets per household, by household size, residence, and zoba, Eritrea 2002 Number of mosquito nets in household Household characteristic None One Two Three or more Total Number of households Percentage with at least one net Mean number of mosquito nets per household (for households with mosquito nets) Household size 1 80.9 17.4 1.7 0.0 100.0 676 19.1 1.1 2 75.6 18.2 5.7 0.5 100.0 1,144 24.4 1.3 3 66.3 25.3 7.1 1.3 100.0 1,407 33.7 1.3 4 63.3 23.4 10.9 2.5 100.0 1,480 36.7 1.4 5 61.1 21.2 13.8 3.9 100.0 1,259 38.6 1.6 6 61.2 21.0 12.0 5.8 100.0 1,176 38.8 1.7 7 63.6 15.9 12.6 8.0 100.0 880 36.4 1.9 8 63.8 17.6 10.4 8.2 100.0 603 36.2 1.9 9+ 64.9 16.2 10.9 8.0 100.0 763 35.1 2.0 Residence Urban 71.7 15.7 8.7 3.9 100.0 3,634 28.3 1.7 Asmara 91.2 6.5 1.9 0.3 100.0 1,678 8.8 1.3 Other towns 54.9 23.6 14.5 7.0 100.0 1,956 45.1 1.7 Rural 62.6 23.3 10.3 3.8 100.0 5,755 37.3 1.5 Zoba Debubawi Keih Bahri 71.4 19.5 6.8 2.3 100.0 328 28.6 1.4 Maekel 91.3 6.5 2.0 0.3 100.0 2,122 8.7 1.3 Semenawi Keih Bahri 57.3 23.0 13.3 6.5 100.0 1,195 42.6 1.7 Anseba 55.3 25.1 15.2 4.4 100.0 1,181 44.6 1.6 Gash-Barka 46.8 27.5 15.9 9.7 100.0 1,800 53.1 1.8 Debub 67.2 23.3 7.9 1.5 100.0 2,763 32.7 1.3 Total 66.1 20.3 9.7 3.8 100.0 9,389 33.8 1.6 Possession of mosquito nets is more common in rural areas (37 percent) than urban areas (28 percent), but it is most common in small towns (45 percent). Mosquito nets are less likely to be available in households in zoba Maekel than in the other zobas, probably because it is not a high-risk malaria area. Households in zobas Gash-Barka, Anseba, and Semenawi Keih Bahri are more likely to own at least one mosquito net than households in the other two zobas. Smaller households with one or two members (19-24 percent) are less likely to possess a mosquito net than larger households (34-39 percent). Among households with mosquito nets, the mean number of nets is 1.6. Although crowding is greater in rural areas (Table 2.2), the mean number of mosquito nets in rural households is smaller than in urban areas. The use of mosquito nets by women age 15-49 and by their children under age five is discussed in Chapter 9. Chapter 9 also discusses intermittent treatment for malaria among women age 15-49 during the last pregnancy ending in a live birth. Women’s Characteristics and Status | 31 WOMEN’S CHARACTERISTICS AND STATUS 3 This chapter provides a demographic and socioeconomic profile of women of reproductive age who were interviewed in the 2002 EDHS. The information is essential for the interpretation of findings later in the report. The chapter starts by presenting a number of basic characteristics of women including age, marital status, residence, educational level, religion, ethnicity, and wealth status. Next, information on women’s migration status, and more detailed information on educational attainment, literacy status, and the extent of exposure to mass media are provided. Finally, factors that enhance women’s empowerment are explored, including employment status, occupation, earnings, and continuity of employment as well as women’s participation in household decisionmaking and their attitudes toward wife beating. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Background characteristics of all women and currently married women age 15-49 interviewed in the 2002 EDHS are presented in Table 3.1. Reflecting the results of high fertility levels in the past, there are proportionally more younger than older women and the proportion of respondents in each age group generally declines as age increases for all women. Sixty-two percent of all women were currently married at the time of the survey, with an additional 4 percent in informal marriages (“living together”). About one-fourth of women age 15-49 have never married. Seven percent of women are divorced or separated, while 4 percent are widowed. In all other tables in this report, the categories “married” and “living together” are combined and referred to collectively as “currently married.” As expected, most women reside in rural areas (57 percent of all women and 66 percent of currently married women). Just over one-fifth of all women reside in Asmara, with the same proportion residing in other towns. The largest proportions of women live in three zobas: Debub (27 percent), Maekel (26 percent), and Gash-Barka (17 percent). Only 4 percent live in zoba Debubawi Keih Bahri. Similar distribution patterns by residence and zoba are observed for currently married women. Table 3.1 shows that half of all women 15-49 have never attended school, while one-fifth have attained primary school only, one-tenth have attained middle school only, and one-fifth have been to secondary school or higher. As expected, currently married women are less likely to have attended school and less likely to have attained higher levels of education than the broader category of all women. Improvements in female education are reflected at all levels of education. For example, the proportion of women age 15-49 who have attended secondary school doubled from 10 percent in 1995 to 20 percent in 2002. Similarly, the proportion of women with no education declined from 66 to 50 percent in the same period. As regards religious affiliation, almost six in ten women (58 percent) are Orthodox, 37 percent are Muslim, and 5 percent are Catholic. Respondents are predominantly Tigrigna (62 percent of all women), followed by Tigre (22 percent). Since the wealth index classifies households into quintiles according to their assets and other economic characteristics, by definition there are roughly equal proportions of women falling into each category of the wealth index. 32 | Women’s Characteristics and Status Table 3.1 Background characteristics of respondents Percent distribution of all women and currently married women by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– All women Currently married women –––––––––––––––––––––––––––––––––– –––––––––––––––––––––––––––––––––––– Number of women Number of women ––––––––––––––––––––– ––––––––––––––––––––– Background Weighted Un- Weighted Un- characteristic percent Weighted weighted percent Weighted weighted ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 22.9 2,001 1,861 10.1 580 552 20-24 16.6 1,454 1,386 16.6 950 956 25-29 17.6 1,543 1,558 21.1 1,212 1,252 30-34 12.7 1,109 1,175 15.8 904 992 35-39 12.4 1,085 1,129 15.7 899 946 40-44 9.5 827 876 11.6 663 711 45-49 8.4 734 769 9.2 526 561 Marital status Never married 23.3 2,044 1,851 na na na Married 61.8 5,409 5,682 94.4 5,409 5,682 Living together 3.7 324 288 5.6 324 288 Divorced/separated 7.4 650 592 na na na Widowed 3.7 328 341 na na na Residence Total urban 43.0 3,767 3,180 34.3 1,967 1,719 Asmara 21.7 1,899 1,123 15.1 868 505 Other towns 21.3 1,868 2,057 19.2 1,099 1,214 Rural 57.0 4,987 5,574 65.7 3,766 4,251 Zoba Debubawi Keih Bahri 3.7 324 1,470 3.7 210 1,005 Maekel 25.9 2,264 1,404 19.2 1,103 689 Semenawi Keih Bahri 13.1 1,148 1,416 14.3 817 1,027 Anseba 12.9 1,130 1,418 13.7 784 1,003 Gash-Barka 17.1 1,500 1,414 19.9 1,142 1,072 Debub 27.3 2,388 1,632 29.3 1,677 1,174 Education No education 50.1 4,384 5,098 61.9 3,549 4,126 Primary 18.7 1,637 1,506 18.8 1,075 961 Middle 11.1 974 831 7.0 400 340 Secondary + 20.1 1,760 1,319 12.4 709 543 Religion Orthodox 57.7 5,048 3,946 52.5 3,009 2,393 Catholic 4.6 400 390 4.0 228 228 Protestant 0.7 60 45 0.5 27 22 Muslim 36.5 3,198 4,319 42.6 2,443 3,293 Traditional believer 0.4 33 42 0.4 23 31 Other 0.1 12 8 0.0 0 0 Missing 0.1 5 4 0.0 3 3 Ethnicity Afar 2.9 254 1,033 3.0 174 752 Bilen 2.7 233 285 2.5 145 179 Hedarib 2.1 187 292 2.6 151 228 Kunama 1.5 132 135 1.3 77 80 Nara 2.0 174 142 2.2 124 101 Rashaida 0.5 47 72 0.6 36 55 Saho 3.6 313 324 4.5 257 266 Tigre 22.2 1,940 2,129 26.7 1,533 1,677 Tigrigna 61.9 5,422 4,218 55.9 3,206 2,546 Amhara 0.4 36 97 0.4 23 69 Other 0.2 17 27 0.1 9 17 Wealth index Lowest 16.8 1,472 1,709 20.3 1,161 1,342 Second 18.6 1,626 2,000 21.2 1,215 1,513 Middle 19.1 1,674 1,815 21.4 1,224 1,344 Fourth 20.9 1,833 1,404 18.8 1,079 832 Highest 24.6 2,149 1,826 18.4 1,053 939 Total 100.0 8,754 8,754 100.0 5,733 5,970 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na=Not applicable Women’s Characteristics and Status | 33 3.2 WOMEN’S MIGRATION In the 2002 EDHS, the migration status of women age 15-49 was determined on the basis of duration of continuous residence. Information on continuous residence was obtained by asking each woman the number of years she continuously lived in the place where she was living at the time of the survey. The duration of stay was recorded in completed years. From this information, it is possible to classify women as migrants or non-migrants. All women except those who have lived at the place of interview continuously since birth are considered migrants. Migrant women were asked whether they had lived in a city, town, or village just before they moved to the current place of residence and in which zoba they lived just before moving to the place of interview. Finally, they were asked the main reason for their move. Table 3.2 shows that 54 percent of women can be considered migrants. As might be expected, older women are more likely to have moved than younger women. The percentage of migrants is higher among urban women (63 percent) than rural women (47 percent), though Asmara has a lower proportion of migrant women than other towns (56 vs. 70 percent). By zoba, the highest percentage of migrants is in zoba Debub (61 percent) and the lowest is in zoba Semenawi Keih Bahri (43 percent). Women with no education or only primary school are somewhat more likely to have moved than those with more education, most probably because they tend to be older. Women in the higher quintiles of the wealth index are generally more likely to have moved than women who are in the lower quintiles. Table 3.2 indicates that the major reason for women’s migration is marriage (41 percent). This reason is most common among migrant women who reside in rural areas (60 percent) and zoba Debub (61 percent), as well as those with no formal education (54 percent) and those who fall in the two lower wealth quintiles (60-61 percent). War-related reasons (war, insecurity, deportation, and internal displacement) are the next most frequently cited reason (14 percent) for migration, followed by employment (13 percent) and housing (11 percent). War-related reasons for moving are more commonly cited by teenage women, women in Gash-Barka, and those who have some secondary education. Employment is mentioned as the main reason for moving among urban women, women in zoba Debubawi Keih Bahri and women in the highest wealth quintile. Not surprisingly, the proportion of those migrating because of education is highest among migrants who are young (21 percent), those with secondary or higher education (18 percent), and those who moved to Asmara (11 percent) and zoba Maekel (10 percent). The first column of Table 3.3 shows that the major type of female migration in Eritrea is rural- rural migration, which constitutes 40 percent of total migration. The next most common type of migration is urban-urban migration (28 percent). Surprisingly, rural-urban migration—the major form of migration in most developing countries—accounts for only one-fifth of total female migration in Eritrea. With the exception of urban-urban migration, marriage is the predominant reason for all forms of migration (Table 3.3), particularly for rural-rural migration. While rural women mainly migrate to urban areas for reasons relating to marriage, employment, and education, those who move from one urban area to another tend to do so for a broader variety of reasons, including almost equally war-related reasons, liberation, a better home, employment, and marriage. Information on migration streams both within and between zobas is presented in Table 3.4. Migration from one place to another within the same zoba (shown in bold figures in Table 3.4) is the major form of migration in all zobas except zoba Debubawi Keih Bahri. This intra-zoba migration is particularly pronounced in zoba Debub, where nearly four in five female migrants came from other areas within the zoba. 34 | Women’s Characteristics and Status Table 3.2 Reasons for migration by background characteristics Percentage of all women who have ever moved from their place of birth and percent distribution of these migrants by the main reason for migrating, according to background characteristics, Eritrea 2002 Migration Reason for migration Background characteristics Per- centage who mig- rated Number of women Libera- tion War- related reasons Drought, deforest- ation, famine Employ- ment Edu- cation Mar- riage Better home Other Missing Total Number of women migrants Age 15-19 36.8 2,001 13.4 22.1 0.6 9.5 21.4 17.1 13.3 2.3 0.3 100.0 737 20-24 51.2 1,454 9.2 16.8 1.2 12.0 4.9 42.0 10.2 3.3 0.3 100.0 744 25-29 56.3 1,543 7.1 12.5 1.5 16.2 3.7 45.3 11.9 1.7 0.2 100.0 869 30-34 59.9 1,109 12.0 11.1 2.1 13.0 2.0 47.2 9.8 2.7 0.2 100.0 664 35-39 66.2 1,085 12.3 12.7 1.9 13.0 3.0 42.6 12.0 2.2 0.2 100.0 719 40-44 62.3 827 12.1 11.4 2.3 14.5 3.3 45.3 9.8 1.1 0.0 100.0 515 45-49 65.1 734 6.7 12.8 2.9 13.2 1.5 49.4 12.5 0.9 0.0 100.0 478 Residence Urban 62.8 3,767 14.3 16.6 1.3 20.5 9.4 21.5 13.6 2.5 0.3 100.0 2,364 Asmara 55.9 1,899 12.3 17.8 1.0 19.2 11.1 18.8 17.4 1.8 0.4 100.0 1,062 Other towns 69.7 1,868 16.0 15.5 1.6 21.6 8.0 23.6 10.4 3.0 0.2 100.0 1,302 Rural 47.4 4,987 6.5 12.3 2.0 5.6 2.7 59.9 9.3 1.7 0.1 100.0 2,363 Zoba Debubawi Keih Bahri 43.7 324 7.1 10.7 0.7 37.2 7.1 23.4 5.7 8.2 0.0 100.0 142 Maekel 55.2 2,264 10.7 16.3 1.1 16.4 10.3 25.8 16.8 2.0 0.5 100.0 1,250 Semenawi Keih Bahri 42.9 1,148 15.5 12.1 3.7 16.0 4.5 33.4 12.9 2.0 0.0 100.0 493 Anseba 46.5 1,130 10.9 6.9 2.0 8.9 4.5 53.8 11.1 1.9 0.0 100.0 526 Gash-Barka 57.1 1,500 20.2 23.2 3.5 11.1 3.9 27.3 9.7 1.1 0.0 100.0 857 Debub 61.1 2,388 2.8 11.5 0.5 9.5 4.6 60.6 8.0 2.3 0.1 100.0 1,460 Education No education 55.8 4,384 8.0 12.3 2.8 10.1 1.7 54.1 9.4 1.6 0.0 100.0 2,448 Primary 59.1 1,637 11.6 12.2 0.9 19.3 3.7 37.7 12.4 2.0 0.2 100.0 968 Middle 45.7 974 16.3 17.8 0.3 9.3 11.4 24.6 14.9 4.7 0.7 100.0 445 Secondary + 49.2 1,760 12.9 21.3 0.2 16.3 18.3 14.1 14.2 2.4 0.4 100.0 866 Wealth index Lowest 40.1 1,472 8.2 12.2 3.6 2.5 2.7 60.4 9.1 1.2 0.0 100.0 590 Second 46.5 1,626 8.2 11.8 2.6 3.4 2.4 61.2 9.7 0.7 0.0 100.0 756 Middle 53.6 1,674 11.8 13.4 1.4 6.9 2.3 54.5 7.7 1.8 0.2 100.0 897 Fourth 69.0 1,833 9.1 15.2 1.7 17.8 9.1 29.4 14.2 3.4 0.2 100.0 1,265 Highest 56.8 2,149 13.1 17.0 0.5 23.8 9.5 19.8 13.4 2.5 0.4 100.0 1,220 Total 54.0 8,754 10.4 14.4 1.7 13.1 6.0 40.7 11.4 2.1 0.2 100.0 4,727 Note: Migration is defined as not having always lived in the place of residence at the time of the survey. It is based on the de jure population. Women’s Characteristics and Status | 35 Table 3.3 Reasons for migration by type of migration Percent distribution of female migrants by main reason for migrating, according to type of migration, Eritrea 2002 Reason for migration Type of migration Total Libera- tion War and war-related reasons Drought, deforesta- tion, famine Employ- ment Edu- cation Mar- riage Better home Other Missing Total Number of women migrants Urban-urban 28.0 17.8 21.1 0.7 17.1 4.8 17.1 18.1 2.8 0.4 100.0 1,324 Urban-rural 9.1 16.6 14.7 1.0 11.6 2.7 32.5 16.5 4.5 0.0 100.0 429 Rural- rural 40.0 4.0 11.9 2.3 4.3 2.7 66.1 7.5 1.1 0.1 100.0 1,892 Rural-urban 21.3 9.2 11.1 2.2 25.2 15.3 26.7 8.0 2.2 0.0 100.0 1,006 Abroad/missing 1.6 21.4 4.2 0.5 7.8 5.8 48.9 8.2 1.8 1.4 100.0 77 Total 100.0 10.4 14.4 1.7 13.1 6.0 40.7 11.4 2.1 0.2 100.0 4,727 Table 3.4 Zoba in-migration and out-migration, and immigration from abroad Percent distribution of female migrants by zoba of origin or country of origin, according to zoba of destination, Eritrea 2002 Zoba of destination Zoba/country of origin Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub Total Debubawi Keih Bahri 17.5 1.8 1.6 0.4 0.1 1.1 1.6 Maekel 18.8 40.6 9.2 6.3 2.7 5.3 15.1 Semenawi Keih Bahri 5.1 4.2 48.3 5.0 0.8 3.8 8.2 Anseba 0.9 4.1 6.6 67.9 3.6 0.4 10.1 Gash-Barka 1.3 3.5 1.2 5.6 64.2 1.8 13.9 Debub 19.3 20.7 10.9 2.2 3.8 78.5 32.4 Ethiopia 33.1 19.1 2.7 0.9 2.6 7.7 9.3 Sudan 0.2 2.5 18.2 11.5 21.6 0.7 8.0 Other Africa/Middle East 3.4 1.9 1.2 0.2 0.5 0.4 0.9 Other/missing 0.4 1.6 0.2 0.0 0.0 0.3 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 142 1,250 493 526 857 1,460 4,727 Percentage of in-migrants 3.0 26.4 10.4 11.1 18.1 30.9 100.0 In-migrants from other zobas 64 429 145 103 95 180 1,016 Percent distribution 6.3 42.2 14.3 10.1 9.4 17.7 100.0 Out-migrants into other zobas 49 206 148 122 107 384 1,016 Percent distribution 4.8 20.3 14.6 12.0 10.5 37.8 100.0 Net number of migrants 15 223 -3 -19 -12 -204 0 Immigrants (returnees from abroad) 53 314 110 66 212 132 887 Percent distribution immigrants 6.0 35.4 12.4 7.4 23.9 14.9 100.0 36 | Women’s Characteristics and Status EDHS 2002 Figure 3.1 In-migration and Out-migration by Zoba Debubawi Keih Bahri 6% Maekel 42% Semenawi Keih Bahri 14% Anseba 10% Gash-Barka 9% Debub 18% Debubawi Keih Bahri 5% Maekel 20% Semenawi Keih Bahri 15% Anseba 12% Gash-Barka 11% Debub 38% In-migration Out-migration Migration between zobas is dominated by a major flow originating from zoba Debub (accounting for 38 percent of all out-migrants), followed by zoba Maekel (20 percent) and zoba Semenawi Keih Bahri (15 percent) (Figure 3.1). Zoba Maekel is the most favored zoba for in-migrants from other zobas (42 percent), followed by zoba Debub (18 percent) and zoba Semenawi Keih Bahri (14 percent). The least favored zoba is Debubawi Keih Bahri, receiving only 6 percent of all in-migrants. Comparing the number of internal in- and out-migrants, zoba Maekel experienced the largest net gain due to female migration and zoba Debub experienced the largest net decline. Table 3.4 also shows that nearly one-fifth (18 percent) of female migrants were from abroad, with the largest number coming from Ethiopia (9 percent) and the Sudan (8 percent). Zoba Maekel and zoba Gash-Barka were the most common destinations for migrants from abroad, accounting for 35 percent and 24 percent of international immigrants, respectively. One-third and one-fifth of the total migrants into zoba Debubawi Keih Bahri and zoba Maekel, respectively, were from Ethiopia. Immigrants from the Sudan constituted roughly one-fifth of the total migrants into zoba Gash-Barka and zoba Semenawi Keih Bahri. 3.3 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Table 3.5 shows the percent distribution of respondents by highest level of schooling attended, according to background characteristics. As mentioned previously, about half of the respondents have never attended school and 16 percent have had only some primary schooling. While one-third of Eritrean women 15-49 have completed primary school, only 8 percent have completed secondary education. Younger women are more likely to be educated and to reach higher levels of education than older women. The proportion of women who have never attended school rises rapidly with increasing age. Only one in five women age 15-19 has no formal education, compared with more than three-fourths of women age 45-49. Similarly, 29 percent of women age 15-19 have some secondary or higher education, compared with only 4 percent of women age 45-49. Women’s Characteristics and Status | 37 Table 3.5 Educational attainment by background characteristics Percent distribution of women by highest level of schooling attended or completed, median number of years of schooling, and percent literate, according to background characteristics, Eritrea 2002 Highest level of schooling attended or completed Background characteristic No edu- cation Some primary Com- pleted primary1 Some middle Com- pleted middle2 Some secon- dary Com- pleted secon- dary3 More than secon- dary Total Number of women Median years of schooling Percent literate Age 15-19 21.2 20.8 3.6 22.3 3.2 25.2 3.2 0.6 100.0 2,001 4.6 77.1 20-24 42.2 17.1 2.8 8.3 3.2 15.6 8.8 1.9 100.0 1,454 2.0 56.4 25-29 47.3 16.9 2.7 6.3 2.1 12.7 10.2 1.8 100.0 1,543 0.8 51.7 30-34 65.0 12.8 1.9 4.3 1.2 5.2 7.6 2.1 100.0 1,109 0.0 36.5 35-39 65.4 15.7 1.2 3.6 1.1 4.5 7.5 1.1 100.0 1,085 0.0 34.5 40-44 73.0 12.0 1.4 3.0 1.1 3.6 3.1 2.9 100.0 827 0.0 26.5 45-49 79.3 12.5 1.2 1.8 1.3 1.6 2.1 0.3 100.0 734 0.0 19.4 Residence Total urban 22.7 16.5 3.0 13.0 3.6 24.0 13.9 3.3 100.0 3,767 5.4 76.0 Asmara 11.0 12.9 2.6 11.5 3.9 31.3 21.2 5.4 100.0 1,899 7.3 88.0 Other towns 34.5 20.1 3.4 14.6 3.2 16.5 6.6 1.0 100.0 1,868 3.3 63.7 Rural 70.8 16.2 1.9 5.9 1.1 3.4 0.6 0.1 100.0 4,987 0.0 28.9 Zoba Debubawi Keih Bahri 51.7 11.8 3.6 8.3 3.8 13.0 7.1 0.6 100.0 324 0.0 45.5 Maekel 14.3 14.4 2.9 12.5 3.9 29.2 18.1 4.7 100.0 2,264 6.7 85.0 Semenawi Keih Bahri 71.8 14.1 1.8 4.8 1.8 3.6 1.9 0.2 100.0 1,148 0.0 26.7 Anseba 59.5 18.8 1.4 10.2 1.4 6.8 1.9 0.0 100.0 1,130 0.0 40.4 Gash-Barka 77.3 13.6 1.2 3.3 1.2 2.4 0.7 0.2 100.0 1,500 0.0 21.2 Debub 51.7 20.4 3.2 10.7 1.4 9.0 2.9 0.7 100.0 2,388 0.0 48.1 Wealth Index Lowest 83.0 10.7 0.7 3.8 0.9 0.8 0.0 0.0 100.0 1,472 0.0 17.2 Second 77.5 13.1 1.1 5.3 0.5 2.2 0.2 0.0 100.0 1,626 0.0 21.2 Middle 65.3 20.1 2.2 7.2 1.1 3.6 0.4 0.1 100.0 1,674 0.0 33.6 Fourth 31.0 23.4 4.4 14.3 3.9 17.3 4.8 0.9 100.0 1,833 3.4 68.6 Highest 11.2 13.6 2.9 12.2 3.6 30.2 21.3 5.1 100.0 2,149 7.2 87.6 Total 50.1 16.3 2.4 9.0 2.1 12.3 6.4 1.5 100.0 8,754 0.0 49.1 1 Completed 5 grades in primary level 2 Completed 7 grades in middle level 3 Completed 11 grades in secondary level 38 | Women’s Characteristics and Status The level of education also varies greatly by residence. Women in rural areas are far less likely to be educated than their urban counterparts. Nearly three-fourths (71 percent) of rural women have not attended school, more than three times the proportion of urban women (23 percent). The urban-rural difference is more pronounced at the secondary-school level or higher. Only 4 percent of women in rural areas have attended secondary school, compared with 41 percent of women in urban areas. As expected, women who reside in Asmara have higher levels of educational attainment, especially at the secondary- school level or higher; 58 percent of women in Asmara have some secondary education. By zoba, the proportion of women with no formal education ranges from a high of 77 percent in zoba Gash-Barka to a low of 14 percent in zoba Maekel. Similarly, some secondary education is most common (52 percent) for women who reside in zoba Maekel and least common (3 percent) for women in zoba Gash-Barka. The wealth index exhibits a positive association with women’s educational attainment. Whereas 83 percent of the women in the lowest quintile of the wealth index have never been to school, the proportion for women in the highest quintile is only 11 percent. Less than 1 percent of women in the lowest quintile have at least some secondary education, compared with 57 percent of women in highest quintile. The median number of years of schooling is shown in Table 3.5 for the various subgroups. The figures confirm the above findings: younger women, those living in urban areas, those living in zoba Maekel, and those in the highest quintile of the wealth index have had more years of schooling. Table 3.5 also shows the percentage of women who are literate. Literacy is widely acknowledged as benefiting both the individual and the society and is associated with a number of positive outcomes for health and nutrition. Knowing the distribution of the literate population can help planners—especially in the areas of health and family planning—reach women with their messages. Literacy is increasingly important for taking advantage of day-to-day opportunities. In the 2002 EDHS, literacy was determined by asking respondents if they could read and write in any language without difficulty. This question was asked only to respondents who had never attended school or had attended primary school only; those who had attended middle school or above were assumed to be literate. This approach to measuring literacy is subjective, since no test of ability to read or write was administered. Overall, nearly half of Eritrean women are literate. The level of literacy is much higher for younger women than older women, ranging from a high of 77 percent for women age 15-19 to a low of 19 percent for women age 45-49. Urban women have a higher level of literacy (76 percent) than rural women (29 percent). Literacy levels also vary widely among zobas, with the percent literate more than four times higher in zoba Maekel (85 percent) than in zoba Gash-Barka (21 percent). There are also marked differences in literacy levels by women’s wealth status, ranging from 17 percent of women in the lowest wealth quintile to 88 percent of those in the highest quintile. Women’s Characteristics and Status | 39 3.4 REASONS FOR LEAVING SCHOOL Knowledge of the reasons for leaving school can guide policies aimed at enhancing women’s status in general and the level of women’s educational attainment in particular. Table 3.6 presents the percent distribution of women age 15-24 years who ever attended school but are not currently attending, by their reason for leaving school. Table 3.6 Reason for leaving school by zoba Percent distribution of women age 15-24 who have ever attended school but are not currently attending school by reason for leaving school, according to zoba, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Debubawi Semenawi Keih Keih Gash- Reason Bahri Maekel Bahri Anseba Barka Debub Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Got pregnant 4.8 1.8 0.9 1.4 3.6 1.3 1.8 Got married 27.8 19.3 25.3 43.7 41.4 60.9 38.1 Care for younger children 4.0 4.8 10.3 5.2 4.0 3.6 4.8 Family needed help 3.5 4.0 5.8 9.6 7.3 6.1 5.8 Could not pay school fees 2.1 2.8 2.2 0.7 2.7 1.9 2.2 Needed to earn money 7.2 4.8 3.7 2.2 6.0 1.8 3.7 Finished schooling 13.6 18.1 8.0 1.5 1.8 3.7 9.0 Did not pass entrance exam 13.8 19.8 2.8 3.2 1.1 3.3 9.1 Did not like school 5.5 7.5 6.9 6.5 6.4 2.7 5.7 School too far 2.7 2.1 6.5 1.8 9.6 3.1 3.6 Illness 11.1 12.4 26.2 20.0 11.9 10.9 14.0 Other 3.8 2.6 1.5 4.2 4.1 0.6 2.3 Missing/Don't know 0.0 0.2 0.0 0.0 0.0 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number not attending 33 489 123 156 153 427 1,381 Marriage is the single most important reason for leaving school among Eritrean women age 15- 24. Thirty-eight percent of women in this age group reported marriage as their major reason for leaving school. The next most frequently cited reason was illness (14 percent). Nine percent of women said they left school because they did not pass the entrance exams required to continue, while another 9 percent said they left school because they “finished” schooling. Other reasons cited for leaving school are: family needed help (6 percent), did not like school (6 percent), care for young children (5 percent), and school too far away (4 percent). It is interesting to note that inability to pay school fees and pregnancy are the two least common reasons for leaving school in Eritrea. Marriage is the main reason for leaving school in all zobas, except in zoba Semenawi Keih Bahri and zoba Maekel where “illness” and “did not pass entrance exams,” respectively, are cited more frequently. Sixty-one percent of women who reside in zoba Debub reported that they stopped schooling because they got married, compared with 44 percent of women in zoba Anseba, 41 percent in zoba Gash- Barka, and 28 percent in zoba Debubawi Keih Bahri. The proportion is relatively lower for zobas Maekel and Semenawi Keih Bahri (19 and 25 percent, respectively). Similar to the nation as a whole, illness is the second most frequently cited reason for leaving school in zoba Debub (11 percent), zoba Gash-Barka (12 percent) and zoba Anseba (20 percent). In zobas Debubawi Keih Bahri and Maekel, “finished schooling” and “did not pass entrance exam” are among the important reasons for leaving school. Twenty percent of women in zoba Maekel mentioned that they left school because they were not able to pass the entrance exams, while 18 percent said they left because they had finished schooling. In zoba 40 | Women’s Characteristics and Status Semenawi Keih Bahri, the need to care for younger children, and in zoba Anseba, that the family needed help, are cited fairly frequently. In zoba Gash-Barka, the third most important reason for girls leaving school is that the school is too far away. 3.5 ACCESS TO MASS MEDIA The 2002 EDHS collected information on the exposure of women to broadcast and print media by asking respondents if they usually read newspapers, listen to the radio, or watch television at least once a week. These data are important because they provide an indication of the extent to which Eritrean women are regularly exposed to the mass media, which are extensively used in Eritrea to disseminate reproductive health and other messages to the population. Table 3.7 shows the percentage of women exposed to different types of mass media by selected background characteristics. Overall, 18 percent of women usually access all three media at least once a week. Radio is the most popular medium; nearly three-fourths of women listen to the radio at least once a week, while much smaller proportions read newspapers (28 percent) or watch television (28 percent) weekly. More than one-fourth (26 percent) of women are not regularly exposed to any of these mass media. Access to the three media has increased since the previous EDHS. The proportion of women who listen to a radio at least once a week has increased by one-third from 53 percent in 1995 to 71 percent in 2002. Exposure to newspapers or magazines and to television has also increased over the same period, from 20 to 28 percent for newspapers/magazines and from 18 to 28 percent for television. The proportion of women who are exposed to any media at least once a week declines with age. As expected, women living in urban areas are much more likely to be exposed to the mass media, particularly newspapers/magazines and television, than rural women. Overall, more than one-third of urban women are exposed to all three media at least once a week, compared with only 2 percent of rural women. Among the zobas, exposure to all three types of media is greatest among women who reside in zoba Maekel (48 percent) and least among women in zoba Gash-Barka (3 percent). As expected, there is a positive association between the level of education and exposure to mass media; as the education level of respondents increases, the proportion who report exposure to each of the three mass media increases, especially the print media and television. Fifty-nine percent of women with some secondary education have access to all three media, compared with less than 1 percent of women with no formal education. Women’s economic status also reflects a positive relationship with access to mass media. Access to all three media ranges from a low of less than 1 percent among women in the two lowest quintiles of the wealth index to a high of 55 percent among women in the highest quintile of the wealth index. The differential is most pronounced for exposure to television: 2 percent for women in the lowest quintile compared with 82 percent for women in the highest quintile of the wealth index. Women’s Characteristics and Status | 41 Table 3.7 Exposure to mass media Percentage of women who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of mass media exposure –––––––––––––––––––––––––––––––––– Reads a Watches Listens to newspaper television the radio at least at least at least All No Number Background once once once three mass of characteristic a week a week a week media media women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 45.2 35.5 81.9 24.8 14.8 2,001 20-24 32.6 31.0 72.3 21.6 25.0 1,454 25-29 29.3 29.6 70.7 19.1 27.6 1,543 30-34 21.3 22.4 66.8 14.5 31.4 1,109 35-39 18.1 25.7 69.9 13.8 28.7 1,085 40-44 14.1 20.6 61.8 9.1 36.1 827 45-49 9.3 20.2 61.6 6.4 36.4 734 Residence Total urban 50.4 60.6 88.6 38.4 7.6 3,767 Asmara 64.0 81.0 93.3 55.5 2.7 1,899 Other towns 36.7 39.8 83.8 21.0 12.6 1,868 Rural 11.0 3.7 58.3 1.8 40.7 4,987 Zoba Debubawi Keih Bahri 24.1 35.3 49.3 16.4 43.0 324 Maekel 58.8 70.6 92.2 47.8 4.0 2,264 Semenawi Keih Bahri 15.0 14.9 57.1 6.1 40.7 1,148 Anseba 19.9 14.7 66.5 8.2 31.4 1,130 Gash-Barka 11.0 4.8 58.4 2.7 41.1 1,500 Debub 19.9 14.4 71.7 8.3 27.0 2,388 Education No education 1.4 6.0 52.0 0.4 47.1 4,384 Primary 35.6 26.9 84.5 13.0 10.8 1,637 Middle 52.3 43.3 92.6 26.9 4.5 974 Secondary + 73.5 76.1 95.4 59.3 1.6 1,760 Wealth index Lowest 7.1 1.6 44.1 0.6 54.8 1,472 Second 8.4 2.4 54.6 0.9 44.4 1,626 Middle 13.3 3.8 67.2 1.8 31.6 1,674 Fourth 34.5 31.4 87.9 16.4 10.1 1,833 Highest 62.9 82.2 91.7 55.1 3.2 2,149 Total 2002 28.0 28.2 71.3 17.6 26.4 8,754 Total 1995 20.2 17.5 52.6 11.0 45.5 5,054 42 | Women’s Characteristics and Status 3.6 EMPLOYMENT STATUS In the 2002 EDHS, respondents were asked a series of questions about their employment, including whether they were currently working and, if not, whether they had worked in the 12 months before the survey. Table 3.8 and Figure 3.2 show the percent distribution of women age 15-49 by employment status, according to background characteristics. Overall, the majority of women (76 percent) did not work at all in the 12 months preceding the survey. Only one in five women reported being currently employed and 4 percent of women worked during the 12 months prior to the survey but were not currently employed. The current employment level has declined from 25 percent in 1995 to 20 percent in 2002 (Table 3.8). Older women are generally more likely to be employed than younger women. Women who are divorced, separated, or widowed are the most likely to be employed (43 percent), followed by those who have not married (24 percent); currently married women are the least likely to be employed (15 percent). Women with five or more children are less likely to be working at the time of the survey than women with fewer children or no children at all. The current employment level is higher for women in urban areas than in rural areas. By zoba, the highest proportion currently employed (35 percent) is in zoba Debubawi Keih Bahri, followed by zoba Maekel (31 percent), and the lowest is in zoba Anseba, at 9 percent. Education generally has a positive association with the level of current employment; the proportion of women who are currently employed ranges from 14 percent among uneducated women to 34 percent among women with at least some secondary education. The employment level has a positive correlation with women’s wealth status. Among women in the highest quintile of the wealth index, 33 percent are currently employed, compared with only 8 percent among women in the lowest quintile. EDHS 2002 Figure 3.2 Employment Status of Women Employed in last 12 months, currently employed 20% Employed in last 12 months, not currently employed 4% Not employed in last 12 months 76% Women’s Characteristics and Status | 43 Table 3.8 Employment status Percent distribution of women by employment status, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Employed in the 12 months Not preceding the survey employed ––––––––––––––––––––– in the 12 Not months Number Background Currently currently preceding of characteristic employed employed the survey Missing Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 10.1 2.8 87.1 0.1 100.0 2,001 20-24 18.5 4.3 77.2 0.0 100.0 1,454 25-29 25.0 3.2 71.8 0.1 100.0 1,543 30-34 21.3 5.3 73.3 0.0 100.0 1,109 35-39 24.9 4.1 71.0 0.0 100.0 1,085 40-44 23.3 4.5 72.1 0.0 100.0 827 45-49 24.4 5.7 69.8 0.2 100.0 734 Marital status Never married 23.5 2.8 73.6 0.0 100.0 2,044 Married or living together 14.5 3.9 81.6 0.0 100.0 5,733 Divorced/separated/widowed 43.3 7.1 49.5 0.2 100.0 977 Number of living children 0 20.4 2.7 76.8 0.0 100.0 3,019 1-2 22.2 5.0 72.7 0.1 100.0 2,287 3-4 21.6 5.0 73.4 0.0 100.0 1,772 5+ 13.6 3.9 82.5 0.0 100.0 1,677 Residence Total urban 28.6 3.5 67.7 0.1 100.0 3,767 Asmara 33.9 3.9 62.1 0.2 100.0 1,899 Other towns 23.3 3.2 73.5 0.1 100.0 1,868 Rural 13.2 4.3 82.5 0.0 100.0 4,987 Zoba Debubawi Keih Bahri 35.2 2.1 62.6 0.1 100.0 324 Maekel 30.8 3.5 65.6 0.2 100.0 2,264 Semenawi Keih Bahri 10.0 1.0 89.0 0.0 100.0 1,148 Anseba 9.4 2.1 88.5 0.0 100.0 1,130 Gash-Barka 14.9 5.2 79.9 0.0 100.0 1,500 Debub 20.0 6.3 73.6 0.0 100.0 2,388 Education No education 13.7 4.1 82.2 0.0 100.0 4,384 Primary 21.9 4.9 73.2 0.0 100.0 1,637 Middle 17.5 3.8 78.6 0.1 100.0 974 Secondary + 34.4 3.0 62.5 0.2 100.0 1,760 Wealth index Lowest 7.6 1.9 90.5 0.0 100.0 1,472 Second 13.0 4.2 82.7 0.0 100.0 1,626 Middle 14.0 7.1 78.9 0.0 100.0 1,674 Fourth 26.0 3.7 70.2 0.1 100.0 1,833 Highest 32.5 3.1 64.2 0.1 100.0 2,149 Total 2002 19.8 4.0 76.1 0.0 100.0 8,754 Total 1995 25.0 1.8 73.0 1.4 100.0 5,054 44 | Women’s Characteristics and Status 3.7 OCCUPATION Respondents who were currently employed or had worked within the year before the survey were asked to state their occupation; results are shown in Table 3.9. The agricultural sector employs 30 percent of currently working women, a far lower proportion than in 1995 (55 percent). In 2002, almost one-fourth of working women were employed in sales and service occupations (24 percent), followed by domestic service (17 percent), and skilled manual jobs (12 percent). Ten percent of employed women work in professional, technical, and managerial occupations. The occupational pattern of women who work varies by age. Women in all age groups except those in their twenties are most likely to be engaged in agricultural work. Those age 20-29 are most likely to be working in sales and service occupations. More than one-fourth (27 percent) of women age 15-19 are domestic-service workers. Currently married women who are working tend to be employed in agricultural work (41 percent), whereas never-married women and those who are divorced, separated or widowed tend to work in either sales and service jobs or in domestic service. The large majority (63 percent) of employed rural women work in agriculture. Working women who reside in urban areas, particularly in Asmara, are almost exclusively employed in non-agricultural occupations; 29 percent of employed urban women work in sales and service jobs and nearly one-fourth (23 percent) work in domestic service. Women are most likely to be employed in agricultural activities in all zobas except zoba Maekel and zoba Semenawi Keih Bahri, where sales and services and domestic service are the predominant occupations. Education is strongly related to the type of occupation. Over half (55 percent) of women who are employed and have never attended school work in agriculture. Working women with primary and middle education are about as likely to be employed in agriculture as in sales and service occupations, in domestic service, and in skilled manual jobs. Women who have at least some secondary education are most likely to be employed in sales and services (29 percent), followed closely by professional, managerial, or technical jobs (28 percent), and clerical occupations (18 percent). Agriculture is by far the major occupation of working women in the lower quintiles of the wealth index, while sales and services account for the largest proportion of women in the fourth and highest quintiles (29 and 28 percent, respectively). Nearly one-fourth of women in the fourth and highest quintile are employed in domestic service. 3.8 EARNINGS, EMPLOYERS AND CONTINUITY OF EMPLOYMENT Table 3.10 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 whether they work in agricultural or non-agricultural jobs. Almost two-thirds (65 percent) of employed women receive payments in cash only, while 15 percent do not receive any form of payment for their work, 13 percent receive payment in kind only, and 8 percent receive both cash and in-kind payments (Figure 3.3). Women who are engaged in nonagricultural jobs are more than five times as likely to be paid in cash only as those who work in agricultural jobs. On the other hand, women employed in the agricultural sector are much more likely to receive payment in kind or no payment than those who work in nonagricultural jobs (Table 3.10). Data on type of employer in Table 3.10 indicate that over half (53 percent) of working women are employed by someone outside the family, while 39 percent are self-employed, and 8 percent work for a family member. These results are also displayed graphically in Figure 3.4. Women engaged in agricultural occupations are predominantly self-employed (68 percent); the majority of women involved in nonagricultural activities are employed by nonfamily members (68 percent). Women’s Characteristics and Status | 45 Table 3.9 Occupation Percent distribution of women employed in the 12 months preceding the survey by occupation, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Professional/ Sales Un- Number Background technical/ and Skilled skilled Domestic Agri- of characteristic managerial Clerical services manual manual service culture Missing Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 4.2 3.0 13.6 15.0 0.1 26.6 37.6 0.0 100.0 258 20-24 14.9 9.3 25.7 10.7 0.3 15.2 23.9 0.1 100.0 331 25-29 9.2 7.9 33.8 12.0 0.3 13.9 21.5 1.4 100.0 434 30-34 12.9 9.8 23.9 10.0 0.3 11.3 31.2 0.5 100.0 296 35-39 10.7 8.0 20.8 14.3 0.5 21.3 22.9 1.4 100.0 314 40-44 13.3 4.4 16.4 7.1 1.3 16.7 39.5 1.4 100.0 230 45-49 3.9 1.5 21.8 15.6 0.9 13.4 41.6 1.2 100.0 220 Marital status Never married 13.6 9.4 26.5 13.0 0.3 21.9 15.3 0.0 100.0 538 Married or living together 11.2 7.0 21.6 8.9 0.6 9.1 40.6 1.0 100.0 1,054 Divorced/separated/widowed 4.1 3.4 24.0 17.8 0.4 27.3 21.4 1.6 100.0 492 Number of living children 0 12.7 9.1 26.1 14.1 0.2 18.5 18.9 0.3 100.0 699 1-2 11.1 7.6 22.9 12.8 0.2 19.3 24.4 1.8 100.0 621 3-4 8.7 4.7 22.9 10.4 1.6 15.6 35.3 1.0 100.0 471 5+ 4.4 2.5 19.2 8.3 0.0 8.6 56.8 0.1 100.0 293 Residence Total urban 15.1 10.8 28.5 14.6 0.6 23.2 5.8 1.5 100.0 1,211 Asmara 17.5 13.5 27.6 15.2 0.6 23.3 1.3 1.1 100.0 717 Other towns 11.7 6.8 29.8 13.8 0.5 23.1 12.2 2.0 100.0 494 Rural 3.2 1.1 16.4 8.5 0.3 7.7 62.6 0.1 100.0 873 Zoba Debubawi Keih Bahri 3.3 9.3 21.1 4.5 0.5 25.0 34.6 1.6 100.0 121 Maekel 16.4 12.8 27.3 15.1 0.6 22.3 4.6 1.0 100.0 775 Semenawi Keih Bahri 7.8 4.8 20.7 12.9 2.0 33.4 18.4 0.0 100.0 126 Anseba 10.9 6.1 16.8 5.0 0.0 15.9 45.4 0.0 100.0 130 Gash-Barka 4.0 2.7 26.4 14.0 0.8 8.9 42.5 0.7 100.0 302 Debub 7.0 1.2 19.7 10.1 0.0 8.8 52.1 1.1 100.0 629 Education No education 0.5 0.0 18.8 9.7 0.7 14.6 55.2 0.5 100.0 780 Primary 1.9 1.4 22.7 18.1 0.0 26.8 28.3 0.7 100.0 439 Middle 6.9 6.8 22.2 16.0 0.1 26.7 18.9 2.3 100.0 207 Secondary + 28.1 18.2 29.8 9.6 0.7 9.3 3.3 1.0 100.0 657 Wealth index Lowest 0.7 0.0 18.0 7.0 0.6 1.7 72.1 0.0 100.0 140 Second 2.5 1.1 13.1 5.2 0.8 3.6 73.3 0.3 100.0 280 Middle 2.5 0.8 14.3 9.7 0.0 10.7 61.7 0.3 100.0 352 Fourth 8.5 3.9 29.4 19.2 0.4 23.1 15.1 0.5 100.0 544 Highest 19.4 14.8 28.2 11.5 0.6 22.4 1.2 1.8 100.0 766 Total 2002 10.1 6.7 23.5 12.1 0.5 16.7 29.6 0.9 100.0 2,084 Total 1995 10.2 na 8.8 12.1 na 13.2 55.4 0.3 100.0 1,265 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable 46 | Women’s Characteristics and Status Table 3.10 Employment characteristics 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), Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of employment ––––––––––––––––––– Agri- Nonagri- cultural cultural Characteristic work work Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of earnings Cash only 16.0 85.4 65.0 Cash and in kind 18.6 2.9 7.5 In kind only 38.0 1.9 12.6 Not paid 27.4 9.6 14.8 Missing 0.0 0.2 0.1 Total 100.0 100.0 100.0 Type of employer Employed by family member 14.9 4.9 7.9 Employed by nonfamily member 17.0 68.2 53.1 Self-employed 68.1 26.4 38.7 Missing 0.0 0.4 0.3 Total 100.0 100.0 100.0 Continuity of employment All year 13.4 79.8 60.1 Seasonal 76.2 7.1 27.5 Occasional 10.4 12.6 12.0 Missing 0.0 0.6 0.4 Total 100.0 100.0 100.0 Wealth index Lowest 16.4 2.7 6.7 Second 33.4 5.1 13.5 Middle 35.3 9.2 16.9 Fourth 13.4 31.7 26.1 Highest 1.5 51.3 36.8 Total 100.0 100.0 100.0 Number of women 616 1,449 2,084 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes women with missing information on type of employment who are not shown separately Table 3.10 shows that 60 percent of working women work all year, 28 percent work seasonally, and 12 percent work occasionally. As expected, the percentage of women who work all year is higher among women who work in nonagricultural jobs than among those who work in agriculture (80 and 13 percent, respectively), while seasonal employment is high among agricultural workers (76 percent). Although by definition, roughly 20 percent of all women fall into each quintile of the wealth index (see Table 3.1), women who work tend to be better off, with 37 percent falling in the highest quintile and only 7 percent in the lowest quintile. Most women employed in nonagricultural occupations are either in the fourth or the highest quintile, while the majority of those who are engaged in agricultural work fall in the second or middle quintiles. Women’s Characteristics and Status | 47 EDHS 2002 Figure 3.3 Type of Earnings among Employed Women Cash only 64% Cash and in kind 8% In kind only 13% Not paid 15% EDHS 2002 Figure 3.4 Type of Employer among Employed Women Family member 8%Non-family member 53% Self-employed 39% 48 | Women’s Characteristics and Status 3.9 CHILD CARE WHILE WORKING Table 3.11 shows the percentage of employed women who have a child under six years of age living at home and, for those who do, the percent distribution by type of child minder (caretaker) used by the mother while working, according to background characteristics. Almost four in ten (38 percent) of employed women have a child under six years of age, a sharp decline from the 53 percent recorded in the 1995 EDHS. Over 80 percent of employed mothers report that their children under six years of age are cared for either by themselves (30 percent), an older female child (22 percent), an older male child (4 percent), or other relatives (25 percent). Women’s husbands account for less than 1 percent of the caretakers of Table 3.11 Childcare while working Percent distribution of currently employed women by whether they have a child under six years of age and the percent distribution of employed mothers who have a child under six by person who usually takes care of the young child while mother works, according to background characteristics, Eritrea 2002 Person who takes care of child while mother works Children < 6 at home Background characteristics No child- ren < 6 at home One or more children Total Number of women Respon- dent Hus- band, partner Older female child Older male child Other rela- tives Neigh- bors/ friends Servants, hired help Child is in school Has not worked since last birth Other Missing Total Number of children Residence Urban 68.9 31.1 100.0 1,078 18.6 0.2 14.7 4.8 33.0 6.9 14.4 2.2 1.6 1.0 2.6 100.0 335 Asmara 73.7 26.3 100.0 643 9.1 0.0 11.9 2.9 42.5 2.4 21.8 3.1 0.8 1.4 4.2 100.0 169 Other towns 61.9 38.1 100.0 435 28.3 0.4 17.5 6.7 23.3 11.6 6.9 1.3 2.5 0.5 1.1 100.0 165 Rural 51.6 48.4 100.0 656 41.3 0.5 29.9 3.7 17.4 2.1 0.0 0.0 3.1 0.1 2.0 100.0 318 Zoba Debubawi Keih Bahri 61.3 38.7 100.0 114 30.3 1.5 15.6 3.2 34.8 8.6 1.0 0.0 1.6 1.1 2.5 100.0 44 Maekel 71.9 28.1 100.0 696 15.0 0.0 12.1 2.5 40.7 2.6 18.9 2.6 0.7 1.2 3.6 100.0 195 Semenawi Keih Bahri 70.7 29.3 100.0 115 (20.4) 0.0 12.7 5.3 30.7 14.8 (12.8) (0.0) (0.0) 1.9 (1.5) 100.0 34 Anseba 61.8 38.2 100.0 106 30.1 0.0 30.0 3.5 16.8 9.1 5.5 0.0 3.4 0.0 1.5 100.0 40 Gash-Barka 57.2 42.8 100.0 224 41.1 0.0 24.1 7.2 21.1 1.1 0.0 0.0 3.7 0.0 1.8 100.0 96 Debub 49.2 50.8 100.0 478 38.0 0.6 30.5 4.7 13.8 4.5 1.8 0.9 3.4 0.0 1.8 100.0 243 Education No education 55.1 44.9 100.0 599 34.4 0.0 35.2 4.9 16.6 3.0 0.5 0.0 2.4 0.4 2.5 100.0 269 Primary 60.6 39.4 100.0 359 42.3 1.3 19.0 4.2 17.8 6.9 0.7 1.6 2.2 1.2 2.9 100.0 142 Middle 69.0 31.0 100.0 171 (26.5) (0.0) (16.5) (3.5) (34.3) (6.5) (2.2) (0.0) (8.5) 0.0 (2.0) 100.0 53 Secondary + 68.7 31.3 100.0 605 14.3 0.1 7.4 3.6 41.0 4.4 23.6 2.7 0.7 0.4 1.7 100.0 189 Type of employer Family member 84.5 15.5 100.0 127 * * * * * * * * * * * 100.0 20 Non-family member 70.8 29.2 100.0 974 15.0 0.6 16.2 5.7 34.1 9.4 12.8 1.5 1.7 0.8 2.1 100.0 284 Self-employed 45.0 55.0 100.0 627 41.9 0.1 28.0 3.4 16.6 0.8 3.1 0.6 3.0 0.4 2.2 100.0 345 Occupation Agricultural 51.2 48.8 100.0 401 28.2 0.0 38.9 6.0 17.0 2.4 0.0 0.0 4.6 0.1 2.7 100.0 196 Nonagricultural 65.7 34.3 100.0 1,333 30.3 0.5 14.9 3.5 29.0 5.4 10.5 1.6 1.4 0.7 2.2 100.0 457 Continuity of work All year 66.6 33.4 100.0 1,181 28.5 0.5 15.4 3.6 31.0 4.5 10.9 1.6 1.2 0.8 1.9 100.0 394 Seasonal 49.0 51.0 100.0 367 30.3 0.0 37.2 4.4 16.7 2.5 1.1 0.0 4.5 0.1 3.1 100.0 187 Occasional 60.9 39.1 100.0 177 35.5 0.0 19.6 7.6 17.8 10.3 4.4 1.4 3.1 0.0 0.3 100.0 69 Work place At home 54.9 45.1 100.0 308 67.3 0.0 11.4 0.0 17.7 0.6 0.8 0.0 2.1 0.0 0.1 100.0 139 Away 64.0 36.0 100.0 1,411 19.3 0.4 25.2 5.4 27.6 5.7 9.3 1.5 2.5 0.7 2.6 100.0 508 Total 62.4 37.6 100.0 1,733 29.7 0.3 22.1 4.3 25.4 4.5 7.4 1.1 2.3 0.5 2.3 100.0 652 Note: Total includes 4, 2, and 5 children with missing information for their mothers on type of employer, on continuity of employment, and whether works at home or away from home, respectively, who are not shown separately. Figures in parentheses are based on 25 to 49 unweighted cases; an asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Women’s Characteristics and Status | 49 young children. Seven percent of mothers report that they depend on servants and hired help for child care and 5 percent report that neighbors and friends provide child care services. Table 3.11 shows that mothers in rural areas, in zoba Gash-Barka, and those with primary education or who are self-employed are most likely to care for their children themselves while they work. Not surprisingly, this is especially true of those women who work at home. Relatives other than respondents’ own children are an especially important source of child care for urban mothers (33 percent), those in zoba Maekel (41 percent), and those with at least some secondary education (41 percent). Children, especially female children, are important providers of child care for women in rural areas, in zoba Debub and zoba Anseba, for those who have never attended school, those engaged in agricultural work, and those who work seasonally. Servants and hired help are used for child care more often by urban mothers, particularly women in Asmara (22 percent), those in zoba Maekel (19 percent), and mothers with secondary or higher education (24 percent). 3.10 DECISION ON USE OF EARNINGS As a means of assessing women’s autonomy, respondents in the 2002 EDHS who had received cash earnings for work in the 12 months before the survey were asked who mainly decides how these earnings will be used. Nearly three-fourths of women who receive cash earnings report that they alone decide how their earnings are used, while about one-fourth say that they decide jointly with their husband or someone else, and only 4 percent report that someone else alone decides how their earnings will be used (Table 3.12). Women age 15-19 are more likely than older women to report that someone else decides how their earnings are to be used. Almost all working women who are divorced, separated, or widowed say that they alone are responsible for deciding how to use their earnings. Among currently married women, over one-half report that they alone decide how their earnings are used, while 40 percent say that such decisions are made jointly with their husband or someone else. Over three-fourths of never-married women make independent decisions on how to use their earnings. Women with five or more children are much less likely to decide on their own how to use their earnings than women with fewer children or no children at all. With respect to control over how their earnings are spent, urban women are more likely than rural women to report that they themselves make decisions about how the money they earn will be used. By zoba, the proportion who make their own decisions on spending their earnings ranges from a high of 82 percent among women in zoba Semenawi Keih Bahri to a low of 65-66 percent among women in zoba Anseba and zoba Debub. Women who reached only primary or middle school are more likely than those who reached secondary school or higher to decide for themselves how to use the money they earn. The most educated women have the highest proportion (29 percent) who decide jointly how to use their earnings. 50 | Women’s Characteristics and Status Table 3.12 Decision on use of earnings Percent distribution of women employed in the 12 months preceding the survey who received cash earnings by person who decides how earnings are used, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Person who decides how earnings are used _––––––––––––––––––––––––––––––––––––– Jointly with Number Background Self someone Someone of characteristic only else1 else only2 Missing Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 68.2 15.8 16.0 0.0 100.0 160 20-24 75.9 18.7 5.5 0.0 100.0 242 25-29 74.4 21.8 3.7 0.1 100.0 352 30-34 72.0 27.4 0.5 0.0 100.0 214 35-39 71.7 25.4 2.1 0.8 100.0 248 40-44 66.2 33.4 0.4 0.0 100.0 152 45-49 77.0 22.0 1.0 0.0 100.0 143 Marital status Never married 76.7 15.2 8.1 0.0 100.0 419 Married or living together 56.2 39.8 3.6 0.3 100.0 694 Divorced/separated/widowed 97.0 2.7 0.4 0.0 100.0 397 Number of living children 0 75.4 16.8 7.7 0.0 100.0 524 1-2 77.9 19.3 2.7 0.1 100.0 487 3-4 72.1 26.0 1.3 0.6 100.0 330 5+ 49.6 49.1 1.3 0.0 100.0 168 Residence Total urban 75.2 21.2 3.4 0.2 100.0 1,069 Asmara 75.7 20.6 3.4 0.3 100.0 651 Other towns 74.3 22.2 3.4 0.1 100.0 418 Rural 66.5 28.2 5.4 0.0 100.0 441 Zoba Debubawi Keih Bahri 73.7 21.9 4.1 0.4 100.0 73 Maekel 76.1 20.2 3.5 0.3 100.0 676 Semenawi Keih Bahri 81.6 14.8 3.6 0.0 100.0 102 Anseba 64.9 31.0 4.2 0.0 100.0 93 Gash-Barka 72.7 20.2 7.1 0.0 100.0 175 Debub 66.0 30.4 3.6 0.0 100.0 392 Education No education 73.6 23.5 2.9 0.0 100.0 449 Primary 79.1 15.3 5.6 0.0 100.0 329 Middle 78.5 17.0 4.5 0.0 100.0 160 Secondary + 66.5 29.3 3.8 0.4 100.0 572 Total 72.6 23.2 4.0 0.1 100.0 1,510 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes husband Women’s Characteristics and Status | 51 3.11 MEASURES OF WOMEN’S EMPOWERMENT In addition to information on women’s education, employment status, and control over earnings, the 2002 EDHS collected information on some other indicators of women’s status and empowerment. In particular, questions were asked on women’s participation in specific household decisions and on their attitudes towards wife beating. This information provides insight into women’s control over their lives, their domestic environment, and their attitudes toward gender roles, which are relevant in understanding women’s demographic and health behavior. Women’s Participation in Household Decisionmaking To assess women’s role in household decisionmaking, respondents in the 2002 EDHS were asked who in their family has the final say in decisions regarding: the respondent’s own health care; making large household purchases; making purchases for daily household needs; visits to family or relatives; what food to cook each day; and assisting her family.1 Table 3.13 shows the percent distribution of women by the person who makes each of these decisions, according to marital status. Table 3.13 Women’s participation in decisionmaking Percent distribution of women by person who has the final say in making specific decisions, according to marital status, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Currently married or living together Not married1 ––––––––––––––––––––––––––––––––––––––––––––––––––––– –––––––––––––––––––––––––––––––––––––– Decision Decision Jointly Jointly Some- not made/ Jointly Some- not made/ with with Hus- one not with one not Self hus- someone band else appli- Self someone else appli- Decision only band else only only cable Total only else only cable Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Own health care 80.2 7.3 0.5 9.3 2.6 0.1 100.0 73.3 4.7 21.1 0.8 100.0 Large household purchases 22.9 31.4 0.9 37.4 6.6 0.9 100.0 30.8 6.8 53.1 9.1 100.0 Daily household purchases 44.8 20.1 1.0 27.0 6.5 0.5 100.0 35.5 6.6 49.3 8.4 100.0 Visits to family or relatives 40.9 30.8 1.1 19.8 6.4 1.0 100.0 38.5 7.7 46.1 7.4 100.0 What food to cook each day 80.1 6.2 1.2 6.8 5.3 0.4 100.0 43.9 8.6 40.3 7.0 100.0 Assisting woman’s family2 26.9 38.1 1.0 23.2 6.9 3.8 100.0 34.2 7.6 47.3 10.7 100.0 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Information is based on 5,733 married and 3,021 not married women. 1 Not married includes never married, divorced, separated or widowed women. 2 Woman’s kin group Eighty percent of currently married women reported that they alone have the final say on decisions involving their own health care and what food to cook each day. Although over 40 percent of married women say they alone make decisions about daily household purchases and visits to family or relatives, these decisions are also likely to be shared with their husbands. Decisions on large household purchases are most likely to be made by the husband alone (37 percent) or jointly (31 percent). Among unmarried women, nearly three-fourths make decisions about their own health care by themselves, although 21 percent say that such decisions are made by someone else alone. Decisions on household purchases and visits to family or relatives also tend to be made by someone else among unmarried women. Almost two-thirds of currently married women either make decisions to assist their family by themselves (27 percent) or share such decisions with their husbands (38 percent). Nearly half of the unmarried women report that someone else has the final say on decisions related to assisting their family. Table 3.14 shows the percentage of women who report that they alone or jointly have the final say in specific household decisions according to background characteristics. The results indicate that, 1 The woman’s kin group 52 | Women’s Characteristics and Status Table 3.14 Women’s participation in decisionmaking by background characteristics Percentage of women who say that they alone or jointly have the final say in specific decisions, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Alone or jointly has final say in: –––––––––––––––––––––––––––––––––––––––––––––––––––––– Making Visits to What None Own Making daily family, food Assisting All of the Number Background health large pur- relatives, to cook woman’s specified specified of characteristic care purchases chases friends daily family1 decisions decisions women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 68.3 19.6 25.4 28.8 41.6 24.9 13.8 21.7 2,001 20-24 86.9 46.5 54.6 61.2 70.7 54.8 37.4 6.3 1,454 25-29 89.3 57.2 66.9 72.8 85.2 66.3 48.1 3.3 1,543 30-34 89.6 60.6 70.0 77.0 88.9 70.2 52.7 2.9 1,109 35-39 90.8 62.7 73.2 79.5 92.5 72.9 53.9 2.5 1,085 40-44 91.0 63.8 73.0 80.5 92.4 74.9 57.1 2.2 827 45-49 90.3 63.3 73.2 81.0 92.6 73.9 56.8 2.2 734 Marital status Never married 70.0 17.8 22.8 28.3 36.2 23.7 12.8 22.1 2,044 Married/living together 88.0 55.1 65.8 72.7 87.6 66.0 45.9 3.2 5,733 Divorced/separated/ widowed 94.9 78.9 82.4 83.9 86.7 79.6 74.3 3.5 977 Number of living children 0 74.5 26.3 32.5 37.6 47.6 32.9 19.8 17.2 3,019 1-2 89.1 60.9 70.2 74.6 86.5 68.8 52.4 3.6 2,287 3-4 90.7 64.6 73.8 79.5 92.1 72.3 55.5 2.0 1,772 5+ 90.0 57.5 68.8 78.7 93.0 71.6 50.2 2.0 1,677 Residence Total urban 85.8 51.7 61.4 64.7 72.0 58.2 43.8 7.8 3,767 Asmara 86.8 48.0 59.1 64.5 67.1 55.7 40.4 6.8 1,899 Other towns 84.9 55.5 63.7 64.9 76.9 60.8 47.2 8.7 1,868 Rural 83.6 47.1 54.8 62.8 78.1 57.2 39.6 7.6 4,987 Zoba Debubawi Keih Bahri 78.4 57.6 66.3 64.4 68.6 59.6 51.7 16.1 324 Maekel 86.6 49.1 59.8 64.7 68.0 55.9 41.0 7.3 2,264 Semenawi Keih Bahri 81.8 42.1 44.6 53.2 72.0 53.7 36.4 9.4 1,148 Anseba 88.4 47.0 51.6 64.3 83.4 57.6 37.2 4.9 1,130 Gash-Barka 84.8 47.1 51.5 62.2 78.3 58.3 39.2 6.7 1,500 Debub 82.8 53.4 67.4 68.0 79.6 60.6 46.0 7.9 2,388 Education No education 86.7 52.8 59.7 68.3 84.3 63.4 44.8 5.2 4,384 Primary 83.2 53.6 64.4 67.1 77.2 59.6 44.9 9.0 1,637 Middle 77.8 36.5 46.5 47.7 58.0 43.2 29.5 13.6 974 Secondary + 84.0 42.4 52.3 57.4 61.5 49.4 36.1 9.4 1,760 Employment Not employed 83.1 44.4 53.3 60.1 74.7 53.8 36.6 8.3 7,011 Employed for cash 93.1 71.8 79.6 81.5 81.2 77.7 64.8 2.8 1,356 Employed not for cash 81.7 53.5 60.2 64.6 70.8 58.7 47.1 12.7 375 Wealth index Lowest 83.5 37.0 41.9 55.8 75.7 51.2 30.3 7.7 1,472 Second 81.5 47.1 54.3 61.7 78.4 59.2 39.7 8.8 1,626 Middle 83.9 52.4 61.1 65.0 77.6 58.8 44.6 7.4 1,674 Fourth 87.6 59.4 69.0 70.3 79.9 62.8 50.0 6.3 1,833 Highest 85.4 47.4 58.6 63.6 67.7 55.8 40.4 8.1 2,149 Total 84.5 49.1 57.6 63.6 75.5 57.7 41.4 7.7 8,754 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 12 women with missing information on employment who are not shown separately. 1 Woman’s kin group Women’s Characteristics and Status | 53 overall, 41 percent of women participate in all of the six types of decisions. Only 8 percent have no involvement in making any of the decisions. Data in Table 3.14 indicate that women’s involvement in all the specified decisions increases with age, from a low of 14 percent among women age 15-19 to a high of 57 percent among women age 40-49. Divorced, separated, or widowed women are much more likely (74 percent) to be involved in all types of household decisions than currently married women (46 percent) and never-married women (13 percent). Women who have no children, those who reside in zoba Semenawi Keih Bahri, and those who are not employed are the least likely to participate in all the specified decisions. Cash employment appears to be related to increased involvement in decisionmaking. Nearly two-thirds of women who are employed for cash are involved in making all types of household decisions, compared with 47 percent of women who are employed but not paid in cash and 37 percent of unemployed women. Women’s Agreement with Reasons for Wife Beating To assess women’s attitudes towards wife beating, women interviewed in the EDHS were asked whether a husband would be justified in beating his wife in each of the following five situations: if the wife burns the food; if she argues with him; if she goes out without informing him; if she neglects the children; and if she refuses to have sex with him. The results are summarized in Table 3.15. The last column gives the percentage of women who feel that a husband is justified in beating his wife for at least one of the specified reasons. A sizable majority of women (71 percent) believe that a husband is justified in beating his wife for at least one of the specified reasons. This is not surprising because in Eritrea—as in many other countries—battery against women is traditionally accepted, tolerated, and rationalized. More than half of women believe that a husband is justified in beating his wife if she goes out without telling him or if she neglects the children. Slightly smaller percentages agree that if a woman refuses to have sex with her husband (48 percent) or argues with him (45 percent), then he is justified in beating her. Only 29 percent of women feel that a husband is justified in beating his wife if she burns the food. The percentage of women who agree with at least one of the reasons justifying a husband beating his wife is higher among older women, divorced, separated, or widowed women, and those with more children. Seventy-eight percent of rural women agree with at least one of the reasons justifying a husband beating his wife, compared with 61 percent among urban women. The percentage is lowest in Asmara, where just over half of women believe that wife beating is justified for at least one reason. Women in zoba Debub are more likely to say that wife beating is justified than other women, with 86 percent agreeing that a man is justified in beating his wife for one or more of the given reasons, compared with only 59 percent of women in zoba Maekel. Differences are also notable by level of education; less than half of women with some secondary education agree with at least one specified reason for wife beating, compared with over three-fourths of women with primary education or no education. Women who are employed for cash are less likely to agree with one of the reasons for wife beating than those who are either not employed or employed but not for cash. Women in the highest quintile of the wealth index are also less accepting of wife beating than other women. 54 | Women’s Characteristics and Status Table 3.15 Women’s attitude toward wife beating Percentage of women who agree that a husband is justified in hitting or beating his wife for specific reasons, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Husband is justified in hitting or beating his wife if she: ––––––––––––––––––––––––––––––––––––––––––––––––– Goes out Refuses Agrees with Burns Argues without Neglects to have at least one Number Background the with telling the sex specified of characteristic food him him children with him reason women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 30.2 41.9 49.4 51.7 42.8 69.9 2,001 20-24 28.1 43.7 49.7 49.1 44.6 68.6 1,454 25-29 26.1 42.7 49.6 49.0 46.6 69.1 1,543 30-34 29.2 47.0 53.9 51.8 50.5 71.5 1,109 35-39 28.7 44.8 52.0 50.6 50.4 70.9 1,085 40-44 31.4 47.9 54.8 50.4 52.1 73.0 827 45-49 33.0 49.8 58.3 56.6 58.0 76.1 734 Marital status Never married 23.9 32.8 39.9 44.9 32.8 61.4 2,044 Married or living together 30.9 48.7 55.6 52.2 52.6 73.1 5,733 Divorced/separated/widowed 29.8 44.7 53.1 56.4 51.5 75.9 977 Number of living children 0 26.4 38.6 45.9 47.2 39.0 65.9 3,019 1-2 28.6 44.8 51.2 51.0 48.7 70.8 2,287 3-4 29.7 46.4 54.8 52.8 52.1 73.2 1,772 5+ 34.2 53.2 59.3 55.8 58.1 76.6 1,677 Residence Total urban 22.2 30.4 39.2 43.7 34.3 61.1 3,767 Asmara 19.0 23.8 31.8 41.0 28.9 56.0 1,899 Other towns 25.4 37.0 46.8 46.3 39.8 66.3 1,868 Rural 34.4 55.3 61.0 56.5 58.1 77.9 4,987 Zoba Debubawi Keih Bahri 29.9 44.2 48.9 45.9 42.4 65.4 324 Maekel 21.0 27.6 36.4 43.7 32.8 59.2 2,264 Semenawi Keih Bahri 25.1 43.7 48.7 46.1 47.3 66.2 1,148 Anseba 16.2 42.3 51.2 41.8 47.1 66.7 1,130 Gash-Barka 26.0 48.4 55.3 48.8 50.8 72.1 1,500 Debub 46.8 59.8 65.8 66.5 61.7 85.5 2,388 Education No education 33.8 55.1 61.5 55.2 58.3 77.5 4,384 Primary 32.6 46.4 54.2 55.6 51.3 75.6 1,637 Middle 28.2 38.1 50.3 53.1 40.6 70.9 974 Secondary + 14.9 20.1 25.5 35.0 22.7 49.0 1,760 Employment Not employed 29.0 45.5 52.8 50.8 49.0 71.1 7,011 Employed for cash 26.5 36.7 43.6 49.3 39.7 65.8 1,356 Employed not for cash 42.2 56.0 60.5 60.8 56.6 80.8 375 Number of decisions in which woman has final say1 0 33.3 48.6 56.0 56.1 49.0 75.4 683 1-2 25.2 40.7 47.6 47.0 42.0 67.0 2,414 3-4 29.6 49.4 55.5 53.2 54.4 76.3 1,813 5 30.7 44.0 51.6 51.5 48.2 69.5 3,844 Wealth index Lowest 28.6 54.0 59.0 50.5 55.4 74.1 1,472 Second 34.3 56.7 62.6 56.3 59.2 78.9 1,626 Middle 39.2 55.6 60.9 60.6 57.7 79.0 1,674 Fourth 28.7 41.3 49.6 50.9 44.7 70.6 1,833 Highest 18.2 23.1 32.9 39.8 29.1 55.8 2,149 Total 29.1 44.6 51.7 51.0 47.9 70.7 8,754 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 12 women with missing information on employment who are not shown separately. 1 Herself or jointly with others Fertility | 55 FERTILITY 4 This chapter presents the 2002 EDHS results on the levels, differentials, patterns, and trends in fertility. It also presents information on children ever born and living, the length of birth intervals, the age at which women initiate childbearing, and levels of adolescent fertility in Eritrea. Knowledge of current and cumulative fertility is central to population dynamics because it plays a major role in changing the size and age structure of a population. It is also essential in monitoring the progress and evaluating the impact of population and health programs in Eritrea. The fertility indicators discussed in this chapter are based on the reproductive history provided by women age 15-49 in the 2002 EDHS. All women interviewed in the survey were asked to report the total number of sons and daughters to whom they have given birth during their lifetime. To encourage complete reporting, women were asked separately about the number of children still living at home, those living away from home, and those who had died. A complete history of live births was then obtained; this included: name, sex, date of birth, and if dead, age at death, or if alive, age of child. 4.1 CURRENT FERTILITY The most commonly used measures of current fertility are the total fertility rate (TFR) and its component age-specific fertility rates1 (ASFRs). The TFR is a summary measure of fertility and is interpreted as the number of children a woman would have in her lifetime if she were to experience the currently observed ASFRs throughout her reproductive years (age 15-49). The ASFRs are a valuable measure of the age pattern of childbearing. They are defined in terms of the number of live births among women in a particular age group divided by the number of woman-years in that age group during the specified period. The other aggregate measures of fertility presented in this chapter are the general fertility rate (GFR) and the crude birth rate (CBR). The GFR is the annual number of births in a population per 1,000 women age 15-44, and the CBR refers to the total number of births occurring in a given year per 1,000 population. Table 4.1 presents the ASFRs and the aggregate fertility measures (TFR, GFR, and CBR) for Eritrea as a whole, by residence (total urban, Asmara, other towns, and rural), and by zoba. The ASFRs and the aggregate fertility measures presented in Table 4.1 are based on births that occurred during the three years preceding the survey, which roughly corresponds to early 1999 to early 2002. The three-year period was chosen for calculating these rates because it reflects the current situation while also allowing the rates to be calculated without compromising the statistical precision of estimates. At the age-specific fertility rates prevailing in the three-year period before the survey, an Eritrean woman would have, on average, 4.8 children during her reproductive life span. Among the 21 other sub- Saharan countries in which DHS surveys have been conducted since 1997, Cameroon (1998) has the same TFR as Eritrea and six other countries have lower TFRs than Eritrea (Figure 4.1). 1 Numerators for the age-specific fertility rates are calculated by summing the number of live births that occurred 1- 36 months preceding the survey (determined by the date of interview and birth date of the child), and classifying them by age (in five-year groups) of the mother at the time of birth (determined by the mother’s birth date). The denominators of the rates are the number of woman-years lived in each of the specified five-year age groups during the 1-36 months preceding the survey. 56 | Fertility Table 4.1 Current fertility Age-specific fertility rates, total fertility rate, general fertility rate, and crude birth rate for the three years preceding the survey, by residence and Zoba, Eritrea 2002 —————————————————————————————————————————————— Residence Zoba ––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––––– Debubawi Semenawi Age Total Other Keih Keih Gash- and rate urban Asmara towns Rural Bahri Maekel Bahri Anseba Barka Debub Total —————————————————————————————————————————————— Age 15-19 51 37 68 97 88 41 82 76 100 94 77 20-24 145 127 164 218 169 133 201 211 209 202 185 25-29 172 167 178 228 185 181 199 237 218 206 204 30-34 144 100 181 221 158 129 195 256 200 200 188 35-39 123 112 134 195 104 118 140 224 172 198 167 40-44 42 46 36 121 52 61 61 89 75 142 88 45-49 20 8 34 62 19 20 25 36 48 91 46 Rate TFR 3.5 3.0 4.0 5.7 3.9 3.4 4.5 5.6 5.1 5.7 4.8 GFR 116 98 134 182 135 109 156 184 168 172 153 CBR 28 27 29 35 34 27 33 35 34 34 32 —————————————————————————————————————————————— Note: Rates are for the period 1-36 months preceding the survey. Rates for age group 45-49 may be slightly biased due to truncation. TFR: Total fertility rate for ages 15-49, expressed per woman GFR: General fertility rate (births divided by number of women 15-44), expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population Figure 4.1 Total Fertility Rate, Eritrea Compared with Other Sub-Saharan Countries 4 4.2 4.4 4.5 4.7 4.7 4.8 4.8 5.2 5.2 5.2 5.5 5.5 5.6 5.6 5.7 5.8 6 6.3 6.4 6.9 7.2 Zim ba bw e 1 99 9 Ga bo n 2 00 0 Gh an a 1 99 8 M au rita nia 20 00 -0 1 Ke ny a 1 99 8 Ni ge ria 19 99 Eri tre a 2 00 2 Ca me roo n 1 99 8 Cô te d’I vo ire 19 98 -9 9 Mo za mb iqu e 1 99 7 To go 19 98 Eth iop ia 20 00 Gu ine a 1 99 9 Be nin 20 01 Ta nz an ia 19 99 Se ne ga l 1 99 7 Za mb ia 20 01 -0 2 M ad ag asc ar 19 97 M ala wi 20 00 Ch ad 19 96 -9 7 Ug an da 20 00 -0 1 Ni ge r 1 99 8 0 2 4 6 8 Children per Woman DHS Surveys 1997-2002 Fertility | 57 Table 4.1 shows that the fertility level among urban women is substantially lower than that among rural women, a pattern that exists in all sub-Saharan countries. The TFR for rural women is 5.7 children, indicating that rural women have 2.7 more children than women in Asmara (3.0) and 1.7 more children than women in other towns (4.0). As the ASFRs show, this pattern of lower urban fertility is prevalent in all age groups (Figure 4.2). The difference in urban and rural fertility is relatively more pronounced among younger women (under 20 years of age) and older women (35 years and above)—age groups that are at greater risk of pregnancy complications than women 20-34. Rural women over age 39, on average, have thrice as many births as urban women. An examination of the patterns of fertility for various age groups in Table 4.1 indicates that although some women begin childbearing at an early age in Eritrea, the pattern is not common. Fertility rises rapidly to reach a peak in the age group 25-29, after which it declines with increasing age. Eritrean women have high fertility in their twenties and early thirties. The fertility age pattern observed for Eritrea as a whole generally holds true by residence also. The peak of childbearing among women for all urban areas, Asmara, and rural areas is age 25-29. However, for other towns, the childbearing peak occurs at age 30-34. Moreover, in all urban areas, and more clearly in Asmara, fertility declines rapidly after age 29, whereas in rural areas childbearing is consistently high from age 20-24 to 30-34 and the decline is more gradual. Similar fertility age patterns were observed in the 1995 EDHS. The contribution of teenage fertility to total fertility is 8 percent. At current age-specific fertility rates, an Eritrean woman would have, on average, nearly half of her lifetime births (2.3) by age 30 and two-thirds (3.3) by age 35. She would have two births considered high-risk2—“too early” (before age 20) or “too late” (after age 35). Rural women in these elevated-risk categories would have twice as many births as their urban counterparts. EDHS 2002 Figure 4.2 Age-Specific Fertility Rates by Residence & & & & & & &$ $ $ $ $ $ $ ! ! ! ! ! ! !* * * * * * *# # # # # # # 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age Group 0 50 100 150 200 250 Births per 1,000 women Urban Asmara Other towns Rural Total# * ! $ & 2 The categories of births defined as high-risk are discussed in Section 8.5 of Chapter 8. 58 | Fertility The ASFRs for zobas show a pattern similar to that of the nation as a whole. However, in zoba Semenawi Keih Bahri, childbearing is uniform in the twenties and early thirties, while in zoba Anseba it peaks at age 30-34. The GFR and CBR are 153 per 1,000 women age 15-44 and 32 per 1,000 population, respectively. The GFR and CBR also vary by residence. With a GFR of 182, the average annual number of births to rural women is 57 percent higher than that for urban women (116), almost twice as high as for women in Asmara (98), and 36 percent higher than that for women in other towns (134). Similarly, the CBR in rural areas (35) is higher than in urban areas (27-29). 4.2 FERTILITY DIFFERENTIALS Current fertility varies by back- ground characteristics of women. The study of current fertility differentials is based on the TFR and the percentage of women currently pregnant. A compari- son of the TFR and completed or past fertility in terms of the mean number of children ever born (CEB) to women age 40-49 is also presented. Table 4.2 and Figure 4.3 present differentials in fertility by residence, zoba, education, and wealth index. The differentials in fertility by residence have already been discussed. A substan- tial variation in TFR also exists among zobas, ranging from 5.7 children per woman in zoba Debub to 3.4 children per women in zoba Maekel. The level of fertility is negatively associated with educational attainment, decreasing rap- idly from 5.5 children among women with no education to 3.1 children among women who have at least some secon- dary education. An even sharper varia- tion is observed by wealth index. Wo- men in the lowest quintile of the wealth index have a TFR of 6.2, which is twice as high as the fertility level of women in the highest quintile (3.0). Table 4.2 shows the mean num- ber of children ever born to women by the end of their reproductive period (40- 49 years), which is a measure of average completed fertility. Although this meas- ure is susceptible to omission of children born to older women, it allows a general assessment of trends in fertility over Table 4.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of women 15-49 currently pregnant, and mean number of children ever born to women age 40-49, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mean number of children Total Percentage ever born Background fertility currently to women characteristic rate1 pregnant1 age 40-49 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 3.5 7.0 4.8 Asmara 3.0 6.0 4.3 Other towns 4.0 8.1 5.4 Rural 5.7 10.2 6.6 Zoba Debubawi Keih Bahri 3.9 8.9 5.1 Maekel 3.4 7.1 4.8 Semenawi Keih Bahri 4.5 8.9 5.8 Anseba 5.6 8.8 6.3 Gash-Barka 5.1 10.2 6.3 Debub 5.7 9.5 6.6 Education No education 5.5 10.5 6.3 Primary 4.4 9.1 5.3 Middle 3.8 5.5 5.4 Secondary + 3.1 6.2 3.5 Wealth index Lowest 6.2 11.0 7.0 Second 5.6 10.3 6.2 Middle 5.2 9.8 6.5 Fourth 4.4 7.3 5.1 Highest 3.0 6.8 4.5 Total 2002 4.8 8.8 5.9 Total 1995 6.1 9.2 6.2 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Women age 15-49 Fertility | 59 time among population subgroups. One way of examining trends in fertility over time is to compare the total fertility rate (current fertility) for the three years preceding the survey with completed fertility (past fertility). If fertility is stable over time in a population, the TFR and the mean CEB for women age 40-49 will be similar. An overall comparison of these two fertility measures suggests a decline of more than one child over the past few years, from 5.9 to 4.8 children. Fertility has declined in both urban and rural areas, in all zobas, at all educational levels, and for all levels of the household wealth index. The difference be- tween the level of current and completed fertility is highest in zoba Maekel (1.4 children), women in the highest quintile of the wealth index (1.5 children), and women with middle-level education (1.6 children). Another indicator of current fertility, the percentage of women who are currently pregnant is in- cluded in Table 4.2. Overall, 9 percent of the 2002 EDHS respondents were pregnant at the time of the survey. The proportion has declined slightly since 1995. The proportion of currently pregnant women is lower in urban areas (7 percent)—with Asmara having the lowest proportion (6 percent)—than in rural areas (10 percent). Women in zoba Gash-Barka, women with no education, and women in the two lowest quintiles of the wealth index are more likely to be pregnant (10-11 percent) than other women. EDHS 2002 Figure 4.3 Total Fertility Rates by Background Characteristics 4.8 3.5 3.0 4.0 5.7 3.9 3.4 4.5 5.6 5.1 5.7 5.5 4.4 3.8 3.1 6.2 5.6 5.2 4.4 3.0 ERITREA RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub EDUCATION No education Primary Middle Secondary + WEALTH INDEX Lowest Second Middle Fourth Highest 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Births per Woman 4.3 FERTILITY TRENDS Besides the comparison of current and completed fertility, trends in fertility can be assessed in two ways. First, the TFRs from the current survey can be compared with estimates obtained in earlier surveys. Second, fertility trends can be investigated using retrospective data from the same survey. Comparison with the 1995 EDHS Table 4.3 presents the ASFRs and TFRs from the 2002 EDHS and 1995 EDHS surveys. The table shows that fertility has declined since the last survey from 6.1 children per woman to 4.8 children, a drop of 21 percent. Urban fertility has declined from 4.2 to 3.5 children per woman or 17 percent, while the rural fertility has declined even more (19 percent), more than one child—from 7.0 to 5.7 children—over the same period. Although not shown in Table 4.3, Asmara experienced a smaller decline in fertility from 60 | Fertility 3.7 to 3.0, but the percent decline in Asmara is the same as in rural areas. The percent decline is highest in other towns, 22 percent (from 5.1 to 4.0 children). Table 4.3 Trends in fertility Age-specific fertility rates and total fertility rates (TFR) for the three years preceding the survey, by residence, Eritrea 1995 and 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban Rural Total ––––––––––– –––––––––––– ––––––––––– Age 2002 1995 2002 1995 2002 1995 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 51 52 97 171 77 125 20-24 145 161 218 282 185 245 25-29 172 215 228 290 204 269 30-34 144 200 221 267 188 245 35-39 123 115 195 224 167 189 40-44 42 83 121 121 88 110 45-49 20 21 62 45 46 37 TFR 3.5 4.2 5.7 7.0 4.8 6.1 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Age-specific fertility rates are per 1,000 women. Table 4.3 and Figure 4.4 show that the fertility decline has been experienced by women of all re- productive ages except those in the oldest age group (45-49), where a slight increase in fertility has oc- curred. (It should be noted that ASFRs for the youngest and the oldest age groups are unstable because of small number of births.) The decline has been more rapid among women under age 35, and most notably among adolescents (38 percent). Fertility has been reduced by around 24 percent among women in the prime reproductive ages (age groups 20-24, 25-29, and 30-34). Figure 4.4 Trends in Age-Specific Fertility Rates, 1995 EDHS and 2002 EDHS * * * * * * * # # # # # # # 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age Group 0 50 100 150 200 250 300 Births per 1,000 women 2002 EDHS 1995 EDHS# * Fertility | 61 The pattern of fertility decline by age is seen in both urban and rural areas. In urban areas, the decline ranges from a high of 49 percent among women age 40-44 to a low of 2 percent among those age 15-19. A small increase in fertility, however, is observed for urban women age 35-39 years. In contrast, rural adolescents have the highest decline (43 percent), followed by women in age groups 20-24 and 25- 29 years (23 percent and 21 percent, respectively). Retrospective Data from 2002 Birth Histories Another way of examining trends in fertility over time is to compare age-specific fertility rates from the 2002 EDHS for successive five-year periods preceding the survey, as presented in Table 4.4. Because women age 50 and over were not interviewed in the survey, the rates are increasingly truncated as the number of years before the survey increases. For example, the rates cannot be calculated for women age 35-39 for the period 15-19 years before the survey, because these women would have been over age 50 at the time of the survey and were not interviewed. Partially truncated rates are enclosed in brackets in the table. It should be noted that misre- porting of dates of birth of children could result in incorrect trends in fertil- ity. Nevertheless, the results presented in the table provide further insights into the fertility decline documented above. The data indicate a 12 percent decline in fertility among women age 15-29, from 2.8 children per women during the period 15-19 years before the survey to 2.5 children per woman during the pe- riod 0-4 years prior to the survey. The ASFRs suggest that most of the fertility decline among younger women (15-29) occurred between the two most recent five-year periods. A 26 percent decline in fertility among women age 15-29 took place between 5-9 and 0-4 years before the survey. With the exception of the two younger age groups (i.e., 15-19 and 20-24), which show slight increases for the period 10-14 to 5-9 years prior to the survey, a decline in fertility over the last 15 years has occurred in all age groups. As indicated earlier, during the two most recent five-years periods (5-9 to 0-4 preceding the survey), the decline is highest for adolescents (15-19), 33 percent, and lowest for women in the age group 35-39 (20 percent). The decline in fertility in Eritrea cannot be attributed to an increasing use of contraception because the contraceptive prevalence rate has remained unchanged since 1995. Reduced levels of sexual activity (see Chapter 6), increases in the median birth interval (see section 4.5), and lower proportions of currently married women in the prime reproductive ages (see Chapter 6), are the primary factors responsible for the decline in fertility. 4.4 CHILDREN EVER BORN AND LIVING Information on lifetime fertility is useful for examining the momentum of childbearing and for estimating levels of primary infertility. As mentioned above, the number of children ever born is useful in understanding the changes that have taken place in the age pattern of current fertility. Table 4.4 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother’s age at the time of the birth, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of years preceding the survey Mother’s age at –––––––––––––––––––––––––––––––––––––––––– time of the birth 0-4 5-9 10-14 15-19 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 85 127 111 95 20-24 199 253 251 211 25-29 214 295 296 259 30-34 213 287 298 [288] 35-39 183 228 [273] 40-44 102 [165] 45-49 [51] ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. 62 | Fertility Table 4.5 shows the percent distribution of all women and currently married women by the number of children ever born, according to age. It also shows the mean number of children ever born and mean number of living children. The difference between the mean number of children ever born and the mean number of living children is an indicator of the level of mortality in the population. On average, Eritrean women age 15-49 have given birth to 2.7 children, of which 2.3 children are still alive, indicating that 14 percent of the children ever born have died. The mean number of children ever born has declined by 10 percent from 3.0 children reported in the 1995 EDHS. The number of children that women have borne increases with age, from 0.1 children for women age 15-19 to more than two children for women in the late twenties, about five children for women in the late thirties, and to more than six children for women at the end of their reproductive years (45-49). Of the 6.2 children ever born to women age 45-49, only 5.0, or about 81 percent, have survived. A similar pattern of lifetime fertility is observed for currently married women except that the mean number of children ever born is higher for currently married women than for all women at all ages, particularly for women at younger and older ages. The difference between currently married women and all women in the mean number of children ever born to younger women is due to a substantial proportion of unmarried young women having minimal fertility. Differences at older ages generally reflect the impact of marital dissolution through either divorce or widowhood. The distribution of women by children ever born shows that among all women only one in ten age 15-19 has already become a mother, indicating that early childbearing is not common in Eritrea. Six in ten women age 45-49 have had six or more children, indicating a pronatalist tendency. There is a sharp Table 4.5 Children ever born and living Percent distribution of all women and currently married women by number of children ever born, mean number of children ever born, and mean number of living children, according to age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mean Mean Number of children ever born Number number number –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– of of children of living Age 0 1 2 3 4 5 6 7 8 9 10+ Total women ever born children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– ALL WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 89.0 9.2 1.7 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 2,001 0.13 0.12 20-24 43.5 26.9 18.6 8.3 2.3 0.4 0.0 0.0 0.0 0.0 0.0 100.0 1,454 1.00 0.91 25-29 18.3 17.9 22.2 21.5 13.3 4.6 1.9 0.2 0.1 0.0 0.0 100.0 1,543 2.16 1.97 30-34 9.4 9.2 14.2 15.5 20.1 13.9 9.7 5.0 1.9 0.5 0.6 100.0 1,109 3.53 3.13 35-39 5.3 6.0 8.9 12.2 11.5 16.4 15.1 11.9 8.0 3.3 1.3 100.0 1,085 4.70 4.09 40-44 3.1 5.1 7.3 8.1 10.0 10.2 17.1 11.3 11.6 8.6 7.6 100.0 827 5.66 4.73 45-49 3.4 3.3 6.0 8.7 9.0 9.5 11.0 12.1 11.8 11.4 13.9 100.0 734 6.20 5.04 Total 2002 33.2 12.4 11.5 10.2 8.4 6.4 6.0 4.2 3.3 2.2 2.1 100.0 8,754 2.66 2.30 Total 1995 28.9 13.6 10.8 9.6 7.9 7.3 6.4 5.1 4.5 2.9 3.1 100.0 5,054 3.01 2.46 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– CURRENTLY MARRIED WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 66.5 27.6 5.3 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 580 0.40 0.37 20-24 23.8 33.2 26.8 12.3 3.2 0.6 0.0 0.0 0.0 0.0 0.0 100.0 950 1.40 1.27 25-29 8.4 16.6 25.1 25.4 16.2 5.6 2.4 0.2 0.1 0.0 0.0 100.0 1,212 2.52 2.30 30-34 4.2 6.8 13.2 16.2 22.0 16.4 11.4 6.1 2.2 0.6 0.8 100.0 904 3.94 3.51 35-39 2.7 4.4 7.7 10.6 11.6 18.1 17.0 13.8 8.7 4.0 1.6 100.0 899 5.09 4.42 40-44 2.4 3.6 5.2 6.6 9.4 9.8 17.6 12.9 13.8 10.1 8.6 100.0 663 6.08 5.09 45-49 2.1 2.1 2.7 4.7 6.8 8.3 11.3 15.0 14.3 14.6 18.1 100.0 526 7.01 5.83 Total 2002 14.0 14.2 14.4 12.9 11.0 8.6 8.0 6.0 4.6 3.2 3.0 100.0 5,733 3.57 3.10 Total 1995 11.5 15.0 12.7 11.9 10.1 9.2 8.3 6.7 6.3 4.1 4.2 100.0 3,371 3.92 3.22 Fertility | 63 decline in the proportion of early childbearing since 1995, from 19 percent to 11 percent, a decline of 40 percent. Results in Table 4.5 indicate that childlessness decreases with increasing age. For teenagers (15- 19 years of age), 89 percent among all women and 67 percent among currently married women have not started childbearing. Since the desire for children is nearly universal in Eritrea, the proportion of married women age 45-49 years who are still childless can be taken as a rough indicator of primary infertility, or the inability to bear children. The survey results suggest that primary infertility is low in Eritrea, with only 2 percent of Eritrean women not able to bear children. It should be pointed out that this estimate does not include women who have had one or more children but who are unable to have more children (secondary infertility). 4.5 BIRTH INTERVALS The birth interval refers to the period of time between two successive live births. Information on birth intervals is important in providing insight into birth spacing patterns, which are known to have an impact on fertility as well as levels of infant and child mortality. Previous research has shown that children born too soon after a previous birth are at increased risk of poor health and dying at an early age. This is particularly true for babies born less than 24 months after a previous birth. Maternal health is also jeopardized when births are closely spaced. Table 4.6 shows the percent distribution of second- and higher-order births in the five years preceding the survey by number of months since the previous birth, according to background characteristics. One in five non-first births in Eritrea occurs less than 24 months after the preceding birth, including 8 percent that occur after an interval of less than 18 months. In other words, the majority of Eritrean children (80 percent) are born at least 24 months after their previous sibling. Thirty-seven percent of second- and higher-order births take place 24-35 months after a prior birth, and 43 percent occur at least three years after the birth of a previous sibling. The overall median birth interval is 33.6 months, which is 10 months longer than the minimum of 24 months considered safe for mother and child. The median birth interval in 2002 is two months longer than the median birth interval of 31.3 months in 1995. There is no substantial difference in the length of the median birth interval by sex of preceding birth, residence, or women’s education level. The median birth interval for the seventh- and higher-order births is three months shorter than intervals for lower-order births. Birth intervals vary by zoba. The median birth interval in zobas Maekel and Gash-Barka is 35 months, which is 2-3 months longer than those in other zobas. The median birth interval increases with increasing age of the mother from 26 months for births to young mothers (age 15-19) to 35 months for births to mothers age 30 or older. The proportion of births occurring within 24 months of the preceding birth declines steeply from 47 percent among women age 15-19 to 20 percent among women age 40 and above. The length of the birth interval is closely associated with the survival status of the previous sibling. The median birth interval is more than six months shorter for children whose previous sibling died than for children whose previous sibling is alive (28 months and 34 months, respectively). The percentage of births occurring after a very short interval (less than 18 months) is almost four times higher for children whose prior sibling died than for children whose prior sibling survived. The shorter intervals for the former group are partially due to the shortened period of breastfeeding (or no breastfeeding) for the preceding child, leading to an earlier return of ovulation and hence increased chance of pregnancy. Minimal use of contraception, presumably because of a desire to replace the dead child as soon as possible, could also be one of the factors responsible for the shorter birth interval in these cases. However, this reason is probably not as important in Eritrea as in other countries that have higher contraceptive prevalence rates. 64 | Fertility Table 4.6 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Median Number number of Number of months since preceding birth of months since Background –––––––––––––––––––––––––––––––––––––––––––––––––––––––– non-first preceding characteristic 7-17 18-23 24-35 36-47 48+ Total births birth –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 (20.0) (26.5) (25.6) (26.0) (2.0) 100.0 37 25.9 20-29 7.5 13.9 40.2 22.5 15.9 100.0 1,842 32.2 30-39 7.6 10.6 35.5 23.8 22.6 100.0 2,206 34.7 40-49 8.3 11.3 33.9 26.3 20.3 100.0 903 34.8 Birth order 2-3 7.4 13.3 34.0 22.7 22.6 100.0 2,104 34.1 4-6 6.7 10.8 37.4 25.2 19.9 100.0 1,878 34.4 7+ 10.5 11.9 41.7 23.4 12.5 100.0 1,006 31.5 Sex of preceding birth Male 7.5 12.2 37.6 22.8 19.9 100.0 2,556 33.4 Female 8.0 11.9 36.0 24.9 19.1 100.0 2,432 33.9 Survival of preceding birth Living 6.2 11.8 37.4 24.6 20.1 100.0 4,509 34.1 Dead 22.6 14.7 31.9 16.6 14.3 100.0 479 28.4 Residence Total urban 8.5 12.3 32.6 21.6 25.0 100.0 1,545 34.3 Asmara 11.6 13.2 28.8 18.7 27.7 100.0 589 34.4 Other towns 6.6 11.7 34.9 23.5 23.3 100.0 957 34.2 Rural 7.4 11.9 38.8 24.8 17.1 100.0 3,443 33.4 Zoba Debubawi Keih Bahri 13.3 12.9 31.4 18.7 23.7 100.0 140 32.2 Maekel 10.2 12.1 31.6 20.6 25.5 100.0 824 34.6 Semenawi Keih Bahri 7.2 13.8 37.0 22.9 19.1 100.0 711 32.7 Anseba 5.3 14.3 41.4 22.6 16.4 100.0 759 32.5 Gash-Barka 6.0 11.3 36.0 27.5 19.2 100.0 905 35.0 Debub 8.4 10.6 38.2 24.7 18.0 100.0 1,649 33.5 Education No education 7.2 12.4 37.7 24.1 18.6 100.0 3,409 33.5 Primary 7.2 9.7 37.4 25.6 20.1 100.0 880 34.3 Middle 10.2 14.1 33.9 18.9 22.8 100.0 254 33.4 Secondary + 11.8 12.8 30.9 20.7 23.9 100.0 446 33.6 Total 2002 7.8 12.0 36.9 23.8 19.5 100.0 4,988 33.6 Total 1995 11.0 14.6 39.0 20.3 15.1 100.0 3,296 31.3 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 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. ( ) Estimate based on 25-49 unweighted cases. Fertility | 65 4.6 AGE AT FIRST BIRTH A woman’s age at the onset of childbearing is one of the factors that determine the level of current fertility in a population. Early initiation of childbearing leads to a longer reproductive period for the woman, which leads to a larger family size, which leads to rapid population growth, particularly in countries like Eritrea, where family planning is not widely practiced. Moreover, early age at first birth (under 20) has a detrimental effect on the health of both mother and child. A rise in the median age at first birth is generally a sign of transition to a lower fertility level. Table 4.7 shows the percentage of women who have given birth by specific exact ages, and median age at first birth, according to current age. Early childbearing is not common in Eritrea; the majority of women become mothers after age 20. Six percent of women age 40-44, 4 percent of women age 45-49, and 1 percent of women age 15-19 had given birth to their first child before age 15. The age at first birth has been decreasing over time. For example, 47 percent of women age 45-49, compared to 62 percent of women age 25-29 had their first birth by age 22. The median ages at first birth are 20.6 and 20.8 years for the age groups 25-29 and 30-34, respectively, and are higher (22-23 years) for older cohorts. The median age at first birth for women in most age groups has remained unchanged since the last survey with the exception of women age 45-49, for whom an increase of more than one year is indicated (from 21.1 years in 1995 to 22.5 years in 2002). This increase is not plausible because almost all married women in the age group 45-49 married many years ago. Table 4.7 Age at first birth Percentage of women who had their first birth by specific exact ages, and median age at first birth, according to current age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of women who had their Percentage Median first birth by exact age: who have Number age at –––––––––––––––––––––––––––––––––––––––––––––––––– never of first Current age 15 18 20 22 25 given birth women birth ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 1.0 na na na na 89.0 2,001 a 20-24 4.9 25.4 42.4 na na 43.5 1,454 a 25-29 3.4 22.0 44.3 61.8 76.4 18.3 1,543 20.6 30-34 4.2 24.6 42.7 59.2 77.0 9.4 1,109 20.8 35-39 3.0 17.4 32.1 50.5 73.5 5.3 1,085 21.9 40-44 6.2 17.0 32.4 49.3 70.8 3.1 827 22.1 45-49 3.6 17.3 32.2 46.7 64.4 3.4 734 22.5 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable a Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group Differentials in median age at first birth for women 25-49 by background characteristics are shown in Table 4.8. Younger women are not included in the analysis because less than 50 percent of women age 15-19 and 20-24 had a birth before age 15 and 20, respectively. The overall median age at first birth for women age 25-49 is 21 years. The median age at first birth has remained unchanged since the last survey but the median age in Eritrea is higher than that reported for some African countries in which recent DHS surveys have been conducted. For example, the median age at first birth is 19 years in Ethiopia (CSA and ORC Macro, 2001), Uganda (UBOS and ORC Macro, 2001), and Malawi (NSO and ORC Macro, 2001), and 20 years in Nigeria (NPC, 2000). 66 | Fertility Table 4.8 Median age at first birth by background characteristics Median age at first birth among women 25-49, by current age and background characteris- tics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Current age Women Background ––––––––––––––––––––––––––––––––––––––––––––– age characteristic 25-29 30-34 35-39 40-44 45-49 25-49 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 21.9 21.7 22.3 22.7 21.9 22.0 Asmara 23.7 24.7 23.5 23.4 21.7 23.5 Other towns 20.3 20.5 21.4 21.8 22.0 20.9 Rural 19.8 20.3 21.7 21.9 23.0 21.0 Zoba Debubawi Keih Bahri 22.1 22.4 22.8 22.2 23.2 22.4 Maekel 22.9 23.1 23.1 23.2 21.7 22.9 Semenawi Keih Bahri 21.1 21.1 21.5 21.5 23.9 21.5 Anseba 19.7 21.2 22.0 22.3 23.6 21.2 Gash-Barka 19.7 20.5 21.4 21.0 21.1 20.6 Debub 19.6 19.7 21.5 22.7 23.0 20.7 Education No education 19.7 20.4 21.6 21.9 22.9 21.1 Primary 19.9 20.2 20.9 21.8 22.1 20.7 Middle 20.5 (20.9) (24.7) * * 21.3 Secondary + 24.4 25.3 25.5 23.7 * 24.6 Wealth index Lowest 19.7 20.5 21.6 21.7 23.0 21.1 Second 19.7 20.6 21.7 22.2 22.8 21.1 Middle 19.8 19.6 21.5 21.7 23.3 20.8 Fourth 20.3 20.3 21.9 21.9 21.1 20.8 Highest 23.6 23.8 23.0 23.0 22.0 23.1 Total 2002 20.6 20.8 21.9 22.1 22.5 21.4 Total 1995 20.9 20.8 22.1 22.0 21.1 21.4 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 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. The median is higher for women in urban areas than women in rural areas or other towns, a difference of one year (22 and 21 years, respectively). The urban-rural difference is highest (2 years) for women in the younger age groups, 25-29 and 30-34. Women in Asmara (24 years) start childbearing almost three years later than women in other towns (21 years) and in rural areas (21 years). Zoba Maekel has the highest median age at first birth (23 years), followed closely by zoba Debubawi Keih Bahri (22 years). Zobas Gash-Barka and Debub have the lowest median age at first birth (21 years). There is almost no difference in median age at first birth between women who have never attended school and those with primary and middle levels of education. However, women with at least some secondary education begin childbearing 3-4 years later than less educated and uneducated women. Women in the highest wealth quintile have a median age at first birth of 23 years; this is at least two years later than women in the other four wealth quintiles. 4.7 ADOLESCENT FERTILITY The issue of adolescent fertility is important for both health and social reasons. Children born to very young mothers (under 20 years of age) face an increased risk of illness and death. Adolescent Fertility | 67 mothers themselves are more likely than more mature women to suffer from severe complications during pregnancy and delivery, leading to maternity-related mortality. Moreover, the ability of teenage mothers to advance in the areas of educational attainment and job opportunities may be curtailed. The percentage of adolescent women (age 15-19) who are mothers or who are pregnant with their first child is shown in Table 4.9. The level of teenage childbearing in Eritrea is 14 percent, of which 3 percent are pregnant with their first child. Teenage fertility has declined substantially in Eritrea. Adolescent childbearing in 2002 was 39 percent lower than that reported in 1995, when the proportion of teenagers who had begun childbearing was 23 percent. The proportion of teenagers on the family formation path rises rapidly with age. Only 2 percent of women age 15 have started childbearing, but by age 19, 36 percent of women have had a baby or are pregnant with their first child. Compared with the 1995 EDHS results, teenage childbearing has declined for all ages (Figure 4.5); the largest decline in childbearing occurred among women age 16 (78 percent), followed by women age 17 (64 percent). In rural areas, the level of teenage childbearing (19 percent) is more than twice as high as in urban areas (8 percent). Women in Asmara have the lowest level of teenage childbearing (4 percent). Early motherhood has remained unchanged in urban women, indicating that the decline in teenage childbearing at the national level is mainly due to the decline in early childbearing among rural women. In 1995, one in three rural teenagers had started childbearing, compared with one in five in 2002, a decline of more than 40 percent. A negative correlation between women’s education and early motherhood is apparent from the survey results. The proportion of women age 15-19 who are pregnant or who have already given birth decreases from 25 percent among women with no education to 7 percent among women with at least some secondary education. Childbearing among teenagers is lowest in zoba Maekel (6 percent) and highest in zobas Debub and Gash-Barka (21 percent and 20 percent, respectively). Differentials by wealth index show an increase in adolescent childbearing from 13 percent among women in the lowest quintile to 23 percent among women in the middle quintile, then declines to 5 percent among women in the highest quintile. 68 | Fertility Table 4.9 Teenage pregnancy and motherhood Percentage of women age 15-19 who are mothers or pregnant with their first child, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage who are: Percentage ––––––––––––––––––––– who have Pregnant begun Number Background with first child- of characteristic Mothers child bearing women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15 0.9 1.2 2.1 426 16 2.2 0.6 2.8 424 17 6.1 1.8 7.9 326 18 19.4 4.7 24.0 546 19 29.0 7.3 36.3 280 Residence Total urban 6.5 1.1 7.6 917 Asmara 3.7 0.6 4.3 456 Other towns 9.3 1.6 10.9 461 Rural 14.7 4.6 19.3 1,084 Zoba Debubawi Keih Bahri 12.0 1.7 13.7 56 Maekel 4.7 1.6 6.3 564 Semenawi Keih Bahri 7.1 4.0 11.1 196 Anseba 8.3 1.3 9.6 266 Gash-Barka 17.5 2.8 20.3 304 Debub 15.9 4.8 20.7 616 Education No education 20.1 5.2 25.3 424 Primary 12.0 4.2 16.2 487 Middle 8.3 2.6 10.9 510 Secondary + 5.8 0.7 6.5 580 Wealth index Lowest 9.5 3.7 13.2 298 Second 14.7 5.2 19.9 362 Middle 18.0 5.4 23.3 377 Fourth 10.7 1.0 11.7 448 Highest 4.4 0.9 5.4 516 Total 2002 11.0 3.0 14.0 2,001 Total 1995 18.8 4.2 23.0 1,129 Fertility | 69 Figure 4.5 Trends in Adolescent Fertility by Age and Residence, 1995 EDHS and 2002 EDHS 0 2 3 8 24 36 8 4 11 19 0 3 13 22 40 50 7 4 14 33 AGE 15 16 17 18 19 RESIDENCE Total urban Asmara Other towns Rural 0 10 20 30 40 50 60 Percentage who Are Mothers or Pregnant with First Child 2002 EDHS 1995 EDHS Fertility Regulation | 71 FERTILITY REGULATION 5 This chapter presents the 2002 EDHS results regarding various aspects of contraceptive knowledge, attitudes, and behavior. The chapter starts with data on knowledge of contraceptive methods and sources of contraceptive methods, on the channels through which Eritrean women receive information about family planning, and the acceptability of electronic media providing information about family planning. Then interpersonal communication about family planning and attitudes toward use of family planning are discussed. After presenting knowledge of, and attitudes toward family planning, levels of ever-use and current use of family planning methods and sources of methods are examined. The last part of the chapter focuses on women who are not using family planning and covers the following topics: reasons for nonuse, intention to use in the future, preferred methods for women who intend to use in the future, and the main reasons for not planning to use in the future. The chapter closes with an evaluation of the role of health facilities in motivating nonusers to adopt family planning. 5.1 KNOWLEDGE OF CONTRACEPTIVE METHODS AND SOURCES Knowledge of Methods Knowledge of contraceptive methods and knowledge of sources of contraceptives are preconditions for their use. Information on knowledge of family planning methods was collected by first asking the respondent to name ways or methods by which a couple could delay or avoid pregnancy. If the respondent failed to mention any of the methods listed in the questionnaire, the interviewer described the method and asked whether she had heard about it. No questions were asked to elicit information on the depth of knowledge of any method except for periodic abstinence. Because married women have the greatest level of exposure to the risk of pregnancy, the following presentation places more emphasis on this group. The results in Table 5.1 show that almost nine in ten women know of at least one modern method of family planning. Knowledge of methods is almost universal among sexually active unmarried women. The pill, male condoms, and injectables are the most widely known modern methods among all subgroups. Four in five currently married women know about the pill, and three-fourths know about condoms and injectables. Female sterilization and IUDs are equally likely to be known by currently married respondents–almost 25 percent each. Nineteen percent of currently married women know about female condoms. Knowledge of other modern methods is low. Traditional methods are not as well known as the modern methods. Among currently married women, the lactational amenorrhea method (LAM)1 is the most commonly known traditional method (50 percent). Thirty-six percent of women know about periodic abstinence and 13 percent mentioned withdrawal. Knowledge of most modern and traditional methods is higher among all women and unmarried women, especially among those who ever had sex, than among currently married women. Knowledge of family planning methods in general and of specific methods has increased since the 1995 EDHS (Figure 5.1). Among all women and currently married women, overall awareness of any method and any modern method has increased by at least 20 percentage points. The most notable increases in knowledge of specific methods among currently married women are for condoms and the 1 LAM is categorized as a traditional method in this survey because while 2 percent of currently married women said they were using LAM, less than 1 percent fit the criteria for LAM users. 72 | Fertility Regulation injectables–from 35 percent to 75 percent for condoms and from 51 percent to 74 percent for injectables. The mean number of methods known by all women increased by almost two methods from 2.6 in 1995 to 4.4 in 2002. Table 5.1 Knowledge of contraceptive methods Percentage of all women, of currently married women, of sexually active unmarried women, of sexually inactive unmarried women, and of women with no sexual experi- ence who know any contraceptive method, by specific method, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Unmarried women who ever had sex Un- –––––––––––––––––– married Currently Not women All married Sexually sexually who never Contraceptive method women women active1 active2 had sex ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Any method 88.9 87.5 99.3 90.8 91.5 Any modern method 87.2 85.0 99.3 89.7 91.3 Female sterilization 23.8 23.2 33.6 30.3 21.8 Male sterilization 7.1 6.3 14.0 5.9 9.8 Pill 78.7 78.0 88.0 80.1 79.5 IUD 24.7 23.9 42.1 28.0 24.5 Injectables 73.1 73.6 76.2 73.4 71.4 Implants 8.5 8.0 15.1 9.6 9.3 Male condom 78.6 75.2 81.5 80.9 86.8 Female condom 23.0 18.8 38.9 22.0 35.7 Diaphragm 10.9 8.1 19.4 10.0 19.6 Foam/jelly 6.1 5.3 14.5 6.5 7.8 Emergency contraception 10.4 9.6 19.4 11.8 11.4 Any traditional method 56.4 59.0 66.0 61.1 45.8 Lactational amenorrhea method (LAM) 45.4 50.1 43.5 50.3 28.8 Periodic abstinence 35.5 35.5 56.8 39.0 32.8 Withdrawal 13.7 13.2 23.6 16.2 13.3 Folk method 1.0 0.8 0.0 1.5 1.2 Mean number of methods known 4.4 4.3 5.7 4.7 4.5 Number of women 8,754 5,733 56 1,038 1,939 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1Had sexual intercourse in the month preceding the survey 2Did not have sexual intercourse in the month preceding the survey Fertility Regulation | 73 Figure 5.1 Trends in Knowledge of Family Planning Methods Among Currently Married Women, 1995 EDHS and 2002 EDHS 88 87 23 6 78 24 74 75 59 36 13 64 62 24 6 60 17 51 35 33 18 7 ANY METHOD ANY MODERN METHOD Female sterilization Male sterilization Pill IUD Injectables Male condom ANY TRADITIONAL METHOD Periodic abstinence Withdrawal 0 20 40 60 80 100 Percent 2002 EDHS 1995 EDHS Knowledge of the Fertile Period An elementary understanding of reproductive physiology, particularly knowledge of the period in the ovulatory cycle when pregnancy is most likely, is critical for the practice of periodic abstinence. To investigate women’s knowledge about the fertile period, respondents were asked whether there are certain days between the two menstrual periods when a woman is more likely to become pregnant if she has sex- ual intercourse. Those who answered affirmatively to the question were asked whether this time is just before the period begins, during the period, right after the period ends, or halfway between the two periods. Table 5.2 shows that only one in nine respondents knows that a woman has the highest probability of be- coming pregnant if she has sexual intercourse halfway between two periods. Thirty- seven percent of respondents either were unable to say when a woman is most at risk of pregnancy or be- lieved that the risk of preg- nancy does not vary. Even among those who know of periodic abstinence as a fam- ily planning method and among those who are current Table 5.2 Knowledge of fertile period Percent distribution of women by knowledge of the fertile period during the ovula- tory cycle, according to knowledge of periodic abstinence and current use/nonuse of periodic abstinence, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Nonuser Knows of User of of periodic periodic periodic All Perceived fertile period abstinence abstinence abstinence women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Just before her period begins 5.2 (4.3) 4.0 4.0 During her period 2.0 (0.0) 2.0 2.0 Right after her period has ended 56.9 (63.6) 45.1 45.2 Halfway between two periods 17.7 (32.1) 11.1 11.2 Other 0.0 (0.0) 0.1 0.1 No specific time 10.7 (0.0) 19.5 19.4 Don't know 7.4 (0.0) 17.9 17.8 Missing 0.2 (0.0) 0.2 0.2 Total 100.0 100.0 100.0 100.0 Number of women 3,106 41 8,713 8,754 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 25-49 unweighted cases. 74 | Fertility Regulation users of the method, understanding of the ovulatory cycle is limited; 18 percent and 32 percent, respec- tively, of these women had correct knowledge of the fertile period in the ovulatory cycle. Differentials in Knowledge of Contraceptive Methods and Knowledge of Sources of Contraceptive Methods Differentials in knowledge of contraceptive methods by residence and education show that only eight in ten rural women and uneducated women know any modern method, whereas knowledge of a modern method is almost universal among urban women and educated women (Table 5.3). Women in Table 5.3 Knowledge of contraceptive methods by background characteristics Percentage of currently married women who know at least one contraceptive method, who know at least one modern method, and who know a source for obtaining a method, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mean Mean Knows number Knows Knows number any of modern source Number Background any of methods modern methods for of characteristic method known method1 known methods women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 87.0 3.8 85.9 3.1 33.4 580 20-24 87.7 4.3 85.2 3.3 41.4 950 25-29 88.4 4.6 86.8 3.5 48.1 1,212 30-34 87.8 4.3 84.1 3.3 43.5 904 35-39 88.2 4.5 85.9 3.4 45.8 899 40-44 85.6 4.1 82.2 3.1 39.6 663 45-49 86.0 3.9 83.1 3.0 39.0 526 Residence Total urban 97.7 6.2 97.2 4.7 70.8 1,967 Asmara 99.2 7.0 98.6 5.2 78.7 868 Other towns 96.5 5.7 96.1 4.3 64.5 1,099 Rural 82.2 3.3 78.7 2.6 27.9 3,766 Zoba Debubawi Keih Bahri 77.8 4.0 72.8 3.0 43.1 210 Maekel 98.6 6.5 97.6 4.9 70.9 1,103 Semenawi Keih Bahri 86.9 3.6 84.7 2.8 34.6 817 Anseba 82.5 3.5 79.7 2.7 32.3 784 Gash-Barka 69.6 2.7 64.1 2.1 24.8 1,142 Debub 96.2 4.7 95.1 3.6 44.8 1,677 Education No education 80.6 3.1 76.8 2.4 26.4 3,549 Primary 97.7 5.3 97.3 4.0 57.6 1,075 Middle 99.2 6.1 98.8 4.7 65.3 400 Secondary + 99.7 7.8 99.5 5.8 88.2 709 Wealth index Lowest 74.3 2.5 69.5 2.0 17.5 1,161 Second 79.2 3.1 75.6 2.4 26.6 1,215 Middle 89.1 3.7 86.7 2.9 33.8 1,224 Fourth 97.7 5.6 96.9 4.2 60.4 1,079 Highest 99.3 7.0 98.8 5.3 80.9 1,053 Total 87.5 4.3 85.0 3.3 42.6 5,733 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1Female sterilization, male sterilization, pill, IUD, injectables, implants, male condom, female condom, diaphragm, foam or jelly, and emergency contraception Fertility Regulation | 75 zobas Debubawi Keih Bahri and Gash-Barka are less likely to know of family planning methods than women in other zobas. Knowledge of family planning methods is positively related to wealth. The mean number of modern methods known varies from 2.0 for women in the lowest quintile of the wealth index to 5.3 methods for women in the highest quintile. In the 2002 EDHS, users of modern methods were asked the source of their method and non- users of modern methods were asked if they knew where they could obtain a method of family planning. Table 5.3 shows that 43 percent of currently married women know a place where they can get a contraceptive method. For background characteristics, knowledge of a source of family planning methods is related to knowledge of any method. 5.2 EXPOSURE TO FAMILY PLANNING INFORMATION Radio and television are the major sources of information about family planning in the electronic media. Print media, that is newspapers or magazines, posters, and leaflets or brochures, can also provide family planning information. Assessment of the level of public exposure to various media allows program managers and planners to effectively target population subgroups for information, education, and communication campaigns. The 2002 EDHS respondents were asked whether in the last 12 months they had heard about family planning on the radio or television or read about family planning in a newspaper or magazine, a poster, or leaflets or brochures. Table 5.4 shows that half of women have heard a family planning message on the radio, the major medium used by all subgroups. Women’s exposure to all other media is much lower. Nineteen percent of women reported having seen a family planning message on television, and the same proportion saw a family planning message on a poster. Only 16 percent saw a family planning message in newspapers or magazines. Forty-five percent of women were not exposed to family planning messages in any of these media. Exposure to family planning messages in all five media has increased since the 1995 EDHS (see the last two rows of the table). Rural women are less likely than urban women to have been exposed to family planning messages in the media. However, since 1995 there has been a sharp increase in exposure to messages on radio among rural women—from 22 percent to 37 percent—while there has been no change in exposure among women in Asmara and other urban areas (Figure 5.2). Although the proportion of Eritrean women who have seen a family planning message on television increased from 11 percent to 19 percent between the two surveys, only 4 percent of rural womenthe same proportion who watch television weekly have been exposed to family planning messages on television. The limited exposure of rural women to television messages is understandable because less than 1 percent of rural households own a television. Exposure to print media is still low in Eritrea but has increased substantially since 1995 because of the progress made in female education (see Chapter 3). Exposure to each medium decreases with age, most notably for print media. Level of education is closely correlated with exposure to family planning messages in both the print media and the two electronic media. For example, 33 percent of uneducated women compared with 77 percent of women with at least secondary education have heard a family planning message on the radio. 76 | Fertility Regulation Table 5.4 Exposure to family planning messages Percentage of women who have heard or seen a family planning message on the radio or television, or in a newspaper/magazine, or on posters or leaflets/brochures in the past 12 months, according to back- ground characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– None Exposed to family planning messages on: of these ––––––––––––––––––––––––––––––––––––––––––––––––– five Number Background Tele- Newspaper/ Leaflets/ media of characteristic Radio vision magazine Poster brochures sources women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 54.0 21.2 22.2 24.6 19.0 39.0 2,001 20-24 53.0 20.0 19.9 22.5 16.5 42.2 1,454 25-29 52.9 20.8 15.3 18.9 13.8 43.5 1,543 30-34 47.6 16.4 12.3 16.1 10.4 49.5 1,109 35-39 50.8 18.1 12.1 14.7 8.9 46.4 1,085 40-44 44.2 17.3 10.0 14.1 8.9 53.6 827 45-49 41.1 13.8 5.6 9.5 4.3 56.2 734 Residence Total urban 68.5 39.4 29.8 32.4 26.0 24.8 3,767 Asmara 75.9 55.5 40.2 39.0 33.7 16.3 1,899 Other towns 61.1 23.1 19.3 25.6 18.1 33.4 1,868 Rural 36.7 3.5 4.8 8.3 3.5 60.9 4,987 Zoba Debubawi Keih Bahri 30.3 14.3 10.6 17.5 10.6 63.4 324 Maekel 75.2 49.5 36.1 36.5 30.3 17.4 2,264 Semenawi Keih Bahri 33.5 7.9 6.7 10.6 5.9 63.1 1,148 Anseba 37.9 10.0 9.0 11.6 7.0 58.9 1,130 Gash-Barka 38.3 3.4 5.1 8.7 3.9 59.4 1,500 Debub 51.4 9.9 10.7 15.5 9.5 45.7 2,388 Education No education 32.8 4.1 1.1 4.2 0.7 65.6 4,384 Primary 60.3 19.5 13.2 18.9 10.4 35.8 1,637 Middle 65.9 29.2 28.9 31.0 24.3 28.0 974 Secondary + 76.6 49.7 46.4 47.8 40.5 13.7 1,760 Total 2002 50.4 18.9 15.6 18.7 13.2 45.4 8,754 Total 1995 36.2 10.5 10.7 10.5 6.6 u 5,054 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– u = Unknown (not available) Fertility Regulation | 77 Figure 5.2 Exposure to Family Planning Messages on Radio, Women Age 15-49, 1995 EDHS and 2002 EDHS Note: Data for 1995 refer to the few months preceding the survey; data for 2002 refer to the 12 months preceding the survey. 50 0 69 76 61 37 30 75 34 38 38 51 36 0 66 73 54 22 19 66 26 19 14 36 TOTAL RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub 0 20 40 60 80 100 Percent 2002 EDHS 1995 EDHS Among zobas, women in zoba Maekel have the highest level of exposure to all five media, with fewer than two in ten women with no exposure to media. Exposure to all types of media is much lower in the other five zobas. Slightly less than half of women in zoba Debub (46 percent) and around six in ten women in other zobas have no exposure to family planning messages through any electronic or print media. Although zoba Debubawi Keih Bahri has the lowest overall exposure to media, women in the zoba have greater exposure to family planning messages on television and in the print media than women in any other zoba except zoba Maekel. 5.3 ACCEPTABILITY OF USE OF ELECTRONIC MEDIA TO DISSEMINATE FAMILY PLANNING MESSAGES To determine the level of acceptance of the dissemination of family planning information through the media, respondents were asked in the 2002 EDHS whether it was acceptable to disseminate family planning information on radio and television. It should be pointed out that the acceptability of dissemination on radio in Eritrea is much more important because the exposure to television is very limited in rural areas where the vast majority of women live (see Table 3.8). Overall, 69 percent of women in the 2002 EDHS reported that it was acceptable to use radio to air family planning messages, up from 57 percent in 1995 (Table 5.5 and Figure 5.3). Although differentials by background characteristics persist, the majority of women in each subgroup now consider it acceptable to have messages about family planning on radio. 78 | Fertility Regulation Table 5.5 Acceptability of media messages on family planning Percent distribution of women by acceptability of messages about family planning on radio and television, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Family planning messages on radio Family planning messages on television ––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––– Not Don’t Not Don’t Number Background Accept- accept- know/ Accept- accept- know/ of characteristic able able Missing Total able able Missing Total women Age 15-19 77.7 13.7 8.7 100.0 65.2 13.3 21.5 100.0 2,001 20-24 72.4 17.8 9.8 100.0 60.8 16.7 22.5 100.0 1,454 25-29 71.9 18.9 9.2 100.0 59.9 17.5 22.6 100.0 1,543 30-34 64.5 22.3 13.2 100.0 51.5 21.1 27.5 100.0 1,109 35-39 66.3 20.7 13.0 100.0 56.4 19.1 24.5 100.0 1,085 40-44 57.0 29.3 13.8 100.0 46.2 26.3 27.5 100.0 827 45-49 55.9 28.4 15.7 100.0 44.0 24.5 31.5 100.0 734 Residence Total urban 85.4 11.5 3.1 100.0 81.1 11.5 7.4 100.0 3,767 Asmara 91.5 7.7 0.8 100.0 90.0 8.6 1.5 100.0 1,899 Other towns 79.2 15.3 5.5 100.0 72.0 14.6 13.4 100.0 1,868 Rural 56.5 26.3 17.1 100.0 39.0 23.7 37.2 100.0 4,987 Zoba Debubawi Keih Bahri 51.7 23.1 25.2 100.0 49.3 23.2 27.5 100.0 324 Maekel 90.3 8.8 0.9 100.0 87.5 9.7 2.8 100.0 2,264 Semenawi Keih Bahri 50.5 31.4 18.1 100.0 33.0 23.7 43.3 100.0 1,148 Anseba 55.0 24.3 20.7 100.0 40.6 23.5 36.0 100.0 1,130 Gash-Barka 55.1 28.7 16.2 100.0 39.8 27.8 32.4 100.0 1,500 Debub 75.2 16.9 7.8 100.0 59.7 15.4 24.9 100.0 2,388 Education No education 50.7 29.7 19.7 100.0 34.3 26.9 38.8 100.0 4,384 Primary 79.2 15.9 4.9 100.0 66.8 14.9 18.3 100.0 1,637 Middle 88.1 9.5 2.4 100.0 79.0 10.4 10.6 100.0 974 Secondary + 94.4 5.2 0.4 100.0 92.8 5.4 1.8 100.0 1,760 Total 2002 68.9 19.9 11.1 100.0 57.1 18.5 24.4 100.0 8,754 Total 1995 56.7 18.0 25.4 100.0 52.2 17.7 30.1 100.0 5,054 Fertility Regulation | 79 Figure 5.3 Trends in Acceptability of Family Planning Messages on Radio, Women Age 15-49 Years, 1995 EDHS and 2002 EDHS 0 85 92 79 57 52 90 51 55 55 75 0 80 86 78 45 30 79 32 21 32 81 RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub 0 20 40 60 80 100 120 Percent 2002 EDHS 1995 EDHS For each subgroup in Table 5.5, the proportion of women who report that it is acceptable to broadcast family planning messages on radio is about the same as the proportion who have exposure to radio (see Table 3.8). Acceptability declines with age, increases with education, is lower in rural areas than in urban areas, and higher in zobas Maekel and Debub than in other zobas. Overall, 57 percent of women in Eritrea consider the dissemination of family planning messages on television acceptable, up from 52 percent in 1995. The differentials by background characteristics in acceptability of television messages on family planning show the same pattern as the differentials in acceptability of messages on radio. For all subgroups, the level of acceptability of messages on television is higher than the level of exposure to television, indicating a general approval of message dissemination through the electronic media. However, in certain subgroups, less than half of women are supportive of having family planning messages on television: women age 40-49 (44-46 percent), rural women (39 percent), uneducated women (34 percent), and women in all zobas except Maekel and Debub. In these subgroups that show a lower support for dissemination of family planning messages, approximately one- fourth of women consider it unacceptable. 5.4 INTERPERSONAL COMMUNICATION ABOUT FAMILY PLANNING Talking about family planning, particularly with a spouse, is not a necessary precondition for adoption of family planning. However, for many women such communication is an important intermediate step. For users of family planning, interpersonal communication may also affect sustained use of contraception, especially for users who experience problems with their method. Discussion of Family Planning with Husband An indication of the acceptability of family planning is the extent to which spouses discuss the topic of family planning with each other. Table 5.6 indicates that in the past 12 months, among currently married women who know a method of family planning, 27 percent have discussed family planning with 80 | Fertility Regulation their husbands at least once and 12 percent have discussed it more often. Women age 20-39 are more likely to discuss family planning with their spouses than women who are younger or older. Discussion of Family Planning with Persons Other than Husband Women were asked in the 2002 EDHS whether they had discussed family planning with relatives, friends, or neighbors (i.e., someone other than the husband) in the past 12 months. The results in Table 5.7 suggest that only one in four currently married Eritrean women discussed family planning with friends or neighbors, 3 percent discussed it with their sisters, and 2 percent discussed it with their mother. Discussion of family planning with other relatives was rare. There are almost no differences by age in the percentage of women who discussed family planning with someone other than their husband. However, in certain subgroups, lower proportions of women discussed family planning with someone other than their husband: rural women (17 percent) and uneducated women (13 percent). Among women whose husbands are uneducated and women who are in the lowest quintile of the wealth index, discussions of family planning with the husband were slightly less common. 5.5 ATTITUDES OF COUPLES TOWARD FAMILY PLANNING Besides knowledge of methods, a positive attitude toward family planning is a prerequisite to adoption of family planning. Attitudinal data were collected by asking respondents whether they approved of a couple using family planning and, if they were currently married, what they thought was their husband’s opinion on the subject. The results presented in Table 5.8 are confined to currently married women and exclude women who do not know any contraceptive method. Overall, 58 percent of married women approve of family planning, 37 percent disapprove, and 5 percent neither approve nor disapprove. Since 1995, women’s approval of family planning has declined from 67 percent to 58 percent (Figure 5.4). Although the proportion of currently married women who discuss family planning with their husbands has remained largely unchanged since the 1995 EDHS survey, the proportion of women reporting that they do not know their husband’s attitude has declined substantially. Two in ten women in 2002, compared with four in ten women in the earlier survey, reported that they did not know their husband’s attitude toward family planning. Approval of family planning by both wife and husband has increased slightly, from 3l to 35 percent. However, disapproval of family planning by both husband and wife has increased substantially, from 10 percent to 25 percent. It is not clear how an increase in the Table 5.6 Discussion of family planning with husband Percent distribution of currently married women who know a contraceptive method by the number of times they discussed family planning with their husbands in the past year, according to current age, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of times family planning was discussed with husband ––––––––––––––––––––––––––––––––––––– Number Once or Three of Age Never two or more Missing Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 74.9 16.3 8.6 0.3 100.0 504 20-24 71.0 16.9 12.0 0.1 100.0 833 25-29 71.5 18.5 9.8 0.2 100.0 1,072 30-34 72.9 14.7 12.4 0.0 100.0 793 35-39 69.4 15.7 14.9 0.0 100.0 793 40-44 75.4 11.8 12.8 0.0 100.0 568 45-49 81.4 8.7 9.6 0.3 100.0 453 Total 73.0 15.3 11.6 0.1 100.0 5,016 Fertility Regulation | 81 proportion of women who could report their husband’s attitude toward family planning has affected their own attitude toward family planning. Table 5.7 Discussion of family planning with persons other than husband Percentage of currently married women knowing at least one contraceptive method who discussed family planning with various persons other than their husband in the past 12 months, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Friends/ Number Background Mother Father neigh- Any of characteristic Mother Father Sister Brother Daughter Son in-law in-law bors Other person women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-24 3.9 0.4 2.8 0.6 0.0 0.0 0.6 0.2 22.1 0.0 23.3 1,337 25-34 1.7 0.1 3.4 0.4 0.0 0.0 0.2 0.2 23.6 0.3 25.2 1,865 35-49 0.8 0.2 2.5 0.7 1.4 0.5 0.2 0.0 21.7 0.3 22.1 1,813 Residence Total urban 2.7 0.1 4.9 0.9 0.8 0.4 0.3 0.1 33.0 0.4 34.5 1,921 Asmara 3.7 0.1 8.8 1.7 1.3 0.8 0.3 0.0 40.8 0.3 43.0 861 Other towns 1.9 0.2 1.7 0.3 0.5 0.0 0.2 0.3 26.7 0.4 27.6 1,060 Rural 1.5 0.2 1.7 0.4 0.3 0.0 0.3 0.1 16.0 0.1 16.8 3,094 Education No education 0.9 0.1 1.1 0.2 0.5 0.1 0.3 0.1 12.4 0.2 12.9 2,861 Primary 1.9 0.0 3.9 0.4 1.0 0.3 0.1 0.3 29.0 0.0 30.5 1,051 Middle 3.2 0.9 4.6 1.3 0.3 0.3 0.6 0.0 35.8 0.4 36.9 397 Secondary + 5.8 0.4 7.9 2.0 0.0 0.1 0.5 0.1 46.5 0.4 48.8 707 Husband’s education No education 0.8 0.2 1.0 0.1 0.3 0.1 0.2 0.1 11.2 0.1 11.7 2,171 Primary 2.7 0.0 3.1 0.2 1.0 0.3 0.6 0.1 24.7 0.1 26.0 1,172 Middle 1.4 0.5 3.7 0.9 0.2 0.2 0.4 0.6 29.5 0.4 31.1 509 Secondary + 3.6 0.2 6.3 1.8 0.5 0.2 0.1 0.1 38.6 0.3 40.4 1,121 Wealth index Lowest 1.4 0.2 1.3 0.2 0.4 0.2 0.1 0.0 10.2 0.2 10.7 862 Second 1.8 0.0 1.5 0.4 0.2 0.0 0.5 0.0 13.5 0.2 14.3 963 Middle 1.3 0.3 1.5 0.2 0.4 0.0 0.3 0.3 17.4 0.0 17.9 1,090 Fourth 1.6 0.2 3.2 0.7 0.3 0.0 0.3 0.2 29.8 0.0 30.8 1,054 Highest 3.5 0.3 6.8 1.3 1.2 0.7 0.3 0.1 39.0 0.7 41.3 1,046 Total 2.0 0.2 2.9 0.6 0.5 0.2 0.3 0.1 22.5 0.2 23.6 5,016 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 43 women who did not know husband’s education; they are not shown separately. 82 | Fertility Regulation Table 5.8 Attitudes toward family planning Percent distribution of currently married women who know of a method of family planning, by approval of family planning and their perception of their husband’s attitude toward family planning, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Respondent approves Respondent disapproves of family planning of family planning ––––––––––––––––––––––– –––––––––––––––––––––– Hus- Hus- Hus- Hus- band band’s band Husband band’s Woman Wife Husband Number Background Husband disap- attitude ap- disap- attitude is un- ap- ap- of characteristic approves proves unknown proves proves unknown sure1 Total proves proves1 women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 39.8 8.3 12.7 2.9 22.1 9.1 5.2 100.0 60.7 43.5 504 20-24 36.2 11.6 12.2 4.6 22.5 8.1 4.8 100.0 60.0 41.2 833 25-29 39.3 12.9 10.7 3.1 21.7 7.6 4.6 100.0 62.9 43.2 1,072 30-34 33.4 12.6 12.1 3.7 25.5 8.1 4.5 100.0 58.1 37.7 793 35-39 34.9 14.0 9.7 4.3 24.0 7.7 5.4 100.0 58.6 39.7 793 40-44 29.2 9.0 7.6 6.0 32.0 9.6 6.6 100.0 45.8 35.5 568 45-49 27.0 13.1 11.2 2.9 29.8 8.9 7.0 100.0 51.3 30.6 453 Residence Total urban 49.2 13.8 8.0 5.6 16.3 4.4 2.7 100.0 71.0 55.5 1,921 Asmara 59.4 12.3 3.6 8.5 12.1 1.9 2.1 100.0 75.3 69.1 861 Other towns 40.9 14.9 11.6 3.2 19.7 6.4 3.3 100.0 67.5 44.5 1,060 Rural 26.1 10.8 12.7 2.9 30.0 10.7 6.8 100.0 49.6 29.5 3,094 Zoba Debubawi Keih Bahri 34.4 9.1 8.1 2.0 19.7 15.6 11.2 100.0 51.6 36.9 163 Maekel 55.2 12.2 4.3 8.2 16.0 1.8 2.3 100.0 71.7 64.3 1,087 Semenawi Keih Bahri 16.6 10.6 17.5 1.8 31.1 13.5 8.9 100.0 44.7 18.7 710 Anseba 21.6 9.9 10.4 1.6 40.6 10.8 5.1 100.0 41.9 23.8 647 Gash-Barka 20.9 15.5 12.1 2.6 34.5 9.7 4.7 100.0 48.5 23.7 794 Debub 41.8 11.6 12.4 3.8 17.3 7.8 5.4 100.0 65.7 46.2 1,614 Education No education 20.9 11.4 13.5 3.2 31.6 11.9 7.5 100.0 45.8 24.6 2,861 Primary 44.7 13.8 10.7 3.9 18.5 5.4 2.9 100.0 69.2 49.3 1,051 Middle 54.0 10.2 7.3 6.3 17.6 2.6 2.0 100.0 71.5 60.8 397 Secondary + 66.7 12.1 3.0 5.7 10.3 0.8 1.5 100.0 81.8 72.9 707 Wealth Index Lowest 17.9 9.1 13.5 1.5 35.8 12.6 9.6 100.0 40.5 19.6 862 Second 23.6 10.8 14.4 2.8 29.9 10.9 7.6 100.0 48.8 27.1 963 Middle 26.8 12.1 12.2 2.9 29.9 10.0 6.1 100.0 51.1 30.3 1,090 Fourth 45.1 14.1 10.5 5.2 17.8 5.3 2.0 100.0 69.7 50.8 1,054 Highest 57.7 12.8 4.7 6.8 12.6 3.4 1.9 100.0 75.2 65.3 1,046 Total 2002 35.0 11.9 10.9 3.9 24.7 8.3 5.3 100.0 57.8 39.5 5,016 Total 19952 31.2 5.7 29.8 1.4 9.7 10.7 11.5 100.0 66.8 33.4 2,145 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes women who are unsure about their own attitude, but know their husbands’ attitude 2 Currently married non-sterilized women Fertility Regulation | 83 Figure 5.4 Trends in Approval of Family Planning, Women Age 15-49, 1995 EDHS and 2002 EDHS 0 71 75 68 50 52 72 45 42 49 66 58 0 75 79 68 63 32 75 43 33 58 78 67 RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub TOTAL 0 20 40 60 80 100 Percent 2002 EDHS 1995 EDHS 5.6 EVER USE OF CONTRACEPTIVE METHODS All women interviewed in the survey who said they had heard of a method of family planning were asked if they had ever used that method. Table 5.9 shows the percentage of all women and currently married women who have ever used a family planning method by specific method and age. The table also shows ever use of methods among sexually active unmarried women. Seventeen percent of all women and 22 percent of currently married women reported having used a method at some time. Ever use of family planning methods has increased by almost 50 percent in both groups; ever-use rates in 1995 were 12 percent and 15 percent for all women and currently married women, respectively. Fifteen percent of currently married women have used a modern method of family planning at some time. Among these women, pills and injectables are the most commonly used modern methods (10 percent and 7 percent, respectively); 3 percent have used condoms. There has been an increase in the use of these three methods since 1995, especially for injectables (from 1 percent to 7 percent). Thirteen percent of currently married women have used a traditional method at some time; 9 percent have used LAM, 6 percent have used periodic abstinence, and 2 percent have used withdrawal. Ever use of any method among the youngest cohort is 8 percent; it is 19 percent among women 20-24, and 28 percent among women in age groups 25-29 and 35-39. For sexually active unmarried women, ever use of contraceptive methods was 47 percent for any method, 41 percent for modern methods, and 12 percent for traditional methods. The most commonly used methods among these women were the male condom (23 percent), the pill (18 percent), and injectables (11 percent). 84 | Fertility Regulation Table 5.9 Ever use of contraception Percentage of all women, of currently married women, and of sexually active unmarried women, who have ever used any contraceptive method, by specific method, according to age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Modern method Traditional method –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––– Female Emer- Any Any steri- Male In- Male Female gency tradi- Periodic Folk Number Any modern liza- steri- ject- Im- con- con- Dia- Foam/ contra- tional absti- With- meth- of Age method method tion lization Pill IUD ables plants dom dom phragm jelly ception method LAM nence drawal od women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– ALL WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 3.5 2.4 0.0 0.0 0.9 0.0 0.7 0.0 0.8 0.0 0.0 0.0 0.2 1.9 0.8 1.1 0.3 0.0 2,001 20-24 14.5 8.7 0.0 0.1 4.6 0.1 3.1 0.0 2.8 0.0 0.0 0.0 0.3 8.5 6.0 4.0 1.2 0.2 1,454 25-29 24.8 16.6 0.0 0.0 9.5 0.6 7.8 0.2 4.6 0.2 0.0 0.1 0.5 13.7 10.1 6.6 2.1 0.0 1,543 30-34 22.5 15.9 0.2 0.0 11.5 1.6 5.7 0.0 3.0 0.0 0.0 0.0 0.2 12.8 8.7 6.1 1.4 0.0 1,109 35-39 27.9 21.4 0.4 0.0 12.9 2.8 10.6 0.0 3.8 0.3 0.2 0.2 0.9 15.0 10.3 7.1 1.5 0.1 1,085 40-44 20.4 15.2 0.4 0.0 11.6 3.7 6.0 0.1 2.2 0.0 0.0 0.3 0.5 11.1 8.4 5.6 1.6 0.0 827 45-49 17.9 11.0 0.3 0.0 7.1 2.4 5.2 0.0 0.9 0.0 0.0 0.0 0.0 10.4 8.9 4.6 0.7 0.2 734 Total 17.3 11.9 0.1 0.0 7.4 1.2 5.1 0.0 2.6 0.1 0.0 0.1 0.4 9.7 6.9 4.6 1.2 0.1 8,754 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– CURRENTLY MARRIED WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 8.2 5.0 0.0 0.0 2.8 0.0 1.6 0.0 0.5 0.0 0.0 0.0 0.2 5.1 2.1 2.5 0.9 0.1 580 20-24 19.0 10.9 0.0 0.2 6.3 0.1 4.3 0.0 2.5 0.0 0.0 0.0 0.4 11.9 8.8 5.1 1.6 0.2 950 25-29 28.0 18.4 0.0 0.0 10.8 0.8 9.1 0.2 4.6 0.1 0.0 0.1 0.6 16.3 12.3 7.6 2.4 0.0 1,212 30-34 23.6 16.4 0.2 0.0 11.5 1.6 6.3 0.0 2.6 0.0 0.0 0.0 0.1 13.3 8.8 6.9 1.3 0.0 904 35-39 28.3 21.3 0.1 0.0 12.3 3.4 11.1 0.0 3.4 0.4 0.2 0.3 0.7 14.9 10.6 6.9 1.4 0.1 899 40-44 20.4 15.4 0.5 0.0 11.7 4.0 6.5 0.0 1.7 0.0 0.0 0.3 0.6 11.3 7.8 5.9 1.6 0.0 663 45-49 20.3 13.3 0.4 0.0 8.5 3.0 6.5 0.0 1.0 0.0 0.0 0.1 0.0 11.2 9.5 5.4 1.0 0.0 526 Total 22.3 15.1 0.2 0.0 9.5 1.7 6.9 0.0 2.7 0.1 0.0 0.1 0.4 12.7 9.1 6.0 1.6 0.1 5,733 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– SEXUALLY ACTIVE UNMARRIED WOMEN1 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Total 47.1 40.5 2.3 0.0 17.8 4.1 10.8 0.0 22.9 0.4 0.0 0.0 0.0 11.7 8.6 7.3 0.0 0.0 56 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– LAM= Lactational amenorrhea method 1Women who had sexual intercourse in the month preceding the survey 5.7 CURRENT USE OF CONTRACEPTIVE METHODS Information on current use of family planning is among the most important data collected in the 2002 EDHS. It provides insight into one of the principal determinants of fertility and serves as a key measure for assessing the success of national family planning efforts. This section focuses on data from the 2002 EDHS on levels, differentials, and trends in current use of contraception. Levels of Family Planning Use In the 2002 EDHS women were asked, “Are you currently doing something or using any method to delay or avoid getting pregnant?” Table 5.10 shows the percent distribution of women currently using a contraceptive method by age. Eight percent of currently married women in Eritrea reported using contraception at the time of the survey: 5 percent modern methods and 3 percent traditional methods. Only three methods are being used by at least 1 percent of currently married women: injectables (3 percent) and the pill (1 percent) Fertility Regulation | 85 Table 5.10 Current use of contraception Percent distribution of all women, of currently married women, and of sexually active unmarried women by contraceptive method currently used, according to age, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Modern method Traditional method –––––––––––––––––––––––––––––––––––––––––––––––– –––––––––––––––––––––––– Female Any Not Using Any steri- In- Male Female tradi- Periodic curren- Number any modern liza- ject- con- con- Foam/ tional absti- With- tly of Age method method tion Pill IUD ables dom dom jelly method LAM nence drawal using Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– ALL WOMEN –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 1.2 0.9 0.0 0.1 0.0 0.3 0.4 0.0 0.0 0.3 0.1 0.1 0.1 98.8 100.0 2,001 20-24 4.2 2.4 0.0 0.8 0.0 1.1 0.4 0.0 0.0 1.8 1.3 0.4 0.0 95.8 100.0 1,454 25-29 8.3 5.6 0.0 1.5 0.2 2.6 1.2 0.0 0.0 2.7 2.3 0.3 0.0 91.7 100.0 1,543 30-34 8.0 4.9 0.2 1.5 0.8 1.9 0.5 0.0 0.0 3.1 2.7 0.4 0.0 92.0 100.0 1,109 35-39 9.4 6.9 0.4 1.4 0.4 4.0 0.6 0.0 0.0 2.5 1.6 0.9 0.0 90.6 100.0 1,085 40-44 7.8 5.0 0.4 1.2 0.4 2.0 0.7 0.0 0.3 2.8 1.6 0.8 0.4 92.2 100.0 827 45-49 5.0 3.3 0.3 0.7 0.2 2.1 0.0 0.0 0.0 1.7 0.8 0.9 0.0 95.0 100.0 734 Total 5.8 3.8 0.1 1.0 0.3 1.8 0.6 0.0 0.0 1.9 1.4 0.5 0.1 94.2 100.0 8,754 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– CURRENTLY MARRIED WOMEN –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 2.4 1.4 0.0 0.4 0.0 0.8 0.2 0.0 0.0 0.9 0.2 0.5 0.2 97.6 100.0 580 20-24 5.9 3.1 0.0 1.2 0.0 1.6 0.3 0.0 0.0 2.8 2.1 0.6 0.0 94.1 100.0 950 25-29 10.0 6.6 0.0 1.9 0.3 3.1 1.3 0.0 0.0 3.4 2.9 0.4 0.0 90.0 100.0 1,212 30-34 9.0 5.3 0.2 1.8 0.8 1.9 0.6 0.0 0.0 3.7 3.3 0.4 0.0 91.0 100.0 904 35-39 10.1 7.3 0.1 1.7 0.5 4.4 0.6 0.0 0.0 2.8 1.8 1.0 0.0 89.9 100.0 899 40-44 9.3 5.8 0.5 1.4 0.5 2.5 0.6 0.0 0.3 3.5 2.0 1.0 0.5 90.7 100.0 663 45-49 6.9 4.6 0.4 0.9 0.2 3.0 0.0 0.0 0.0 2.4 1.1 1.2 0.0 93.1 100.0 526 Total 8.0 5.1 0.2 1.4 0.4 2.6 0.6 0.0 0.0 2.9 2.1 0.7 0.1 92.0 100.0 5,733 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– SEXUALLY ACTIVE UNMARRIED WOMEN1 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Total 26.6 26.3 2.3 2.6 0.0 8.8 12.2 0.4 0.0 0.4 0.0 0.4 0.0 73.4 100.0 56 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: If more than one method is used, the most effective method is tabulated here. LAM= Lactational amenorrhea method 1 Women who had sexual intercourse in the month preceding the survey among modern methods, and LAM (2 percent)2 among traditional methods. Current use is clearly associated with a woman’s age; younger and older women are less likely to be using contraception than women age 25-44. Current use rises from 2 percent among the youngest age group (15-19) of married women to 6 percent among women age 20-24 and to 9 or 10 percent until age 44, and then falls to 7 percent among the oldest age group (45-49). Trends in Contraceptive Use Contraceptive use remains low in Eritrea; there has been no increase since the previous survey. Although the prevalence rate has remained the same, it is encouraging that among contracepting women, use of modern methods has increased. The higher use of modern methods and lower use of traditional methods has occurred in all subgroups shown in Table 5.11. Considering that the total prevalence rate has 2 This is the percentage of women who said that they were using LAM; however, the percentage of women who had given birth in the eight months preceding the survey, were breastfeeding, and who were amenorrheic is less than 1 percent. For this reason, LAM is considered a traditional method in this context. 86 | Fertility Regulation not changed since 1995, although at first glance it may seem incongruent that prevalence has decreased for both urban and rural women, the explanation for this anomaly is the increase in the proportion of women who live in urban areas in the 2002 EDHS since the 1995 survey. Current Use of Contraception by Background Characteristics Differentials in the level of current use by background characteristics other than age are presented in Table 5.11. There are marked differences by background characteristics in current use of family planning methods among currently married women as shown in Figure 5.5 and Table 5.11. Urban women are almost five times as likely to use a method of contraception as rural women. Not surprisingly, current use is highest in Asmara, the most urbanized area in the country, with nearly one in four currently married women reporting use of a method and one in five reporting use of a modern method. By zone, the highest contraceptive prevalence rate (20 percent) is in zoba Maekel, which includes Asmara, and the lowest rate is in zoba Gash-Barka (2 percent). In other zobas, the contraceptive prevalence rates are also low (4-8 percent). Table 5.11 Current use of contraception by background characteristics Percent distribution of currently married women by contraceptive method currently used, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Modern method Traditional method ––––––––––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––– Female Any Using Any steri- In- Male tradi- Periodic Not Number Background any modern liza- ject- con- Foam/ tional absti- With- currently of characteristic method method tion Pill IUD ables dom jelly method LAM nence drawal using Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 16.5 12.3 0.4 3.3 1.0 5.8 1.6 0.1 4.3 2.8 1.3 0.1 83.5 100.0 1,967 Asmara 23.2 17.6 0.5 5.1 2.1 7.3 2.4 0.2 5.7 3.3 2.1 0.3 76.8 100.0 868 Other towns 11.2 8.1 0.3 1.9 0.2 4.7 0.9 0.0 3.1 2.4 0.7 0.0 88.8 100.0 1,099 Rural 3.6 1.4 0.0 0.5 0.0 0.8 0.1 0.0 2.2 1.8 0.3 0.1 96.4 100.0 3,766 Zoba Debubawi Keih Bahri 7.1 5.1 0.1 1.3 0.0 2.5 1.0 0.0 2.0 0.8 1.1 0.1 92.9 100.0 210 Maekel 19.6 14.7 0.4 4.4 1.7 6.2 1.9 0.2 5.0 3.1 1.7 0.2 80.4 100.0 1,103 Semenawi Keih Bahri 5.1 3.2 0.4 0.9 0.1 1.5 0.2 0.0 1.9 1.5 0.4 0.0 94.9 100.0 817 Anseba 4.4 2.7 0.0 0.3 0.1 1.4 0.8 0.0 1.7 1.1 0.6 0.0 95.6 100.0 784 Gash-Barka 1.9 1.1 0.1 0.4 0.0 0.5 0.1 0.0 0.8 0.6 0.1 0.1 98.1 100.0 1,142 Debub 7.9 3.7 0.0 1.0 0.0 2.6 0.1 0.0 4.2 3.5 0.5 0.1 92.1 100.0 1,677 Education No education 3.5 1.7 0.1 0.5 0.1 1.0 0.1 0.0 1.8 1.5 0.2 0.0 96.5 100.0 3,549 Primary 10.8 7.0 0.1 1.4 0.3 4.5 0.7 0.0 3.8 3.1 0.5 0.1 89.2 100.0 1,075 Middle 16.7 12.8 0.0 5.0 0.9 5.6 1.3 0.0 3.9 1.5 2.4 0.0 83.3 100.0 400 Secondary + 21.8 15.1 0.5 4.4 1.6 5.6 2.7 0.3 6.7 4.1 2.3 0.3 78.2 100.0 709 Number of living children 0 0.7 0.6 0.0 0.2 0.0 0.1 0.4 0.0 0.1 0.0 0.0 0.0 99.3 100.0 875 1-2 7.4 4.3 0.1 1.5 0.2 1.6 0.9 0.0 3.1 1.8 1.1 0.2 92.6 100.0 1,802 3-4 11.6 7.2 0.2 1.7 0.8 3.6 0.7 0.1 4.4 3.7 0.7 0.0 88.4 100.0 1,509 5+ 9.5 6.7 0.2 1.8 0.3 4.0 0.3 0.0 2.8 2.3 0.5 0.1 90.5 100.0 1,547 Total 8.0 5.1 0.2 1.4 0.4 2.6 0.6 0.0 2.9 2.1 0.7 0.1 92.0 100.0 5,733 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: If more than one method is used, the most effective method is tabulated here. LAM= Lactational amenorrhea method Fertility Regulation | 87 EDHS 2002 Figure 5.5 Contraceptive Use by Background Characteristics, Currently Married Women 15-49 8 17 23 11 4 7 20 5 4 2 8 TOTAL RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub 0 5 10 15 20 25 30 Percent As expected, current use increases with level of education, from 4 percent among women with no education to 11 percent among women with primary education, and 17 percent among those with middle education to 22 percent among women with some secondary education. Current use rises with the number of living children and peaks at 12 percent among women with 3-4 living children, then falls slightly to 10 percent among women with five or more children. Current Use of Contraception by Women’s Status A woman’s desire and ability to control her fertility and her choice of contraceptive methods are in part affected by her status and self-image. A woman who feels that she is unable to control her life may be less likely to feel she can make decisions about childbearing. Table 5.12 shows the distribution of currently married women by contractive use, according to two women’s status indicators. Use is directly related to the number of decisions that a woman makes herself or jointly with others. The prevalence of family planning increases from 1 percent among women who are not involved in any decisionmaking to 10 percent among women who have a final say in 5 or 6 decisions. The prevalence of contraceptive use and the number of reasons women consider wife beating justified (an indicator of women’s status) have a negative relationship. The highest prevalence is among women who think that wife beating is not justified for any reason (10 percent). Prevalence is half this level among women who think that wife beating is justified for all five of the specified reasons for which their opinion was sought. 88 | Fertility Regulation Table 5.12 Current use of contraception by women's status Percent distribution of currently married women by contraceptive method currently used, according to indicators of women's status, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Modern method Traditional method ––––––––––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––– Any Using Any Female In- Male tradi- Periodic Not Number Indicator of any modern sterili- ject- con- Foam/ tional absti- With- Folk currently of women's status method method zation Pill IUD ables dom jelly method LAM nence drawal method using Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of decisions in which woman has final say1 0 1.2 1.2 0.0 0.6 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 98.8 100.0 189 1-2 4.3 2.2 0.1 0.9 0.2 1.0 0.1 0.0 2.1 1.8 0.2 0.1 0.1 95.7 100.0 1,240 3-4 7.8 4.2 0.1 0.8 0.3 2.8 0.2 0.0 3.5 2.9 0.7 0.0 0.0 92.2 100.0 1,485 5-6 10.3 7.2 0.2 2.1 0.4 3.3 1.1 0.1 3.1 2.1 0.9 0.1 0.0 89.7 100.0 2,819 Number of reasons wife beating is justified 0 10.2 7.8 0.3 1.6 0.6 4.3 0.9 0.1 2.4 1.6 0.8 0.0 0.0 89.8 100.0 1,543 1-2 8.9 4.9 0.0 1.6 0.7 1.7 0.9 0.0 3.9 3.1 0.7 0.2 0.0 91.1 100.0 1,337 3-4 7.4 4.6 0.1 1.4 0.1 2.7 0.3 0.0 2.8 1.9 0.7 0.1 0.1 92.6 100.0 1,722 5 5.1 2.7 0.3 1.1 0.1 1.0 0.2 0.0 2.4 2.1 0.3 0.0 0.0 94.9 100.0 1,132 Total 8.0 5.1 0.2 1.4 0.4 2.6 0.6 0.0 2.9 2.1 0.7 0.1 0.0 92.0 100.0 5,733 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: If more than one method is used, the most effective method is tabulated here. LAM= Lactational amenorrhea method 1Herself or jointly with others First Use of Family Planning Women who reported that they had used family planning methods at some time were asked about the number of children they had when they first used a method. These data are useful in identifying the stage in the family-building process when women begin using family planning. Table 5.13 shows the percent distribution of women by the number of living children they had at the time of first use of family planning. More than half (53 percent) of women who have ever used Table 5.13 Number of children at first use of contraception Percent distribution of women who have ever used contraception by number of living children at the time of first use of contraception, according to current age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of living children at the time of first use of contraception Don't Number –––––––––––––––––––––––––––––––––––––––––––––– know/ of Current age 0 1 2 3 4+ missing Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 44.0 42.1 4.5 0.0 0.0 9.4 100.0 71 20-24 22.5 55.1 13.8 2.1 2.7 3.8 100.0 211 25-29 15.7 48.5 16.7 9.4 5.9 3.7 100.0 382 30-34 14.1 33.3 20.0 10.4 20.1 2.1 100.0 250 35-39 9.0 29.1 16.2 18.7 26.0 0.9 100.0 303 40-44 9.2 26.0 19.5 10.1 35.3 0.0 100.0 169 45-49 6.1 28.4 12.4 7.4 45.6 0.0 100.0 131 Total 14.8 38.5 16.1 9.9 18.2 2.4 100.0 1,516 Fertility Regulation | 89 contraception began using a method before they had two children, including 15 percent of women who were then childless. One-fourth of women who have used contraception initiated use when they had 2-3 children. Eighteen percent used contraception only after they had four or more children. Early use of family planning increases with decreasing age. For example, 44 percent of women age 15-19 began using contraceptives before they had had any children, compared with 6 percent of women age 45-49. In contrast, 45-53 percent of women age 35 and older first began using contraception after they had at least three children. 5.8 SOURCE OF MODERN FAMILY PLANNING METHODS Information on where women obtain their contraceptives methods is important for family planning program managers. In the 2002 EDHS, information was collected on sources from which modern family planning methods were obtained. For women using female sterilization, the place where the operation was performed was considered the source, while women using other methods were asked the most recent source of the method (Figure 5.6). Table 5.14 shows results for specific methods. As in 1995, three-fourths of pill users and more than 90 percent of users of injectables rely on the public sector. The share of various public sector sources for the pill has remained about the same, with the Family Reproductive Health Association of Eritrea (formerly Planned Parenthood Federation of Eritrea) being the major source for pills. Government health facilities are the predominant source for injectables, providing supplies to 58 percent of users. As expected, women who say they rely on condoms as a method of family planning report shops and pharmacies as the main sources of the method. EDHS 2002 Figure 5.6 Distribution of Current Users of Modern Contraceptive Methods by Source of Supply Public sector 74% Private medical sector 15% Other source 8% Don’t know/ missing 3% 90 | Fertility Regulation Table 5.14 Source of contraception Percent distribution of current users of modern contraceptive methods by most recent source of method, according to specific methods, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– All Inject- Male modern Source Pill ables condoms methods1 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Public sector 73.5 91.0 11.3 74.0 Government hospital 18.7 36.0 1.4 26.5 Government health center 18.0 21.7 2.0 16.6 Family Reproductive Health Association 36.8 33.3 7.8 30.9 Private medical sector 20.7 7.3 30.7 14.6 Private hospital or clinic 8.1 3.2 0.4 4.4 Pharmacy 12.6 1.3 26.4 7.9 Private doctor 0.0 2.8 3.9 2.0 Other private medical 0.0 0.0 0.0 0.4 Other source 4.1 0.0 46.7 8.4 Shop 0.0 0.0 31.8 5.0 Friends/relatives 4.1 0.0 14.9 3.4 Don't know 0.0 0.0 11.3 1.8 Missing 1.6 1.7 0.0 1.2 Total 100.0 100.0 100.0 100.0 Number of women 85 160 52 334 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes 37 cases; 13 users of female sterilization, 22 users of IUD, and 2 users of other modern methods. 5.9 REASONS FOR NONUSE OF CONTRACEPTION Table 5.15 presents information on the main reasons why women are not using family planning by urban-rural residence. Overall, the most important reasons for not using a contraceptive method were that women were not married (23 percent) or not sexually active (21 percent). Reasons given by 22 percent of women included: had infrequent sex, menopausal or had hysterectomy, subfecund or infecund, or were postpartum amenorrheic. Fourteen percent of women indicated that they were fatalistic (e.g., believe that childbearing is beyond their control); 10 percent reported that they were breastfeeding; 5 percent said that they were opposed to family planning, and 2 percent said that their husbands were opposed to contraception. From the point of view of family planning programs, the programmatically important reasons for nonuse—knowing no method and knowing no source of methods—were mentioned by 9 percent and 6 percent of women, respectively. Six percent cited either health concerns or fear of side effects of contraceptive methods as reasons for not using, while 2 percent mentioned lack of access to, cost of, or inconvenience in using family planning methods. There are some important differences in reasons given for not using contraceptive methods by residence. Urban women mention fertility-related reasons more often than rural women. For example, 37 percent of urban women are not using contraceptives because they are not married, in comparison with 13 percent of women in rural area; and 28 percent of urban women are not sexually active compared with 15 Fertility Regulation | 91 percent of rural women. On the other hand, 21 percent of rural women but only 6 percent of urban women cited fatalistic reasons for not using contraception. Not knowing methods and not knowing sources of methods are more frequently mentioned by rural women than by urban women. This clearly points to a need to launch an aggressive campaign of information and education in rural areas, where most nonusers live. Table 5.15 Reasons for not using family planning Percent distribution of nonpregnant nonusers by main reason for not using family planning currently, according to residence and desire to limit or space childbearing, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban Rural Total –––––––––––––––––––––––– ––––––––––––––––––––––––– –––––––––––––––––––––––––– Wants Wants Wants Wants Wants Wants Reason to limit to space Total to limit to space Total to limit to space Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Fertility-related reason Not married 10.7 49.5 36.9 3.3 16.7 12.5 6.7 31.1 23.3 Not having sex 36.3 23.8 27.9 20.7 12.2 14.8 27.8 17.3 20.6 Infrequent sex 14.7 9.8 11.4 10.0 9.9 9.9 12.1 9.9 10.6 Menopausal/had hysterectomy 8.9 0.4 3.2 7.4 0.3 2.5 8.1 0.3 2.8 Subfecund/infecund 4.1 1.2 2.2 6.5 1.0 2.8 5.4 1.1 2.5 Breastfeeding 6.8 8.6 8.0 5.1 14.9 11.8 5.8 12.1 10.1 Postpartum amenorrheic 6.7 3.9 4.8 6.7 7.2 7.0 6.7 5.7 6.0 Opposition to use Respondent opposed 3.7 3.5 3.6 6.3 7.2 6.9 5.1 5.6 5.4 Husband opposed 1.8 2.0 2.0 1.3 2.2 1.9 1.6 2.1 1.9 Others opposed 0.0 0.1 0.1 0.0 0.2 0.1 0.0 0.1 0.1 Religious prohibition 1.8 1.2 1.4 1.8 4.0 3.3 1.8 2.7 2.4 Lack of knowledge Knows no method 1.6 1.4 1.5 16.9 12.9 14.1 9.9 7.8 8.5 Knows no source 1.0 0.7 0.8 13.0 9.1 10.3 7.6 5.4 6.1 Method-related reason Health concerns 6.7 2.5 3.9 4.3 0.7 1.8 5.4 1.5 2.7 Fear of side effects 3.7 4.0 3.9 3.1 2.4 2.7 3.4 3.1 3.2 Lack of access/too far 1.1 0.0 0.3 0.9 0.6 0.7 1.0 0.3 0.5 Costs too much 0.2 0.1 0.1 0.3 0.2 0.2 0.3 0.2 0.2 Inconvenient to use 1.3 0.6 0.8 1.3 0.7 0.9 1.3 0.6 0.9 Interferes with body’s normal process 0.9 0.8 0.8 0.3 0.0 0.1 0.6 0.3 0.4 Fatalistic 7.9 5.4 6.2 15.9 23.0 20.8 12.3 15.3 14.3 Other 2.3 3.3 3.0 1.2 2.0 1.7 1.7 2.6 2.3 Don’t know 0.1 0.0 0.0 0.4 0.3 0.4 0.3 0.2 0.2 Missing 0.5 1.5 1.2 0.0 0.2 0.1 0.2 0.8 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 541 1,117 1,659 650 1,423 2,073 1,192 2,540 3,732 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: “Wants to limit” means wants no more children, while “wants to space” refers to women who want another child after two years. 92 | Fertility Regulation 5.10 INTENTION TO USE FAMILY PLANNING AMONG NONUSERS An important indicator of the changing demand for family planning is the extent to which non- users of contraception intend to use family planning in the future. Women who were not using contraception at the time of the survey were asked about their intention to use family planning in the future. The results for currently married women are presented in Table 5.16. Among currently married women, 26 percent intend to use in future, 16 percent in the next 12 months and 10 percent after 12 months. Seven in ten nonusers do not intend to use any method in the future, and 3 percent are unsure. The proportion of nonusers intending to use in future, shows no consistent pattern according to number of living children. Since 1995, the proportion of nonusers who do not intend to use has increased from 63 percent to 71 percent. Table 5.16 Future use of contraception Percentage of currently married women who are not using a contraceptive method, by intention to use in the future and number of living children, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of living children1 ––––––––––––––––––––––––––––––––––––– Intention 0 1 2 3 4+ Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Intends to use 21.3 29.8 25.7 31.4 24.5 26.1 In next 12 months 7.5 17.4 15.2 17.3 17.5 15.7 After 12 months 13.8 12.4 10.6 14.1 7.0 10.4 Unsure 4.9 1.5 3.2 3.7 2.6 3.0 Does not intend to use 73.5 68.5 70.6 64.7 72.8 70.7 Missing 0.3 0.1 0.5 0.1 0.1 0.2 Number of women 730 867 800 764 2,112 5,272 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes current pregnancy 5.11 REASONS FOR NOT INTENDING TO USE A CONTRACEPTIVE METHOD IN THE FUTURE An understanding of the reasons why people do not use family planning methods is critical to designing programs that are effective in reaching people with unmet need and to improving the quality of family planning services. Table 5.17 shows the main reasons for not intending to use family planning given by currently married nonusers who do not intend to use contraceptive methods in the future. Desire for more children was the most common reason for not intending to use a method in the future for both women 15-29 (71 percent) and women 30-49 (52 percent). Since 1995, there has been a marked increase in the proportion of women who cite this reason for nonuse, from 47 to 60 percent. Fertility Regulation | 93 More importantly, 13 percent of women would not use any method in the future because they cited religious prohibition or their own or their husband’s opposition to family planning methods. Eight percent cited lack of knowledge of methods or sources of methods. These reasons are almost as likely to be mentioned by younger women as by older women. Table 5.17 Reasons for not intending to use contraception in the future Percent distribution of currently married women who are not using a contra- ceptive method and who do not intend to use one in the future by main reason for not intending to use, according to age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age –––––––––––––––––––– Main reason 15-29 30-49 Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Fertility-related reason 74.7 70.6 72.4 Infrequent sex/no sex 3.5 2.3 2.9 Menopausal/had hysterectomy 0.0 5.6 3.1 Subfecund/infecund 0.5 10.7 6.2 Wants as many children as possible 70.7 52.0 60.3 Opposition to use 12.1 13.5 12.9 Respondent opposed 6.4 5.9 6.2 Husband opposed 0.9 1.4 1.2 Religious prohibition 4.8 6.2 5.6 Lack of knowledge 7.4 8.9 8.2 Knows no method 4.4 4.4 4.4 Knows no source 3.0 4.5 3.9 Method-related reason 4.4 5.6 5.1 Health concerns 1.2 2.5 1.9 Fear of side effects 3.0 2.7 2.9 Lack of access/too far 0.0 0.1 0.1 Costs too much 0.0 0.2 0.1 Inconvenient to use 0.2 0.1 0.1 Interfere with body's normal processes 0.0 0.1 0.0 Other 1.1 1.1 1.1 Don’t know 0.2 0.3 0.3 Total 100.0 100.0 100.0 Number of women 1,649 2,078 3,727 5.12 PREFERRED METHOD OF CONTRACEPTION FOR FUTURE USE Nonusers who planned to use family planning in the future were asked about the method they would prefer to use. Table 5.18 shows that in each subgroup, three-fourths of women prefer pills or injectables. Women age 15-29 prefer pills to injectables, whereas older women prefer injectables to pills. Three percent of nonusers who plan to use in the future prefer condoms, 5 percent among younger women and only 1 percent among older women. For traditional methods, 6 percent and 5 percent of younger and older women, respectively, prefer to use periodic abstinence in the future. It should be noted that 7 percent and 13 percent of younger and older nonusers, respectively, were not sure what method they would prefer to use in the future. 94 | Fertility Regulation Table 5.18 Preferred method of contraception for future use Percent distribution of currently married women who are not using a contraceptive method but who intend to use in the future by preferred method, according to age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––– Age –––––––––––––––– Preferred method 15-29 30-49 Total ––––––––––––––––––––––––––––––––––––––––––––––––––––– Female sterilization 0.4 0.6 0.5 Pill 41.3 35.9 39.1 IUD 0.9 1.6 1.2 Injectables 35.9 39.1 37.2 Implants 0.4 1.0 0.6 Condom 4.5 1.2 3.2 Female condom 0.1 0.1 0.1 Diaphragm 0.1 0.2 0.2 Lactation amenorrhea 2.9 1.9 2.5 Periodic abstinence 6.0 4.9 5.6 Withdrawal 0.2 0.6 0.4 Other 0.2 0.0 0.1 Unsure 6.9 12.7 9.3 Missing 0.0 0.3 0.1 Total 100.0 100.0 100.0 Number of women 812 565 1,377 5.13 CONTACT OF NONUSERS WITH HEALTH CARE PROVIDERS To get an insight into the level of “missed opportunities,” that is, contacts between nonusers and health workers that are not utilized to provide information about family planning and to motivate them to adopt family planning, nonusers were asked whether they had visited any health facility in the 12 months preceding the survey. Those who had visited a health facility were further asked whether during any visit to the health facility, anyone at the facility discussed family planning with them. Slightly more than half of nonusers visited a health facility, but only 10 percent of nonusers visited a facility and had a health worker speak to them about family planning (Table 5.19). By age, women 25 to 39 were more likely to discuss family when they visited a health facility than younger or older women. Rural women and women in zoba Debubawi Keih Bahri had the highest level of “missed opportunities.” Although women with no education and women with primary education are equally likely to have visited a health facility, those with primary education are more likely to have discussed family planning with a provider than other women. Fertility Regulation | 95 Table 5.19 Contact of nonusers with family planning providers Percentage of women who are not using contraception who visited a health facility in the 12 months preceding the survey and discussed family planning and percentage who visited a health facility but did not discuss family planning,, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Nonusers who visited a health facility in the past 12 months ––––––––––––––––––––––––––––––––––– Did not Discussed discuss Number Background family family of characteristic planning planning Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 2.4 25.6 28.0 1,978 20-24 9.6 43.0 52.6 1,393 25-29 13.6 47.3 61.0 1,416 30-34 14.4 49.2 63.6 1,020 35-39 14.8 48.9 63.7 983 40-44 13.2 44.0 57.2 762 45-49 8.3 41.4 49.7 697 Residence Total urban 12.5 39.0 51.4 3,406 Asmara 10.8 33.5 44.3 1,677 Other towns 14.1 44.3 58.4 1,729 Rural 8.3 42.4 50.7 4,844 Zoba Debubawi Keih Bahri 6.8 42.9 49.7 304 Maekel 11.0 34.0 44.9 2,026 Semenawi Keih Bahri 9.3 41.2 50.5 1,102 Anseba 10.8 45.3 56.1 1,094 Gash-Barka 8.9 40.8 49.7 1,472 Debub 10.2 45.0 55.2 2,251 Education No education 9.4 44.6 53.9 4,257 Primary 13.1 40.4 53.4 1,505 Middle 7.5 33.9 41.4 903 Secondary + 10.2 36.0 46.2 1,585 Total 10.0 41.0 51.0 8,250 Other Proximate Determinants of Fertility | 97 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6 This chapter addresses the principal factors other than contraception that influence fertility. Marriage is among the most important of these proximate determinants because it is a primary indicator of women’s exposure to the risk of pregnancy. Early age at first marriage in a population is usually associated with a longer period of exposure to the risk of pregnancy and thus higher fertility levels. The early initiation of childbearing associated with early marriage may also adversely affect the health of women and their children. Besides marriage, this chapter explores three other factors that influence fertility: postpartum amenorrhea, postpartum abstinence, and menopause. Postpartum amenorrhea and postpartum abstinence determine the length of time a woman is insusceptible to pregnancy after childbirth, which affects the length of the birth interval and thus fertility levels. Menopause is important because it marks the end of a woman’s period of exposure to the risk of pregnancy. 6.1 CURRENT MARITAL STATUS Table 6.1 and Figure 6.1 show the percent distribution of all women age 15-49 by current marital status. Overall, 66 percent of women are currently married (including 4 percent who are living together), 4 percent are widowed, 5 percent are divorced, 2 percent are separated (not living together), and 23 percent have never married. There has been a slight increase in the proportion of women never married since the 1995 EDHS, from 20 percent to 23 percent. In the rest of this report, marriage is defined by including informal as well as formal unions, i.e., the categories “married” and “living together” are Table 6.1 Current marital status Percent distribution of women by current marital status, according to age and wealth index, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Marital status ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number Age and Never Living of wealth index married Married together Divorced Separated Widowed Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 69.0 28.2 0.8 1.5 0.5 0.1 100.0 2,001 20-24 27.3 62.0 3.3 4.7 1.8 0.9 100.0 1,454 25-29 11.5 73.5 5.0 6.0 2.4 1.6 100.0 1,543 30-34 4.6 76.3 5.2 6.9 3.5 3.4 100.0 1,109 35-39 2.2 76.9 6.0 6.8 2.9 5.2 100.0 1,085 40-44 0.9 76.3 3.9 5.7 2.8 10.4 100.0 827 45-49 0.9 67.8 3.9 9.7 3.2 14.6 100.0 734 Wealth index Lowest 14.9 77.0 1.8 3.3 0.6 2.4 100.0 1,472 Second 14.6 72.7 2.0 5.5 1.0 4.1 100.0 1,626 Middle 14.7 69.4 3.8 6.9 1.9 3.4 100.0 1,674 Fourth 26.3 53.3 5.6 6.4 3.6 4.9 100.0 1,833 Highest 40.0 44.4 4.6 4.1 3.2 3.7 100.0 2,149 Total 2002 23.3 61.8 3.7 5.2 2.2 3.7 100.0 8,754 Total 1995 20.0 61.4 5.3 6.8 1.7 4.8 100.0 5,054 98 | Other Proximate Determinants of Fertility combined and referred to as “currently married.” Respondents who are widowed, divorced, and separated (not living together) make up the remainder of the ever-married category. The proportion of women who have never married declines sharply with increasing age, from 69 percent at age 15-19 to 27 percent at age 20-24; by age 35 almost all are married. On the other hand, the proportion of women who are currently married increases with age and peaks at age 35-39. The decline in the proportion currently married after age 39 is the result of increasing levels of divorce and widowhood. The proportion widowed increases from less than 1 percent among women age 20-24 to 15 percent among women age 45-49. The differentials by wealth index show that the proportion never married increases rapidly from one in seven women in the three lowest quintiles to one in four women in the fourth quintile, and two in five women in the highest quintile. 6.2 POLYGYNY The extent of polygyny in Eritrea was measured by asking currently married women whether their husband or partner had other wives, and if so, how many. Table 6.2 shows the percentage of currently married women by number of co-wives, according to background characteristics. Overall, 9 percent of currently married women in Eritrea are in a polygynous union, compared with 7 percent in 1995. The prevalence of polygynous unions increases with age and peaks at age 35-39; thus, young women are more likely to be in a monogamous union than older women. Women in all urban areas (total urban) and women in rural areas are equally likely to be in a polygynous union; however, there are marked differences between women in Asmara and women in other towns. Women in other towns are twice as likely to be in a polygynous union as women in Asmara (12 percent and 6 percent, respectively). By zoba, zoba Maekel has the lowest level of polygyny (6 percent), and the two Red Sea zobas, Debubawi Keih Bahri and Semenawi Keih Bahri, have the highest levels of polygyny (19 percent and 16 percent, respectively). Between 8 and 9 percent of women in other zobas are in a polygynous union. EDHS 2002 Figure 6.1 Current Marital Status Never married 23% Married 62% Living together 4% Divorced 5% Separated 2% Widowed 4% Never married Married Living together Divorced Separated Widowed Other Proximate Determinants of Fertility | 99 Table 6.2 Number of co-wives Percent distribution of currently married women by number of co-wives, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of co-wives Number Background –––––––––––––––––––––––––– of characteristic 0 1 2+ Missing Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 95.9 2.5 1.4 0.2 100.0 580 20-24 93.6 4.7 1.4 0.3 100.0 950 25-29 91.1 6.1 2.7 0.1 100.0 1,212 30-34 88.7 8.9 2.2 0.1 100.0 904 35-39 87.2 10.2 2.4 0.3 100.0 899 40-44 88.5 9.4 2.1 0.0 100.0 663 45-49 88.9 7.5 3.2 0.4 100.0 526 Residence Total urban 90.5 7.5 1.8 0.2 100.0 1,967 Asmara 93.8 3.9 1.8 0.5 100.0 868 Other towns 87.9 10.3 1.9 0.0 100.0 1,099 Rural 90.5 6.9 2.4 0.2 100.0 3,766 Zoba Debubawi Keih Bahri 81.0 12.6 6.4 0.0 100.0 210 Maekel 93.0 4.6 1.8 0.6 100.0 1,103 Semenawi Keih Bahri 83.6 13.1 3.0 0.3 100.0 817 Anseba 91.4 7.4 1.1 0.1 100.0 784 Gash-Barka 92.0 6.0 1.9 0.1 100.0 1,142 Debub 92.0 5.7 2.3 0.0 100.0 1,677 Education No education 89.3 8.0 2.5 0.2 100.0 3,549 Primary 91.0 6.8 2.2 0.0 100.0 1,075 Middle 93.8 4.3 1.9 0.0 100.0 400 Secondary + 94.1 4.6 0.7 0.6 100.0 709 Wealth index Lowest 90.5 7.5 1.7 0.3 100.0 1,161 Second 89.6 7.3 3.1 0.0 100.0 1,215 Middle 90.3 7.4 2.3 0.1 100.0 1,224 Fourth 89.5 7.8 2.4 0.3 100.0 1,079 Highest 92.8 5.5 1.5 0.2 100.0 1,053 Total 90.5 7.1 2.2 0.2 100.0 5,733 There is an inverse relationship between education and polygyny. The proportion of currently married women in a polygynous union decreases from 11 percent among women with no education, to 9 percent among women with a primary education and 5 percent among women with some secondary or higher education. Although education and economic status are generally correlated, there is much less variation in the prevalence of polygyny by wealth index. Seven percent of currently married women in the highest quintile of the wealth index are in a polygynous union, compared with 9-10 percent of women in the other quintiles. 100 | Other Proximate Determinants of Fertility 6.3 AGE AT FIRST MARRIAGE In general, marriage marks the point in a woman’s life when childbearing becomes socially acceptable. Women who marry early will, on the average, have longer exposure to the risk of pregnancy; therefore, early age at first marriage usually implies a higher fertility level for a society. In the 2002 EDHS survey, information on age at first marriage was obtained by asking all ever-married respondents the month and year that they started living together with their first husband or partner. The women who could not give the year of their first union were asked the age at which they first married. Table 6.3 shows that marriage occurs relatively early in Eritrea. Among women age 20-49 as well as among women age 25-49, 20 percent were married by age 15, 48 percent were married by age 18, and 63 percent were married by age 20. The findings also indicate that there has been a sharp decline in the proportion of women married in their early teens. The proportion of women married by age 15 has dropped from 21 percent among women age 30-34 to 9 percent among women age 15-19. Table 6.3 Age at first marriage Percentage of women who were first married by specific exact ages and median age at first marriage, according to current age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Median Percentage first married by exact age: Percentage Number age at ––––––––––––––––––––––––––––––––––––––––––– never of first Current age 15 18 20 22 25 married women marriage ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 8.5 na na na na 69.0 2,001 a 20-24 19.6 47.0 63.3 na na 27.3 1,454 18.3 25-29 16.2 46.4 62.6 74.1 84.9 11.5 1,543 18.4 30-34 20.9 51.8 66.7 76.5 86.4 4.6 1,109 17.8 35-39 19.1 44.2 58.6 73.0 85.7 2.2 1,085 18.6 40-44 21.4 47.4 61.4 75.0 85.1 0.9 827 18.3 45-49 24.6 53.5 64.9 74.8 83.1 0.9 734 17.5 20-49 2002 19.7 48.0 62.9 na na 9.8 6,753 18.2 25-49 2002 19.8 48.2 62.8 74.6 85.2 5.0 5,298 18.2 20-49 1995 23.3 59.0 72.3 na na 7.8 3,925 16.9 25-49 1995 24.6 60.3 73.0 82.7 89.4 4.0 3,102 16.7 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable a Omitted because less than 50 percent of the women married for the first time before age 15 A comparison of the results of the 2002 EDHS and the 1995 EDHS shows that among women 25- 49, the proportion married by each age is lower in 2002 than in 1995. For example, the percentage of women married by age 15 has declined from 25 percent to 20 percent in 2002. Three-fourths of women age 25-49 were married by age 22 and 85 percent were married by age 25, compared with 83 percent and 89 percent, respectively, in 1995. The median age at first marriage for women age 20-49 is 18 years. Since the minimum legal age for a woman to get married in Eritrea is also 18 years, almost half of women marry before the minimum legal age. Since 1995, the median age at first marriage for women age 20-49 and age 25-49 has increased by more than one year (from 17 to 18 years). Other Proximate Determinants of Fertility | 101 6.4 MEDIAN AGE AT FIRST MARRIAGE Table 6.4 examines the median age at first marriage for women 25-49 by current age and background characteristics. As was shown in Table 6.3, the overall median age at first marriage for women age 25-49 is 18 years. Urban women, especially those in Asmara, are more likely to marry later than their rural counterparts. The median age at first marriage varies widely by zoba, ranging from 17 years in zoba Gash- Barka to 21 years in zoba Maekel; that is, women in zoba Maekel marry an average of four years later than those in zoba Gash-Barka. The median age in zoba Debubawi Keih Bahri is 20 years. Zobas Semenawi Keih Bahri, Anseba, and Debub have the same median age at first marriage (18 years). There is a strong relationship between education and age at first marriage. The median age at first marriage for women with no education or with primary education is five years lower than the median age for women with a secondary or higher education. By wealth index, median age at marriage increases from a low of 17 years for women in the lowest quintile to 21 years for women in the highest quintile. The differentials observed for background variables generally hold for all age groups. Table 6.4 Median age at first marriage Median age at first marriage among women 25-49, by current age and background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Current age Women Background ––––––––––––––––––––––––––––––––––––––––––– age characteristic 25-29 30-34 35-39 40-44 45-49 25-49 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 20.4 19.3 19.0 18.9 17.5 19.3 Asmara 22.5 22.7 21.1 20.5 16.8 21.5 Other towns 18.3 18.0 18.4 18.1 18.3 18.2 Rural 17.2 17.1 18.3 18.0 17.5 17.5 Zoba Debubawi Keih Bahri 20.0 19.1 19.9 19.0 20.3 19.7 Maekel 21.7 21.1 20.9 20.1 17.0 20.7 Semenawi Keih Bahri 18.4 17.6 18.2 17.6 18.1 18.0 Anseba 17.5 18.0 18.5 18.2 17.4 17.9 Gash-Barka 16.9 16.7 17.1 16.8 16.5 16.9 Debub 17.1 17.1 18.6 18.6 17.9 17.7 Education No education 16.9 17.0 18.1 18.1 17.4 17.4 Primary 17.7 17.7 18.3 18.4 17.9 17.9 Middle 19.3 (17.6) (21.7) * * 18.9 Secondary + 22.9 23.7 22.9 22.2 * 22.8 Wealth index Lowest 17.0 17.0 17.0 17.4 17.5 17.1 Second 16.8 17.1 18.3 18.1 17.6 17.5 Middle 17.6 17.3 18.8 17.8 18.3 17.9 Fourth 18.2 17.4 18.7 17.6 17.2 18.0 Highest 21.9 22.2 20.6 20.3 17.2 20.9 Total 2002 18.4 17.8 18.6 18.3 17.5 18.2 Total 1995 17.4 17.1 16.6 16.3 15.9 16.7 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Numbers in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a number is based on fewer than 25 unweighted cases and has been suppressed. 102 | Other Proximate Determinants of Fertility 6.5 AGE AT FIRST SEXUAL INTERCOURSE Age at first marriage and age at first sexual intercourse do not always coincide, because women may engage in sexual relations prior to marriage. Thus, using marriage alone as an indicator of sexual activity will result in an underestimate of the proportion of women who are sexually active. To avoid the problem, the 2002 EDHS asked women to give the age at which they first had sexual intercourse. Table 6.5 shows the percentage of women who had first sexual intercourse by specific ages. The findings indicate that 20 percent of women age 20-49 had sexual intercourse by age 15, 50 percent by age 18, and 65 percent by age 20. The median age at first intercourse for women age 25-49 and the median age at first marriage are almost the same (18 years). This suggests that women generally begin sexual intercourse at the time of marriage. Furthermore, median age at first sex across age groups is similar to median age at first marriage, indicating little change over time in the pattern of initiation of sexual activity. However, women in age group 45-49 have a much lower median age at first intercourse than younger women. Table 6.5 Age at first sexual intercourse Percentage of women who had first sexual intercourse by specific exact ages and median age at first intercourse, according to current age, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of women who had first Percentage Median sexual intercourse by exact age: that never Number age at ––––––––––––––––––––––––––––––––––––––––––– had of first Current age 15 18 20 22 25 intercourse women intercourse –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15-19 8.8 na na na na 67.6 2,001 a 20-24 19.4 46.9 64.3 na na 25.2 1,454 18.3 25-29 15.7 46.6 62.8 72.8 82.1 9.9 1,543 18.3 30-34 20.3 51.9 66.8 74.6 83.4 3.6 1,109 17.7 35-39 18.4 48.1 62.6 74.5 82.1 1.5 1,085 18.2 40-44 21.5 49.5 62.8 75.8 82.1 0.7 827 18.1 45-49 28.5 61.8 72.0 80.1 86.2 0.5 734 16.4 20-49 2002 19.8 49.8 64.8 na na 8.7 6,753 18.0 25-49 2002 19.9 50.6 64.9 75.0 82.9 4.1 5,298 17.9 20-49 1995 21.0 56.9 70.7 79.3 84.7 7.2 3,925 17.0 25-49 1995 22.3 58.6 71.3 80.6 86.8 3.6 3,102 16.8 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable aOmitted because less than 50 percent of the women had intercourse for the first time before age 15 6.6 MEDIAN AGE AT FIRST INTERCOURSE Table 6.6 shows the median age at first intercourse among women age 25-49 by current age and background characteristics. There are marked differences in the median age at first intercourse by residence. Women start sexual intercourse at a younger age in rural areas (17 years) than in urban areas (19 years); in Asmara the average is 21 years. By zoba, age at first sexual intercourse is the lowest in zobas Gash-Barka and Debub (17 years), followed by zobas Semenawi Keih Bahri and Anseba (18 years); it is highest in zoba Maekel (20 years). Other Proximate Determinants of Fertility | 103 Table 6.6 Median age at first sexual intercourse Median age at first sexual intercourse among women 25-49, by current age and background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Current age Women Background ––––––––––––––––––––––––––––––––––––––––––– age characteristic 25-29 30-34 35-39 40-44 45-49 25-49 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 20.2 19.0 18.8 18.7 16.0 18.9 Asmara 22.4 22.5 19.8 20.0 15.8 20.6 Other towns 18.1 17.7 18.4 17.6 16.9 18.0 Rural 17.2 16.8 17.5 17.6 16.6 17.1 Zoba Debubawi Keih Bahri 19.7 19.0 19.4 18.9 20.0 19.4 Maekel 21.6 20.3 19.5 19.5 15.9 20.0 Semenawi Keih Bahri 18.3 17.7 18.1 17.5 17.3 17.9 Anseba 17.6 18.1 18.7 18.6 17.3 18.0 Gash-Barka 17.0 16.6 17.0 16.7 15.8 16.7 Debub 16.9 16.6 17.2 17.5 16.0 16.8 Education No education 16.9 16.9 17.4 17.5 16.3 17.0 Primary 17.9 17.0 17.6 18.3 16.5 17.5 Middle 18.6 (18.4) (20.4) * * 18.5 Secondary + 22.6 23.3 22.3 21.2 * 22.5 Wealth index Lowest 17.1 16.9 16.8 17.4 17.1 17.0 Second 16.9 17.1 17.9 17.3 16.5 17.2 Middle 17.5 16.8 18.2 17.8 16.2 17.3 Fourth 18.0 17.2 18.0 17.0 16.1 17.6 Highest 21.9 21.7 20.1 19.8 16.2 20.4 Total 2002 18.3 17.7 18.2 18.1 16.4 17.9 Total 1995 17.7 17.1 16.8 16.4 16.0 16.8 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 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. Median age at first sexual intercourse increases with women’s education. Women with at least a secondary-level education tend to delay sexual relations more than 5 years later than women with no education. Between the 1995 EDHS and the 2002 EDHS, the median age at first sexual intercourse for women increased by one year. 6.7 RECENT SEXUAL ACTIVITY In societies with low levels of contraceptive use, the probability of becoming pregnant is related to exposure to and frequency of sexual intercourse. Information on sexual activity is useful as a measure of exposure to the risk of pregnancy. Table 6.7 shows the percent distribution of women by the timing of last sex, according to background characteristics. During the four weeks before the survey, 38 percent of women age 15-49 were sexually active, 22 percent had been sexually active in the past 12 months but not in the four weeks before the survey, and 14 percent had had sex at some time but not in the past 12 months. The proportion of women who were 104 | Other Proximate Determinants of Fertility Table 6.7 Recent sexual activity Percent distribution of women by timing of last sexual intercourse, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Timing of last sexual intercourse –––––––––––––––––––––––––––––––––––– Within One or Never had Number Background the past Within more sexual of characteristic 4 weeks 1 year1 years ago Missing intercourse Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 11.6 15.9 3.2 1.7 67.6 100.0 2,001 20-24 28.0 28.3 13.9 4.5 25.2 100.0 1,454 25-29 39.9 27.9 16.4 5.9 9.9 100.0 1,543 30-34 48.8 25.0 17.0 5.5 3.6 100.0 1,109 35-39 54.1 23.5 15.9 4.9 1.5 100.0 1,085 40-44 60.6 15.5 18.4 4.7 0.7 100.0 827 45-49 56.7 12.6 26.0 4.2 0.5 100.0 734 Marital status Never married 0.7 1.9 2.9 0.3 94.2 100.0 2,044 Married or living together 56.6 30.7 8.2 4.3 0.2 100.0 5,733 Divorced/separated/widowed 4.2 11.7 71.4 12.4 0.2 100.0 977 Marital duration for women married only once2 0-4 years 44.9 42.1 8.0 4.0 1.0 100.0 1,214 5-9 years 48.2 35.1 12.5 4.2 0.0 100.0 1,132 10-14 years 54.1 28.8 10.7 6.4 0.0 100.0 856 15-19 years 63.0 28.1 4.9 4.0 0.0 100.0 647 20-24 years 71.0 21.4 4.5 3.1 0.0 100.0 504 25+ years 79.5 14.6 4.4 1.5 0.0 100.0 538 Married more than once 59.2 28.5 7.0 5.4 0.0 100.0 843 Residence Total urban 31.1 16.5 15.4 4.3 32.7 100.0 3,767 Asmara 27.5 13.8 15.3 4.3 39.1 100.0 1,899 Other towns 34.8 19.2 15.5 4.3 26.2 100.0 1,868 Rural 42.7 26.0 12.9 4.2 14.2 100.0 4,987 Zoba Debubawi Keih Bahri 42.2 17.9 16.4 4.9 18.6 100.0 324 Maekel 28.8 15.3 14.6 4.4 36.9 100.0 2,264 Semenawi Keih Bahri 48.2 18.5 13.0 2.6 17.7 100.0 1,148 Anseba 41.4 22.8 10.3 3.4 22.1 100.0 1,130 Gash-Barka 46.0 25.2 13.6 4.0 11.2 100.0 1,500 Debub 33.6 27.7 15.5 5.4 17.7 100.0 2,388 Education No education 49.4 24.3 15.8 4.7 5.8 100.0 4,384 Primary 32.6 26.5 15.1 5.1 20.8 100.0 1,637 Middle 19.6 18.7 10.2 3.6 48.0 100.0 974 Secondary + 23.3 13.4 10.7 2.8 49.8 100.0 1,760 Current contraceptive method Pill 70.6 26.1 0.0 3.2 0.0 100.0 85 Condom 54.1 39.1 6.8 0.0 0.0 100.0 52 Periodic abstinence 62.4 33.9 3.7 0.0 0.0 100.0 41 Other method3 65.0 26.0 5.7 3.2 0.0 100.0 327 No method 36.1 21.5 14.6 4.4 23.5 100.0 8,250 Wealth index Lowest 52.0 21.6 8.0 3.5 14.9 100.0 1,472 Second 44.0 25.3 11.7 4.7 14.4 100.0 1,626 Middle 36.9 27.1 18.1 3.9 14.0 100.0 1,674 Fourth 29.7 22.8 17.4 5.8 24.2 100.0 1,833 Highest 30.6 14.6 13.7 3.4 37.6 100.0 2,149 Total 37.7 21.9 14.0 4.3 22.2 100.0 8,754 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Excludes women who had sexual intercourse within the past four weeks 2 Currently married women only 3 Includes 11 sterilized women and 14 women using IUD Other Proximate Determinants of Fertility | 105 sexually active in the four weeks before the survey increases with age up to age 40-44, and increases with the number of years in union. For example, 80 percent of women who have been married for 25 years or longer were sexually active in the four weeks before the survey, compared with only 45 percent of recently married women (0-4 years before the survey). A higher proportion of women were sexually active during the four weeks before the survey in zobas Semenawi Keih Bahri (48 percent), Gash-Barka (46 percent), Debubawi Keih Bahri (42 percent) and Anseba (41 percent) than in zobas Debub (34 percent) and Maekel (29 percent). Four in ten rural women compared with three in ten urban women had sex in the past four weeks. Recent sexual activity is inversely related to level of education. The proportion of women who were recently sexually active falls from 49 percent among women with no education to 20 percent among women with middle school education. The lower proportion sexually active among women in urban areas and those with more education is due to a greater proportion of unmarried women in these subgroups. Women who are current users of contraceptive methods were more likely to be sexually active in the four weeks before the survey than those who are not using a method. One important factor is that almost one-fourth of women who were not using a contraceptive method had never had sex. The proportion of women who had sex in the four weeks before the survey varies by type of method used, ranging from 71 percent among women who rely on the pill to 54 percent among condom users. There is a marked difference in recent sexual activity by wealth index. Among women in the lowest quintile of the wealth index, 52 percent were sexually active during the four weeks preceding the survey, compared with 31 percent among women in the highest quintile. The latter group has a high proportion of women who never had sex. 6.8 POSTPARTUM AMENORRHEA, ABSTINENCE, AND INSUSCEPTIBILITY Studies have shown that for a few weeks or months after the birth of a child, a woman does not ovulate and therefore is not susceptible to pregnancy. This period, during which a woman is temporarily infecund, is known as postpartum amenorrhea, which may be six weeks or longer, depending on whether and how a woman breastfeeds. Thus, besides contraceptive use and cultural norms that may dictate sexual abstinence after childbirth, exposure to pregnancy is influenced by breastfeeding practices. Women are considered insusceptible if they are not exposed to the risk of pregnancy because they are either amenorrheic or abstaining from sexual intercourse after a birth. Table 6.8 shows the percentage of women who gave birth in the three years before the survey who are still amenorrheic, abstaining, and insusceptible to the risk of pregnancy. The proportion of women remaining amenorrheic, abstaining, or insusceptible declines as the interval since the birth increases. During the first two months after a birth, 94 percent of women in Eritrea are amenorrheic, 90 percent are abstaining, and almost all (99 percent) are insusceptible to pregnancy. Eritrean women are amenorrheic for a median duration of 14 months, abstain only for a median of 3 months, and are insusceptible to pregnancy for a median of 15 months. After six months (the recommended duration for exclusive breastfeeding), 81 percent of women are still insusceptible to pregnancy, mainly because their menstrual period has not returned. By 34-35 months after birth, only 4 percent are amenorrheic and the same proportion is abstaining; 6 percent are insusceptible to pregnancy. 106 | Other Proximate Determinants of Fertility Table 6.8 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, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Postpartum: –––––––––––––––––––––––––––– Number Amenor- Insuscep- of Months since birth rheic Abstaining tible births –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– < 2 94.4 90.3 99.0 202 2-3 85.2 55.5 89.2 246 4-5 84.8 25.1 88.1 227 6-7 77.0 17.0 80.6 231 8-9 74.8 14.8 76.0 209 10-11 74.1 18.6 78.9 203 12-13 52.8 8.9 54.9 190 14-15 43.2 11.2 53.2 187 16-17 31.5 12.6 41.4 153 18-19 26.0 9.1 31.7 173 20-21 24.6 15.7 35.0 147 22-23 13.6 10.5 22.9 158 24-25 11.9 10.7 22.3 227 26-27 8.5 8.7 15.8 231 28-29 6.7 10.5 17.0 164 30-31 3.0 5.8 7.6 145 32-33 9.5 9.2 17.7 170 34-35 3.6 3.5 6.2 160 Total 2002 43.6 20.1 49.7 3,424 Median 2002 13.5 3.0 14.6 na Mean 2002 14.8 7.1 17.0 na Total 1995 44.5 14.8 48.0 2,556 Median 1995 14.2 2.7 16.6 na Mean 1995 16.0 5.4 17.3 na –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Estimates are based on status at the time of the survey. na = Not applicable 6.9 MEDIAN DURATION OF POSTPARTUM INSUSCEPTIBILITY BY BACKGROUND CHARACTERISTICS The median duration of postpartum insusceptibility by various background characteristics is shown in Table 6.9 and Figure 6.2. There is little variation in the duration of postpartum abstinence; therefore, the observed variation in postpartum insusceptibility is mainly due to differences in the duration of postpartum amenorrhea. Women under 30 are insusceptible to pregnancy for a shorter period of time than women 30 years and older because they have a shorter period of amenorrhea. Rural women remain amenorrheic and insusceptible after birth for 2-3 months longer than urban women. Women in zobas Debub and Semenawi Keih Bahri have the longest duration of amenorrhea (15 months), while women in zobas Debubawi Keih Bahri and Maekel have the shortest duration (11 months). Insusceptibility to pregnancy is shortest in zoba Maekel (13 months) and longest in zobas Debub and Semenawi Keih Bahri (16 months). Other Proximate Determinants of Fertility | 107 Table 6.9 Median duration of postpartum insusceptibility by background characteristics Median number of months of postpartum amenorrhea, postpartum abstinence, and postpartum insusceptibility for births in the three years preceding the survey, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Postpartum: –––––––––––––––––––––––––––– Number Background Amenor- Absti- Insuscep- of characteristic rhea nence tibility births –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-29 12.8 3.2 13.7 1,776 30-49 14.6 2.7 15.7 1,648 Residence Total urban 11.2 3.1 13.2 1,136 Asmara 9.6 3.3 12.9 491 Other towns 12.1 2.9 13.4 645 Rural 14.5 3.0 15.5 2,287 Zoba Debubawi Keih Bahri 11.4 3.2 13.7 113 Maekel 11.4 2.8 13.4 634 Semenawi Keih Bahri 14.7 2.7 16.1 457 Anseba 13.7 2.6 14.0 511 Gash-Barka 13.8 3.1 14.9 660 Debub 14.7 3.3 15.6 1,048 Education No education 15.3 3.0 16.3 2,117 Primary 12.9 2.9 13.5 612 Middle 12.6 3.0 13.2 249 Secondary + 8.4 3.0 10.4 445 Wealth index Lowest 15.1 2.5 15.5 730 Second 14.2 3.3 14.5 724 Middle 14.9 3.5 17.6 725 Fourth 13.6 2.5 14.4 686 Highest 8.8 2.9 9.9 560 Total 13.5 3.0 14.6 3,424 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Medians are based on current status. There is an inverse relation between women’s education and insusceptibility to the risk of pregnancy; the median duration of amenorrhea and insusceptibility shorten as women’s education increases. The duration of amenorrhea declines with increasing wealth; however, the relationship between insusceptibility and the wealth index has no discernable pattern. The median duration of insusceptibility is highest for births to women in the middle quintile of the wealth index. In Table 6.9, the number of months of postpartum amenorrhea and insusceptibility are lowest for births to women in the highest quintile of the wealth index. A comparison of the results of the 1995 EDHS and the 2002 EDHS indicates that median duration of insusceptibility has decreased by two months in Eritrea over the period. However, there has been practically no change in the median duration of abstinence or amenorrhea. 108 | Other Proximate Determinants of Fertility EDHS 2002 Figure 6.2 Median Duration of Postpartum Insusceptibility by Background Characteristics 15 14 16 13 13 13 16 14 13 16 14 15 16 16 14 13 10 TOTAL AGE 15-29 30-49 RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub EDUCATION No education Primary Middle Secondary + 0 5 10 15 20 Months 6.10 MENOPAUSE Table 6.10 shows the percentage of women age 30- 49 who are menopausal. In the context of the available survey data, women are considered menopausal if they are neither pregnant nor postpartum amenorrheic but have not had a menstrual period for at least six months preceding the survey. Twelve percent of Eritrean women age 30-49 are menopausal. As expected, the proportion of women in menopause increases with age, particularly after age 40. Only 1 percent of women in their early thirties, 4 percent of the women in their late thirties, and 12 percent of women age 40-41 are menopausal. The proportion of women in menopause rises sharply from 18 percent at age 42-43 to 54 percent at age 48-49. Table 6.10 Menopause Percentage of women age 30-49 who are menopausal, by age, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––– Number Percentage of Age menopausal1 women –––––––––––––––––––––––––––––––––––––––– 30-34 1.3 1,109 35-39 3.8 1,085 40-41 11.9 577 42-43 17.8 171 44-45 25.7 353 46-47 39.4 193 48-49 53.6 266 Total 12.4 3,755 –––––––––––––––––––––––––––––––––––––––– 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 Fertility Preferences and Unmet Need for Family Planning | 109 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING 7 The subject of future reproductive preferences is of fundamental importance for population policy and for family planning programs. Whether couples want to cease childbearing or delay the next pregnancy determines the demand for family planning. The data on this fertility preference indicator and current contraceptive use allow estimation of unmet need for family planning. Another indicator of fertility preferences which pertains to both past and future reproductive behavior, perhaps the most common measure of fertility preference, is ideal number of children—i.e., how many children a woman would want in total if she could start afresh. The information on ideal family size (ideal number of children) provides two measures. First, for women who have not yet started childbearing, the data provide an idea of future fertility (to the extent that women are able to realize their fertility desires). Second, for all women, the excess of past fertility over the ideal family size provides a measure of unwanted fertility. Another topic that is discussed in this chapter is fertility planning in the past and future. The last two sections focus on the planning status of births in the five years preceding the survey (and current pregnancies) and attitudes of nonusers toward unplanned pregnancies in the near future. 7.1 REPRODUCTIVE PREFERENCES To obtain information on fertility preferences, currently married nonpregnant women were asked the question: “Would you like to have a/another child or would you prefer not to have any more children?” For pregnant women, the wording, “After the child you are expecting…” prefaced the question. Women who said that they did want to have another child were then asked how long they would like to wait before the birth of the next child. Women’s reproductive preferences are summarized in Table 7.1 and Figure 7.1. More than half of currently married women (56 percent) express a desire to control their future fertility. Seventeen percent of women report that they do not want any more children, and another 39 percent express a desire Table 7.1 Fertility preferences by number of living children Percent distribution of currently married women by desire for children, according to number of living children, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of living children1 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Desire for children 0 1 2 3 4 5 6 7+ Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Have another soon2 69.0 40.9 36.2 30.5 25.0 20.2 15.8 10.8 33.0 Have another later3 23.8 51.4 49.6 50.1 41.0 34.2 28.2 15.5 38.6 Have another, undecided when 1.3 1.2 1.8 2.3 1.9 4.1 1.7 1.9 1.9 Undecided 3.9 3.4 4.4 5.2 7.3 10.0 9.6 9.8 6.2 Want no more 0.8 2.2 5.6 9.7 21.8 26.4 41.0 55.8 17.4 Sterilized 0.0 0.0 0.2 0.1 0.3 0.5 0.0 0.2 0.2 Declared infecund 0.9 0.7 1.8 1.7 2.6 4.5 3.7 6.1 2.5 Missing 0.3 0.2 0.4 0.4 0.1 0.1 0.0 0.0 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 736 921 879 857 705 546 440 649 5,733 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes current pregnancy 2 Want next birth within 2 years 3 Want to delay next birth for 2 years 110 | Fertility Preferences and Unmet Need for Family Planning to have a child after at least two years. The desire for a child is strongly related to the number of living children a woman has. The desire to delay childbearing among women with no children is 24 percent, doubling to 50-51 percent among women with 1-3 children, and then declining to 16 percent among women with seven or more children. The proportion of women who want no more children increases slowly with number of living children. Eritrean women exhibit pronatalist tendencies in that less than half of women with up to six children want to cease childbearing. One-fourth of women with five children, four in ten of women with six children, and just over half (56 percent) of women with seven or more children want to cease childbearing. Among women with the seven or more children, 11 percent want to have another child soon and another 16 percent want a child later. 7.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Table 7.2 shows the variation in the percentage of currently married women who want no more children (or who are sterilized) for various groups, according to the number of living children (including any current pregnancy). The results indicate that a higher proportion of urban women want to limit family size than rural women. Women in zobas Maekel and Debub are not as pronatalist as those in other zobas. Differentials by education present an interesting picture. Although overall, the proportions of uneducated women and women with some secondary school education who want no more children are almost the same, the proportion of educated women who want no more children is much higher at all parities for which comparisons can be made. The largest difference is among women with four children; half of these women who have secondary or higher education want to stop childbearing, compared with 14 percent of uneducated women. The differentials by wealth index indicate that women in the fourth and highest quintiles are more likely to want to stop childbearing than women in other quintiles. EDHS 2002 Figure 7.1 Fertility Preferences of Currently Married Women 33% 39% 2% Undecided 6% Want no more 17% Declared infecund 3% Want child later (2+ years) Want child, unsure when 2% Want child soon (<2 years) 33% Fertility Preferences and Unmet Need for Family Planning | 111 Table 7.2 Desire to limit childbearing by background characteristics Percentage of currently married women who want no more children, by number of living children and background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of living children1 Background ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– characteristic 0 1 2 3 4 5 6 7+ Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 0.0 3.6 9.8 14.4 38.2 39.5 53.4 69.0 22.4 Asmara 0.0 4.4 12.7 20.6 50.2 (43.5) (61.9) (81.8) 25.6 Other towns 0.0 2.7 7.7 10.0 27.1 36.9 48.0 62.9 19.9 Rural 1.0 1.4 3.2 6.6 12.2 20.5 36.2 52.1 15.0 Zoba Debubawi Keih Bahri 0.0 6.0 6.0 14.5 27.0 30.6 26.9 24.7 13.0 Maekel 0.0 3.8 12.4 17.7 45.2 39.3 47.1 66.4 24.6 Semenawi Keih Bahri 0.0 0.8 5.1 8.5 15.3 19.6 34.2 42.5 12.4 Anseba 0.0 0.0 1.0 5.5 9.7 11.9 32.5 48.1 14.6 Gash-Barka 1.0 4.2 6.5 8.6 15.9 28.2 48.7 55.9 16.1 Debub 1.8 0.3 3.2 7.3 17.2 30.6 42.2 61.9 18.4 Education No education 1.1 1.8 4.8 7.8 13.9 22.6 40.5 53.2 18.4 Primary 0.8 1.2 4.1 7.9 17.0 37.5 31.3 64.4 14.3 Middle 0.0 0.0 6.7 (19.4) (65.2) * * * 17.7 Secondary + 0.0 5.3 11.1 16.7 49.8 * * * 18.1 Wealth index Lowest 0.6 2.0 3.2 7.4 10.4 19.7 30.9 47.2 18.1 Second 1.9 1.2 3.0 5.6 7.7 15.4 39.4 52.3 13.4 Middle 0.0 2.1 3.4 6.6 15.1 28.6 35.5 61.4 14.3 Fourth 1.3 2.1 8.9 9.6 32.6 39.5 53.9 57.8 19.5 Highest 0.0 3.4 9.6 18.7 45.6 38.8 55.9 79.4 23.7 Total 0.8 2.2 5.8 9.8 22.1 26.8 41.0 56.0 17.6 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 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 Includes current pregnancy 7.3 NEED FOR FAMILY PLANNING SERVICES One of the major concerns of family planning programs is to assess the size of the potential demand for contraception and to identify women who are in need of contraceptive services. Table 7.3 presents estimates of unmet need, met need, and the total demand for family planning in Eritrea. The table also shows the percentage of the total demand that is satisfied. Women who are currently married and who either do not want any more children or want to wait two or more years before having another child, but are not using contraception, are considered to have an unmet need for family planning. Women with a met need for family planning are those who are currently using contraception. The total demand for family planning is the sum of unmet need and met need. According to Table 7.3, the total unmet need in Eritrea is 27 percent, 21 percent for spacing and 6 percent for limiting. Combining total unmet need with the 8 percent of married women who are 112 | Fertility Preferences and Unmet Need for Family Planning Table 7.3 Need for family planning Percentage of currently married women with unmet need for family planning and with met need for family planning, and the total demand for family planning, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Met need for Unmet need for family planning Total demand for Percentage family planning1 (currently using)2 family planning of –––––––––––––––––––– ––––––––––––––––––––– –––––––––––––––––––– demand Number Background For For For For For For satis- of characteristic spacing limiting Total spacing limiting Total spacing limiting Total fied women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 41.7 1.2 42.8 2.4 0.0 2.4 44.0 1.2 45.2 5.2 580 20-24 27.2 1.2 28.4 5.5 0.4 5.9 32.7 1.6 34.3 17.2 950 25-29 19.7 1.7 21.3 9.1 0.9 10.0 28.8 2.6 31.4 32.0 1,212 30-34 24.4 4.5 28.9 6.1 2.9 9.0 30.5 7.4 37.9 23.8 904 35-39 17.2 11.3 28.5 3.8 6.3 10.1 21.0 17.6 38.6 26.1 899 40-44 10.8 12.5 23.3 2.2 7.1 9.3 12.9 19.7 32.6 28.5 663 45-49 4.2 15.2 19.4 1.6 5.3 6.9 5.8 20.5 26.3 26.3 526 Residence Total urban 18.8 6.0 24.8 10.1 6.4 16.5 28.9 12.4 41.3 40.0 1,967 Asmara 16.8 5.1 21.8 14.2 9.0 23.2 31.0 14.1 45.1 51.5 868 Other towns 20.4 6.7 27.0 6.9 4.3 11.2 27.3 11.0 38.3 29.3 1,099 Rural 22.2 6.0 28.2 2.4 1.2 3.6 24.6 7.3 31.9 11.3 3,766 Zoba Debubawi Keih Bahri 14.8 4.5 19.3 5.3 1.8 7.1 20.1 6.3 26.3 26.9 210 Maekel 19.1 5.7 24.8 11.9 7.7 19.6 31.0 13.5 44.4 44.2 1,103 Semenawi Keih Bahri 20.2 3.4 23.6 4.0 1.1 5.1 24.2 4.5 28.7 17.7 817 Anseba 19.6 4.1 23.7 2.5 1.9 4.4 22.1 6.0 28.1 15.7 784 Gash-Barka 20.9 6.2 27.1 1.2 0.8 1.9 22.1 6.9 29.0 6.6 1,142 Debub 24.3 8.4 32.7 4.8 3.0 7.9 29.1 11.5 40.6 19.4 1,677 Education No education 19.5 6.8 26.3 1.7 1.7 3.5 21.3 8.5 29.8 11.7 3,549 Primary 23.9 4.5 28.4 6.7 4.2 10.8 30.6 8.7 39.3 27.6 1,075 Middle 30.6 4.7 35.3 9.8 6.9 16.7 40.3 11.7 52.0 32.1 400 Secondary + 18.8 5.1 24.0 16.3 5.4 21.8 35.2 10.6 45.8 47.6 709 Wealth index Lowest 20.6 6.5 27.1 0.9 0.8 1.7 21.5 7.3 28.8 5.9 1,161 Second 21.9 5.8 27.7 1.6 1.0 2.6 23.5 6.8 30.3 8.5 1,215 Middle 26.0 5.3 31.3 2.8 1.5 4.3 28.8 6.8 35.6 12.0 1,224 Fourth 21.1 6.6 27.7 8.0 5.3 13.2 29.1 11.9 40.9 32.3 1,079 Highest 14.8 5.8 20.6 13.1 7.3 20.4 27.9 13.1 41.0 49.8 1,053 Total 21.0 6.0 27.0 5.0 3.0 8.0 26.1 9.0 35.1 22.9 5,733 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Unmet need for spacing includes pregnant women whose pregnancy was mistimed, amenorrheic women who are not using family planning and whose last birth was mistimed, and fecund women who are neither pregnant nor amenorrheic and who are not using any method of family planning and say they want to wait two or more years for their next birth. Also included in unmet need for spacing are fecund women who are not using any method of family planning and say they are unsure whether they want another child or who want another child but are unsure when to have the birth unless they say it would not be a problem if they discovered they were pregnant in the next few weeks. Unmet need for limiting refers to pregnant women whose pregnancy was unwanted, amenorrheic women whose last child was unwanted, and to fecund women who are neither pregnant nor amenorrheic and who are not using any method of family planning and who want no more children. 2 Using for spacing is defined as women who are using some method of family planning and say they want to delay their next child or are undecided whether to have another. Using for limiting is defined as women who are using and who want no more children. Note that the specific methods used are not taken into account. Fertility Preferences and Unmet Need for Family Planning | 113 currently using a contraceptive method yields the total demand for family planning, which encompasses more than one-third of married women in Eritrea. It was noted in Chapter 5 that contraceptive prevalence has not changed since 1995; interestingly, levels of unmet need for spacing and unmet need for limiting are also the same as those reported in 1995. By age, unmet need for family planning is highest among women age 15-19 (43 percent), and lowest among women age 45-49 (19 percent); a substantial portion of the latter group are menopausal (see Table 6.10). Virtually all unmet need among women under age 30 is for spacing births, while for women in their forties, unmet need is mainly for limiting births. Although in 1995 unmet need in urban areas was higher than in rural areas, the opposite was seen in the 2002 EDHS—a slightly higher level of unmet need in rural areas. Substantial zoba differences are observed in unmet need for contraception, from a low of 19 percent in zoba Debubawi Keih Bahri to 27 percent in zoba Gash-Barka and 33 percent in zoba Debub. Unmet need increases from 26 percent for uneducated women to 35 percent for women who have attained middle-school level, and then declines to 24 percent among women with at least secondary-school education. Unmet need is practically the same among women in the two lowest quintiles and the fourth quintile of the wealth index (27-28 percent), is higher among women in the middle quintile (31 percent), and is the lowest among women in the highest quintile. Because both unmet and met need have remained unchanged since 1995, the overall percentage of demand satisfied has not changed. Less than one-fourth of the total demand for family planning is being satisfied (see next-to-last column in Table 7.3). Demand is least likely to be satisfied among younger women (under age 25), and those who live in rural areas and zoba Gash-Barka. The percentage of need satisfied has increased in zoba Anseba since 1995, but the situation has deteriorated in the other subgroups mentioned above. The total demand satisfied is positively correlated with education and the wealth index. The percentage of demand satisfied ranges from 12 percent for uneducated women to 48 percent for the women in the highest education category. Similarly, for the wealth index, the demand satisfied increases steadily to 50 percent for women in the highest quintile. 7.4 IDEAL FAMILY SIZE The discussion of fertility preferences earlier in this chapter focused on the respondent’s wishes for the future. The number of children she already has clearly influences a woman’s preferences. As in the 1995 EDHS, the 2002 EDHS attempted to obtain a measure that is less dependent on a woman’s current family size—the ideal family size (ideal number of children). Information on what a woman considers the ideal family size was elicited by asking respondents who had no children: “If you could choose exactly the number of children to have in your whole life, how many would that be?” Respondents with children were asked: “If you could go back to the time you did not have any children and choose exactly the number of children to have in your whole life, how many would that be?” The question about ideal family size requires a woman to perform the difficult task of considering the desired family size regardless of the number of children that she already has. As Table 7.4 shows, one in eight respondents in Eritrea gave a non-numeric response, most of them saying that “it is up to God.” The proportion of women giving non- numeric responses increases with the woman’s family size, from one in eleven women with one child to one in four women with seven or more children. This is because the more children a woman has, the more likely she is to be older (see Table 4.4) and uneducated (see Table 3.2); and such women are less likely to have formed specific ideas about desired family size. Table 7.4 indicates that Eritrean women desire large families; overall, only one in ten women wants less than four children. A four-child family is the modal response (21 percent). Almost one-third of women want five or six children, one-sixth want 7-9 children, and one in ten want 10 or more children. Women in Eritrea, regardless of their present family size, desire large families. More than one in ten women with four children, two in ten women with five or six children, and one-fourth of women with 114 | Fertility Preferences and Unmet Need for Family Planning seven or more children consider 10 or more children the ideal family size. It should be noted that all percentages referring to the ideal family size in Table 7.4 would have been higher if they were based on all women and not just those who gave numeric responses. If it were assumed that the women who gave non-numeric responses want all the children God gives them, then half of women who have seven or more children would have an ideal family size of 10 or more children. Table 7.4 also shows the mean ideal number of children for all women and currently married women by current family size. These means exclude women who gave non-numeric responses. The mean ideal number of children for all women is 5.8 and for currently married women 6.3. The mean ideal family size increases with the number of living of children, from 5.3 for women with one child to 8.1 for women with seven or more children. The lower mean ideal family size for all women than for currently married women is more noticeable before women start childbearing. All childless women want fewer than five children, or 0.8 children less than currently married childless women. However, these women may have more children than they currently want if they do not do something to avoid having unwanted children. Table 7.5 presents the mean ideal number of children for all women by age and background characteristics. There is a direct relationship between age and ideal number of children. The mean ideal number of children increases from 4.8 for women age 15-19 to 5.6 for women age 25-29, and 7.2 for women age 45-49. The mean ideal number of children among rural women is much higher than that among their urban counterparts (6.4 and 5.0, respectively). Women in zobas Semenawi Keih Bahri and Anseba (6.5-6.6) have much higher mean ideal family sizes than women in zoba Maekel (4.9). The mean ideal family size is negatively related to both education and the wealth index. For example, the women in the lowest quintile of the wealth index want 7.0 children, whereas the women in the highest quintile have a mean ideal family size of 4.7. The differentials in the mean ideal family size hold across all age groups for all background characteristics shown in Table 7.5. Table 7.4 Ideal number of children Percent distribution of all women by ideal number of children, and mean ideal number of children for all women and for currently married women, according to number of living children, Eritrea 2002 —————————————————————————————————————————————————————————————— Number of living children ———————————————————————————————————————— Ideal number of children 0 1 2 3 4 5 6 7+ Total —————————————————————————————————————————————————————————————— 0 2.5 1.3 1.2 1.3 1.3 0.9 1.4 2.0 1.7 1 0.5 0.2 0.3 0.3 0.0 0.0 0.0 0.0 0.3 2 4.7 1.9 2.6 1.2 0.4 0.2 1.2 0.0 2.4 3 9.4 8.7 3.4 3.5 1.2 1.1 1.0 0.9 5.4 4 31.9 27.7 22.1 16.3 14.8 5.8 5.9 3.5 21.3 5 16.8 17.9 16.7 15.4 9.4 7.2 5.4 5.0 13.9 6 15.3 15.0 18.7 24.0 22.6 17.4 18.9 11.6 17.4 7 3.2 4.5 4.8 8.2 12.4 11.2 7.0 6.9 6.1 8 4.2 5.4 6.4 7.2 11.4 18.3 15.2 15.2 8.1 9 0.4 0.6 0.8 0.8 0.9 3.4 4.7 4.9 1.4 10+ 5.0 7.4 8.2 8.8 11.1 15.1 21.0 26.0 10.0 Non-numeric responses 6.0 9.5 14.7 13.0 14.5 19.4 18.4 23.9 12.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 2,874 1,218 1,070 1,034 794 603 480 682 8,754 Mean ideal number of children for: All women 4.9 5.3 5.6 5.9 6.4 7.2 7.5 8.1 5.8 Number 2,700 1,102 912 900 679 486 392 519 7,689 Currently married women 5.7 5.5 5.8 6.0 6.5 7.3 7.6 8.0 6.3 Number 670 835 758 752 599 434 357 491 4,895 Fertility Preferences and Unmet Need for Family Planning | 115 Table 7.5 Mean ideal number of children by background characteristics Mean ideal number of children for all women, by age and background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Current age of woman Background ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– characteristic 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 4.3 4.8 5.0 5.3 5.4 6.2 6.3 5.0 Asmara 4.0 4.6 4.7 4.6 4.9 5.8 5.5 4.7 Other towns 4.6 4.9 5.3 5.9 5.9 6.6 7.1 5.4 Rural 5.3 5.9 6.3 6.9 7.3 7.5 7.8 6.4 Zoba Debubawi Keih Bahri 4.6 5.2 5.4 6.1 6.7 6.4 6.8 5.7 Maekel 4.2 4.7 4.8 5.0 5.2 5.9 5.7 4.9 Semenawi Keih Bahri 5.3 5.9 6.4 6.7 7.4 7.6 8.1 6.6 Anseba 5.4 5.9 6.4 7.2 7.0 7.6 7.9 6.5 Gash-Barka 5.0 5.6 6.3 7.0 6.8 7.6 7.5 6.2 Debub 5.0 5.3 5.5 6.0 6.5 6.8 7.4 5.7 Education No education 5.7 5.9 6.5 6.8 7.2 7.4 7.5 6.7 Primary 5.0 5.5 5.5 5.9 5.7 6.4 6.2 5.5 Middle 4.7 4.9 4.9 (5.5) (5.0) * * 4.9 Secondary + 4.3 4.6 4.6 4.5 4.7 5.0 * 4.5 Wealth index Lowest 5.7 6.2 6.8 7.7 7.7 7.9 8.3 7.0 Second 5.1 6.0 6.6 6.8 7.4 7.2 8.0 6.4 Middle 5.1 5.8 6.0 6.4 7.0 7.4 7.2 6.1 Fourth 4.8 5.1 5.2 5.7 5.8 6.8 6.6 5.4 Highest 4.1 4.6 4.8 4.9 5.1 5.5 5.9 4.7 Total 4.8 5.3 5.6 6.2 6.4 6.9 7.2 5.8 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 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. 7.5 IDEAL FAMILY SIZE, UNMET NEED, AND STATUS OF WOMEN An increase in women’s empowerment is recognized as important for efforts to reduce fertility through at least two main pathways: its negative association with desired family size and its positive association with women’s ability to meet their own family-size goals through the effective use of contraception. Table 7.6 shows how women’s ideal family size and unmet need for family planning vary according to two indicators of women’s empowerment. The first indicator is the number of decisions in which the respondent has the final say, by herself or jointly with someone (for list of decisions see Table 3.15); and ranges in value from 0 to 6. The indicator is positively related to women’s empowerment and reflects the degree of control women are able to exercise in areas that affect their life and environment. The second indicator, which ranges in value from 0 to 5, is the number of specified situations in which the respondent feels a husband would be justified in beating his wife (see Table 3.16 for the list of reasons). A lower score on this indicator is interpreted to reflect a greater sense of entitlement, self-esteem, and status. Contrary to expectation, the mean ideal number of children is lowest (5.9) for women who have no say in any of the six decisions. However, among other women, the mean ideal number of children 116 | Fertility Preferences and Unmet Need for Family Planning decreases from 6.7 for women with a final say in 1-2 decisions to 6.1 for women with a final say in 5-6 decisions. The relationship between the mean ideal number of children and the number of reasons for which women consider wife beating justified shows the expected pattern. The mean ideal number of children is lower for women who believe that wife beating is not justified for any of the specified reasons than for women who agree with three or more reasons. Overall, women’s autonomy in terms of their final say, alone or jointly, in decisionmaking is negatively related to the total unmet need for family planning. Total unmet need and unmet need for spacing decrease as women’s autonomy increases, while unmet need for limiting increases as the decisionmaking power of women increases. Total unmet need and the number of reasons for which women consider wife beating justified show no consistent relationship. However, each type of unmet need is lowest among women who consider wife beating unjustified for any reason. 7.6 FERTILITY PLANNING Several indicators of the level of unwanted fertility can be derived from the 2002 EDHS data. First, responses to a question about the planning status of recent births and any current pregnancies—that is, whether a birth or pregnancy was planned (wanted then), mistimed (wanted later), or unwanted (not wanted at all)—provide an indication of the extent of unplanned fertility. In interpreting these data, however, it is important to remember that women may rationalize mistimed and unwanted pregnancies, declaring them as wanted after the children are born. Table 7.7 shows the percent distribution of births in the five years preceding the survey and current pregnancies by fertility planning status. Three-fourths of births in the five-year period were Table 7.6 Ideal number of children and unmet need by women’s status Mean ideal number of children and unmet need for spacing and limiting among currently married women, by women's status indicators, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mean ideal Number Unmet need for family planning2 Number number of of –––––––––––––––––––––––––––––– of Women’s status indicator children1 women For spacing For limiting Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of decisions in which woman has final say3 0 5.9 142 33.5 2.4 35.9 189 1-2 6.7 1,057 25.0 4.9 29.9 1,240 3-4 6.5 1,291 21.3 6.9 28.2 1,485 5-6 6.1 2,405 18.3 6.3 24.6 2,819 Number of reasons wife beating is justified 0 6.0 1,355 18.9 5.3 24.1 1,543 1-2 6.2 1,136 23.2 6.3 29.4 1,337 3-4 6.6 1,489 21.5 5.9 27.5 1,722 5 6.5 915 20.7 6.8 27.5 1,132 Total 6.3 4,895 21.0 6.0 27.0 5,733 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Means are calculated excluding the women giving non-numeric responses. 2 See Table 7.3 for definition of unmet need for family planning 3 Herself or jointly with others Fertility Preferences and Unmet Need for Family Planning | 117 wanted when they occurred (planned) and one-fourth were not planned; 6 percent were unwanted, while 20 percent were mistimed (wanted later). The proportion of mistimed births has increased from 14 percent in 1995 to 20 percent in 2002, while the proportion of unwanted births has increased only slightly (from 5 to 6 percent). According to Table 7.7, around one in four births of orders 1-6 (22-26 percent) were not planned, compared with more than one-third (36 percent) of higher-order births. Of the unplanned births, three- fourths of first-order births were mistimed but higher-order births were as likely to be unwanted as mistimed. Births to women age 20-34 were less likely to be unplanned than births to younger women (under age 20) or older women (age 35 and above). Births to women under age 35 were more likely to be mistimed than unwanted. The proportion of unwanted births increases after age 34—because these women have larger families—from 10 percent for women age 30-34 to 31 percent for women age 45-49. By wealth index, mistimed births increase from 16 percent for women in the lowest quintile to 22 percent for women in the middle and fourth quintiles. A second approach to measuring unwanted fertility is to calculate wanted fertility rates. The wanted fertility rate is computed in the same way as the total fertility rate, except that unwanted births are Table 7.7 Fertility planning status Percent distribution of births in the five years preceding the survey (including current pregnancies) by fertility planning status, according to birth order, mother’s age at birth, and wealth index, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Planning status of birth Birth order, –––––––––––––––––––––––––––– mother's age Number at birth, and Wanted Wanted Wanted of weight index then later no more Missing Total births ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Birth order 1 77.4 16.6 5.1 0.9 100.0 1,295 2 76.7 20.6 1.9 0.8 100.0 1,240 3 76.0 20.7 2.2 1.1 100.0 1,118 4 75.9 19.9 4.1 0.1 100.0 839 5 73.5 20.8 4.7 1.1 100.0 691 6 73.3 21.0 4.9 0.8 100.0 594 7+ 63.2 18.8 17.2 0.9 100.0 1,151 Mother's age at birth <20 66.0 27.8 5.1 1.0 100.0 845 20-24 76.6 19.9 2.6 0.9 100.0 1,613 25-29 78.7 17.7 3.0 0.6 100.0 1,713 30-34 75.2 18.3 5.5 1.0 100.0 1,207 35-39 70.6 18.9 10.0 0.6 100.0 1,056 40-44 66.7 15.1 17.1 1.1 100.0 394 45-49 54.9 14.3 30.7 0.0 100.0 100 Wealth index Lowest 77.2 16.3 5.9 0.6 100.0 1,495 Second 76.0 18.5 4.7 0.7 100.0 1,470 Middle 71.2 21.9 6.1 0.8 100.0 1,447 Fourth 69.5 22.1 7.2 1.1 100.0 1,392 Highest 74.9 18.8 5.5 0.8 100.0 1,123 Total 2002 73.8 19.5 5.9 0.8 100.0 6,928 Total 1995 80.8 13.5 4.9 0.7 100.0 3,047 118 | Fertility Preferences and Unmet Need for Family Planning excluded from the numerator. In this case, unwanted births are those that exceed the number mentioned as ideal by the respondent. This rate represents the level of fertility that would have prevailed in the three years preceding the survey if all unwanted births had been avoided. A comparison of the total wanted fertility rate and the total fertility rate suggests the potential demographic impact of the elimination of unwanted births. The total wanted fertility rate for Eritrea is 4.4, roughly one-half child less than the total fertility rate (Table 7.8). Stated another way, the total wanted fertility rate is 92 percent of the observed total fertility rate. The differences between total fertility rates and total wanted fertility rates are small for all subgroups in Table 7.8. The total wanted fertility rate declined substantially between the two surveys, from 5.7 in 1995 to 4.4 in 2002. Table 7.8 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 2002 EDHS 1995 EDHS ––––––––––––––––––– ––––––––––– Total Total wanted Total wanted Background fertility fertility fertility characteristic rate rate rate –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 3.1 3.5 3.8 Asmara 2.8 3.0 3.2 Other towns 3.5 4.0 4.8 Rural 5.3 5.7 6.5 Zoba Debubawi Keih Bahri 3.5 3.9 * Maekel 3.1 3.4 3.9 Semenawi Keih Bahri 4.3 4.5 (6.4) Anseba 5.1 5.6 5.1 Gash-Barka 4.6 5.1 5.1 Debub 5.2 5.7 7.5 Education No education 5.1 5.5 6.4 Primary 4.0 4.4 u Middle 3.6 3.8 u Secondary + 2.9 3.1 (2.6) Total 4.4 4.8 5.7 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Rates are 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 4.2. Figures in parentheses are based on 250-499 woman-years of exposure. An asterisk indicates that a figure is based on fewer than 250 women-years of exposure and has been suppressed. u = Unknown (not available) Fertility Preferences and Unmet Need for Family Planning | 119 7.7 ATTITUDES TOWARD UNPLANNED PREGNANCY In the preceding section, the success in fertility planning in the past was measured by classifying births into three categories: planned, mistimed, and unwanted. This section examines the attitudes of women toward a possible unplanned pregnancy in the near future. Women who are using contraception or are pregnant are considered not at risk of pregnancy. This is also true for women who want to have a child soon (within two years). Currently married women who want to space births (wait at least two years for the next birth) as well as those who want no more children and who are not using any family planning method are at risk of an unplanned pregnancy. Women at risk of unplanned pregnancy were asked: “In the next few weeks, if you discovered that you were pregnant, would that be a big problem, a small problem, or no problem for you?” The response to the question reflects the seriousness of a woman’s future fertility intentions and the level of distress associated with a deviation from the stated intention. In Table 7.9, the responses are summarized in Table 7.9 separately for those who want to space births and those who want to limit births. The left panel of Table 7.9 shows the responses of women who want no more children but are not using contraception. Almost nine in ten women said that getting pregnant in the next few weeks would be a problem; including 78 percent who termed the problem “a big problem.” Women under age 30 are more likely than older women to consider an unwanted pregnancy in the near future a big problem. The level of distress of an unplanned future pregnancy is most often positively related to the number of living children. For example, 72 percent of women with 0-2 children think that an unwanted pregnancy would be a big problem, compared with 79 percent of women with five or more children. However, the proportion of women who say that an unwanted pregnancy would not be a problem does not differ by number of living children. The differences in planning status are largest for the most recent birth. Women with no birth in the past five years are less likely to say that an unwanted pregnancy would be a big problem than women who have already had a mistimed or unwanted birth. Eighty-six percent of women whose last birth was wanted later and almost all (97 percent) women whose last birth was unwanted, said that an unplanned pregnancy would be a big problem. There is no clear pattern by wealth index. For women who want to space their next birth but are not using a family planning method (the right panel of Table 7.9), the level of distress associated with an unplanned pregnancy is not as high as among women who want no more children. Sixty-three percent of women who wanted to space their next birth consider an unplanned pregnancy a big problem, 15 percent consider it a small problem, and 22 percent regard it as no problem. The percentage of women who say that an unplanned pregnancy would be a problem shows an inverted U-shaped pattern by age and by current family size. Women who had no births in the last five years are least likely to consider an unplanned pregnancy in the near future a big problem; more than two-thirds mentioned that an unplanned pregnancy is either a small problem (13 percent) or no problem (54 percent). The proportion of women saying that a pregnancy in the near future would be no problem increases with increasing education and wealth. Rural women who want to space their next birth are more likely to say that a pregnancy in the near future would be a problem (81 percent) than their urban counterparts: Total urban (67 percent) and Asmara (58 percent). These results clearly suggest a greater need to provide family planning education and services to rural women who want to space and who are currently not using a contraceptive method. 120 | Fertility Preferences and Unmet Need for Family Planning Ta bl e 7. 9 A tti tu de s of n on us er s to w ar d m ist im ed a nd u nw an te d pr eg na nc ie s Pe rc en t d ist rib ut io n of c ur re nt ly m ar rie d w om en e xp os ed to p re gn an cy w ho w an t n o m or e ch ild re n or w an t t o w ai t t w o or m or e ye ar s fo r th e ne xt c hi ld b y th e pe rc ei ve d pr ob le m if th ey go t p re gn an t i n th e ne xt fe w w ee ks a nd b y fe rt ili ty p re fe re nc es , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, E rit re a 20 02 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — At tit ud e to w ar d be co m in g pr eg na nt At tit ud e to w ar d be co m in g pr eg na nt am on g no nu se rs w ho w an t t o lim it am on g no nu se rs w ho w an t t o sp ac e — — — — — — — — — — — — — — — — — — — N um be r — — — — — — — — — — — — — — — — — — — — N um be r Ba ck gr ou nd Bi g Sm al l N o of Bi g Sm al l N o of ch ar ac te ris tic pr ob le m pr ob le m pr ob le m M iss in g To ta l w om en pr ob le m pr ob le m pr ob le m M iss in g To ta l w om en — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — Ag e 1 5- 19 * * * * 10 0. 0 11 59 .4 13 .8 26 .0 0. 9 10 0. 0 24 3 2 0- 29 89 .2 3. 4 5. 9 1. 4 10 0. 0 67 66 .3 14 .4 18 .4 0. 9 10 0. 0 71 9 3 0- 49 76 .1 10 .3 11 .9 1. 7 10 0. 0 64 0 58 .9 15 .3 23 .8 2. 0 10 0. 0 54 3 Re si de nc e T ot al u rb an 77 .5 7. 6 12 .4 2. 4 10 0. 0 27 0 54 .9 12 .0 30 .5 2. 6 10 0. 0 41 7 A sm ar a 76 .2 7. 0 12 .5 4. 3 10 0. 0 12 1 48 .6 8. 9 39 .6 3. 0 10 0. 0 18 5 O th er to w ns 78 .6 8. 1 12 .4 0. 9 10 0. 0 15 0 60 .0 14 .5 23 .3 2. 2 10 0. 0 23 2 R ur al 77 .6 10 .7 10 .7 1. 1 10 0. 0 44 8 65 .4 15 .6 18 .2 0. 8 10 0. 0 1, 08 8 Ed uc at io n N o ed uc at io n 78 .2 9. 9 10 .7 1. 2 10 0. 0 52 0 63 .2 16 .7 18 .4 1. 6 10 0. 0 89 0 P rim ar y 81 .8 10 .2 8. 0 0. 0 10 0. 0 94 66 .4 11 .3 22 .0 0. 4 10 0. 0 30 5 M id dl e (7 6. 8) (0 .0 ) (2 3. 2) (0 .0 ) 10 0. 0 38 61 .6 13 .9 24 .5 0. 0 10 0. 0 13 7 S ec on da ry + (6 6. 7) (1 0. 9) (1 4. 2) (8 .2 ) 10 0. 0 65 52 .6 10 .2 34 .7 2. 5 10 0. 0 17 3 N um be r of li vi ng c hi ld re n 0 -2 71 .9 9. 6 12 .8 5. 8 10 0. 0 58 58 .1 14 .8 26 .1 0. 9 10 0. 0 77 5 3 -4 76 .1 7. 9 12 .5 3. 6 10 0. 0 14 2 71 .4 12 .9 14 .3 1. 5 10 0. 0 47 2 5 + 78 .6 10 .0 10 .8 0. 6 10 0. 0 51 8 59 .5 17 .3 21 .2 2. 0 10 0. 0 25 7 Fe rt ili ty p la nn in g st at us (l as t 5 y ea rs ) N o bi rth 62 .9 16 .0 18 .2 2. 9 10 0. 0 25 0 31 .5 13 .3 53 .5 1. 6 10 0. 0 21 1 W an te d th en 79 .7 10 .0 10 .3 0. 0 10 0. 0 24 4 65 .0 16 .7 17 .1 1. 3 10 0. 0 97 0 W an te d la te r 85 .8 3. 2 7. 9 3. 1 10 0. 0 10 9 73 .7 10 .2 15 .4 0. 7 10 0. 0 29 0 W an te d no m or e 97 .3 0. 4 1. 4 0. 9 10 0. 0 11 1 (9 3. 1) (2 .0 ) (3 .6 ) (1 .3 ) 10 0. 0 31 W ea lth in de x L ow es t 80 .3 12 .0 6. 0 1. 7 10 0. 0 17 2 61 .6 20 .6 17 .4 0. 4 10 0. 0 29 5 S ec on d 78 .4 8. 4 13 .1 0. 0 10 0. 0 13 4 66 .6 16 .6 16 .1 0. 7 10 0. 0 34 8 M id dl e 77 .7 9. 1 13 .2 0. 0 10 0. 0 13 0 64 .4 13 .7 20 .5 1. 4 10 0. 0 37 7 F ou rth 83 .8 4. 8 8. 3 3. 1 10 0. 0 13 3 61 .9 11 .6 25 .1 1. 5 10 0. 0 28 4 H ig he st 67 .9 12 .2 16 .9 3. 0 10 0. 0 14 9 54 .1 8. 3 34 .3 3. 3 10 0. 0 20 0 To ta l 77 .5 9. 5 11 .3 1. 6 10 0. 0 71 8 62 .5 14 .6 21 .6 1. 3 10 0. 0 1, 50 5 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — N ot e: E xp os ed w om en a re th os e cu rr en tly m ar rie d an d fe cu nd w ho a re n ot u sin g co nt ra ce pt io n an d w ho a re n ot p re gn an t. To ta l i nc lu de s 3 w om en w ith m iss in g in fo rm at io n on fe rti lit y st at us o f la st b irt h in t he f iv e ye ar s pr ec ed in g th e su rv ey , w ho a re n ot s ho w n se pa ra te ly . 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. An a st er isk in di ca te s a fig ur e is ba se d on 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. Infant and Child Mortality | 121 INFANT AND CHILD MORTALITY 8 The information presented in this chapter is important not only for the demographic assessment of the country’s population, but also in the design and evaluation of health policies and programs. Furthermore, information on infant and child mortality is important for the improvement of child survival programs and for identifying the most vulnerable subgroups of children. The reduction of infant and child mortality and the incidence of high-risk pregnancies remain priority targets of the National Health Policy (MOH, 1998). This chapter presents information on levels, trends, and differentials in mortality among children under five years of age in Eritrea. The chapter also examines variations in mortality levels according to certain demographic and socioeconomic characteristics that have been shown to influence infant and child mortality (e.g., rural residence, young maternal age at birth, and short birth intervals). The mortality levels from the 2002 EDHS are central to the assessment of the current demographic situation in Eritrea. Mortality levels are also one of the main indicators of the standard of living or development of a population. Thus, identifying segments of the child population that are at greater risk of dying contributes to efforts directed at improving child survival and lowering the exposure of young children to risk. 8.1 ASSESSMENT OF DATA QUALITY The 2002 EDHS mortality estimates are calculated from information that was collected in the birth history section of the Women’s Questionnaire. The birth history section begins with questions about the respondent’s experience with childbearing (i.e., the number of sons and daughters living with the mother, the number who live elsewhere, and the number who have died). These questions were followed by a retrospective birth history in which each respondent was asked to list each of her births, starting with the first birth. For each birth, data were obtained on sex, month and year of birth, survivorship status, and current age, or if the child was dead, age at death. This information is used to directly estimate mortality rates. In this chapter, the following rates are used to assess and measure infant and child mortality: • Neonatal mortality: the probability of dying within the first month of life; • Postneonatal mortality: the difference between infant and neonatal mortality; • Infant mortality: the probability of dying during the first year of life; • Child mortality: the probability of dying between the first and fifth birthday; • Under-five mortality: the probability of dying before the fifth birthday. All rates are expressed as deaths per 1,000 live births, except the child mortality rate, which is expressed as deaths per 1,000 children surviving to the first birthday. The reliability of mortality estimates from surveys such as the 2002 EDHS that derive estimates from retrospective birth histories is affected by a number of factors. These factors include the completeness with which deaths of children are reported, and the extent to which birth dates and ages at death are accurately reported. Omission of either births or deaths is the most serious problem because it 122 | Infant and Child Mortality directly affects mortality estimates. When selective omission of childhood deaths occurs, it is usually more severe for deaths occurring early in infancy. Errors in reporting of birth dates may cause a distortion of trends over time, while errors in reporting of age at death can distort the age pattern of mortality. One way such omissions can be detected is by examining the proportion of neonatal deaths and infant deaths. Generally, if there is substantial underreporting of deaths, the result is an abnormally low ratio of neonatal deaths to infant deaths and deaths under seven days to all neonatal deaths. Since underreporting of deaths is likely to be more common for births that occurred a long time before the survey, it is important to explore whether these ratios change markedly over time. The extent to which such errors in survey data manifested themselves in the 2002 EDHS is examined below. Results from Appendix Table C.5 suggest that early infant deaths have not been seriously underreported in Eritrea because the ratios of deaths under seven days to all neonatal deaths are quite high. Seventy-four percent of the neonatal births in the five years prior to the 2002 EDHS were early neonatal births (a ratio of less than 25 percent is generally consider to indicate underreporting of early neonatal deaths). However, the fact that the ratios show declines from 74 and 73 in the periods 0-4 and 5- 9 years before the survey to 62 and 64 in the periods 10-14 and 15-19 years preceding the survey, respectively, suggests that there is some underreporting of births that occurred more than 20 years preceding the 2002 survey. Similar patterns of declining ratios were observed in the relevant periods in the 1995 EDHS. Generally, a higher proportion of early neonatal deaths was observed in the 2002 EDHS than in the 1995 EDHS. Inspection of the ratios shown in Appendix Tables C.5 and C.6 indicates that there was no selective underreporting of early neonatal deaths in the 2002 EDHS for two reasons. First, the proportion of early neonatal deaths is high for the two most recent five-year periods. Second, the proportion of infant deaths is plausible (see Appendix Table C.6). Another factor that affects childhood mortality estimates is the quality of reporting of age at death. In general, these problems are less serious for periods in the recent past than for those in the more distant past. If age at death is misreported, it will bias the estimates, especially if the net effect of the age misreporting results in transference of deaths from one age bracket to another. For example, a net transfer of deaths from under one month to a higher age, will affect the estimates of neonatal and postneonatal mortality. To minimize errors in the reporting of age at death, 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 two, and in years if the child was two years or older. Table C.5 shows age heaping at ages 7 and 14 days, which is a sign of approximation of age to one and two weeks, respectively. Although age heaping at 14 days may not bias any indicator, the heaping at 7 days is likely to lead to a lower estimate of early neonatal mortality. Appendix Table C.6 shows some evidence of heaping at age 12 months (an approxi- mation of age to one year). However, age heaping is higher for births in the three preceding five-year periods (5-9, 10-14, and 15-19 years prior to survey) than for births in the most recent period (0-4 years before the survey). The reporting of deaths in the five years preceding the survey shows some heaping but does not show substantial heaping, and it is therefore not necessary to adjust the data used to estimate mortality levels. 8.2 EARLY CHILDHOOD MORTALITY RATES: LEVELS AND TRENDS Early childhood mortality rates for the 15 years preceding the survey are presented by five-year periods in Table 8.1. For the most recent period (i.e., 0-4 years before the survey, which corresponds roughly to the period 1997-2001), the infant mortality rate is 48 deaths per 1,000 live births. This means that one in every 21 babies born in Eritrea does not live to the first birthday. Of those who survive to their first birthday, another 48 out of 1,000 die before reaching their fifth birthday. The overall under-five mortality is estimated at 93 deaths per 1,000 live births, which implies that one in every 11 Eritrean babies does not survive to his or her fifth birthday. Infant and Child Mortality | 123 Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods preceding the survey, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Neonatal Postneonatal Infant Child Under-five Years Approximate mortality mortality mortality mortality mortality preceding calendar rate rate1 rate rate rate the survey years (NN) (PNN) (1q0) (4q1) (5q0) ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 0-4 1997-2001 24 24 48 48 93 5-9 1992-1996 35 32 67 58 121 10-14 1987-1991 28 45 73 81 148 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Computed as the difference between the infant and the neonatal mortality rates In the first year of life, the first month is the hardest to survive. The neonatal and postneonatal rates are the same, 24 deaths per 1,000 live births, indicating that the same number of children die in the first month of life as in the subsequent 11 months. Although, theoretically, the postneonatal period should exhibit a lower risk of death than the neonatal period. Table 8.1 show that although infant mortality in Eritrea was high in the past, it has declined substantially. Between the two most recent five-year periods, there was a decline in infant mortality of 19 percentage points, and during the previous two five-year periods there was a decline of 6 percentage points. Under-five mortality has declined 28 percentage points between the most recent five-year periods, and there was about the same amount of decline during the earlier two periods. Another way of examining trends in mortality is by comparing the 2002 EDHS results with findings from other sources, such as the 1995 EDHS, in which data were collected using the same techniques and estimates were calculated using the same methodology. Comparison of estimates of infant mortality from the 2002 EDHS and adjusted estimates from the 1995 EDHS shows that mortality in Eritrea has declined by 33 percent during the period (from 72 to 48 deaths per 1,000), an annual decline of 5 percent (Figure 8.1). This decline is mainly accounted for by a drop in postneonatal mortality from 41 deaths per 1,000 in the five years before the 1995 survey to 24 deaths per 1,000 in 2002. In the same period, child mortality and under-five mortality declined from 68 and 136 deaths per 1,000 to 48 and 93 deaths per 1,000, respectively. The declines in child mortality and under-five mortality are close to 5 percent per year. These figures suggest that early childhood mortality in Eritrea declined substantially between the two surveys. The main reasons for this decline were the concerted efforts of health providers and the Expanded Program on Immunization (EPI) in the design and successful implementation of health programs such as antenatal care and treatment of childhood diseases (see Chapter 9). 8.3 DIFFERENTIALS IN MORTALITY Differentials in early childhood mortality indicators are presented in Tables 8.2 and 8.3. For all but one variable, mortality estimates are calculated for a ten-year period before the survey (approximately 1992-2001), so that the rates are based on a sufficient number of cases in each subgroup to ensure adequate statistical precision of estimates. Five-year rates are presented for size of child at birth in Table 8.3 because information for this indicator was collected only for births since January 1997. 124 | Infant and Child Mortality Socioeconomic Differentials Table 8.2 and Figure 8.2 show the early childhood mortality rates in Eritrea by socioeconomic characteristics. Mortality levels for all indicators in urban areas are consistently lower than those in rural areas. For example, under-five mortality in urban areas is 26 percent lower than in rural areas. The 2002 EDHS results show wide regional differences in mortality in Eritrea. Infant mortality ranges from a low of 37 deaths per 1,000 live births in zoba Anseba to a high of 122 deaths per 1,000 in zoba Debubawi Keih Bahri. For under-five mortality, only zobas Maekel and Anseba have rates under 74 deaths per 1,000, whereas other zobas have substantially higher mortality, ranging from 111 deaths per 1,000 in zoba Debub to 187 deaths per 1,000 in zoba Debubawi Keih Bahri. Children in the two Red Sea zobas are at especially high risk of dying in early childhood. Generally, a mother’s level of education is inversely related to her child’s risk of dying. Although the relationship is not linear, children born to mothers with no education suffer the highest mortality at all ages. Data in Table 8.2 indicate that the effect of mother’s education is greater on child mortality and under-five mortality than on neonatal, postneonatal, and infant mortality. The infant mortality rate for children whose mothers have a primary education is 25 percent lower than that of children whose mothers have no education. The gap between children of mothers with at least a secondary education and children of mothers with no education is 36 percent. The corresponding figure for child mortality is 70 percent, and for under-five mortality, 51 percent. The gaps in neonatal and postneonatal mortality rates between infants whose mothers have some secondary education and infants whose mothers have no education are 36 percent and 35 percent, respectively. This pattern of mortality differentials is not unexpected and is due to the fact that the causes of neonatal mortality are more biological in nature and less influenced by socioeconomic factors; the causes of child mortality and under-five mortality are more likely to be nonbiological factors. The last panel in Table 8.2 shows that early childhood mortality has an inverted U-shaped relationship with the wealth index; the middle quintile has the highest mortality rates. However, at all EDHS 2002 Figure 8.1 Trends in Childhood Mortality Note: Infant mortality and child mortality rates for 1991-95 are adjusted rates. 25 41 72 68 136 24 24 48 48 93 Neonatal mortality Postneonatal mortality Infant mortality Child mortality Under-five mortality rate 0 20 40 60 80 100 120 140 160 1991-95 1997-2001 EDHS 1995 and EDHS 2002 Infant and Child Mortality | 125 Table 8.2 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period pre- ceding the survey, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Neonatal Postneonatal Infant Child Under-five mortality mortality mortality mortality mortality Background rate rate1 rate rate rate characteristic (NN) (PNN) (1q0) (4q1) (5q0) –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Urban 23 26 48 40 86 Rural 33 29 62 59 117 Zoba Debubawi Keih Bahri 55 67 122 74 187 Maekel 19 20 39 22 60 Semenawi Keih Bahri 39 38 77 83 154 Anseba 20 16 37 37 73 Gash-Barka 41 25 66 61 123 Debub 27 31 58 56 111 Mother’s education No education 33 31 64 60 121 Primary 25 23 48 44 89 Middle 15 19 34 (29) (62) Secondary + 21 20 41 18 59 Wealth index Lowest 24 24 48 54 100 Second 40 29 68 64 127 Middle 43 38 81 66 142 Fourth 20 26 47 43 88 Highest 18 20 38 28 65 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 250-499 unweighted cases. 1 Computed as the difference between the infant and the neonatal mortality rates EDHS 2002 Figure 8.2 Under-five Mortality by Background Characterstics 0 86 117 187 60 154 73 123 111 121 89 62 59 100 127 142 88 65 RESIDENCE Urban Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub EDUCATION No education Primary Middle Secondary + WEALTH INDEX (quintile) Lowest Second Middle Fourth Highest 0 50 100 150 200 250 126 | Infant and Child Mortality ages, the children in the fourth and highest quintiles have lower mortality rates than the two lowest quintiles. For socioeconomic characteristics for which comparisons can be made between the 1995 EDHS and the 2002 EDHS, there is a marked decline in all mortality indicators. Demographic Differentials The demographic characteristics of both mother and child have been found to play an important role in the survival probability of children. Table 8.3 presents early childhood mortality rates by demographic characteristics (sex of child, mother’s age at birth, birth order, previous birth interval, and birth size). Table 8.3 Early childhood mortality rates by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey, by demographic characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Neonatal Postneonatal Infant Child Under-five mortality mortality mortality mortality mortality Demographic rate rate1 rate rate rate characteristic (NN) (PNN) (1q0) (4q1) (5q0) –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Child’s sex Male 36 28 64 55 116 Female 23 28 50 50 98 Mother’s age at birth <20 42 31 73 56 125 20-29 27 26 53 48 99 30-39 28 30 58 57 111 40-49 32 29 61 (55) (113) Birth order 1 42 27 69 49 115 2-3 25 24 49 45 91 4-6 23 28 52 60 109 7+ 38 38 75 57 129 Previous birth interval2 <2 43 49 92 75 160 2 years 21 22 43 44 85 3 years 16 19 34 39 72 4+ years 18 16 33 47 78 Birth size3 Small or very small 24 25 49 * * Average or larger 21 23 44 (34) (76) –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 250-499 unweighted cases. An asterisk indicates that a figure is based on fewer than 250 unweighted cases and has been suppressed. 1 Computed as the difference between the infant and the neonatal mortality rates 2 Excludes first-order births 3 Based on the five-year period before the survey Infant and Child Mortality | 127 In Eritrea, during the postneonatal period, both sexes have an equal chance of dying (28 deaths per 1,000 live births), but for all other early childhood mortality indicators the levels are consistently higher for male children than for female children. Neonatal mortality is 57 percent higher and under-five mortality is 16 percent higher for males than females. The 1995 EDHS results showed a similar mortality pattern; the differences were slightly higher in the 1995 EDHS than in the 2002 EDHS. Although the hypothesis “too early and too late increases child mortality” is generally upheld in the 2002 EDHS, evidence from Table 8.3 suggests that in Eritrea, too-early childbearing is more risky than too-late childbearing. The safest age for childbearing ranges from 20 to 29. Compared with a child’s risk of dying before the first birthday for a child born to mothers age 20-29, having a child before age 20 increases the child’s risk of dying by 38 percent; the risk of having a child at age 40-49 increases the child’s risk of dying by 15 percent. The effect of birth order operates mostly during infancy, with second- and third-order births having the lowest risk of dying in the first year of life. First-order births, on the other hand, have a 41 percent greater risk of dying (69 deaths per 1,000 births) before the first birthday than second- and third- order births. First births and seventh- and higher-order births have the highest neonatal, infant, and under- five mortality rates. Short birth intervals are associated with increased risk of dying. Children born less than two years after a previous birth are twice as likely to die before age five as those born after an interval of at least three years. These results reinforce the need to promote child spacing mechanisms such as breastfeeding and family planning as ways of ensuring child survival. Birth weight is a factor often associated with the child survival, particularly during the first year. Since few women in Eritrea give birth in a health facility (28 percent), there was no birth weight recorded for most children. As a measure of birth size, women were asked whether, in their judgment, the size of their baby at birth was very small, small, average, or larger than average. As expected, babies reported as small or very small at birth have higher mortality rates than those reported as average or large at birth. But the differences are small. 8.4 EARLY CHILDHOOD MORTALITY BY WOMEN’S STATUS Women’s status, as measured by their ability to control resources and make decisions, is associated with infant and child mortality levels. In the 2002 EDHS, women were asked questions related to women’s autonomy (see Chapter 3). The questions included the number of household decisions in which the woman participates in the final say and the number of reasons the woman thinks wife beating is justified. A woman is considered more independent if she participates in a large number of household decisions. On the other hand, the more reasons she perceives wife beating as justified, the less independent she is. Although there is an inverse relationship between women’s status and early childhood mortality, the relationship is not necessarily linear (Table 8.4). Women’s status, as measured by decisionmaking power, seems to be most strongly associated with infant mortality. Among children born to women who have no final say in any decisions, 101 per 1,000 die before the first birthday, compared with about 59 per 1,000 children born to women who participate in some decisionmaking. In Eritrea, childhood mortality levels are associated with whether or not the mother has some power to make final decisions; it does not depend on the number of decisions the mother makes. Attitudes toward wife beating are a reflection of women’s status. Women who do not approve of any form of wife beating are assumed to enjoy a higher status in the household and in society. In turn, this translates into a more favorable mortality profile for their children. Table 8.4 shows the pattern of the 128 | Infant and Child Mortality relationship. Generally, children of lower-status women have higher levels of mortality. The infant mortality rate for children of mothers who consider wife beating unjustified for any reason is 51 per 1,000 compared with 72 per 1,000 for children whose mothers agree with all of the specified reasons for wife beating. A similar relationship is observed between women’s status and levels of child mortality and under-five mortality. Table 8.4 Early childhood mortality rates by women’s status indicators Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preced- ing the survey, by women’s status indicators, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Neonatal Postneonatal Infant Child Under-five mortality mortality mortality mortality mortality Indicator of rate rate1 rate rate rate women’s status (NN) (PNN) (1q0) (4q1) (5q0) –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of decisions in which woman has final say2 0 56 45 101 (68) (162) 1-2 33 27 59 56 112 3-4 28 26 54 53 104 5-6 28 29 57 50 104 Number of reasons wife beating is justified 0 27 24 51 41 90 1-2 32 22 54 46 98 3-4 26 29 56 57 110 5 35 37 72 64 132 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 250-499 unweighted cases. 1 Computed as the difference between the infant and the neonatal mortality rates 2 Either herself or jointly with others 8.5 HIGH-RISK FERTILITY BEHAVIOR Research has indicated that there is a strong relationship between patterns of fertility and children's survival risks. Typically, the risk of death in early childhood increases among children born to mothers who are too young or too old, children born after too short a birth interval, and children who are of high birth order. For the purpose of this analysis, a mother is classified as "too young" if she is less than 18 years of age, and "too old" if she is over 34 years at the time of the birth. A "short birth interval" is one in which a birth occurs less than 24 months after a preceding birth; and a child is of "high birth order" if the mother has previously given birth to three or more children (i.e., the child is of birth order four or higher). Table 8.5 shows the percent distribution of births in the five-year period before the survey and the percent distribution of currently married women by category of elevated risk. The table also examines the relative risk of dying for children by comparing the proportion dead in each specified high-risk category with the proportion dead among children not-in-any-high-risk category. First births, although often at increased risk, are in the “not-in-any-high-risk” category in this analysis because they are not considered an avoidable risk. The risk factors examined are of programmatic interest because they are avoidable at little or no cost. Infant and Child Mortality | 129 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 dying and the 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, Eri- trea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Births in the five years Percentage preceding the survey of –––––––––––––––––––– currently Percentage Risk married Risk category of births ratio women1 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Not in any high risk category 25.0 1.00 16.6a Unavoidable risk category First order births between ages 18 and 34 years 14.3 1.32 11.0 Single high-risk category Mother’s age <18 4.9 2.14 2.2 Mother’s age >34 2.0 0.97 4.0 Birth interval <24 months 6.3 1.67 8.4 Birth order >3 21.7 0.95 13.8 Subtotal 34.9 1.25 28.4 Multiple high-risk category Age <18 & birth interval <24 months2 0.4 * 0.2 Age >34 & birth interval <24 months 0.3 * 0.4 Age >34 & birth order >3 16.2 1.43 26.0 Age >34 & birth interval <24 months & birth order >3 3.4 4.10 7.1 Birth interval <24 months & birth order >3 5.6 2.95 10.4 Subtotal 25.9 2.11 44.0 In any avoidable high-risk category 60.8 1.61 72.4 Total 100.0 na 100.0 Number of births 6,156 na 5,733 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 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. An asterisk indicates that the figure is based on fewer than 25 unweighted cases and has been sup- pressed. 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 occurred less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the combined categories age<18 and birth order >3 The first column in Table 8.5 shows the percentage of births occurring in the five years before the survey that fall into various risk categories. Sixty-one percent of births in the five years preceding the survey have elevated mortality risks that are avoidable (35 percent in single high-risk categories and 26 percent in multiple high-risk categories); this is a slight decline from 65 percent in the 1995 EDHS. One- fourth of births were not in any high-risk category and 14 percent are first births to mothers age 18-34, and are considered an unavoidable risk. 130 | Infant and Child Mortality Among single high-risk categories, the highest proportion of births classified as high risk are those of birth order four or higher (22 percent). The single category associated with the highest risk ratio (2.1) is mother’s age under 18, followed by births occurring less than 24 months after a previous sibling (1.7). In the 1995 EDHS, for single high-risk categories, the highest risk ratios were for births that occurred after a short birth interval and births to mothers age 35 and older. Since many births can be classified in more than one high-risk category, it makes sense for programmatic purposes to focus on births in the multiple high-risk categories. Among multiple high-risk categories, the largest proportion of births are fourth—or higher—order births to women 35 and older (16 percent). The category with the highest multiple-risk ratio (4.1) is higher-order births to older women (age 35 or older) with a short birth interval (less than 24 months). This category involves only 3 percent of births. The second highest risk ratio in the multiple high-risk category is for higher-order births after a short birth interval (3.0). This category involves 6 percent of births. The last column of Table 8.5 shows the distribution of currently married women by category of increased risk if they were to conceive at the time of the survey. Although many women are protected from conception due to use of family planning, postpartum insusceptibility, and prolonged abstinence, in this analysis, only those who have been sterilized are included in the not-in-any-high-risk category. The criteria for placing women into specific risk categories have been adjusted to take into account gestation. Overall, only 17 percent of currently married women in Eritrea are not in any high-risk category, while 72 percent have the potential of giving birth to a child at elevated risk of dying. Forty-four percent of married women are in multiple high-risk categories. Maternal and Child Health | 131 MATERNAL AND CHILD HEALTH 9 Women of childbearing age and children under 15 years constitute about 60 percent of the total population in developing countries. Thus, improving the health status of these groups means improving the health status of the majority of people. Many health problems of women are related to labor and delivery and can be prevented with appropriate antenatal, delivery, and postnatal care. Most childhood health problems are also easily preventable. For these reasons, maternal and child health care is one of the highest priorities of the Ministry of Health (MOH). Three-fourths of all MOH health facilities in the country provide mainly preventive services including antenatal and delivery care, immunizations, growth monitoring, health education, and family planning. Therefore, the findings of the 2002 EDHS will be extremely useful to the MOH and other organizations interested in health programs for planning, monitoring, and evaluating maternal and child health care in Eritrea. The first part of this chapter is concerned with maternal health. The 2002 EDHS results are presented on pregnancy care, delivery care, pregnancy complications, and postnatal care for recent births. The Integrated Management of Childhood Illness (IMCI) strategy combines improved management of childhood illness––preventive and curative—with aspects of nutrition. All illnesses that have an impact on child survival in Eritrea are covered in this program. The second part of this chapter focuses on findings on immunization of young children and the prevalence and treatment of three common childhood illnesses, namely, acute respiratory infections, diarrhea, and fever (or malaria). Given the importance of malaria in many parts of Eritrea, current use of mosquito nets by pregnant women, all women 15-49, and children under five is presented in this chapter. The last section of the chapter discusses women’s perception of problems in accessing health care. 9.1 PREGNANCY CARE The 2002 EDHS collected a range of information on the type of care that Eritrean women receive during pregnancy, including components of antenatal care and tetanus toxoid vaccinations. Information on delivery care was collected for all births in the five years before the survey; however, information about antenatal care was restricted to the last birth in that period. Antenatal Care Coverage and Provider Antenatal care (ANC) is provided to enhance healthy motherhood through early detection of risk factors and, when necessary, timely intervention. It is important that health professionals provide antenatal care to all pregnant women. Although interviewers were instructed to record all persons a woman had consulted for care, only the provider with the highest qualifications is considered in Table 9.1. The table indicates that 71 percent of women who had a live birth in the five years before the survey had antenatal care for the most recent birth. Nurses and midwives provide antenatal care to 46 percent of mothers; doctors provide care to 24 percent. Traditional birth attendants (TBA) play a negligible role in the provision of antenatal care (less than 1 percent). Twenty-eight percent of mothers do not receive any antenatal care. Maternal age at birth, birth order, and residence are related to use of antenatal care. Older women have lower antenatal care coverage than younger women, but the differences are small. Differences by birth orders are somewhat larger. The likelihood of receiving antenatal care and having a health 132 | Maternal and Child Health Table 9.1 Antenatal care Percent distribution of women who had a live birth in the five years preceding the survey by antenatal care (ANC) pro- vider during pregnancy for the most recent birth, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Antenatal care provider ––––––––––––––––––––––––––––––––––––––––––––– Nurse/ Traditional midwife/ birth Number Background auxiliary attendant/ of characteristic Doctor midwife other No one Missing Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age at birth <20 26.9 45.4 0.8 26.5 0.4 100.0 510 20-34 24.4 49.2 0.6 25.1 0.7 100.0 2,675 35-49 21.1 39.5 0.4 38.3 0.8 100.0 990 Birth order 1 31.7 45.8 0.6 21.8 0.2 100.0 761 2-3 22.8 52.6 0.5 23.3 0.8 100.0 1,411 4-5 23.8 45.0 0.8 29.7 0.7 100.0 922 6+ 20.2 39.9 0.4 38.6 0.9 100.0 1,081 Residence Total urban 30.8 60.4 0.6 7.7 0.6 100.0 1,448 Asmara 37.3 56.1 0.2 5.7 0.7 100.0 618 Other towns 25.9 63.6 0.8 9.2 0.5 100.0 830 Rural 20.3 39.0 0.5 39.4 0.8 100.0 2,727 Zoba Debubawi Keih Bahri 33.6 34.4 0.2 31.3 0.5 100.0 136 Maekel 35.0 54.1 0.3 9.1 1.5 100.0 801 Semenawi Keih Bahri 25.4 48.7 1.5 23.9 0.5 100.0 560 Anseba 16.7 51.8 0.3 30.3 0.8 100.0 589 Gash-Barka 29.2 34.9 1.2 34.2 0.5 100.0 789 Debub 15.6 46.5 0.0 37.6 0.3 100.0 1,301 Education No education 18.7 41.2 0.8 38.8 0.5 100.0 2,581 Primary 28.6 50.8 0.2 19.1 1.3 100.0 766 Middle 31.5 58.5 0.4 8.7 0.9 100.0 293 Secondary + 38.3 58.5 0.0 2.7 0.5 100.0 534 Wealth index Lowest 20.6 36.9 0.9 41.2 0.4 100.0 744 Second 20.6 37.1 0.4 41.1 0.7 100.0 903 Middle 22.6 38.9 0.4 37.5 0.7 100.0 890 Fourth 22.5 63.1 0.7 12.7 1.0 100.0 795 Highest 34.1 59.3 0.2 6.0 0.5 100.0 697 Total 23.9 46.4 0.5 28.4 0.7 100.0 4,175 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. professional as a provider for antenatal care decreases with increasing birth order. This situation calls for attention and intervention because older women and high-parity women are more vulnerable to high-risk births. Rural woman in Eritrea are five times as likely to receive no antenatal care as urban women. However, the proportion of antenatal care provided by doctors is the same in urban and rural areas; one- third of both urban and rural women who received antenatal care received it from doctors. Zoba Maekel Maternal and Child Health | 133 leads other zobas in antenatal coverage (89 percent), followed by zoba Semenawi Keih Bahri (76 percent). Antenatal coverage is lower in the other zobas and varies from 62 to 69 percent. Antenatal care coverage is strongly associated with education. For example, 61 percent of mothers with no education, compared with 97 percent of the mothers with some secondary education obtain antenatal services. A woman with some secondary or higher education is twice as likely to receive antenatal care from a doctor as a woman without schooling. Antenatal coverage varies by wealth of women’s households. Coverage is around 60 percent in the three lowest quintiles of the wealth index, then rises sharply. However, antenatal care is almost equally likely (21-23 percent) to be provided by doctors for women in all quintiles except the highest quintile; one-third of mothers in the highest quintile received antenatal services from doctors. No direct comparison of antenatal care indicators reported in the 2002 EDHS and 1995 EDHS can be made because the published results of the previous survey are for all births in the three years preceding the survey. To measure the change in antenatal care between the surveys, a special tabulation of 1995 EDHS data was done to obtain the most comparable data. This was done by analyzing the maternal care indicators for the last birth in the three years preceding the survey.1 Overall, antenatal care coverage has increased from 50 percent in 1995 to 71 percent in 2002. The increase in antenatal care has occurred in all subgroups (data not shown). It is encouraging to note that there has been an increase of at least 45 percent in antenatal care coverage in rural areas, in zobas Debubawi Keih Bahri and Semenawi Keih Bahri, and among women with no education. In fact, the overall increase in antenatal care in the country is almost entirely due to a tremendous increase in antenatal care coverage among uneducated women. Number and Timing of Antenatal Visits Health professionals recommend that the first antenatal visit should occur within the first trimester of the pregnancy and continue on a monthly basis through the 28th week of pregnancy and fortnightly up to 36th week or until birth; this means that ideally 12-13 visits should be made during pregnancy. According to safe motherhood protocol, a pregnant woman should have at least one antenatal visit in each trimester, and at least four visits during her pregnancy. It is recommended that pregnant women register in the first trimester for antenatal care. The earlier the first visit and the more frequent the visits, the better the prospects for the pregnancy, because of timely detection of risk factors and appropriate interventions. Data in Table 9.2 indicate that 41 percent of women with a birth in the five years preceding the survey made four or more antenatal care visits for the last birth. Only 22 percent were registered in their first trimester. Urban women (72 percent) are much more likely to make at least four visits than their rural counterparts (24 percent). The median number of months pregnant at first ANC visit is 4.3 for urban women and 5.5 for rural women, indicating that the majority of women in both urban and rural areas had their first ANC visit in the second trimester. However, a higher proportion of urban women than rural women started ANC in the first trimester; a majority of women in Asmara had their first ANC visit during the first trimester. Antenatal Care Content Pregnancy complications are an important cause of maternal and child morbidity and mortality, and thus informing pregnant women about the danger signs associated with pregnancy and the appropriate action that they should take is an essential component of antenatal care. Also, there are routine health 1 The comparison of antenatal care indicators was done for last births in the three years preceding the survey in 1995 and last births in the five years before the survey in 2002. 134 | Maternal and Child Health services (tests and examinations) that should be provided to all pregnant women for identifying risk factors. Table 9.2 Number of antenatal care visits and timing of first visit Percent distribution of women who had a live birth in the five years preceding the survey by number of antenatal care (ANC) visits for the most recent birth, and by the timing of the first visit, according to residence, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence ––––––––––––––––––––––––––––––––– Number and timing Total Other of ANC visits urban Asmara towns Rural Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of ANC visits None 8.3 6.4 9.6 39.9 28.9 1 2.1 1.6 2.5 7.0 5.3 2-3 16.1 8.7 21.6 28.4 24.2 4+ 72.3 82.0 65.0 24.2 40.9 Don't know/missing 1.3 1.3 1.3 0.5 0.8 Total 100.0 100.0 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 8.3 6.4 9.6 39.9 28.9 <4 39.3 54.2 28.1 13.1 22.2 4-5 33.5 30.6 35.7 24.5 27.7 6-7 17.4 7.7 24.6 18.7 18.2 8+ 1.4 1.0 1.6 3.4 2.7 Don't know/missing 0.2 0.0 0.3 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 Median months pregnant at first visit (for those with ANC) 4.3 3.8 5.0 5.5 5.0 Number of women 1,448 618 830 2,727 4,175 As in 1995, all women who had a birth in the five years preceding the survey—whether they had ANC or not—were asked if they received iron tablets and multivitamin tablets during pregnancy. In the 2002 EDHS, women were also asked whether they received antimalarial drugs and vitamin C tablets during pregnancy for births in the five years preceding the survey. Unlike the 1995 EDHS survey, the 2002 EDHS collected information on the components of antenatal care. Women who had antenatal care were asked about the routine screenings they received during any visits to their provider. The women were also asked whether they had been told about the signs of pregnancy complications. In principle, all pregnant women who visit a health facility for antenatal care should be informed about the signs of pregnancy complications and other antenatal care issues so that they can seek appropriate help in time. Table 9.3 shows that among women who had birth in the five years preceding the survey, only 33 percent who received antenatal care for the most recent birth reported that they were informed about pregnancy complications. Older women, urban women, and those with higher education are better informed about pregnancy complications, compared with younger women, rural women, and uneducated women. Women in zobas Semenawi Keih Bahri (22 percent) and Debub (28 percent) were the least informed and those in zoba Maekel (45 percent) were the most informed about the signs of pregnancy complications. Maternal and Child Health | 135 Concerning the routine tests and examinations, 88 percent, 64 percent, and 82 percent of the women who had ANC reported that their weight, height, and blood pressure, respectively, were measured. These results indicate that some providers do not consider height measurement an essential part of the ANC. These routine examinations are more common in urban areas than rural areas and slightly less common for mothers with sixth- or higher-parity births than for mothers with lower-parity births. The three routine measurements are more likely to be part of ANC in zoba Maekel than in other zobas. As a part of ANC in zoba Debub, only four in ten women had their height measured, whereas in other zobas at least six in ten women reported that their height was measured. Women’s education and the provision of these ANC services has a positive correlation, that is, the higher the educational level of a woman, the more likely her weight, height, and blood pressure are measured. Table 9.3 Components of antenatal care Percentage of women with a live birth in the five years preceding the survey who received antenatal care for the most recent birth, by content of antenatal care, and percentage of women with a live birth in the five years preceding the survey who received iron/folic acid tablets, antimalarial drugs, and multivitamins or vitamin C for the most recent birth, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Among women with a birth in the 5 years preceding the survey, Content of antenatal care percentage who received: ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––– Informed of signs of pregnancy Blood Urine Blood Number Anti- Multi- Number Background compli- Weight Height pressure sample sample of Iron malarial vitamins/ of characteristic cations measured measured measured taken taken women tablets drugs vitamin C women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age at birth <20 28.3 87.8 58.7 84.2 42.4 47.8 373 41.1 4.3 30.3 510 20-34 32.4 89.2 66.5 82.3 49.1 51.3 1,983 41.1 4.6 33.2 2,675 35-49 35.6 85.5 60.3 81.0 40.7 44.9 603 34.9 4.3 29.5 990 Birth order 1 35.2 89.8 66.2 84.2 57.2 60.5 594 41.9 3.0 32.1 761 2-3 33.0 89.6 64.9 83.0 46.8 51.1 1,071 41.0 4.1 30.9 1,411 4-5 31.7 89.8 64.5 83.3 45.4 47.1 641 38.7 4.7 32.2 922 6+ 30.2 83.3 61.2 78.5 37.6 39.4 654 37.0 5.9 33.0 1,081 Residence Total urban 40.6 95.6 74.3 89.3 68.9 70.8 1,329 44.6 3.8 35.3 1,448 Asmara 50.5 98.2 88.0 95.3 82.1 85.5 578 41.7 0.6 26.7 618 Other towns 33.0 93.6 63.8 84.7 58.8 59.5 751 46.8 6.2 41.7 830 Rural 26.0 82.3 56.1 76.5 28.3 32.2 1,631 37.0 4.9 30.2 2,727 Zoba Debubawi Keih Bahri 35.3 87.6 63.0 87.6 72.1 73.4 92 35.4 1.8 23.5 136 Maekel 44.9 97.2 84.4 93.4 74.4 77.4 716 43.5 0.6 28.0 801 Semenawi Keih Bahri 22.1 88.0 71.8 80.2 28.4 26.9 423 49.2 1.4 41.8 560 Anseba 30.6 89.3 69.7 77.4 35.7 38.1 405 41.9 2.7 37.3 589 Gash-Barka 32.8 84.6 59.0 76.4 41.1 45.0 515 41.8 14.0 34.9 789 Debub 27.6 82.5 43.2 79.2 37.5 42.6 808 31.3 3.6 26.8 1,301 Education No education 28.2 82.8 58.6 75.5 32.5 34.8 1,567 36.9 5.2 31.6 2,581 Primary 31.7 91.7 61.5 85.7 48.6 53.9 610 41.1 5.5 32.0 766 Middle 28.8 96.2 70.1 88.1 57.8 64.9 265 48.8 2.7 39.7 293 Secondary + 48.7 97.0 81.5 95.6 80.9 81.0 517 45.6 0.7 29.5 534 Total 32.6 88.3 64.3 82.3 46.6 49.5 2,960 39.6 4.5 32.0 4,175 136 | Maternal and Child Health The results in Table 9.3 indicate that blood and urine tests are not a routine part of ANC. Slightly less than 50 percent of pregnant women report giving blood and urine samples as a part of their ANC. The likelihood of these laboratory tests being performed decreases with increasing birth order and increases with mother’s education. Urban women are more than twice as likely to give blood and urine samples for testing as their rural counterparts. Zoba Semenawi Keih Bahri has the most limited ANC in this respect. In Eritrea, iron and multivitamin supplements and intermittent treatment against malaria are provided to pregnant women by health facilities only when considered necessary. Iron tablets are given to those pregnant women found to be anemic. Since the EDHS data show that blood samples were taken from only half of mothers during pregnancy, some women who needed iron supplementation may have been missed. The data show that 40 percent of pregnant mothers received iron supplementation, 32 percent received multivitamin supplementation, and 5 percent received antimalaria treatment. Iron supplementation is related to residence, age, birth order, and education. Urban mothers are more likely to receive iron supplements than rural mothers. For low-parity births, births to younger women, and births to educated women, mothers are somewhat more likely to receive iron supplements during pregnancy. Multivitamin supplementation does not follow this pattern, except that coverage is higher in urban areas (35 percent) than in rural areas (30 percent). The differences in antimalarial treatment by background characteristics are small. Women with higher-order births and lower levels of education are slightly more likely to receive antimalarial treatments. For example, 5 to 6 percent of women with six or more births and women with some primary education or no education received antimalaria treatment compared with 3 percent of women with first births, and less than 1 percent of women with some secondary or higher education. Women in zoba Gash- Barka (14 percent) are most likely to receive antimalarial treatment during pregnancy. Tetanus Toxoid Immunization Tetanus toxoid vaccine (TT) is provided to pregnant and nonpregnant women of childbearing age in Eritrea to prevent tetanus in newborns and women during delivery in unhygienic environments. For a minimum protection against tetanus, a pregnant woman should have at least two doses of TT. Table 9.4 shows that for the last birth in the five years before the survey, half of mothers received at least one tetanus toxoid injection. The corresponding figure from the 1995 EDHS is 35 percent (special tabulation), indicating an increase of almost 50 percent. In 2002, 35 percent of women had at least two doses of TT while 49 percent had none. Age, birth order, residence, education, and household wealth are related to TT immunization coverage. TT coverage (for two doses) decreases with increasing age of mother and birth order. For example, 44 percent of women under 20 years had two or more TT injections, compared with 29 percent of women age 35 and older. Coverage is higher among women in Asmara and other towns (44 percent each) than among women in rural areas (30 percent), and higher among women in the highest quintile of the wealth index (44 percent) than women in the lowest quintile (28 percent). Although zoba Debubawi Keih Bahri has the lowest antenatal care coverage, it has the highest TT coverage (50 percent) among zobas. On the other hand, zoba Debub has the lowest coverage (29 percent). 9.2 DELIVERY CARE The objective of providing safe delivery services is to protect the life and health of the mother and her child. An important component of efforts to reduce the health risk to mothers and children is to increase the proportion of babies delivered under the supervision of health professionals. Proper medical attention under hygienic conditions during delivery can reduce the risk of complications and infections that may cause death or serious illness either to the mother or the baby, or both. To assess delivery care in Maternal and Child Health | 137 Eritrea, place of delivery, assistance at delivery, and delivery characteristics for births in the five years preceding the survey are presented in Tables 9.5, 9.6, and 9.7. Place of Delivery Although 70 percent (Table 9.1) of pregnant women in Eritrea receive antenatal care, only 26 percent deliver in health facilities, compared with 73 percent who deliver at home. Almost all deliveries in health facilities are in public sector facilities; the private sector plays a negligible role in delivery Table 9.4 Tetanus toxoid injections Percent distribution of women who had a live birth in the five years preceding the survey by number of tetanus toxoid injections received during pregnancy for the most recent birth, ac- cording to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of injections ––––––––––––––––––––––––––––––––––– Two Don’t Number Background One or more know/ of characteristic None injection injections missing Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age at birth <20 40.1 13.8 44.4 1.7 100.0 510 20-34 47.8 15.9 35.0 1.3 100.0 2,675 35-49 54.7 15.8 28.5 1.0 100.0 990 Birth order 1 36.0 15.4 47.2 1.4 100.0 761 2-3 45.1 15.8 37.5 1.6 100.0 1,411 4-5 52.6 18.1 28.2 1.1 100.0 922 6+ 58.1 13.4 27.4 1.0 100.0 1,081 Residence Total urban 33.2 20.7 43.8 2.4 100.0 1,448 Asmara 35.0 17.1 43.7 4.2 100.0 618 Other towns 31.8 23.4 43.8 1.0 100.0 830 Rural 56.6 12.9 29.7 0.7 100.0 2,727 Zoba Debubawi Keih Bahri 35.0 13.5 50.0 1.5 100.0 136 Maekel 39.6 15.4 40.7 4.3 100.0 801 Semenawi Keih Bahri 43.3 19.0 37.1 0.7 100.0 560 Anseba 49.5 15.3 34.6 0.6 100.0 589 Gash-Barka 52.2 14.4 32.7 0.7 100.0 789 Debub 54.9 15.4 29.3 0.4 100.0 1,301 Education No education 55.8 14.0 29.4 0.8 100.0 2,581 Primary 44.4 17.5 37.0 1.1 100.0 766 Middle 30.7 16.6 49.9 2.8 100.0 293 Secondary + 28.9 19.9 47.9 3.3 100.0 534 Wealth index Lowest 60.2 11.2 28.2 0.4 100.0 744 Second 57.4 12.9 28.8 0.8 100.0 903 Middle 52.2 14.4 32.8 0.6 100.0 890 Fourth 39.3 19.8 40.0 1.0 100.0 795 Highest 32.8 20.4 43.8 3.1 100.0 697 Total 48.5 15.6 34.6 1.3 100.0 4,175 138 | Maternal and Child Health services (less than 1 percent). The likelihood of delivery in a health facility decreases with increasing birth order. Forty-two percent of first births are delivered in a health facility, compared with only 15 percent of sixth- and higher-order births. There are marked variations between urban and rural areas in the proportion of births delivered in health facilities. Less than one in ten births in rural areas, slightly less than half in other towns, and more than eight in ten in Asmara are delivered in health facilities. Differentials by zoba are striking; only 9 percent of births in Gash-Barka are delivered in health facilities, compared with 67 percent in Maekel and 42 percent in Debubawi Keih Bahri. Wealth and educational background influence where a woman delivers. The higher the educational level of the woman and the higher the level of household wealth, the more likely she is to deliver in a health facility. As expected, women who receive antenatal care are more likely to deliver in a health facility. The percentage of births delivered in health facilities has increased from 17 percent in 1995 to 26 percent in 2002. The increase is notable in all subgroups shown in Table 9.5. Delivery Assistance As mentioned above, 73 percent of births in Eritrea occur at home and therefore a majority are likely to be assisted by non-medical persons. Table 9.6 indicates that 43 percent of births are attended by traditional birth attendants (TBA) and 27 percent by relatives or friends. Twenty-eight percent of births are assisted by health professionals, mostly nurses and midwives. As age of mother and birth order increase, births are less likely to occur under the supervision of a health professional. For example, health professionals attend 43 percent of first births and only 17 percent of deliveries for sixth- or higher-order births. Residence, education, and household wealth also influence the provision of delivery care by health professionals. The differentials by background characteristics for delivery assistance show the same pattern as the differentials for delivery in a health facility. The proportion of births attended by health professionals has increased from 21 percent in 1995 to 28 percent in 2002. Caesarean Section and Size at Birth Caesarean sections (C-sections) are generally performed because the mother has medical problems or complications at the time of delivery. Table 9.7 shows that 3 percent of births in the five years preceding the survey were by caesarean section, a slight increase from 1995. Generally, a C-section rate below 5 percent is thought to be a reflection of limited access to maternal health services (FCI, 1998). Therefore, these findings suggest that many Eritrean women do not have access to life-saving emergency obstetrical care. C-sections are less common among rural women, women with a large number of children, women with no education, and those in the lower quintiles of the wealth index. Deliveries by C-section are less than 2 percent in all zobas except zoba Maekel (9 percent). Birth weight is closely related to infant and child health and mortality. Two and half kilograms is consider normal birth weight, and babies weighing less than that are regarded as having low birth weight. In the 2002 EDHS, for all births during the five years preceding the survey, mothers were asked whether their baby had been weighed at birth, and if so, how much the baby weighed. In addition, because most women do not deliver in a health facility, the mothers were asked for their subjective assessment of whether the child was very large, larger than average, average, smaller than average, or very small at birth. Birth weight was reported for slightly more than one-fourth (27 percent) of births (Table 9.7). Among these births, 8 percent (2 percent of all births) were classified as low birth weight; i.e., the infant weighed less than 2.5 kg at birth. The proportion of births classified as low birth weight in 1995 was Maternal and Child Health | 139 Table 9.5 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Health facility –––––––––––––––– Don’t Number Background Public Private know/ of characteristic sector sector Home Other missing Total births ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mother's age at birth < 20 27.9 0.4 70.4 0.3 0.9 100.0 773 20-34 27.5 0.2 71.5 0.2 0.6 100.0 4,035 35-49 20.6 0.4 78.2 0.4 0.4 100.0 1,347 Birth order 1 41.1 0.4 57.9 0.0 0.6 100.0 1,160 2-3 29.5 0.3 69.2 0.2 0.8 100.0 2,111 4-5 21.0 0.3 78.2 0.2 0.4 100.0 1,350 6+ 14.4 0.2 84.3 0.6 0.6 100.0 1,533 Residence Total urban 61.5 0.2 37.4 0.0 0.9 100.0 2,030 Asmara 82.9 0.4 15.6 0.0 1.0 100.0 844 Other towns 46.2 0.1 52.9 0.0 0.8 100.0 1,186 Rural 8.6 0.3 90.2 0.4 0.5 100.0 4,125 Zoba Debubawi Keih Bahri 41.5 0.5 57.4 0.0 0.7 100.0 195 Maekel 66.8 0.4 31.2 0.0 1.6 100.0 1,118 Semenawi Keih Bahri 19.2 0.1 80.5 0.0 0.3 100.0 845 Anseba 14.0 0.6 85.2 0.0 0.2 100.0 911 Gash-Barka 9.0 0.0 90.0 0.4 0.7 100.0 1,136 Debub 19.7 0.3 79.2 0.5 0.3 100.0 1,950 Mother’s education No education 10.2 0.2 88.8 0.3 0.5 100.0 3,909 Primary 32.9 0.3 65.7 0.1 1.0 100.0 1,118 Middle 54.1 0.4 44.9 0.0 0.7 100.0 399 Secondary + 85.5 0.3 13.6 0.0 0.5 100.0 729 Antenatal care visits1 None 6.9 0.1 91.2 0.4 1.4 100.0 1,207 1-3 14.7 0.2 85.0 0.1 0.1 100.0 1,230 4+ 53.4 0.4 46.2 0.0 0.0 100.0 1,705 Wealth index Lowest 5.1 0.3 94.0 0.1 0.5 100.0 1,107 Second 8.3 0.4 90.5 0.1 0.6 100.0 1,389 Middle 10.6 0.1 88.6 0.4 0.4 100.0 1,336 Fourth 40.6 0.1 57.9 0.6 0.9 100.0 1,163 Highest 78.7 0.5 20.3 0.0 0.5 100.0 959 Total 26.1 0.3 72.8 0.2 0.6 100.0 6,156 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 32 women with missing information on antenatal care visits, who are not shown separately. 1 Includes only the most recent birth in the five years preceding the survey 140 | Maternal and Child Health Table 9.6 Assistance during delivery Percent distribution of live births in the five years preceding the survey by person providing assistance during delivery, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Nurse/ midwife/ Traditional Don't Number Background auxiliary birth Relative/ know/ of characteristic Doctor midwife attendant other No one missing Total births ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mother's age at birth < 20 10.6 19.4 41.2 27.7 0.6 0.5 100.0 773 20-34 7.6 22.2 42.9 26.4 0.3 0.7 100.0 4,035 35-49 7.1 15.7 45.5 30.4 0.7 0.6 100.0 1,347 Birth order 1 15.3 27.9 33.6 22.6 0.2 0.4 100.0 1,160 2-3 8.8 23.2 40.8 26.1 0.3 0.8 100.0 2,111 4-5 4.5 18.3 47.3 29.2 0.3 0.4 100.0 1,350 6+ 4.0 12.8 50.4 31.4 0.7 0.8 100.0 1,533 Residence Total urban 17.1 47.6 24.5 9.6 0.4 0.9 100.0 2,030 Asmara 24.0 62.7 10.2 2.2 0.2 0.7 100.0 844 Other towns 12.1 36.8 34.7 14.9 0.4 1.0 100.0 1,186 Rural 3.3 7.1 52.5 36.2 0.4 0.5 100.0 4,125 Zoba Debubawi Keih Bahri 16.4 25.5 38.2 19.0 0.2 0.7 100.0 195 Maekel 19.9 52.1 24.3 2.2 0.2 1.4 100.0 1,118 Semenawi Keih Bahri 5.3 17.1 51.7 25.5 0.1 0.2 100.0 845 Anseba 5.0 10.4 59.3 25.0 0.0 0.3 100.0 911 Gash-Barka 4.2 6.8 56.5 31.5 0.0 0.9 100.0 1,136 Debub 4.7 15.8 35.8 42.3 1.1 0.3 100.0 1,950 Mother’s education No education 3.5 8.5 52.5 34.8 0.3 0.5 100.0 3,909 Primary 9.7 25.9 39.7 22.7 1.0 1.0 100.0 1,118 Middle 18.0 41.2 25.4 14.7 0.0 0.7 100.0 399 Secondary + 23.1 64.8 9.2 2.4 0.0 0.5 100.0 729 Wealth index Lowest 1.5 5.2 57.9 34.9 0.1 0.5 100.0 1,107 Second 4.3 5.4 53.4 35.7 0.3 0.8 100.0 1,389 Middle 4.0 8.9 49.4 36.7 0.6 0.4 100.0 1,336 Fourth 11.2 32.7 36.8 18.5 0.1 0.7 100.0 1,163 Highest 21.5 59.5 12.1 5.7 0.7 0.5 100.0 959 Total 2002 7.9 20.4 43.3 27.4 0.4 0.6 100.0 6,156 Total 1995 7.9 12.7 53.8 23.7 1.7 0.2 100.0 2,580 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: If the respondent mentioned more than one person assisting during delivery, only the most qualified person is considered in this tabulation. 14 percent (2 percent of all births), implying a decline in low birth weight babies. However, the results should be interpreted with caution because only a small proportion of births were weighed (27 percent in 2002 and 14 percent in 1995). Table 9.7 presents information on mothers’ assessment of their baby’s size at birth. It is important to remember that these assessments may vary among respondents because they are based on the mother’s Maternal and Child Health | 141 Table 9.7 Delivery characteristics Percentage of live births in the five years preceding the survey delivered by caesarean section, and percent distribution by birth weight and by mother's estimate of baby's size at birth, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Birth weight Size of child at birth Delivery –––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––– by Less Don’t Smaller Average Don't Number Background caesarean Not than 2.5 kg know/ Very than or know/ of characteristic section weighed 2.5 kg or more missing Total small average larger missing Total births ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mother's age at birth < 20 3.9 69.7 3.9 22.7 3.7 100.0 22.1 10.1 67.0 0.9 100.0 773 20-34 2.6 68.2 2.1 27.1 2.5 100.0 15.8 8.8 73.1 2.3 100.0 4,035 35-49 2.3 75.9 1.5 20.2 2.4 100.0 17.4 10.2 70.9 1.5 100.0 1,347 Birth order 1 6.4 57.3 4.4 36.1 2.2 100.0 20.4 9.1 69.1 1.3 100.0 1,160 2-3 2.8 65.9 2.5 28.7 2.9 100.0 15.7 9.0 72.8 2.5 100.0 2,111 4-5 1.7 74.5 1.5 22.0 2.0 100.0 14.8 9.8 73.7 1.7 100.0 1,350 6+ 0.7 81.6 0.8 14.3 3.3 100.0 17.9 9.4 71.1 1.7 100.0 1,533 Residence Total urban 7.0 31.3 5.3 60.1 3.3 100.0 11.7 7.1 79.6 1.6 100.0 2,030 Asmara 11.3 8.8 8.9 80.4 2.0 100.0 9.0 5.0 84.7 1.3 100.0 844 Other towns 4.0 47.3 2.8 45.7 4.2 100.0 13.5 8.7 76.0 1.8 100.0 1,186 Rural 0.6 89.2 0.7 7.8 2.4 100.0 19.5 10.3 68.1 2.1 100.0 4,125 Zoba Debubawi Keih Bahri 1.9 57.0 3.5 33.9 5.6 100.0 47.2 8.4 42.3 2.1 100.0 195 Maekel 8.9 21.2 7.4 68.4 2.9 100.0 9.5 5.2 83.1 2.2 100.0 1,118 Semenawi Keih Bahri 1.4 77.8 1.9 15.1 5.2 100.0 19.4 12.6 63.4 4.6 100.0 845 Anseba 1.4 84.3 1.1 13.0 1.6 100.0 20.0 9.6 70.0 0.4 100.0 911 Gash-Barka 0.5 85.9 0.7 11.6 1.8 100.0 18.3 10.4 70.2 1.2 100.0 1,136 Debub 1.8 80.2 0.7 17.1 2.1 100.0 14.8 9.5 74.0 1.7 100.0 1,950 Mother’s education No education 0.8 86.6 0.9 9.6 2.8 100.0 19.9 10.7 67.4 2.0 100.0 3,909 Primary 3.0 61.6 3.1 32.4 2.9 100.0 12.4 7.7 77.9 2.0 100.0 1,118 Middle 1.8 40.8 7.3 49.5 2.4 100.0 13.7 7.8 76.9 1.6 100.0 399 Secondary + 13.1 10.3 4.9 83.3 1.5 100.0 9.6 5.1 83.6 1.6 100.0 729 Wealth index Lowest 0.3 92.8 0.7 4.1 2.4 100.0 23.3 9.9 64.7 2.1 100.0 1,107 Second 0.8 89.6 0.6 6.7 3.1 100.0 18.4 12.5 66.6 2.4 100.0 1,389 Middle 0.7 85.7 0.6 11.2 2.6 100.0 18.0 9.3 71.2 1.5 100.0 1,336 Fourth 3.6 51.3 3.9 41.6 3.2 100.0 12.8 8.3 76.9 2.0 100.0 1,163 Highest 9.2 18.1 5.9 74.1 1.9 100.0 10.4 5.3 83.0 1.3 100.0 959 Total 2.7 70.1 2.2 25.0 2.7 100.0 16.9 9.3 71.9 1.9 100.0 6,156 own perception of the size of her baby and not on a uniform definition. Twenty-six percent of mothers reported that their child was either smaller than average or very small (9 percent and 17 percent, respectively), compared with 27 percent estimated from the 1995 EDHS. Zoba Debubawi Keih Bahri has the highest proportion of children reported as very small or smaller than average at birth (56 percent). In addition, first-born children, and children of young mothers, rural mothers, uneducated mothers, and mothers in the lowest quintile of the wealth index are more likely than other births to be reported as smaller than average or very small at birth. 142 | Maternal and Child Health 9.3 POSTNATAL CARE Proper care after delivery is important for mothers, particularly in the case of births that occur at home; therefore, postnatal care is a vital component of maternal and child health care services. For noninstitutional births particularly, postnatal care enables detection of complications that may threaten the survival of the mother. In the 2002 EDHS, to assess the extent of postnatal care utilization, women whose last birth was delivered outside a health facility were asked whether they received a postpartum checkup from a health professional or a traditional birth attendant. Table 9.8 shows the percent distribution of women whose last birth in the five years preceding the survey occurred outside a health facility by timing of postnatal care. The data indicate that postnatal care is rare in Eritrea. More than nine in ten women (92 percent) with noninstitutional births do not receive any checkup. Only 2 percent of such mothers in the 2002 EDHS received postnatal care in the first two days after delivery, and 5 percent 7 to 41 days after delivery. The highest proportion of women who received postnatal care within two days after birth is 7 percent among women in Asmara and those who have at least some secondary education. It is surprising that postnatal care is so uncommon when 43 percent of children age 12-23 months receive polio vaccine at birth (Table 9.12) and 43 percent of births are attended by traditional birth attendants (Table 9.6). These findings indicate that little attention has been given to postnatal care as a component of maternal and child health care. 9.4 REPRODUCTIVE HEALTH CARE BY WOMEN’S STATUS Table 9.9 shows whether a woman’s use of reproductive health services varies according to her level of empowerment, as measured by two women’s status indicators: participation in household decisionmaking and attitude toward wife beating. The more say a woman has in decisionmaking, the more likely she is to have control over her reproductive health care. On the other hand, reproductive health care coverage is likely to vary negatively relative to the number of reasons she believes wife beating is justified. Table 9.9 indicates that the number of household decisions in which a woman participates has a positive influence on her likelihood of receiving antenatal, delivery, and postnatal care. For example, three-fourths of women who participate in making five or six decisions received antenatal care from health professionals, compared with 53 percent of women who are not involved in any decisionmaking. One-third of women who participate in five or six decisions utilized postnatal care2 in the first two days after delivery, compared with one-fourth of women who had no say in any decisionmaking. Similarly, women who believe a husband is not justified in beating his wife for any reason are more likely to receive antenatal, delivery, and postnatal care than women who believe there are reasons that justify wife beating. For example, 78 percent of women who are against wife beating for any reason received antenatal care, compared with 60 percent of women who believe that wife beating is justified for five reasons. 2 Mothers who delivered in a health facility are assumed to have received a postnatal checkup. Maternal and Child Health | 143 Table 9.8 Postnatal care by background characteristics Percent distribution of women whose last live birth in the five years preceding the survey occurred outside a health facility by timing of postnatal care, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Timing of first postnatal checkup ––––––––––––––––––––––––––––––––––– Within Did not 2 days 3-6 days 7-41 days Don't receive Number Background of after after know/ postnatal of characteristic delivery delivery delivery missing checkup1 Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Mother's age at birth <20 1.4 2.2 4.7 0.0 91.7 100.0 351 20-34 2.1 1.1 4.8 0.1 92.0 100.0 1,872 35-49 1.5 1.3 4.3 0.6 92.3 100.0 761 Birth order 1 1.7 1.6 5.8 0.1 90.8 100.0 424 2-3 2.0 1.2 4.7 0.1 92.0 100.0 947 4-5 2.6 1.5 6.0 0.1 89.8 100.0 703 6+ 1.2 0.9 3.1 0.5 94.3 100.0 910 Residence Total urban 3.1 2.5 5.5 0.1 88.8 100.0 513 Asmara 6.5 0.0 7.0 0.0 86.5 100.0 84 Other towns 2.5 3.0 5.2 0.2 89.2 100.0 429 Rural 1.6 1.0 4.5 0.2 92.7 100.0 2,471 Zoba Debubawi Keih Bahri 3.2 2.6 7.4 0.7 86.1 100.0 72 Maekel 4.2 1.1 6.9 0.5 87.3 100.0 236 Semenawi Keih Bahri 1.3 2.1 4.8 0.4 91.3 100.0 437 Anseba 1.1 1.1 3.4 0.0 94.4 100.0 495 Gash-Barka 2.3 1.5 7.0 0.2 89.0 100.0 704 Debub 1.5 0.7 2.9 0.2 94.7 100.0 1,038 Education No education 1.5 1.0 4.4 0.3 92.9 100.0 2,278 Primary 2.5 1.8 5.6 0.1 89.9 100.0 502 Middle 2.6 4.1 5.4 0.0 87.9 100.0 126 Secondary + 7.1 1.4 5.6 0.0 85.9 100.0 77 Total 1.9 1.2 4.7 0.2 92.0 100.0 2,984 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes women who received the first postnatal checkup after 41 days 144 | Maternal and Child Health Table 9.9 Reproductive health care by women’s status Percentage of women with a live birth in the five years preceding the survey who received antenatal and postnatal care from a health professional for the most recent birth, and percentage of births in the five years preceding the survey for which mothers received professional delivery care, by women's status indicators, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of Percentage women with received Percentage antenatal postnatal care of births care from within the Number assisted by Number a health first two days of a health of Women’s status indicator professional1 of delivery2 women professional1 births –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of decisions in which woman has final say3 0 53.4 26.2 120 19.6 189 1-2 65.1 23.2 820 21.1 1,201 3-4 69.1 25.8 1,061 24.4 1,596 5-6 73.9 34.6 2,174 33.5 3,170 Number of reasons wife beating is justified 0 77.7 39.9 1,109 39.3 1,610 1-2 75.6 36.0 988 34.3 1,433 3-4 66.2 22.6 1,250 20.5 1,865 5 60.4 20.0 827 18.8 1,247 Total 70.4 29.9 4,175 28.3 6,156 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Doctor, nurse or midwife 2 Include mothers who delivered in a health facility; mothers who delivered in a health facility are as- sumed to have received postnatal care. 3 Herself or jointly with others 9.5 USE OF MOSQUITO NETS BY WOMEN Malaria, which is transmitted by mosquitoes, is an endemic problem in Eritrea and is one of the leading causes of outpatient and inpatient morbidity. According to the National Malaria Control Program of the Ministry of Health, about 70 percent of Eritrean people live in malaria endemic areas. The World Health Organization reported that 3,000 children in Africa die from malaria every day because of lack of access to health care, life-saving drugs, and treated mosquito nets (WHO/UNICEF, 2003). Children under five and pregnant women are more vulnerable to malaria. The report indicates that malaria causes one in four deaths among children in Africa. During pregnancy the risk of malaria increases four times and the risk of death from malaria doubles. It is important therefore that women and children use mosquito nets to reduce the risk of illness and death. The Ministry of Health is distributing insecticide-treated nets (ITNs) to all residents in malaria risk areas free of charge (MOH/CDC, 2002). Every household in these areas should get at least two ITNs. In the 2002 EDHS, all women age 15-49 were asked if they slept under a mosquito net the night before the interview. If they did, they were asked how long ago they bought the net and when the net was last treated. Mosquito nets that had been bought or treated in the six months before the interview were Maternal and Child Health | 145 assumed to be ITNs. Table 9.10 shows that 7 percent of all women as well as pregnant women slept under a mosquito net the night before the interview, however, only 3 percent slept under an ITN, indicating that most pregnant women are exposed to malaria risk that can easily be prevented by using ITNs. The results show that pregnant women in urban areas (5 percent), those with at least some secondary education (5 percent), and those who are in the highest quintile of the wealth index (6 percent) are more likely to use ITNs than other pregnant women. By zoba, use of ITNs by pregnant women is highest in zoba Anseba (5 percent) and lowest in zobas Maekel and Gash-Barka (1 percent). For all women, use of mosquito nets and ITNs is highest in zobas Semenawi Keih Bahri, Anseba and Debub. Table 9.10 Use of mosquito nets by all women and pregnant women Percentage of all women and pregnant women age 15-49 who slept under a mosquito net (treated or untreated) and an insecticide treated net (ITN) the night before the interview, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– All women Pregnant women –––––––––––––––––––––––––– ––––––––––––––––––––––––––– Slept Slept under a Slept under a Slept Number Background mosquito under Number mosquito under of pregnant characteristic net1 an ITN2 of women net an ITN2 women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 5.4 2.3 3,767 8.7 4.5 265 Asmara 1.3 0.4 1,899 0.0 0.0 113 Other towns 9.6 4.2 1,868 15.1 7.8 152 Rural 7.4 3.0 4,987 5.5 2.1 508 Zoba Debubawi Keih Bahri 4.6 1.7 324 6.1 2.5 29 Maekel 1.5 0.5 2,264 0.6 0.6 161 Semenawi Keih Bahri 12.3 5.7 1,148 11.3 3.9 103 Anseba 8.5 2.7 1,130 11.8 5.4 1000 Gash-Barka 4.8 2.0 1,500 1.6 1.2 152 Debub 8.9 3.8 2,388 9.8 4.2 227 Education No education 8.0 3.0 4,384 6.5 2.3 462 Primary 7.1 2.9 1,637 8.9 3.8 149 Middle 5.4 2.8 974 (1.4) (1.4) 54 Secondary + 2.8 1.4 1,760 6.3 5.0 108 Wealth index Lowest 7.8 3.1 1,344 7.4 3.4 140 Second 8.1 2.9 1,626 5.5 2.3 164 Middle 7.3 3.1 1,659 5.2 0.8 185 Fourth 6.7 3.2 1,806 8.7 3.8 119 Highest 3.5 1.3 1,978 7.0 5.5 132 Total 6.5 2.7 8,754 6.6 2.9 772 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes ITNs 2 Mosquito net either bought or treated with insecticide during the six months preceding the interview 146 | Maternal and Child Health 9.6 CHILDHOOD VACCINATION Although currently, no community-based data are available on the prevalence of vaccine preventable diseases in Eritrea, experience and health facility reports of the Ministry of Health (MOH), indicate that vaccine preventable diseases account for a substantial number of deaths among young children. Among vaccine preventable diseases, measles is responsible for the highest number of cases and childhood deaths. Universal immunization is one of the main strategies to reduce infant and child mortality. The MOH in Eritrea vaccinates children against six vaccine preventable diseases—tuberculosis, diphtheria, whooping cough, tetanus, polio, and measles. In January 2002, a new vaccine against another important disease, hepatitis B, was added to the routine Expanded Program on Immunization (EPI) vaccines but was too new to be included in the 2002 EDHS questionnaire. Data on immunizations collected in the 2002 EDHS are useful for monitoring and evaluating the current immunization program and for assisting in future program planning. The Eritrean EPI generally follows the WHO guidelines for vaccinating children. BCG is given at birth or first clinic contact. DPT and polio vaccines require three vaccinations at approximately 6, 10, and 14 weeks of age; measles vaccine is given at nine months of age. A first dose of polio—Polio 0—should be given at or around birth. A child is considered to be fully vaccinated if the child has received a dose of BCG vaccine (against tuberculosis), three doses of DPT (to prevent diphtheria, pertussis, and tetanus); three doses of polio vaccine (excluding Polio 0); and a measles vaccination. In the 2002 EDHS, information on childhood immunizations was obtained for children under five from interviewed mothers in two ways. When a vaccination card was available, this served as the source of information. The dates of vaccination were copied from the card to the questionnaire. The mother was asked also to recall which vaccines the child received if there was no vaccination card or if the vaccination was not recorded on the card. Mothers were also asked the number of doses of DPT and polio vaccine the children received. Table 9.11 shows information on vaccination coverage according to the source of the information, that is, the child’s vaccination card or the mother’s report. The table is restricted to children 12-23 months of age in order to focus on recent coverage levels. It should be noted that vaccination data are subject to memory bias when mothers cannot show their children’s vaccination cards. Vaccination cards were available for 77 percent of children. For the rest of the children, vaccination information was based on mothers’ reports. Overall, 76 percent of children age 12-23 months are fully immunized, while 5 percent have not received any vaccinations at all (third row in the table). This is a substantial improvement since 1995 when only 41 percent of children were fully vaccinated and 38 percent had no vaccinations. Polio 0 vaccine, a vaccine given at or around the time of birth, was given to 43 percent of children age 12-23 months. The proportion receiving Polio 0 is higher than the percentage of children who were delivered at health facilities (26 percent), indicating that some children may have received Polio 0 vaccine at their first contact with a health worker. Coverage for BCG and the first doses of polio and DPT vaccines is over 90 percent; coverage for measles is also high (84 percent). Although DPT and polio vaccines are given at the same time, a slightly higher percentage of children received the polio vaccine. This is no doubt attributable to the national immunization day campaigns against polio. Vaccine coverage declines slightly for subsequent doses of polio and DPT, with 83 percent of children 12-23 months receiving three doses of these vaccines. Maternal and Child Health | 147 One way to measure the success of the immunization program is to calculate the dropout rates for polio and DPT. The dropout rate is the proportion of children who received the first dose but did not receive the third dose of a specific vaccine. The dropout rate for both vaccines is about 10 percent. Vaccinations are most effective if given at the proper age. It is recommended that all children receive a complete schedule of vaccinations by their first birthday. Table 9.11 also shows the percentage of children age 12-23 months vaccinated by 12 months of age: BCG (89 percent), measles (76 percent), and the third dose of DPT (79 percent). These levels of coverage are only slightly lower than those for children age 12-23 months vaccinated at any time before the survey. The largest difference between the two groups is for measles (9 percent). Comparison of results of the 2002 EDHS and the 1995 EDHS in Figure 9.1 shows that there has been substantial improvement in coverage for all vaccines. Table 9.11 Vaccinations by source of information Percentage of children 12-23 months who had received specific vaccines at any time before the survey, by source of information (vaccination card or mother's report), and percentage vaccinated by 12 months of age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of children who had received: –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– DPT Polio1 Number ––––––––––––––– ––––––––––––––––––––––– of Source of information BCG 1 2 3 0 1 2 3 Measles All2 None children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Vaccinated any time before the survey Vaccination card 76.3 76.3 74.2 72.1 36.1 76.3 74.7 72.5 70.8 68.2 0.0 736 Mother's report 15.0 14.3 13.4 10.7 6.5 17.6 15.6 10.8 13.3 7.7 5.2 223 Either source 91.4 90.6 87.6 82.8 42.6 93.9 90.3 83.3 84.2 75.9 5.2 959 Vaccinated by 12 months of age3 89.3 88.2 84.7 79.1 42.2 91.4 87.1 79.3 75.5 69.2 7.9 959 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) 3 For children whose information was based on the mother's report, the proportion of vaccinations given during the first year of life was assumed to be the same as for children with a written record of vaccination. EDHS 2002 Figure 9.1 Percentage of Children Age 12-23 Months Who Have Received Specific Vaccinations, 1995 EDHS and 2002 EDHS Note: Based on vaccination card and mother’s report 61 49 48 51 41 38 91 83 83 84 76 5 BCG DPT3 Polio 3 Measles All None 0 20 40 60 80 100 1995 EDHS 2002 EDHS EDHS 1995 and EDHS 2002 148 | Maternal and Child Health Vaccination Coverage by Background Characteristics Table 9.12 presents vaccination coverage among children 12-23 months by background characteristics. The differentials are discussed in terms of children fully vaccinated because the coverage Table 9.12 Vaccinations by background characteristics Percentage of children 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, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of children who received: –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percent- DPT Polio1 age with Number Background ––––––––––––––––– ––––––––––––––––––––––– vaccina- of characteristic BCG 1 2 3 0 1 2 3 Measles All2 None tion card children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Sex Male 90.1 88.7 86.3 81.6 40.5 92.7 89.7 84.0 83.8 76.0 6.0 75.8 519 Female 92.9 92.8 89.1 84.2 45.1 95.3 91.0 82.4 84.6 75.9 4.3 77.9 439 Birth order 1 96.0 94.9 91.7 88.9 50.3 96.4 93.0 86.6 88.7 79.5 2.7 77.9 206 2-3 92.6 91.9 88.9 85.2 50.3 93.2 91.0 86.6 86.3 79.5 4.9 80.9 332 4-5 91.8 91.0 90.0 82.3 38.3 94.6 90.0 81.9 83.7 76.6 5.4 76.0 216 6+ 84.3 83.7 78.9 73.4 27.1 91.8 86.8 76.1 76.8 65.9 8.1 69.6 205 Residence Total urban 97.6 96.7 96.1 93.5 74.0 97.1 96.0 91.3 93.8 88.4 1.8 82.7 355 Asmara 98.7 98.1 98.1 95.4 95.4 97.5 97.5 91.1 96.1 89.2 1.3 80.2 175 Other towns 96.6 95.3 94.1 91.6 53.0 96.8 94.5 91.4 91.7 87.6 2.3 85.2 180 Rural 87.7 87.0 82.6 76.5 24.2 92.0 86.9 78.6 78.5 68.6 7.2 73.2 604 Zoba Debubawi Keih Bahri 90.8 88.5 81.1 76.5 59.5 93.5 85.2 75.6 70.2 60.1 6.0 70.7 28 Maekel 97.9 97.3 97.3 95.0 90.7 97.3 97.3 91.9 96.1 89.2 1.6 81.0 205 Semenawi Keih Bahri 89.1 90.6 86.9 78.8 29.8 91.9 88.2 79.8 80.3 69.9 7.4 76.8 130 Anseba 97.9 96.9 96.0 94.8 22.6 97.3 95.9 93.0 93.8 91.5 2.1 92.4 149 Gash-Barka 87.1 84.0 79.4 73.5 36.8 90.1 83.9 75.6 75.7 64.2 8.5 66.1 186 Debub 86.8 86.6 82.1 75.8 25.1 93.0 87.7 79.0 78.7 69.6 6.3 72.7 261 Mother’s education No education 86.4 85.7 81.9 75.0 25.4 91.2 86.4 77.2 77.1 67.0 8.1 71.0 563 Primary 98.0 97.6 94.8 93.1 51.8 98.5 95.7 92.7 92.7 87.1 1.2 88.0 182 Middle 100.0 96.1 94.6 92.9 60.4 97.6 94.7 85.3 95.5 82.1 0.0 81.7 65 Secondary + 98.3 98.1 97.3 95.3 88.9 96.9 96.3 94.1 95.6 93.5 1.7 82.5 148 Wealth index Lowest 92.0 91.8 87.5 81.5 24.2 95.8 92.3 84.9 83.8 74.4 4.2 78.4 179 Second 88.1 84.4 81.5 75.0 23.1 89.2 83.0 74.2 76.8 65.5 8.7 71.0 184 Middle 83.3 83.7 78.8 73.2 24.5 90.7 85.5 75.8 72.6 64.2 8.9 69.8 194 Fourth 95.0 94.6 92.3 88.5 53.0 94.5 92.4 87.8 90.4 84.5 3.5 82.1 190 Highest 99.2 98.5 97.8 96.2 86.7 99.2 98.5 93.4 96.4 90.9 0.8 85.2 182 Total 2002 91.4 90.6 87.6 82.8 42.6 93.9 90.3 83.3 84.2 75.9 5.2 76.7 959 Total 1995 60.7 60.9 55.3 48.8 19.1 60.6 55.9 47.7 51.0 41.4 37.7 50.3 725 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1Polio 0 is the polio vaccination given at birth. 2BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) Maternal and Child Health | 149 patterns for all vaccines are similar. As expected, urban coverage is higher than rural coverage, with 88 percent of urban children age 12-23 months immunized, compared with 69 percent of children in rural areas. However, the urban-rural gap has narrowed dramatically. In 1995, urban children were more than two and one-half times as likely to be fully immunized as rural children. Children of sixth- or higher birth order are less likely to be vaccinated compared with children of lower birth orders. Mother’s education is positively related to children’s immunization. Coverage ranges from 67 percent among children of mothers with no schooling to 94 percent among children of mothers with at least some secondary education. However, it is encouraging to note that since 1995, the proportion of children of uneducated mothers who are fully immunized has more than doubled, from 32 to 67 percent. Zoba variations give some indication of the success of the EPI program in reaching out to all population subgroups. Coverage by zoba ranges from a high of 92 percent in zoba Anseba to a low of 60 percent in zoba Debubawi Keih Bahri. 9.7 ACUTE RESPIRATORY INFECTIONS Acute respiratory infection (ARI), particularly pneumonia, is one of the leading causes of childhood morbidity and mortality throughout the world. Early recognition and treatment is important for the prevention of death due to pneumonia. Therefore, emphasis is placed on early recognition of the signs of impending severity, both by mothers and primary health care workers, and early treatment. In the 2002 EDHS, the prevalence of ARI was estimated by asking mothers with children under five years of age whether their children had been ill with cough accompanied by short, rapid breathing in the two weeks preceding the survey. These symptoms are signs of pneumonia. Mothers were then asked about their response to the illness. It should be noted, however, that morbidity data collected in surveys are subjective and are based on perception of the illness. As with other common childhood diseases, estimates of the prevalence of ARI are subject to recall bias and seasonal variation. Table 9.13 shows that 19 percent of children under age five had symptoms of ARI in the two weeks before the survey. ARI is low in children under six months (17 percent), peaks at age 6-11 months (24 percent), and then decreases to 15 percent at age 48-59 months. There are only slight differences in prevalence by sex of the child or birth order. ARI is much lower in urban areas (13 percent) than in rural areas (22 percent). Mother’s education is also a factor in the prevalence of ARI; children of uneducated mothers are twice as likely to have ARI as children whose mothers have at least some secondary level of education. ARI is lower in zobas Debubawi Keih Bahri (8 percent) and Maekel (12 percent) than in other zobas. There are only small variations among the other four zobas: Semenawi Keih Bahri (19 percent), Anseba (17 percent), Gash-Barka (21 percent) and Debub (23 percent). ARI is highest among children from households in the lowest quintile of the wealth index (25 percent). Table 9.13 shows that 44 percent of children with respiratory illness were taken to a health provider or facility. Children between 6 and 23 months with ARI (52-56 percent) are more likely to be taken to a health facility than older or younger children. Also, more than 50 percent of first-born children ill with ARI are taken to a health facility or provider. Urban children are much more likely to be taken to a health facility when they have ARI than their rural counterparts. Educated mothers were more likely than uneducated mothers to seek medical treatment for their children with ARI. Children living in zobas Maekel and Gash-Barka are more likely to receive care for ARI at a health facility than children in other zobas. This regional variation may be due to access to health facilities or knowledge of symptoms of ARI; zoba Maekel has the highest level of access to health providers (62 percent) while Anseba has the lowest (33 percent). 150 | Maternal and Child Health Table 9.13 Prevalence and treatment of symptoms of acute respiratory infection (ARI) Percentage of children under five years of age who had a cough accompanied by short, rapid breathing (symptoms of ARI), and percentage of children with symptoms of ARI for whom treatment was sought from a health facility or provider, by back- ground characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Prevalence of ARI Treatment of children among children under five with symptoms of ARI –––––––––––––––––––––– ––––––––––––––––––––––– Percentage Percentage for of children whom treatment with Number was sought from Number Background symptoms of a health facility of characteristic of ARI children or provider1 children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age in months <6 17.3 660 39.8 114 6-11 24.4 621 52.3 152 12-23 23.2 959 55.7 222 24-35 20.8 1,042 36.9 217 36-47 16.3 1,205 34.8 196 48-59 14.5 1,262 41.5 182 Sex Male 19.3 2,948 44.2 570 Female 18.3 2,800 42.9 513 Birth order 1 17.5 1,075 52.9 188 2-3 17.5 2,002 45.6 351 4-5 19.5 1,269 33.2 248 6+ 21.2 1,402 44.1 297 Residence Total urban 13.0 1,931 56.7 250 Asmara 11.4 810 60.7 92 Other towns 14.1 1,121 54.3 158 Rural 21.8 3,817 39.7 833 Zoba Debubawi Keih Bahri 7.9 174 41.1 14 Maekel 12.3 1,069 61.5 131 Semenawi Keih Bahri 19.4 778 40.3 151 Anseba 17.1 877 32.7 150 Gash-Barka 21.3 1,039 57.2 221 Debub 22.9 1,811 36.0 416 Mother’s education No education 21.0 3,620 39.4 760 Primary 19.1 1,048 54.3 200 Middle 14.3 380 (48.7) 54 Secondary + 9.9 700 (54.9) 69 Wealth index Lowest 24.9 1,025 32.8 256 Second 18.7 1,280 41.7 239 Middle 22.2 1,234 43.1 274 Fourth 14.9 1,097 50.1 163 Highest 12.6 926 63.3 117 Total 18.9 5,748 43.6 1,083 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 25-49 unweighted cases. ARI = Acute respiratory infection 1 Excludes pharmacy, shop and traditional practitioner Maternal and Child Health | 151 9.8 FEVER Fever is a major manifestation of malaria, although it also accompanies other illnesses. Malaria contributes to high levels of malnutrition and mortality in children. People most at risk to malaria are children and pregnant women. While fever can occur all year round, malaria is more prevalent after the end of the rainy season. Therefore, temporal factors need to be considered when interpreting fever as an indicator of malaria. Presumptive treatment of fever with antimalarial drugs is advocated where malaria is endemic. Mothers were asked for each child under five whether the child had fever any time in the two weeks prior to the survey. If fever was reported, the mother was asked whether any drugs were given for treatment of fever. Table 9.14 shows that 30 percent of children under five had fever during the reference period. The peak ages for fever among children under five are from 6 to 23 months, a pattern similar to that of ARI. Fever is lowest in children under six months of age and shows a progressive reduction starting at age 24-35 months. The prevalence of fever is higher in rural areas (33 percent) than urban areas (24 percent). By zoba, it is highest in zobas Semenawi Keih Bahri and Debub (33 percent each) and lowest in zoba Maekel (21 percent). The likelihood of children getting fever is negatively related to mother’s level of education and household wealth. Prevalence is twice as high for children whose mothers have no schooling as for children whose mothers have some secondary school education. Table 9.14 shows that only 4 percent of children with fever were treated with antimalarial medications, mostly chloroquine. About 2 percent of children started this treatment on either the day they got the fever or the following day. 9.9 DIARRHEAL DISEASES Unhygienic practices of food preparation and excreta disposal, and use of contaminated drinking water are well known causative factors for diarrheal diseases. Dehydration caused by severe diarrhea is a major cause of death among young children in Eritrea. Dehydration due to diarrhea is easily preventable and can be treated effectively by a prompt increase in the child’s fluid intake through food and oral rehydration therapy (ORT), that is, administration of a solution prepared from oral rehydration salts (ORS) and water, or a homemade solution prepared from sugar, salt, and water (recommended home fluid). ORS packets are available in health institutions and pharmacies. Families should also be encouraged to feed the child well during episodes of diarrhea. Table 9.15 shows the prevalence of diarrheal disease in children under five year of age, according to background characteristics. Thirteen percent of children under five experienced diarrhea at some time in the two weeks preceding the survey. The prevalence of diarrhea is highest among children age 12-23 months (23 percent). Thereafter, the risk of diarrhea decreases with increasing age of the child. Boys are more likely than girls to have diarrhea. Among zobas, diarrhea prevalence ranges from 7 percent in zoba Debubawi Keih Bahri to 18 percent in zoba Debub. Diarrhea is more common among rural children than urban children. The mother’s education, household wealth, and source of drinking water are other factors that affect the prevalence of diarrhea. The higher the mother’s education and wealth, the less likely her child is to have diarrhea in the two weeks before the survey. Children living in households with access to piped drinking water are the least likely to have diarrhea, while children in households using surface water are the most likely to have diarrhea. 152 | Maternal and Child Health Table 9.14 Prevalence and treatment of fever Percentage of children under five years with fever in the two weeks preceding the survey, and percentage of children with fever who were treated with any antimalarial drugs, and specific types of drugs taken, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Prevalence of fever Treatment of fever ––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage Number Chloro- Any Took Number Background of children of Fansidar quine Quinine antimalarial antimalarial of children characteristic with fever children given given given given same/next day with fever ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age in months <6 19.3 660 0.0 0.8 0.0 0.8 0.0 128 6-11 44.8 621 0.5 0.2 0.4 1.2 0.9 278 12-23 42.9 959 0.8 5.3 0.8 6.5 2.3 411 24-35 31.4 1,042 0.6 2.6 1.5 4.7 3.1 327 36-47 24.2 1,205 0.0 2.4 0.4 2.7 1.5 292 48-59 22.0 1,262 0.5 1.0 1.2 2.7 1.3 278 Sex Male 30.5 2,948 0.5 3.4 0.4 4.2 2.1 900 Female 29.1 2,800 0.4 1.3 1.2 2.9 1.4 814 Residence Total urban 24.2 1,931 0.3 2.8 0.9 4.0 2.1 467 Asmara 19.3 810 0.0 4.2 0.8 5.0 2.6 156 Other towns 27.7 1,121 0.4 2.1 1.0 3.5 1.9 311 Rural 32.7 3,817 0.6 2.3 0.8 3.5 1.6 1,247 Zoba Debubawi Keih Bahri 32.3 174 0.0 0.0 0.0 0.0 0.0 56 Maekel 20.8 1,069 0.5 4.7 0.6 5.8 3.2 222 Semenawi Keih Bahri 32.7 778 0.0 0.7 0.0 0.7 0.3 254 Anseba 31.2 877 0.7 0.9 3.5 4.4 3.2 273 Gash-Barka 30.5 1,039 0.7 4.4 0.5 5.6 2.5 316 Debub 32.6 1,811 0.5 2.3 0.2 3.0 1.0 591 Mother's Education No education 33.1 3,620 0.5 1.9 0.8 3.1 1.2 1,197 Primary 29.6 1,048 0.7 4.0 1.3 5.8 2.9 310 Middle 21.2 380 0.0 3.1 0.0 3.1 3.1 81 Secondary + 17.9 700 0.0 3.2 0.0 3.2 3.2 126 Wealth index Lowest 35.9 1,025 0.3 1.5 0.7 2.4 0.4 368 Second 32.8 1,280 0.6 1.8 1.2 3.3 1.6 420 Middle 30.7 1,234 0.7 2.5 1.0 4.2 2.7 378 Fourth 28.3 1,097 0.7 4.9 0.5 5.8 3.2 311 Highest 19.7 926 0.0 0.9 0.7 1.5 0.9 182 Total 29.8 5,748 0.5 2.4 0.8 3.6 1.8 1,714 Maternal and Child Health | 153 Table 9.15 Prevalence of diarrhea Percentage of children under five years with diarrhea in the two weeks preceding the survey, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––– Diarrhea in the Number Background two weeks pre- of characteristic ceding the survey children –––––––––––––––––––––––––––––––––––––––––––––– Age in months <6 7.1 660 6-11 20.4 621 12-23 22.6 959 24-35 16.1 1,042 36-47 9.2 1,205 48-59 7.2 1,262 Sex Male 14.6 2,948 Female 11.8 2,800 Residence Total urban 10.7 1,931 Asmara 9.0 810 Other towns 11.9 1,121 Rural 14.5 3,817 Zoba Debubawi Keih Bahri 7.3 174 Maekel 9.2 1,069 Semenawi Keih Bahri 15.0 778 Anseba 10.1 877 Gash-Barka 12.1 1,039 Debub 17.5 1,811 Mother's education No education 14.0 3,620 Primary 14.0 1,048 Middle 10.3 380 Secondary + 9.7 700 Source of drinking water Piped 10.2 1,892 Protected well 13.3 1,033 Open well 15.0 983 Surface 17.7 1,131 Other/missing 11.3 709 Wealth index Lowest 15.3 1,025 Second 12.8 1,280 Middle 13.7 1,234 Fourth 13.8 1,097 Highest 9.2 926 Total 13.2 5,748 154 | Maternal and Child Health Knowledge about ORS A major component of ORT is the early administration of a solution prepared from ORS packets to prevent dehydration. To assess knowledge of ORS, women who had at least one birth in the five years preceding the survey were asked whether they knew about ORS packets. The results in Table 9.16 show that almost all mothers know about ORS packets (96 percent) with almost no variation by background characteristics. Table 9.16 Knowledge of ORS packets Percentage of women with births in the five years preceding the survey who know about ORS packets for treatment of diarrhea in children, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––– Percentage of mothers who know Number Background about ORS of characteristic packets mothers –––––––––––––––––––––––––––––––––––––––––––– Age 15-19 92.9 220 20-24 93.6 760 25-29 96.8 1,052 30-34 97.4 800 35-49 96.8 1,343 Residence Total urban 97.1 1,448 Asmara 95.1 618 Other towns 98.6 830 Rural 95.6 2,727 Zoba Debubawi Keih Bahri 98.3 136 Maekel 96.0 801 Semenawi Keih Bahri 96.9 560 Anseba 97.8 589 Gash-Barka 95.0 789 Debub 95.6 1,301 Education No education 95.6 2,581 Primary 97.5 766 Middle 96.0 293 Secondary + 96.8 534 Wealth index (quintile) Lowest 94.9 744 Second 95.6 903 Middle 96.8 890 Fourth 97.8 795 Highest 95.3 697 Total 96.1 4,175 –––––––––––––––––––––––––––––––––––––––––––– ORS = Oral rehydration salts Maternal and Child Health | 155 Treatment of Diarrhea Forty-two percent of children who had diarrhea in the two weeks before the survey were taken to health providers (Table 9.17). Children age 12-23 months are most likely to be taken for treatment, followed by children age 6-11 months and age 24-35 months. Around half the children with diarrhea in zobas Maekel and Gash-Barka were taken to health provider for treatment, compared with one-third of children in zobas Anseba and Semenawi Keih Bahri. Overall, more than two-thirds of children with diarrhea received some kind of oral rehydration therapy: ORS (45 percent), recommended home fluids (28 percent), or increased fluids (38 percent). Other types of treatments were less common—pills or syrup (20 percent) and home remedies (11 percent). More than one-fourth of children with diarrhea were given neither ORT nor any other type of Table 9.17 Diarrhea treatment Percentage of children under five years of age who had diarrhea in the two weeks preceding the survey taken for treatment to a health provider, percentage who received oral rehydration therapy (ORT), and percentage given other treatments, according to place of residence, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Oral rehydration therapy (ORT) Other treatments Percent- –––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––– Number age ORS,RHF of taken to Either In- or in- Pill Intra- Home No children Background a health ORS ORS creased creased or Injec- venous remedy/ treat- with characteristic provider1 packets RHF or RHF fluids fluids syrup tion solution other Missing ment diarrhea ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age in months <6 (25.2) (12.6) (11.4) (24.0) (13.0) (34.5) (10.9) (0.0) (0.0) (0.0) (0.0) (58.7) 47 6-11 46.1 41.2 19.8 49.0 34.8 59.8 22.4 0.0 0.0 8.9 0.0 36.6 127 12-23 51.0 55.7 26.9 63.6 43.9 76.5 21.3 2.4 0.4 10.1 0.0 18.9 216 24-35 44.0 48.7 34.6 57.9 40.0 68.6 20.7 0.6 0.0 10.9 0.0 24.1 168 36-47 33.4 33.5 29.1 52.2 35.0 68.1 21.1 2.2 0.0 10.4 1.0 26.1 110 48-59 29.0 46.0 35.9 62.7 43.2 78.7 16.1 1.2 0.0 23.3 0.0 17.4 90 Sex Male 42.4 45.2 26.5 55.5 43.9 71.8 22.3 1.5 0.0 11.7 0.2 22.9 430 Female 41.2 43.9 29.6 55.9 30.9 64.0 17.2 1.0 0.3 10.3 0.0 30.9 329 Residence Total urban 43.7 58.9 31.2 69.6 49.4 81.2 20.0 1.0 0.5 9.1 0.0 15.2 207 Asmara 48.0 66.7 37.6 77.1 60.5 91.9 18.5 0.0 1.3 11.5 0.0 8.1 73 Other towns 41.3 54.6 27.6 65.5 43.4 75.4 20.8 1.5 0.0 7.8 0.0 19.1 134 Rural 41.2 39.3 26.6 50.5 34.1 63.6 20.1 1.4 0.0 11.8 0.2 30.5 552 Zoba Debubawi Keih Bahri 35.6 43.1 14.5 47.1 34.9 58.6 18.1 1.7 0.0 1.6 0.0 37.7 13 Maekel 51.3 65.3 39.9 75.8 47.7 86.8 17.7 0.0 1.0 10.3 1.1 10.9 98 Semenawi Keih Bahri 33.2 49.9 28.7 64.4 43.5 78.1 15.2 0.8 0.0 9.7 0.0 18.4 117 Anseba 33.2 43.2 18.4 51.3 45.5 66.2 19.1 1.9 0.0 9.0 0.0 29.6 89 Gash-Barka 49.1 49.0 26.2 57.7 52.3 72.6 26.1 2.2 0.0 17.0 0.0 19.9 126 Debub 41.9 35.0 27.7 47.1 25.9 58.5 20.6 1.2 0.0 10.4 0.0 35.2 317 Mother’s education No education 39.5 40.0 25.2 51.0 34.7 64.6 18.7 1.5 0.0 11.1 0.2 30.0 505 Primary 47.0 47.7 31.2 59.7 37.3 70.4 20.3 0.8 0.7 9.9 0.0 25.5 147 Middle 48.6 71.7 28.0 71.7 48.1 77.5 27.4 2.5 0.0 5.5 0.0 18.7 39 Secondary + 44.4 57.6 40.2 73.2 61.2 87.5 25.9 0.0 0.0 16.6 0.0 4.9 68 Total 41.9 44.7 27.9 55.7 38.2 68.4 20.1 1.3 0.1 11.1 0.1 26.3 759 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Oral rehydration therapy (ORT) includes solution prepared from oral rehydration salt (ORS) packets, recommended home fluids (RHF), and increased fluids. Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes pharmacy, shop and traditional practitioner 156 | Maternal and Child Health treatment. Thirty percent or more of children with diarrhea in rural areas and in zobas Debub and Debubawi Keih Bahri did not get any treatment. Mother’s education is positively related to seeking treatment for children with diarrhea. Children in urban areas (81 percent) are more likely to receive some type of ORT than children in rural areas (64 percent) and children of educated mothers are more likely to receive ORT than children of less-educated mothers. Slightly less than 60 percent of children in zobas Debub and Debubawi Keih Bahri compared with 87 percent in zoba Maekel received ORT for treatment of diarrhea. Feeding Practices During Diarrhea It is recommended that children be given more liquids to drink during diarrhea and that food intake not be reduced. Mothers of children who had diarrhea in the two weeks before the survey were asked about feeding practices during their children’s illness. Figure 9.2 shows that 19 percent of children who had diarrhea were given the same amount of liquids as usual and 38 percent were given more liquids than usual. On the other hand, more than four in ten children were given less than the usual amount of liquids to drink or no liquids at all. Only 28 percent of children with diarrhea received either the same amount of food as usual or more during their illness. Forty-seven percent of children received less food and 12 percent were not given anything to eat when they had diarrhea. EDHS 2002 Figure 9.2 Feeding Practices During Diarrhea Compared to Normal Practice Same as usual 19% More 38% Somewhat less 34% None 8% Don’t know/ missing 1% Same as usual 17% More 11% Somewhat less 47% None 12% Never gave food 12% Don’t know/ missing 1% Amount of liquids offered Amount of food offered < 9.10 WOMEN’S STATUS AND CHILD HEALTH CARE A woman’s social status and self-respect can be a major determinant of her ability to obtain adequate health care for herself and her children. Table 9.18 shows the proportion of children age 12-23 months who have been fully immunized, and the proportions of children with ARI and diarrhea in the two Maternal and Child Health | 157 weeks preceding the survey who were taken to a health facility for treatment, according to two indicators of women’s empowerment. The first indicator is the number of decisions in which the woman has the final say by herself or jointly with someone else, ranging from 0 to 6 (see Table 3.15 for the list of decisions). The indicator is positively related to women’s empowerment and reflects the degree of control women are able to exercise in areas that affect them and their environment. The second indicator is the number of specific situations in which the respondent thinks a husband is justified in beating his wife, ranging from 0 to 5 (see Table 3.16 for the list of reasons). A lower score on this indicator is interpreted as reflecting a greater sense of entitlement and self-esteem for women, and higher status. Table 9.18 shows that women’s participation in decisionmaking and children’s immunization status are positively related. Women who participate in more decisions are more likely to have fully vaccinated children, but the differences are small. The relationship between this women’s status indicator and treatment-seeking behavior for sick children does not show consistent results. There is no relationship between decisionmaking power and seeking treatment for children with ARI from health providers. However, the proportion of children sick with diarrhea who were taken to a health provider increases as women’s participation in decisionmaking increases. The table shows that there is a negative relationship between each of the three variables for children’s health and women’s status in terms of the number of situations in which women consider it justifiable for a husband to beat his wife. For example, almost half of children with ARI whose mothers Table 9.18 Children’s health care by women’s status Percentage of children age 12-23 months who are fully vaccinated, and percentage of children under five years who were ill with symptoms of acute respiratory infection (ARI) and diarrhea in the two weeks preceding the survey who were taken to a health provider for treatment, by women's status indicators, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Children under five years Children under Children age 12-23 months with symptoms of ARI five years with diarrhea ––––––––––––––––––––––– ––––––––––––––––––––––– –––––––––––––––––––––––– Percentage Percentage Percentage of children Number of children Number of children Number fully of taken to a of taken to a of Women’s status indicator vaccinated1 children health provider2 children health provider2 children –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of decisions in which woman has final say3 0 68.6 35 (44.1) 26 (34.8) 19 1-2 71.1 190 43.3 210 33.4 140 3-4 74.3 264 46.4 326 42.3 225 5-6 79.3 470 42.0 521 45.1 375 Number of reasons wife beating is justified 0 80.0 281 49.4 191 45.7 143 1-2 80.3 206 46.2 313 46.4 187 3-4 71.7 282 44.0 318 41.9 252 5 71.4 190 35.8 262 33.8 177 Total 75.9 959 43.6 1,083 41.9 759 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Those who have received BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) 2 Excludes pharmacy, shop and traditional practitioner 3 Either by herself or jointly with others 158 | Maternal and Child Health regard wife beating as not justified under any circumstances were taken to a health facility, compared with only 36 percent of children whose mothers consider wife beating justified in all five situations. 9.11 USE OF MOSQUITO NETS BY CHILDREN In Chapter 2 it was mentioned that 34 percent of households in Eritrea have mos- quito nets (Table 2.11). By residence, owner- ship of mosquito nets is higher in rural areas (37 percent) than urban areas (29 percent), and it is highest in small towns (45 percent). Because malaria-causing mosquitoes vary by season—with a peak during and immediately following periods of rain—use of mosquito nets may be expected to follow a similar sea- sonal pattern. Since the survey was conducted mostly before the rainy season, from the last week of March to the first week of July 2002, estimates of mosquito net use reflect the dry season levels. Table 9.19 shows the percentage of children under five who slept under a mosquito net the night before the interview. Mothers reported that 12 percent of children slept un- der a mosquito net the previous night; 4 per- cent of children had insecticide-treated mos- quito nets (ITNs). The use of ITNs decreases with increasing age of child from 7 percent for children under one year to 3 percent for children 2-4 years old. The use of ITNs for children is higher in other towns (8 percent) than in rural areas, in zoba Semenawi Keih Bahri (8 percent) than in other zobas. It is surprising that only 9 percent of children in zoba Gash-Barka used a mosquito net the night before the survey (3 percent ITNs), since the zoba has the highest percentage of households owning mosquito nets. 9.12 WOMEN’S PERCEPTION OF PROBLEMS IN ACCESSING HEALTH CARE Many factors can be barriers to a woman seeking health care for herself. In the 2002 EDHS, women age 15-49 were asked whether they thought certain issues or circumstances pose a “big problem” when they want to get treatment for an illness. Table 9.20 shows the percentage of women who reported specific problems in accessing health care for themselves, according to background characteristics. Seventy-two percent of women reported at least one issue or circumstance as a big problem. The major constraints to women’s access to health services are lack of money and physical access to health facilities. Almost half of the respondents (47 percent) reported that getting money for treatment is a big problem; four in ten women said that the health facility was far away; and four in ten said that taking transportation to the health facility was a big problem. It is not surprising that these problems are felt most acutely by Table 9.19 Use of mosquito nets by children Percentage of children under five who slept under any mos- quito net (treated or untreated) and percentage who slept un- der an insecticide-treated net (ITN) the night before the survey, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––– Slept under Slept Number Background a mosquito under of characteristic net1 an ITN2 children –––––––––––––––––––––––––––––––––––––––––––––––––––– Child's age in months < 12 17.4 7.0 1,281 12-23 12.7 4.7 959 24-35 10.8 3.1 1,042 36-47 10.1 3.4 1,205 48-59 9.2 2.8 1,262 Sex Male 11.8 4.3 2,948 Female 12.4 4.1 2,800 Residence Total urban 14.3 4.8 1,931 Asmara 5.2 0.6 810 Other towns 20.9 7.8 1,121 Rural 11.0 4.0 3,817 Zoba Debubawi Keih Bahri 7.7 2.1 174 Maekel 6.2 0.7 1,069 Semenawi Keih Bahri 19.6 8.1 778 Anseba 14.4 4.5 877 Gash-Barka 8.6 3.0 1,039 Debub 13.8 5.4 1,811 Total 12.1 4.2 5,748 –––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Excludes children whose mothers were not interviewed. 1 Includes ITNs 2 Mosquito net either bought or treated with insecticide during the six months preceding the interview Maternal and Child Health | 159 Table 9.20 Problems in accessing health care Percentage of women who reported they have big problems in accessing health care for themselves when they are sick, by type of problem and background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Problems in accessing health care ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Knowing Getting Concerned where permission Getting Distance Not there may Queuing Quality Any to go to go money to Having to wanting not be a in line of the of the Number Background for for for health take to go female for health specified of characteristic treatment treatment treatment facility transport alone provider treatment services problems women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 11.1 10.3 35.7 33.3 37.8 31.2 14.1 35.0 14.3 69.2 2,001 20-29 10.2 10.7 44.8 37.7 41.5 28.7 14.6 38.3 15.4 70.1 2,998 30-39 10.5 11.1 51.8 40.5 44.1 28.0 15.5 40.2 16.9 73.9 2,194 40-49 12.0 10.7 59.7 43.1 49.5 29.9 17.3 40.4 18.7 78.5 1,561 Number of living children 0 11.1 11.1 35.9 32.9 36.8 30.0 14.3 34.8 15.1 67.3 3,019 1-2 9.5 9.2 47.2 38.2 42.9 27.7 15.1 39.7 16.1 71.5 2,287 3-4 11.0 11.1 55.6 40.2 44.6 26.8 15.1 38.7 17.0 75.1 1,772 5+ 11.9 11.4 58.5 46.5 51.2 32.9 17.0 42.9 17.1 79.5 1,677 Marital status Never married 9.3 9.4 32.8 27.0 31.0 25.3 10.9 31.8 13.2 63.0 2,044 Married or living together 11.6 11.5 49.7 42.9 47.0 31.4 17.0 41.3 17.3 74.8 5,733 Divorced, separated, widowed 9.3 8.6 61.8 35.3 41.8 25.5 13.3 35.1 15.2 77.1 977 Residence Total urban 5.1 4.4 32.0 14.3 16.7 13.4 4.6 27.7 10.8 54.9 3,767 Asmara 4.9 3.9 24.5 10.8 12.4 12.3 2.8 23.1 10.1 47.8 1,899 Other towns 5.3 4.9 39.6 17.7 21.0 14.5 6.4 32.3 11.6 62.2 1,868 Rural 15.1 15.4 58.6 56.6 62.4 41.3 23.2 46.5 20.1 85.4 4,987 Zoba Debubawi Keih Bahri 10.9 13.6 38.6 37.6 43.3 39.2 36.5 43.8 35.8 66.8 324 Maekel 5.2 4.4 27.5 14.7 17.3 13.4 3.6 22.9 10.5 51.2 2,264 Semenawi Keih Bahri 13.7 13.9 54.1 48.5 51.0 40.3 27.8 54.4 21.9 81.6 1,148 Anseba 8.3 12.3 53.2 51.7 54.5 35.5 19.9 36.9 18.2 77.5 1,130 Gash-Barka 17.4 21.5 55.4 49.2 55.5 39.8 25.7 46.1 22.1 82.3 1,500 Debub 11.8 7.1 55.4 42.9 49.1 28.2 8.3 40.5 11.3 79.9 2,388 Education No education 16.4 16.2 62.2 53.9 58.9 41.1 24.6 48.2 20.1 85.0 4,384 Primary 7.1 6.3 44.0 33.4 37.6 24.1 8.6 33.7 13.8 71.9 1,637 Middle 5.2 4.3 33.2 21.9 25.4 19.6 6.5 27.1 10.8 59.2 974 Secondary + 3.5 4.5 20.2 13.4 16.8 10.1 2.6 24.6 11.3 48.2 1,760 Employment Not employed 12.2 12.2 49.1 41.5 45.3 31.8 17.5 40.3 17.1 74.7 6,670 Working for cash 5.4 5.9 38.7 23.9 28.8 16.5 5.6 28.9 11.9 62.3 1,510 Not working for cash 8.5 5.5 47.2 39.8 49.9 34.5 13.9 40.9 16.2 71.6 571 Wealth index Lowest 18.6 20.5 61.5 63.8 70.1 50.5 29.2 49.8 23.0 88.5 1,344 Second 15.8 16.5 60.3 57.1 62.6 41.9 25.3 47.1 19.8 84.9 1,626 Middle 13.4 12.0 56.0 50.5 57.1 36.2 18.9 47.1 19.3 83.8 1,659 Fourth 5.8 4.5 41.3 23.7 26.1 15.7 5.5 30.8 10.6 65.2 1,806 Highest 4.1 3.8 25.6 10.1 11.8 11.2 3.4 23.8 10.5 49.4 1,978 Total 10.8 10.7 47.1 38.4 42.7 29.3 15.2 38.4 16.1 72.3 8,754 160 | Maternal and Child Health rural women, older women, women with large families, and women in the least wealthy households. At least half of women in all zobas except Maekel and Debubawi Keih Bahri mentioned money constraints, distance to the health facility, and having to take transport. Eleven percent of women in Eritrea do not know where to go for health care. For three potential problems associated with quality of care, women cited them in order of frequency as: waiting in line at the health facility (38 percent), the quality of health services (16 percent), and concern that a female health provider might not be available at the health facility (15 percent). Queuing in line is mentioned more often by rural women than urban women, and by less educated women than educated women. Rural women, less educated women, and women in less wealthy households are more concerned with the quality of health services and more concerned that a female health provider might not be available at the health facility than other women. By zoba, the problem of queuing in line is more frequently mentioned in Semenawi Keih Bahri and Gash-Barka; concern about the quality of health services is reported most in zoba Debubawi Keih Bahri. Reporting personal reasons that hinder access to health facilities is less common. Three in ten women report that they do not want to go to a health provider alone. Eleven percent of women say that needing “permission” to seek health care is a big problem, which is consistent with the results in Table 3.15 on women’s decisionmaking about health care for themselves. Infant Feeding and Nutritional Status of Children and Women | 161 INFANT FEEDING AND NUTRITIONAL STATUS OF CHILDREN AND WOMEN 10 Malnutrition is one of the most important health and welfare problems facing Eritrea today. Young children and women of reproductive age are especially vulnerable to nutritional deficits and micronutrient deficiency disorders. Evidence also suggests that life expectancy is directly related to poverty and nutrition (Sachs, 1999). The 2002 EDHS survey collected data from mothers on the feeding patterns of their children under five years of age. In this chapter, these data are used to evaluate infant feeding practices, including breastfeeding duration, introduction of complementary foods, and use of feeding bottles with nipples. Other important nutritional issues that pertain to micronutrients—vitamin A and iron supplements, and use of iodized salt—are also discussed. The last two sections present nutritional status data based on anthropometric indices (height and weight measures) of all children under five years of age and all women age 15-49. 10.1 BREASTFEEDING AND COMPLEMENTARY FEEDING The pattern of infant feeding has important effects on both the child and the mother. Feeding practices are the underlying determinant of children’s nutritional status. Appropriate feeding practices are of fundamental importance for the survival, growth, development, health, and nutrition of infants and children, and for the well-being of mothers. Poor nutrition in young children exposes them to greater risk of illness and death. Breastfeeding also affects mothers through the physiological suppression of the return to fertile status, thereby affecting the length of interval between pregnancies. These effects are influenced by both the duration and frequency of breastfeeding, and by the age at which the child receives foods and liquids to complement breast milk. Prevalence and Initiation of Breastfeeding The initiation of breastfeeding immediately after childbirth is important because it benefits both the mother and the infant. As soon as the infant starts suckling at the breast, the hormone oxytocin is released in the mother, resulting in uterine contractions that facilitate the expulsion of the placenta and reduce the risk of postpartum hemorrhage. Early initiation also encourages bonding between the mother and newborn, and helps to maintain the baby’s body temperature. Breast milk is sufficient for newborn infants; it is not necessary to give them anything else. It is also recommended that the first breast milk should be given to the child because it contains colostrum, which provides natural immunity to the child and protects the child from infections before the child’s immune system has matured. Prelacteal feeding (giving something other than breast milk in the first three days of life) is discouraged because it inhibits breastfeeding and exposes the newborn to illness. Contaminants may cause infection, leading to diarrhea and other diseases. Table 10.1 shows that breastfeeding is nearly universal in Eritrea, with 98 percent of children born in the five years before the survey having been breastfed. There are no marked differences in the proportion of children ever breastfed by background characteristics. Overall, 78 percent of children are breastfed within an hour of delivery and 90 percent within the first 24 hours after delivery; these rates of early initiation of breastfeeding are among the highest in sub- Saharan countries. Variations among population subgroups are minimal, but certain characteristics are 162 | Infant Feeding and Nutritional Status of Children and Women Table 10.1 Initial breastfeeding Percentage of children born in the five years preceding the survey who were ever breastfed, and among chil- dren ever breastfed, the percentage who started breastfeeding within one hour and within one day of birth, and percentage who received a prelacteal feed, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Among children ever breastfed, percentage who started Percentage All children breastfeeding: of children Number ––––––––––––––––––––– ––––––––––––––––––– who of Percentage Number Within Within received a children Background ever of one hour one day prelacteal ever characteristic breastfed children of birth of birth1 feed2 breastfed ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Sex Male 97.6 3,186 77.1 88.1 17.7 3,110 Female 98.3 2,969 78.7 90.9 16.7 2,920 Residence Urban 98.0 2,030 85.7 94.7 6.8 1,989 Asmara 97.6 844 86.6 94.0 4.8 824 Other towns 98.3 1,186 85.1 95.1 8.2 1,166 Rural 97.9 4,125 74.0 86.9 22.3 4,040 Zoba Debubawi Keih Bahri 93.7 195 81.2 89.9 33.1 183 Maekel 98.0 1,118 84.1 92.1 6.4 1,096 Semenawi Keih Bahri 98.1 845 82.3 94.7 15.5 830 Anseba 99.0 911 88.8 95.6 11.5 902 Gash-Barka 97.4 1,136 77.7 88.5 19.7 1,106 Debub 98.1 1,950 67.1 83.3 23.9 1,913 Mother’s education No education 98.4 3,909 75.4 87.9 21.5 3,846 Primary 97.2 1,118 80.3 91.1 12.0 1,087 Middle 97.0 399 83.6 93.7 9.1 388 Secondary + 97.4 729 84.4 93.0 6.6 709 Wealth index Lowest 98.2 1,333 77.9 90.1 19.5 1,309 Second 98.4 1,303 71.6 85.0 26.7 1,283 Middle 97.5 1,284 73.1 85.7 21.0 1,252 Fourth 97.7 1,258 82.9 93.2 9.8 1,229 Highest 97.9 977 86.2 94.5 5.9 957 Assistance at delivery Health professional3 97.5 1,742 86.3 94.1 6.0 1,697 Traditional birth attendant 98.0 2,663 79.3 91.5 19.0 2,609 Other 98.4 1,688 68.9 83.6 26.1 1,662 Place of delivery Health facility 97.2 1,621 86.5 94.3 6.2 1,576 At home 98.2 4,482 75.5 88.5 21.2 4,401 Total 98.0 6,156 77.9 89.5 17.2 6,029 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Table is based on all births whether the children are living or dead at the time of interview. Total in- cludes 24 children who had no assistance at birth and 37 children for whom information was missing on assis- tance at delivery. Total also includes 15 children who were delivered in places other than health facility or home, and 38 children with missing information on place of delivery. 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 before the mother started breastfeeding regularly. 3 Doctor, nurse/midwife, or auxiliary midwife Infant Feeding and Nutritional Status of Children and Women | 163 associated with lower likelihood of a child being put to the breast within an hour of delivery. Residence in zoba Debub and use of non-medically trained personnel at delivery are associated with a lower likelihood of initiating breastfeeding within an hour of delivery. Prelacteal feeding is not widely practiced in Eritrea. Only one in six newborns receives a prelacteal feed. The practice is more prevalent in rural areas (22 percent) than urban areas and in zobas Debubawi Keih Behari and Debub than other zobas. Children of uneducated mothers and less wealthy mothers are more likely to receive prelacteal feeds. Some delivery characteristics are related to the practice of prelacteal feeding of newborns. Infants are more likely to receive prelacteal feeds when they are delivered at home and when delivery is not assisted by a health professional or a TBA. 10.2 AGE PATTERN OF BREASTFEEDING Breast milk is the primary source of nutrients for infants. Children who are exclusively breastfed receive only breast milk. The World Health Organization (WHO) recommends that during the first six months of life, children should be exclusively breastfed and that they should be given solid or mushy complementary foods starting at six months of age (WHO, 1998). Supplementing breast milk with other foods before six months is strongly discouraged because of the possible introduction of disease-causing agents. To obtain information on feeding patterns, mothers interviewed in the 2002 EDHS were asked about breastfeeding patterns in the 24-hour period before the survey for all children under the age of three and whether other liquids or foods were given to the child during the period. Table 10.2 shows the percent distribution of youngest children under three living with the mother by breastfeeding status, according to child’s age in months. The table indicates that almost all children are breastfed for at least one year; at two years of age 62 percent of children are still breastfeeding. Thereafter, breastfeeding declines rapidly so that by age 28-31 months only one-fifth of children are still breastfed. Despite the universal prevalence of breastfeeding of newborns in Eritrea, the majority of infants are not fed in compliance with WHO/UNICEF recommendations. Exclusive breastfeeding, which should continue until age six months, is common but not universal in early infancy in Eritrea. Although 79 percent of children under two months are exclusively breastfed, this proportion falls to slightly more than half for children 2-3 months (53 percent) and to one in four (26 percent) among those 4-5 months of age. The reason that prevalence of exclusive breastfeeding at young ages is not higher is early supplementation of breast milk with plain water. Sixteen percent of children under two months and almost one-third of children 2-3 months receive water and breast milk. In addition to water, other supplements are introduced at a fairly early age: 5 percent of children under two months receive water-based liquids and other milk (cow’s or goat’s) in addition to breast milk. Fifteen percent of children 2-3 months receive breast milk and these two supplements. At age 6-9 months, when children should be receiving both breast milk and solid or mushy foods, only 43 percent are receiving breast milk and complementary foods, while almost one-third are receiving breast milk or breast milk and water only. Infant formula, even if correctly prepared, does not adequately substitute for breast milk. More- over, formula is often mixed incorrectly, leading to undernutrition among infants. The use of a bottle with a nipple regardless of the content (formula or any other liquid) requires attention in terms of hygiene and handling. Because of inadequate and insufficient cleaning and ease of contamination after cleaning, the nipple may house disease-causing agents. Fortunately, in Eritrea bottle-feeding is relatively uncommon. Less than 10 percent of children in any age group drink from a bottle with a nipple. 164 | Infant Feeding and Nutritional Status of Children and Women Table 10.2 Breastfeeding status by child’s age Percent distribution of youngest children under three years living with the mother by breastfeeding status and percentage of children under three years using a bottle with a nipple, according to age in months, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Breastfeeding and consuming: Exclu- ––––––––––––––––––––––––––––––– Using a Number Not sively Plain Water-based Comple- Number bottle of breast- breast- water liquids/ Other mentary of with a living Age in months feeding fed only juice milk foods Total children nipple1 children –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– <2 0.0 79.4 15.8 2.5 2.3 0.0 100.0 196 3.9 200 2-3 0.1 53.1 30.9 11.2 4.0 0.6 100.0 239 0.9 242 4-5 0.1 25.8 39.3 14.6 10.3 9.9 100.0 217 6.7 217 6-7 1.9 13.1 26.5 18.2 7.3 33.0 100.0 220 8.9 222 8-9 2.1 3.8 19.1 15.7 6.0 53.3 100.0 196 8.7 200 10-11 3.8 4.8 12.1 7.2 4.5 67.6 100.0 194 8.2 199 12-15 8.1 3.5 5.8 4.9 5.0 72.8 100.0 351 7.5 358 16-19 14.9 1.4 0.7 2.5 0.7 79.7 100.0 301 7.8 313 20-23 38.3 3.1 1.9 2.6 0.2 54.0 100.0 270 4.8 287 24-27 62.1 0.1 0.4 1.0 0.6 35.8 100.0 352 5.7 433 28-31 79.3 1.1 0.3 3.0 0.0 16.3 100.0 202 4.6 296 32-35 86.9 0.0 0.0 0.0 0.2 12.8 100.0 195 3.6 312 <6 0.0 52.0 29.2 9.7 5.6 3.5 100.0 651 3.7 660 6-9 2.0 8.8 23.0 17.0 6.7 42.5 100.0 416 8.8 422 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Breastfeeding status refers to a “24-hour” period (yesterday and last night). Children classified as breastfeeding and consuming plain water only consume no supplements. The categories of not breastfeeding, exclusively breastfed, breast- feeding and consuming plain water, water-based liquids/juice, other milk, and complementary foods (solids or semi-solids or both) are hierarchical and mutually exclusive, and their percentages add to 100 percent. Thus children who receive breast milk and water-based liquids and who do not receive complementary foods are classified in the water-based 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 Based on all children under three years 10.3 DURATION AND FREQUENCY OF BREASTFEEDING Table 10.3 presents information on the median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children under three years of age. It also provides information on the percentage of children below six months of age who are breastfed six or more times in a 24-hour period. At the national level, the median duration of any breastfeeding is 22 months, which has remained unchanged since 1995. The median duration of exclusive breastfeeding is three months and the median duration of predominant breastfeeding (breastfeeding exclusively or with plain water, water-based liquids, or juice) is seven months. All mean durations are slightly higher than the corresponding median duration. The median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding varies little across background characteristics. The median duration of any breastfeeding is shortest in zoba Debubawi Keih Bahri (18 months), as is the median duration of exclusive breastfeeding (less than a month). The frequency of breastfeeding during a 24-hour period before the survey is examined in Table 10.3. The daily frequency of breastfeeding of children under six month in Eritrea exceeds or meets the WHO recommendation (WHO, 1998). Ninety-eight percent of children under six months were breastfed six or more times in the 24 hours preceding the survey. The average number of daytime and nighttime feeds is 7 and 5, respectively. Infant Feeding and Nutritional Status of Children and Women | 165 Table 10.3 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey, percentage of breastfeeding children under six months living with the mother who were breastfed six or more times in the 24 hours preceding the survey, and mean number of daytime and nighttime feeds, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Median duration (months) Breastfeeding children of breastfeeding1 under six months2 ––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––– Pre- Percentage Mean Mean Any Exclusive dominant Number breastfed 6+ number number Number Background breast- breast- breast- of times in last of of of characteristic feeding feeding feeding3 children 24 hours day feeds night feeds children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Sex Male 22.1 2.3 7.1 1,760 97.7 7.0 4.8 329 Female 21.4 2.6 7.2 1,717 98.1 6.9 4.7 326 Residence Urban 21.6 2.8 5.5 1,145 96.8 6.6 4.8 187 Asmara 21.7 2.6 4.5 493 98.1 (6.2) (4.8) 75 Other towns 21.6 3.0 6.3 652 95.9 6.8 4.9 111 Rural 22.0 2.3 7.9 2,332 98.3 7.1 4.7 468 Zoba Debubawi Keih Bahri 17.9 0.6 5.6 114 97.6 5.8 4.1 22 Maekel 21.5 2.9 5.1 643 98.6 6.2 4.7 101 Semenawi Keih Bahri 21.0 2.1 7.9 463 98.9 8.4 5.4 92 Anseba 21.6 3.0 7.5 516 98.3 8.1 5.2 96 Gash-Barka 22.2 2.1 7.6 673 99.3 6.7 4.3 112 Debub 22.2 2.6 7.7 1,068 96.4 6.5 4.7 232 Mother’s Education No education 22.2 2.2 8.0 2,154 99.6 7.4 5.0 409 Primary 21.3 2.8 7.0 618 99.1 6.6 4.6 112 Middle 21.8 3.1 6.3 254 92.4 (6.3) (4.2) 60 Secondary + 20.7 3.0 4.6 451 91.3 5.7 4.1 74 Wealth index Lowest 20.8 2.2 8.5 743 97.1 7.6 4.8 156 Second 24.3 2.1 7.8 735 99.7 7.1 4.7 137 Middle 23.1 2.6 7.7 737 99.5 7.0 4.8 143 Fourth 21.8 2.7 6.0 702 96.2 6.4 4.6 121 Highest 20.8 2.7 5.1 560 96.4 6.4 5.0 96 Total 21.8 2.5 7.1 3,477 97.9 na na 655 Mean 22.3 4.3 8.9 na na 7.0 4.8 na ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Medians and means durations are based on current status. Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 1 It is assumed that non-last-born children not living with the mother are not currently breastfeeding. 2 Excludes children for whom there is no a valid answer on the number of times breastfed 3 Either exclusively breastfed or received breast milk and plain water, water-based liquids and/or juice only (excludes other milk) 166 | Infant Feeding and Nutritional Status of Children and Women 10.4 TYPES OF COMPLEMENTARY FOODS CONSUMED Table 10.4 presents information on the different types of food that are given to children in the first three years of life. Data are shown separately for breastfeeding children and nonbreastfeeding children. It is important to note that the categories presented in Table 10.4 are not exclusive. The child who consumes milk may also consume semisolid foods. While only a few breastfeeding infants under 6 months receive infant formula, a larger proportion of children over one year and those who are not breastfeeding receive infant formula. Table 10.4 Foods consumed by children in the day or night preceding the interview Percentage of children under three years of age living with the mother who consumed specific foods in the day or night pre- ceding the interview, by breastfeeding status and age, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Any Food Meat/ Food Fruits and solid Other Food made Food fish/ made vegetables or milks/ made Fruits/ from made shellfish/ with rich in semi- Number Child’s age Infant cheese/ Other from vege- roots/ from poultry oil/fat/ vitamin solid of in months formula yogurt liquids1 grains tables2 tubers legumes eggs butter A3 food children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– BREASTFEEDING CHILDREN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– <2 0.0 2.3 2.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.1 196 2-3 1.4 4.6 11.7 0.5 0.5 0.0 0.5 0.6 0.0 0.5 3.4 239 4-5 6.3 14.2 23.9 4.8 3.1 0.0 1.0 1.0 1.4 1.5 18.0 216 6-7 14.8 20.7 42.3 18.7 11.9 1.7 3.9 9.8 4.5 10.2 46.1 216 8-9 15.8 25.5 56.9 27.6 17.9 1.0 8.4 22.9 9.6 12.7 63.8 191 10-11 19.3 32.1 59.2 32.0 29.3 7.3 12.7 23.0 11.1 26.6 79.0 187 12-15 23.2 43.5 73.6 36.6 35.7 8.9 19.1 26.3 23.9 29.2 91.0 323 16-19 21.2 41.4 89.1 44.4 40.6 9.4 32.7 41.7 36.0 31.5 96.5 256 20-23 18.6 41.4 82.9 36.5 33.3 8.9 26.4 34.1 28.9 26.1 92.1 167 24-27 13.1 41.9 82.3 36.5 43.8 7.6 33.7 39.7 35.9 36.6 99.1 133 28-31 (9.5) (39.6) (86.6) (24.5) (32.9) (3.6) (23.0) (11.5) (26.5) (27.8) (96.8) 42 32-35 (49.7) (36.2) (93.8) (44.6) (42.8) (0.0) (25.4) (33.9) (51.5) (18.9) (98.2) 26 <6 2.6 7.1 13.0 1.8 1.2 0.0 0.5 0.5 0.5 0.7 8.5 651 6-9 15.3 22.9 49.2 22.9 14.7 1.4 6.0 16.0 6.9 11.4 54.4 407 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– NONBREASTFEEDING CHILDREN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 16-19 43.6 83.0 91.3 48.6 56.5 8.7 16.3 66.3 36.3 47.3 99.6 45 20-23 25.2 59.0 89.7 35.1 45.6 10.4 27.9 34.3 40.5 37.4 99.0 103 24-27 26.0 49.1 88.2 47.6 49.3 9.1 27.6 41.3 41.8 42.8 100.0 218 28-31 26.9 54.1 86.5 51.8 46.2 17.2 34.4 40.5 37.7 41.6 99.6 160 32-35 27.8 52.8 89.0 39.5 51.9 14.5 41.5 43.4 41.5 39.3 99.1 169 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Breastfeeding status and food consumed refer to a “24 hour” recall period (yesterday and last night). Figures are not shown for nonbreastfeeding children under 16 months because there were fewer than 25 unweighted cases in each age group. Figures in parentheses are based on 25-49 unweighted cases. 1 Does not include plain water 2 Includes fruits and vegetables rich in vitamin A 3 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, green leafy vegetables, mangoes, papayas, and other locally grown fruits and vegetables that are rich in vitamin A Under the age of six months, 9 percent of children are fed solid or semisolid foods. Seven percent of infants in this age group are fed other milks, cheese, or yogurt, 3 percent are fed infant formula, and 2 percent are fed foods made from grains. At age 6-9 months, the period of the introduction of complementary foods, only 54 percent of infants receive solid or semisolid foods. Of those who receive complementary foods, the variety of foods is limited. Twenty-three percent receive foods made from grains, 23 percent receive other kinds of milk, cheese, or yogurt, while 16 percent receive animal products Infant Feeding and Nutritional Status of Children and Women | 167 (a major source of iron, zinc, and vitamin A); 15 percent are given fruits and vegetables and 15 percent are given infant formula. Other fruits and vegetables rich in vitamin A are consumed by 11 percent of infants age 6-9 months. At one year of age (10-11 months), one in five breastfeeding children is not receiving solid foods. Three in ten children are receiving milk, cheese, or yogurt, foods made from grains, and fruits and vegetables. One-fourth are receiving fruits and vegetables rich in vitamin A and animal products. Infant formula is given to one in five children in this age group. By 20-23 months of age, 92 percent of children are fed solid foods; including foods made from grains (37 percent), animal products (34 percent), and fruits and vegetables (33 percent). One in four children age 20-23 months eats legumes and fruits and vegetables rich in vitamin A. Three in ten young children in this age group consume foods enriched with oils, fats, or butter (increasing the caloric density of the foods). Few children under two years of age are not breastfed in Eritrea. For nonbreastfeeding children, at two years of age the pattern of feeding is markedly different from that among breastfeeding children. Over 40 percent of nonbreastfeeding children receive fruits and vegetables and foods enriched with oil, fats or butter; and more than one-third are fed animal products and fruits and vegetables rich in vitamin A along with foods made from grains. Sixty percent of children in this age receive milk products, and 25 percent are fed infant formula. 10.5 FREQUENCY OF FOODS CONSUMED BY CHILDREN IN THE PAST DAY AND NIGHT The nutritional requirements of young children are more likely to be met if they are fed a variety of foods. Infants and young children eat small meals, and therefore, frequent meals are necessary to provide them with required nutrients. In the 2002 EDHS survey, interviewers read a list of specific foods or food types and asked the mother to report the number of times during the last 24 hours their youngest child under three had consumed each food. Table 10.5 shows the mean number of times specific foods were consumed by children under three years in the day and night preceding the interview. Table 10.5 shows that among breastfeeding children age 6-7 months, only other liquids (juice and water-based liquids) are given almost once a day, with solid foods given much less frequently. At one year of age (10-11 months), young children are fed milk, cheese or yogurt and fruits and vegetables almost once per day. Other liquids that are not as nutritious and may interfere with continued breastfeeding are given twice a day. At two years of age (20-23 months), breastfed children are eating foods at about the same frequency as the one-year-olds, except there has been an increase in animal products, fruits and vegetables rich in vitamin A, and foods fortified with oil, fats and butter to almost once per day. For children who are no longer breastfeeding, the need for varied and substantial nutritious foods is even greater. The EDHS data show that among children 20-23 months who are not breastfed, the frequency of eating most foods is similar to that of breastfed children. However, fruits and vegetables are given, on average, more than once a day. Other foods rich in vitamin A, like carrots, pumpkin, mango, and papaya, are also provided about once per day, which is slightly more frequent than among breastfed children; milk products are also given more frequently. It is recommended by the World Health Organization that for the average healthy breastfed infant, meals of complementary foods should be provided 2-3 times per day at 6-8 months of age and 3-4 times per day at 9-11 and 12-24 months of age, with additional nutritious snacks offered 1-2 times per day (Dewey, 2001). The number of meals required for children is based on the energy density of foods. Consuming an appropriate variety of foods is essential for the nutrition of children. 168 | Infant Feeding and Nutritional Status of Children and Women Figure 10.1 shows the mean number of meals (solid, semisolid, or soft foods) breastfeeding children under three years and nonbreastfeeding children 16-35 months received in the day and night before the survey. For nonbreastfeeding children, data are not shown for children under 16 months because there were fewer than 25 cases in each age group. Figure 10.1 indicates that among breastfeeding and nonbreastfeeding children neither those age 6-8 months nor older children get the recommended number of meals and snacks in a 24-hour period. Although nonbreastfeeding children get more meals, the extra meals are not sufficient to compensate for lack of breast milk. Table 10.5 Frequency of foods consumed by children in the day and night preceding the interview Mean number of times specific foods were consumed in the day or night preceding the interview by youngest children under three years of age living with the mother, according to breastfeeding status and age, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Food Meat/ Food Fruits and Other Food made Food fish/ made vegetables milk/ made Fruits/ from made shellfish/ with rich in Number Child’s age Infant cheese/ Other from vege- roots/ from poultry oil/fat/ vitamin of in months formula yogurt liquids 1 grains tables2 tubers legumes eggs butter A3 children –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– BREASTFEEDING CHILDREN –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– <2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 196 2-3 0.1 0.1 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 239 4-5 0.1 0.3 0.6 0.1 0.0 0.0 0.0 0.0 0.0 0.0 216 6-7 0.3 0.5 0.9 0.3 0.2 0.0 0.1 0.1 0.1 0.2 216 8-9 0.2 0.5 1.3 0.5 0.3 0.0 0.1 0.3 0.1 0.2 191 10-11 0.4 0.8 1.6 0.6 0.7 0.1 0.2 0.3 0.2 0.5 187 12-15 0.4 0.9 2.0 0.6 0.9 0.1 0.3 0.4 0.4 0.6 323 16-19 0.4 0.9 2.7 0.7 1.0 0.2 0.4 0.6 0.7 0.6 256 20-23 0.4 1.1 2.8 0.6 0.9 0.1 0.4 0.6 0.7 0.6 167 24-27 0.2 1.0 2.7 0.7 1.1 0.1 0.5 0.6 0.8 0.8 133 28-31 (0.2) (0.9) (2.9) (0.5) (0.8) (0.0) (0.4) (0.1) (0.6) (0.6) 42 32-35 (1.0) (0.7) (3.1) (0.6) (0.8) (0.0) (0.3) (0.5) (0.9) (0.4) 26 <6 0.1 0.2 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 651 6-9 0.3 0.5 1.1 0.4 0.3 0.0 0.1 0.2 0.1 0.2 407 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– NONBREASTFEEDING CHILDREN –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 16-19 1.0 2.4 3.1 0.6 1.7 0.1 0.2 0.9 0.6 1.0 45 20-23 0.5 1.6 3.6 0.6 1.5 0.2 0.5 0.6 0.8 0.9 103 24-27 0.5 1.1 3.1 0.8 1.2 0.1 0.5 0.7 0.9 0.8 218 28-31 0.6 1.4 3.6 1.1 1.6 0.3 0.6 0.8 0.8 1.1 160 32-35 0.6 1.2 3.3 0.6 1.5 0.3 0.7 0.7 1.0 1.1 169 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Breastfeeding status and food consumed refer to a “24 hour” recall period (yesterday and last night). For nonbreast- feeding children, figures for children under 16 months are not shown because there were fewer than 25 unweighted cases in each category. Figures in parentheses are based on 25-49 unweighted cases. 1 Does not include plain water 2 Includes fruits and vegetables rich in vitamin A 3 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, green leafy vegetables, mangoes, papayas, and other locally grown fruits and vegetables that are rich in vitamin A Infant Feeding and Nutritional Status of Children and Women | 169 EDHS 2002 Figure 10.1 Frequency of Meals Consumed by Children Under 36 Months of Age Living with Their Mother Note: Data are not shown for age groups with fewer than 25 unweighted cases. 0.2 0.1 0.4 0.9 1.4 1.9 2.3 2.9 2.8 3.3 3.6 3.4 0.2 1.1 3.5 3.9 4.2 4.0 4.2 1.3 2.3 <2 2-3 4-5 6-7 8-9 10-11 12-15 16-19 20-23 24-27 28-31 32-35 <6 6-9 Child’s Age (Months) 0.0 1.0 2.0 3.0 4.0 5.0 Mean number of meals (solid/semisolid/soft food) Breastfed Not breastfed 10.6 FREQUENCY OF FOODS CONSUMED BY CHILDREN IN THE PAST SEVEN DAYS Table 10.6 shows the average number of days specific foods were consumed by youngest children under three years in the seven days preceding the interview. Breastfeeding children age 6-9 months drank plain water during six of the preceding seven days and consumed each type of food and each type of other liquid on one or two of the preceding seven days. For example, breastfeeding children drank sugar water as well as tea or other beverages an average of 1.5 days in the past week, and injera1 as well as food made from grains only one day. Other foods and liquids were fed to breastfeeding children age 6-9 months less than one day in the week preceding the interview. Breastfeeding children age 10-11 months consume a variety of foods but each of these foods is given only two days a week or less. Foods and liquids given to this group of children most often are plain water (six days), injera (three days), and the tea category, sugar water, and foods made from grains (two days each). Breastfeeding children age 20-23 months have a similar feeding pattern but consume most of these foods more often than children age 10-11 months. Children age 20-23 months who are not receiving breast milk consume water and most water- based liquids at the same frequency as breastfeeding children, but they consume all types of milk and dairy products more often than breastfeeding children. Nonbreastfeeding children in this age group also eat injera one day more than breastfeeding children. Nonbreastfeeding children also eat most other solid and semisolid food slightly more frequently than breastfeeding children. 1 Pancake-like bread made from fermented sorghum or teff 170 | Infant Feeding and Nutritional Status of Children and Women Ta bl e 10 .6 Fr eq ue nc y of fo od s co ns um ed b y ch ild re n in p re ce di ng s ev en d ay s M ea n nu m be r o f d ay s sp ec ifi c fo od s w er e re ce iv ed in th e se ve n da ys p re ce di ng th e in te rv ie w b y yo un ge st c hi ld re n un de r t hr ee y ea rs o f a ge li vi ng w ith th e m ot he r, by b re as tfe ed in g st at us a nd ag e, E rit re a 20 02 –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – So lid /s em iso lid fo od s –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – Fr ui ts a nd v eg et ab le s ric h in v ita m in A –– –– –– –– –– –– –– –– –– –– –– Li qu id s Pu m pk in / Fr ui ts re d or Te a, ve ge - M ea t/ Fo od ye llo w ke rk ed e, Fo od ta bl es fis h/ m ad e O th er ya m s or M an go / Po w de re d ab ak e, Fo od m ad e no t Fo od sh el l- w ith so lid , sq ua sh / G re en p ap ay a/ C hi ld ’s or co ffe e, m ad e fro m ric h in m ad e C he es e/ fis h/ oi l/ se m i- ca rr ot s/ le af y ot he r N um be r ag e in Pl ai n In fa nt tin ne d Fr es h Fr ui t Su ga r so ft O th er fro m ro ot s/ vi ta m in fro m yo g- po ul try / fa t/ so lid re d sw ee t ve ge - lo ca l of m on th s w at er fo rm ul a m ilk m ilk ju ic e w at er dr in ks liq ui ds gr ai ns tu be rs A le gu m es hu rt eg gs bu tte r In je ra 1 fo od po ta to es ta bl es fru it ch ild re n –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – BR EA ST FE ED IN G C H IL D RE N –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – < 2 1. 4 0. 0 0. 0 0. 1 0. 0 0. 2 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 19 6 2- 3 2. 6 0. 1 0. 2 0. 1 0. 1 0. 4 0. 2 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 23 9 4- 5 4. 5 0. 3 0. 4 0. 6 0. 2 0. 8 0. 5 0. 3 0. 2 0. 0 0. 1 0. 1 0. 0 0. 1 0. 1 0. 1 0. 2 0. 0 0. 0 0. 0 21 6 6- 7 5. 5 0. 8 0. 6 0. 7 0. 4 1. 3 1. 0 0. 7 1. 1 0. 0 0. 3 0. 2 0. 1 0. 4 0. 2 0. 5 0. 4 0. 2 0. 2 0. 0 21 6 8- 9 6. 1 1. 0 0. 6 0. 9 0. 5 1. 7 2. 1 0. 7 1. 6 0. 1 0. 6 0. 5 0. 3 1. 2 0. 5 1. 6 0. 6 0. 6 0. 3 0. 2 19 1 10 -1 1 6. 3 1. 2 0. 9 1. 3 0. 6 2. 1 2. 2 0. 5 2. 0 0. 2 0. 4 0. 7 0. 3 1. 2 0. 7 3. 0 1. 2 0. 9 0. 5 0. 3 18 7 12 -1 5 6. 3 1. 4 1. 1 1. 4 0. 8 2. 0 3. 2 0. 9 1. 9 0. 3 0. 9 0. 9 0. 5 1. 5 1. 4 3. 6 1. 3 0. 9 0. 8 0. 4 32 3 16 -1 9 6. 7 1. 1 0. 6 2. 0 0. 6 2. 2 4. 8 1. 0 2. 6 0. 5 1. 0 1. 7 0. 4 2. 2 2. 2 4. 8 1. 8 0. 9 0. 9 0. 4 25 6 20 -2 3 6. 6 1. 0 0. 9 1. 9 0. 7 1. 9 4. 4 0. 8 2. 2 0. 5 0. 8 1. 2 0. 5 1. 8 1. 7 4. 9 2. 2 1. 0 1. 0 0. 4 16 7 24 -2 7 6. 5 0. 8 0. 7 1. 6 0. 6 2. 7 4. 2 1. 0 2. 0 0. 3 0. 7 1. 6 0. 6 2. 1 2. 0 5. 1 2. 1 1. 2 1. 1 0. 1 13 3 28 -3 1 (6 .5 ) (1 .0 ) (0 .5 ) (2 .0 ) (0 .4 ) (3 .5 ) (4 .3 ) (1 .3 ) (1 .8 ) (0 .4 ) (1 .0 ) (1 .7 ) (0 .3 ) (0 .9 ) (1 .7 ) (5 .3 ) (2 .1 ) (0 .9 ) (0 .6 ) (0 .2 ) 42 32 -3 5 (6 .9 ) (1 .7 ) (0 .8 ) (1 .4 ) (1 .6 ) (2 .5 ) (5 .8 ) (0 .5 ) (2 .2 ) (0 .0 ) (1 .3 ) (0 .8 ) (0 .7 ) (2 .1 ) (3 .4 ) (5 .9 ) (3 .8 ) (0 .3 ) (0 .9 ) (0 .8 ) 26 < 6 2. 9 0. 1 0. 2 0. 3 0. 1 0. 5 0. 2 0. 1 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 65 1 6- 9 5. 8 0. 9 0. 6 0. 8 0. 4 1. 5 1. 5 0. 7 1. 3 0. 1 0. 4 0. 4 0. 2 0. 7 0. 4 1. 0 0. 5 0. 4 0. 3 0. 1 40 7 –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – N O N BR EA ST FE ED IN G C H IL D RE N –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – 16 -1 9 6. 1 2. 7 2. 0 3. 9 1. 9 1. 8 4. 7 1. 6 3. 1 0. 4 2. 1 0. 9 1. 3 2. 9 2. 5 5. 1 2. 9 2. 3 0. 6 1. 0 45 20 -2 3 6. 6 1. 6 1. 2 2. 5 0. 9 1. 9 5. 6 1. 3 2. 0 0. 4 1. 2 1. 3 1. 0 2. 2 2. 3 6. 0 2. 4 1. 0 1. 1 0. 5 10 3 24 -2 7 6. 7 1. 6 0. 4 2. 7 0. 5 2. 2 5. 5 1. 2 2. 7 0. 4 1. 2 1. 6 0. 8 2. 6 2. 6 5. 7 2. 5 1. 4 1. 6 0. 3 21 8 28 -3 1 6. 6 1. 6 1. 0 2. 2 0. 7 2. 8 4. 6 1. 2 2. 9 0. 9 1. 3 1. 9 0. 8 2. 3 2. 2 5. 6 2. 5 1. 1 1. 3 0. 6 16 0 32 -3 5 6. 8 1. 6 1. 0 2. 3 1. 2 2. 0 5. 6 0. 9 2. 2 0. 7 1. 2 2. 2 0. 9 2. 1 2. 4 6. 1 3. 1 1. 2 1. 4 0. 6 16 9 –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– –– – N ot e: B re as tfe ed in g st at us r ef er s to a “ 24 h ou r” r ec al l p er io d (y es te rd ay a nd la st n ig ht ). Fo r th e no nb re as tfe ed in g ch ild re n, fi gu re s fo r ch ild re n un de r 16 m on th s a re n ot s ho w n be ca us e of fe w er th an 2 5 un w ei gh te d ca se s in e ac h gr ou p. 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. 1 P an ca ke -li ke b re ad m ad e fro m s or gh um o r t ef f Infant Feeding and Nutritional Status of Children and Women | 171 10.7 MICRONUTRIENT SUPPLEMENTATION Micronutrients are essential for the metabolic processes in the body and play a major role in nutrition and health. Micronutrient deficiencies constitute a serious threat to child health and survival. The 2002 EDHS survey collected various types of data that are useful in assessing the micronutrient intake among young children and women. Use of Iodized Salt in Households Disorders induced by dietary iodine deficiency constitute a major global nutrition concern. Iodine deficiency in the fetus leads to increased rates of abortion, stillbirths, congenital anomalies, cretinism, psychomotor defects, and neonatal mortality. In children and adults, the effects are demonstrated as goiter, hypothyroidism, impaired mental functions, retarded mental and physical development, and diminished school performance. Iodine deficiency can be avoided by using salt that has been fortified with iodine. In the 2002 EDHS survey, the iodine content of the salt used in the household was measured using a rapid test kit developed by UNICEF. The test kit consists of ampoules of a stabilized starch solution and a weak acid-based solution. A drop of the starch solution was squeezed onto a salt sample obtained in the household, causing the salt to change color if it was fortified with iodine. The interviewers conducting the test matched the color of the salt to a color chart included with the test kit to determine the level of iodine. Salt containing at least 15 parts per million (ppm) is considered adequately iodized. Ninety-six percent of households interviewed in the EDHS provided salt for testing, while 3 percent had no salt available in the household. Table 10.7 shows that slightly more than two-thirds of households use adequately iodized salt for cooking (15 ppm or more). Rural households are less likely to use adequately iodized salt (60 percent) than urban households (81 percent). It is not surprising that use of adequately iodized salt increases from 52 percent in households in the lowest quintile of the wealth index to 85 percent in households in the highest quintile. Households in the two Red Sea zobas, Semenawi Keih Bahri and Debubawi Keih Bahri, are least likely to use adequately iodized salt. Although more than two-thirds of households in Gash- Barka use iodized salt, the iodine content of the salt used in one in ten households is below 15 ppm. 172 | Infant Feeding and Nutritional Status of Children and Women Table 10.7 Iodization of household salt Percent distribution of households with salt tested for iodine content by level of iodine in salt (parts per million), per- centage of households tested, and percentage of households with no salt, according to background characteristics, Eri- trea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Level of iodine in household salt Percentage Percentage –––––––––––––––––––––––––––––– Number of of house- Number Background None Inadequate Adequate of households holds with of characteristic (0 ppm) (<15 ppm) ( 15+ ppm) Total households tested no salt households ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Urban 14.8 4.6 80.5 100.0 3,507 96.5 2.3 3,634 Asmara 11.5 5.3 83.1 100.0 1,632 97.3 1.6 1,678 Other towns 17.7 4.0 78.3 100.0 1,875 95.8 3.0 1,956 Rural 32.6 7.5 60.0 100.0 5,510 95.7 2.9 5,755 Zoba Debubawi Keih Bahri 41.8 7.2 51.0 100.0 305 92.8 6.5 328 Maekel 15.5 5.4 79.1 100.0 2,068 97.5 1.3 2,122 Semenawi Keih Bahri 45.6 5.6 48.7 100.0 1,135 95.0 3.9 1,195 Anseba 24.4 5.4 70.2 100.0 1,155 97.8 1.6 1,181 Gash-Barka 32.6 10.3 57.1 100.0 1,714 95.2 3.1 1,800 Debub 19.2 5.2 75.6 100.0 2,640 95.6 2.9 2,763 Wealth index Lowest 38.8 8.9 52.3 100.0 1,481 96.7 2.5 1,532 Second 36.1 8.0 55.9 100.0 1,829 95.4 3.3 1,918 Middle 30.6 6.6 62.8 100.0 1,940 95.1 3.2 2,041 Fourth 14.7 4.5 80.8 100.0 1,929 96.0 2.8 2,011 Highest 10.9 4.4 84.8 100.0 1,836 97.3 1.5 1,887 Total 25.7 6.4 68.0 100.0 9,017 96.0 2.7 9,389 Micronutrient Status of Young Children In addition to receiving vitamin A through diet, vitamin A supplements may be received as part of primary prevention programs. Women may get vitamin A supplements during the postpartum period to benefit both the women and their breastfeeding children. Vitamin A is an essential micronutrient for the normal functioning of the visual system, growth and development, resistance to disease, and reproduction. Severe vitamin A deficiency is associated with total loss of vision or with other vision impairments including night blindness. Vitamin A is believed to improve immunity and hence reduce mortality rates in children and women. Table 10.8 shows the percentage of youngest children under three years who consumed fruits and vegetables rich in vitamin A in the seven days preceding the survey, and the percentage of children 6-59 months old who received vitamin A supplements in the six months before the survey. Table shows that 23 percent of children under three years consumed fruits and vegetables rich in vitamin A and 38 percent of children 6-59 months old were reported to have received a vitamin A supplement in the previous 6 months. Infant Feeding and Nutritional Status of Children and Women | 173 Table 10.8 Micronutrient intake among children Percentage of youngest children under age three living with the mother who consumed fruits and vegetables rich in vitamin A in the seven days preceding the survey, and percentage of children age 6-59 months who received vitamin A supplements in the six months preceding the survey, and percentage of children under five living in households using adequately iodized salt, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number Children Consumed of youngest Number living in fruits and children of households Number vegetables under three Consumed children using of Background rich in living with vitamin A 6-59 adequately children characteristic vitamin A1 mother supplements months iodized salt2 under five –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age in months <6 0.7 651 na na 69.8 638 6-9 12.1 416 31.6 422 68.7 406 10-11 27.1 194 37.5 199 67.7 191 12-23 31.2 922 41.6 959 65.9 930 24-35 39.0 749 41.5 1,042 68.4 1,002 36-47 na na 42.2 1,205 65.3 1,159 48-59 na na 30.7 1,262 70.0 1,215 Sex Male 24.1 1,474 38.1 2,615 67.3 2,844 Female 22.8 1,457 37.9 2,472 68.4 2,698 Birth order 1 27.0 547 41.2 938 69.8 1,046 2-3 26.0 1,015 40.8 1,796 72.3 1,931 4-5 20.6 659 35.9 1,119 65.5 1,205 6+ 19.6 710 33.5 1,235 62.1 1,359 Breastfeeding status Breastfeeding 17.5 2,191 38.6 1,597 66.4 2,183 Not breastfeeding 41.0 735 37.8 3,473 68.7 3,342 Residence Total urban 41.5 990 49.9 1,743 80.9 1,875 Asmara 52.6 428 56.8 734 84.6 800 Other towns 33.0 562 44.9 1,010 78.2 1,075 Rural 14.3 1,942 31.8 3,345 61.2 3,667 Zoba Debubawi Keih Bahri 15.6 92 22.1 152 44.1 166 Maekel 47.3 548 51.7 964 80.1 1,054 Semenawi Keih Bahri 14.5 385 36.0 687 47.9 752 Anseba 20.8 439 37.3 780 70.5 858 Gash-Barka 18.0 556 32.2 926 56.5 991 Debub 18.2 912 35.8 1,579 76.5 1,721 Mother’s education No education 14.7 1,798 32.9 3,210 60.2 3,475 Primary 30.1 526 38.1 932 77.0 1,005 Middle 36.6 218 44.4 320 85.6 367 Secondary + 47.6 390 60.7 625 83.3 694 Mother’s age at birth <20 24.3 367 37.1 623 67.0 696 20-24 23.7 648 40.9 1,230 70.9 1,322 25-29 25.4 802 37.4 1,284 67.1 1,388 30-34 20.3 454 41.1 867 64.9 950 35-49 22.5 662 33.6 1,084 68.2 1,186 Wealth index Lowest 11.6 606 30.3 1,090 54.8 1,204 Second 10.3 608 33.0 1,055 55.7 1,144 Middle 18.3 625 32.7 1,042 64.7 1,127 Fourth 34.6 604 43.5 1,059 79.7 1,138 Highest 47.2 488 54.1 842 89.1 927 Total 23.4 2,932 38.0 5,088 67.8 5,542 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Information on vitamin A supplements is based on mother’s recall. Total includes 18 children with missing informa- tion on breastfeeding status, who are not shown separately. na = Not applicable 1 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, green leafy vegetables, mango, papaya, and other locally grown fruits and vegetables that are rich in vitamin A 2 Salt containing 15 ppm of iodine or more. Excludes children in households in which salt was not tested. 174 | Infant Feeding and Nutritional Status of Children and Women As expected, youngest children (under 6 months) were least likely to have consumed some type of food rich in vitamin A because most are being exclusively breastfed and only 4 percent are receiving complementary foods (see Table 10.2). As age increases, the consumption of foods rich in vitamin A and also the consumption of vitamin A supplements increase. For example, 12 percent of children age 6-9 months and 39 percent of children age 24-25 months consumed fruits and vegetables rich in vitamin A in the week before the survey. Rural children under three years are only one-third as likely to eat foods rich in vitamin A as children in urban areas. Rural children are also less likely than urban children to receive vitamin A supplements, but the differences are not as large. Zoba differentials are substantial; supplementation of vitamin A is as low as 22 percent in zoba Debubawi Keih Bahri and as high as 52 percent in zoba Maekel. Vitamin A supplementation and consumption of fruits and vegetables rich in vitamin A are positively associated with mother’s education. Compared with children of uneducated mothers, children of mothers with at least some secondary education are twice as likely to receive vitamin A supplements, and more than thrice as likely to consume foods rich in vitamin A. The relationship between the wealth index and vitamin A supplementation and consumption of foods rich in vitamin A is also positive, and the disparity between the highest and the lowest quintiles is wider for consumption of foods rich in vitamin A than by education. Differences in vitamin A supplementation by other background characteristics are minimal. Sixty-eight percent of children under five live in households that use adequately iodized salt–the same as the proportion of households that possess adequately iodized salt. Differentials in the proportion of children living in households using adequately iodized salt by residence, zoba, and the wealth index are similar to those for households (Table 10.7). The differentials by other background characteristics show the same pattern as the differentials in vitamin A supplementation among children under five. Micronutrient Supplementation for Women Vitamin A Supplementation Provision of vitamin A supplements to women after delivery of a child is intended to boost stores of vitamin A in the woman and ensure adequate delivery of this essential micronutrient to the child in breast milk. The 2002 EDHS survey asked women whether they had received a vitamin A supplement in the two-month period after delivery of their last born child in the five years preceding the survey. The women were also asked whether they had experienced any vision problems during pregnancy. Night blindness in pregnancy is a common manifestation of vitamin A deficiency. Table 10.9 shows that 13 percent of mothers received a vitamin A supplement during the postnatal period. Variations in postpartum vitamin A supplementation by child’s birth order and age of the mother are minimal. Vitamin A supplementation is much higher in urban areas than rural areas, higher in zoba Maekel than other zobas, and higher among women with some secondary or higher education than women with no schooling. Table 10.9 shows that 4 percent of women with a recent birth experienced night blindness, an indication of vitamin A deficiency. Night blindness during pregnancy is more prevalent among women age 35-49, women in rural areas, women without schooling, and among mothers with sixth- or higher- order births. Zoba Debub has the highest prevalence of night blindness among mothers and zoba Maekel, the lowest. Infant Feeding and Nutritional Status of Children and Women | 175 Table 10.9 Micronutrient intake among mothers Percentage of women with a birth in the five years preceding the survey who received a vitamin A dose in the first two months after delivery, percentage who suffered from night blindness during pregnancy, percentage who took iron tablets for specific numbers of days, and percentage who live in households using adequately iodized salt, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Suffered Living in Received night blindness Number of days iron tablets households vitamin A during pregnancy were taken during pregnancy using ade- dose ––––––––––––––––– ––––––––––––––––––––––––––––––––––––– Number quately Number Background post- Don’t know/ of iodized of characteristic partum1 Reported Adjusted2 None <60 60-89 90+ missing women salt3 women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age at birth <20 15.1 8.9 3.7 58.2 38.3 0.7 0.9 1.8 510 67.1 501 20-24 12.7 7.8 2.8 56.4 39.1 1.1 0.5 2.8 946 70.8 921 25-29 12.8 10.1 3.3 58.6 37.5 1.0 0.9 2.0 1,050 67.5 1,007 30-34 15.7 12.3 4.0 60.1 35.8 1.2 0.8 2.2 679 65.0 657 35-49 12.4 17.9 5.6 64.6 31.8 0.6 0.6 2.4 990 67.9 954 Number of children ever born 1 15.9 6.5 2.3 57.8 37.8 0.8 1.3 2.3 761 70.5 747 2-3 13.5 8.7 3.4 57.9 38.0 1.0 0.8 2.4 1,411 72.0 1,366 4-5 13.3 13.3 4.3 61.1 35.6 0.8 0.5 2.0 922 65.7 880 6+ 11.7 17.7 5.3 62.3 33.8 1.0 0.5 2.4 1,081 62.4 1,048 Residence Total urban 21.9 6.5 2.3 54.5 39.9 1.2 1.4 3.1 1,448 80.6 1,415 Asmara 28.9 3.6 1.8 57.6 37.0 1.0 2.4 2.1 618 83.4 611 Other towns 16.8 8.7 2.6 52.2 42.0 1.3 0.7 3.8 830 78.4 803 Rural 8.9 14.4 4.8 62.5 34.5 0.8 0.4 1.9 2,727 61.0 2,626 Zoba Debubawi Keih Bahri 10.7 19.2 3.0 64.1 31.3 2.0 0.4 2.1 136 45.5 130 Maekel 25.8 3.4 1.5 55.2 39.1 0.8 1.9 3.0 801 79.0 792 Semenawi Keih Bahri 12.7 11.9 4.5 50.6 44.1 1.5 0.3 3.5 560 49.4 542 Anseba 12.7 9.9 2.2 57.7 39.8 0.6 0.5 1.4 589 71.5 576 Gash-Barka 11.4 13.7 4.4 57.6 38.6 1.4 0.3 2.1 789 56.3 753 Debub 8.0 15.4 5.7 68.1 28.8 0.6 0.6 2.0 1,301 76.4 1,247 Mother’s education No education 9.9 15.1 4.7 62.6 34.0 1.0 0.3 2.1 2,581 60.2 2,482 Primary 11.7 8.7 3.6 57.8 37.7 0.6 1.2 2.7 766 76.2 743 Middle 18.1 2.7 0.5 49.9 45.6 0.7 0.5 3.3 293 83.3 285 Secondary + 30.5 3.8 2.3 53.6 40.6 1.4 2.2 2.1 534 83.8 530 Total 13.4 11.6 3.9 59.7 36.3 0.9 0.7 2.3 4,175 67.9 4,040 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: For women with two or more live births in the five-year period, data refer to the most recent birth. 1 In the first two months after delivery 2 Women who reported night blindness but did not report difficulty with vision during the day 3 Salt containing 15 ppm of iodine or more. Excludes women in households in which salt was not tested. Iron Supplementation Iron-deficiency anemia is a major threat to maternal health; it contributes to low birth weight, lowered resistance to infection, poor cognitive development, and decreased work capacity. Furthermore, anemia increases morbidity from infections because it adversely affects the body’s immune response. International recommendations are that iron tablets be taken daily for at least three months during pregnancy. 176 | Infant Feeding and Nutritional Status of Children and Women In the EDHS survey, women who had a recent birth were asked whether they had bought or received any iron tablets during their last pregnancy. If so, the woman was asked the number of days the iron tablets were actually taken during that pregnancy. Table 10.9 shows that four in ten mothers received iron tablets for the last birth in the five years preceding the survey but almost all of them took the tablets for less than 60 days. Coverage of iron supplementation was lower among mothers age 35-49 and mothers in zobas Debubawi Keih Bahri and Debub. Coverage of iron supplementation shows a slight positive relationship with education. In Eritrea, the Ministry of Health gives pregnant women 120 iron tablets for 60 days, when considered necessary. Women are advised to take two tablets a day. One-third of women who received iron tablets during pregnancy for the most recent birth in the five years before the survey took iron tablets for 6 days or less; two-thirds took tablets for 18 days or less. Only 10 percent of women took iron tablets for more than 30 days (data not shown). With one of the highest levels of antenatal care in sub-Saharan Africa, it is surprising that Eritrea has such low coverage for iron supplementation during pregnancy. Use of Iodine-Fortified Salt Sixty-eight percent of women live in households with adequately iodized salt. The differentials for women living in households that use adequately iodized salt by background characteristics show the same patterns as differentials for children. 10.8 NUTRITIONAL STATUS OF CHILDREN UNDER AGE FIVE The nutritional well being of young children reflects household, community, and national investment in family health and contributes both directly and indirectly to the country’s development. In collecting anthropometric data (height and weight), the 2002 EDHS survey permits objective measurement and evaluation of the nutritional status of young children in Eritrea. This evaluation allows identification of subgroups of the child population that are at increased risk of growth faltering, disease, impaired mental development, and death. In the 1995 EDHS, anthropometric data were restricted to children born to women interviewed with the Women’s Questionnaire. These data did not represent all children because they exclude children whose mothers were not in the household at the time of the interview or were not interviewed for some other reason. To overcome biases in estimating children’s nutritional status in the 2002 EDHS, all children under age five listed in the Household Questionnaire were weighed and measured. Measures of Nutritional Status in Childhood Evaluation of nutritional status is based on the rationale that in a well-nourished population there is a statistically predictable distribution of children of a given age with respect to height and weight. Use of a standard reference population facilitates analysis of any given population over time as well as comparisons among population subgroups. One of the most commonly used reference populations, and the one used in this report, is the U.S. National Center for Health Statistics (NCHS) standard, which is recommended for use by the World Health Organization. In the reference population, only 2.3 percent of children fall below minus two standard deviations (-2 SD) for each of the three indices. Three standard indices of physical growth that describe the nutritional status of children are presented: • height-for-age • weight-for-height • weight-for-age Infant Feeding and Nutritional Status of Children and Women | 177 Each of these indices measures different aspects of children’s nutritional status. The height-for- age index is a measure of linear growth retardation and cumulative growth deficit. Children who are more than minus two standard deviations (-2 SD) below the median of the NCHS reference population in terms of height-for-age are considered short for their age, or stunted, a condition that reflects the cumulative effect of chronic malnutrition. If children are more than minus three standard deviations (-3 SD) below the reference median, then they are considered severely stunted. Children between -2 SD and -3 SD are considered moderately stunted. Weight-for-height describes a child’s current nutritional status. Children who are more than minus two standard deviations (-2 SD) below the reference median are considered thin for their height, or wasted. Wasting represents the failure to receive adequate food in the period immediately preceding the survey or may be the result of a recent episode of illness, causing loss of weight and the onset of malnutrition. As with stunting, if children are more than minus three standard deviations (-3 SD) below the reference median, they are considered severely wasted. Severe wasting is closely linked to mortality risk. Weight-for-age is a composite index of weight-for-height and height-for-age and thus does not distinguish between chronic malnutrition (stunting) and acute malnutrition (wasting). Children can be underweight for their age because they are stunted, because they are wasted, or because they are wasted and stunted. Children whose weight-for-age is more than minus two standard deviations (-2 SD) below the median of the reference population are underweight for their age, while those who are below minus three standard deviations (-3 SD) from the reference median are severely underweight. The weight-for- age index is sometimes used as a proxy of a population’s health. Levels of Child Malnutrition In the 2002 EDHS, data were complete for 91 percent of children. Table 10.10 shows the percentage of children under five years classified as malnourished according to height-for-age, weight- for-height, and weight-for-age indices, by children’s background characteristics. Overall, 38 percent of children under five are stunted (short for their age) and 16 percent are severely stunted. Thirteen percent of children under age five are wasted (thin for their height) and 2 percent are severely wasted. Forty percent of children under five are underweight (low weight-for-age)—which reflects stunting, wasting, or both. Twelve percent of children are severely underweight. Differentials by Child’s Characteristics Figure 10.2 shows the percentage of children who are malnourished by age, in terms of the three indicators of nutritional status. It is clear from this graph that deterioration in nutritional status begins a few months after birth. A rapid worsening in the linear growth of Eritrean children takes place during the first year, especially late in the first year, and continues through the second year, when stunting peaks at 57-59 percent at age 21-22 months. The prevalence of stunting remains above 40 percent through the fifth year. Weight-for-age malnutrition follows a similar pattern but increases rapidly initially and peaks at 55 percent at age 22 months, and then drops off somewhat faster than stunting. Wasting shows earlier worsening of nutritional status than either stunting or underweight, and peaks at 24 percent at age 11-12 months. 178 | Infant Feeding and Nutritional Status of Children and Women EDHS 2002 Figure 10.2 Nutritional Status of Children Under Age Five Note: Plotted values are smoothed by a five-month moving average. ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * # # ## ### # # # ## # # # ## ## ## #### #### ## ### ### ########## ## ########### 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 Age in Months 0 10 20 30 40 50 60 70 Percent Stunted Wasted Underweight# * ! Table 10.10 shows that for all nutritional indices, boys are slightly more likely to be malnourished than girls. First-order births and children born after a long birth interval (more than 47 months) are less likely to be stunted and underweight than higher-order births and children born after shorter birth intervals. The size of the baby at birth is related to the child’s future health and nutritional status. Birth weight or size at birth is an important determinant of the child’s nutritional status in the future. According to Table 10.10, for each nutritional index, a higher percentage of children who were reported as small or very small at birth are malnourished, compared with children who were average or larger in size. Differentials by Mother’s Characteristics Table 10.11 and Figure 10.3 show nutritional status of children by mother’s characteristics. Children born to young mothers (age 15-19) are more likely to be first births and less likely to be stunted or underweight than children born to older mothers. A child’s nutritional status is in part determined by the socioeconomic situation of his/her household, which in turn is affected by where that household is physically located, by the wealth index of the household, and the educational level of the child’s mother. For instance, rural children are 50 percent more likely to be stunted and underweight, and 69 percent more likely to be wasted, than urban children (Table 10.11). Differentials in malnutrition as indicated by each index are even greater between children in rural areas and Asmara. Children in rural areas are more than twice as likely to be stunted and underweight, and more than three times as likely to be wasted as children in Asmara. Among zobas, malnutrition is more prevalent in zobas Gash-Barka, Anseba, and Semenawi Keih Bahri than in other zobas. In these three zobas, 41-45 percent of children under five years are stunted, 16-18 percent are wasted, and 47-51 percent are underweight. The prevalence of severe malnutrition among children in these zobas is also higher than in other zobas. By contrast, in zoba Maekel, which has the lowest rates of childhood malnutrition, less than one-fourth of children under five are stunted, the same proportion are underweight, and 6 percent are wasted. Mother’s education is negatively correlated with childhood Infant Feeding and Nutritional Status of Children and Women | 179 Table 10.10 Nutritional status of children by child’s characteristics Percentage of children under five years classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by child’s characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Height-for-age Weight-for-height Weight-for-age (stunted) (wasted) (underweight) ––––––––––––––––––––––– ––––––––––––––––––––––– ––––––––––––––––––––––– Percent- Percent- Percent- Percent- Percent- Percent- age age Mean age age Mean age age Mean Number Child’s below below Z-score below below Z-score below below Z-score of characteristic -3 SD -2 SD1 (SD) -3 SD -2 SD1 (SD) -3 SD -2 SD1 (SD) children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age in months <6 0.6 3.0 0.1 0.8 5.8 -0.3 0.2 4.5 -0.1 573 6-9 2.9 13.1 -0.5 3.3 15.0 -0.8 5.3 22.6 -1.1 411 10-11 7.2 26.6 -1.1 1.3 22.5 -1.1 13.4 47.1 -1.8 194 12-23 18.5 46.3 -1.8 4.6 20.8 -1.2 15.5 52.4 -1.9 895 24-35 23.9 48.3 -1.9 1.7 12.9 -1.0 19.6 51.9 -2.0 1,007 36-47 22.4 45.3 -1.9 1.2 10.7 -0.9 11.1 41.6 -1.8 1,168 48-59 15.7 41.4 -1.7 1.4 8.7 -0.9 9.2 39.2 -1.7 1,218 Sex Male 16.7 38.9 -1.5 2.6 13.7 -0.9 11.2 40.5 -1.6 2,781 Female 15.8 36.3 -1.5 1.4 11.3 -0.9 11.8 38.8 -1.6 2,686 Birth order2 1 12.5 29.6 -1.3 2.2 12.9 -0.9 9.3 35.3 -1.5 946 2-3 16.0 37.3 -1.5 2.1 11.1 -0.9 10.1 39.6 -1.6 1,826 4-5 18.1 40.1 -1.6 1.6 12.6 -0.9 13.5 40.3 -1.7 1,156 6+ 17.8 41.9 -1.6 2.0 13.9 -0.9 12.5 42.2 -1.7 1,311 Birth interval in months2 First birth3 12.9 29.9 -1.3 2.2 12.9 -0.9 9.4 35.6 -1.5 954 <24 18.1 43.2 -1.7 1.4 11.7 -1.0 12.4 42.0 -1.7 786 24-47 17.8 40.2 -1.6 2.2 12.4 -0.9 12.0 41.0 -1.7 2,658 48+ 13.8 33.3 -1.3 1.7 12.8 -0.9 10.3 37.5 -1.4 842 Size at birth2 Very small 18.6 42.1 -1.7 3.7 17.7 -1.1 16.4 48.7 -1.9 917 Small 21.9 43.2 -1.8 3.0 15.9 -1.1 17.9 48.8 -1.9 495 Average or larger 15.0 35.8 -1.4 1.5 10.9 -0.9 9.4 36.4 -1.5 3,993 Missing 17.2 48.5 -1.6 3.0 17.9 -0.9 18.8 37.2 -1.7 61 Total 16.3 37.6 -1.5 2.0 12.6 -0.9 11.5 39.6 -1.6 5,466 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Table is based on children who stayed in the household the night before the interview. Each of the indices is expressed in standard deviation units (SD) from the median of the NCHS/CDC/WHO International Reference Population. The percentage of children who are more than three or more than two standard deviations below the median of the International Reference Popula- tion (-3 SD and -2 SD) are shown according to child’s characteristics. Table is based on children with valid dates of birth (month and year) and valid measurement of both height and weight. 1 Includes children who are below -3 standard deviations from the International Reference Population median 2 Excludes children whose mothers were not interviewed 3 First born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval. 180 | Infant Feeding and Nutritional Status of Children and Women Table 10.11 Nutritional status of children by mother’s characteristics Percentage of children under five years classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by mother’s characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Height-for-age Weight-for-height Weight-for-age (stunted) (wasted) (underweight) ––––––––––––––––––––––– ––––––––––––––––––––––– ––––––––––––––––––––––– Percent- Percent- Percent- Percent- Percent- Percent- age age Mean age age Mean age age Mean Number Mother’s below below Z-score below below Z-score below below Z-score of characteristic -3 SD -2 SD1 (SD) -3 SD -2 SD1 (SD) -3 SD -2 SD1 (SD) children ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Total urban 10.5 27.9 -1.2 1.3 8.6 -0.8 5.8 29.1 -1.3 1,826 Asmara 5.8 17.9 -0.8 0.8 4.0 -0.6 1.4 18.2 -1.0 744 Other towns 13.8 34.9 -1.4 1.6 11.7 -0.9 8.8 36.7 -1.5 1,081 Rural 19.1 42.5 -1.7 2.4 14.5 -1.0 14.3 44.9 -1.8 3,641 Zoba Debubawi Keih Bahri 15.4 37.4 -1.4 2.8 13.8 -0.9 12.1 41.1 -1.6 156 Maekel 8.5 23.0 -1.0 0.9 6.1 -0.6 3.5 23.4 -1.1 984 Semenawi Keih Bahri 22.0 41.9 -1.7 3.0 18.0 -1.1 18.0 51.2 -1.9 752 Anseba 17.0 40.5 -1.6 2.3 15.6 -1.1 13.2 46.7 -1.8 873 Gash-Barka 21.2 44.8 -1.7 2.6 16.9 -1.1 18.6 49.6 -1.9 963 Debub 15.1 38.7 -1.5 1.6 9.8 -0.8 8.3 34.6 -1.5 1,738 Mother’s education No education 20.2 44.6 -1.7 2.5 14.5 -1.0 15.1 46.7 -1.8 3,397 Primary 11.7 30.2 -1.4 1.2 10.2 -0.8 6.4 32.8 -1.4 1,325 Middle 4.5 16.1 -0.7 1.3 6.6 -0.6 2.1 17.5 -1.0 574 Secondary + (4.1) (18.2) (-0.6) (0.0) (4.2) (-0.5) (0.0) (10.1) (-0.8) 54 Age2 15-19 12.7 29.0 -1.2 2.0 12.6 -0.8 10.3 34.5 -1.3 214 20-24 15.9 36.0 -1.5 2.2 10.8 -0.9 10.3 39.4 -1.6 943 25-29 15.5 35.5 -1.5 2.0 12.1 -0.9 10.2 38.1 -1.6 1,403 30-34 17.4 41.3 -1.6 2.2 14.3 -0.9 12.9 41.8 -1.7 1,109 35-49 16.7 39.0 -1.5 1.7 12.7 -0.9 12.3 40.2 -1.6 1,798 Wealth index2 Lowest 20.5 44.8 -1.7 3.1 17.7 -1.1 18.0 49.3 -1.9 1,183 Second 22.1 45.3 -1.8 2.5 15.6 -1.0 16.5 47.4 -1.8 1,157 Middle 17.8 41.5 -1.7 1.8 12.5 -0.9 11.6 42.4 -1.7 1,133 Fourth 12.5 33.9 -1.4 1.3 8.9 -0.8 6.2 33.8 -1.5 1,123 Highest 5.5 17.6 -0.8 0.9 6.3 -0.7 2.5 20.1 -1.0 871 Mother's status Mother interviewed 16.3 37.7 -1.5 2.0 12.5 -0.9 11.3 39.6 -1.6 5,240 Mother not interviewed 2 Mother in household 15.3 39.7 -1.6 3.1 15.2 -1.1 14.5 46.5 -1.8 115 Mother not in the household3 15.9 33.3 -1.4 1.9 14.5 -1.0 16.2 32.8 -1.6 112 Total 16.3 37.6 -1.5 2.0 12.6 -0.9 11.5 39.6 -1.6 5,466 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Table is based on children who stayed in the household the night before the interview. Each of the indices is expressed in standard deviation units (SD) from the median of the NCHS/CDC/WHO International Reference Population. The percentage of children who are more than three or more than two standard deviations below the median of the International Reference Popula- tion (-3 SD and -2 SD) are shown according to demographic characteristics. Table is based on children with valid dates of birth (month and year) and valid measurement of both height and weight. Figures in parentheses are based on 25-49 unweighted cases. 1Includes children who are below -3 standard deviations (SD) from the International Reference Population median 2For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the household schedule. 3Includes children whose mothers are deceased Infant Feeding and Nutritional Status of Children and Women | 181 Figure 10.3 Percentage of Children Under Age Five that Are Underweight (weight-for-age below -2 SD) by Background Characteristics Note: Weight-for-age is a composite index of height-for-age and weight-for-height. 0 29 18 37 45 41 23 51 47 50 35 47 33 18 10 35 39 38 42 40 49 47 42 34 20 RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub MOTHER’S EDUCATION No education Primary Middle Secondary + MOTHER’S AGE 15-19 20-24 25-29 30-34 35-49 WEALTH INDEX Lowest Second Middle Fourth Highest 0 10 20 30 40 50 60 Percentage below -2 SD EDHS 2002 malnutrition. Children of mothers who have not attended school are two and one-half times more likely to be stunted, three and one-half times more likely to be wasted, and four and one-half times more likely to be underweight than children of mothers who have at least some secondary education. Levels of stunting, wasting, and underweight are negatively correlated with household wealth. Children’s level of malnutrition decreases as household wealth increases from the lowest to the highest quintile. The children from households in the lowest quintile of the wealth index are two and one-half times more likely to be stunted and underweight than children from households in the highest quintile. The disparity in malnutrition between the lowest and the highest quintiles is even greater for wasting. Although the number of children whose mothers were in the household but were not interviewed is small, these children have higher rates of stunting and underweight than other children. Surprisingly, compared with children whose mothers were interviewed, the children whose mothers were not in the household are less likely to be stunted and moderately underweight but more likely to be severely underweight. Comparison between the results of the 2002 EDHS and the 1995 EDHS is complicated by the fact that unlike the earlier survey, the 2002 EDHS covers children under five and includes anthropometric measurements for children whose mothers were not interviewed. However, if the comparison is limited to children under three years whose mothers were interviewed, it appears that since 1995, the nutritional 182 | Infant Feeding and Nutritional Status of Children and Women status of children—as indicated by three measures of nutritional status—has improved slightly (Figure 10.4). EDHS 2002 Figure 10.4 Trends in Levels of Undernutrition among Children Under Age Three, 1995 and 2002 38 16 44 33 15 38 Stunted Wasted Underweight 0 10 20 30 40 50 1995 2002 EDHS 1995 and EDHS 2002 10.9 NUTRITIONAL STATUS OF WOMEN The 2002 EDHS collected data on the height and weight of all women age 15-49. Several measures have been used to assess the nutritional status of women (Krasovec and Anderson, 1991). In this report, two indices are presented—height and body mass index (BMI). BMI is an indicator that combines height and weight measures. Table 10.12 presents the mean values of the anthropometric indicators and the proportions of women falling into high-risk categories, according to background characteristics. Height of a woman is associated with past socioeconomic status and nutrition during her childhood and adolescence. Women’s height is also used to predict the risk of difficult delivery, since small stature is often associated with small pelvis size and the potential for obstructed labor. The risk of having a low-birth-weight baby is higher in short women. The cutoff point for height, below which a woman is identified as “at risk,” is in the range of 140-150 cm. As in other DHS surveys, a cutoff point of 145 cm is used for the 2002 EDHS. The mean height of women measured in the 2002 EDHS survey was 156 cm, which is above the critical height of 145 cm. Overall, 2 percent of women are shorter than 145 cm. There are only small differences in the mean height of women by background characteristics. On average, women in Asmara compared with women in rural areas, and women with at least some secondary education compared with women who have not attended school, are 2 cm taller. As in 1995, women in zoba Semenawi Keih Bahri have the shortest mean height and also the highest proportion below 145 cm among all subgroups shown in Table 10.12. Short stature (below 145 cm) is less prevalent (1 percent) among women in Asmara and zobas Debub and Maekel. Infant Feeding and Nutritional Status of Children and Women | 183 Table 10.12 Nutritional status of women by background characteristics Among women age 15-49, mean height, percentage under 145 cm, mean body mass index (BMI), and percentage with specific BMI levels, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Body mass index BMI 1 (kg/m2) ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Height Normal Thin Overweight/obese ––––––––––––––––––––––– –––––––– –––––––––––––––––––––––––––––– ––––––––––––––––––––––––– Percent- 17.0- 16.0- ≥ 25.0 25.0- 30.0 Mean age Number 18.5- 18.4 16.9 <16.0 (over- 29.9 or Number Background height below of Mean 24.9 <18.5 (mildly (moder- (severe- weight/ (over- higher of characteristic in cm 145 cm women BMI (normal) (thin) thin) ately thin) ly thin) obese) weight) (obese) women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 156.3 2.3 1,970 19.3 57.3 39.9 21.9 9.0 8.9 2.8 2.5 0.4 1,875 20-24 156.6 2.7 1,419 19.5 54.2 39.8 20.6 11.6 7.6 6.0 5.7 0.4 1,230 25-29 156.8 1.9 1,528 19.8 51.4 40.6 23.4 10.3 6.9 8.0 7.0 1.1 1,296 30-34 156.0 3.1 1,099 20.2 54.6 36.1 20.3 7.7 8.2 9.2 6.5 2.8 910 35-39 156.3 2.2 1,076 20.8 55.0 30.3 17.9 5.6 6.8 14.6 11.9 2.8 932 40-44 156.3 2.1 817 20.9 49.4 33.5 17.2 8.2 8.0 17.1 13.4 3.7 742 45-49 156.0 3.0 722 20.6 50.4 34.5 19.6 7.6 7.3 15.1 12.6 2.5 701 Residence Total urban 157.0 1.6 3,703 21.0 56.3 28.0 15.9 6.8 5.3 15.7 12.7 3.0 3,390 Asmara 157.7 1.3 1,862 21.6 57.7 23.3 13.4 6.6 3.3 19.1 15.4 3.7 1,730 Other towns 156.4 2.0 1,841 20.5 54.8 33.0 18.6 7.0 7.4 12.2 10.0 2.2 1,659 Rural 155.9 3.0 4,929 19.2 51.9 44.6 24.3 10.5 9.8 3.5 3.1 0.5 4,296 Zoba Debubawi Keih Bahri 155.4 3.5 320 20.0 44.4 43.4 19.2 9.9 14.3 12.3 9.7 2.6 287 Maekel 157.7 1.2 2,220 21.2 57.2 26.0 15.2 6.9 3.9 16.8 13.4 3.4 2,035 Semenawi Keih Bahri 154.0 5.4 1,138 19.6 46.7 44.4 20.9 10.7 12.8 8.9 7.1 1.8 1,016 Anseba 156.4 2.9 1,119 19.5 50.2 43.6 23.4 10.0 10.2 6.2 5.4 0.7 991 Gash-Barka 155.2 3.5 1,482 19.5 50.1 43.2 23.9 9.3 10.0 6.7 5.8 0.8 1,296 Debub 157.2 1.1 2,354 19.5 59.4 37.2 22.5 9.0 5.7 3.4 3.0 0.4 2,060 Education No education 155.6 3.3 4,329 19.4 51.1 43.0 23.5 9.7 9.7 6.0 5.2 0.8 3,757 Primary 156.6 1.7 1,618 20.3 54.4 34.4 19.5 8.1 6.8 11.2 9.5 1.7 1,438 Middle 157.5 1.0 962 20.1 56.0 35.2 19.2 10.5 5.6 8.8 7.1 1.7 887 Secondary + 157.6 1.6 1,723 21.0 58.7 27.5 15.5 6.6 5.4 13.8 10.5 3.4 1,603 Total 156.4 2.4 8,632 20.0 53.8 37.3 20.6 8.9 7.8 8.9 7.3 1.6 7,685 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Excludes pregnant women and women with a birth in the preceding 2 months Various indices of body mass are used to assess thinness and obesity. The most commonly used body mass index (BMI)—also known as the Quetelet index—is defined as the weight in kilograms divided by the height squared in meters. A cutoff point of 18.5 has been recommended for defining thinness or chronic energy deficiency. The BMI can also be used to evaluate the percentage of the population that is overweight and obese. A cutoff point of 25.0 has been recommended for defining “overweight.” Heart disease, diabetes, and high blood pressure are all linked to being overweight. Someone with a BMI of 26 to 27 is about 20 percent overweight, which is generally believed to carry moderate health risks. A BMI of 30 and higher is considered obese and increases the risk of death. The mean BMI among measured women was 20. Slightly more than half of women age 15-49 have a normal BMI (18.5-24.9), and 37 percent have a BMI below 18.5, reflecting a nutritional deficit 184 | Infant Feeding and Nutritional Status of Children and Women (Table 10.12). The 2002 EDHS survey found that 9 percent of Eritrean women are overweight, including 2 percent who are severely overweight or obese. Figure 10.5 and Table 10.12 show that there are large differentials across background characteristics in the percentage of women assessed as malnourished (BMI less than 18.5) or “thin” and overweight (BMI 25 or higher). Four in ten women under age 30 fall below the cutoff of 18.5; thereafter, the proportion of women with chronic energy deficiency drops. Three in ten women age 35-39 and one- third of older women are thin. Rural women are almost 60 percent more likely than urban women to be thin. On the other hand, the proportion of women in urban areas who are overweight and obese is more than four times that of women in rural areas. One in five women in Asmara is either obese (4 percent) or overweight (15 percent). Among zobas, women in Debub and Maekel are the least likely to be thin; more than four in ten women in other zobas have a low BMI (<18.5). Although both zobas Maekel and Debub have lower proportions of women who are considered thin, zoba Maekel (which includes Asmara) has the highest rate of obesity among women age 15-49; zoba Debub has the lowest. EDHS 2002 Figure 10.5 Percentage of Women Age 15-49 with Low Body Mass Index (BMI < 18.5) by Background Characteristics 0 40 40 41 36 30 34 35 28 23 33 45 43 26 44 44 43 37 43 34 35 28 AGE 15-19 20-24 25-29 30-34 35-39 40-44 45-49 RESIDENCE Total urban Asmara Other towns Rural ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub EDUCATION No education Primary Middle Secondary + 0 10 20 30 40 50 Percent HIV/AIDS and Other Sexually Transmitted Infections | 185 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS 11 Acquired Immune Deficiency Syndrome (AIDS) is caused by a human immunodeficiency virus (HIV) that weakens the immune system, making the body susceptible to and unable to recover from other diseases. The HIV/AIDS epidemic has become a serious health and development problem in many countries around the world. The Joint United Nations Programme on HIV/AIDS estimated the number of HIV infections worldwide at about 42 million at the end of 2002, of which 70 percent are found in sub- Saharan Africa (UNAIDS, 2002). Another 20 million people infected with HIV have died from the disease since the beginning of the epidemic—4 million of them were children. Most of these deaths occurred in Africa. The first AIDS case in Eritrea was identified in 1988 in the port city of Assab in zoba Debubawi Keih Bahri. Since then, the disease has spread throughout the country. By the end of 2001, there were about 13,500 cumulative reported clinical AIDS cases (6 percent were children under 15 years) in Eritrea. These represent a small portion of the total cases because of incomplete and inconsistent reporting. At the same time, an estimated 60,000-70,000 persons are infected by HIV, and an estimated 11,000 deaths have been caused by AIDS (MOH, 2001a). According to the 2001 nationwide behavioral and biological survey in Eritrea, HIV seroprevalence among the five targeted population subgroups is as follows: secondary- school students (0.1 percent), general population (2.4 percent), antenatal clinic attendees (2.8 percent), military personnel (4.6 percent) and bar workers (including prostitutes) (22.8 percent) (MOH, 2001b). The survey showed that the knowledge of HIV/AIDS was nearly universal, with 99 percent of all respondents having heard about AIDS. The principal mode of HIV transmission in Eritrea is heterosexual contact. HIV infection can also spread through blood and blood products and from HIV-positive mothers to their children during pregnancy, at birth, and through breastfeeding. HIV-negative children of HIV-infected parents are at a great disadvantage because of the health and social consequences of losing one or both parents to AIDS. It is estimated that there are about 1,000 AIDS orphans in Eritrea (UNAIDS, 2002). The government of Eritrea developed a national policy on HIV/AIDS and sexually transmitted infections (STIs) in 1998. The policy is designed to guide the implementation of successful programs to prevent the spread of HIV/AIDS and STIs. Prevention and control measures include discouraging multiple sexual relationships, promoting the use of condoms among high-risk groups, maintaining a safe blood supply, ensuring safe use of needles, and disseminating information through public campaigns to change social attitudes and behavior. The response to the epidemic has been collaboration to deal with the problem by government agencies, development partners, nongovernmental organizations, religious groups, individuals, cultural groups, community groups, research institutions, and networks of persons infected and affected by HIV/ AIDS. For this purpose, the multisectoral approach of the HAMSET control project was launched. The Government of the State of Eritrea HAMSET (HIV/AIDS, Malaria, STIs, and Tuberculosis (TB)) Control Project, a World Bank financed, five-year mulitsector project launched in 2001, aims at reducing the economic, social, and disease burden caused by the targeted diseases. The desired outcome or impact indicators are a 15 percent reduction of HIV prevalence in the general population as well as target groups by 2006; reduction of the case fatality rate for malaria; and reduced stigma and discrimination against 186 | HIV/AIDS and Other Sexually Transmitted Infections persons with STIs, TB, and AIDS. The future course of the AIDS epidemic in Eritrea depends on a number of important variables including the level of public awareness about HIV and AIDS, the level and pattern of risk-related behaviors, access to high quality services for STIs, and provision of HIV-testing and counseling. 11.1 KNOWLEDGE OF HIV/AIDS AND ITS PREVENTION Since there is no cure for AIDS, the main strategy for combating the disease has been prevention through practicing absti- nence, being faithful to one sexual partner, and using condoms. This strategy depends heavily on the level of knowledge of the population and their perception of the HIV/ AIDS problem. For this reason, the 2002 EDHS sought to measure the levels of know- ledge of HIV/AIDS and other sexually trans- mitted infections in the population and to ex- amine the behaviors women adopt to protect themselves from infection. In the 2002 EDHS, respondents were asked whether they had heard of AIDS and if so, whether there is anything one can do to avoid getting infected with HIV. Table 11.1 shows that general awareness of AIDS is nearly universal among women in Eritrea, with 96 percent of women reporting that they have heard of AIDS. This figure is consistent with the results of the 2001 survey mentioned earlier. Fewer, but still a large proportion of women report that they think that there is a way to avoid getting AIDS (88 percent). Women living in rural areas and in zoba Gash-Barka are less likely to report that AIDS can be avoided than urban respondents and those living in other zobas. Education is also strongly related to understanding of HIV/ AIDS prevention. For example, 99 percent of women who have attended some secondary school or higher education report that HIV/ AIDS can be avoided, compared with 79 per- cent of women who have not attended school. If respondents reported that AIDS can be avoided, they were asked what a per- son can do to avoid getting the AIDS virus. Two types of questions were asked about ways to avoid getting HIV/AIDS. First, an open-ended question was asked and respon- dents were allowed to spontaneously report Table 11.1 Knowledge of HIV/AIDS Percentage of women who have heard of HIV/AIDS and per- centage who believe there is a way to avoid HIV/AIDS, by back- ground characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––– Has Believes heard there is a way Number of to avoid of Background characteristic AIDS HIV/AIDS women –––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 97.2 92.1 2,001 20-24 96.0 87.9 1,454 25-29 95.8 88.7 1,543 30-39 95.9 87.5 2,194 40-49 95.6 83.6 1,561 Marital status Never married 97.9 93.8 2,044 Ever had sex 98.2 94.9 118 Never had sex 97.8 93.7 1,925 Married or living together 95.5 86.2 5,733 Divorced/separated/ widowed 96.0 87.6 977 Residence Total urban 99.3 95.9 3,767 Asmara 99.5 96.7 1,899 Other towns 99.1 95.2 1,868 Rural 93.7 82.3 4,987 Zoba Debubawi Keih Bahri 85.5 72.8 324 Maekel 99.5 96.4 2,264 Semenawi Keih Bahri 95.4 82.6 1,148 Anseba 97.3 92.2 1,130 Gash-Barka 88.6 68.9 1,500 Debub 98.9 95.3 2,388 Education No education 92.7 78.8 4,384 Primary 99.5 96.1 1,637 Middle 99.8 97.4 974 Secondary + 99.5 99.0 1,760 Wealth index Lowest 91.0 75.7 1,472 Second 92.8 78.9 1,626 Middle 95.9 86.2 1,674 Fourth 99.4 97.1 1,833 Highest 99.6 97.5 2,149 Total 96.1 88.1 8,754 HIV/AIDS and Other Sexually Transmitted Infections | 187 without prompting all the ways that they knew to avoid HIV/AIDS. Next, women were asked two specific questions. The questions were phrased as follows: “Can people reduce their chances of getting the AIDS virus by using a condom every time they have sex?” and, “Can people reduce their chance of getting the AIDS virus by having just one sex partner who has no other partners?” Table 11.2 provides the results on AIDS prevention knowledge. These results answer the ques- tions asked in the preceding paragraph. The base for estimates (denominator) is all women interviewed in the 2002 EDHS. The base includes those women who reported that they did not know about HIV/AIDS, those who did not know whether HIV/AIDS could be avoided, and those who failed to mention any spe- cific way to avoid HIV/AIDS. The most frequently reported way to prevent HIV/AIDS was limiting sex to one partner or staying faithful to one partner (72 percent). Condom use and abstaining from sex to pre- vent AIDS were mentioned by 54 percent and 47 percent, respectively. Although HIV is rarely transmit- ted by sharing razor blades, 38 percent of the women cited avoidance of this practice. All other means were reported much less frequently; 10 percent mentioned avoidance of injections as a way to prevent HIV/AIDS. The pattern of these responses indicates the relative importance of different ways to prevent HIV infection in the population. The data on knowledge of HIV/ AIDS collected in the 1995 EDHS and the 2002 EDHS are comparable. Between 1995 and 2002, unprompted knowledge of use of condoms to avoid HIV/AIDS rose substan- tially, from 35 percent to 54 percent. In 1995, 22 percent of women cited sexual ab- stinence as a ways to prevent HIV/AIDS, compared with 47 percent in 2002. It may be that these sharp increases relate more to greater acceptance of sexual abstinence and condom use as feasible or socially practical behaviors than a change in knowledge per se. This underscores the difficulty in collect- ing and interpreting data on knowledge of AIDS prevention. It should be recognized that complex and changing psychosocial contextual factors are embedded in the indi- cator knowledge of HIV/AIDS. AIDS prevention programs focus their messages and efforts on three impor- tant aspects of behavior: use of condoms, restricting sexual behavior (limiting the number of sexual partners, staying faithful to one partner or having just one sex partner who has no other partners), and delaying sexual debut in young persons (i.e., absti- nence). Table 11.3 shows the percent distri- bution of women who reported none, one, and two or three of the programmatically Table 11.2 Knowledge of ways to avoid HIV/AIDS Percentage of women who spontaneously mentioned ways to avoid HIV/AIDS, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of Ways to avoid HIV/AIDS women ––––––––––––––––––––––––––––––––––––––––––––––––––––––– Has not heard of AIDS 3.9 Does not know if AIDS can be avoided 4.6 Believes there is no way to avoid AIDS 3.4 Does not know any specific way1 0.1 Abstain from sex 47.1 Use condoms 53.9 Limit number of sexual partners 3.7 Limit sex to one partner or stay faithful to one partner 71.7 Avoid sex with prostitutes 6.2 Avoid sex with persons who have many partners 2.0 Avoid sex with homosexuals 0.1 Avoid sex with persons who inject drugs intravenously 0.2 Avoid blood transfusions 6.4 Avoid injections 9.9 Avoid sharing razor or blades 37.7 Avoid kissing 0.4 Avoid mosquito bites 0.8 Seek protection from traditional healer 1.4 Other 1.2 Number of women 8,754 ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Believes there is something a person can do to avoid AIDS, but cannot spontaneously mention any specific way 188 | HIV/AIDS and Other Sexually Transmitted Infections Table 11.3 Knowledge of programmatically important ways to avoid HIV/AIDS Percent distribution of women by knowledge of three programmatically important ways to avoid HIV/AIDS, and percentage of women who know of two specific ways to avoid HIV/AIDS, according to background charac- teristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Knowledge of programmatically Specific ways important ways to avoid HIV/AIDS to avoid HIV/AIDS ––––––––––––––––––––––––––––––––––– –––––––––––––––– Two Restrict Number Background One or three Use sexual of characteristic None1 way ways Missing Total condoms behavior2 women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 5.5 8.4 86.1 0.1 100.0 78.5 90.9 2,001 20-24 8.9 10.9 80.1 0.0 100.0 72.0 89.1 1,454 25-29 8.6 13.6 77.8 0.1 100.0 69.3 90.1 1,543 30-39 8.9 15.1 76.0 0.0 100.0 63.6 88.5 2,194 40-49 10.9 18.7 70.3 0.1 100.0 58.0 86.8 1,561 Marital status Never married 4.4 6.4 89.2 0.0 100.0 81.9 93.0 2,044 Ever had sex 1.8 3.8 93.5 0.9 100.0 89.5 94.4 118 Never had sex 4.5 6.5 88.9 0.0 100.0 81.5 92.9 1,925 Married or living together 9.9 15.9 74.1 0.0 100.0 63.4 87.8 5,733 Divorced/separated/widowed 8.5 11.6 79.7 0.2 100.0 69.4 89.2 977 Residence Total urban 1.9 6.6 91.3 0.1 100.0 84.0 96.4 3,767 Asmara 1.0 4.4 94.4 0.2 100.0 88.9 97.7 1,899 Other towns 2.8 8.8 88.2 0.1 100.0 79.0 95.0 1,868 Rural 13.4 18.2 68.4 0.0 100.0 56.6 83.7 4,987 Zoba Debubawi Keih Bahri 22.0 14.3 63.6 0.2 100.0 58.2 76.2 324 Maekel 1.1 5.3 93.4 0.2 100.0 88.1 97.4 2,264 Semenawi Keih Bahri 12.4 24.6 63.0 0.0 100.0 47.0 83.5 1,148 Anseba 6.5 14.0 79.5 0.0 100.0 59.7 91.9 1,130 Gash-Barka 25.0 21.9 53.1 0.0 100.0 45.7 71.1 1,500 Debub 2.1 9.3 88.5 0.0 100.0 79.8 95.9 2,388 Education No education 15.8 21.4 62.8 0.0 100.0 49.4 81.2 4,384 Primary 2.1 8.3 89.6 0.0 100.0 81.6 95.4 1,637 Middle 0.6 4.2 95.1 0.1 100.0 89.4 97.9 974 Secondary + 0.4 2.5 96.9 0.2 100.0 91.9 98.2 1,760 Wealth index Lowest 19.9 21.9 58.2 0.0 100.0 42.4 76.2 1,472 Second 15.3 20.6 64.0 0.0 100.0 51.6 82.0 1,626 Middle 9.2 16.6 74.3 0.0 100.0 65.6 87.9 1,674 Fourth 1.3 6.9 91.7 0.1 100.0 82.7 96.9 1,833 Highest 0.9 4.5 94.5 0.1 100.0 89.0 97.8 2,149 Total 8.4 13.2 78.3 0.1 100.0 68.4 89.1 8,754 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Programmatically important ways are abstaining from sex, using condoms, and limiting the number of sexual partners. Abstinence from sex is measured from a spontaneous response only, and using condoms and limiting the number of sexual partners is measured from spontaneous and probed responses. 1 Those who have not heard of HIV/AIDS or do not know of any programmatically important ways to avoid HIV/AIDS. 2 Refers to limiting number of sexual partners, limiting sex to one partner/staying faithful to one partner, and having just one partner who has no other partners. HIV/AIDS and Other Sexually Transmitted Infections | 189 important ways to avoid AIDS (spontaneous or prompted). Seventy-eight percent of women know of two or three effective ways to avoid infection with HIV. Sixty-eight percent of rural women know of two or three ways, compared with 91 percent of urban women. Other factors that are related to knowledge of ways to prevent HIV infection include age, sexual activity, education, and household wealth. Differentials by zoba and education are striking (Figure 11.1). Among zobas, knowledge of at least two ways to avoid infection with HIV/AIDS varies from 53 percent to 93 percent. By education, 97 percent of women with at least secondary education know two or three ways of AIDS prevention, compared with 63 percent of women with no schooling. Older respondents (age 40-49) and those who are married or living together know fewer AIDS prevention methods than younger women and those who have never married (Table 11.3). Women’s knowledge (spontaneously and prompted) of two specific ways to avoid HIV/AIDS— condom use and restricting sexual behavior—is shown in Table 11.3. With the inclusion of prompted knowledge, knowledge of condom use for HIV/AIDS protection rises from 54 percent (unprompted) to 68 percent. Similarly, after prompting, 89 percent of women agree that limiting the number of partners and staying faithful to one partner or having just one partner who has no other partners are ways to avoid HIV/AIDS. EDHS 2002 Figure 11.1 Percentage of Women Who Know at Least Two Programmatically Important Ways to Avoid HIV/AIDS, by Zoba and Education 0 64 93 63 80 53 89 63 90 95 97 ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub EDUCATION No education Primary Middle Secondary + 0 20 40 60 80 100 Percent 11.2 KNOWLEDGE OF OTHER AIDS-RELATED ISSUES In addition to asking questions about ways to prevent HIV/AIDS, the respondents who had heard about AIDS were asked whether they agreed or disagreed with some statements about AIDS-related issues. Table 11.4 shows the distribution of women by their responses to questions intended to evaluate important aspects of their knowledge of HIV/AIDS. When asked whether a healthy-looking person can have the AIDS virus, 76 percent of women correctly responded “yes.” This represents an increase in knowledge from 1995, when 59 percent of women responded correctly to the same question. 190 | HIV/AIDS and Other Sexually Transmitted Infections Table 11.4 Knowledge of HIV/AIDS-related issues Percentage of women who know various HIV/AIDS-related issues, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage who say HIV/AIDS Percentage can be transmitted from Percentage who who say a mother to child: know someone healthy- –––––––––––––––––––––––––––– personally who looking person Through has the virus that Number Background can have the During During breast- causes AIDS or of characteristic AIDS virus delivery pregnancy feeding has died of AIDS women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 80.3 74.4 82.7 75.0 40.4 2,001 20-24 76.8 71.9 79.8 68.6 35.8 1,454 25-29 76.8 73.4 80.9 70.6 39.2 1,543 30-39 73.3 71.0 79.2 66.6 35.0 2,194 40-49 70.3 68.7 77.7 68.1 34.7 1,561 Marital status Never married 84.3 77.1 85.2 74.6 45.5 2,044 Ever had sex 88.1 74.9 88.6 81.7 50.7 118 Never had sex 84.1 77.3 85.0 74.2 45.2 1,925 Married or living together 72.7 70.2 78.3 68.0 33.5 5,733 Divorced/separated/widowed 74.0 71.2 80.5 70.7 40.7 977 Residence Total urban 88.5 79.8 89.5 74.1 52.1 3,767 Asmara 92.5 81.3 92.7 72.8 58.4 1,899 Other towns 84.5 78.3 86.4 75.5 45.7 1,868 Rural 65.8 66.0 73.0 66.6 25.8 4,987 Zoba Debubawi Keih Bahri 62.5 65.7 71.9 66.2 37.4 324 Maekel 91.9 81.7 92.6 74.1 56.8 2,264 Semenawi Keih Bahri 60.5 62.2 69.7 63.9 14.9 1,148 Anseba 74.7 74.7 83.0 73.5 23.0 1,130 Gash-Barka 50.0 50.6 58.0 50.2 17.0 1,500 Debub 85.7 80.2 87.0 79.8 48.3 2,388 Education No education 60.8 61.9 69.3 62.6 21.4 4,384 Primary 84.7 79.4 88.7 77.2 42.4 1,637 Middle 91.0 83.4 92.9 81.6 52.6 974 Secondary + 95.4 83.5 92.0 74.5 62.6 1,760 Wealth index Lowest 55.3 57.7 63.6 59.0 14.0 1,472 Second 61.2 62.3 70.7 65.3 23.3 1,626 Middle 71.0 70.6 77.4 69.4 29.2 1,674 Fourth 88.9 80.8 89.3 75.4 48.8 1,833 Highest 92.5 82.4 92.9 76.4 59.5 2,149 Total 75.6 71.9 80.1 69.8 37.1 8,754 HIV/AIDS and Other Sexually Transmitted Infections | 191 The 2002 EDHS survey included some questions on transmission of AIDS virus from mother to child, which were not asked in the 1995 survey. The respondents were asked whether they thought that the AIDS virus could be transmitted from a mother to her child during pregnancy, during delivery, and during breastfeeding. The results indicate that eight in ten women responded “yes,” to transmission of infection during pregnancy, but only seven in ten women gave an affirmative answer to the other two modes of mother-to-child transmission. In addition, respondents were asked the question: “Do you personally know someone who has the AIDS virus or who has died from AIDS?” Thirty-seven percent of women reported that they knew someone with the AIDS virus or who died from AIDS. Women in the lowest quintile of the wealth index, women with no education, women in rural areas, women who are married or living together, and women in the older age group, are least knowledgeable about AIDS-related issues. These women are also least likely to know somebody who has the virus that causes AIDS or has died of AIDS. On the other hand, women most likely to respond correctly to these AIDS-related questions are young women, sexually inexperienced women, urban women, women from zobas Maekel and Debub, highly educated women, and women in the higher quintiles of the wealth index. 11.3 SOCIAL ASPECTS OF HIV/AIDS PREVENTION AND MITIGATION In the 2002 EDHS survey, currently married women who had heard of AIDS were asked whether they had ever discussed AIDS prevention with their spouse or partner. Table 11.5 indicates that 37 percent of women have had such a discussion with their partners. Higher level of education is associated with greater communication between spouses about AIDS prevention (75 percent). Urban women are twice as likely to discuss HIV/AIDS with their spouses as women in rural areas. Differences among zobas are also large. Women in zoba Maekel are four times as likely to discuss HIV/AIDS with their spouses as women in zoba Semenawi Keih Bahri. 192 | HIV/AIDS and Other Sexually Transmitted Infections Table 11.5 Discussion of HIV/AIDS with partner Percent distribution of currently married women by whether they had ever discussed HIV/AIDS prevention with their husband or partner, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Never Discussed discussed HIV/AIDS HIV/AIDS prevention prevention Has not Total with with Don’t heard Number Background husband/ husband/ know/ of of characteristic partner partner missing AIDS Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 32.2 63.5 0.0 4.2 100.0 580 20-24 35.5 59.8 0.2 4.5 100.0 950 25-29 42.4 53.0 0.1 4.5 100.0 1,212 30-39 38.9 56.8 0.0 4.2 100.0 1,803 40-49 30.5 64.8 0.0 4.6 100.0 1,189 Residence Total urban 55.0 44.1 0.2 0.8 100.0 1,967 Asmara 69.5 29.8 0.3 0.4 100.0 868 Other towns 43.6 55.4 0.1 1.0 100.0 1,099 Rural 27.1 66.6 0.0 6.3 100.0 3,766 Zoba Debubawi Keih Bahri 27.6 55.3 0.3 16.8 100.0 210 Maekel 65.7 33.7 0.2 0.3 100.0 1,103 Semenawi Keih Bahri 15.9 78.8 0.0 5.3 100.0 817 Anseba 33.7 63.5 0.0 2.8 100.0 784 Gash-Barka 24.2 64.2 0.1 11.6 100.0 1,142 Debub 38.7 60.3 0.0 1.0 100.0 1,677 Education No education 22.2 70.9 0.0 6.9 100.0 3,549 Primary 50.8 48.8 0.0 0.4 100.0 1,075 Middle 59.4 40.6 0.0 0.0 100.0 400 Secondary + 74.8 24.3 0.3 0.5 100.0 709 Wealth index Lowest 15.8 75.1 0.1 9.0 100.0 1,161 Second 24.2 68.6 0.0 7.2 100.0 1,215 Middle 29.5 66.3 0.0 4.2 100.0 1,224 Fourth 54.3 45.1 0.0 0.6 100.0 1,079 Highest 64.3 35.1 0.3 0.4 100.0 1,053 Total 36.7 58.8 0.1 4.4 100.0 5,733 Fear of public disclosure has been seen as a major barrier to HIV-testing and programs aimed at assisting people living with HIV and their families. Table 11.6 provides responses to questions that evaluate the level of stigma attached to AIDS and to persons living with HIV and AIDS in Eritrea. Respondents were asked, "If a member of your family got infected with the virus that causes AIDS, would you want it to remain a secret or not?" Among women who know about AIDS, only 16 percent said they would want the HIV-positive status of a relative to remain secret. HIV/AIDS and Other Sexually Transmitted Infections | 193 Table 11.6 Social aspects of HIV/AIDS Among women who have heard of AIDS, percentage giving specific responses to questions on two social aspects of HIV/AIDS, by background characteristics, Eritrea 2002 Women who have heard of HIV/AIDS Believe Not willing HIV-positive to care status of family for relative Number Background member should with AIDS of characteristic be kept secret at home women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 16.2 19.5 1,945 20-24 18.6 23.9 1,396 25-29 15.0 25.8 1,478 30-39 15.8 27.5 2,104 40-49 13.6 30.4 1,493 Marital status Never married 16.6 14.6 2,000 Ever had sex 17.0 14.2 116 Never had sex 16.6 14.6 1,884 Married or living together 15.8 29.7 5,478 Divorced/separated/widowed 14.6 22.4 938 Residence Total urban 15.4 14.9 3,741 Asmara 16.4 9.9 1,889 Other towns 14.4 20.0 1,852 Rural 16.2 33.6 4,675 Zoba Debubawi Keih Bahri 12.2 18.8 277 Maekel 16.9 10.2 2,253 Semenawi Keih Bahri 10.9 42.8 1,095 Anseba 14.7 33.8 1,100.0 Gash-Barka 20.1 36.5 1,329 Debub 15.7 22.0 2,362 Education No education 15.8 36.4 4,065 Primary 15.4 24.9 1,629 Middle 14.4 10.6 972 Secondary + 17.1 8.0 1,751 Wealth index Lowest 16.0 41.7 1,339 Second 14.9 37.8 1,509 Middle 15.6 30.6 1,606 Fourth 16.9 15.1 1,821 Highest 15.7 10.9 2,141 Total 15.8 25.3 8,416 194 | HIV/AIDS and Other Sexually Transmitted Infections Programs designed to assist in the support and care of AIDS-affected persons can be hindered by fear of association with HIV and AIDS. In Eritrea, women who were aware of AIDS were asked, "If a relative of yours became sick with AIDS, would you be willing to care for her or him in your own household?" Only one-fourth of women responded that they would not be willing to take care of a relative who had AIDS. Willingness to care for a relative with AIDS at home is highest among young women, urban women, women with higher education, and women in the highest wealth quintile. 11.4 KNOWLEDGE OF SIGNS AND SYMPTOMS OF SEXUALLY TRANSMITTED INFECTIONS Sexually transmitted infections (STIs) are believed to be a predisposing factor for HIV/AIDS transmission. As such, the presence of STIs in a population increases the likelihood of the occurrence of HIV. AIDS prevention programs should therefore also address the prevention and treatment of STIs. Three questions were included in the 2002 EDHS to assess the level of awareness of STIs among women and their knowledge of the symptoms of STIs in men and in women. Table 11.7 shows knowledge of symptoms of STIs in a man and in a woman. Fifty-eight percent of women in Eritrea report that they have no knowledge of STIs. One in ten women do not know any of the symptoms of STIs in a man, while 7 percent of women mentioned only one symptom, and one-fourth mentioned at least two symptoms. A similar pattern is seen for knowledge of symptoms of STIs in a woman. One in ten women do not know any symptoms of STIs in a woman, 6 percent know only one symptom, and 27 percent know two or more symptoms. Surprisingly, there is little difference in knowledge by age. Knowledge of STIs and symptoms of STIs is especially low among women with no education and women in zoba Semenawi Keih Bahri (Figure 11.2). Women in rural areas and those who are married or living with a man also have very low levels of knowledge of STIs and symptoms of STIs (Table 11.7). EDHS 2002 Figure 11.2 Percentage of Women Who Know at Least One Symptom of Sexually Transmitted Infections (STIs) in Men 0 24 52 19 27 24 29 18 33 41 64 ZOBA Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash-Barka Debub EDUCATION No education Primary Middle Secondary + 0 20 40 60 80 100 Percent HIV/AIDS and Other Sexually Transmitted Infections | 195 Table 11.7 Knowledge of symptoms of STIs Percent distribution of women by knowledge of symptoms of sexually transmitted infections (STIs) in a man and by knowledge of STIs in a woman, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Knowledge of symptoms of Knowledge of symptoms of STIs in a man STIs in a woman –––––––––––––––––––––––––––––––– –––––––––––––––––––––––––––––––– Two Two No No or more No or more knowl- symptoms One symptoms symptoms One symptoms Number Background edge men- symptom men- men- symptom men- of characteristic of STIs tioned mentioned tioned Missing tioned mentioned tioned Missing women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 60.0 9.2 7.9 22.8 0.1 10.1 6.0 23.9 0.1 2,001 20-24 57.6 10.2 6.0 25.9 0.3 10.5 4.5 27.2 0.3 1,454 25-29 54.8 10.6 5.3 29.3 0.1 10.7 4.7 29.8 0.1 1,543 30-39 58.8 8.5 7.3 25.4 0.0 9.0 5.8 26.5 0.0 2,194 40-49 57.8 9.3 7.0 25.7 0.2 8.0 6.3 27.7 0.2 1,561 Marital status Never married 48.4 11.9 10.1 29.3 0.2 13.0 7.3 31.1 0.2 2,044 Ever had sex 28.2 12.4 15.8 41.9 1.8 18.6 6.2 45.3 1.8 118 Never had sex 49.6 11.9 9.8 28.6 0.1 12.6 7.4 30.2 0.1 1,925 Married or living together 62.2 8.5 5.7 23.5 0.0 8.4 4.9 24.4 0.0 5,733 Divorced/separated/widowed 53.1 10.0 6.2 30.5 0.2 9.5 5.4 31.9 0.2 977 Residence Total urban 38.3 13.0 10.1 38.4 0.2 13.6 8.2 39.7 0.2 3,767 Asmara 29.4 15.1 10.3 45.0 0.3 16.1 7.6 46.7 0.3 1,899 Other towns 47.4 10.9 10.0 31.6 0.1 11.0 8.8 32.7 0.1 1,868 Rural 72.8 6.8 4.3 16.0 0.0 6.6 3.5 17.0 0.0 4,987 Zoba Debubawi Keih Bahri 69.0 6.7 4.3 19.9 0.2 6.4 4.0 20.5 0.2 324 Maekel 33.4 14.5 9.7 42.2 0.3 15.3 7.2 43.9 0.3 2,264 Semenawi Keih Bahri 76.4 4.3 4.3 14.9 0.0 4.8 3.7 15.1 0.0 1,148 Anseba 64.5 8.2 4.1 23.2 0.0 8.3 3.3 23.9 0.0 1,130 Gash-Barka 70.1 6.1 4.2 19.4 0.1 6.2 3.9 19.7 0.1 1,500 Debub 60.2 10.3 8.5 20.9 0.0 9.7 7.1 23.0 0.0 2,388 Education No education 76.7 5.6 3.5 14.2 0.1 5.5 3.1 14.7 0.1 4,384 Primary 56.5 10.4 6.8 26.2 0.0 10.4 5.5 27.6 0.0 1,637 Middle 46.4 12.7 8.5 32.3 0.1 13.9 7.6 32.0 0.1 974 Secondary + 19.1 16.5 14.1 50.0 0.3 16.8 10.4 53.4 0.3 1,760 Total 58.0 9.5 6.8 25.6 0.1 9.6 5.5 26.8 0.1 8,754 11.5 KNOWLEDGE OF SOURCE AND USE OF CONDOMS Condom use plays an important role in preventing the transmission of HIV/AIDS. Table 11.8 shows data on knowledge and use of condoms. Fifty-four percent of women know a source for condoms. Younger women, never-married women who ever had sex, urban women, women in zoba Maekel, and those with higher education are more likely to know a source of condoms than other women. Knowledge of a source for condoms is positively correlated with education. Table 11.8 shows the percentage of women who had sexual intercourse in the 12 months preceding the survey who used condoms during the most recent sexual intercourse, by background characteristics. The use of condoms is negligible among 196 | HIV/AIDS and Other Sexually Transmitted Infections Eritrean women (2 percent). However, never-married women who have ever had sex are more likely to have used condoms (36 percent) than other women, although the sample size is small. Table 11.8 Knowledge of source and use of condoms Percentage of women who know a source for condoms and among women who had sexual intercourse in the last year, percentage who used a condom during the most recent sexual intercourse, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Knows Percentage source Number who used Number Background for of a condom of characteristic condoms women at last sex women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 65.5 2,001 2.9 560 20-24 57.4 1,454 1.5 837 25-29 57.6 1,543 2.5 1,072 30-39 48.4 2,194 1.6 1,706 40-49 40.2 1,561 0.6 1,147 Marital status Never married 75.6 2,044 (36.4) 47 Ever had sex 83.0 118 (36.4) 47 Never had sex 75.2 1,925 na na Married or living together 46.3 5,733 1.2 5,121 Divorced/separated/ widowed 53.3 977 7.6 153 Residence Total urban 79.7 3,767 3.8 1,836 Asmara 84.3 1,899 4.4 815 Other towns 75.2 1,868 3.4 1,021 Rural 34.5 4,987 0.5 3,485 Zoba Debubawi Keih Bahri 53.1 324 4.3 200 Maekel 80.5 2,264 3.5 1,035 Semenawi Keih Bahri 37.8 1,148 1.1 768 Anseba 45.6 1,130 1.9 737 Gash-Barka 30.4 1,500 0.9 1,088 Debub 55.4 2,388 0.8 1,493 Education No education 28.8 4,384 0.4 3,282 Primary 64.8 1,637 2.4 1,004 Middle 79.3 974 3.5 381 Secondary + 92.5 1,760 5.9 655 Total 54.0 8,754 1.7 5,321 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable Female Circumcision | 197 FEMALE CIRCUMCISION 12 The 1995 EDHS was the first national-level survey in Eritrea that included questions about the practice of female circumcision. Nowadays this practice is also called female genital cutting (FGC); in this chapter these two terms are used interchangeably. The 1995 survey found that the practice was very widespread in Eritrea. In the 2002 EDHS, information was collected to further investigate prevalence of and attitudes toward FGC among Eritrean women and to assess whether there is evidence of changes in attitudes or behavior since 1995. Female genital cutting (FGC) is a term used for a variety of types of ritual surgery carried out on female genitals for traditional, religious, and aesthetic reasons, and usually backed by social pressure. The negative consequences of FGC can be immediate, with long-term health risks and complications. Although variations exist, there are three generally recognized types of circumcision: clitoridec- tomy, excision, and infibulation. Clitoridectomy is the removal of the prepuce with or without excision of all or part of the clitoris. Excision is the removal of the prepuce and clitoris along with all or part of the labia minora. Infibulation (also called “pharaonic circumcision”) is the most severe form of female circumcision. It consists of removal of all or part of the external genitalia, followed by joining together of the two sides of the labia majora using threads, thorns, or other materials to narrow the vaginal opening (WHO, 1996). The types of circumcision are not strictly defined and categorization may not be exact because of variations in the procedure used by practitioners. For this reason unlike the 1995 EDHS, the names of these categories were not used in the 2002 EDHS questionnaire; rather respondents were asked about the severity of their operations. 12.1 CIRCUMCISION OF EDHS RESPONDENTS Knowledge and Prevalence Results from the 2002 EDHS show that knowledge of female circumcision is almost universal among Eritrean women. Table 12.1 indicates that almost all respondents (99 percent) have heard of female genital cutting. FGC is very common in Eritrea; 89 percent of women reported that they had been circumcised, a decline of 6 percent since 1995. There has been a slight decline in prevalence in all subgroups shown in Table 12.1. However, the decline is most notable among younger women (under 25) and among women in zoba Debub. As in 1995, by residence, there is almost no difference between other towns (89 percent) and rural areas (91 percent) in the prevalence of circumcision; prevalence remains lowest in Asmara (83 percent). The practice of female circumcision is somewhat lower in zobas Maekel and Debub than in other zobas. By wealth index, the practice decreases from 94 percent among women in the lowest quintile to 84 percent among women in the highest quintile. Type of Circumcision The percent distribution of circumcised women by type of circumcision or severity of circumcision is shown in Table 12.1 and Figure 12.1. Thirty-nine percent of circumcised women had their vaginal area sewn closed (the most severe form of circumcision), while a small proportion (4 percent) had only some genital flesh removed, and 46 percent were just nicked with no flesh removed from genitals (the least severe form of circumcision). For 11 percent of women the type of circumcision could not be 198 | Female Circumcision determined. Urban women in general, and women in Asmara in particular, are less likely to have their vaginal area sewn closed than women in rural areas. More than half (52 percent) of circumcised women in rural areas compared with only 6 percent in Asmara had their vaginal area sewn closed. In urban areas, 56 percent of circumcised women were nicked with no flesh removed, compared with 39 percent of women in rural areas. The most severe form of circumcision is least prevalent in zobas Maekel and Debub (5 percent and 11 percent, respectively). In other zobas, this type of circumcision is extremely high, ranging from 57 percent in Debubawi Keih Bahri to 78 percent in Semenawi Keih Bahri. Table 12.1 Knowledge and prevalence of female circumcision Percentage of women who have heard of female circumcision, percentage of women circumcised, and the percent distribution of circumcised women by type of circumcision, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage Type of circumcision of women Percent- ––––––––––––––––––––––––––––– who have age of Nicked, heard of women Number no Not Number Background female circum- of Sewn Flesh flesh deter- of characteristic circumcision cised women closed removed removed mined Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 97.9 78.3 2,001 33.8 4.1 49.7 12.5 100.0 1,568 20-24 99.3 87.9 1,454 41.1 3.9 44.6 10.4 100.0 1,279 25-29 99.6 90.8 1,543 37.3 4.9 45.9 11.9 100.0 1,402 30-34 99.8 93.4 1,109 42.5 3.6 42.3 11.6 100.0 1,036 35-39 99.6 92.6 1,085 40.0 3.5 45.7 10.8 100.0 1,005 40-44 99.9 94.1 827 42.0 3.7 44.1 10.2 100.0 779 45-49 99.7 95.0 734 35.8 4.8 48.4 10.9 100.0 697 Residence Total urban 99.2 86.4 3,767 20.7 6.5 55.6 17.2 100.0 3,254 Asmara 99.0 83.4 1,899 5.5 11.0 56.4 27.1 100.0 1,584 Other towns 99.5 89.4 1,868 35.1 2.3 54.8 7.8 100.0 1,669 Rural 99.2 90.5 4,987 51.5 2.3 39.1 7.1 100.0 4,511 Zoba Debubawi Keih Bahri 99.6 92.2 324 56.5 0.3 39.8 3.3 100.0 299 Maekel 98.9 83.5 2,264 4.7 11.0 57.8 26.4 100.0 1,891 Semenawi Keih Bahri 100.0 97.7 1,148 78.1 2.2 17.9 1.8 100.0 1,121 Anseba 99.9 96.4 1,130 68.7 1.0 27.4 2.9 100.0 1,090 Gash-Barka 99.5 94.6 1,500 63.3 1.6 32.1 3.0 100.0 1,419 Debub 98.6 81.5 2,388 11.1 2.6 72.1 14.2 100.0 1,946 Wealth index Lowest 99.5 94.0 1,472 74.8 1.7 20.9 2.6 100.0 1,383 Second 98.9 91.4 1,626 56.8 1.7 36.2 5.4 100.0 1,487 Middle 99.1 88.5 1,674 42.2 2.6 46.4 8.7 100.0 1,482 Fourth 99.4 87.3 1,833 18.0 5.9 60.7 15.4 100.0 1,600 Highest 99.2 84.3 2,149 11.3 7.5 59.9 21.3 100.0 1,813 Total 99.2 88.7 8,754 38.6 4.1 46.0 11.3 100.0 7,765 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: The total excludes one woman with missing information on whether circumcised. Female Circumcision | 199 EDHS 2002 Figure 12.1 Distribution of Circumcised Women by Type of Circumcision 89 39 4 46 11 Total circumcised Sewn closed Flesh removed Nicked, no flesh removed Not determined 0 20 40 60 80 100 Percent Age at Circumcision for Respondents Table 12.2 shows the percent distribution of circumcised women by age at circumcision. Sixty- two percent of circumcised women reported that they were circumcised before their first birthday, including one-half (49 percent) who were circumcised when they were one month of age or younger. One in six women was circumcised at five years of age or older. Urban women are more likely to be circumcised at an early age than women in rural areas. Age at circumcision by zoba shows differences in the timing of circumcising. The majority of women in zobas Debubawi Keih Bahri, Maekel, and Debub were circumcised within the first 30 days after birth, while the majority of women in other zobas were circumcised after infancy—most commonly after 5 years of age. 200 | Female Circumcision Table 12.2 Age at circumcision Percent distribution of circumcised women by age at circumcision, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age at circumcision Number Background <8 8-30 One 2-11 1-2 3-4 5+ Missing/ of characteristic days days month months years years years don’t know Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 13.7 17.4 13.4 19.2 6.9 6.9 14.3 8.1 100.0 1,568 20-24 15.0 17.3 11.8 16.2 4.8 9.8 17.1 7.9 100.0 1,279 25-29 20.6 17.7 13.0 11.9 4.2 7.7 15.6 9.2 100.0 1,402 30-34 16.4 19.7 12.8 11.4 5.4 8.6 17.3 8.4 100.0 1,036 35-39 19.9 20.1 11.2 11.5 3.7 7.3 17.1 9.3 100.0 1,005 40-44 17.0 21.0 10.6 9.6 4.4 8.8 18.4 10.2 100.0 779 45-49 23.0 21.7 12.9 9.6 2.5 7.5 14.5 8.4 100.0 697 Residence Total urban 22.3 22.7 14.4 15.9 4.1 3.7 7.6 9.2 100.0 3,254 Asmara 22.9 28.6 18.0 16.9 2.8 0.3 1.3 9.1 100.0 1,584 Other towns 21.7 17.1 11.1 14.9 5.4 6.9 13.6 9.3 100.0 1,669 Rural 14.0 16.0 10.9 11.8 5.3 11.2 22.4 8.3 100.0 4,511 Zoba Debubawi Keih Bahri 40.1 15.4 10.1 10.4 13.3 3.0 1.2 6.5 100.0 299 Maekel 22.0 29.0 18.8 17.3 2.6 0.4 1.1 8.8 100.0 1,891 Semenawi Keih Bahri 14.0 5.8 3.9 7.1 6.3 12.1 40.1 10.8 100.0 1,121 Anseba 7.4 12.4 8.9 11.3 4.1 15.6 31.0 9.3 100.0 1,090 Gash-Barka 9.6 9.3 5.5 8.3 9.0 20.0 30.1 8.2 100.0 1,419 Debub 22.9 27.6 18.4 19.1 2.2 0.9 0.9 7.8 100.0 1,946 Total 17.5 18.8 12.4 13.5 4.8 8.0 16.2 8.7 100.0 7,765 Person Who Performed Circumcision Table 12.3 shows the percent distribution of circumcised women by type of person who performed the circumcision. The risks of complications and infections with female genital cutting are a function of the conditions under which the surgery is performed and the cleanliness of the instruments used for circumcising. In the 2002 EDHS, circumcised women were asked who had performed their circumcision, to indirectly gauge exposure to these risks. Special persons, circumcision practitioners, perform the vast majority of female circumcisions in Eritrea. Eighty-four percent were performed by circumcision practitioners and 8 percent by traditional birth attendants (TBAs). Five percent of women did not know who performed the procedure. The number of circumcisions performed by trained health professionals is very small, less than 1 percent. The most notable fact in Table 12.3 is that, although TBAs performed less than 10 percent of circumcisions, they are more likely to perform the two most severe types of circumcisions. Some people believe that non-health workers who perform circumcisions have a financial interest in the continuation of the practice; therefore, it may be practical to use health workers to dissuade people from circumcising their daughters. Female Circumcision | 201 Table 12.3 Person who performed female circumcision Percent distribution of circumcised women by type of person who performed circumcision, according to background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of person who performed circumcision –––––––––––––––––––––––––––––––––––––––– Number Trained Circum- of Background nurse/ cision Missing/ circumcised characteristic Doctor midwife TBA practitioner Other don’t know Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of Circumcision Sewn closed 0.1 0.4 11.9 81.6 2.6 3.4 100.0 2,997 Flesh removed 0.0 1.0 18.2 73.5 2.7 4.7 100.0 318 Nicked, no flesh removed 0.1 0.5 5.7 86.5 1.9 5.3 100.0 3,572 Not determined 0.1 0.3 4.2 83.7 2.9 8.8 100.0 879 Age 15-19 0.2 1.0 8.1 83.6 1.9 5.1 100.0 1,568 20-24 0.2 0.4 7.8 85.1 2.2 4.2 100.0 1,279 25-29 0.2 0.5 7.7 84.0 2.7 4.9 100.0 1,402 30-34 0.0 0.1 7.2 84.5 3.3 5.0 100.0 1,036 35-39 0.0 0.5 9.7 82.6 2.4 4.9 100.0 1,005 40-44 0.0 0.1 9.7 83.6 2.0 4.6 100.0 779 45-49 0.0 0.2 10.5 81.6 1.6 6.0 100.0 697 Residence Total urban 0.3 0.7 6.6 85.0 1.6 5.8 100.0 3,254 Asmara 0.5 1.2 5.0 84.8 1.5 7.0 100.0 1,584 Other towns 0.1 0.3 8.1 85.2 1.7 4.7 100.0 1,669 Rural 0.0 0.3 9.7 82.8 2.9 4.3 100.0 4,511 Zoba Debubawi Keih Bahri 0.0 0.5 11.1 84.8 0.6 3.0 100.0 299 Maekel 0.5 1.0 6.1 84.3 1.6 6.5 100.0 1,891 Semenawi Keih Bahri 0.0 0.1 10.3 82.7 3.1 3.7 100.0 1,121 Anseba 0.0 1.0 11.3 80.9 1.5 5.3 100.0 1,090 Gash-Barka 0.0 0.2 7.1 88.1 1.2 3.4 100.0 1,419 Debub 0.0 0.0 8.5 82.1 4.2 5.3 100.0 1,946 Total 0.1 0.5 8.4 83.8 2.3 4.9 100.0 7,765 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– TBA = Traditional birth attendant 12.2 CIRCUMCISION EXPERIENCE OF DAUGHTERS Prevalence and Type of Circumcision Women interviewed in the survey who had living daughters were asked if any of their daughters had been circumcised, and if yes, how many. Then questions were asked about the most recently circumcised daughter, that is, type of circumcision, age at circumcision, and the person who performed the circumcision. Table 12.4 shows the percentage of women who have at least one circumcised daughter and the percent distribution of the most recently circumcised daughters by type of circumcision, according to background characteristics. Overall, 63 percent of women reported that at least one of their daughters had been circumcised, indicating a slight decline since 1995. In the 1995 EDHS, the questions about daughter’s circumcision were asked for the eldest daughter, 71 percent of whom were circumcised. 202 | Female Circumcision Table 12.4 Daughter’s circumcision experience and type of circumcision Percentage of women with at least one living circumcised daughter, and percent distribution of most recently cir- cumcised daughters by type of circumcision, according to mother’s background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage of women Type of circumcision with at –––––––––––––––––––––––––––––––––––––––– Mother’s least one Number Nicked, Number background circumcised of Sewn Flesh no flesh Not of characteristic daughter women closed removed removed determined Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of circumcision Sewn closed 73.0 1,689 84.3 3.0 11.7 0.9 100.0 1,234 Flesh removed 59.3 161 9.4 73.5 12.1 5.0 100.0 95 Nicked, no flesh removed 64.1 1,933 2.2 2.6 93.2 2.0 100.0 1,238 Not determined 56.1 445 1.2 8.0 58.8 32.0 100.0 250 Not circumcised 16.5 376 11.8 9.6 75.4 3.2 100.0 62 Age 15-19 23.2 119 (14.3) (0.0) (76.1) (9.7) 100.0 28 20-24 39.8 510 30.2 6.2 58.5 5.1 100.0 203 25-29 48.8 905 31.7 4.4 57.9 6.1 100.0 441 30-34 61.5 826 42.2 3.2 50.6 4.0 100.0 508 35-39 70.1 902 37.9 7.6 51.5 3.0 100.0 632 40-44 77.1 711 44.1 5.8 46.8 3.4 100.0 548 45-49 82.3 631 35.8 7.3 52.1 4.8 100.0 519 Residence Total urban 58.5 1,727 21.1 8.6 63.3 7.1 100.0 1,011 Asmara 50.7 761 3.4 13.8 69.3 13.5 100.0 386 Other towns 64.6 966 32.0 5.3 59.6 3.1 100.0 625 Rural 64.9 2,877 46.8 4.2 46.3 2.7 100.0 1,868 Zoba Debubawi Keih Bahri 78.2 162 66.3 1.1 32.0 0.7 100.0 126 Maekel 54.1 956 2.7 14.0 69.4 13.8 100.0 517 Semenawi Keih Bahri 71.8 643 66.0 4.3 28.9 0.8 100.0 462 Anseba 76.6 645 58.8 3.8 36.5 0.9 100.0 494 Gash-Barka 61.8 837 58.4 3.9 36.2 1.5 100.0 517 Debub 56.0 1,361 12.1 4.3 79.2 4.4 100.0 763 Education level No education 67.5 2,989 49.0 5.1 43.0 2.9 100.0 2,018 Primary 62.5 827 14.6 6.9 72.4 6.1 100.0 517 Middle 50.3 280 7.2 4.3 78.9 9.6 100.0 141 Secondary + 40.0 508 6.4 10.8 74.1 8.8 100.0 203 Wealth index Lowest 71.0 917 67.4 2.9 28.8 0.9 100.0 652 Second 65.4 943 51.1 4.2 42.0 2.7 100.0 617 Middle 60.1 920 35.3 4.4 57.5 2.7 100.0 553 Fourth 62.0 949 16.3 8.7 68.1 6.9 100.0 588 Highest 53.6 875 8.9 9.6 72.1 9.4 100.0 469 Total 62.5 4,604 37.8 5.8 52.2 4.2 100.0 2,879 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Figures in parentheses are based on 25-49 cases. Female Circumcision | 203 Among circumcised daughters for whom information was collected, 38 percent had their vaginal area sewn, and 52 percent had their genitals nicked with no flesh removed. However, for mothers under age 30, the prevalence of the most severe type of circumcision among daughters is lower than the prevalence among their own cohorts. For each background variable, the percentage of mothers who had at least one daughter circumcised is lower than the percentage of respondents circumcised. One reason for the lower prevalence of circumcision among daughters than among respondents is that some women— especially young mothers—may have daughters who are too young to be circumcised. It is discouraging to note that 17 percent of mothers, who have themselves not undergone circumcision, have at least one daughter circumcised. Overall, the pattern of circumcision for the most recently circumcised daughters is almost the same as that of circumcised respondents. Mother’s education influences both the likelihood of a daughter being circumcised and the severity of the operation. For example, 68 percent of the daughters of uneducated mothers have been circumcised, compared with 40 percent of daughters whose mothers have at least some secondary education. The likelihood of circumcised daughters having the severest form of circumcision varies between 6 and 15 percent when mothers have some schooling, compared with almost 50 percent when mothers have not attended school. Age at Circumcision for Daughters Two-thirds of daughters were reported by their mothers to have been circumcised in infancy. Thirty-seven percent of daughters were reported by their mothers to have been circumcised during the first 30 days of life and 14 percent were circumcised when they were one month old (Figure 12.2). One- fourth were circumcised when the daughters were at least three years old. A comparison of age at circumcision for all respondents and the most recently circumcised daughters indicates that there is a tendency to circumcise daughters at younger ages. EDHS 2002 Figure 12.2 Daughter’s Age at Circumcision <8 days 15% 8-30 days 22% One month 14% 2-11 months 18% 1-2 years 8% 3-4 years 10% 5+ years 14% Persons Who Performed Daughter’s Circumcision Table 12.5 shows that female circumcision is performed the same way now as in 1995. Circumcision practitioners performed more than 80 percent of the daughters’ circumcisions as they did 204 | Female Circumcision for the respondents themselves; traditional birth attendants performed only a small proportion (11 percent). TBAs performed somewhat higher proportions of circumcisions in zoba Debubawi Keih Bahri (18 percent). 12.3 OBJECTIONS TO DAUGHTER’S CIRCUMCISION The 2002 EDHS results presented in Table 12.6 show that among women who have at least one daughter circumcised, 95 percent reported that no one objected to the most recent circumcision, indicating acceptance of the continuation of the practice of circumcision by respondents, their relatives, and friends. Mothers age 15-29 are more likely than older mothers to report that someone objected to the circumcision. The percentage of mothers reporting that someone objected to their daughter’s circumcision is highest among mothers with some secondary education. One-third of these mothers reported that someone objected to their daughter being circumcised; one in four reported that their husband objected. Reports that some person objected to the daughter’s circumcision were also high among mothers living in urban areas (11 percent), zoba Maekel (11 percent) and Asmara (14 percent), and in the highest quintile of the wealth index (17 percent). In almost all subgroups, fathers are more likely than mothers to object to their daughter’s circumcision. Table 12.5 Person who performed daughter’s circumcision Percent distribution of most recently circumcised daughters by person who performed the circumcision, according to daughter’s type of circumcision and mother’s background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Person who performed circumcision Number ––––––––––––––––––––––––––––––––––––––– of most Trained Circum- recently Background nurse/ cision Missing/ circumcised characteristic Doctor midwife TBA practitioner Other don’t know Total daughters ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Daughter’s type of circumcision Sewn closed 0.1 0.9 15.0 79.1 4.6 0.3 100.0 1,087 Flesh removed 0.0 1.3 15.2 77.5 5.9 0.0 100.0 166 Nicked, no flesh removed 0.6 0.6 7.9 87.7 3.1 0.0 100.0 1,504 Not determined 0.0 1.8 2.2 91.2 4.0 0.8 100.0 122 Residence Total urban 1.0 1.6 10.0 86.0 1.4 0.1 100.0 1,011 Asmara 1.6 1.3 7.7 87.3 1.8 0.3 100.0 386 Other towns 0.6 1.7 11.5 85.1 1.1 0.1 100.0 625 Rural 0.0 0.4 11.2 83.0 5.3 0.1 100.0 1,868 Zoba Debubawi Keih Bahri 0.0 0.2 17.5 80.8 1.3 0.3 100.0 126 Maekel 1.2 1.2 8.4 87.4 1.6 0.2 100.0 517 Semenawi Keih Bahri 0.2 1.1 12.5 79.7 6.6 0.0 100.0 462 Anseba 0.0 1.9 13.2 83.7 1.2 0.0 100.0 494 Gash-Barka 0.5 0.2 7.8 88.9 2.2 0.4 100.0 517 Debub 0.0 0.1 10.8 81.8 7.2 0.1 100.0 763 Total 0.3 0.8 10.8 84.0 3.9 0.1 100.0 2,879 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– TBA = Traditional birth attendant Female Circumcision | 205 Table 12.6 Objections to daughter’s circumcision Among women who have at least one circumcised daughter, percentage reporting objections raised by specific persons to the last daughter’s circumcision, by daughter’s circumcision status and mother’s background charac- teristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Persons who raised objections ––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number Respon- Other of women Respon- Respon- dent’s relatives with Background Any Respon- dent’s dent’s mother- of respon- No circumcised characteristic person dent husband mother in-law dent Others one daughter ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Daughter’s circumcision Sewn closed 2.0 1.0 0.4 0.0 0.1 0.8 0.0 97.6 1,087 Flesh removed 5.0 2.0 2.7 0.0 0.0 2.1 0.0 93.6 166 Nicked, no flesh removed 6.2 1.3 4.6 0.2 0.1 0.5 0.2 93.8 1,504 Not determined 8.4 3.7 4.8 0.0 0.0 0.0 0.0 90.8 122 Mother’s age 15-19 8.9 0.0 8.9 0.0 0.0 0.0 0.0 91.1 28 20-24 9.1 2.7 4.5 0.8 0.5 1.6 1.0 90.4 203 25-29 8.5 3.0 5.2 0.0 0.0 1.1 0.0 91.5 441 30-34 4.6 1.4 2.6 0.0 0.0 1.0 0.0 94.8 508 35-39 4.8 0.7 4.0 0.2 0.0 0.2 0.1 95.0 632 40-44 3.3 1.0 1.4 0.0 0.2 1.1 0.0 96.4 548 45-49 0.6 0.1 0.5 0.0 0.0 0.0 0.0 99.2 519 Residence Total urban 10.5 3.1 7.2 0.1 0.2 1.4 0.1 89.3 1,011 Asmara 14.0 3.9 10.9 0.0 0.3 1.2 0.0 85.8 386 Other towns 8.4 2.5 4.9 0.1 0.2 1.5 0.2 91.4 625 Rural 1.4 0.3 0.6 0.1 0.0 0.3 0.1 98.2 1,868 Zoba Debubawi Keih Bahri 5.5 2.1 2.4 0.0 0.0 0.8 0.3 94.5 126 Maekel 10.7 3.1 8.4 0.0 0.2 0.9 0.0 89.1 517 Semenawi Keih Bahri 3.4 0.4 1.9 0.2 0.0 0.8 0.3 96.6 462 Anseba 2.7 1.4 1.3 0.0 0.2 0.6 0.0 97.2 494 Gash-Barka 0.7 0.0 0.1 0.0 0.0 0.6 0.0 98.5 517 Debub 5.0 1.2 2.8 0.3 0.0 0.6 0.1 94.6 763 Mother’s education No education 1.4 0.3 0.7 0.1 0.0 0.4 0.1 98.1 2,018 Primary 6.3 1.8 3.8 0.2 0.0 1.9 0.2 93.7 517 Middle 5.1 2.9 0.9 0.0 0.0 1.3 0.0 94.9 141 Secondary + 31.8 9.1 23.8 0.4 1.1 0.6 0.1 68.2 203 Wealth index Lowest 0.7 0.1 0.2 0.1 0.0 0.3 0.0 98.7 652 Second 0.6 0.0 0.3 0.0 0.0 0.3 0.0 99.3 617 Middle 2.5 0.4 1.1 0.2 0.0 0.5 0.2 97.2 553 Fourth 5.4 1.8 2.7 0.2 0.0 1.4 0.2 94.4 588 Highest 16.8 5.0 12.4 0.0 0.5 1.2 0.1 83.0 469 Total 4.6 1.3 2.9 0.1 0.1 0.7 0.1 95.1 2,879 206 | Female Circumcision 12.4 ATTITUDES TOWARD FEMALE CIRCUMCISION Women’s Attitudes toward Female Circumcision Table 12.7 shows the percent distribution of women who know about female circumcision by their attitudes toward female circumcision, according to background characteristics. Attitudes of Eritrean women toward circumcision are evenly divided; the proportion who want female circumcision to continue is the same as the proportion who want it discontinued (49 percent). As expected, women who are not circumcised are more likely to want the practice discontinued (86 percent) than women who have been circumcised (44 percent). However, one-fourth of women who have the most severe type of circumcision and more than half of those with less severe types of circumcision (56-57 percent) think that the practice of circumcision should be discontinued. Not surprisingly, support for continuing the practice is stronger among women who have at least one circumcised daughter (68 percent) than among women with daughters who are not circumcised (32 percent). The pattern of support for circumcision seen in the case of the daughter’s circumcision is the same as the pattern for all women, except that support for continuation of the practice is higher for each type of circumcision in the case of daughters. Seventy-two percent of women in Asmara, 57 percent of women in other urban areas, and 37 percent of women in rural areas believe that female circumcision should be discontinued. Attitudes toward circumcision vary widely by zoba; between 26 percent and 69 percent of women oppose the practice. In zobas Maekel and Debub, the majority of women favor discontinuing the practice. Support for the practice is negatively related to the wealth index. The higher the wealth index, the lower the support is for the continuation of female circumcision. Greater support for discontinuation of circumcision among younger women suggests that the practice is likely to continue declining in the future. However, the change is likely to be much slower in rural areas and in zobas where the most severe form of circumcision is prevalent. Although the 2002 EDHS asked the attitudinal questions on circumcision only to women who reported knowing about female circumcision, while the 1995 EDHS asked these questions to all respondents, the results can still be considered comparable because 99 percent of respondents in the 2002 survey reported knowing about circumcision. It is encouraging to note that women’s attitudes toward circumcision have changed substantially since 1995. The proportion of women who support discontinuing the practice has increased from 38 percent to 49 percent. The change in attitudes has occurred in all sub- groups shown in Table 12.7, and more rapidly in some subgroups, especially those which in the past had the strongest support for continuation. Support for discontinuation of female circumcision increased from 28 percent to 37 percent among rural women, and from 15 percent to 26 percent among women in zoba Gash-Barka. Nonetheless, the changes in attitude do not imply that a similar change in practice will follow soon, because the practice of female circumcision in Eritrea has its roots deep in tradition. Female Circumcision | 207 Table 12.7 Attitudes toward female circumcision by background characteristics Percent distribution of women who have heard of female circumcision by attitude toward female circumcision, according to background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of Thinks female circumcision should be: women who _______________________________ have heard Background Dis- Missing/ of female characteristic Continued continued Depends don’t know Total circumcision ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Respondent’s circumcision Not circumcised 10.7 86.1 0.8 2.4 100.0 920 Circumcised 53.3 44.2 1.7 0.8 100.0 7,765 Sewn closed 73.6 24.2 1.5 0.7 100.0 2,997 Flesh removed 40.0 57.0 1.7 1.4 100.0 318 Nicked, no flesh removed 42.5 55.5 1.5 0.5 100.0 3,572 Not determined 32.4 62.5 2.9 2.3 100.0 879 Daughter’s circumcision No daughter 42.4 55.3 1.2 1.2 100.0 4,081 Daughter not circumcised 32.0 65.9 1.0 1.0 100.0 1,725 Daughter circumcised 67.8 29.0 2.5 0.7 100.0 2,879 Sewn closed 81.1 16.2 2.0 0.7 100.0 1,087 Flesh removed 55.0 43.3 1.6 0.0 100.0 166 Nicked, no flesh removed 61.4 35.3 2.6 0.7 100.0 1,504 Not determined 47.1 45.6 6.0 1.3 100.0 122 Age 15-19 36.9 60.6 1.1 1.4 100.0 1,958 20-24 44.8 53.3 1.1 0.9 100.0 1,443 25-29 46.2 51.8 1.0 1.0 100.0 1,536 30-34 54.1 43.7 1.3 0.9 100.0 1,107 35-39 55.0 42.0 2.2 0.8 100.0 1,081 40-44 60.3 38.0 1.3 0.4 100.0 827 45-49 63.4 30.5 4.8 1.3 100.0 732 Residence Total urban 33.6 64.1 1.6 0.7 100.0 3,738 Asmara 25.6 71.5 1.8 1.1 100.0 1,880 Other towns 41.7 56.6 1.5 0.2 100.0 1,858 Rural 60.2 37.0 1.6 1.2 100.0 4,946 Zoba Debubawi Keih Bahri 57.6 37.3 3.5 1.6 100.0 323 Maekel 27.9 69.3 1.8 1.0 100.0 2,239 Semenawi Keih Bahri 67.9 29.5 1.9 0.7 100.0 1,147 Anseba 56.4 42.3 1.2 0.2 100.0 1,129 Gash-Barka 72.5 25.6 1.0 0.9 100.0 1,492 Debub 39.4 57.6 1.6 1.4 100.0 2,354 Education No education 66.5 30.5 1.9 1.1 100.0 4,361 Primary 45.8 51.4 1.9 0.8 100.0 1,617 Middle 30.5 68.0 0.6 0.9 100.0 962 Secondary + 17.3 80.8 1.1 0.8 100.0 1,745 Wealth index Lowest 71.4 26.9 0.8 0.9 100.0 1,465 Second 62.5 34.4 2.2 0.9 100.0 1,607 Middle 55.9 40.6 1.6 1.8 100.0 1,659 Fourth 37.0 61.4 1.0 0.6 100.0 1,821 Highest 27.4 69.8 2.1 0.7 100.0 2,133 Total 48.8 48.7 1.6 1.0 100.0 8,685 208 | Female Circumcision 12.5 WOMEN’S PERCEPTIONS OF THEIR HUSBAND’S ATTITUDE TOWARD FEMALE CIRCUMCISION Table 12.8 shows women’s perceptions of their husband’s attitude toward circumcision. The table indicates that 43 percent of women believe that their husband supports continuation of the practice of circumcision, while 35 percent feel that their husband supports discontinuation. Twenty-two percent of women do not know their husband’s attitude, which may mean that many couples either do not consider circumcision an important issue to discuss or they are embarrassed to discuss it. Even among currently married women who have at least one circumcised daughter, almost one in five does not know her husband’s attitude toward circumcision. The majority of women believe that their husband shares their attitude toward circumcision. Two- thirds of women who think that female circumcision should be continued, and two-thirds of those who think that the practice should be discontinued, believe that their husband holds the same attitude on the subject. The proportion of women who do not know their husband’s attitude is the same for both groups. By residence, half of rural women think that their husband supports continuation of the practice, compared with only 29 percent of urban women. 12.6 PERCEIVED BENEFITS OF FEMALE CIRCUMCISION Table 12.9 shows the responses of women who have heard of female circumcision to the question about the benefits of a girl being circumcised. Among women who have heard of female circumcision, three in ten report that there are no benefits from circumcision. The subgroups in which at least half of women report no benefits from circumcision are women who are not circumcised, women living in Asmara, and women with at least some secondary education. Additionally, 40 percent of younger women (age 15-19) and women with some middle-level education, and almost half of women living in zoba Maekel and women in the highest quintile of the wealth index, mentioned that there are no benefits from female circumcision. For many Eritrean women circumcision is an important factor in attaining social acceptance and having better marriage prospects. Social acceptance (42 percent) is the most frequently cited benefit of circumcision, followed by better marriage prospects (25 percent), and religious approval (18 percent) (Figure 12.3). Although the subgroups shown in Table 12.9 vary markedly in terms of whether they perceive any benefits from circumcision, these three benefits (in that order) are cited most often by almost all subgroups. Religious approval as a benefit of circumcision was mentioned by one-third of women who had the most severe form of circumcision and 24-30 percent of women in zobas Debubawi Keih Bahri, Gash-Barka, Semenawi Keih Bahri, and Anseba and women in the two lowest quintiles of the wealth index. Among these women, social acceptance is the most frequently mentioned benefit of circumcision followed by religious approval and better marriage prospects. Personal cleanliness or hygiene (13 percent) and the view that female circumcision preserves virginity and prevents premarital sex (4 percent) are mentioned less frequently as benefits of circumcision. However, one-fourth of women who had some flesh removed from their genitals during circumcision and women in zoba Debubawi Keih Bahri, and one-fifth of women in zoba Semenawi Keih Bahri, mentioned personal cleanliness or hygiene as one of the benefits of the practice. Female Circumcision | 209 Table 12.8 Women’s perception of their husband’s attitude toward circumcision Percent distribution of currently married women by their perception of their husband’s attitude toward female circumcision, according to background characteristics, Eritrea 2002 Wife believes husband thinks circumcision should be: Background characteristic Continued Discontinued Missing/ Don’t know Total Number of currently married women Age 15-19 34.6 30.6 34.8 100.0 576 20-24 38.2 34.2 27.6 100.0 945 25-29 39.1 41.8 19.1 100.0 1,206 30-34 48.6 32.5 18.9 100.0 902 35-39 43.3 38.0 18.7 100.0 897 40-44 51.4 30.9 17.7 100.0 663 45-49 54.0 26.4 19.6 100.0 526 Residence Urban 29.2 53.2 17.6 100.0 1,965 Asmara 19.1 64.7 16.2 100.0 867 Other towns 37.2 44.1 18.8 100.0 1,099 Rural 50.9 25.0 24.1 100.0 3,749 Zoba Debubawi Keih Bahri 39.8 26.8 33.4 100.0 210 Maekel 22.0 61.8 16.2 100.0 1,100 Semenawi Keih Bahri 59.6 20.5 19.9 100.0 817 Anseba 56.4 23.8 19.7 100.0 784 Gash-Barka 67.5 14.2 18.3 100.0 1,135 Debub 27.6 43.8 28.6 100.0 1,669 Education No education 54.4 22.2 23.4 100.0 3,538 Primary 32.8 42.9 24.3 100.0 1,068 Middle 27.5 49.9 22.7 100.0 400 Secondary + 13.7 76.1 10.2 100.0 708 Husband’s education No education 60.4 17.6 22.0 100.0 2,808 Primary 35.3 40.8 23.9 100.0 1,207 Middle 26.2 49.4 24.4 100.0 527 Secondary + 19.0 63.5 17.5 100.0 1,129 Wife’s attitude toward circumcision Continued 68.6 10.7 20.6 100.0 3,105 Discontinued 13.0 65.9 21.1 100.0 2,460 Depends 28.2 21.0 50.7 100.0 97 Daughter’s circumcision status No daughter 37.4 31.9 30.7 100.0 1,760 Daughter not circumcised 28.1 54.9 17.0 100.0 1,503 Daughter circumcised 57.2 24.2 18.6 100.0 2,452 Sewn closed 73.3 11.9 14.8 100.0 990 Flesh removed 50.0 40.8 9.2 100.0 136 Nicked, no flesh removed 46.6 30.8 22.6 100.0 1,231 Not determined 37.6 43.4 18.9 100.0 96 Total 43.4 34.7 21.9 100.0 5,714 Note: Total includes 44 women with missing information on husband’s education, and 52 women with missing information on their attitude toward circumcision, who are not shown separately. 210 | Female Circumcision Table 12.9 Perceived benefits of female circumcision Percentage of women who have heard of female circumcision and who report specific benefits of female circumcision for a girl, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Perceived benefits of female circumcision –––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of Preserves women who Clean- Better virginity/ have heard Background No liness/ Social marriage prevents pre- Religious of female characteristic benefit hygiene acceptance prospects marital sex approval Other circumcision ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of circumcision Not circumcised 62.8 3.1 15.9 13.6 2.8 4.8 4.9 920 Circumcised 25.1 14.3 45.3 25.8 4.5 19.2 3.1 7,765 Sewn closed 12.5 17.2 59.7 23.1 5.3 32.2 0.9 2,997 Flesh removed 37.7 23.9 26.0 20.6 5.2 21.8 1.7 318 Nicked, no flesh removed 29.7 12.2 39.3 30.1 3.9 10.6 4.9 3,572 Not determined 45.1 9.2 27.8 19.3 4.0 8.8 3.8 879 Age 15-19 40.0 7.9 34.4 19.5 2.8 13.0 4.1 1,958 20-24 32.4 11.7 38.9 23.0 3.7 16.8 3.7 1,443 25-29 30.7 13.6 41.6 24.8 4.7 18.2 2.8 1,536 30-34 25.3 15.2 44.5 25.7 3.8 21.1 2.3 1,107 35-39 23.0 17.2 46.9 27.5 4.8 19.1 2.5 1,081 40-44 20.3 15.5 49.6 26.5 7.4 20.4 2.8 827 45-49 14.8 17.2 52.1 31.6 4.9 19.9 4.6 732 Residence Total urban 40.5 11.6 32.5 22.4 3.5 12.0 3.6 3,738 Asmara 50.1 9.1 20.5 20.0 4.4 9.2 4.2 1,880 Other towns 30.8 14.2 44.6 24.8 2.6 14.8 2.9 1,858 Rural 20.5 14.2 49.6 26.1 4.9 21.9 3.1 4,946 Zoba Debubawi Keih Bahri 23.9 25.0 50.8 19.1 2.5 25.1 2.6 323 Maekel 48.7 9.6 21.3 20.9 4.2 9.4 4.1 2,239 Semenawi Keih Bahri 14.8 21.1 51.5 26.5 4.0 26.5 1.1 1,147 Anseba 18.2 7.0 62.9 23.9 5.6 30.3 0.9 1,129 Gash-Barka 15.0 15.2 58.2 22.6 4.4 24.3 5.3 1,492 Debub 32.4 12.6 36.3 29.1 4.1 9.9 3.6 2,354 Education No education 16.3 16.2 53.1 27.2 5.2 24.2 2.9 4,361 Primary 28.4 14.0 40.9 27.5 3.9 14.1 4.4 1,617 Middle 40.8 8.4 32.6 21.4 3.9 11.9 3.2 962 Secondary + 55.4 7.3 21.4 16.7 2.7 7.6 3.4 1,745 Wealth index Lowest 13.7 15.0 57.3 25.0 6.5 27.8 1.6 1,465 Second 18.1 15.0 52.2 26.2 4.7 23.8 3.6 1,607 Middle 23.4 13.7 47.1 25.4 4.0 18.3 3.8 1,659 Fourth 36.1 13.6 34.2 25.9 3.3 12.5 3.0 1,821 Highest 46.5 9.5 27.3 20.9 3.6 9.9 4.1 2,133 Total 29.1 13.1 42.2 24.5 4.3 17.6 3.3 8,685 Female Circumcision | 211 EDHS 2002 Figure 12.3 Perceived Benefits of Female Circumcision 13 42 25 4 18 3 29 Cleanliness Social acceptance Better marriage prospects Preserve virginity Religious approval Other No benefit 0 20 40 60 80 100 Percent 12.7 PERCEIVED BENEFITS OF GIRLS NOT BEING CIRCUMCISED Table 12.10 shows the responses of women who have heard of female circumcision to the question about the benefits of a girl not being circumcised. Forty-three percent of women report that there would be no benefit to a girl not being circum- cised. More than half of women age 40-49, rural women, uneducated women, women in zobas Semenawi Keih Bahri and Anseba, and women in the lowest quintile of the wealth index say that there are no benefits to a girl not being circumcised. Among those who perceive benefits to not being circumcised, avoiding pain (30 percent), having fewer medical problems (16 percent), and more sexual pleasure for the woman (14 percent) are the most frequently cited benefits (Figure 12.4). Less than 5 percent reported that an uncircumcised girl would give more pleasure to her husband than a circumcised girl, and the same proportion said that an uncircumcised girl would be following religion. Avoiding pain is the most frequently cited benefit among all subgroups; more than four in ten uncircumcised women (45 percent) cited this benefit. The proportion mentioning “fewer medical problems” as a benefit to not being circumcised increases steadily from 8 percent of women in the lowest wealth quintile to 22 percent in the highest wealth quintile. A similar pattern is observed by women’s education. The more education a woman has, the more likely she is to believe that girls have fewer medical problems if they are not circumcised. Urban women—especially those in Asmara—are more likely than rural women to cite more sexual pleasure for the girl as a benefit of not being circumcised. 212 | Female Circumcision Table 12.10 Perceived benefits of not undergoing female circumcision Percentage of women who have heard of female circumcision and who report specific benefits of a girl not being circumcised, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Perceived benefits of not undergoing female circumcision –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of More women who Fewer More sexual sexual have heard Background No medical Avoiding pleasure pleasure Follows of female characteristic benefits problems pain for her for men religion Other circumcision –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of circumcision Not circumcised 30.2 22.9 44.7 12.9 2.7 1.3 5.4 920 Circumcised 44.8 14.7 28.3 13.6 5.1 4.4 4.9 7,765 sewn closed 51.3 10.6 25.3 7.7 4.1 8.5 3.8 2,997 Flesh removed 32.9 23.4 26.9 20.6 9.5 5.0 8.7 318 Nicked, no flesh removed 41.4 18.0 30.1 17.8 5.1 1.9 4.9 3,572 Not determined 40.5 12.3 31.3 14.1 6.5 0.7 6.7 879 Age 15-19 38.8 19.3 35.4 11.2 3.6 3.4 6.2 1,958 20-24 39.2 17.7 33.2 13.5 4.9 4.1 4.9 1,443 25-29 41.7 16.1 33.2 13.7 4.9 4.9 4.3 1,536 30-34 45.5 12.6 27.4 15.6 6.2 3.7 3.0 1,107 35-39 44.2 13.8 26.9 17.5 4.7 3.9 5.6 1,081 40-44 50.3 12.5 22.0 13.4 6.0 5.1 4.6 827 45-49 53.4 11.2 20.1 10.6 4.8 4.1 5.1 732 Residence Total urban 34.7 20.9 35.1 18.3 5.6 2.5 5.1 3,738 Asmara 31.3 20.2 32.8 22.9 7.2 2.2 7.1 1,880 Other towns 38.1 21.7 37.4 13.6 4.0 2.8 3.1 1,858 Rural 49.7 11.6 26.2 9.9 4.2 5.3 4.7 4,946 Zoba Debubawi Keih Bahri 41.0 16.2 27.3 7.9 1.2 9.5 12.0 323 Maekel 32.3 19.7 31.4 22.1 7.0 2.2 7.8 2,239 Semenawi Keih Bahri 57.4 13.7 28.5 7.1 1.1 2.5 0.8 1,147 Anseba 53.7 11.0 31.5 6.1 3.9 5.5 1.0 1,129 Gash-Barka 48.6 14.6 19.5 11.6 6.7 9.7 5.3 1,492 Debub 38.6 15.4 35.7 14.1 4.3 1.8 4.8 2,354 Education level No education 51.4 9.8 24.7 9.8 4.5 6.2 4.6 4,361 Primary 43.0 16.8 29.4 15.9 4.8 2.1 5.2 1,617 Middle 36.8 19.0 34.1 15.5 5.0 1.9 7.0 962 Secondary + 26.6 27.2 41.6 19.5 5.4 1.8 4.3 1,745 Wealth index Lowest 54.6 8.2 24.6 9.6 3.7 5.7 3.2 1,465 Second 49.0 10.4 25.6 9.1 4.8 8.1 4.2 1,607 Middle 48.7 15.9 25.4 9.2 4.3 3.5 5.5 1,659 Fourth 37.2 19.0 35.4 16.7 4.8 2.4 4.6 1,821 Highest 31.9 21.5 36.1 20.2 6.1 2.0 6.4 2,133 Total 43.2 15.6 30.0 13.5 4.8 4.1 4.9 8,685 Female Circumcision | 213 EDHS 2002 Figure 12.4 Perceived Benefits of Not Undergoing Female Circumcision 16 30 14 5 4 5 43 Fewer medical problems Avoiding pain More sexual pleasure for woman More sexual pleasure for man Follows religion Other No benefit 0 20 40 60 80 100 Percent 12.8 BELIEFS ABOUT CIRCUMCISION Female circumcision is practiced by all religious groups in Eritrea, including traditional believers, despite the fact that in recent years religious leaders of all faiths have either spoken against the practice or distanced themselves from showing support for the practice. Table 12.11 shows the percentage of women who agree with two statements about circumcision—that circumcision is required by religion and that circumcision prevents premarital sex. The results provide insight into the factors that contribute to the widespread support for female circumcision. Overall, 60 percent of women who have heard of female circumcision agree with the statement that circumcision is required by religion and 29 percent of women agree with the statement that female circumcision prevents premarital sex. The differentials by background characteristics in the belief that circumcision is required by religion and that circumcision prevents premarital sex show the same pattern. Women’s age has a positive relationship with both statements, while women’s education and wealth have strong negative relationships with both statements. The differences by education are most marked. For example, 70 percent of women with no education believe that circumcision is required by religion, compared with 41 percent of women with at least some secondary education. The same pattern is seen for belief that female circumcision prevents premarital sex (38 percent and 13 percent, respectively). Women in urban areas, Asmara, and zoba Maekel, and women in the highest quintile of the wealth index are considerably less likely than other women to believe that circumcision is a religious requirement (47-51 percent) or that it prevents premarital sex (18-21 percent). In contrast, around seven in ten women age 45-49, women in the two lowest quintiles of the wealth index, and women in zobas Gash-Barka and Anseba believe that female circumcision is required by religion. Almost four in ten women age 40 and older and women in Gash- Barka believe that female circumcision prevents premarital sex. 214 | Female Circumcision Table 12.11 Beliefs about female circumcision Percentage of women who have heard of female circumcision and who agree with two specific statements about circumcision, by background characteristics, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––– Female Number of Female circumcision women who circumcision prevents have heard Background is required premarital of female characteristic by religion sex circumcision –––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 53.4 20.1 1,958 20-24 60.4 23.6 1,443 25-29 59.0 28.8 1,536 30-34 62.8 31.3 1,107 35-39 62.4 32.1 1,081 40-44 63.7 38.7 827 45-49 68.6 38.6 732 Residence Total urban 51.3 20.6 3,738 Asmara 46.7 17.7 1,880 Other towns 56.1 23.5 1,858 Rural 66.8 34.5 4,946 Zoba Debubawi Keih Bahri 66.8 36.6 323 Maekel 47.9 19.3 2,239 Semenawi Keih Bahri 65.9 36.9 1,147 Anseba 68.1 26.8 1,129 Gash-Barka 70.0 37.6 1,492 Debub 58.1 27.0 2,354 Education No education 70.1 37.8 4,361 Primary 59.4 26.8 1,617 Middle 52.0 17.0 962 Secondary + 40.6 13.2 1,745 Wealth index Lowest 71.2 36.4 1,465 Second 69.1 37.5 1,607 Middle 62.3 31.6 1,659 Fourth 56.8 23.8 1,821 Highest 47.0 17.9 2,133 Total 60.1 28.5 8,685 12.9 PROBLEMS ASSOCIATED WITH FEMALE CIRCUMCISION Long-term complications of female circumcision can cause suffering for many years. Hardening of the scar tissue (keloids) can cause problems during sexual intercourse or at the time of delivery. In order to ascertain the extent of complications, circumcised women who had ever had sex were asked whether they had had any health problems or other complications during sexual intercourse due to circumcision. Women who had had at least one birth were also asked whether they had had any problem at the time of delivery. Because the problems associated with circumcision were self-diagnosed, it is likely that some respondents did not report having problems because they did not recognize them as such Female Circumcision | 215 and regarded their experience as normal and natural for women. This is most likely among women in groups with higher rates of female circumcision. Seven percent of circumcised women who had ever had sex reported having problems during sexual relations due to their circumcision (Table 12.12). Among circumcised women who had at least one birth, 11 percent reported having problems during delivery and 4 percent reported having problems both during sexual relations and delivery. These findings indicate a slight decrease from 1995 in the extent of the problems. For example, the proportion of women reporting problems during sexual relations declined from 12 percent in 1995 to 7 percent in 2002, and the proportion citing problems during delivery fell from 17 to 11 percent. The type of circumcision has a direct link with the proportion of women who have problems Table 12.12 Problems associated with female circumcision Among circumcised women who have ever had sex, the percentage who had problems or complica- tions during sexual relations as a result of being circumcised, and among circumcised women who had at least one birth, the percentage who had problems or complications during delivery as a result of be- ing circumcised, by background characteristics, Eritrea 2002 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Circumcised women who have ever had sex Circumcised women who have given birth ––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––– Had Had Number of problem Number of problem circumcised Had during circumcised during women who problem sexual women who Background sexual have ever during relations have given characteristic relations had sex delivery and delivery birth ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of circumcision Sewn closed 14.6 2,556 21.7 9.4 2,158 Flesh removed 6.6 234 6.2 3.6 203 Nicked, no flesh removed 0.9 2,779 2.5 0.5 2,434 Not determined 2.3 647 4.3 1.0 561 Age 15-19 11.0 524 18.6 8.6 167 20-24 9.7 967 13.1 6.1 722 25-29 6.9 1,264 11.5 4.2 1,144 30-34 5.3 1,002 9.5 3.2 942 35-39 5.0 989 9.3 3.2 950 40-44 6.1 774 9.7 4.3 754 45-49 5.7 695 8.5 4.3 677 Education No education 8.3 3,831 12.8 5.3 3,412 Primary 6.0 1,157 8.3 3.3 971 Middle 4.0 446 7.3 2.7 345 Secondary + 2.8 781 3.8 1.0 629 Wealth index Lowest 10.1 1,181 15.1 5.8 1,019 Second 8.1 1,287 14.3 5.0 1,093 Middle 8.6 1,291 10.4 5.3 1,093 Fourth 4.1 1,246 7.8 3.0 1,106 Highest 3.6 1,211 5.2 2.2 1,046 Total 6.9 6,216 10.5 4.3 5,357 216 | Female Circumcision during sexual relations and at delivery. Women who have had the most severe type of circumcision are much more likely to report experiencing problems during sexual relations (15 percent) and at delivery (22 percent) than women who have had the least severe form of circumcision (1 percent and 3 percent, respectively). Younger women (under 25) are more likely than older women to report having problems during sexual relations because of circumcision. For example, 11 percent of women age 15-19 reported having problems during sexual relations, compared with 5 percent of women age 30-34. Both level of education and wealth index quintile are negatively correlated with women reporting problems during sexual relations or delivery because of circumcision. Women who had problems or complications during sexual relations and at delivery as a result of being circumcised were asked what they did to treat the problems. 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Statistics Department, Ministry of Finance and Economic Planning [Uganda] and Macro International Inc. 1996. Uganda Demographic and Health Survey, 1995. Calverton, Maryland, USA: Statistics Department, Ministry of Finance and Economic Planning and Macro International Inc. Uganda Bureau of Statistics (UBOS) and ORC Macro. 2001. Uganda Demographic and Health Survey 2000-2001. Calverton, Maryland, USA: Uganda Bureau of Statistics and ORC Macro. UNAIDS. 2002. Report on the global HIV/AIDS epidemic. Geneva, Switzerland: UNAIDS. United Nations Development Program (UNDP). 2001. Human development index. New York: Oxford University Press. University of Asmara. 2000. From border dispute to open invasion: A report on Ethiopia’s aggression against Eritrea and its consequences. Asmara, Eritrea: University of Asmara. World Food Programme (WFP). 2002. Nutrition mission report. Asmara, Eritrea: World Food Programme. World Health Organization (WHO). 1996. Female genital mutilation: A report of a WHO technical working group, Geneva, 17-19 July 1995. Geneva: World Health Organization. World Health Organization (WHO). 2002a. Primary health care review, 1995-2000. Asmara, Eritrea: World Health Organization. World Health Organization (WHO). 2002b. Roll back malaria. Geneva: World Health Organization. World Health Organization (WHO) and UNICEF. 1998. Complementary feeding of young children in developing countries: A review of current scientific knowledge. Geneva: World Health Organization. World Health Organization (WHO) and UNICEF. 2003. The Africa malaria report 2003. Geneva: World Health Organization. Appendix A | 219 SAMPLE DESIGN APPENDIX A A.1 INTRODUCTION The 2002 Demographic and Health Survey in Eritrea was expected to provide a minimum of 7,500 completed interviews of women age 15-49 years, after taking into account a similar level of non- response found in the 1995 EDHS. Actually, the sample yielded 8,754 completed cases. The sample design provides reliable estimates of indicators for the entire country, for urban and rural areas, and for each of the six zobas in Eritrea. A.2 SAMPLE FRAME Administratively, Eritrea is divided into six zobas, and each zoba is divided into subzobas. For each subzoba, the sample design is based on a list of all towns in urban areas and all villages in rural areas. Because no census material or recent sampling frame was available, the 2000 list of residential units with basic statistical information, compiled by the Ministry of Local Government, was used as the frame for the 2002 EDHS sample design. A.3 STRATIFICATION In the frame, the lists of towns and villages were stratified separately by urban and rural areas within each subzoba and zoba. For practical purposes, the village is a convenient unit for a new household listing. However, since towns have large variations in population size, they are not very convenient for a complete household listing process. Large towns required a further subsampling of smaller units (blocks) and/or an additional segmentation process. A.4 SAMPLE ALLOCATION The primary sampling unit (PSU)—cluster—for the 2002 EDHS was defined on the basis of Standard Segment Areas (SSA). Since each SSA has about 200 households, a minimum requirement of 200 households per cluster size was imposed in the design. The number of clusters in each of the six zobas was not allocated proportionally to their total population because of the need to present estimates for each zoba. In Eritrea, about three-fourths of the population reside in rural areas. Table A.1 shows the proportional and square root allocations of the 368 clusters. The target for the 2002 EDHS sample was to obtain a minimum of about 7,500 completed interviews. Based on the level of nonresponse found in the 1995 EDHS, to achieve this target, approximately 9,800 households were selected, and all women age 15-49 were to be interviewed. The target was to reach a minimum of 1,000 completed interviews per zoba. In each zoba the number of households was distributed proportionately between urban and rural areas. Table A.2 shows the distribution of households by zoba. 220 | Appendix A Table A.1 Proportional and square root allocations of clusters Proportional and square root allocations of 368 clusters, by zoba, Eritrea 2002 Sample of 368 clusters Zoba Percentage of households 2000 Proportional allocation Square root allocation Adjusted Debubawi Keih Bahri 2.97 11 28 41 Semenawi Keih Bahri 18.12 67 68 60 Anseba 15.68 58 64 59 Gash-Barka 24.50 90 79 71 Debub 33.67 123 93 79 Maekel 5.07 19 36 58 Total 100.00 368 368 368 Table A.2 Expected number of selected households to reach the target of completed interviews Expected number of selected households to reach the target of completed interviews, by zoba, Eritrea 2002 Zoba Expected number of completed interviews, 2002 EDHS Completed interviews, 1995 EDHS Selected households, 1995 EDHS Expected house- holds selected, 2002 EDHS Debubawi Keih Bahri 1,000 273 447 1,637 Semenawi Keih Bahri 1,000 803 1,213 1,511 Anseba 1,100 559 743 1,462 Gash-Barka 1,300 834 1,146 1,786 Debub 1,550 852 1,081 1,967 Maekel 1,550 1,733 1,628 1,456 Total 7,500 5,054 6,258 9,819 The selected households were distributed in 368 clusters (119 clusters in the urban areas and 249 clusters in the rural areas). Table A.3 and the map on page 221 show the distribution of clusters selected for the 2002 EDHS. Table A.3 Final allocation of women 15-49 with completed interviews and clusters in each zoba Final allocation of women 15-49 with completed interviews and clusters in each zoba, by urban and rural areas, Eritrea 2002 Number of clusters Zoba Expected number of completed interviews Rural Urban Total Debubawi Keih Bahri 1,000 23 18 41 Semenawi Keih Bahri 1,000 41 19 60 Anseba 1,100 45 14 59 Gash-Barka 1,300 60 11 71 Debub 1,550 67 12 79 Maekel 1,550 13 45 58 Total 7,500 249 119 368 Sampling Points for the 2002 Eritrea Demographic and Health Survey Appendix A | 221 Ethiopia Djibouti Sudan R E D S E A Saudi Arabia Republic of Yemen Note: This is not the official and political map of Eritrea. 222 | Appendix A Under this final allocation, estimates could also be produced for Asmara city since there were 43 selected clusters in Asmara. A.5 SAMPLE SELECTION The 2002 EDHS sample was selected using a stratified two-stage cluster design. In every zoba except zoba Debubawi Keih Bahri, the calculated average sample take was 25 households. In zoba Debubawi Keih Bahri, the calculated average sample take was about 40 households. All women age 15- 49 years in the selected households were eligible for the individual interview. Once the number of households was allocated to each zoba, clusters were selected using the following procedure. Lists of towns and villages in each zoba were ordered by urban and rural residence. All rural units were ordered at the top of the list and then all urban units were ordered at the bottom of the list. The selected clusters were identified using a systematic selection with sampling interval I=[{Σ Mi}]/a, (see symbol definition below), which is equivalent to a systematic selection of PSUs with probability proportional to the number of households in each unit. The selection was done using the following formula: P1i = (a * Mi) / (Σ Mi) where, a: is the number of clusters to be selected in the given zoba, Mi: is the number of households in the ith PSU reported in the 2000 sample frame, Σ Mi: is the number of households in the zoba according to the 2000 sample frame. In the selected PSUs that contained two or more standard segments, a segmentation process was recommended to choose only one segment part with probability proportional to size (i.e., P2i, meaning the probability of selecting a segment within a PSU). A complete household listing process was implemented in the selected segment. In all other selected PSUs, a complete household listing operation was carried out and households were selected to achieve a self-weighted sampling fraction in each zoba. However, since the 2002 EDHS sample is unbalanced among zobas, a final weighting adjustment was required to provide estimates in every other domain. In a given zoba, if the overall sampling fraction (f) has been calculated, and if ci is the number of households selected in the ith cluster out of the total number of households (Li), found in the 2002 listing process, then the self-weighting condition can be expressed as: f = P1i * P2i * (ci / Li) The final number of households in the ith cluster is calculated as: ci = ( f * Li ) / (P1i * P2i ) and the household selection interval for the ith cluster is given as: Ii = Li / ci Ii = (P1i * P2i) / f Appendix A | 223 A.6 SAMPLE IMPLEMENTATION The results of the sample implementation for the households and the individual interviews are shown in Table A.4. In all, 9,824 households were selected for interviewing. The 2002 EDHS fieldwork teams successfully completed interviews in 9,389 households. The main reasons that selected potential households were not interviewed were that the dwellings where the selected households were living were destroyed or households were away for an extended time period (3 percent of selected households could not be interviewed for these reasons). A total of 9,512 households were occupied, of which 9,389 were successfully interviewed. Overall, the household response rate was 98.7 percent. The household response rate was similar in urban and rural areas and in the six zobas (between 98.1 and 99.7 percent). In the interviewed households, 9,096 eligible women were identified, of whom 96.2 percent were interviewed. The individual women’s response rate was similar in urban and rural areas and in the six zobas (between 93.0 percent and 97.8 percent). Table A.4 Sample implementation Percent distribution of households and eligible women by results of the household and individual interviews, and household, eligible women and overall response rates, according to urban-rural residence and zoba, Eritrea 2002 Residence Zoba Result Total urban Asmara Other urban Rural Debubawi Keih Bahri Maekel Semenawi Keih Bahri Anseba Gash- Barka Debub Total Selected households Completed (C) 96.4 95.1 97.0 95.2 92.5 94.7 98.4 99.6 93.8 95.2 95.6 HH present but no competent respondent at home (HP) 1.4 1.7 1.3 1.1 0.9 1.7 0.7 0.3 1.7 1.6 1.2 Refused (R) 0.1 0.2 0.1 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 Dwelling not found (DNF) 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 Household absent (HA) 1.5 2.0 1.2 3.1 6.1 2.3 0.5 0.1 3.6 2.5 2.6 Dwelling vacant/ address not a dwelling (DV) 0.5 0.9 0.3 0.4 0.2 0.9 0.1 0.0 0.6 0.7 0.4 Dwelling destroy (DD) 0.1 0.1 0.1 0.2 0.1 0.2 0.2 0.0 0.3 0.1 0.1 Other (O) 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of sampled households 3,245 1,076 2,169 6,579 1,632 1,453 1,502 1,476 1,778 1,983 9,824 Household response rate (HRR) 98.4 98.1 98.6 98.8 98.8 98.1 99.3 99.7 98.2 98.3 98.7 Eligible women Completed (EWC) 95.1 93.2 96.2 96.9 95.8 93.0 96.3 97.8 97.8 96.8 96.2 Not at home (EWNH) 2.9 3.9 2.3 1.8 2.7 3.7 2.2 1.6 1.2 1.7 2.2 Postponed (EWP) 0.1 0.2 0.0 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 Refused (EWR) 0.4 0.4 0.4 0.1 0.5 0.4 0.2 0.0 0.0 0.2 0.2 Partly completed (EWPC) 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 Incapacitated (EWI) 0.7 0.8 0.7 1.0 0.7 1.1 1.2 0.5 0.9 1.1 0.9 Other (EWO) 0.6 1.4 0.1 0.1 0.1 1.6 0.1 0.0 0.0 0.0 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 3,343 1,205 2,138 5,753 1,535 1,509 1,470 1,450 1,446 1,686 9,096 Eligible women response rate (EWRR) 95.1 93.2 96.2 96.9 95.8 93.0 96.3 97.8 97.8 96.8 96.2 Overall response rate (ORR) 93.6 91.4 94.9 95.8 94.6 91.3 95.6 97.5 96.1 95.2 95.0 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: 100 x C C + HP + R + DNF 2 Using the number of eligible women falling in to specific response categories, the eligible woman response rate (EWRR) is calculated as: 100 x EWC EWC + EWNH+ EWP + EWR + EWPC+ EWI + EWO Appendix B | 225 SAMPLING ERRORS APPENDIX B The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2002 EDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2002 EDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design. If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2002 EDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2002 EDHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration. The variance of r is computed using the formula given below, with the standard error being the square root of the variance: var( )r f x m m z z m h h hi h hi m h H h = − − −        == ∑∑ 1 12 2 2 11 in which zhi = yhi – r.xhi, and zh = yh – r.xh where h represents the stratum which varies from 1 to H, mh is the total number of clusters selected in the hth stratum, yhi is the sum of the values of variable y in ith cluster in the hth stratum, 226 | Appendix B xhi is the sum of the number of cases in ith cluster in the hth stratum, and f is the overall sampling fraction, which is so small that it is ignored. The Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one clusters in the calculation of the estimates. Pseudo- independent replications are thus created. In the 2002 EDHS, there were 368 non-empty clusters. Hence, 368 replications were created. The variance of a rate r is calculated as follows: SE r r k k r r i k i 2 1 21 1 ( ) var( ) ( ) ( )= = − − = ∑ in which ri = kr − (k − 1 ) r(i) where r is the estimate computed from the full sample of 368 clusters, r(i) is the estimate computed from the reduced sample of 367 clusters (ith cluster excluded), and k is the total number of clusters. In addition to the standard error, ISSAS computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. ISSAS also computes the relative error and confidence limits for the estimates. Sampling errors for the 2002 EDHS are calculated for selected variables considered to be of primary interest. The results are presented in this appendix for the country as a whole, for total urban, Asmara, other towns, and rural areas, and for each of six the zobas in the country. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1. Tables B.2 to B.12 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), for each variable. The DEFT is considered undefined when the standard error assuming a simple random sample is zero (when the estimate is close to 0 or 1). In general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of sub-populations. For example, for the variable contraceptive use for currently married women age 15-49, the relative standard errors as a percent of the estimated mean for the whole country, for urban areas, and for rural areas are 6.7 percent, 7.0 percent, and 14.8 percent, respectively. The confidence interval (e.g., as calculated for contraceptive use for currently married women age 15-49) can be interpreted as follows: the overall national sample proportion is 0.080 and its standard error is 0.005. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e. 0.080±2 (0.005). There is a high probability (95 percent) that the true average proportion of contraceptive use for currently married women age 15 to 49 is between 0.070 and 0.090. Appendix B | 227 Table B.1 List of selected variables for sampling errors, Eritrea 2002 Variable Estimate Base population Urban residence Proportion All women No education Proportion All women Literate Proportion All women Primary school net attendance ratio Proportion Children 7-11 years Secondary education or higher Proportion All women Migrant Proportion All women Migrant due to marriage Proportion Migrant women Adolescent childbearing Proportion Women 15-19 Never married Proportion All women Currently married Proportion All women Married before age 20 Proportion Women age 20-49 Had first sexual intercourse before age 18 Proportion Women age 25-49 Currently pregnant Proportion All women Children ever born Mean All women Children ever born to women age 40-49 Mean Women 40-49 Children surviving Mean All women Know any contraceptive method Proportion Currently married women Know any modern method Proportion Currently married women Ever used any contraceptive method Proportion Currently married women Currently using any contraceptive method Proportion Currently married women Current using a modern method Proportion Currently married women Currently using pill Proportion Currently married women Currently using IUD Proportion Currently married women Currently using injectables Proportion Currently married women Currently using Norplant Proportion Currently married women Currently using condom Proportion Currently married women Currently using female sterilization Proportion Currently married women Currently using periodic abstinence Proportion Currently married women Currently using withdrawal Proportion Currently married women Used public sector source for contraceptive Proportion Currently married women using modern methods Want no more children Proportion Currently married women Want to delay birth at least two years Proportion Currently married women Ideal family size Mean All women Mother received tetanus injection for last birth Proportion Women with at least one live birth in five years before survey Mother received medical assistance at delivery Proportion Births occurring 1-59 months before survey Child had diarrhea in the last two weeks Proportion Children under age five Child treated for diarrhea with ORS solution Proportion Children with diarrhea in two weeks before interview Child received medical treatment for diarrhea Proportion Children with diarrhea in two weeks before interview Child’s vaccination card seen Proportion Children age 12-23 months Child received BCG vaccination Proportion Children age 12-23 months Child received DPT vaccination (three doses) Proportion Children age 12-23 months Child received polio vaccination (three doses) Proportion Children age 12-23 months Child received measles vaccination Proportion Children age 12-23 months Child fully immunized Proportion Children age 12-23 months Weight-for-height (below –2 SD) Proportion Children age 0-59 months Height-for-age (below –2 SD) Proportion Children age 0-59 months Weight-for-age (below –2 SD) Proportion Children age 0-59 months Total fertility rate (three years) Rate All women Neonatal mortality rate Rate Births in 5 (10) years before the survey Postneonatal mortality rate Rate Births in 5 (10) years before the survey Infant mortality rate Rate Births in 5 (10) years before the survey Child mortality rate Rate Births in 5 (10) years before the survey surviving to age one Under-five mortality rate Rate Births in 5 (10) years before the survey 228 | Appendix B Table B.2 Sampling errors for selected variables, total sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.430 0.010 8754 8754 1.970 0.024 0.409 0.451 No education 0.501 0.011 8754 8754 2.032 0.022 0.479 0.522 Literate 0.491 0.010 8754 8754 1.953 0.021 0.470 0.512 Primary school net attendance ratio 0.612 0.011 6947 6859 1.645 0.018 0.590 0.633 Secondary education or higher 0.201 0.008 8754 8754 1.984 0.042 0.184 0.218 Migrant 0.540 0.010 8754 8754 1.832 0.018 0.520 0.560 Migrant due to marriage 0.407 0.013 4285 4727 1.731 0.032 0.381 0.433 Adolescent childbearing 0.140 0.010 1861 2001 1.201 0.069 0.120 0.159 Never married 0.233 0.007 8754 8754 1.502 0.029 0.220 0.247 Currently married 0.655 0.008 8754 8754 1.545 0.012 0.639 0.671 Married before age 20 0.629 0.008 6893 6753 1.441 0.013 0.612 0.646 Had first sexual intercourse before 18 0.506 0.009 5507 5298 1.385 0.018 0.487 0.524 Children ever born 2.662 0.037 8754 8754 1.244 0.014 2.587 2.737 Children ever born to women age 40-49 5.916 0.098 1645 1561 1.377 0.017 5.720 6.112 Children surviving 2.298 0.031 8754 8754 1.197 0.014 2.236 2.361 Currently pregnant 0.088 0.004 8754 8754 1.199 0.041 0.081 0.095 Know any contraceptive method 0.875 0.009 5970 5733 2.144 0.010 0.857 0.893 Know any modern method 0.850 0.010 5970 5733 2.068 0.011 0.831 0.869 Ever used any contraceptive method 0.223 0.009 5970 5733 1.644 0.040 0.205 0.241 Currently using any method 0.080 0.005 5970 5733 1.540 0.067 0.070 0.091 Current using a modern method 0.051 0.005 5970 5733 1.643 0.091 0.042 0.061 Currently using pill 0.014 0.003 5970 5733 1.737 0.186 0.009 0.020 Currently using IUD 0.004 0.001 5970 5733 1.238 0.268 0.002 0.005 Currently using injectables 0.026 0.003 5970 5733 1.401 0.112 0.020 0.031 Currently using Norplant 0.000 0.000 5970 5733 0.467 0.999 0.000 0.000 Currently using condom 0.006 0.001 5970 5733 1.218 0.203 0.004 0.008 Currently using female sterilization 0.002 0.001 5970 5733 1.066 0.352 0.000 0.003 Currently using periodic abstinence 0.007 0.001 5970 5733 1.235 0.194 0.004 0.009 Currently using withdrawal 0.001 0.000 5970 5733 1.274 0.585 0.000 0.002 Used public sector source for contraceptive 0.740 0.029 272 334 1.106 0.040 0.681 0.799 Want no more children 0.176 0.006 5970 5733 1.282 0.036 0.163 0.188 Want to delay next birth at least two years 0.386 0.009 5970 5733 1.382 0.023 0.369 0.404 Ideal family size 5.778 0.045 7452 7689 1.521 0.008 5.688 5.868 Mother received tetanus injection for last birth 0.502 0.012 4271 4175 1.507 0.023 0.479 0.525 Mother received medical assistance at delivery 0.283 0.012 6366 6156 1.682 0.041 0.259 0.306 Child had diarrhea in the last two weeks 0.132 0.005 5893 5748 1.210 0.042 0.121 0.143 Child treated for diarrhea with ORS solution 0.447 0.022 740 759 1.163 0.049 0.403 0.490 Child received medical treatment for diarrhea 0.419 0.023 740 759 1.238 0.054 0.374 0.464 Child’s vaccination card seen 0.767 0.019 971 959 1.386 0.025 0.729 0.806 Child received BCG vaccination 0.914 0.013 971 959 1.445 0.015 0.887 0.941 Child received DPT vaccination (three doses) 0.828 0.016 971 959 1.315 0.020 0.796 0.860 Child received polio vaccination (three doses) 0.833 0.015 971 959 1.228 0.018 0.803 0.863 Child received measles vaccination 0.842 0.015 971 959 1.270 0.018 0.811 0.872 Child fully immunized 0.759 0.017 971 959 1.246 0.023 0.725 0.794 Weight-for-height (below -2 SD) 0.126 0.005 5551 5466 1.097 0.040 0.116 0.136 Height-for-age (below -2 SD) 0.376 0.008 5551 5466 1.232 0.022 0.360 0.393 Weight-for-age (below -2 SD) 0.396 0.008 5551 5466 1.175 0.021 0.380 0.413 Total fertility rate (three years) 4.767 0.126 na 24327 1.565 0.027 4.515 5.020 Neonatal mortality rate (0-4 years) 23.620 2.498 6518 6315 1.200 0.106 18.624 28.616 Postneonatal mortality rate (0-4 years) 24.049 2.205 6531 6325 1.116 0.092 19.638 28.460 Infant mortality rate (0-4 years) 47.669 3.317 6536 6328 1.163 0.070 41.035 54.302 Infant mortality rate (0-4 years) 66.596 3.809 7044 6769 1.161 0.057 58.979 74.213 Infant mortality rate (0-4 years) 72.829 4.591 5346 5030 1.117 0.063 63.647 82.010 Child mortality rate (0-4 years) 47.869 3.236 6668 6456 1.210 0.068 41.397 54.340 Under-five mortality rate (0-4 years) 93.256 4.754 6691 6472 1.269 0.051 83.747 102.765 na = Not applicable Appendix B | 229 Table B.3 Sampling errors for selected variables, urban sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 1.000 0.000 3180 3767 na 0.000 1.000 1.000 No education 0.227 0.013 3180 3767 1.720 0.056 0.201 0.252 Literate 0.760 0.012 3180 3767 1.595 0.016 0.736 0.784 Primary school net attendance ratio 0.800 0.014 1910 2198 1.395 0.018 0.772 0.828 Secondary education or higher 0.412 0.014 3180 3767 1.638 0.035 0.383 0.440 Migrant 0.628 0.016 3180 3767 1.836 0.025 0.596 0.659 Migrant due to marriage 0.215 0.014 1985 2364 1.570 0.067 0.186 0.243 Adolescent childbearing 0.076 0.011 742 917 1.148 0.147 0.054 0.099 Currently married 0.522 0.012 3180 3767 1.334 0.023 0.499 0.546 Currently pregnant 0.070 0.006 3180 3767 1.271 0.082 0.059 0.082 Know any contraceptive method 0.977 0.006 1719 1967 1.573 0.006 0.966 0.988 Know any modern method 0.972 0.006 1719 1967 1.522 0.006 0.960 0.984 Ever used any contraceptive method 0.437 0.018 1719 1967 1.468 0.040 0.401 0.472 Currently using any method 0.165 0.012 1719 1967 1.293 0.070 0.142 0.188 Current using a modern method 0.123 0.011 1719 1967 1.374 0.089 0.101 0.144 Currently using pill 0.033 0.007 1719 1967 1.553 0.203 0.020 0.046 Currently using IUD 0.010 0.003 1719 1967 1.123 0.264 0.005 0.016 Currently using injectables 0.058 0.007 1719 1967 1.211 0.117 0.045 0.072 Currently using Norplant 0.000 0.000 1719 1967 0.428 0.998 0.000 0.000 Currently using condom 0.016 0.003 1719 1967 1.139 0.217 0.009 0.023 Currently using female sterilization 0.004 0.001 1719 1967 0.965 0.372 0.001 0.007 Currently using periodic abstinence 0.013 0.003 1719 1967 1.153 0.239 0.007 0.020 Currently using withdrawal 0.001 0.001 1719 1967 1.312 0.893 0.000 0.003 Ideal family size 5.042 0.062 2928 3522 1.496 0.012 4.918 5.166 Mother received tetanus injection for last birth 0.645 0.018 1227 1448 1.302 0.028 0.609 0.680 Mother received medical assistance at delivery 0.647 0.022 1712 2030 1.556 0.033 0.603 0.690 Child had diarrhea in the last two weeks 0.107 0.009 1604 1931 1.204 0.088 0.088 0.126 Child treated for diarrhea with ORS solution 0.589 0.040 169 207 1.069 0.069 0.508 0.670 Child received medical treatment for diarrhea 0.437 0.043 169 207 1.142 0.098 0.352 0.522 Child’s vaccination card seen 0.827 0.030 289 355 1.359 0.036 0.768 0.887 Child received BCG vaccination 0.976 0.010 289 355 1.127 0.010 0.956 0.996 Child received DPT vaccination (three doses) 0.935 0.014 289 355 0.961 0.015 0.907 0.962 Child received polio vaccination (three doses) 0.913 0.017 289 355 1.015 0.018 0.879 0.946 Child received measles vaccination 0.938 0.015 289 355 1.099 0.016 0.908 0.969 Child fully immunized 0.884 0.020 289 355 1.095 0.023 0.843 0.924 Weight-for-height (below -2 SD) 0.086 0.008 1528 1826 1.168 0.097 0.069 0.103 Height-for-age (below -2 SD) 0.279 0.014 1528 1826 1.163 0.049 0.252 0.307 Weight-for-age (below -2 SD) 0.291 0.014 1528 1826 1.160 0.048 0.263 0.319 Total fertility rate (three years) 3.485 0.152 na 10406 1.396 0.043 3.181 3.788 Neonatal mortality rate (0-9 years) 22.762 3.384 3631 4231 1.199 0.149 15.993 29.531 Postneonatal mortality rate (0-9 years) 25.593 3.232 3632 4235 1.119 0.126 19.129 32.056 Infant mortality rate (0-9 years) 48.354 5.189 3634 4235 1.309 0.107 37.976 58.732 Child mortality rate (0-9 years) 39.615 4.106 3665 4264 1.211 0.104 31.403 47.828 Under-five mortality rate (0-9 years) 86.054 7.107 3670 4269 1.413 0.083 71.840 100.268 na = Not applicable 230 | Appendix B Table B.4 Sampling errors for selected variables, Asmara sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 1.000 0.000 1123 1899 na 0.000 1.000 1.000 No education 0.110 0.012 1123 1899 1.320 0.112 0.086 0.135 Literate 0.880 0.012 1123 1899 1.258 0.014 0.856 0.904 Primary school net attendance ratio 0.881 0.016 508 831 1.089 0.019 0.848 0.913 Secondary education or higher 0.579 0.018 1123 1899 1.230 0.031 0.543 0.616 Migrant 0.560 0.023 1123 1899 1.577 0.042 0.513 0.606 Migrant due to marriage 0.189 0.016 625 1062 0.999 0.083 0.158 0.221 Adolescent childbearing 0.043 0.013 276 456 1.074 0.304 0.017 0.070 Currently married 0.457 0.014 1123 1899 0.952 0.031 0.429 0.485 Currently pregnant 0.060 0.009 1123 1899 1.221 0.145 0.042 0.077 Know any contraceptive method 0.992 0.004 505 868 0.931 0.004 0.985 1.000 Know any modern method 0.986 0.005 505 868 0.916 0.005 0.977 0.996 Ever used any contraceptive method 0.584 0.028 505 868 1.264 0.047 0.529 0.640 Currently using any method 0.232 0.022 505 868 1.150 0.093 0.189 0.276 Current using a modern method 0.176 0.020 505 868 1.156 0.111 0.137 0.215 Currently using pill 0.051 0.013 505 868 1.368 0.264 0.024 0.077 Currently using IUD 0.021 0.006 505 868 0.914 0.276 0.009 0.033 Currently using injectables 0.073 0.010 505 868 0.841 0.134 0.053 0.092 Currently using Norplant 0.000 0.000 505 868 na na 0.000 0.000 Currently using condom 0.024 0.006 505 868 0.910 0.260 0.011 0.036 Currently using female sterilization 0.005 0.003 505 868 0.929 0.578 0.000 0.011 Currently using periodic abstinence 0.021 0.007 505 868 1.029 0.311 0.008 0.034 Currently using withdrawal 0.003 0.003 505 868 1.126 0.998 0.000 0.008 Ideal family size 4.678 0.080 1074 1824 1.297 0.017 4.518 4.838 Mother received tetanus injection for last birth 0.608 0.028 356 618 1.082 0.046 0.552 0.663 Mother received medical assistance at delivery 0.867 0.020 487 844 1.156 0.024 0.826 0.908 Child had diarrhea in the last two weeks 0.090 0.013 466 810 0.965 0.143 0.065 0.116 Child treated for diarrhea with ORS solution 0.667 0.083 44 73 1.197 0.125 0.500 0.833 Child received medical treatment for diarrhea 0.480 0.071 44 73 0.965 0.148 0.338 0.622 Child’s vaccination card seen 0.802 0.048 99 175 1.230 0.060 0.706 0.898 Child received BCG vaccination 0.987 0.010 99 175 0.840 0.010 0.967 1.006 Child received DPT vaccination (three doses) 0.954 0.021 99 175 1.040 0.022 0.911 0.997 Child received polio vaccination (three doses) 0.911 0.027 99 175 0.948 0.029 0.858 0.964 Child received measles vaccination 0.961 0.022 99 175 1.165 0.023 0.916 1.005 Child fully immunized 0.892 0.034 99 175 1.118 0.038 0.823 0.960 Weight-for-height (below -2 SD) 0.040 0.010 439 744 1.104 0.250 0.020 0.060 Height-for-age (below -2 SD) 0.179 0.020 439 744 1.116 0.112 0.139 0.219 Weight-for-age (below -2 SD) 0.182 0.016 439 744 0.874 0.090 0.149 0.214 Total fertility rate (three years) 3.040 0.216 na 5380 1.213 0.071 2.608 3.473 na = Not applicable Appendix B | 231 Table B.5 Sampling errors for selected variables, other towns sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 1.000 0.000 2057 1868 na 0.000 1.000 1.000 No education 0.345 0.021 2057 1868 2.011 0.061 0.303 0.387 Literate 0.637 0.021 2057 1868 1.936 0.032 0.596 0.678 Primary school net attendance ratio 0.751 0.020 1402 1367 1.581 0.026 0.711 0.790 Secondary education or higher 0.242 0.017 2057 1868 1.851 0.072 0.207 0.276 Migrant 0.697 0.017 2057 1868 1.700 0.025 0.662 0.731 Migrant due to marriage 0.236 0.023 1362 1301 2.006 0.098 0.190 0.282 Adolescent childbearing 0.109 0.016 466 461 1.136 0.151 0.076 0.142 Currently married 0.588 0.018 2057 1868 1.636 0.030 0.553 0.624 Currently pregnant 0.081 0.007 2057 1868 1.230 0.091 0.066 0.096 Know any contraceptive method 0.965 0.010 1214 1099 1.828 0.010 0.945 0.984 Know any modern method 0.961 0.010 1214 1099 1.802 0.010 0.940 0.981 Ever used any contraceptive method 0.320 0.022 1214 1099 1.612 0.067 0.277 0.363 Currently using any method 0.112 0.013 1214 1099 1.410 0.114 0.087 0.138 Current using a modern method 0.081 0.012 1214 1099 1.557 0.151 0.056 0.105 Currently using pill 0.019 0.006 1214 1099 1.410 0.292 0.008 0.030 Currently using IUD 0.002 0.001 1214 1099 1.072 0.710 0.000 0.005 Currently using injectables 0.047 0.010 1214 1099 1.611 0.207 0.028 0.067 Currently using Norplant 0.000 0.000 1214 1099 0.480 0.996 0.000 0.001 Currently using condom 0.009 0.004 1214 1099 1.354 0.397 0.002 0.017 Currently using female sterilization 0.003 0.001 1214 1099 0.695 0.367 0.001 0.005 Currently using periodic abstinence 0.007 0.002 1214 1099 0.960 0.324 0.003 0.012 Currently using withdrawal 0.000 0.000 1214 1099 0.552 0.998 0.000 0.001 Ideal family size 5.432 0.093 1854 1698 1.676 0.017 5.246 5.619 Mother received tetanus injection for last birth 0.672 0.023 871 830 1.484 0.034 0.626 0.718 Mother received medical assistance at delivery 0.489 0.030 1225 1186 1.831 0.062 0.429 0.550 Child had diarrhea in the last two weeks 0.119 0.013 1138 1121 1.388 0.109 0.093 0.145 Child treated for diarrhea with ORS solution 0.546 0.039 125 134 0.920 0.072 0.468 0.625 Child received medical treatment for diarrhea 0.413 0.052 125 134 1.285 0.127 0.308 0.518 Child’s vaccination card seen 0.852 0.035 190 180 1.371 0.041 0.783 0.921 Child received BCG vaccination 0.966 0.017 190 180 1.343 0.018 0.931 1.000 Child received DPT vaccination (three doses) 0.916 0.017 190 180 0.869 0.019 0.881 0.950 Child received polio vaccination (three doses) 0.914 0.020 190 180 1.004 0.022 0.874 0.954 Child received measles vaccination 0.917 0.019 190 180 0.986 0.021 0.878 0.955 Child fully immunized 0.876 0.022 190 180 0.935 0.025 0.832 0.919 Weight-for-height (below -2 SD) 0.117 0.012 1089 1081 1.235 0.100 0.094 0.141 Height-for-age (below -2 SD) 0.349 0.019 1089 1081 1.313 0.055 0.310 0.387 Weight-for-age (below -2 SD) 0.367 0.019 1089 1081 1.293 0.053 0.328 0.405 Total fertility rate (three years) 3.925 0.188 na 5027 1.393 0.048 3.549 4.302 na = Not applicable 232 | Appendix B Table B.6 Sampling errors for selected variables, rural sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.000 0.000 5574 4987 na na 0.000 0.000 No education 0.708 0.013 5574 4987 2.169 0.019 0.681 0.734 Literate 0.289 0.013 5574 4987 2.130 0.045 0.263 0.315 Primary school net attendance ratio 0.523 0.014 5037 4660 1.801 0.027 0.495 0.551 Secondary education or higher 0.042 0.006 5574 4987 2.323 0.149 0.029 0.054 Migrant 0.474 0.012 5574 4987 1.863 0.026 0.449 0.499 Migrant due to marriage 0.599 0.021 2300 2363 2.018 0.034 0.557 0.640 Adolescent childbearing 0.193 0.015 1119 1084 1.263 0.077 0.163 0.223 Currently married 0.755 0.009 5574 4987 1.571 0.012 0.737 0.773 Currently pregnant 0.102 0.005 5574 4987 1.152 0.046 0.092 0.111 Know any contraceptive method 0.822 0.013 4251 3766 2.218 0.016 0.796 0.848 Know any modern method 0.787 0.013 4251 3766 2.135 0.017 0.760 0.813 Ever used any contraceptive method 0.111 0.009 4251 3766 1.795 0.078 0.094 0.129 Currently using any method 0.036 0.005 4251 3766 1.868 0.148 0.025 0.047 Current using a modern method 0.014 0.004 4251 3766 2.227 0.286 0.006 0.022 Currently using pill 0.005 0.002 4251 3766 2.037 0.459 0.000 0.009 Currently using IUD 0.000 0.000 4251 3766 na na 0.000 0.000 Currently using injectables 0.008 0.002 4251 3766 1.582 0.265 0.004 0.013 Currently using Norplant 0.000 0.000 4251 3766 na na 0.000 0.000 Currently using condom 0.001 0.001 4251 3766 1.138 0.603 0.000 0.002 Currently using female sterilization 0.000 0.000 4251 3766 1.127 1.001 0.000 0.001 Currently using periodic abstinence 0.003 0.001 4251 3766 1.261 0.336 0.001 0.006 Currently using withdrawal 0.001 0.000 4251 3766 1.100 0.717 0.000 0.001 Ideal family size 6.401 0.057 4524 4167 1.467 0.009 6.286 6.515 Mother received tetanus injection for last birth 0.426 0.015 3044 2727 1.631 0.034 0.397 0.456 Mother received medical assistance at delivery 0.104 0.009 4654 4125 1.784 0.090 0.085 0.123 Child had diarrhea in the last two weeks 0.145 0.007 4289 3817 1.231 0.046 0.131 0.158 Child treated for diarrhea with ORS solution 0.393 0.026 571 552 1.281 0.067 0.341 0.446 Child received medical treatment for diarrhea 0.412 0.027 571 552 1.308 0.064 0.359 0.465 Child’s vaccination card seen 0.732 0.025 682 604 1.426 0.034 0.683 0.781 Child received BCG vaccination 0.877 0.020 682 604 1.541 0.023 0.837 0.917 Child received DPT vaccination (three doses) 0.765 0.024 682 604 1.433 0.031 0.718 0.813 Child received polio vaccination (three doses) 0.786 0.021 682 604 1.321 0.027 0.744 0.828 Child received measles vaccination 0.785 0.021 682 604 1.308 0.027 0.743 0.827 Child fully immunized 0.686 0.023 682 604 1.295 0.034 0.640 0.733 Weight-for-height (below -2 SD) 0.145 0.006 4023 3641 1.106 0.044 0.133 0.158 Height-for-age (below -2 SD) 0.425 0.010 4023 3641 1.212 0.023 0.405 0.445 Weight-for-age (below -2 SD) 0.449 0.009 4023 3641 1.127 0.021 0.430 0.468 Total fertility rate (three years) 5.702 0.143 na 13921 1.339 0.025 5.416 5.988 Neonatal mortality rate (0-9 years) 32.923 2.405 9932 8826 1.175 0.073 28.114 37.732 Postneonatal mortality rate (0-9 years) 29.127 2.459 9938 8831 1.344 0.084 24.209 34.045 Infant mortality rate (0-9 years) 62.050 3.426 9941 8833 1.253 0.055 55.198 68.902 Child mortality rate (0-9 years) 58.664 3.550 10051 8935 1.285 0.061 51.565 65.763 Under-five mortality rate (0-9 years) 117.074 5.228 10063 8944 1.397 0.045 106.617 127.531 na = Not applicable Appendix B | 233 Table B.7 Sampling errors for selected variables, zoba Debubawi Keih Bahri sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.630 0.037 1470 324 2.923 0.058 0.557 0.704 No education 0.517 0.032 1470 324 2.420 0.061 0.454 0.580 Literate 0.455 0.032 1470 324 2.478 0.071 0.391 0.520 Primary school net attendance ratio 0.527 0.036 920 189 1.764 0.068 0.455 0.599 Secondary education or higher 0.208 0.022 1470 324 2.041 0.104 0.165 0.251 Migrant 0.437 0.031 1470 324 2.376 0.070 0.375 0.498 Migrant due to marriage 0.234 0.026 541 142 1.416 0.110 0.182 0.286 Adolescent childbearing 0.137 0.028 246 56 1.262 0.202 0.082 0.193 Currently married 0.649 0.016 1470 324 1.265 0.024 0.617 0.680 Currently pregnant 0.089 0.007 1470 324 0.954 0.079 0.075 0.103 Know any contraceptive method 0.778 0.026 1005 210 2.016 0.034 0.725 0.831 Know any modern method 0.728 0.031 1005 210 2.229 0.043 0.665 0.790 Ever used any contraceptive method 0.220 0.027 1005 210 2.083 0.124 0.165 0.274 Currently using any method 0.071 0.010 1005 210 1.188 0.136 0.052 0.090 Current using a modern method 0.051 0.007 1005 210 0.951 0.130 0.038 0.064 Currently using pill 0.013 0.004 1005 210 0.989 0.267 0.006 0.021 Currently using IUD 0.000 0.000 1005 210 na na 0.000 0.000 Currently using injectables 0.025 0.006 1005 210 1.125 0.221 0.014 0.036 Currently using Norplant 0.001 0.001 1005 210 0.980 0.977 0.000 0.003 Currently using condom 0.010 0.002 1005 210 0.552 0.172 0.007 0.014 Currently using female sterilization 0.001 0.001 1005 210 0.980 0.977 0.000 0.003 Currently using periodic abstinence 0.011 0.004 1005 210 1.321 0.393 0.002 0.020 Currently using withdrawal 0.001 0.001 1005 210 1.133 0.984 0.000 0.004 Ideal family size 5.690 0.214 1034 242 1.652 0.038 5.262 6.119 Mother received tetanus injection for last birth 0.635 0.032 656 136 1.658 0.051 0.571 0.699 Mother received medical assistance at delivery 0.419 0.045 974 195 2.196 0.107 0.330 0.508 Child had diarrhea in the last two weeks 0.073 0.010 860 174 1.024 0.131 0.054 0.092 Child treated for diarrhea with ORS solution 0.431 0.066 64 13 0.998 0.153 0.299 0.562 Child received medical treatment for diarrhea 0.356 0.078 64 13 1.230 0.220 0.200 0.513 Child’s vaccination card seen 0.707 0.037 136 28 0.921 0.053 0.632 0.781 Child received BCG vaccination 0.908 0.019 136 28 0.724 0.021 0.870 0.945 Child received DPT vaccination (three doses) 0.765 0.044 136 28 1.163 0.057 0.677 0.853 Child received polio vaccination (three doses) 0.756 0.045 136 28 1.186 0.060 0.665 0.847 Child received measles vaccination 0.702 0.052 136 28 1.270 0.074 0.599 0.806 Child fully immunized 0.601 0.051 136 28 1.160 0.084 0.500 0.702 Weight-for-height (below -2 SD) 0.138 0.015 766 156 1.081 0.105 0.109 0.167 Height-for-age (below -2 SD) 0.374 0.025 766 156 1.319 0.066 0.325 0.424 Weight-for-age (below -2 SD) 0.411 0.019 766 156 1.004 0.047 0.373 0.450 Total fertility rate (three years) 3.873 0.248 na 901 1.412 0.064 3.377 4.369 Neonatal mortality rate (0-9 years) 55.328 6.249 2110 423 1.039 0.113 42.830 67.825 Postneonatal mortality rate (0-9 years) 67.014 6.140 2112 423 1.010 0.092 54.733 79.294 Infant mortality rate (0-9 years) 122.341 10.621 2113 423 1.279 0.087 101.100 143.583 Child mortality rate (0-9 years) 73.499 8.358 2131 427 1.245 0.114 56.783 90.215 Under-five mortality rate (0-9 years) 186.848 12.696 2135 427 1.253 0.068 161.457 212.239 na = Not applicable 234 | Appendix B Table B.8 Sampling errors for selected variables, zoba Maekel sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.858 0.014 1404 2264 1.504 0.016 0.829 0.886 No education 0.143 0.012 1404 2264 1.256 0.082 0.120 0.167 Literate 0.850 0.011 1404 2264 1.190 0.013 0.828 0.873 Primary school net attendance ratio 0.875 0.014 826 1232 1.165 0.016 0.847 0.903 Secondary education or higher 0.520 0.017 1404 2264 1.272 0.033 0.486 0.554 Migrant 0.552 0.020 1404 2264 1.518 0.036 0.512 0.593 Migrant due to marriage 0.258 0.016 770 1250 0.985 0.060 0.227 0.289 Adolescent childbearing 0.063 0.015 358 564 1.158 0.237 0.033 0.093 Currently married 0.487 0.013 1404 2264 0.987 0.027 0.461 0.514 Currently pregnant 0.071 0.009 1404 2264 1.254 0.121 0.054 0.088 Know any contraceptive method 0.986 0.004 689 1103 0.874 0.004 0.978 0.994 Know any modern method 0.976 0.006 689 1103 0.994 0.006 0.965 0.988 Ever used any contraceptive method 0.516 0.027 689 1103 1.434 0.053 0.461 0.571 Currently using any method 0.196 0.018 689 1103 1.211 0.093 0.160 0.233 Current using a modern method 0.147 0.016 689 1103 1.215 0.112 0.114 0.179 Currently using pill 0.044 0.011 689 1103 1.425 0.254 0.021 0.066 Currently using IUD 0.017 0.005 689 1103 0.951 0.278 0.007 0.026 Currently using injectables 0.062 0.008 689 1103 0.876 0.130 0.046 0.078 Currently using Norplant 0.000 0.000 689 1103 na na 0.000 0.000 Currently using condom 0.019 0.005 689 1103 0.932 0.257 0.009 0.028 Currently using female sterilization 0.004 0.002 689 1103 0.976 0.586 0.000 0.009 Currently using periodic abstinence 0.017 0.005 689 1103 1.060 0.310 0.006 0.027 Currently using withdrawal 0.002 0.002 689 1103 1.167 0.998 0.000 0.006 Ideal family size 4.853 0.075 1324 2150 1.287 0.015 4.703 5.003 Mother received tetanus injection for last birth 0.561 0.025 500 801 1.142 0.045 0.510 0.612 Mother received medical assistance at delivery 0.719 0.022 702 1118 1.043 0.030 0.676 0.763 Child had diarrhea in the last two weeks 0.092 0.011 670 1069 0.948 0.119 0.070 0.114 Child treated for diarrhea with ORS solution 0.653 0.068 63 98 1.136 0.105 0.517 0.790 Child received medical treatment for diarrhea 0.513 0.055 63 98 0.861 0.107 0.403 0.623 Child’s vaccination card seen 0.810 0.043 123 205 1.239 0.053 0.723 0.896 Child received BCG vaccination 0.979 0.011 123 205 0.831 0.011 0.958 1.000 Child received DPT vaccination (three doses) 0.950 0.020 123 205 1.022 0.021 0.910 0.990 Child received polio vaccination (three doses) 0.919 0.023 123 205 0.962 0.025 0.873 0.966 Child received measles vaccination 0.961 0.020 123 205 1.149 0.020 0.922 1.001 Child fully immunized 0.892 0.030 123 205 1.104 0.034 0.831 0.953 Weight-for-height (below -2 SD) 0.061 0.008 635 984 0.856 0.134 0.045 0.077 Height-for-age (below -2 SD) 0.230 0.018 635 984 1.030 0.077 0.195 0.266 Weight-for-age (below -2 SD) 0.234 0.017 635 984 0.940 0.072 0.200 0.267 Total fertility rate (three years) 3.422 0.241 na 6260 1.338 0.070 2.941 3.903 Neonatal mortality rate (0-9 years) 18.658 4.004 1459 2289 0.996 0.215 10.649 26.666 Postneonatal mortality rate (0-9 years) 20.235 4.140 1459 2289 1.001 0.205 11.955 28.516 Infant mortality rate (0-9 years) 38.893 5.407 1459 2289 0.957 0.139 28.079 49.707 Child mortality rate (0-9 years) 21.997 3.655 1462 2293 0.851 0.166 14.688 29.306 Under-five mortality rate (0-9 years) 60.035 6.580 1462 2293 1.001 0.110 46.875 73.194 na = Not applicable Appendix B | 235 Table B.9 Sampling errors for selected variables, Zoba Semenawi Keih Bahri sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.366 0.019 1416 1148 1.507 0.053 0.327 0.404 No education 0.718 0.021 1416 1148 1.734 0.029 0.677 0.760 Literate 0.267 0.022 1416 1148 1.840 0.081 0.224 0.310 Primary school net attendance ratio 0.427 0.026 1153 935 1.628 0.062 0.374 0.479 Secondary education or higher 0.057 0.011 1416 1148 1.771 0.192 0.035 0.079 Migrant 0.429 0.025 1416 1148 1.885 0.058 0.380 0.479 Migrant due to marriage 0.334 0.031 578 493 1.592 0.094 0.271 0.396 Adolescent childbearing 0.111 0.021 240 196 1.048 0.192 0.068 0.154 Currently married 0.712 0.015 1416 1148 1.259 0.021 0.682 0.742 Currently pregnant 0.089 0.009 1416 1148 1.167 0.099 0.072 0.107 Know any contraceptive method 0.869 0.019 1027 817 1.763 0.021 0.832 0.906 Know any modern method 0.847 0.020 1027 817 1.766 0.023 0.808 0.887 Ever used any contraceptive method 0.132 0.019 1027 817 1.813 0.145 0.094 0.170 Currently using any method 0.051 0.010 1027 817 1.449 0.196 0.031 0.071 Current using a modern method 0.032 0.008 1027 817 1.474 0.255 0.016 0.048 Currently using pill 0.009 0.005 1027 817 1.624 0.528 0.000 0.019 Currently using IUD 0.001 0.001 1027 817 1.153 0.991 0.000 0.004 Currently using injectables 0.015 0.004 1027 817 1.171 0.296 0.006 0.024 Currently using Norplant 0.000 0.000 1027 817 na na 0.000 0.000 Currently using condom 0.002 0.002 1027 817 1.119 0.717 0.000 0.006 Currently using female sterilization 0.004 0.001 1027 817 0.754 0.386 0.001 0.007 Currently using periodic abstinence 0.004 0.002 1027 817 1.106 0.514 0.000 0.009 Currently using withdrawal 0.000 0.000 1027 817 na na 0.000 0.000 Ideal family size 6.571 0.136 1210 976 1.640 0.021 6.300 6.842 Mother received tetanus injection for last birth 0.561 0.021 709 560 1.130 0.038 0.518 0.604 Mother received medical assistance at delivery 0.225 0.023 1083 845 1.488 0.102 0.179 0.271 Child had diarrhea in the last two weeks 0.150 0.016 997 778 1.302 0.104 0.119 0.181 Child treated for diarrhea with ORS solution 0.499 0.048 161 117 1.073 0.096 0.404 0.595 Child received medical treatment for diarrhea 0.332 0.060 161 117 1.433 0.180 0.213 0.452 Child’s vaccination card seen 0.768 0.043 165 130 1.297 0.056 0.681 0.854 Child received BCG vaccination 0.891 0.035 165 130 1.421 0.039 0.821 0.961 Child received DPT vaccination (three doses) 0.788 0.035 165 130 1.076 0.044 0.718 0.857 Child received polio vaccination (three doses) 0.798 0.040 165 130 1.255 0.050 0.718 0.877 Child received measles vaccination 0.803 0.036 165 130 1.152 0.045 0.730 0.875 Child fully immunized 0.699 0.038 165 130 1.058 0.055 0.622 0.776 Weight-for-height (below -2 SD) 0.180 0.013 956 752 1.030 0.074 0.153 0.207 Height-for-age (below -2 SD) 0.419 0.024 956 752 1.465 0.057 0.371 0.467 Weight-for-age (below -2 SD) 0.512 0.022 956 752 1.300 0.043 0.467 0.556 Total fertility rate (three years) 4.514 0.237 na 3208 1.359 0.052 4.040 4.987 Neonatal mortality rate (0-9 years) 39.092 6.407 2292 1823 1.254 0.164 26.279 51.905 Postneonatal mortality rate (0-9 years) 38.406 4.504 2297 1829 1.032 0.117 29.398 47.414 Infant mortality rate (0-9 years) 77.498 8.966 2298 1830 1.310 0.116 59.566 95.430 Child mortality rate (0-9 years) 82.452 9.152 2341 1862 1.440 0.111 64.147 100.756 Under-five mortality rate (0-9 years) 153.560 11.709 2348 1869 1.352 0.076 130.141 176.978 na = Not applicable 236 | Appendix B Table B.10 Sampling errors for selected variables, zoba Anseba sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.329 0.016 1418 1130 1.246 0.047 0.298 0.360 No education 0.595 0.023 1418 1130 1.742 0.038 0.550 0.641 Literate 0.404 0.021 1418 1130 1.589 0.051 0.363 0.446 Primary school net attendance ratio 0.533 0.025 1288 1052 1.745 0.047 0.482 0.583 Secondary education or higher 0.087 0.012 1418 1130 1.617 0.140 0.062 0.111 Migrant 0.465 0.023 1418 1130 1.754 0.050 0.419 0.512 Migrant due to marriage 0.538 0.036 642 526 1.830 0.067 0.466 0.610 Adolescent childbearing 0.096 0.018 322 266 1.100 0.188 0.060 0.132 Currently married 0.693 0.016 1418 1130 1.345 0.024 0.660 0.726 Currently pregnant 0.088 0.007 1418 1130 0.974 0.083 0.074 0.103 Know any contraceptive method 0.825 0.020 1003 784 1.648 0.024 0.786 0.865 Know any modern method 0.797 0.026 1003 784 2.034 0.032 0.746 0.849 Ever used any contraceptive method 0.088 0.015 1003 784 1.692 0.172 0.058 0.119 Currently using any method 0.044 0.012 1003 784 1.858 0.273 0.020 0.068 Current using a modern method 0.027 0.011 1003 784 2.076 0.392 0.006 0.049 Currently using pill 0.003 0.003 1003 784 1.400 0.746 0.000 0.009 Currently using IUD 0.001 0.001 1003 784 1.139 1.013 0.000 0.004 Currently using injectables 0.014 0.006 1003 784 1.542 0.403 0.003 0.026 Currently using Norplant 0.000 0.000 1003 784 na na 0.000 0.000 Currently using condom 0.008 0.005 1003 784 1.736 0.606 0.000 0.018 Currently using female sterilization 0.000 0.000 1003 784 na na 0.000 0.000 Currently using periodic abstinence 0.006 0.003 1003 784 1.105 0.462 0.000 0.011 Currently using withdrawal 0.000 0.000 1003 784 na na 0.000 0.000 Ideal family size 6.531 0.093 1396 1112 1.487 0.014 6.345 6.718 Mother received tetanus injection for last birth 0.499 0.019 748 589 1.056 0.039 0.460 0.538 Mother received medical assistance at delivery 0.154 0.018 1159 911 1.429 0.120 0.117 0.191 Child had diarrhea in the last two weeks 0.101 0.010 1113 877 1.135 0.101 0.081 0.122 Child treated for diarrhea with ORS solution 0.432 0.047 112 89 1.007 0.110 0.337 0.526 Child received medical treatment for diarrhea 0.332 0.057 112 89 1.251 0.170 0.219 0.445 Child’s vaccination card seen 0.924 0.018 182 149 0.925 0.019 0.888 0.960 Child received BCG vaccination 0.979 0.009 182 149 0.872 0.009 0.961 0.997 Child received DPT vaccination (three doses) 0.948 0.014 182 149 0.873 0.015 0.919 0.976 Child received polio vaccination (three doses) 0.930 0.017 182 149 0.926 0.019 0.896 0.965 Child received measles vaccination 0.938 0.016 182 149 0.890 0.017 0.907 0.970 Child fully immunized 0.915 0.018 182 149 0.867 0.019 0.880 0.950 Weight-for-height (below -2 SD) 0.156 0.013 1088 873 1.111 0.081 0.131 0.182 Height-for-age (below -2 SD) 0.405 0.020 1088 873 1.277 0.050 0.365 0.446 Weight-for-age (below -2 SD) 0.467 0.013 1088 873 0.824 0.029 0.440 0.494 Total fertility rate (three years) 5.644 0.250 na 3086 1.147 0.044 5.144 6.145 Neonatal mortality rate (0-9 years) 20.283 3.033 2448 1937 1.014 0.150 14.216 26.349 Postneonatal mortality rate (0-9 years) 16.281 2.438 2446 1935 0.875 0.150 11.406 21.157 Infant mortality rate (0-9 years) 36.564 3.972 2448 1937 0.980 0.109 28.620 44.509 Child mortality rate (0-9 years) 37.350 3.928 2467 1953 0.915 0.105 29.494 45.207 Under-five mortality rate (0-9 years) 72.549 5.715 2469 1954 0.995 0.079 61.119 83.978 na = Not applicable Appendix B | 237 Table B.11 Sampling errors for selected variables, zoba Gash-Barka sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.196 0.011 1414 1500 1.025 0.055 0.174 0.218 No education 0.773 0.023 1414 1500 2.077 0.030 0.727 0.820 Literate 0.212 0.023 1414 1500 2.112 0.108 0.166 0.258 Primary school net attendance ratio 0.533 0.025 1288 1052 1.745 0.047 0.482 0.583 Secondary education or higher 0.033 0.009 1414 1500 1.929 0.276 0.015 0.052 Migrant 0.571 0.025 1414 1500 1.879 0.043 0.522 0.621 Migrant due to marriage 0.273 0.028 785 857 1.730 0.101 0.218 0.328 Adolescent childbearing 0.203 0.021 285 304 0.869 0.102 0.161 0.244 Currently married 0.761 0.015 1414 1500 1.333 0.020 0.731 0.791 Currently pregnant 0.102 0.010 1414 1500 1.245 0.099 0.082 0.122 Know any contraceptive method 0.696 0.032 1072 1142 2.289 0.046 0.631 0.760 Know any modern method 0.641 0.029 1072 1142 1.964 0.045 0.583 0.698 Ever used any contraceptive method 0.085 0.016 1072 1142 1.821 0.183 0.054 0.116 Currently using any method 0.019 0.005 1072 1142 1.251 0.274 0.009 0.030 Current using a modern method 0.011 0.005 1072 1142 1.479 0.428 0.002 0.020 Currently using pill 0.004 0.003 1072 1142 1.351 0.657 0.000 0.009 Currently using IUD 0.000 0.000 1072 1142 na na 0.000 0.000 Currently using injectables 0.005 0.003 1072 1142 1.239 0.516 0.000 0.011 Currently using Norplant 0.000 0.000 1072 1142 na na 0.000 0.000 Currently using condom 0.001 0.001 1072 1142 0.885 1.002 0.000 0.002 Currently using female sterilization 0.001 0.001 1072 1142 1.030 1.003 0.000 0.003 Currently using periodic abstinence 0.001 0.001 1072 1142 0.885 0.995 0.000 0.002 Currently using withdrawal 0.001 0.001 1072 1142 0.909 1.007 0.000 0.002 Ideal family size 6.221 0.128 1142 1216 1.567 0.021 5.965 6.478 Mother received tetanus injection for last birth 0.471 0.028 742 789 1.520 0.059 0.415 0.526 Mother received medical assistance at delivery 0.110 0.022 1071 1136 2.015 0.199 0.067 0.154 Child had diarrhea in the last two weeks 0.121 0.009 976 1039 0.857 0.074 0.103 0.139 Child treated for diarrhea with ORS solution 0.490 0.049 115 126 1.046 0.100 0.393 0.588 Child received medical treatment for diarrhea 0.491 0.059 115 126 1.297 0.119 0.374 0.608 Child’s vaccination card seen 0.661 0.046 178 186 1.290 0.070 0.568 0.753 Child received BCG vaccination 0.871 0.028 178 186 1.100 0.032 0.815 0.927 Child received DPT vaccination (three doses) 0.735 0.041 178 186 1.236 0.056 0.652 0.817 Child received polio vaccination (three doses) 0.756 0.034 178 186 1.049 0.045 0.688 0.825 Child received measles vaccination 0.757 0.035 178 186 1.091 0.047 0.686 0.828 Child fully immunized 0.642 0.040 178 186 1.102 0.062 0.562 0.722 Weight-for-height (below -2 SD) 0.169 0.014 883 963 1.097 0.082 0.141 0.196 Height-for-age (below -2 SD) 0.448 0.016 883 963 0.901 0.035 0.416 0.479 Weight-for-age (below -2 SD) 0.496 0.015 883 963 0.850 0.030 0.466 0.525 Total fertility rate (three years) 5.115 0.242 na 4252 1.201 0.047 4.631 5.600 Neonatal mortality rate (10 years) 40.765 5.324 2287 2424 1.144 0.131 30.118 51.412 Postneonatal mortality rate (10 years) 25.238 3.871 2289 2426 1.189 0.153 17.495 32.980 Infant mortality rate (10 years) 66.002 6.278 2289 2426 1.129 0.095 53.447 78.558 Child mortality rate (10 years) 61.443 5.508 2310 2448 1.031 0.090 50.428 72.459 Under-five mortality rate (10 years) 123.390 9.123 2312 2450 1.224 0.074 105.145 141.636 na = Not applicable 238 | Appendix B Table B.12 Sampling errors for selected variables, zoba Debub sample, Eritrea 2002 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative error (SE/R) (R-2SE) (R+2SE) Urban residence 0.224 0.021 1632 2388 2.078 0.096 0.181 0.267 No education 0.517 0.022 1632 2388 1.761 0.042 0.473 0.561 Literate 0.481 0.021 1632 2388 1.670 0.043 0.439 0.522 Primary school net attendance ratio 0.711 0.020 1541 2158 1.580 0.028 0.672 0.751 Secondary education or higher 0.126 0.014 1632 2388 1.653 0.108 0.099 0.153 Migrant 0.611 0.019 1632 2388 1.545 0.031 0.574 0.649 Migrant due to marriage 0.606 0.035 969 1460 2.203 0.057 0.537 0.675 Adolescent childbearing 0.207 0.022 410 616 1.085 0.105 0.163 0.250 Currently married 0.702 0.018 1632 2388 1.565 0.025 0.667 0.738 Currently pregnant 0.095 0.006 1632 2388 0.852 0.065 0.083 0.108 Know any contraceptive method 0.962 0.009 1174 1677 1.584 0.009 0.945 0.980 Know any modern method 0.951 0.011 1174 1677 1.702 0.011 0.930 0.973 Ever used any contraceptive method 0.232 0.015 1174 1677 1.192 0.063 0.202 0.261 Currently using any method 0.079 0.011 1174 1677 1.417 0.142 0.056 0.101 Current using a modern method 0.037 0.009 1174 1677 1.678 0.250 0.019 0.056 Currently using pill 0.010 0.004 1174 1677 1.504 0.441 0.001 0.018 Currently using IUD 0.000 0.000 1174 1677 na na 0.000 0.000 Currently using injectables 0.026 0.007 1174 1677 1.544 0.276 0.012 0.040 Currently using Norplant 0.000 0.000 1174 1677 na na 0.000 0.000 Currently using condom 0.001 0.001 1174 1677 0.946 0.743 0.000 0.003 Currently using female sterilization 0.000 0.000 1174 1677 na na 0.000 0.000 Currently using periodic abstinence 0.005 0.002 1174 1677 1.058 0.419 0.001 0.010 Currently using withdrawal 0.001 0.001 1174 1677 0.921 0.998 0.000 0.002 Ideal family size 5.708 0.073 1346 1993 1.241 0.013 5.563 5.854 Mother received tetanus injection for last birth 0.447 0.027 916 1301 1.624 0.061 0.393 0.501 Mother received medical assistance at delivery 0.205 0.021 1377 1950 1.600 0.104 0.162 0.248 Child had diarrhea in the last two weeks 0.175 0.012 1277 1811 1.147 0.071 0.150 0.200 Child treated for diarrhea with ORS solution 0.350 0.037 225 317 1.074 0.105 0.277 0.424 Child received medical treatment for diarrhea 0.419 0.036 225 317 1.058 0.086 0.347 0.491 Child’s vaccination card seen 0.727 0.044 187 261 1.304 0.061 0.638 0.816 Child received BCG vaccination 0.868 0.039 187 261 1.459 0.045 0.789 0.946 Child received DPT vaccination (three doses) 0.758 0.043 187 261 1.304 0.057 0.672 0.843 Child received polio vaccination (three doses) 0.790 0.038 187 261 1.205 0.048 0.714 0.865 Child received measles vaccination 0.787 0.037 187 261 1.182 0.047 0.712 0.862 Child fully immunized 0.696 0.042 187 261 1.200 0.060 0.612 0.781 Weight-for-height (below -2 SD) 0.098 0.010 1223 1738 1.115 0.099 0.079 0.118 Height-for-age (below -2 SD) 0.387 0.016 1223 1738 1.104 0.041 0.355 0.419 Weight-for-age (below -2 SD) 0.346 0.016 1223 1738 1.114 0.047 0.314 0.379 Total fertility rate (three years) 5.666 0.254 na 6620 1.258 0.045 5.158 6.175 Neonatal mortality rate (10 years) 26.762 3.427 2967 4162 1.032 0.128 19.907 33.617 Postneonatal mortality rate (10 years) 30.715 4.506 2967 4163 1.245 0.147 21.703 39.727 Infant mortality rate (10 years) 57.477 5.846 2968 4164 1.222 0.102 45.785 69.169 Child mortality rate (10 years) 56.316 5.778 3005 4216 1.143 0.103 44.761 67.872 Under-five mortality rate (10 years) 110.557 8.953 3007 4219 1.336 0.081 92.650 128.464 na = Not applicable Appendix C | 239 DATA QUALITY TABLES APPENDIX C Table C.1 Household age distribution Single-year age distribution of the de facto household population by sex (weighted), Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Male Female Male Female ––––––––––––––––––– –––––––––––––––––– –––––––––––––––––– ––––––––––––––––––– Age Number Percent Number Percent Age Number Percent Number Percent –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 0 629 3.5 664 3.1 37 64 0.4 191 0.9 1 508 2.8 448 2.1 38 86 0.5 216 1.0 2 542 3.0 550 2.5 39 48 0.3 119 0.5 3 663 3.7 615 2.8 40 300 1.7 555 2.6 4 692 3.9 638 2.9 41 45 0.3 56 0.3 5 510 2.9 536 2.5 42 82 0.5 95 0.4 6 754 4.2 743 3.4 43 59 0.3 80 0.4 7 794 4.4 737 3.4 44 49 0.3 59 0.3 8 814 4.6 751 3.5 45 227 1.3 290 1.3 9 579 3.2 593 2.7 46 60 0.3 81 0.4 10 738 4.1 668 3.1 47 57 0.3 112 0.5 11 493 2.8 502 2.3 48 93 0.5 157 0.7 12 705 3.9 686 3.2 49 36 0.2 113 0.5 13 511 2.9 709 3.3 50 363 2.0 312 1.4 14 576 3.2 527 2.4 51 54 0.3 102 0.5 15 526 2.9 457 2.1 52 83 0.5 150 0.7 16 469 2.6 450 2.1 53 75 0.4 102 0.5 17 424 2.4 344 1.6 54 73 0.4 85 0.4 18 487 2.7 600 2.8 55 233 1.3 307 1.4 19 166 0.9 285 1.3 56 68 0.4 98 0.5 20 329 1.8 592 2.7 57 58 0.3 64 0.3 21 109 0.6 169 0.8 58 89 0.5 110 0.5 22 118 0.7 290 1.3 59 31 0.2 37 0.2 23 113 0.6 233 1.1 60 407 2.3 512 2.4 24 81 0.5 230 1.1 61 23 0.1 28 0.1 25 156 0.9 504 2.3 62 73 0.4 50 0.2 26 117 0.7 268 1.2 63 71 0.4 48 0.2 27 76 0.4 281 1.3 64 31 0.2 46 0.2 28 126 0.7 344 1.6 65 226 1.3 233 1.1 29 52 0.3 219 1.0 66 42 0.2 31 0.1 30 269 1.5 649 3.0 67 63 0.4 38 0.2 31 37 0.2 82 0.4 68 59 0.3 64 0.3 32 95 0.5 197 0.9 69 27 0.1 21 0.1 33 59 0.3 113 0.5 70+ 903 5.1 791 3.6 34 43 0.2 89 0.4 Don’t know/ 35 176 1.0 433 2.0 Missing 13 0.1 8 0.0 36 56 0.3 147 0.7 Total 17,865 100.0 21,703 100.0 240 | Appendix C Table C.2 Age distribution of eligible and interviewed women Distribution of the de facto household population of women age 10-54, and of inter- viewed women age 15-49, and percentage of eligible women who were interviewed (weighted), by five-year age groups, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Interviewed women Percentage Household age 15-49 of eligible population of ––––––––––––––––––– women Age group women age 10-54 Number Percent interviewed –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 10-14 3,092 na na na 15-19 2,136 1,997 22.8 93.5 20-24 1,515 1,444 16.5 95.4 25-29 1,618 1,569 17.9 97.0 30-34 1,130 1,098 12.5 97.2 25-39 1,105 1,083 12.4 98.0 40-44 845 826 9.4 97.8 45-49 753 736 8.4 97.8 50-54 750 na na na 15-49 9,100 8,753 100.0 96.2 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: The de facto population includes all residents and nonresidents who stayed in the household the night before interview. Weights for both household population of women and interviewed women are household weights. Age is based on the household sched- ule. na = Not applicable Table C.3 Completeness of reporting Percentage of observations with missing information for selected demographic and health ques- tions, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage Number missing of Subject Reference group information cases –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Birth Date Births in the past 15 years Month only 6.56 17,975 Month and year 0.14 17,975 Age at death Dead children born in the past 15 years 0.77 1,996 Age/date at first union1 Ever-married women age 15-49 0.99 6,710 Respondent's education All women age 15-49 0.02 8,754 Diarrhea in last 2 weeks Living children age 0-59 months 0.44 5,748 Anthropometry Living children age 0-59 months Height 4.34 5,994 Weight 2.51 5,994 Height or weight 4.41 5,994 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Both year and age missing Appendix C | 241 Table C.4 Births by calendar years Distribution of births by calendar years for living, dead, and all children, according to completeness of birth dates, sex ratio at birth, and ratio of births by calendar year (weighted), Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Percentage with Number of births complete birth date1 Sex ratio at birth2 Calendar year ratio3 –––––––––––––––––––––– –––––––––––––––––––––– –––––––––––––––––––––– –––––––––––––––––––––– Year Living Dead Total Living Dead Total Living Dead Total Living Dead Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 2002 520 18 538 100.0 91.2 99.7 96.7 198.5 99.0 na na na 2001 1,166 68 1,233 99.2 86.3 98.5 106.1 250.4 110.8 na na na 2000 1,064 74 1,138 98.9 88.5 98.2 97.5 93.1 97.2 96.7 106.2 97.3 1999 1,034 72 1,106 98.8 81.6 97.7 106.6 116.0 107.2 87.5 81.1 87.1 1998 1,299 104 1,403 98.4 85.7 97.5 115.2 156.6 117.8 120.2 110.9 119.5 1997 1,127 115 1,242 97.1 90.2 96.5 99.6 102.8 99.9 89.6 77.1 88.3 1996 1,216 195 1,411 95.4 84.0 93.8 100.2 148.7 105.7 100.8 149.2 105.6 1995 1,284 146 1,430 94.5 77.5 92.7 112.8 101.9 111.6 99.8 78.4 97.1 1994 1,358 178 1,536 92.7 79.6 91.2 102.0 121.9 104.2 113.8 113.7 113.8 1993 1,102 167 1,269 91.5 81.5 90.2 110.4 132.9 113.1 91.9 99.1 92.8 1993-1997 5,082 337 5,419 98.9 85.9 98.1 105.5 144.0 107.6 na na na 1988-1992 6,087 802 6,888 94.2 82.2 92.8 104.9 122.9 106.8 na na na 1983-1987 4,427 783 5,209 91.3 79.8 89.6 98.8 121.5 101.9 na na na < 1983 2,627 596 3,224 88.8 79.5 87.0 108.5 118.8 110.3 na na na All 18,223 2,518 20,741 94.0 81.3 92.5 104.0 124.1 106.3 na na na –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na= Not applicable 1Both year and month of birth given 2(Bm/Bf)*100, where Bm and Bf are the numbers of male and female births, respectively 3[2Bx/(Bx-1+Bx+1)]*100, where Bx is the number births in calendar year x 242 | Appendix C Table C.5 Reporting of age at death in days Distribution of reported deaths under one month of age by age at death in days and the percentage of neonatal deaths reported to occur at ages 0-6 days, for five-year periods of birth preceding the survey, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of years preceding the survey Age at ––––––––––––––––––––––––––––––––– Total death (days) 0-4 5-9 10-14 15-19 0-19 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– <1 31 42 23 10 105 1 33 62 34 13 141 2 14 11 8 11 44 3 16 35 16 15 82 4 6 3 2 4 15 5 7 12 5 5 29 6 3 3 4 2 12 7 9 15 20 13 57 8 3 4 4 1 12 9 1 2 3 0 6 10 3 4 5 4 17 11 1 2 0 0 3 12 1 2 2 3 8 14 10 8 4 2 23 15 6 9 6 2 23 18 0 0 2 0 2 20 0 5 2 0 6 21 3 10 3 3 19 22 1 0 0 0 1 23 0 0 1 0 1 25 0 0 1 4 5 28 0 2 0 0 2 30 1 0 3 1 5 31+ 0 2 2 6 10 Total 0-30 148 230 147 93 617 Percent early neonatal1 74 73 62 64 69 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 0-6 days/0-30 days Appendix C | 243 Table C.6 Reporting of age at death in months Distribution of reported deaths under two years of age by age at death in months and the percentage of infant deaths reported to occur at less than one month of age, for five-year periods of birth preceding the survey, Eritrea 2002 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of years preceding the survey Age at ––––––––––––––––––––––––––––––––––– Total death (months) 0-4 5-9 10-14 15-19 0-19 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– < 1 month1 148 230 147 93 617 1 34 49 38 22 143 2 23 19 9 19 69 3 6 26 27 13 73 4 11 12 27 10 59 5 3 8 13 4 28 6 18 25 27 18 88 7 3 19 12 11 45 8 5 21 10 12 48 9 12 13 16 7 49 10 10 6 9 11 36 11 5 12 11 2 30 12 13 26 24 21 84 13 3 5 8 5 21 14 4 6 5 6 20 15 2 9 5 1 16 16 0 2 5 0 7 17 2 1 1 0 3 18 11 23 22 20 76 19 0 0 2 2 3 20 5 4 3 0 13 21 1 2 1 2 6 22 1 3 4 0 9 23 2 4 5 2 13 24+ 2 1 3 1 7 1 year 27 47 44 33 151 Total 0-11 277 440 344 224 1,285 Percent neonatal2 53 52 43 41 48 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Includes deaths under one month reported in days 2 Under one month/under one year Appendix D | 245 SURVEY PERSONNEL APPENDIX D NATIONAL STATISTICS AND EVALUATION OFFICE (NSEO) MANAGEMENT Georgies Teclemichael, Head, National Statistics and Evaluation Office Ainom Birhane, Deputy Head Gebrekristos Ogbamichael, Head, Administration and Finance TECHNICAL STAFF Woldeyesus Elisa, Senior Statistician and Demographer, Project Director Hagos Ahmed, Statistician and Demographer, Project Technical Director Yacob Yishak, Master in Public Health Gebreselassie Mebrahtu, Sampling Expert Yemane Yohennes, Cartography Expert FIELD COORDINATORS Haile Tewolde, Economist, Zoba Technical Coordinator Mengesteab Beleste, Statistician, Zoba Administrative Coordinator Omega Bokre, Statistician, Zoba Technical Coordinator Tirhas Tsegay, Statistician, Zoba Technical Coordinator Tecleab Yirgalem, Statistician, Zoba Administrative Coordinator Medhane Asrat, Statistician, Zoba Administrative Coordinator Mebrat Abreha, Statistician, Zoba Technical Coordinator Amleset Amenay, Statistician, Zoba Technical Coordinator Samson Hadish, Statistician, Zoba Technical Coordinator Teclom Tsegay, Zoba Administrative Coordinator Taeme Araya, Zoba Administrative Coordinator DATA PROCESSING STAFF Hurui Habtai, Computer Programmer Weldeselasie Hidray, Supervisor Medhane Gebrengus, Supervisor AUTHORS Chapter 1: Introduction Chapter 2: Characteristics of Households and Household Members Chapter 3: Women Characteristics and Status Chapter 4: Fertility Chapter 5: Fertility Regulation Chapter 6: Proximate Determinant of Fertility Chapter 7: Fertility Preferences Chapter 8: Infant and Child Mortality Chapter 9: Maternal and Child Health Chapter 10: Infant Feeding and Nutrition Gebremariam Woldemicael Omega Bokre and Sushil Kumar Hagos Ahmed and Anne Cross Hagos Ahmed Sushil Kumar Yacob Yisak Sushil Kumar Woldeyesus Elisa Michael Mehari, Shashu Gebraselasie, and Sushil Kumar Salma Mohamed 246 | Appendix D Chapter 11: AIDS and Other Sexually Transmitted Infections Chapter 12: Female Circumcision Andeberhan Tesfazion Azenegash Ghebreselasie, Hailemariam Andemariam, and Sushil Kumar TRAINERS Woldeyesus Elisa Hagos Ahmed Woldeselasie Hidray Abdulhamid Musanur Brhane Yohannes Michael Tekle Omega Bokre Almaz Seyum Salma Mohamed Samson Hadish Tekleab Yirgealem Tesfalul Andebrhan Tirhas Tesgay Yemane Kidane Yisahk Zekarias Shashu Gebreselasie TRANSLATORS: TIGRINA MANUAL AND QUESTIONNAIRE Abdulhamid Musanur Daniel Gebreyohanes Gebru Andom Medhane Asrat Michael Tekle Mulugheta Tekle Omega Bokre Tekleab Yirgealem Tesfalul Andebrhan Tirhas Tsegay Woldeselasie Hidray TRANSLATORS: LOCAL LANGUAGE QUESTIONNAIRES Osman Hamedu Sulus Beyen John Abraha Dawed Adem Ibrahim Mohammed Saleh Mohammud Afar Bilen Kunama Nara Saho Tigre FIELD STAFF Supervisors Abadit Estifanos Alem Fitwi Alganesh Tesfagaber Amal Abdunur Elsa Estifanos Hiriti Mebrahtu Legeset Fitseha Mineya Abraham Rahma Yacob Salha Ibrahim Semira Ahmedin Senait Haile Senbetu Ejidio Tirhas B’edemariam Field Editors Almaz Tekeste Awalet Eyob Awet Araya Dehab Tesfay Ji’mea Sulieman Kidsti Daniel Koyba Habteab Natalina Pawlo Nebyat Tekie Nitshti Tekle Rahwa Mohamed Resan Ghbrezghier Roble Mohamud Tinsu Aibu Appendix D | 247 Interviewers Abdu Yusuf Adiam Mehari Amasi Ghebrue Amuna Mehamed Angelina Eugenio Asmeret Asmerom Azeb Tareke Azeb Teklemariam Elsa Salm Elsa Resom Fana Indrias Fatma Edris Fozia Abdunur Freweini Habtay Fyori Tsegay Genet Zeray Halima Asmael Halima Kelifa Ali Hassan Idris Hawa Mohamed Hayat Ebrahim Hayat Abdela Haymanot Debesay Kedija Mahamed Kedja Abdu Kibret Tesfa Lemlem Kibrom Letehaimanot Gebreab Letekidan Birhane Lidya Eyob Mebrat Weldu Medhanit Weldegabr Meriem Ebrahim Mitsilal Abraham Natsnet Andemikael Natsnet Drar Ne’ima Salh Nefisa Abdela Netsanet Butsamlak Nura Faid Nuria Sead Rahel Petros Rahma Sulman Rekia Abdella Rigbe Kibrom Roman Freselase Ruta Ameno Saba Araya Saba Teklebrhan Sad’ya Ahmed Sadiya Musa Selemawit Estifanos Semret Tekle Senait Kiros Senait Weldegergish Sewsen Hlaf Tiakel Tekle Tigsti Fsahaye Tigsti Legese Tsega Zemichal Tsegereda Abib Tsehanesh G/nigus Tsgheweyni Tekie Yokbit Aron Zahra Edris Zebiba Mohammed LISTING AND MAPPING Coordinators Araya Woldegebreal Teklom Tsegay Taeme Araya Supervisors Medhane Asrat Gebru Andom Mulugeta Tekle Daniel Gebreyohannis Kiflemariam Hayle Medhane Yohannis Yosef Haile Tedros Tekle Negasi Girmay Debesay Tesfay Mebrahtu Gebremikael 248 | Appendix D Mappers Abdella Idris Abraham Tesfatsion Amanuel Isaya Asmelash Yemane Awet Kidane Bereket Gebreigzabiher Daniel Kiros Destalem Berhe Efrem Gebray Fesseha Yohannes Henok Gebrehiwot Iyasu Habte Luwam Tiumizgi Medhane Gebrenegus Mekonnen Berhane Hassen Idris Yonas Berhane Ristom Amlesom Yasin Ali Samson Gayim Abdu Yusuf Listers Abdulkadir Hamedzein Abraham Gebrezgi Berhane Gebrehanis Efrem Tesfay Goytom Tsegay Habtom Makele Gerezgiher Hibret Estifanos Huriya Noray Jemal Mehamednur Layde Anselmo Gini Bakit Merhawi Tsegai Nejat Ahmed Ibrahim Romadan Yusuf Selemawit Melake Taame Negash Tsegay Teklehaymanot Yohannis Girmatsio Mohammedhagos Ata Zeynab Umar DATA PROCESSING Computer Programmer Hurui Habtai Supervisor Weldeselasie Hidray Medhane Gebrengus Questionnaire Administrator Aster Gebremariam Data Entry Operators Akberet Gebremariam Asmait Negash Fithawit T/Michael Fiyori Gebremichael Freweigni Gebremariam Ghenet Keleta Lydia Girmay Natsenet Betsuamlak Selamawit Kurban Selamawit T/Berhan Senait Tesfazghi Simret Mesfun Tereza Ferdinando Timnit G/Michael Appendix D | 249 DRIVERS Abdelwasie Ata Abduselam Mohamednur Abreham Fesehatsion Afewerki Tekleab Fesehaye Gebremariam Fitwi Araya Hagos Abdelwahab Johar Mohamednur Kiflom Tesfatsion Mebrahtu Seyum Mehari Beyene Michael Brhane Mohamed Ali Okbay Zeweldi Pawlos Weldegebriel Samuel Afewerki Seltene Gaym Tesfalem Tekle SUPPORT STAFF Tecleab Ogbatsion Freweigni Alemseged Andemariam Woldeselasie Aster Estifanos Nardos Teklegiorgis Accountant Cashier Purchaser Secretary Secretary ORC MACRO Sushil Kumar, Country Manager Anne Cross, Regional Coordinator Ann Way, Vice President Jeanne Cushing, Senior Data Processing Specialist Jeanetta Churchill, Data Processing Specialist Alfredo Aliaga, Senior Sampling Specialist Daniel Vadnais, Data Dissemination Coordinator Sidney Moore, Editor Tulshi Saha, Demographer Fred Arnold, Vice President Katherine Senzee, Document Production Specialist Luis Hernando Ochoa, Regional Coordinator Kaye Mitchell, Document Production Specialist Appendix E | 251 QUESTIONNAIRES APPENDIX E Appendix E | 253 THE STATE OF ERITREA OFFICE OF THE PRESIDENT NATIONAL STATISTICS AND EVALUATION OFFICE ERITREA DEMOGRAPHIC AND HEALTH SURVEY HOUSEHOLD SCHEDULE ALL INFORMATION COLLECTED IS CONFIDENTIAL AND IS ONLY FOR STATISTICAL USE IDENTIFICATION ZOBA . SUB-ZOBA . VILLAGE/TOWN NAME________________________________________________________________________________ [ASMARA=1, OTHER TOWN =2, RURAL = 3] . CLUSTER NUMBER . HOUSEHOLD NUMBER . NAME OF HOUSEHOLD HEAD__________________________________________________________________________  INTERVIEWER VISITS 1 2 3 FINAL VISIT DATE TEAM INTERVIEWER’S NAME RESULT SEE * BELOW ____/______/______ DD MM YYYY  ________________ ____/______/______ DD MM YYYY  ________________ ____/______/______ DD MM YYYY  ________________ DAY. MONTH. YEAR. TEAM . NAME. RESULT  . NEXT VISIT: DATE TIME ____/______/______ DD MM YYYY ________________ ____/______/______ DD MM YYYY ________________  TOTAL NO. OF VISITS * RESULT CODES 1=COMPLETED 4=POSTPONED 7=DWELLING DESTROYED 2=NO HOUSEHOLD MEMBER/COMPETENT 5=REFUSED 8=DWELLING NOT FOUND RESPONDENT AT HOME AT TIME OF VISIT 6=DWELLING VACANT OR 9=OTHER________________ 3=ENTIRE HOUSEHOLD ABSENT FOR EXT. PERIOD ADDRESS NOT A DWELLING (SPECIFY) LANGUAGE:SEE ** BELOW TOTAL PERSONS IN THE HOUSEHOLD QUESTIONNAIRE LANGUAGE OF NATIVE LANGUAGE INTERVIEW OF THE RESPONDENT ** LANGUAGE CODES: 01=AFAR 02= BILEN 03= HEDARIB (Tobedawi) 04= KUNAMA 05= NARA 06= RASHAIDA (Arabic) 07= SAHO 08= TIGRE 09= TIGRIGNA 10= OTHER TRANSLATOR USED (1= NOT AT ALL, 2= SOMETIMES, 3= ALL THE TIME)…………….……. TOTAL ELIGIBLE WOMEN LINE NUMBER OF RESPONDENT TO HOUSEHOLD SCHEDULE SUPERVISOR NAME______________________ DATE____/_____/_____ DD MM YYYY FIELD EDITOR NAME_________________ DATE____/_____/_____ DD MM YYYY OFFICE EDITOR KEYED BY 254 | Appendix E HOUSEHOLD SCHEDULE Now we would like some information about the people who usually live in your household or who are staying with you now EDUCATION LINE NO. USUAL RESIDENTS AND VISTORS SEX RELATION TO HEAD OF HOUSE- HOLD* RESIDENCE AGE IF AGE 6 YEARS OR OLDER IF ATTENDED SCHOOL IF AGE LESS THAN 25 YEARS Please give me the name of the persons who usually live in your household and guests of the household who stayed here last night, starting with the head of the household. Is (NAME) male or female? What is the relation-ship of (NAME) to the head of the household ? SEE * BELOW Does (NAME) usually live here? Did (NAME) Stay here last night? How old is (NAME)? Can (NAME) read and write in any language without difficulty? Has (NAME) ever been to school? IF NO GO TO 12 What is the highest level of school (NAME) attended? What is the highest grade (NAME) completed at that level? SEE **BELOW Is (NAME) still in school? (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 01  M F 1 2 YES NO 1 2 YES NO 1 2 IN YEARS YES NO 1 2 YES NO 1 2 LEVEL GRADE YES NO 1 2 02 1 2 1 2 1 2 1 2 1 2 1 2 03 1 2 1 2 1 2 1 2 1 2 1 2 04 1 2 1 2 1 2 1 2 1 2 1 2 05 1 2 1 2 1 2 1 2 1 2 1 2 06 1 2 1 2 1 2 1 2 1 2 1 2 07 1 2 1 2 1 2 1 2 1 2 1 2 08 1 2 1 2 1 2 1 2 1 2 1 2 09 1 2 1 2 1 2 1 2 1 2 1 2 10 1 2 1 2 1 2 1 2 1 2 1 2 11 1 2 1 2 1 2 1 2 1 2 1 2 12 1 2 1 2 1 2 1 2 1 2 1 2 13 1 2 1 2 1 2 1 2 1 2 1 2 14 1 2 1 2 1 2 1 2 1 2 1 2 TICK HERE IF CONTINUATION SHEET USED Just to make sure that I have a complete listing: 1. Are there any other persons such as small children or infants that we have not listed?………………………………………. .YES ENTER EACH IN TABLE NO 2. In addition, are there any other people who may not be members of your family such as domestic servants , lodgers or friends who usually live here?…………………….…YES ENTER EACH IN TABLE NO 3. Are there any guests or temporary visitors staying here, or any one else who slept here last night that have not been listed?………………………………………………….….YES ENTER EACH IN TABLE NO Appendix E | 255 PARENTAL SURVIVORSHIP AND RESIDENCE FOR PERSONS LESS THAN 15 YEARS OLD These questions refer to the biological parents of the child. Record "00" if parent not member of the household. IF AGE >=15 ASK FOR THOSE AGED 10 YEARS OR MORE IF ALIVE IF ALIVE IF YES TO QUESTION 15B:ASK QUESTIONS 15C AND 15D ELIGIBILITY Is (NAME)’s natural mother alive? Does (NAME)’s natural mother live in this household? If YES, what is her name? RECORD MOTHER’S LINE NUMBER Is (NAME)’s natural father alive? Does (NAME)’s natural father live in this household? If YES, what is his name? RECORD FATHER’S LINE NUMBER What is (NAME)’s current marital status? SEE *** BELOW Did (NAME) work during last month? Is (NAME) paid in cash or kind for the work he/she does? 1=CASH 2=KIND 3=BOTH 4=NOT PAID What is the main work that (NAME) does? OCCU PA- TION CODE CIRCLE LINE NUMBER OF ALL WOMEN AGED 15-49 CIRCLE LINE NUMBER OF ALL CHILDREN UNDER AGE 6 (12) (13) (14) (15) (15A) (15B) (15C) (15D) (15E) (16) (17) YES NO DK 1 2 3 YES NO DK 1 2 3 YES NO 1 2 1 2 3 4 01 01 1 2 3 1 2 3 1 2 1 2 3 4 02 02 1 2 3 1 2 3 1 2 1 2 3 4 03 03 1 2 3 1 2 3 1 2 1 2 3 4 04 04 1 2 3 1 2 3 1 2 1 2 3 4 05 05 1 2 3 1 2 3 1 2 1 2 3 4 06 06 1 2 3 1 2 3 1 2 1 2 3 4 07 07 1 2 3 1 2 3 1 2 1 2 3 4 08 08 1 2 3 1 2 3 1 2 1 2 3 4 09 09 1 2 3 1 2 3 1 2 1 2 3 4 10 10 1 2 3 1 2 3 1 2 1 2 3 4 11 11 1 2 3 1 2 3 1 2 1 2 3 4 12 12 1 2 3 1 2 3 1 2 1 2 3 4 13 13 1 2 3 1 2 3 1 2 1 2 3 4 14 14 * CODES FOR Q.4 ** CODES FOR Q.10 ***CODES FOR Q.15A RELATIONSHIP TO HEAD OF HOUSEHOLD: EDUCATIONAL LEVEL: MARITAL STATUS: 01=Head 07=Parent-in-law 1=Primary/elementary 2=Middle 1=Married 02=Wife or husband 08=Brother or sister 3=Secondary 4=Higher 2=Living together 03=Son or daughter 09=Co-wife 8=Don’t know 3=Widowed 04=Son in-law or daughter in-law 10=Other relatives 4=Divorced 05=Grand child 11= Adopted/foster/step child EDUCATIONAL GRADE: 5=Separated 06=Parent 12= Not related 00=Less than one year completed 6=Single /never married 98=Don’t know 98=Don’t know THE QUESTIONNAIRE HAS SPACES TO RECORD UP TO 14 HOUSEHOLD MEMBERS, IF MORE ADD ANOTHER QUESTIONNAIRE. 256 | Appendix E 17A During the past two years, that is 24 months, has any of the usual members of this household died? YES NO SKIP TO 18 Now we would like to have some information about all of the deaths that occurred in this household to usual residents during the past 24 months. IF MORE THAN FOUR DEATHS ADD NEW HOUSEHOLD QUESTIONNAIRE DATE OF DEATH NAME OF PERSON SEX AGE AT DEATH MONTH YEAR Sr. No. Please give me the names of all the persons who were usual residents of this household and died during the past 24 months, that is, since 2000 to the to the month of interview. Was (NAME) Male or Female? How old was (NAME) when he/she died? RECORD IN COMPLETED YEARS In what month did (NAME) die? PROBE: During what season? In what year did (NAME) die? PROBE: This year or last year? (17B) (17C) (17D) (17E) (17F) 1 M F 1 2 AGE MONTH YEAR  2 1 2 3 1 2 4 1 2 TOTAL DEATHS IN THE HOUSEHOLD   NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 18 Are there any members in this household who are displaced because of the recent war between Eritrea and Ethiopia? IF YES, how many? IF NONE RECORD "00". NUMBER OF PERSONS DISPLACED  .  19 What is the main source of drinking water for members of your household? PIPED WATER PIPED IN TO RESIDENCE /YARD /PLOT. 11 PUBLIC TAP. 12 PROTECTED WELL WATER WELL IN RESIDENCE/YARD/PLOT . 21 PUBLIC WELL . 22 UN PROTECTED WELL WATER WELL IN RESIDENCE/YARD/PLOT . 31 PUBLIC WELL . 32 SURFACE WATER SPRING . 41 RIVER/STREAM . 42 POND/LAKE. 43 DAM . 44 TANKER TRUCK. 61 OTHER _______________________________________ 96 (SPECIFY) 21 21 21 Appendix E | 257 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 20 How long does it take to go there, get water, and come back? IF LESS THAN ONE MINUTE CIECLE ‘996’. MINUTES . ON PREMISES. 996 21 20A How long is the normal wait to take your turn to get water at the (NAME OF THE WATER SOURCE)? MINUTES . NO WAIT . 996 20B Who mainly fetch water for the household? MALE . 1 FEMALE. 2 21 What kind of toilet facility does your household have? FLUSH TOILET OWN FLUSH TOILET . 11 SHARED FLUSH TOILET. 12 PIT TOILET /LATRINE TRADITIONAL PIT TOILET . 21 VENTILATED IMPROVED PIT (VIP) LATRINE . 22 NO FACILITY /BUSH/FIELD. 31 OTHER _____________________________________ 96 (SPECIFY) 22 Does your household have: Electricity? A radio? A television? A telephone? A refrigerator? YES NO ELECTRICITY. 1 2 RADIO. 1 2 TELEVISION . 1 2 TELEPHONE . 1 2 REFRIGERATOR . 1 2 22A Does your household: Own the house it is living in? Have cropland? Have cattle or camels? Have horse or mule or donkey? Have sheep or goats? Grow cash crops? YES NO OWN HOUSE. 1 2 CROPLAND. 1 2 CATTLE/CAMEL. 1 2 HORSE/MULE/DONKEY. 1 2 SHEEP/GOATS. 1 2 CASH CROPS . 1 2 23A How many rooms excluding kitchen and toilet in this dwelling are for the exclusive use for the members of this household? NUMBER OF ROOMS.  23B How many rooms in your household are used for sleeping? NUMBER OF ROOMS.  23C Are any farm animals kept within the living area of the household? YES . 1 NO. 2 258 | Appendix E NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 24 MAIN MATERIAL OF THE FLOOR RECORD OBESERVATION. NATURAL FLOOR EARTH /SAND. 11 DUNG. 12 RUDIMENTARY FLOOR WOOD PLANKS. 21 PALM /BAMBOO . 22 FINISHED FLOOR PARQUET OR POLISHED WOOD. 31 VINIL OR ASPHALT STRIPS . 32 CERAMIC TILES. 33 CEMENT. 34 CARPET. 35 OTHER ________________________________________ 96 (SPECIFY) 25 Does any member of your household own: A donkey cart? A bicycle? A motorcycle? A car or truck? YES NO DONKEY CART . 1 2 BICYCLE. 1 2 MOTORCYCLE . 1 2 CAR\TRUCK. 1 2 25A What type of fuel dose your household mainly use for cooking? ELECTRICITY . 01 LPG/NATURAL GAS . 02 BIOGAS . 03 KEROSINE . 04 COAL, LIGINITE . 05 CHARCOAL . 06 FIREWOOD, STRAW. 07 ANIMAL DUNG CAKES . 08 OTHERS _______________________________________ 96 (SPECIFY) 26 ASK RESPONDENT FOR A TEASPOONFUL OF SALT THEY USUALLY USE. TEST FOR IODINE RECORD PPM (PARTS PER MILLION) 0 PPM (NO IODINE). 1 7 PPM . 2 15 PPM . 3 30 PPM . 4 NO SALT IN THE HH . 5 SALT NOT TESTED ______________________________ 6 (SPECIFY REASONS) 27 Does your household have any mosquito nets that can be used while sleeping? YES. 1 NO . 2 28A 28 How many mosquito nets are there in this household? MOSQUITO NETS. DON’T KNOW . 98 Appendix E | 259 WEIGHT AND HEIGHT MEASUREMENT 28A. CHECK COLUMNS (16) AND (17): RECORD THE LINE NUMBER, NAME AND AGE OF ALL WOMEN AGE 15-49 AND ALL CHILDREN UNDER AGE 6. WOMEN 15-49 WEIGHT AND HEIGHT MEASUREMENT OF WOMEN 15-49 LINE NO. FROM COL. (16) NAME FROM COL. (2) AGE FROM COL. (7) What is (NAME)’s date of birth? WEIGHT (KILOGRAMS) HEIGHT (CENTIMETERS) MEASURED LYING DOWN OR STANDING UP RESULT 1= MEASURED 2= NOT PRESENT 3= REFUSED 6= OTHER (29) (30) (31) (32) (33) (34) (35) (36) YEARS . . . . . . . . . . CHILDREN UNDER AGE 6 WEIGHT AND HEIGHT MEASUREMENT OF CHILDREN BORN IN 1997 OR LATER LINE NO. FROM COL. (17) NAME FROM COL. (2) AGE FROM COL. (7) What is (NAME)’s date of birth? WEIGHT (KILOGRAMS) HEIGHT (CENTIMETERS) HEIGHT MEASURED LYING DOWN OR STANDING UP RESULT 1= MEASURED 2=NOT PRESENT 3= REFUSED 6= OTHER YEARS DAY MONTH YEAR 0 . . LYING STAND 1 2 0 . . 1 2 0 . . 1 2 0 . . 1 2 0 . . 1 2 0 . . 1 2 TICK HERE IF CONTINUATION SHEET USED THANK YOU! THANK YOU!! THANK YOU!!! 260 | Appendix E INTERVIEWER'S OBSERVATIONS TO BE FILLED IN AFTER COMPLETING INTERVIEW COMMENTS ABOUT RESPONDENT: COMMENTS ON SPECIFIC QUESTIONS: ANY OTHER COMMENTS: SUPERVISOR'S OBSERVATIONS NAME OF THE SUPERVISOR:______________________________________DATE: __________/________/__________ EDITOR'S OBSERVATIONS NAME OF EDITOR:_______________________________________________DATE: _________/_________/__________ Appendix E | 261 THE STATE OF ERITREA OFFICE OF THE PRESIDENT NATIONAL STATISTICS AND EVALUATION OFFICE ERITREA DEMOGRAPHIC AND HEALTH SURVEY WOMEN’S QUESTIONNAIRE ALL INFORMATION COLLECTED IS CONFIDENTIAL AND IS ONLY FOR STATISTICAL USE IDENTIFICATION ZOBA . SUB-ZOBA . VILLAGE/TOWN NAME ________________________________________________________________________ [ASMARA=1, OTHER TOWN =2, RURAL = 3] CLUSTER NUMBER . HOUSEHOLD NUMBER . NAME OF HOUSEHOLD HEAD __________________________________________________________________ NAME AND LINE NUMBER OF WOMAN _________________________________________________________ INTERVIEWER VISITS 1 2 3 FINAL VISIT DATE TEAM INTERVIEWER’S NAME RESULT SEE* BELOW ____/_____/_____ DD MM YYYY _______________________ ____/_____/_____ DD MM YYYY _______________________ ____/_____/_____ DD MM YYYY _______________________ DAY MONTH YEAR TEAM NAME RESULT NEXT VISIT: DATE TIME ____/_____/_____ DD MM YYYY _______________ ____/_____/_____ DD MM YYYY _______________ TOTAL NO. OF VISITS * RESULT CODES 1=COMPLETED 4= REFUSED 7=OTHER_________________ 2=NOT AT HOME 5=PARTIALLY COMPLETED (SPECIFY) 3=POSTPONED 6=INCAPACITATED LANGUAGE: SEE ** BELOW LANGUAGE OF NATIVE LANGUAGE QUESTIONNAIRE INTERVIEW OF RESPONDENT ** LANGUAGE CODES: 01=AFAR 02= BILEN 03= HEDARIB (Tobedawi) 04= KUNAMA 05= NARA 06= RASHAIDA (Arabic) 07= SAHO 08= TIGRE 09= TIGRIGNA 10= OTHER __________________ TRANSLATOR USED (1= NOT AT ALL, 2= SOMETIMES, 3= ALL THE TIME)……………………………………. SUPERVISOR NAME________________________ DATE____/_____/_____ DD MM YYYY FIELD EDITOR NAME________________________ DATE____/_____/_____ DD MM YYYY OFFICE EDITOR KEYED BY 262 | Appendix E SECTION 1. RESPONDENT’S BACKGROUND INTRODUCTION Hello. My name is _____________________________________ and I am working with the National Statistics and Evaluation Office. We are conducting a national survey about the health of women and children. We would very much appreciate your participation in this survey. I would like to ask you about your health (and the health of your children). This information will help the government to plan health services. The questionnaire usually takes between 20 and 45 minutes to complete. Whatever information you provide will be kept strictly confidential and will not be shown to other persons. NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 101 RECORD THE TIME. HOUR . MINUTES. 102 First I would like to ask some questions about you and your household. For most of the time until you were 12 years old, did you live in a city, in a town, or in a village? CITY . 1 TOWN. 2 VILLAGE . 3 102A What was the name of the village/town/city in which you lived as child? RECORD NAME OF VILLAGE/TOWN AND ZOBA. IF PLACE WAS OUTSIDE OF ERITREA, RECORD NAME OF THE COUNTRY. VILLAGE/TOWN/CITY____________ ZOBA NAME ______________ COUNTRY _________________________ 96 103 How long have you been living continuously in (NAME OF CURRENT PLACE OF RESIDENCE)? IF LESS THAN ONE YEAR, RECORD ‘00' YEARS. YEARS. ALWAYS. 95 VISITOR. 96 105 104 Just before you moved here, did you live in a city, in a town, or in a village? CITY . 1 TOWN. 2 VILLAGE . 3 104A What was the name of the zoba in which you lived just before you moved here? RECORD NAME OF ZOBA. IF PLACE WAS OUTSIDE OF ERITREA, RECORD NAME OF THE COUNTRY ZOBA NAME _____________ COUNTRY _________________________ 96 104B What was the main reason for your move? LIBERATION. 01 WAR . 02 DROUGHT/DEFORESTATION . 03 FAMINE . 04 EMPLOYMENT. 05 EDUCATION . 06 SECURITY . 07 MARRIAGE . 08 OWN/BETTER HOME. 09 DEPORTED. 10 INTERNAL DISPLACEMENT. 11 OTHER ___________________________ 96 (SPECIFY) Appendix E | 263 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 105 In what month and year were you born? MONTH. DON’T KNOW MONTH. 98 YEAR. DON’T KNOW YEAR. 9998 106 How old were you at your last birthday? COMPARE AND CORRECT 105 AND/OR 106 IF INCONSISTENT. AGE IN COMPLETED YEARS. 107 Have you ever attended school? YES . 1 NO. 2 113A 108 What is the highest level of school you attended: Primary, middle, secondary, or higher? PRIMARY . 1 MIDDLE . 2 SECONDARY . 3 HIGHER. 4 109 What is the highest grade you completed at that level? GRADE. 110 CHECK 106: AGE 24 AGE 25 OR BELOW OR ABOVE 113 111 Are you currently attending school? YES . 1 NO . 2 113 112 What was the main reason you stopped attending school? GOT PREGNANT . 01 GOT MARRIED . 02 TO CARE FOR YOUNGER CHIDREN . 03 FAMILY NEEDED HELP ON FARM OR IN BUSINESS . 04 COULD NOT PAY SCHOOL FEES . 05 NEEDED TO EARN MONEY. 06 GRADUATED/HAD ENOUGH SCHOOLING. 07 DID NOT PASS ENTRANCE EXAM. 08 DID NOT LIKE SCHOOL . 09 SCHOOL NOT ACCESSABLE/TOO FAR . 10 ILLNESS. 11 OTHER ____________________________ 96 (SPECIFY) DON’T KNOW. 98 113 CHECK 108: PRIMARY MIDDLE SCHOOL OR ABOVE 114 113A Are you currently participating in a literacy program or any other program (not including primary school) that involves learning to read or write? YES . 1 NO. 2 113B Can you read and write in any language without any difficulty? YES . 1 NO. 2 115 264 | Appendix E NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 114 Do you usually read a newspaper or magazine at least once a week? YES . 1 NO. 2 115 Do you usually listen to a radio at least once a week? YES . 1 NO. 2 116 Do you usually watch television at least once a week? YES . 1 NO. 2 117 What is your religion? ORTHODOX . 1 CATHOLIC . 2 PROTESTANT. 3 MUSLIM. 4 TRADITIONAL BELIEVER. 5 OTHER _____________________________ 6 (SPECIFY) 118 To which ethnic group do you belong? AFAR. 01 BILEN. 02 HEDARIB. 03 KUNAMA. 04 NARA . 05 RASHAIDA. 06 SAHO. 07 TIGRE. 08 TIGRIGNA . 09 OTHER ____________________________ 96 (SPECIFY) Appendix E | 265 SECTION 2: REPRODUCTION NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 201 Now I would like to ask about all the births you have had during your life. Have you ever given birth? YES . 1 NO. 2 206 202 Do you have any sons or daughters to whom you have given birth who are now living with you? YES . 1 NO. 2 204 203 How many sons live with you? And how many daughters live with you? IF NONE, RECORD ‘00'. SONS AT HOME . DAUGHTERS AT HOME . 204 Do you have any sons or daughters to whom you have given birth who are alive but do not live with you? YES . 1 NO. 2 206 205 How many sons are alive but do not live with you? And how many daughters are alive but do not live with you? IF NONE, RECORD ‘00'. SONS ELSEWHERE. DAUGHTERS ELSEWHERE . 206 Have you ever given birth to a boy or girl who was born alive but later died? IF NO, PROBE: Any baby who cried or showed signs of life but did not survive? YES . 1 NO. 2 208 207 How many boys have died? And how many girls have died? IF NONE, RECORD ‘00'. BOYS DEAD. GIRLS DEAD. 208 SUM ANSWERS TO 203, 205, AND 207, AND ENTER TOTAL. IF NONE, RECORD ‘00'. TOTAL. 209 CHECK 208: Just to make sure that I have this right: you have had in TOTAL _____ births during your life. Is that correct? PROBE AND YES NO CORRECT 201-208 AS NECESSARY. 210 CHECK 208: ONE OR MORE NO BIRTHS BIRTHS 225 266 | Appendix E 211 Now I would like to record the names of all your births, whether still alive or not, starting with the first one you had. RECORD NAMES OF ALL THE BIRTHS IN 212. RECORD TWINS AND TRIPLETS ON SEPARATE LINES. 212 213 214 215 216 217 IF ALIVE: 218 IF ALIVE: 219 IF ALIVE: 220 IF DEAD: 221 What name was given to your (first/next) baby? (NAME) Were any of these births twins? Is (NAME ) a boy or a girl? In what month and year was (NAME) born? PROBE: What is his/her birthday? Is (NAME) still alive? How old was (NAME) at his/her last birthday? RECORD AGE IN COM- PLETED YEARS. Is (NAME) living with you? RECORD HOUSEHOLD LINE NUMBER OF CHILD (RECORD '00' IF CHILD NOT LISTED IN HOUSEHOLD). How old was (NAME) when he/she died? IF ‘1 YR.’, PROBE: How many months old was (NAME)? RECORD DAYS IF LESS THAN 1 MONTH; MONTHS IF LESS THAN TWO YEARS; OR YEARS. Were there any other live births between [NAME OF PREVIOUS BIRTH] AND [NAME]? 01 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (NEXT BIRTH) DAYS . 1 MONTHS . 2 YEARS. 3 IF YES, ADD THAT BIRTH TO THE END OF THE BIRTH HISTORY (212) 02 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GO TO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 03 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GO TO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 04 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GO TO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 05 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GO TO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 06 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GO TO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 07 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GO TO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 Appendix E | 267 212 213 214 215 216 217 IF ALIVE: 218 IF ALIVE: 219 IF ALIVE 220 IF DEAD: 221 What name was given to your next baby? (NAME) Were any of these births twins? Is (NAME ) a boy or a girl? In what month and year was (NAME) born? PROBE: What is his/her birthday? Is (NAME) still alive? How old was (NAME) at his/her last birthday? RECORD AGE IN COM- PLETED YEARS. Is (NAME) living with you? RECORD HOUSEHOLD LINE NUMBER OF CHILD (RECORD '00' IF CHILD NOT LISTED IN HOUSEHOLD). How old was (NAME) when he/she died? IF ‘1 YR.’, PROBE: How many months old was (NAME)? RECORD DAYS IF LESS THAN 1 MONTH; MONTHS IF LESS THAN TWO YEARS; OR YEARS. Were there any other live births between [NAME OF PREVIOUS BIRTH] AND [NAME]? 08 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GOTO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 09 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GOTO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 10 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GOTO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 11 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GOTO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 12 SING . 1 MULT 2 BOY. 1 GIRL 2 MONTH YEAR YES. 1 NO . 2 220 AGE IN YEARS YES. 1 NO. 2 LINE NUMBER (GOTO 221) DAYS . 1 MONTHS . 2 YEARS. 3 YES. 1 NO . 2 222 Have you had any live births since the birth of (NAME OF LAST BIRTH)? IF YES, ADD THAT BIRTH TO THE END OF THE BIRTH HISTORY (212) YES. 1 NO . 2 223 COMPARE 208 WITH NUMBER OF BIRTHS IN HISTORY ABOVE AND MARK: NUMBERS NUMBERS ARE ARE SAME DIFFERENT (PROBE AND RECONCILE) CHECK: FOR EACH BIRTH: YEAR OF BIRTH IS RECORDED . FOR EACH LIVING CHILD: CURRENT AGE IS RECORDED . FOR EACH DEAD CHILD: AGE AT DEATH IS RECORDED. FOR AGE AT DEATH 12 MONTHS OR 1 YEAR: PROBED TO DETERMINE EXACT NUMBER OF MONTHS . 224 CHECK 215 AND ENTER THE NUMBER OF BIRTHS IN 1997 OR LATER. IF NONE, RECORD “0”. 268 | Appendix E NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 225 Have you ever had a pregnancy that miscarried, was aborted, or ended in a stillbirth? YES . 1 NO. 2 226 225A When did the last such pregnancy end? MONTH. YEAR. 225B CHECK 225A: LAST PREGNANCY LAST PEGNANCY ENDED IN ENDED BEFORE 1997 OR LATER 1997 226 225C How many months pregnant were you when the last such pregnancy ended? RECORD NUMBER OF COMPLETED MONTHS MONTHS . 226 Are you pregnant now? YES . 1 NO . 2 UNSURE. 8 237 227 How many months pregnant are you? RECORD NUMBER OF COMPLETED MONTHS. NUMBER OF MONTHS. 228 At the time you became pregnant did you want to become pregnant then, did you want to wait until later, or did you not want to have any (more) children at all? THEN . 1 LATER . 2 NOT AT ALL. 3 237 When did your last menstrual period start? _____________________________________________________ (DATE, IF GIVEN) DAYS AGO . 1 WEEKS AGO. 2 MONTHS AGO . 3 YEARS AGO . 4 IN MENOPAUSE/ HAS HAD HYSTERECTOMY. 994 BEFORE LAST BIRTH . 995 NEVER MENSTRUATED. 996 238 From one menstrual period to the next, are there certain days when a woman is more likely to become pregnant if she has sexual relations? YES . 1 NO . 2 DON’T KNOW . 8 301 239 Is this time just before her period begins, during her period, right after her period has ended, or halfway between two periods? JUST BEFORE HER PERIOD BEGINS. 1 DURING HER PERIOD. 2 RIGHT AFTER HER PERIOD HAS ENDED. 3 HALFWAY BETWEEN TWO PERIODS . 4 OTHER_______________________________ 6 (SPECIFY) DON’T KNOW . 8 Appendix E | 269 SECTION 3. CONTRACEPTION Now I would like to talk about family planning - the various ways or methods that a couple can use to delay or avoid a pregnancy. CIRCLE CODE 1 IN 301 FOR EACH METHOD MENTIONED SPONTANEOUSLY. THEN PROCEED DOWN COLUMN 301, READING THE NAME AND DESCRIPTION OF EACH METHOD NOT MENTIONED SPONTANEOUSLY. CIRCLE CODE 1 IF METHOD IS RECOGNIZED, AND CODE 2 IF NOT RECOGNIZED. THEN, FOR EACH METHOD WITH CODE 1 CIRCLED IN 301 ASK 302. 301 Which ways or methods have you heard about? FOR METHODS NOT MENTIONED SPONTANEOUSLY, ASK Have you ever heard of (METHOD)? 302 Have you ever used (METHOD)? 01 FEMALE STERILIZATION Women can have an operation to avoid having any (more) children. YES. 1 NO . 2 Have you ever had an operation to avoid having any (more) children? YES . 1 NO. 2 02 MALE STERILIZATION Men can have an operation to avoid having any (more) children. YES. 1 NO . 2 Have you ever had a partner who had an operation to avoid having any (more) children? YES . 1 NO. 2 03 PILL Women can take a pill every day to avoid becoming pregnant. YES. 1 NO . 2 YES . 1 NO. 2 04 IUD Women can have a loop or coil placed inside them by a doctor or a nurse. YES. 1 NO . 2 YES . 1 NO. 2 05 INJECTIONS Women can have an injection by a health provider that stops them from becoming pregnant for one or more months. YES. 1 NO . 2 YES . 1 NO. 2 06 IMPLANTS Women can have several small rods placed in their upper arm by a doctor or nurse which can prevent pregnancy for one or more years. YES. 1 NO . 2 YES . 1 NO. 2 07 CONDOM Men can put a rubber sheath on their penis before sexual intercourse. YES. 1 NO . 2 YES . 1 NO. 2 08 FEMALE CONDOM Women can place a sheath in their vagina before sexual intercourse. YES. 1 NO . 2 YES . 1 NO. 2 09 DIAPHRAGM Women can place a thin flexible disk in their vagina before intercourse. YES. 1 NO . 2 YES . 1 NO. 2 10 FOAM OR JELLY Women can place a suppository, jelly, or cream in their vagina before intercourse. YES. 1 NO . 2 YES . 1 NO. 2 11 LACTATIONAL AMENORRHEA METHOD (LAM) Up to 6 months after childbirth, a woman can use a method that requires that she breastfeeds frequently, day and night, and that her menstrual period has not returned. YES. 1 NO . 2 YES . 1 NO. 2 12 RHYTHM OR PERIODIC ABSTINENCE Every month that a woman is sexually active she can avoid pregnancy by not having sexual intercourse on the days of the month she is most likely to get pregnant. YES. 1 NO . 2 YES . 1 NO. 2 13 WITHDRAWAL Men can be careful and pull out before climax YES. 1 NO . 2 YES . 1 NO. 2 14 EMERGENCY CONTRACEPTION Women can take pills up to three days after sexual intercourse to avoid becoming pregnant. YES. 1 NO . 2 YES . 1 NO. 2 15 Have you heard of any other ways or methods that women or men can use to avoid pregnancy? YES. 1 (SPECIFY) (SPECIFY) NO . 2 YES . 1 NO. 2 YES . 1 NO. 2 303 CHECK 302: NOT A SINGLE AT LEAST ONE ‘YES’ ‘YES’ (NEVER USED) (EVER USED) 307 270 | Appendix E NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 304 Have you ever used anything or tried in any way to delay or avoid getting pregnant? YES. 1 NO. 2 329 306 What have you used or done? CORRECT 302 (AND 301 IF NECESSARY). _______________________________ 307 Now I would like to ask you about the first time that you did something or used a method to avoid getting pregnant. How many living children did you have at that time, if any? IF NONE, RECORD ‘00'. NUMBER OF CHILDREN. 307A When you first began to use family planning, did you want to have a (another) child but at a later time, or did you not want to have a (another) child at all ? WANTED CHILD LATER. 1 DID NOT WANT A (ANOTHER) CHILD AT ALL. 2 OTHER ____________________________ 6 (SPECIFY) 308 CHECK 302 (01): WOMAN NOT WOMAN STERILIZED STERILIZED 311A 309 CHECK 226: NOT PREGNANT PREGNANT OR UNSURE 329A 310 Are you currently doing something or using any method to delay or avoid getting pregnant? YES. 1 NO. 2 329 311 311A Which method are you using? IF MORE THAN ONE METHOD MENTIONED, FOLLOW SKIP INSTRUCTION FOR HIGHEST METHOD ON LIST. CIRCLE ‘A' FOR FEMALE STERILIZATION. FEMALE STERILIZATION . A MALE STERILIZATION . B PILL. C IUD . D INJECTABLES . E IMPLANTS . F CONDOM. G FEMALE CONDOM . H DIAPHRAGM . I FOAM/JELLY. J LACTATIONAL AMEN. METHOD. K PERIODIC ABSTINENCE. L WITHDRAWAL . M OTHER X (SPECIFY) 313 316A 312 How much does one packet or cycle of pills cost you? COST . . FREE. 9996 DON’T KNOW . 9998 316A Appendix E | 271 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 313 In what facility did the sterilization take place? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. _______________________________________ (NAME OF PLACE) PUBLIC SECTOR GOVT. HOSPITAL . 11 OTHER PUBLIC __________________ 16 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC. 21 PRIVATE DOCTOR . 23 OTHER PRIVATE MEDICAL ______________________ 26 (SPECIFY) OTHER 96 (SPECIFY) DON’T KNOW. 98 316 In what month and year was the sterilization performed? MONTH. YEAR. 332 316A In what month and year did you start using (CURRENT METHOD) continuously? MONTH. YEAR. 327 CHECK 311/311A: CIRCLE METHOD CODE: PILL . 03 IUD . 04 INJECTABLES . 05 IMPLANTS . 06 CONDOM. 07 FEMALE CONDOM. 08 DIAPHRAGM . 09 FOAM/JELLY. 10 LACTATIONAL AMEN. METHOD . 11 PERIODIC ABSTINENCE. 12 WITHDRAWAL . 13 OTHER METHOD. 96 329A 328 Where did you obtain (CURRENT METHOD) the last time? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. ___________________________________________ (NAME OF PLACE) PUBLIC SECTOR GOVT. HOSPITAL . 11 GOVT. HEALTH CENTER. 12 FAMILY PLANNING CLINIC. 13 OTHER PUBLIC ___________________16 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC. 21 PHARMACY . 22 PRIVATE DOCTOR . 23 OTHER PRIVATE MEDICAL 26 (SPECIFY) OTHER SOURCE SHOP. 31 FRIEND/RELATIVE. 32 OTHER 96 (SPECIFY) DON’T KNOW. 98 332 272 | Appendix E NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 329 What is the main reason you are not using a method of contraception to delay or avoid pregnancy? NOT MARRIED. 11 FERTIILITY RELATED REASONS NOT HAVING SEX. 21 INFREQUESNT SEX . 22 MENOPOSAL/HYSTERECTOMY . 23 SUBFECUND/INFECUND . 24 POSTPARTUM/BREASTFEEDING . 25 WANTS MORE CHILDREN . 26 OPPOSITION TO USE RESPONDENT OPPOSED . 31 HUSBAND OPPOSED . 32 OTHERS OPPOSED. 33 RELIGIOUS PROHIBITION. 34 LACK OF KNOWLEDGE KNOWS NO METHODS. 41 KNOWS NO SOURCE . 42 METHOD RELATED REASONS HEALTH CONCERNS. 51 FEAR OF SIDE EFFECTS . 52 LACK OF ACCESS/TOO FAR. 53 COST TOO MUCH. 54 INCONVINIENT TO USE. 55 INTERFEARS WITH BODY'S NORMAL PROCESSES. 56 OTHER _____________________________96 (SPECIFY) DON'T KNOW . 98 329A Do you know of a place where you can obtain a method of family planning? YES. 1 NO. 2 332 330 Where is that? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC,WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. ____________________________________________________ (NAME OF PLACE) Any other place? RECORD ALL PLACES MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL . A GOVT. HEALTH CENTER. B FAMILY PLANNING CLINIC. C OTHER PUBLIC __________________ D (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC. E PHARMACY . F PRIVATE DOCTOR . G OTHER PRIVATE MEDICAL _____________________ H (SPECIFY) OTHER SOURCE SHOP. I FRIEND/RELATIVE. J OTHER ____________________________ X (SPECIFY) 332 In the last 12 months, have you visited a health facility for care of yourself (or your children)? YES. 1 NO. 2 401 333 Did any staff member at the health facility speak to you about family planning methods? YES. 1 NO. 2 Appendix E | 273 SECTION 4A. PREGNANCY, POSTNATAL CARE AND BREASTFEEDING 401 CHECK 224: ONE OR MORE NO BIRTH IN BIRTHS IN 1997 1997 OR LATER OR LATER 483A 402 ENTER IN THE TABLE THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH BIRTH IN 1997 OR LATER. ASK THE QUESTIONS ABOUT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH. (IF THERE ARE MORE THAN 2 BIRTHS, USE LAST COLUMN OF ADDITIONAL QUESTIONNAIRES). Now I would like to ask you some questions about the health of all your children born in the last five years. (We will talk about each separately) 403 LINE NUMBER FROM 212 LAST BIRTH LINE NUMBER . NEXT-TO-LAST BIRTH LINE NUMBER . 404 NAME FROM 212 AND SURVIVAL STATUS FROM 216 NAME ______________________ ALIVE DEAD NAME _____________________ ALIVE DEAD 405 At the time you became pregnant with (NAME), did you want to become pregnant then, did you want to wait until later, or did you not want to have any (more) children at all? THEN. 1 (SKIP TO 406A) LATER. 2 NOT AT ALL . 3 (SKIP TO 406A) THEN . 1 (SKIP TO 423) LATER. 2 NOT AT ALL . 3 (SKIP TO 423) 406 How much longer would you like to have waited? MONTHS . 1 YEARS . 2 DON’T KNOW . 998 MONTHS. 1 YEARS. 2 DON’T KNOW. 998 406A When you were pregnant with (NAME), did you see anyone for antenatal care? YES. 1 NO. 2 (SKIP TO 415) 407 Whom did you see for antenatal care for this pregnancy? Anyone else? PROBE FOR THE TYPE OF PERSON AND RECORD ALL PERSONS SEEN. PUBLIC MEDICAL SECTOR DOCTOR. A NURSE/MIDWIFE . B AUXILIARY MIDWIFE . C PRIVATE MEDICAL SECTOR DOCTOR. D NURSE/MIDWIFE . E AUXILIARY MIDWIFE . F OTHER PERSON TRADITIONAL BIRTH ATTENDANT . G OTHER _______________________ X (SPECIFY) 408 How many months pregnant were you when you first received antenatal care for this pregnancy? MONTHS . DON’T KNOW . 98 409 How many times did you receive antenatal care during this pregnancy? NO. OF TIMES . DON’T KNOW . 98 410 CHECK 409: NUMBER OF TIMES RECEIVED ANTENATAL CARE ONCE (SKIP TO 412) MORE THAN ONCE OR DON’T KNOW 274 | Appendix E LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 411 How many months pregnant were you the last time you received antenatal care? MONTHS. DON’T KNOW. 98 412 During this pregnancy, were any of the following done at least once? Were you weighed? Was your height measured? Was your blood pressure measured? Did you give a urine sample? Did you give a blood sample? YES NO WEIGHT. 1 2 HEIGHT. 1 2 BLOOD PRESSURE. 1 2 URINE SAMPLE . 1 2 BLOOD SAMPLE. 1 2 413 Were you told about the signs of pregnancy complications? YES . 1 NO. 2 (SKIP TO 415) DON’T KNOW. 8 414 Were you told where to go if you had these complications? YES . 1 NO. 2 DON’T KNOW. 8 415 During this pregnancy, were you given an injection in the arm to prevent the baby from getting tetanus, that is, convulsions after birth? YES . 1 NO. 2 (SKIP TO 417) DON’T KNOW. 8 416 During this pregnancy, how many times did you get this injection? TIMES. DON'T KNOW . 8 417 During this pregnancy, did you receive iron tablets? SHOW TABLETS YES . 1 NO. 2 (SKIP TO 418A) DON’T KNOW. 8 418 During the whole pregnancy, for how many days did you take the tablets? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER OF DAYS. NUMBER OF DAYS. DON'T KNOW . 998 418A During this pregnancy, did you receive multiple vitamin tablets or syrup? SHOW TABLET AND SYRUP YES . 1 NO. 2 DON’T KNOW. 8 418B During this pregnancy, did you receive vitamin C tablets like this? SHOW TABLETS YES . 1 NO. 2 DON’T KNOW. 8 419 During this pregnancy did you have difficulty with your vision during the daylight? YES . 1 NO. 2 DON’T KNOW. 8 420 During this pregnancy, did you suffer from night blindness? YES . 1 NO. 2 DON’T KNOW. 8 421 During this pregnancy, did you take any drugs in order to prevent you from getting malaria? YES . 1 NO. 2 (SKIP TO 423) DON’T KNOW. 8 Appendix E | 275 LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 422 Which drugs did you take to prevent malaria? RECORD ALL MENTIONED IF TYPE OF DRUG IS NOT DETERMINED, SHOW ANTIMALARIAL DRUGS TO RESPONDENT FOR EACH DRUG CIRCLED, ASK: How many times did you take (NAME OF DRUG) during this pregnancy? TIMES CHLOROQUINE. A FANSIDAR. B OTHER_______________ X (SPECIFY) DON’T KNOW. Z 422A CHECK 406A: SEE ANYONE FOR ANTENATAL CARE DURING THIS PREGNANCY? ANY ONE NO ONE (SKIP TO 423) 422B Did you get these drugs during an antenatal visit, another visit to health facility or from some other source? ANTENATAL VISIT . 1 ANOTHER FACILITY VISITS. 2 OTHER SOURCE ________________ 6 (SPECIFY ) 423 When (NAME) was born, was he/she very large, larger than average, average, smaller than average, or very small? VERY LARGE . 1 LARGER THAN AVERAGE . 2 AVERAGE . 3 SMALLER THAN AVERAGE . 4 VERY SMALL . 5 DON’T KNOW. 8 VERY LARGE . 1 LARGER THAN AVERAGE. 2 AVERAGE . 3 SMALLER THAN AVERAGE . 4 VERY SMALL. 5 DON’T KNOW . 8 424 Was (NAME) weighed at birth? YES . 1 NO. 2 (SKIP TO 426) DON’T KNOW. 8 YES. 1 NO. 2 (SKIP TO 426) DON’T KNOW . 8 425 How much did (NAME) weigh? RECORD WEIGHT FROM HEALTH CARD, IF AVAILABLE. GRAMS FROM CARD . 1 GRAMS FROM RECALL. 2 DON’T KNOW. 99998 GRAMS FROM CARD . 1 GRAMS FROM RECALL. 2 DON’T KNOW . 99998 426 Who assisted with the delivery of (NAME)? Anyone else? PROBE FOR THE TYPE OF PERSON AND RECORD ALL PERSONS ASSISTING. IF RESPONDENT SAYS NO ONE ASSISTED, PROBE TO DETERMINE WHETHER ANY ADULTS WERE PRESENT AT THE DELIVERY PUBLIC MEDICAL SECTOR DOCTOR. A NURSE/MIDWIFE . B AUXILIARY MIDWIFE . C PRIVATE MEDICAL SECTOR DOCTOR. D NURSE/MIDWIFE . E AUXILIARY MIDWIFE. F OTHER PERSON TRADITIONAL BIRTH ATTENDANT. G RELATIVE/FRIEND . H OTHER________________________ X (SPECIFY) NO ONE. Y PUBLIC MEDICAL SECTOR DOCTOR. A NURSE/MIDWIFE . B AUXILIARY MIDWIFE . C PRIVATE MEDICAL SECTOR DOCTOR. D NURSE/MIDWIFE . E AUXILIARY MIDWIFE. F OTHER PERSON TRADITIONAL BIRTH ATTENDANT . G RELATIVE/FRIEND . H OTHER ______________________ X (SPECIFY) NO ONE . Y 276 | Appendix E LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 426A At the time of the birth of (NAME), did you have any of the following problems: Long labor, that is , did your regular contractions last more than 12 hours? Excessive bleeding that was so much that you feared it was life threatening? A high fever with bad smelling vaginal discharge? Convulsions not caused by fever? YES NO LABOR MORE THAN12 HOURS. 1 2 EXCESSIVE BLEEDING. 1 2 FEVER/BAD SMELLING VAG. DISCHARGE. 1 2 CONVULSIONS . 1 2 YES NO LABOR MORE THAN12 HOURS. 1 2 EXCESSIVE BLEEDING. 1 2 FEVER/BAD SMELLING VAG. DISCHARGE. 1 2 CONVULSIONS . 1 2 427 Where did you give birth to (NAME)? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) HOME YOUR HOME . 11 (SKIP TO 429) OTHER HOME . 12 PUBLIC SECTOR GOVT.HOSPITAL . 21 GOVT. HEALTH CENTER. 22 GOVT. HEALTH STATION . 23 OTHER PUBLIC _____________26 (SPECIFY) PRIVATE MEDICAL SECTOR PVT.HOSPITAL/CLINIC . 31 OTHER PRIVATE MEDICAL ____________________________ 36 (SPECIFY) OTHER_______________________ 96 (SPECIFY) (SKIP TO 429) HOME YOUR HOME . 11 (SKIP TO 429) OTHER HOME . 12 PUBLIC SECTOR GOVT.HOSPITAL. 21 GOVT. HEALTH CENTER. 22 GOVT. HEALTH STATION . 23 OTHER PUBLIC _____________26 (SPECIFY) PRIVATE MEDICAL SECTOR PVT.HOSPITAL/CLINIC. 31 OTHER PRIVATE MEDICAL ____________________________ 36 (SPECIFY) OTHER ______________________ 96 (SPECIFY) (SKIP TO 429) 428 Was (NAME) delivered by caesarian section? YES . 1 (SKIP TO 433) NO. 2 YES. 1 (SKIP TO 435) NO. 2 429 After (NAME) was born, did a health professional or a traditional birth attendant check on your health? YES . 1 NO. 2 (SKIP TO 433) YES. 1 NO. 2 430 How many days or weeks after delivery did the first check take place? RECORD ‘00' DAYS IF SAME DAY. DAYS AFTER DEL . 1 WEEKS AFTER DEL . 2 DON’T KNOW. 998 431 Who checked on your health at that time? PROBE FOR MOST QUALIFIED PERSON. PUBLIC MEDICAL SECTOR DOCTOR. 11 NURSE/MIDWIFE . 12 AUXILIARY MIDWIFE .13 PRIVATE MEDICAL SECTOR DOCTOR.21 NURSE/MIDWIFE .22 AUXILIARY MIDWIFE.23 OTHER PERSON TRADITIONAL BIRTH ATTENDANT. 31 OTHER_______________________ 96 (SPECIFY) Appendix E | 277 LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 432 Where did this first check take place? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) HOME YOUR HOME. 11 OTHER HOME. 12 PUBLIC SECTOR GOVT. HOSPITAL . 21 GOVT. HEALTH CENTER. 22 GOVT. HEALTH STATION . 23 OTHER PUBLIC______________ 26 (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . 31 OTHER PVT. MEDICAL _________________ 36 (SPECIFY) OTHER________________________ 96 (SPECIFY) 433 In the first two months after delivery, did you receive a vitamin A dose like this? SHOW AMPULE, CAPSULE, AND SYRUP. YES . 1 NO. 2 434 Has your period returned since the birth of (NAME)? YES . 1 (SKIP TO 436) NO. 2 (SKIP TO 437) 435 Did your period return between the birth of (NAME) and your next pregnancy? YES. 1 NO. 2 (SKIP TO 439) 436 For how many months after the birth of (NAME) did you not have a period? MONTHS. DON’T KNOW. 98 MONTHS. DON’T KNOW . 98 437 CHECK 226: IS RESPONDENT PREGNANT? NOT PREGNANT PREG- OR UNSURE NANT (SKIP TO 439) 438 Have you resumed sexual relations since the birth of (NAME)? YES . 1 NO. 2 (SKIP TO 440) 439 For how many months after the birth of (NAME) did you not have sexual relations? MONTHS. DON’T KNOW. 98 MONTHS. DON’T KNOW . 98 440 Did you ever breastfeed (NAME)? YES . 1 NO. 2 (SKIP TO 447) YES. 1 NO. 2 (SKIP TO 447) 278 | Appendix E LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 441 How long after birth did you first put (NAME) to the breast? IF LESS THAN 1 HOUR, RECORD ‘00' HOURS. IF LESS THAN 24 HOURS, RECORD HOURS. OTHERWISE, RECORD DAYS. IMMEDIATELY . 000 HOURS. 1 DAYS. 2 IMMEDIATELY . 000 HOURS. 1 DAYS . 2 442 In the first three days after delivery, was (NAME) given anything to drink other than breast milk? YES. 1 NO. 2 (SKIP TO 444) YES. 1 NO. 2 (SKIP TO 444) 443 What was (NAME) given to drink ? Anything else? RECORD ALL LIQUIDS MENTIONED. FRESH MILK (OTHER THAN BREAST MILK). A TINNED /POWDERED MILK . B PLAIN WATER. C SUGAR OR GLUCOSE WATER. D GRIPE WATER. E SUGAR-SALT-WATER SOLUTION. F FRUIT JUICE . G INFANT FORMULA . H TEA/INFUSIONS/ABAKE OR KERKEDE . I HONEY. J BUTTER . K OTHER_________________________ X (SPECIFY) FRESH MILK (OTHER THAN BREAST MILK). A TINNED /POWDERED MILK. B PLAIN WATER . C SUGAR OR GLUCOSE WATER . D GRIPE WATER. E SUGAR-SALT-WATER SOLUTION . F FRUIT JUICE. G INFANT FORMULA . H TEA/INFUSIONS/ABAKE OR KERKEDE . I HONEY. J BUTTER. K OTHER________________________ X (SPECIFY) 444 CHECK 404: CHILD ALIVE? ALIVE DEAD (SKIP TO 446) ALIVE DEAD (SKIP TO 446) 445 Are you still breastfeeding (NAME)? YES. 1 (SKIP TO 448) NO. 2 YES. 1 (SKIP TO 448) NO. 2 446 For how many months did you breastfeed (NAME)? MONTHS. DON’T KNOW.98 MONTHS . DON’T KNOW . 98 446A Why did you stop breastfeeding (NAME)? MOTHER ILL/ WEAK . 01 CHILD ILL/ WEAK. 02 CHILD DIED. 03 NIPPLE/BREAST PROBLEM . 04 NOT ENOUGH MILK . 05 MOTHER WORKING . 06 CHILD REFUSED . 07 WEANING AGE/ AGE TO STOP . 08 BECAME PREGNANT . 09 STARTED USING CONTRACEPTION. 10 OTHER ______________________ 96 (SPECIFY) MOTHER ILL/ WEAK. 01 CHILD ILL/ WEAK. 02 CHILD DIED. 03 NIPPLE/BREAST PROBLEM . 04 NOT ENOUGH MILK. 05 MOTHER WORKING. 06 CHILD REFUSED . 07 WEANING AGE/ AGE TO STOP . 08 BECAME PREGNANT . 09 STARTED USING CONTRACEPTION. 10 OTHER _____________________ 96 (SPECIFY) Appendix E | 279 LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 447 CHECK 404: CHILD ALIVE? ALIVE (SKIP TO 450) DEAD (GO BACK TO 403/404 IN NEXT COLUMN OR, IF NO MORE BIRTHS, GO TO 452) ALIVE (SKIP TO 450) DEAD (GO BACK TO 403/404 IN LAST COLUMN OF NEW QUESTION- NAIRE; OR, IF NO MORE BIRTHS, GO TO 452) 448 How many times did you breastfeed last night between sunset and sunrise? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. NUMBER OF NIGHT TIME FEEDINGS. NUMBER OF NIGHT TIME FEEDINGS. 449 How many times did you breastfeed yesterday during the daylight hours? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. NUMBER OF DAYLIGHT FEEDINGS . NUMBER OF DAYLIGHT FEEDINGS . 450 Did (NAME) drink anything from a bottle with a nipple yesterday or last night? YES. 1 NO. 2 DON’T KNOW. 8 YES. 1 NO. 2 DON’T KNOW . 8 451 Was sugar added to any of the foods or liquids (NAME) ate yesterday? YES. 1 NO. 2 DON’T KNOW. 8 YES. 1 NO. 2 DON’T KNOW . 8 451A (Aside from breastfeeding and other liquids), how many times did (NAME) eat solid, semi- solid or soft foods yesterday or at night, including both meals and snacks? IF 7 OR MORE TIMES, RECORD ‘7’. NUMBER OF TIMES . DON’T KNOW. 8 NUMBER OF TIMES . DON’T KNOW . 8 451B GO BACK TO 403/404 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 452. GO BACK TO 403/404 IN LAST COLUMN OF NEW QUESTIONNAIRE; OR, IF NO MORE BIRTHS, GO TO 452. 280 | Appendix E NO. QUESTIONS AND FILTERS SKIP CHECK 215 AND 218 HAS AT LEAST ONE CHILD BORN IN 1999 OR LATER AND LIVING WITH HER DOES NOT HAVE ANY CHILDREN BORN IN 1999 OR LATER AND LIVING WITH HER 452 RECORD NAME OF YOUNGEST CHILD LIVING WITH HER (AND CONTINUE WITH 452A) __________________________________ (NAME) 454 452A Now I would like to ask you about liquids (NAME FROM Q452) drank over the last seven days, including yesterday. How many days during the last 7 days did (NAME FROM Q452) drink each of the following? FOR EACH ITEM GIVEN AT LEAST ONCE IN LAST SEVEN DAYS, BEFORE PROCEEDING TO THE NEXT ITEM, ASK: In total, how many times yesterday during the day or at night did (NAME FROM Q452) drink (ITEM)? LAST 7 DAYS NUMBER OF DAYS YESTERDAY/ LAST NIGHT NUMBER OF TIMES a b c d e f g h Plain water? Sugar water? Fruit juice? Tea, kerkede,abake, coffee, soft drinks? Baby formula? Tinned or powdered milk? Fresh milk? Any other liquids? FOR EACH ITEM NOT GIVEN IN THE LAST SEVEN DAYS RECORD ‘0’ IN THE CORROSPO NDING NUMBER OF DAYS BOX AND LEAVE THE NUMBER OF TIMES BOX BLANK. IF 7 OR MORE TIMES, RECORD '7'. IF DON'T KNOW RECORD '8'. a b c d e f g h a b c d e f g h 452B Now I would like to ask you about type of foods (NAME FROM Q452) ate over the last seven days, including yesterday. How many days during the last 7 days did (NAME FROM Q452) eat each of the following foods either separately or combined with other food? FOR EACH ITEM GIVEN AT LEAST ONCE IN LAST SEVEN DAYS, BEFORE PROCEEDING TO THE NEXT ITEM, ASK: In total, how many times yesterday during the day or at night did (NAME FROM Q452) eat (ITEM)? LAST 7 DAYS NUMBER OF DAYS YESTERDAY/ LAST NIGHT NUMBER OF TIMES a b c d e f g h i j k l Any green leafy vegetables? Mangos and Papayas? Any other fruits such as orange, bananas, apples/sauce, avocados, tomatoes? Pumpkin, red or yellow yams or squash, carrots, or red sweet potatoes? Injera Any food made from grains such as gaat, sebko, ajja, biscuits etc.? Any other food made from roots or tubers such as white potatoes, white yams, manioc, cassava, or other local roots or tubers? Any food made from legumes such as lentils, beans, soyabeans, pulses, or peanuts? Cheese or yoghurt? Meat, poultry, fish or Eggs? Any food made with oil, fat, or butter? Any other solid or semi-solid foods? FOR EACH ITEM NOT GIVEN IN THE LAST SEVEN DAYS RECORD ‘0’ IN THE CORROSPO NDING NUMBER OF DAYS BOX AND LEAVE THE NUMBER OF TIMES BOX BLANK. IF 7 OR MORE TIMES, RECORD '7'. IF DON'T KNOW RECORD '8'. a b c d e f g h i j k l a b c d e f g h i j k l Appendix E | 281 SECTION 4B. IMMUNIZATION, HEALTH AND NUTRITION 454 ENTER IN THE TABLE THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH BIRTH IN 1997 OR LATER. ASK THE QUESTIONS ABOUT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH (IF THERE ARE MORE THAN 2 BIRTHS, USE LAST COLUMN OF ADDITIONAL QUESTIONNAIRES). 455 LINE NUMBER FROM 212 LAST BIRTH LINE NUMBER. NEXT-TO-LAST BIRTH LINE NUMBER . 456 NAME FROM 212 AND ALIVE OR DEAD FROM 216 NAME ______________________ NAME __________________________ ALIVE DEAD (GO TO 456 IN NEXT COLUMN OR, IF NO MORE BIRTHS, GO TO 483A) ALIVE DEAD (GO TO 456 IN LAST COLUMN OF NEW QUESTION- NAIRE; OR, IF NO MORE BIRTHS, GO TO 483A) 457 Did (NAME) receive a vitamin A dose like this during the last 6 months? SHOW AMPULE, CAPSULE AND SYRUP. YES. 1 NO . 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 458 Do you have a card where (NAME’S) vaccinations are written down? IF YES: May I see it please? YES, SEEN. 1 (SKIP TO 460) YES, NOT SEEN . 2 (SKIP TO 462) NO CARD . 3 YES, SEEN . 1 (SKIP TO 460) YES, NOT SEEN. 2 (SKIP TO 462) NO CARD. 3 459 Did you ever have a vaccination card for (NAME)? YES. 1 (SKIP TO 462) NO . 2 YES . 1 (SKIP TO 462) NO. 2 460 (1) COPY VACCINATION DATE FOR EACH VACCINE FROM THE CARD. (2) WRITE ‘44' IN ‘DAY’ COLUMN IF CARD SHOWS THAT A VACCINATION WAS GIVEN, BUT NO DATE IS RECORDED. VACCINE DAY MONTH YEAR VACCINE DAY MONTH YEAR BCG BCG BCG POLIO 0 (POLIO GIVEN AT BIRTH) POLIO 0 POLIO 0 POLIO 1 POLIO 1 POLIO 1 POLIO 2 POLIO 2 POLIO 2 POLIO 3 POLIO 3 POLIO 3 DPT 1 DPT 1 DPT 1 DPT 2 DPT 2 DPT 2 DPT 3 DPT 3 DPT 3 MEASLES MEASLES MEASLES 282 | Appendix E LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 460A CHECK 460: CHILD RECEIVED ALL VACCINATIONS NO YES (SKIP TO 464) NO YES (SKIP TO 464) 461 Has (NAME) received any vaccinations that are not recorded on this card? RECORD ‘YES’ ONLY IF RESPONDENT MENTIONS BCG, POLIO 0-3, DPT 1-3, AND/OR MEASLES VACCINE (S). YES. 1 (PROBE FOR VACCINATIONS AND WRITE ‘66' IN THE CORRESPONDING DAY COLUMN IN 460) (SKIP TO 464) NO. 2 DON’T KNOW . 8 YES . 1 (PROBE FOR VACCINATIONS AND WRITE ‘66' IN THE CORRESPONDING DAY COLUMN IN 460) (SKIP TO 464) NO. 2 DON’T KNOW. 8 462 Did (NAME) ever receive any vaccinations to prevent him/her from getting diseases, including vaccinations received in a national immunization day campaign? YES. 1 NO. 2 (SKIP TO 465A) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 465A) DON’T KNOW. 8 463 Please tell me if (name) received any of the following vaccinations: 463A A BCG vaccination against tuberculosis that is, an injection in the arm or shoulders that usually causes a scar? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 463B Polio vaccine, that is, drops in the mouth? YES. 1 NO. 2 (SKIP TO 463E) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 463E) DON’T KNOW. 8 463C When was the first polio vaccine received, just after birth or later? JUST AFTER BIRTH . 1 LATER . 2 JUST AFTER BIRTH. 1 LATER. 2 463D How many times was the polio vaccine received? NUMBER OF TIMES. NUMBER OF TIMES . 463E A DPT vaccination, that is, an injection given in the thigh or buttocks, sometimes at the same time as polio drops? YES. 1 NO. 2 (SKIP TO 463G) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 463G) DON’T KNOW. 8 463F How many times was the DPT received? NUMBER OF TIMES. NUMBER OF TIMES . 463G An injection to prevent measles? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 464 Were any of the vaccinations (NAME) received during the last two years given as a part of a national immunization day campaign? YES. 1 NO. 2 (SKIP TO 465A) NO VACCINATION IN THE LAST 2 YEARS . 3 (SKIP TO 465A) DON’T KNOW . 8 (SKIP TO 465A) YES . 1 NO. 2 (SKIP TO 465A) NO VACCINATION IN THE LAST 2 YEARS. 3 (SKIP TO 465A) DON’T KNOW. 8 (SKIP TO 465A) 465 At which national immunization day campaigns did (NAME) receive vaccinations? RECORD ALL CAMPAIGNS MENTIONED POLIO VACCINATION COMPAIGN 2000. A POLIO VACCINATION COMPAIGN 2001. B POLIO VACCINATION COMPAIGN 2002. C POLIO VACCINATION COMPAGIN 2000 . A POLIO VACCINATION COMPAGIN 2001 . B POLIO VACCINATION COMPAIGN 2002 . C Appendix E | 283 LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 465A CHECK 27 IN THE HOUSEHOLD QUESTIONNAIRE BED NETS IN THE HOUSEHOLD? YES NO (SKIP TO 466) YES NO (SKIP TO 466) 465B Does (NAME) usually sleep under a mosquito net? YES. 1 NO. 2 YES . 1 NO. 2 465C Did (NAME) sleep under a mosquito net last night? YES. 1 (SKIP TO 465E) NO. 2 DON’T KNOW . 8 YES . 1 (SKIP TO 465E) NO. 2 DON’T KNOW. 8 465D CHECK 465B: SLEEPS UNDER A MOSQUITO NET? YES NO (SKIP TO 466) YES NO (SKIP TO 466) 465E Now let us talk about the mosquito net (NAME) sleeps under. How long ago was the mosquito net bought or obtained? IF LESS THAN ONE MONTH, RECORD ‘00’. IF MORE THAN 95 MONTHS, RECORD ‘95’. MONTHS . DON’T KNOW . 98 MONTHS. DON’T KNOW. 98 465F Since you got the mosquito net, was it ever soaked or dipped in a liquid to repel mosquitoes or bugs? YES. 1 NO. 2 (SKIP TO 466) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 466) DON’T KNOW. 8 465G How long ago was the mosquito net last soaked or dipped? IF LESS THAN 1 MONTH, RECORD ‘00’. IF MORE THAN 95 MONTHS, RECORD ‘95’. MONTHS . DON’T KNOW . 98 MONTHS. DON’T KNOW. 98 466 Has (NAME) been ill with a fever at any time in the last 2 weeks? YES. 1 NO. 2 (SKIP TO 467) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 467) DON’T KNOW. 8 466A Does (NAME) have a fever now? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 466B Was (NAME) given drugs for the fever? YES. 1 NO. 2 (SKIP TO 467) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 467) DON’T KNOW. 8 284 | Appendix E LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 466C What drugs did (NAME) take? RECORD ALL MENTIONED ASK TO SEE DRUG(S) IF TYPE OF DRUG IS NOT KNOWN. IF TYPE OF DRUGS IS STILL NOT DETREMINED, SHOW TYPICAL ANTI-MALARIAL DRUGS TO RESPONDENT. FOR EACH ANTI-MALARIAL DRUGS TAKEN ASK: For how many days (NAME) take (NAME OF THE DRUGS)? ANTI-MALARIAL DAYS CHLOROQUINE. A FANSIDAR. B QUININE . C OTHER DRUGS ASPRIN. E PANADOL . F OTHER X (SPECIFY) DON’T KNOW . Z ANTI-MALARIAL DAYS CHLOROQUINE . A FANSIDAR . B QUININE. C OTHER DRUGS ASPRIN . E PANADOL . F OTHER X (SPECIFY) DON’T KNOW. Z 466D CHECK 466C: ANTI-MALARIAL DRUG GIVEN? CODE A, B, CODES A, B OR C CIRCLED AND C NOT CIRCLED (SKIP TO 467) CODE A, B, CODES A, B OR C CIRCLED AND C NOT CIRCLED (SKIP TO 467) 466E How long after the fever started did (NAME) first take (NAMES OF THE ANTI-MALARIAL DRUGS CIRCLED IN 466C)? SAME DAY . 0 NEXT DAY. 1 TWO DAYS AFTER THE FEVER. 2 THREE OR MORE DAYS AFTER THE FEVER. 3 DON’T KNOW . 8 SAME DAY. 0 NEXT DAY . 1 TWO DAYS AFTER THE FEVER. 2 THREE OR MORE DAYS AFTER THE FEVER . 3 DON’T KNOW. 8 466F Is the child still taking (NAMES OF THE ANTI- MALARIAL DRUGS CIRCLED IN 466C)? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 467 Has (NAME) had an illness with a cough at any time in the last 2 weeks? YES. 1 NO. 2 (SKIP TO 475) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 475) DON’T KNOW. 8 468 When (NAME) had an illness with a cough, did he/she breathe faster than usual with short, rapid breaths? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 470 Did you seek advice or treatment for the cough? YES. 1 NO . 2 (SKIP TO 475) YES. 1 NO. 2 (SKIP TO 475) Appendix E | 285 LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 471 Where did you seek advice or treatment for the cough? Anywhere else? RECORD ALL SOURCES MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL. A GOVT. HEALTH CENTER. B GOVT. HEALTH STATION . C OTHER PUBLIC ______________ F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . G PHARMACY. H PVT. DOCTOR. I COMM. HEALTH WORKER . K OTHER PVT. MEDICAL _________________ L (SPECIFY) OTHER SOURCE SHOP . M TRAD. PRACTITIONER. N OTHER X (SPECIFY) PUBLIC SECTOR GOVT. HOSPITAL . A GOVT. HEALTH CENTER . B GOVT. HEALTH STATION . C OTHER PUBLIC _____________ F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC. G PHARMACY . H PVT. DOCTOR. I COMM. HEALTH WORKER. K OTHER PVT. MEDICAL _________________ L (SPECIFY) OTHER SOURCE SHOP. M TRAD. PRACTITIONER . N OTHER X (SPECIFY) 475 Has (NAME) had diarrhea in the last 2 weeks? YES. 1 NO. 2 (SKIP TO 483) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 483) DON’T KNOW. 8 475A Was there any blood in the stools? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 476 Now I would like to now haw much (NAME) was offered to drink during the diarrhea. Was he\she offered less then usual to drink, about the same amount, more than usual to drink? LESS. 1 ABOUT SAME . 2 MORE. 3 NOTHING TO DRINK. 4 DON’T KNOW . 8 LESS . 1 ABOUT SAME. 2 MORE . 3 NOTHING TO DRINK . 4 DON’T KNOW. 8 477 When name had diarrhea, was he\she offered less then usual to eat, about the same amount, more than usual to eat? LESS. 1 ABOUT SAME . 2 MORE. 3 STOPED TO EAT. 4 NOTHING TO EAT. 5 DON’T KNOW . 8 LESS . 1 ABOUT SAME. 2 MORE . 3 STOPED TO EAT . 4 NOTHING TO EAT . 5 DON’T KNOW. 8 478 Was (NAME) given a fluid made from a special packet called ORS to drink? SHOW ORS PACKET YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 478A Was (NAME) given a government- recommended homemade fluid? YES. 1 NO. 2 DON’T KNOW . 8 YES . 1 NO. 2 DON’T KNOW. 8 479 Was anything (else) given to treat the diarrhea? YES. 1 NO. 2 (SKIP TO 481) DON’T KNOW . 8 YES . 1 NO. 2 (SKIP TO 481) DON’T KNOW. 8 286 | Appendix E LAST BIRTH NAME __________________________ NEXT-TO-LAST BIRTH NAME __________________________ 480 What was given to treat the diarrhea? Anything else? RECORD ALL MENTIONED. HOME MADE LIQUIDS. A PILL OR SYRUP . B INJECTION. C (I.V.) INTRAVENOUS. D HOME REMEDIES/ HERBAL MEDICINES. E OTHER _______________________ X (SPECIFY) HOME MADE LIQUIDS. A PILL OR SYRUP. B INJECTION . C (I.V.) INTRAVENOUS . D HOME REMEDIES/ HERBAL MEDICINES . E OTHER _______________________ X (SPECIFY) 481 Did you seek advice or treatment for the diarrhea? YES. 1 NO . 2 (SKIP TO 483) YES. 1 NO. 2 (SKIP TO 483) 482 Where did you seek advice or treatment for diarrhea? IF SOURCE IS HOSPITAL, HEALTH CENYTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE _____________________________ (NAME OF PLACE) Anywhere else? RECORD ALL SOURCES MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL. A GOVT. HEALTH CENTER. B GOVT. HEALTH STATION . C OTHER PUBLIC ______________ F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . G PHARMACY. H PVT. DOCTOR. I COMM. HEALTH WORKER . K OTHER PVT. MEDICAL _________________ L (SPECIFY) OTHER SOURCE SHOP . M TRAD. PRACTITIONER. N OTHER ________________________ X (SPECIFY) PUBLIC SECTOR GOVT. HOSPITAL . A GOVT. HEALTH CENTER . B GOVT. HEALTH STATION . C OTHER PUBLIC _____________ F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC. G PHARMACY .