Moldova - Demographic and Health Survey - 2006

Publication date: 2006

REPUBLIC OF MOLDOVA Moldova Demographic and Health Survey 2005 National Scientific and Applied Center for Preventive Medicine Ministry of Health and Social Protection Chisinau, Moldova ORC Macro Calverton, Maryland, USA September 2006 This report summarizes the findings of the 2005 Moldova Demographic and Health Survey (MDHS 2005), which was conducted by the National Scientific and Applied Center for Preventive Medicine (NCPM) of the Ministry of Health and Social Protection (MOHSP). Funding for the project was provided by the United States Agency for International Development (USAID) through the worldwide MEASURE DHS project (Contract No. GPO-C-00-03- 00002-00). Additional funding for the MDHS was provided by the United Nations Children’s Fund (UNICEF) and the United Nations Population Fund (UNFPA). ORC Macro provided technical assistance. The opinions expressed herein are those of the authors and do not necessarily reflect the views of USAID or the Government of Moldova. Additional information about the 2005 MDHS may be obtained from the National Scientific and Applied Center for Preventive Medicine of the Ministry of Health and Social Protection, 67 A str. Gh. Asachi, 2028 Chisinau, Republic of Moldova (Telephone: 373 22 57 46 74 or 373 22 72 96 47; Fax: 373 22 72 97 25). Additional information about the MEASURE DHS project may be obtained from ORC Macro, MEASURE DHS, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705 USA; Telephone: 301-572-0200, Fax: 301-572-0999, E- mail: reports@orcmacro.com, Internet: http://www.measuredhs.com. Recommended citation: National Scientific and Applied Center for Preventive Medicine (NCPM) [Moldova] and ORC Macro. 2006. Moldova Demographic and Health Survey 2005. Calverton, Maryland: National Scientific and Applied Center for Preventive Medicine of the Ministry of Health and Social Protection and ORC Macro. Contents | iii CONTENTS TABLES AND FIGURES . vii PREFACE. xv SUMMARY OF FINDINGS . xvii MILLENNIUM DEVELOPMENT GOAL INDICATORS . xxv MAP OF MOLDOVA. xxvi CHAPTER 1 INTRODUCTION 1.1 Geography And Population .1 1.2 History .1 1.3 Economy.3 1.4 Characteristics of the Health System.4 1.4.1 Facilities and Human Resources .4 1.4.2 Reforms of the Health System of the Republic of Moldova .5 1.4.3 Specific Health Care Services .6 1.5 Health Information System.10 1.6 Objectives and Organization of the Survey.10 1.6.1 Sample Design and Implementation .11 1.6.2 Questionnaires .11 1.6.3 Field Staff and Fieldwork .13 1.6.4 Data Processing.14 1.6.5 Response Rates .14 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2.1 Household Population by Age and Sex.16 2.2 Household Composition .17 2.3 Children’s Living Arrangements .18 2.4 Educational Attainment of Household Members.20 2.5 Housing Characteristics .23 2.6 Household Durable Goods .24 CHAPTER 3 CHARACTERISTICS OF SURVEY RESPONDENTS 3.1 Background Characteristics of Respondents.27 3.2 Educational Level of Respondents .29 3.3 Exposure to Mass Media .30 3.3.1 Language Preferences for Print Media .32 3.4 Employment .34 3.4.1 Employment Status.34 3.4.2 Occupation.36 iv Ň Contents 3.4.3 Use of Earnings.39 3.5 Women’s Empowerment .41 3.5.1 Women’s Participation in Decisionmaking .41 3.5.2 Women’s and Men’s Attitudes toward Wife Beating.43 3.5.3 Women’s and Men’s Attitudes toward Wife Refusing Sex with Husband .46 CHAPTER 4 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 4.1 Introduction.49 4.2 Current Fertility Levels .50 4.3 Fertility Differentials by Background Characteristics.51 4.4 Fertility Trends .52 4.5 Children Ever Born and Living.53 4.6 Birth Intervals.54 4.7 Age at First Birth.56 4.8 Teenage Pregnancy and Motherhood.57 CHAPTER 5 FAMILY PLANNING 5.1 Knowledge of Contraceptive Methods.59 5.2 Ever Use of Contraception .60 5.3 Current Use of Contraceptive Methods .61 5.4 Trends in Contraceptive Use .63 5.5 Differentials in Contraceptive Use by Background Characteristics.64 5.6 Current Use of Contraceptives by Women’s Status.65 5.7 Timing of First Use of Contraception .66 5.8 Knowledge of the Fertile Period .66 5.9 Source of Contraception .67 5.10 Informed Choice.68 5.11 Contraceptive Discontinuation .69 5.12 Future Use of Contraception .71 5.13 Reasons for Not Intending to Use .72 5.14 Preferred Method for Future Use .73 5.15 Exposure to Family Planning Messages .73 5.16 Attitudes of Respondents Towards Family Planning .75 CHAPTER 6 ABORTION 6.1 Pregnancy Outcomes .77 6.2 Lifetime Experience with Induced Abortion.79 6.3 Rates of Induced Abortion.80 6.4 Trends in Induced Abortion .82 CHAPTER 7 OTHER PROXIMATE DETERMINANTS OF FERTILITY 7.1 Introduction.85 Contents | v 7.2 Marital Status .85 7.3 Age at First Marriage .86 7.4 Age at First Sexual Intercourse.88 7.5 Recent Sexual Activity .90 7.6 Postpartum Amenorrhea, Abstinence, and Insusceptibility.93 7.7 Termination of Exposure to Pregnancy .94 CHAPTER 8 FERTILITY PREFERENCES 8.1 Desire for More Children .95 8.2 Need for Family Planning Services.98 8.3 Wanted and Unwanted Fertility . 100 CHAPTER 9 INFANT AND CHILD MORTALITY 9.1 Definitions and Methodology . 103 9.2 Assessment of Data Quality . 104 9.3 Levels and Trends in Infant and Child Mortality. 105 9.4 Socioeconomic Differentials in Childhood Mortality. 107 9.5 Demographic Differentials in Childhood Mortality . 108 9.6 Perinatal Mortality. 109 CHAPTER 10 MATERNAL AND CHILD HEALTH 10.1 Antenatal Care . 111 10.2 Delivery Care. 122 10.3 Delivery Characteristics . 124 10.4 Postnatal Care. 126 10.5 Woman’s Perception of Access to Health Care. 127 10.6 Immunization Coverage . 129 10.7 Acute Respiratory Infections and Fever. 112 10.8 Diarrhea . 114 CHAPTER 11 NUTRITION 11.1 Breastfeeding and Supplementation . 139 11.2 Iodine Intake and Vitamin A Consumption. 143 11.3 Micronutrient Intake . 146 11.4 Anemia . 148 11.5 Nutritional Status of Children . 152 11.6 Nutritional Status of Women. 156 CHAPTER 12 ADULT HEALTH 12.1 Health Insurance. 159 12.2 Tobacco Use. 160 12.3 Alcohol Consumption . 163 vi Ň Contents 12.4 Tuberculosis. 166 CHAPTER 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR 13.1 Knowledge of HIV Transmission and Prevention Methods . 174 13.2 Stigma and Attitudes Related to HIV/AIDS. 181 13.3 Higher-Risk Sex. 185 13.4 Testing for HIV. 189 13.5 Reports of Recent Sexually Transmitted Infections . 192 13.6 Injections . 193 13.7 HIV/AIDS-Related Knowledge and Behavior among Youth . 195 13.8 Recent Sexual Activity among Young Women and Men . 199 CHAPTER 14 DOMESTIC VIOLENCE 14.1 Introduction. 205 14.2 Data Collection. 205 14.3 Violence Since Age 15 . 207 14.4 Marital Violence. 209 14.5 Onset of Spousal Violence Against Women. 211 14.6 Physical Consequences of Spousal Violence . 212 14.7 Violence by Spousal Characteristics and Women’s Status Indicators . 213 CHAPTER 15 EMIGRATION 15.1 Households Having at Least One Former Member Living Abroad. 217 15.2 Household Characteristics of Emigrants’ Former Households. 219 15.3 Background Characteristics of Emigrants. 220 15.4 Main Reason for Emigrating. 221 15.5 Trends in Emigration: Current Age and Sex of Emigrants . 222 15.6 Destination Countries. 224 15.7 Children of Emigrants. 226 REFERENCES .229 APPENDIX A SAMPLE DESIGN. 235 APPENDIX B ESTIMATES OF SAMPLING ERRORS. 239 APPENDIX C DATA QUALITY TABLES . 249 APPENDIX D PERSONS INVOLVED IN THE 2005 MOLDOVA DEMOGRAPHIC AND HEALTH SURVEY. 253 APPENDIX E QUESTIONNAIRES . 257 Tables and Figures | vii TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.2 Results of the household and individual interviews. 14 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Table 2.1 Household population by age, sex, and residence. 16 Table 2.2 Household composition. 18 Table 2.3 Children’s living arrangements and orphanhood . 19 Table 2.4 Parental residence apart from children. 19 Table 2.5 Educational attainment of household population . 22 Table 2.6 Household characteristics . 23 Table 2.7 Household durable goods . 25 Figure 2.1 Population pyramid . 17 Figure 2.2 Living arrangements of mothers and fathers not living in household interviewed. 20 CHAPTER 3 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 Background characteristics of respondents . 28 Table 3.2.1 Educational attainment by background characteristics: women . 29 Table 3.2.2 Educational attainment by background characteristics: men. 30 Table 3.3.1 Exposure to mass media: women. 31 Table 3.3.2 Exposure to mass media: men. 32 Table 3.4 Language preference for printed media. 33 Table 3.5.1 Employment status: women . 35 Table 3.5.2 Employment status: men. 36 Table 3.6.1 Occupation: women. 37 Table 3.6.2 Occupation: men . 38 Table 3.7 Decision on use of earnings . 40 Table 3.8 Women’s participation in decisionmaking. 41 Table 3.9 Women's participation in decisionmaking by background characteristics. 42 Table 3.10.1 Women’s attitudes toward wife beating . 44 Table 3.10.2 Men’s attitudes toward wife beating. 45 Table 3.11.1 Women’s attitude toward a wife refusing sex with husband . 47 Table 3.11.2 Men’s attitude toward a wife refusing sex with husband. 48 Figure 3.1 Percent distribution of women and men who are currently employed, by occupation. 39 viii | Tables and Figures CHAPTER 4 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS Table 4.1 Current fertility . 50 Table 4.2 Fertility by background characteristics . 52 Table 4.3 Trends in age-specific fertility rates. 53 Table 4.4 Children ever born and mean number of living children . 54 Table 4.5 Birth intervals. 55 Table 4.6 Age at first birth . 56 Table 4.7 Median age at first birth by background characteristics. 57 Table 4.8 Pregnancy and motherhood among teenage women. 58 Figure 4.1 Age-specific fertility rates (ASFR), by region . 50 Figure 4.2 Trends in age-specific fertility rates. 53 CHAPTER 5 FAMILY PLANNING Table 5.1 Knowledge of contraceptive methods . 59 Table 5.2 Ever use of contraception. 61 Table 5.3 Current use of contraception . 62 Table 5.4 Current use of contraception by background characteristics . 64 Table 5.5 Current use of contraception by women's status. 65 Table 5.6 Number of children at first use of contraception . 66 Table 5.7 Knowledge of fertile period. 67 Table 5.8 Source of contraception. 68 Table 5.9 Informed choice . 69 Table 5.10 First-year contraceptive discontinuation rate . 70 Table 5.11 Reasons for discontinuation . 71 Table 5.12 Future use of contraception . 72 Table 5.13 Reason for not intending to use contraception . 72 Table 5.14 Preferred method of contraception for future use. 73 Table 5.15.1 Exposure to family planning messages: women . 74 Table 5.15.2 Exposure to family planning messages: men. 75 Table 5.16 Men’s attitudes toward contraception . 76 Figure 5.1 Contraceptive use among currently married women . 63 CHAPTER 6 ABORTION Table 6.1 Pregnancy outcome by background characteristics. 78 Table 6.2 Lifetime experience with induced abortion . 79 Table 6.3 Induced abortion rates . 80 Table 6.4 Induced abortion by background characteristics. 81 Table 6.5 Abortion trends. 83 Table 6.6 Use of contraception prior to pregnancy . 84 Figure 6.1 Age-specific fertility rtes (ASFR) and age-specific abortion rates (ASAR). 81 Figure 6.2 Total abortion rate by background characteristics. 82 Figure 6.3 Age-specific abortion rates (ASAR) for three-year periods prior to the 2005 MDHS . 83 Tables and Figures | ix CHAPTER 7 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 7.1 Current marital status . 86 Table 7.2 Age at first marriage . 87 Table 7.3 Median age at first marriage. 88 Table 7.4 Age at first sexual intercourse . 89 Table 7.5 Median age at first intercourse . 90 Table 7.6.1 Recent sexual activity: women. 91 Table 7.6.2 Recent sexual activity: men. 92 Table 7.7 Postpartum amenorrhea, abstinence, and insusceptibility. 93 Table 7.8 Menopause. 94 CHAPTER 8 FERTILITY PREFERENCES Table 8.1 Fertility preferences by number of living children . 96 Table 8.2 Desire to limit childbearing . 97 Table 8.3 Need for family planning among currently married women. 99 Table 8.4 Fertility planning status. 100 Figure 8.1 Fertility preferences among currently married women and men age 15-49 . 96 Figure 8.2 Distribution of births in the five years preceding the survey by fertility planning status . 101 CHAPTER 9 INFANT AND CHILD MORTALITY Table 9.1 Early childhood mortality rates . 105 Table 9.2 Regional infant mortality rates that correspond closely with the 5-9-year period prior to the 2005 MDHS. 106 Table 9.3 Early childhood mortality rates by socioeconomic characteristics. 107 Table 9.4 Early childhood mortality rates by demographic characteristics. 108 Table 9.5 Perinatal mortality. 109 Figure 9.1 Early childhood mortality rates for three 5-year periods prior to the 2005 MDHS . 106 CHAPTER 10 MATERNAL AND CHILD HEALTH Table 10.1 Antenatal care. 112 Table 10.2 Number of antenatal care visits and timing of first visit . 113 Table 10.3 Means of transport to last antenatal visit . 114 Table 10.4 Antenatal care education received during antenatal visit . 115 Table 10.5 Components of antenatal care . 117 Table 10.6 Tetanus toxoid injections . 120 Table 10.7 Pregnancy complications . 121 Table 10.8 Place of delivery . 123 Table 10.9 Assistance during delivery . 124 Table 10.10 Delivery characteristics . 125 Table 10.11 Problems in accessing health care . 128 x | Tables and Figures Table 10.12 Vaccinations by source of information. 130 Table 10.13 Vaccinations by background characteristics . 132 Table 10.14 Vaccinations in first 15 months of life. 133 Table 10.15 Prevalence and treatment of symptoms of ARI and fever. 134 Table 10.16 Prevalence of diarrhea . 135 Table 10.17 Knowledge of ORS packets . 136 Table 10.18 Feeding practices during diarrhea . 137 Figure 10.1 Proportion of women encouraged to invite a companion to attend the delivery. 116 Figure 10.2 Proportion of costs covered by the government or by an insurance program for antenatal care. 118 Figure 10.3 Proportion of costs covered by the government or by an insurance program for treatment of pregnancy complication. 122 Figure 10.4 Timeliness of postnatal examinations by a trained provider . 126 Figure 10.5 Percentage of children age 15-26 months vaccinated against childhood diseases at any time preceding the survey . 131 Figure 10.6 Proportion of children age 15-26 months who have received recommended vaccines before their first birthday . 131 Figure 10.7 Amount of food and liquid offered to children under five with diarrhea . 137 CHAPTER 11 NUTRITION Table 11.1 Initial breastfeeding. 140 Table 11.2 Breastfeeding status by child’s age. 141 Table 11.3 Foods consumed by children in the day and night preceding the interview . 142 Table 11.4 Iodization of household salt . 143 Table 11.5 Micronutrient intake among children . 146 Table 11.6 Micronutrient intake among mothers . 147 Table 11.7 Prevalence of anemia in children . 148 Table 11.8 Prevalence of anemia in women . 151 Table 11.9 Prevalence of anemia in children by anemia status of mother . 152 Table 11.10 Nutritional status of children . 155 Table 11.11 Nutritional status of women by background characteristics. 157 Figure 11.1 Type of salt used in daily food preparation, reported versus observed use . 144 Figure 11.2 Type of salt used for pickling. 145 Figure 11.3 Percentage of children with anemia, by severity of anemia and age . 150 CHAPTER 12 ADULT HEALTH Table 12.1 Type of health insurance coverage . 160 Table 12.2.1 Use of tobacco: women. 161 Table 12.2.2 Use of tobacco: men . 162 Table 12.3.1 Use of alcohol: women. 164 Table 12.3.2 Use of alcohol: men. 165 Table 12.4 Drinking more alcohol than usual . 166 Table 12.5 Knowledge of tuberculosis and its transmission modes . 168 Table 12.6.1 Knowledge of symptoms of tuberculosis: women . 169 Tables and Figures | xi Table 12.6.2 Knowledge of symptoms of tuberculosis: men. 170 Table 12.7 Knowledge of treatment of tuberculosis and attitude towards those with TB. 171 Figure 12.1 Percentage of cigarette smokers, by age group and sex . 162 Figure 12.2 Average number of alcoholic beverages consumed by females and males on a typical drinking occasion, by residence. 166 CHAPTER 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR Table 13.1 Knowledge of AIDS. 174 Table 13.2 Knowledge of ways to avoid HIV/AIDS. 175 Table 13.3 Knowledge of HIV prevention methods. 176 Table 13.4.1 Misconceptions and general knowledge about AIDS: women . 178 Table 13.4.2 Misconceptions and general knowledge about AIDS: men . 179 Table 13.5 Knowledge of prevention of mother-to-child transmission of HIV. 180 Table 13.6.1 Accepting attitudes toward those living with HIV: women. 182 Table 13.6.2 Accepting attitudes toward those living with HIV: men . 183 Table 13.7 Attitudes toward negotiating safer sex with husband. 184 Table 13.8 Adult support of education about condom use to prevent AIDS . 185 Table 13.9.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: women . 186 Table 13.9.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: men . 187 Table 13.10 Payment for sexual intercourse: men . 188 Table 13.11.1 Coverage of HIV testing: women . 189 Table 13.11.2 Coverage of HIV testing: men . 190 Table 13.12 Pregnant women who received information and counseling about HIV/AIDS. 191 Table 13.13 Self-reporting of sexually transmitted infections (STI) and STI symptoms. 193 Table 13.14 Prevalence of injections . 194 Table 13.15 General knowledge about AIDS and knowledge of a source of condoms among youth . 196 Table 13.16 Age at first sex among youth . 197 Table 13.17 Condom use at first sexual intercourse among youth. 198 Table 13.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 199 Table 13.19 Higher-risk sex and condom use at last higher-risk sex in the past year among youth . 201 Table 13.20 Age-mixing in sexual relationships. 202 Table 13.21 Drunkenness during sexual intercourse among youth. 203 Table 13.22 Recent HIV tests among youth . 204 Figure 13.1 Reasons for having an HIV test among women and men age 15-49 who have ever been tested. 192 xii | Tables and Figures CHAPTER 14 DOMESTIC VIOLENCE Table 14.1 Experience of physical mistreatment . 208 Table 14.2 Perpetrators of violence . 209 Table 14.3 Marital violence . 210 Table 14.4 Onset of spousal violence . 212 Table 14.5 Physical consequences of spousal violence. 213 Table 14.6 Spousal violence by spousal characteristics and women’s status indicators . 214 Figure 14.1 Percentage of women who have experienced specific forms of spousal violence ever and in the 12 months preceding the survey . 211 CHAPTER 15 EMIGRATION Table 15.1 Households from which former members have emigrated. 218 Table 15.2 Characteristics of households from which former members have emigrated . 219 Table 15.3 Background characteristics of emigrants at time of emigration . 220 Table 15.4 Main reason for emigrating . 221 Table 15.5 Current age and sex of emigrants . 224 Table 15.6 Destination countries of emigrants . 226 Table 15.7 Characteristics of households caring for the children of emigrants . 226 Table 15.8 Children of emigrants left behind . 227 Figure 15.1 Percentage of households with at least one emigrant by wealth quintile . 219 Figure 15.2 Percent distribution of emigrants by year of emigration and sex . 222 Figure 15.3.1 Current age of emigrants from urban areas. 223 Figure 15.3.1 Current age of emigrants from rural areas. 223 Figure 15.4 Destination countries of emigrants . 225 Figure 15.5 Current age of emigrants’ children . 227 APPENDIX A SAMPLE IMPLEMENTATION Table A.1 Number of selected households and completed women and children interviews, by residence . 236 Table A.2 Proportional and non-proportional sample allocation. 236 Table A.3 Final recommended sample size . 237 Table A.4 Sample implementation: women . 237 Table A.5 Sample implementation: men. 238 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors . 241 Table B.2 Sampling errors for national sample . 242 Table B.3 Sampling errors for urban sample. 243 Table B.4 Sampling errors for rural sample. 244 Table B.5 Sampling errors for North sample. 245 Table B.6 Sampling errors for Center sample . 246 Table B.7 Sampling errors for South sample . 247 Tables and Figures | xiii Table B.8 Sampling errors for Chisinau sample . 248 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . 249 Table C.2.1 Age distribution of eligible and interviewed women . 250 Table C.2.2 Age distribution of eligible and interviewed men. 250 Table C.3 Completeness of reporting . 251 Table C.4 Births by calendar years . 251 Table C.5 Reporting of age at death in days . 252 Table C.6 Reporting of age at death in months. 252 Preface | xv PREFACE On August 27, 1991, after almost 50 years as a Soviet republic, the Republic of Moldova became an independent country. The first decade of transition to a democratic system and market economy met with many challenges and hardships for the population. In the new millenium, however, there is evidence of trends towards social economic stability and improvement. These developments are due in large part to collaborative efforts between the Government of Moldova, the international community, and non- governmental organizations working together towards common goals. Population-based surveys are useful in quantifying the impact of these efforts because they provide an array of development indicators which reflect the current situation in the country. The 2005 Moldova Demographic and Health Survey (MDHS) provides many indicators for Moldova’s Millenium Development Goals (2004-2015), for example. Information from the 2005 MDHS will be used by policy- makers in various ministries, by program managers for planning purposes, by the international donor community, and by academic institutions and experts conducting in-depth research. Many of the results from the 2005 MDHS will also be used to analyze trends; indicators from this survey can be compared to results from other national surveys conducted previously in Moldova, including the 1997 Reproductive Health Survey and the 2000 Multiple Indicator Survey. Finally, indicators from the MDHS will be compared with those from other countries in the region. This final report, summarizing the demographic and health information collected in the 2005 MDHS, represents a significant undertaking and coordinated efforts of many entities. It was sponsored by the United States Government through the Agency for International Development (USAID) and co- sponsored by the United Nations Children’s Fund (UNICEF) and the United Nations Population Fund (UNFPA). It was carried out by the National Center for Preventive Medicine, of the Moldova Ministry of Health and Social Protection, with technical assistance provided by ORC Macro. Considerable expertise was given by Moldova’s Department of Statistics, the Institute for Scientific Research in Mother and Child Protection, the Centers for Preventive Medicine, and other institutions. It is likewise important to recognize the work of field staff who collected data from over 11,000 households throughout the country, as they are ultimately responsible for the good quality data that were collected. Ion Bahnarel Director, National Scientific and Applied Center for Preventive Medicine, MOHSP Summary of Findings | xvii SUMMARY OF FINDINGS Moldova’s first Demographic and Health Survey (2005 MDHS) is a nationally representa- tive sample survey of 7,440 women age 15-49 and 2,508 men age 15-59 selected from 400 sample points (clusters) throughout Moldova (excluding the Transnistria region). It is designed to provide data to monitor the population and health situation in Moldova; it includes several indicators which follow up on those from the 1997 Moldova Repro- ductive Health Survey (1997 MRHS) and the 2000 Multiple Indicator Cluster Survey (2000 MICS). The 2005 MDHS used a two-stage sample based on the 2004 Population and Housing Census and was designed to produce separate estimates for key indicators for each of the major regions in Moldova, including the North, Center, and South regions and Chisinau Municipality. Unlike the 1997 MRHS and the 2000 MICS surveys, the 2005 MDHS did not cover the region of Transnis- tria. Data collection took place over a two-month period, from June 13 to August 18, 2005. The survey obtained detailed information on fertility levels, abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, adult health, and awareness and behavior regard- ing HIV infection and other sexually transmitted diseases. Hemoglobin testing was conducted on women and children to detect the presence of anemia. Additional features of the 2005 MDHS include the collection of information on interna- tional emigration, language preference for reading printed media, and domestic violence. The 2005 MDHS was carried out by the National Scientific and Applied Center for Preventive Medicine, hereafter called the National Center for Preventive Medicine (NCPM), of the Ministry of Health and Social Protection. ORC Macro provided technical assistance for the MDHS through the USAID-funded MEASURE DHS project. Local costs of the survey were also supported by USAID, with additional funds from the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), and in-kind contributions from the NCPM. CHARACTERISTICS OF RESPONDENTS Ethnicity and Religion. Most women and men in Moldova are of Moldovan ethnicity (77 percent and 76 percent, respectively), followed by Ukrainian (8-9 percent of women and men), Rus- sian (6 percent of women and men), and Gagauzan (4-5 percent of women and men). Romanian and Bulgarian ethnicities account for 2 to 3 percent of women and men. The overwhelming majority of Moldovans, about 95 percent, report Orthodox Christianity as their religion. Residence and Age. The majority of respondents, about 58 percent, live in rural areas. For both sexes, there are proportionally more respondents in age groups 15-19 and 45-49 (and also 45-54 for men), whereas the proportion of respondents in age groups 25-44 is relatively lower. This U-shaped age distribution reflects the aging baby boom cohort following World War II (the youngest of the baby boomers are now in their mid-40s), and their children who are now mostly in their teens and 20s. The smaller proportion of men and women in the middle age groups reflects the smaller cohorts following the baby boom gen- eration and those preceding the generation of baby boomers’ children. To some degree, it also reflects the disproportionately higher emigration of the working-age population. Education. Women and men in Moldova are universally well educated, with virtually 100 percent having at least some secondary or higher education; 79 percent of women and 83 percent of men have only a secondary or secondary special education, and the remainder pursues a higher education. More women (21 percent) than men (16 percent) pursue higher education. xviii | Summary of Findings Language Preference. Among women, preferences for language of reading material are about equal for Moldovan (37 percent) and Rus- sian (35 percent) languages. Among men, prefer- ence for Russian (39 percent) is higher than for Moldovan (25 percent). A substantial percentage of women and men prefer Moldovan and Russian equally (27 percent of women and 32 percent of men). Living Conditions. Access to electricity is almost universal for households in Moldova. Ninety percent of the population has access to safe drinking water, with 86 percent in rural areas and 96 percent in urban areas. Seventy-seven percent of households in Moldova have adequate means of sanitary disposal, with 91 percent of households in urban areas and only 67 percent in rural areas. Children’s Living Arrangements. Com- pared with other countries in the region, Moldova has the highest proportion of children who do not live with their mother and/or father. Only about two-thirds (69 percent) of children under age 15 live with both parents. Fifteen percent live with just their mother although their father is alive, 5 percent live with just their father although their mother is alive, and 7 percent live with neither parent although they are both alive. Compared with living arrangements of children in 2000, the situation appears to have worsened. FERTILITY Fertility Levels and Trends. The total fer- tility rate (TFR) in Moldova is 1.7 births. This means that, on average, a woman in Moldova will give birth to 1.7 children by the end of her repro- ductive period. Overall, fertility rates have de- clined since independence in 1991. However, data indicate that fertility rates may have increased in recent years. For example, women of childbearing age have given birth to, on average, 1.4 children at the end of their childbearing years. This is slightly less than the total fertility rate (1.7), with the dif- ference indicating that fertility in the past three years is slightly higher than the accumulation of births over the past 30 years. Fertility Differentials. The TFR for rural areas (1.8 births) is higher than that for urban areas (1.5 births). Results show that this urban-rural dif- ference in childbearing rates can be attributed almost exclusively to younger age groups. Unplanned Fertility. Twelve percent of births in Moldova are mistimed (wanted later) and almost 9 percent are unwanted. The percentage of births considered to have been unwanted is highest for births of order four and above, almost half of which were reported as not wanted at the time of conception. Similarly, a larger proportion of births to older women are reported as unwanted, com- pared with births to younger women. For example, only 5 percent of births to women age 20-24 are unwanted, compared with 30 percent among women age 35-39. Fertility Preferences. Results show that Moldovan women and men generally want small families. Overall, 64 percent of married women either do not want another child or are sterilized, 28 percent want to have another child—12 percent soon (within two years), 14 percent later, and 3 percent are undecided when—and the remaining 7 percent are either undecided or say they are unable to have another child. Fertility preferences among married men show a similar pattern to women, with an identical proportion (64 percent) either wanting no more children or sterilized. Men are slightly less likely than women to want another child (24 percent) and slightly more likely to be undecided. Furthermore, a large majority of those with two children (83 percent of women and 75 percent of men) say they do not want any more, as do 90 percent of women and 84 percent of men with three children. Even among those with one child, over one-third do not want to have another child. And surprisingly, 9 percent of women and 18 per- cent of men with no children say that they do not want any children. Age at First Birth. MDHS findings indicate that childbearing begins relatively late in Moldova; the majority of women age 20-24 years have never given birth. Between age 30 and 34, however, over 90 percent of women have given birth. The median age at first birth for women age Summary of Findings | xix 25 and older is 21 or 22 years, with little variation between age groups. CONTRACEPTION Knowledge of Contraception. Knowledge of family planning is nearly universal, with 99 per- cent of all women age 15-49 knowing at least one modern method of family planning. Among all women, the male condom, IUD, pills, and with- drawal are the most widely known methods of family planning, with over 80 percent of all women saying they have heard of these methods. Female sterilization is known by two-thirds of women, while periodic abstinence (rhythm meth- od) is recognized by almost six in ten women. Just over half of women have heard of the lactational amenorrhea method (LAM), while 40-50 percent of all women have heard of injectables, male ster- ilization, and foam/jelly. The least widely known methods are emergency contraception, diaphragm, and implants. Use of Contraception. Sixty-eight percent of currently married women are using a family planning method to delay or stop childbearing. Most are using a modern method (44 percent of married women), while 24 percent use a traditional method of contraception. The IUD is the most widely used of the modern methods, being used by 25 percent of married women. The next most widely used method is withdrawal, used by 20 percent of married women. Male condoms are used by about 7 percent of women, especially younger women. Five percent of married women have been sterilized and 4 percent each are using the pill and periodic abstinence (rhythm method). The results show that Moldovan women are adopting family planning at lower parities (i.e., when they have fewer children) than in the past. Among younger women (age 20-24), almost half (49 percent) used contraception before having any children, compared with only 12 percent of women age 45-49. Trends in Contraceptive Use. Contracep- tive use appears to have decreased slightly since 1997, from 74 to 72 percent of married women age 15-44.1 The proportion of women using modern methods has also decreased slightly from 50 to 48 percent. Use of the IUD has dropped considerably, from 38 percent of married women age 15-44 in 1997 to 28 percent of those age 15-44 in 2005. This decline has been partially offset by slight in- creases in use of condoms (from 6 to 9 percent of married women age 15-44), the pill (from 2 to 4 percent), and other methods like LAM and female sterilization. Use of traditional methods has remained steady. Differentials in Contraceptive Use. Although the level of any contraceptive use is about the same for married women in urban and rural areas (67-68 percent), urban women are more likely than rural women to use modern methods (48 and 41 percent, respectively). As expected, contraceptive use increases with level of educa- tion. For example, 72 percent of married women with higher education are using a method of con- traception, compared with 65 percent of women with secondary education. Use also tends to in- crease with the number of living children—from 36 percent among married women with no chil- dren to 74 percent among married women with 3 or 4 children. Although there is almost no difference in use of any contraceptive method by wealth quin- tile, there is a steady rise in use of modern meth- ods as wealth increases. For example, 37 percent of married women in the lowest wealth quintile are using a modern contraceptive method, compared with 51 percent of those in the highest wealth quintile. Source of Modern Methods. Public (gov- ernment) facilities provide contraceptives to more than two in three contraceptive users (69 percent), while 28 percent are supplied through private medical sources, and 3 percent through other pri- vate sources (e.g., shops). 1 The 1997 MRHS data refer to married women age 15-44; consequently, the data from the 2005 MDHS were recalculated for the same age group. Interpretation of trends is also hampered by the fact that the 1997 sur- vey included Transnistria, whereas the 2005 survey did not. xx | Summary of Findings Discontinuation Rates. Overall, more than one-third (38 percent) of family planning users in Moldova discontinue using their method within 12 months of starting its use. Seven percent of users stop using as a result of method failure (i.e., unin- tended pregnancy), while 4 percent discontinue because of a desire to become pregnant, and 18 percent switch to another method. Discontinuation rates are highest for users of LAM (91 percent), presumably because it is only usable immediately after giving birth and its effec- tiveness declines sharply after six months. Discon- tinuation rates are also high for pill users—half of whom stop using within 12 months after starting— and for users of condoms (39 percent), withdrawal (37 percent), and rhythm method (35 percent). On the other hand, very few IUD users (7 percent) discontinue using their method within a year. For all methods, the most common reason for discon- tinuation was to switch to another method. Unmet Need for Family Planning. Seven percent of currently married women in Moldova have an unmet need for family planning, 3 percent for spacing births and 4 percent for limiting. If all these women with unmet need were to join the 68 percent who already are using family planning (met need), the contraceptive prevalence rate could increase from the current level of 68 percent to 75 percent (total demand). In short, 91 percent of the total demand for family planning among married women has been satisfied. ABORTION Reliance on induced abortion was the pri- mary means of fertility control throughout the for- mer Soviet Union, including the former Soviet Republic of Moldova. In the decade after Moldova’s independence in 1991, abortion rates began to decrease as the practice of modern con- traception became more widespread. This decreas- ing trend, however, has stalled since 2000 mainly because older women still rely on abortion to limit childbearing. Thus, abortion is still a key factor in Moldova’s reproductive trends. Pregnancy Outcomes. Slightly more than half of pregnancies in Moldova end in a live birth (55 percent). The majority of pregnancy losses are due to induced abortions (34 percent of pregnan- cies), followed by miscarriages (10 percent) and stillbirths (less than 1 percent). These estimates do not appear to have changed significantly since those in 1997 despite sampling differences (see chapter 6). Lifetime Experience with Abortion. Over- all, more than a third of women (37 percent) of reproductive age have had at least one abortion. This proportion increases rapidly with age, with 61 percent of women age 35 or older having had at least one abortion. The mean number of abortions among women who have had at least one abortion is 2.2. Among women who have ever had an abor- tion, over half have had more than one (59 per- cent). The 2005 MDHS data do not differ signifi- cantly from those in the 1997 MRHS in terms of the percentage of women who reported ever hav- ing had an abortion (37 percent and 39 percent, respectively). Abortion Rates. The lifetime total abortion rate (TAR) for the three-year period prior to the survey is 1.1 abortions per woman. The TAR for married women only, during the same time period, is 1.3 abortions per married woman. Comparing national abortion rates with fer- tility rates, the pattern indicates that fertility rates are significantly higher than abortion rates for women under age 30. The pattern is reversed for older women, with older women more likely to have an abortion than to bear a child. Abortion Differentials. The TAR is slightly higher in urban areas than rural areas (1.3 and 1.0, respectively). TARs do not vary significantly by residence or level of education. The lowest TAR of 0.7 is recorded for women in the poorest wealth quintile, while the highest TAR (1.4) is observed among women in the highest quintile and also for women in Chisinau. Trends in Abortion Rates. On average, women in Moldova who have come to the end of their reproductive years have had an average of 1.5 abortions. Comparing this with the TAR of 1.1—a measure of the current level of induced Summary of Findings | xxi abortion across all age groups—the level of in- duced abortion appears to have decreased over time. However, another more sensitive approach to identifying abortion trends points to stagnation in the TARs for women age 15-44 since the mid- 1990s, and an increase in age-specific abortion rates (ASAR) for women in their 30s since 2003. The general abortion rate (GAR), the number of abortions annually per 1,000 women age 15-44, shows a modest decrease since the late 1990s, but no improvement since 2002. MATERNAL HEALTH Antenatal Care and Delivery Care. Among women with a birth in the five years pre- ceding the survey, almost all reported seeing a health professional at least once for antenatal care during their last pregnancy; nine in ten reported 4 or more antenatal care visits. Seven in ten women had their first antenatal care visit in the first trimester. In addition, virtually all births were deliv- ered by a health professional, in a health facility. Results also show that the vast majority of women have timely checkups after delivering; 89 percent of all women received a medical checkup within two days of the birth, and another 6 percent within six weeks. Components of Antenatal Care. Among women with a birth in the past five years, over 95 percent had their weight measured, their blood pressure taken, and gave a blood and urine sample for analysis during their last pregnancy. Fewer of these mothers, however, benefited from additional preventive care; only 54 percent received iron tab- lets during their last pregnancy and 21 percent received folic acid. Ninety percent had received at least one tetanus toxoid injection at some time in their life. Antenatal Education. Approximately 8 in 10 women with a birth in the five years preceding the survey received information on: smoking and alcohol use during pregnancy; the benefits of breastfeeding; emergency delivery plans; and fam- ily planning. However, given that 61 percent of women experienced some pregnancy complication during their last birth, however, pregnancy care education during antenatal visits could be im- proved. CHILD HEALTH Childhood Mortality. The infant mortality rate for the 5-year period preceding the survey is 13 deaths per 1,000 live births, meaning that about 1 in 76 infants dies before the first birthday. The under-five mortality rate is almost the same with 14 deaths per 1,000 births. The near parity of these rates indicates that most all early childhood deaths take place during the first year of life. Comparison with official estimates of IMRs suggests that this rate has been improving over the past decade. Childhood Vaccination Coverage. Overall, 85 percent of children age 15-26 months are fully vaccinated, and 76 percent of these children were fully vaccinated in their first year of life (or by 15 months for measles, mumps and rubella). These levels show a slight improvement since the 2000 MICS estimates, but more timely coverage is needed so that children benefit from the protective effects of all vaccinations by their first birthday. Similarly, overall coverage levels could be im- proved if children in urban areas, and especially Chisinau, completed all doses of all vaccines required by the National Immunization Program of the Republic of Moldova. Childhood Illness and Treatment. Among children under 5 years of age, 7 percent were re- ported to have had symptoms of acute respiratory illness in the two weeks preceding the survey, while 16 percent had a fever, and 7 percent had diarrhea. Fifty-four percent of children with symp- toms of ARI and/or fever were taken to a health facility or provider for treatment. NUTRITION Breastfeeding Practices. Breastfeeding is nearly universal in Moldova: 97 percent of chil- dren are breastfed. However the duration of breast- feeding is not long, exclusive breastfeeding is not widely practiced, and bottle-feeding is not un- common. In terms of the duration of breastfeeding, xxii | Summary of Findings data show that by age 12-15 months, well over half of children (59 percent) are no longer being breastfed. By age 20-23 months, almost all chil- dren have been weaned. Exclusive breastfeeding is not widely prac- ticed and supplementary feeding begins early: 57 percent of breastfed children less than 4 months are exclusively breastfed, and 46 percent under six months are exclusively breastfeed. The remaining breastfed children also consume plain water, wa- ter-based liquids or juice, other milk in addition to breast milk, and complimentary foods. Bottle-feeding is fairly widespread in Mol- dova; almost one-third (29 percent) of infants un- der 4 months old are fed with a bottle with a nip- ple. Iodine Consumption. Disorders induced by dietary iodine deficiency constitute a major nutri- tional concern in Moldova. Sixty percent of households currently use adequately iodized salt. Improvement in coverage is most needed in rural areas, and especially the South region where only 44 percent of households use iodized salt. Anemia Status of Women and Children. Iron deficient anemia is a health concern that could be addressed with adequate iron supple- ments for women—especially pregnant women— and young children. Twenty-eight percent of women in Moldova have some level of anemia— 40 percent of pregnant women are anemic—and about one-third of children age 6-59 months have mild or moderate anemia. Nutritional Status of Children. At the na- tional level, about 8 percent of children under age five are stunted (low height-for-age), while about 4 percent of children are wasted (low weight-for- height), and 4 percent are underweight (low weight-for-age). Nutritional Status of Women. The mean body mass index (BMI) for women age 15-49 is 25. This is the cutoff point between a normal and overweight BMI. The proportion of overweight or obese women is positively correlated with women’s age. The age group 45-49 has the highest proportion (74 percent) of overweight or obese women, while age group 15-19 has the lowest pro- portion (8 percent). At the national level, the mean height for women is 161 cm, with less than 1 percent of women falling below the cutoff of 145 cm. HIV/AIDS KNOWLEDGE Awareness of HIV/AIDS. Awareness of HIV/AIDS is almost universal among persons of reproductive age. Ninety-seven percent of men and women age 15-49 have heard of HIV/AIDS, but men are slightly better informed than women about specific ways to avoid contracting the dis- ease: 81 percent of women and 89 percent of men indicate that the chances of getting the AIDS virus can be reduced by limiting sex to one faithful partner; 78 percent of women and 87 percent of men are aware that condoms can reduce the risk of contracting HIV during sexual intercourse; and 63 percent of women and 85 percent of men know that abstaining from sex reduces the chances of getting the disease. Seventy-six percent of women and 78 percent of men know that a healthy-looking person can have the AIDS virus. Knowledge patterns between men and women are reversed for mother-to-child transmis- sion of HIV: 68 percent of women compared with 53 percent of men know that HIV can be transmit- ted by breastfeeding; 86 percent of women and 79 percent of men know the disease can be transmit- ted from the mother to the child during pregnancy; and 82 percent of women and 76 percent of men know it can be transmitted during delivery. Attitudes Toward People with HIV. The level of stigma associated with HIV/AIDS is high in Moldova, for both sexes. While most respon- dents age 15-49 would be willing to care for a family member with HIV at home (76 percent of women and 56 percent of men) and would not necessarily want the HIV-positive status of a fam- ily member to remain a secret (61 percent of women and 51 percent of men), far fewer would buy fresh vegetables from a vendor with AIDS (11 percent of both women and men), or believe a fe- male teacher with HIV should be allowed to teach (28 percent of women and 23 percent of men). Summary of Findings | xxiii Only 5 percent of women and 3 percent of men express acceptance on all four measures. HIV-Related Behavioral Indicators. Among respondents who reported having sex in the 12 months preceding the survey, a substan- tially larger proportion of men than women re- ported having had more than one sexual partner (14 percent for men and 2 percent for women). More men than women also reported having had higher-risk sex at some time in the past 12 months (34 and 13 percent, respectively). Only about one- third of women reported using a condom the last time they had sex with a nonmarital, nonco- habiting partner (34 percent), while over half of men did (54 percent). The proportion of women and men age 15-24 that had sex before age 15 is about 1 percent for young women and 9 percent for young men. By age 18, however, 19 percent of young women and 44 percent of young men have had sex. Among sexually active women and men age 15-24, 36 percent and 84 percent, respectively, have had sexual relations with a nonmarital, non- cohabitating partner in the year preceding the sur- vey. Injections. The data show that receiving medical injections is a common practice in Moldova. One-third of women and 28 percent of men received at least one medical injection in the year preceding the survey—women received an average of 6 injections and men received an aver- age of 3.2 injections. Ninety-nine percent of the last injections were administered with an unused syringe from a previously unopened package. HIV Testing. Thirty-six percent of women in Moldova have been tested for HIV at some time, compared with 30 percent of men. Thirty- four percent of women and 27 percent of men were tested and also received the results of their HIV test. DOMESTIC VIOLENCE Violence Since Age 15. MDHS data show that one-quarter of all women (27 percent) have experienced violence since they were age 15 and 13 percent experienced violence in the 12 months preceding the survey. The main perpetrators of violence against women are husbands (69 percent) and, to a lesser extent, fathers/stepfathers (14 per- cent), and mothers/stepmothers (7 percent). Marital Violence. Twenty-three percent of ever-married women report having experienced emotional violence by husbands, 24 percent report physical violence, and 4 percent report sexual vio- lence. Almost one-third (32 percent) of ever- married women report suffering emotional, physi- cal, or sexual violence, while 3 percent have experienced all three forms of violence by their current or most recent husband. The data further show that divorced or sepa- rated women are more than twice as likely as mar- ried women to have been abused emotionally, physically, and sexually, suggesting that the vio- lence might have been a factor in the termination of their marriages. EMIGRATION In Moldova, and in post-Soviet states in gen- eral, large-scale labor emigration is an important demographic phenomenon that has a substantial negative impact on the population growth as well as on the social and economic structure of society. Emigrant Households. Seventeen percent of households in Moldova have at least one former member who emigrated. This percentage is about the same in urban and rural households. The high- est percentage of households with at least one emigrant is in the South region (21 percent) and the lowest is in Chisinau (13 percent). Emigrant Characteristics. A slightly high- er proportion of emigrants are males (52 percent, compared with 48 percent for women). However, in Chisinau and the South region, a slightly higher proportion of emigrants are females. The distribu- tion of emigrants by age at emigration is similar for males and females. The most common age group for emigration is age 20-24 for both sexes. This age group accounts for roughly one-quarter of all emigrants (22 percent of females and 27 per- cent of males). Approximately three-quarters of all emigrants leave the country between age 15 and xxiv | Summary of Findings 39 (73 percent of females and 79 percent of males). More than one-quarter of both males and females living abroad have left behind a wife or husband in their original household. Over half of emigrants are the son or daughter, or son-in-law or daughter-in-law, of the head of the household (55 percent of female emigrants are the daughter or daughter-in-law, 64 percent of male emigrants are the son or son-in-law). Forty-two percent of emigrants left children in Moldova, with 37 percent of emigrants from urban areas and 45 percent from rural areas having left at least one child behind. Among the emi- grants who left children behind, about 2 in 10 left behind two or more children. Main Reason for Emigrating. Not surpris- ingly, labor is overwhelmingly the main reason that people from Moldova emigrate. Household respondents report that for 83 percent of female emigrants and 91 percent of male emigrants, work was the main reason for moving abroad. An addi- tional 7 percent of women and 3 percent of men emigrated to accompany their spouse or family abroad; 3 percent of women and 1 percent of men emigrated in order to marry a foreigner. Five per- cent or less of emigrants left Moldova with their main purpose being to study abroad. Emigration Trends. Data show that emi- gration was negligible prior to the dissolution of the Soviet Union in 1991, and throughout most of the first decade of Moldova’s independence. Emi- gration accelerated in the late 1990s and was con- tinuing to accelerate at the time of the survey. Over half (57 percent) of all emigrants reported in the survey left Moldova between 2001 and mid- 2005. Destination Countries. Given that many Moldovans are ethnic Russian, half of emigrants went to Russia (a total of 54 percent went to some country of the former Soviet Union, including Russia). One-third of all emigrants moved to Western Europe, with Italy as a primary destina- tion (20 percent), followed by Portugal, Greece, and Spain. The remaining emigrant destinations included Turkey, North America, Israel, Romania, and other countries. Millennium Development Goal Indicators | xxv Millennium Development Goal Indicators na = Not applicable 1 Based on children born in the 5 years preceding the survey. 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. 2 Based on de jure members. Numerator is children age 7-11 currently attending school; denominator is children 7-11 years old. 3 Based on de jure members. This indicator is calculated using rates of promotion, dropout, and repetition for a given school year. These rates are used to project an estimate for the percentage of students attending grade 1 who are expected to reach grade 5, with or without repetition. 4 Numerator is respondents 15-24 years old who can read part of a sentence or the whole sentence; denominator is respondents 15-24 years old. 5 The ratio of girls to boys for primary/secondary/tertiary education is the ratio of the primary/secondary/tertiary education GAR for females to the GAR for males. (The GAR is the total number of primary/secondary/ tertiary education students, expressed as a percentage of the official level of education-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent.) 6 Numerator is all women working in the non-agricultural sector who received payment in cash or kind; denominator is all women. 7 In Moldova, the measles vaccination is given at the age of 12 months (unlike the standard 9 months in many countries). The values presented in the table are for children 12-59 months who have been vaccinated at any time against measles. The prevalence of children vaccinated against measles by age 15 months is significantly lower, however, at 83.4 percent. 8 Skilled health personnel includes: doctor, nurse, midwife, and auxiliary midwife. 9 Higher-risk sex is sexual intercourse with a nonmarital, noncohabiting partner. 10 Respondents with “general knowledge” of AIDS are those who say that using a condom for every sexual intercourse and having just one uninfected and faithful partner can reduce the chance of getting the AIDS virus, and furthermore say that a healthy-looking person can have the AIDS virus, and who reject the common misconception that HIV can be spread by sharing food with someone with AIDS. 11 Note that these indicators do not take into account children who live outside of households, e.g., in institutions or on the street, because the MDHS includes only households in its sample. 12 Solid fuel includes: wood, straw, crops and other. 13 Improved drinking water sources includes: water from pipe/tap and from protected well. 14 Improved sanitary means of excreta disposal includes: flush toilet, ventilated improved pit latrine, and latrine with a slab. Goal Indicator Value Male Female Total 1. Eradicate extreme poverty and hunger Prevalence of underweight in children under five years of age 1 3.4 5.2 4.3 Male Female Total 2. Achieve universal primary education Net enrollment ratio in primary education2 77.5 78.8 78.2 Percent of pupils starting grade 1 who reach grade 53 99.8 100.0 99.9 Literacy rate of young people age 15-24 years4 99.5 99.7 99.6 3. Promote gender equality and empower women Ratio of girls to boys in primary school5 1.03 Ratio of girls to boys in secondary school5 1.05 Ratio of girls to boys in tertiary education5 1.34 Ratio of literate women to men, age group 15-24 years 1.00 Share of women in wage employment in the nonagricultural sector6 80.2 Male Female Total 4. Reduce child mortality Under-five mortality rate 12.8 14.9 13.6 Infant mortality rate 11.3 14.5 12.8 Percent of children age 15-26 months immunized against measles7 90.8 90.3 90.6 5. Improve maternal health Percent of births attended by skilled health personnel8 99.5 Male Female Total 6. Combat HIV/AIDS, malaria, and other diseases Percentage of current users of contraception who are using condoms (all women) na 20.4 na Condom use at last higher-risk sex9 53.7 33.8 42.4 Percentage of population age 15-24 years with general knowledge about HIV/AIDS10 54.3 41.6 44.3 Contraceptive prevalence rate (all women) 49.8 Contraceptive prevalence rate (married women and women in union) 67.8 Ratio of school attendance of orphans to school attendance of nonorphans age 10-14 years11 0.9 Percent of population in malaria-risk areas using effective malaria prevention and treatment measures na Urban Rural Total 7. Ensure environmental sustainability Percent of population using solid fuels for cooking, urban and rural 12 1.4 24.3 15.1 Percent of population with sustainable access to an improved water source, urban and rural13 96.4 85.5 89.7 Percent of population with access to improved sanitation, urban and rural14 91.1 67.4 76.8 Percent of households with access to secure tenure na na na xxvi | Map of Moldova Introduction | 1 INTRODUCTION 1 1.1 GEOGRAPHY AND POPULATION The Republic of Moldova is a small, landlocked country in Eastern Europe. It has a surface area of 33,700 square kilometers and shares a border with Romania and Ukraine. The main water arteries are the Dniester River (657 km long) and the Prut River (695 km long). The terrain consists mainly of rolling plains with the highest point in the country measuring an altitude of 430 meters. Moldova became independent from the Soviet Union on August 27, 1991. A new constitution was adopted in 1994. The judicial branch of government is composed of a Supreme Court and a Constitutional Court which reviews legislative acts and governmental decisions. The legislative branch of government is composed of a unicameral Parliament. In the executive branch, the president is elected by Parliament for a four-year term and eligible for a second term. The territory of Moldova is divided into administrative-territorial units. As of January 1, 2006 these units consist of 32 districts (raions), 5 municipalities, 60 towns and 917 villages (communities), and 1,575 rural settlements. There are two territorial units to which special terms of autonomy are attributed: the autonomous territory of Gagauz, and the territory of Transnistria located on the east side of the Dniester River. Moldova’s official population count registered in the population census of October 5, 2004, excluding the districts in the region of Transnistria, was 3.4 million. Moldova has the highest population density of any of the former Soviet Republics; on average, there are about 111 people per square kilometer, and about 1,255 people per square kilometer in Chisinau. Compared with the population count in the 1989 census, Moldova’s population has decreased by approximately 274,000 people. The rate of population decline, determined both by a greater number of deaths than live births, as well as a surplus of emigrants over immigrants, results in a negative population growth estimated to be about -0.5 percent. An aging population is a consequence of a declining population; since 1989, there has been a decrease in the proportion of young people under age 15 and a simultaneous increase in the proportion of working-age and elderly people age 60 and older. The average age registered in the 2004 census was 35.3 years, compared with 32 years in the 1989 census data. The average life expectancy at birth in 2004 was 64.5 years for males and 72.2 years for females. The life expectancy is also higher in urban areas than rural areas—both men and women in urban areas live approximately 3 years longer than those in rural areas. The ethnic composition of Moldova as registered in the 2004 census reveals that the majority of the population is ethnic Moldovan (76 percent), followed by Ukrainian (8 percent), Russian (6 percent), Gagauz (4 percent), Romanian (2 percent) and Bulgarian (2 percent). Other ethnic groups make up about 1 percent of the population. The overwhelming majority of Moldovans are affiliated with the Orthodox religion. 1.2 HISTORY Moldova lies between the Carpathian Mountains, the Black Sea, and the Dniester River. The first communities in this region emerged approximately 300,000 years ago. This territory, lying in the path of numerous migrating tribes and peoples, evolved as a mix of cultures, civilizations, and communities. From the 3rd century B.C. to the 1st century A.D., Geto-Dacian kingdoms emerged in the Carpathian- Balkan region; the strongest of these were the Burebista (82-44 B.C.) and Decebal (87-106 A.D.) king- doms. The domination of the Roman Empire in Dacia (106-275) led to the Romanization of the 2 | Introduction Carpathian-Danube population and of tribes migrating from the east, including Slavs who settled in the region. By the 8th or 9th century, a distinct East-Romanic (Romanian) community had emerged. From the end of the 13th century to the first half of the 14th century, the process of establishing independent states to the east of the Carpathian Mountains accelerated. The medieval state of Moldova dates back to 1359. The territory of Moldova expanded in the second half of the 14th century when, with the liberation of the Carpathian-Danube region from Mongol-Tatar domination, it extended its borders to the Black Sea. The peak of development of the medieval Moldovan state was reached in the second half of the 15th century, during the rule of Stephen the Great; this period saw the consolidation of internal power in Moldova and an increase in its prestige in international relations. In 1538 Moldova fell under the domination of the Ottoman Empire. This lasted three centuries and during that time Moldova lost part of its territory—first the southern part of the country and later other parts were taken from Moldovan jurisdiction and governed directly by the Ottoman and Tatar authorities. The vassalage regime was initially a protective suzerainty but eventually became more restrictive as it laid down its power structures. Moldova, however, remained autonomous in the organi- zation and management of the state’s internal affairs. In the 18th century, Moldova experienced a range of military confrontations with the Ottoman, Russian, and Habsburg Empires; the battles conducted on Moldovan territory resulted in the loss of more territory. Following the Russian-Turkish war (1806-1812), the eastern part of Moldova between the Prut and the Dniester Rivers, called Bessarabia, became part of the Russian Empire. In 1859, the western part of Moldova between the Carpathian Mountains and the Prut River joined with Wallachia to be united as the Kingdom of Romania. On December 2, 1917, Bessarabian authorities proclaimed the independence of the Republic of Moldova. Shortly thereafter, however, on March 27, 1918, Bessarabia united with Romania. After the creation of the Soviet Union in 1922, the Soviet government established the Moldavian Autonomous Soviet Socialist Republic (Moldovan ASSR); on August 2, 1940, the Soviets created the Moldavian Soviet Socialist Republic (Moldavian SSR) by combining the territories of Bessarabia (eastern Moldova) and the Moldovan ASSR. During the 1940s the population inhabiting this region experienced difficult times: thousands of peasants were uprooted or killed, and many villages were devastated as a result of the Soviet invasion (1940), the Romanian-German operations in World War II (1941-1944), and the subsequent forced collectivization and deportations to Siberia and Kazakhstan. An estimated 115,000 peasants died because of the famine in 1946-1947 (Gribincea, 1995; Taran et al., 1993). Post-war development of Moldovan society was characterized by greater integration into the Soviet social, economic, and cultural spheres. An important economic and scientific potential evolved but its development was hampered by an inflexible totalitarian, centralized regime. By the end of the 1980s, the social economic situation deteriorated abruptly, portending the eventual break-down of the Soviet system. Following the collapse of the Soviet Union on August 27, 1991, an independent Republic of Moldova (Moldova) was proclaimed, marking the beginning of a new epoch in the development of the country and its society. Independent Moldova undertook the difficult challenges of transitioning from a totalitarian society, based on a centrally planned economy, to a liberal democratic society, based on a market economy. It confronted complex political, economic, social, and cultural issues. The formation of Moldova as an independent state took place under already difficult social economic conditions, during a tense political situation, and in the face of substantial social and cultural differences within the population. Introduction | 3 The first decade of transition saw a continuous decrease in the value of the gross domestic product (GDP), such that by the end of the decade it was less than 40 percent of that registered in 1990. In 1992, Moldova underwent a short but bloody conflict in the territory situated to the east of the Dniester River (Transnistria). This conflict resulted in over 1,000 deaths and casualties and over 130,000 refugees. The situation remains unresolved today. Now, at the beginning of the 21st century, Moldova is making serious efforts to overcome obstacles and avoid crises. It is seeking ways to optimize reforms in political and economic life such that it continues to become more integrated into the European Community and on its way towards a better future. 1.3 ECONOMY Moldova is an agrarian-industrial country. It enjoys a favorable climate and has an abundance of arable lands. Since Moldova does not have within its borders an important quantity of mineral resources, the economy depends greatly on its agricultural potential. Rich, black soil covers almost three quarters of the territory’s surface, and the favorable climate is conducive to reaping two harvests per year. The main crops are cereals, maize, sugar beet, sunflower, tobacco, vine, vegetables, and fruit. Agricultural products account for approximately 60 percent of the export values. Moldova’s industry is concentrated mainly on processing agricultural raw materials, in particular, the production of wine and cigarettes and the processing of tobacco. This activity is complemented by light industries such as chemical industry, wood processing, machine building, and the manufacturing of some equipment. Heavy industry such as cement works and metallurgy is concentrated in the Transnistria region and has a market in Russia. Some of Moldova’s electrical power is generated at the hydroelectric station on the Dniester River and at thermoelectric power plants. These sources of energy, however, are not sufficient to meet the needs of the country. This circumstance creates a significant dependence on Russia and Ukraine to supply supplemental energy sources, which in turn results in payment issues and ultimately in an increase in Moldova’s external debt. Moldova’s need for energy resources (e.g., petrol, coal, natural gas) are thus only satisfied when supplemental energy is imported, and in particular from Russia. The Government of Moldova has made progress in implementing economic reforms, including the introduction of a stable currency, privatization of enterprises, liberalization of prices and interest rates, etc. Overall, the reforms implemented in recent years have had positive results. For example, the private sector currently contributes over 60 percent of the GDP and the market is functioning with commercial banks, stock exchanges, free economic zones, etc. The distribution of GDP per economic sector is, for agriculture, 48 percent; for industry, 28 percent; and for services, 24 percent. Economic reforms in Moldova have been largely supported by international agencies. Since 1992, when Moldova joined the International Monetary Fund (IMF), the Word Bank (WB), and the European Bank for Reconstruction and Development (EBRD), it has benefited from many investments from international financial banking structures as well as various states such as Romania, Russia, USA, Germany, Japan, and others. Despite attaining some macroeconomic benchmarks, however, the sharp decline of economic activity in the first decade after independence lead to an acute growth of poverty in the 1990s—Moldova went from a country with an overall medium income level to one with an overall low income level. At the end of the 1990s, over 70 percent of the country’s population was considered poor (and approximately 60 percent were considered very poor), the GDP reached in real terms only 34 percent of the 1990 level (Ministry of Economics and Commerce, 2005). Moldova’s social indicators have also been among the 4 | Introduction worst in the region. In 2003, UNDP’s human development indicators ranked Moldova only 117th out of a total of 177 countries, and in last place among all CIS countries except Tajikistan (UNDP, 2005). The crisis related to Moldova’s transition lasted until 2000, when the economy finally started to manifest a sustainable growth. Between 2001 and 2004, Moldova’s economy grew by over 30 percent, while the GDP average annual growth constituted about 7 percent. The economic growth has determined a marked decrease in poverty rates, which, according to estimates, have dropped in 2004 to over a half of the highest levels registered in 1999 (World Bank, 2005). The export of labor force denoted by emigrating Moldovans of working age, and the resulting influx of currency transfers generated by the activity of Moldovans living abroad, represent important social and economic trends in Moldova. The 2004 population census revealed that over 357,000 Moldovans (approximately one-quarter of the total labor force) currently work abroad. Due to the increase in the flow of emigrants, especially between 1999 and 2004, the officially registered currency transfers from abroad have increased from 5 percent to approximately 27 percent of the GDP, thus placing Moldova among world economies that are most dependent on remittances (World Bank, 2005). 1.4 CHARACTERISTICS OF THE HEALTH SYSTEM 1.4.1 Facilities and Human Resources The main goal of Moldova’s health system is the assurance of quality medical services to all citizens. In recent years, the health system has undergone numerous functional and administrative reforms and readjustments. The Ministry of Health and Social Protection has concentrated its efforts on the following objectives: • Establishment of a legislative and normative basis for the implementation of compulsory health insurance; • Consolidation of primary and emergency health care sectors; • Increase in the quality of medical services offered; • Establishment of a network of state pharmaceutical institutions to rationally distribute medical supplies of high quality and low price; • Establishment of an evaluation and accreditation system for sanitary conditions in medical institutions; • Establishment of financial and contractual requirements between payers, suppliers and consumers of medical services; and • Identification of evidence-based clinical protocols for quality management of medical services. The principles of family medicine underpin Moldova’s national health care system. The national health care system promises to offer all citizens an equal opportunity to receive certain medical services free of charge. These services have been stipulated in the United Program of Compulsory Health Insurance (United Program), which is approved annually by the Government of Moldova. The United Program is financed with funds from the National Health Insurance Company. Those insured under the United Program benefit from the following health services: Introduction | 5 • Emergency care at the pre-hospital stage, provided by the district, municipal, or zonal emergency health care services; • Primary care, provided by a family doctor, in a Family Doctor Center or as home-based health care; • Specialized outpatient care, provided by specialized doctors at consulting hospitals and regional medical institutions; • Dental care; • Hospital care at in-patient medical institutions; • Paramedical services of simple or complicated nature; and • Maternal and child health including iron and folic acid for pregnant women, out-patient treatment for children under age 5, and partial or full compensation for medical supplies. Almost all employees in Moldova’s health system—including 10,753 doctors and 23,147 paramedical personnel—are state employees. Approximately 36 doctors per 10,000 persons serve people in urban areas, while about 12 doctors per 10,000 persons serve rural inhabitants. The coverage of paramedical personnel is better and constitutes 66 paramedics per 10,000 people. The average ratio of paramedical personnel per doctor is 2.2 (SACPHHM, 2005). A widespread and persistent problem in Moldova’s health care system is low salaries for medical personnel; the average monthly salary, despite general economic growth experienced in recent years, is about 125 USD for doctors and 70 USD for nurses. 1.4.2 Reforms of the Health System of the Republic of Moldova Throughout the past decade, as a result of the 1995 Health Protection Law and the 1997-2003 Health Sector Strategy, the Government of Moldova has put forth a variety of regulations and statutory acts aimed at addressing structural inefficiencies, streamlining human resources, improving health sector financing and equitable access to services, ensuring implementation and monitoring of national health policies, working out inter-sectoral programs, and involving the community in healthcare related decisions. The following legislative and statutory acts underlie the structural and organizational reforms in the healthcare system, namely: • Reform of primary health care (PHC) through institutionalizing family doctors and promoting the principle of free choice by the patient; institutionalizing per capita financing of PHC; and delegating the management of PHC, hospitals and emergency services to local public administration authorities (1997); • Establishment of the State Sanitary Epidemiologic Service (SSES); • Adoption of a legislative framework to introduce compulsory health insurance in January 2004, based on the taxation of salaries (2 percent from employees and 2 percent from employers); and • Reorganization of health services into a single package, comprising, at the district level, services at a hospital, a PHC service, emergency services, and specialized out-patient services. Although still from separate budgets, they would be managed by a single district Chief Medical Officer. 6 | Introduction A distinctive achievement in the past decade is the establishment of a minimal package of services offered free of charge to the entire population of Moldova.1 Those who are not insured through their work or otherwise insured receive free health care including preventive and primary health care (provided by a family doctor at the pre-hospital stage), inpatient medical care in case of major surgery or a medical emergency, and health care for infectious and chronic diseases such as tuberculosis, cancer, mental disorders, HIV/AIDS, and other diseases. 1.4.3 Specific Health Care Services Emergency Health Care. The National Scientific and Practical Emergency Medicine Center oversees emergency health care in Moldova. Emergency services are administered through 4 regional nodes located in the North, Center, South, and Autonomous Territory of Gagauzia, as well as 43 sub-units and 74 emergency health care posts in rural settlements. Altogether, 497 doctors, 907 paramedical personnel, and 303 ambulance fleets attend to medical emergencies. Primary Health Care Service. The main objectives of primary health services are to promote health and wellness, protect maternal and child health, improve health care coverage in rural areas, develop professional and technological capacity, prevent and control transmissible diseases, and implement a family planning program. Primary health care services are provided by 35 district Family Doctor Centers, 392 Health Centers, and 551 Family Doctor Offices. The number of family doctors in 2005 was 2,066. Hospital and Specialized Out-patient Health Care. Hospital and specialized out-patient health care, including dental care, is provided by specialized consulting sections of district hospitals. A review of hospitals in rural areas concluded that the average number of beds in rural hospitals was too high and thus inefficient from an economic and medical standpoint; Moldova, therefore, worked to streamline the number of beds in hospitals. Overall, the absolute number of beds dropped from 45,665 in 1998 to 20,457 in 2005, due mainly to the liquidation of hospitals in rural settlements that had a capacity of 50-100 beds each. In the same period, the number of hospitals was reduced from 245 to 65. Improvements in hospital indicators have since been observed, for example, the average duration of hospitalization decreased from 17.5 days in 1998 to 9.8 days in 2005, and the use of beds increased from 251 days per year in 2000 to 265 days in 2005. Mother and Child Health Care. Health care provision for mothers and children is a priority for the Ministry of Health and Social Protection. The MOHSP has implemented an array of national and sub- national programs aimed at ensuring access to quality health care for all children and pregnant women in order to reduce the incidence of morbidity, disability, and mortality. Under the United Program, children under age five benefit from subsidized medical supplies for outpatient treatment, while pregnant women are provided free iron and folic acid prophylaxes during pregnancy. The implementation of the “Promotion of Quality Perinatal Services” program and of the Global Initiative “Making Pregnancy Safer” has resulted in strengthening the regionalized system of perinatal care, providing quality health services, and institutionalizing a perinatal supervision system. As a result, the perinatal mortality in the most recent three years has stabilized. The “National Strategy for Reproductive Health” was approved on August 26, 2005 by Government Regulation no. 913. The main objective of the Strategy is to uphold the rights of citizens to achieve their reproductive desires, and to assure women their health in childbearing years. 1 Article 36 of the Constitution of the Republic of Moldova guarantees provision of minimal health care services to the noninsured population, free of charge. Introduction | 7 Since 2000, Moldova has implemented the strategy of “Integrated Management of Childhood Illnesses,” promoted by the World Health Organization (WHO). This strategy aims at improving the quality of the primary health care provided to children, and in particular, it aims to reduce infant mortality and mortality in children under age five. The strategy also contains a communication component designed to improve awareness in families regarding measures they should take to ensure the harmonious development of their children. In order to improve primary health care services to children, two important measures have been conceived: one, directives for standardized care, “Standards of Supervision of Pregnant Women and Infants under Out-patient Conditions”; and two, in order to track child health and immunizations, a “Card of Development of a Healthy Child” is distributed to the child’s parent or caretaker. Specialized care is provided to children at the Institute of Scientific Research in the section of Protection of Maternal and Infant Health. Family Planning Services. The Ministry of Health and Social Protection is in charge of providing family planning services. The priorities in this domain are to provide family planning information, improve sexual and reproductive health of adults and youth, and prevent domestic violence, sexual abuse, and trafficking of women and children. Under the auspices of the “National Program in Family Planning and Protection of Reproductive Health for the years 1999-2003,” the National Strategy in Reproductive Health, and the National Concept of “Friendly Health Services to the Young,” detailed measures are outlined to promote family planning services, information, education, and communication services, and to counsel the population in repro- ductive health issues. Abortions are legal in Moldova provided that the pregnant woman consents and that the abortion is carried out by a licensed health professional at a hospital or another specialized medical institution. Abortions are therefore not allowed to be carried out in private clinics. Abortions in Moldova may be carried out within the first 12 weeks of pregnancy. After this period, abortions may be carried out up to 28 weeks for outstanding medical, social-economic, or personal reasons, and with a special authorization from a board of local doctors. As of 1996, abortions are paid for by women; the costs of an abortion vary between 7.50 USD and 11.00 USD. State Sanitary Epidemiologic Service. As in other countries, prevention of contagious and non- contagious diseases is a key concern in Moldova. The State Sanitary Epidemiologic Service (SSES) carries out functions relevant to these concerns, including: supervising epidemiologic activities all over the country; drafting statutory acts and guidelines relevant to preventive medicine and epidemiologic measures to protect the population; coordinating and conducting scientific research in preventive medicine; working out measures to combat epidemics in the environment and in the workplace; training and educating the population about health issues; regularly monitoring establishments in areas of increased epidemiologic risk; promoting preventive measures against infectious diseases; ensuring immunization coverage of the population; protecting the country’s borders against the emergence and spread of conventional and extremely contagious diseases; ensuring the safety of the population in case of a nuclear disaster; monitoring public hygiene; and promoting a generally healthy lifestyle. Additionally, the functions of the SSES include conducting bacteriological, virological, serological, immunological, and parasitological laboratory tests, including tests for diagnosing contagious diseases and other tests capable of identifying factors that may adversely influence the population’s health. On an annual basis, the SSES laboratories carry out over a million microbiological, virological, immunological, and parasitological tests and over 250,000 sanitary hygienic laboratory tests, radiological measurements, and tests of physical factors of the life environment. 8 | Introduction The SSES comprises the National Scientific and Practical Center for Preventive Medicine, two municipal Centers for Preventive Medicine (Chisinau and Balti), and 34 district Centers for Preventive Medicine. The joint activity of the SSES with other health institutions and with regional and local public administration authorities has contributed to achieving a stable epidemiological oversight in the country. As a result, there have been no widespread crises of cholera, diphtheria, brucellosis, tetanus, pseudo- tuberculosis, anthrax, tularemia, acute poliomyelitis, congenital rubella, hemorrhagic fevers, rabies, epidemic typhus, vernal tick-born encephalitis, hepatitis E, etc. The incidence of rubella, measles, and viral hepatitis has already been greatly reduced; the incidence of typhoid fever, salmonellas, whooping cough, epidemic parotitis, and scarlet fever is likewise dropping. There have been no serious outbreaks of infectious diseases and toxic infections, nor events of extremely contagious diseases. National Program for Combating Tuberculosis. The National Program for Combating Tuberculosis, adopted by the Government of Moldova, is based on the Directly Observed Treatment Short-course (DOTS) strategy that provides guidelines for the diagnosis, treatment, and monitoring of tuberculosis. This strategy, put forth by the World Health Organization, is being successfully applied in many European countries. The major objectives of National Program are achieved by implementing four components based on the DOTS system, namely: 1) establishing a National Network of Tuberculosis Laboratories to diagnose pulmonary infectious tuberculosis; 2) increasing human resources capacity and disease control services within the general health system, in particular emphasizing early detection of infected persons at the primary health care level and follow-up with curative care; 3) improving tuberculosis prevention; and 4) increasing the degree of public awareness about tuberculosis-related problems. Program implementation started on November 1, 2001 in three pilot zones, including Chisinau and the former districts of Lapusna and Orhei. The program will eventually be implemented throughout the country. A significant batch of medical supplies that covers the needs of hospitals across the country has been purchased with international funds. Diagnostic laboratories have also been equipped with state- of-the-art microscopes, allowing for a more reliable and timely detection of the disease. In 2005, the National Program initiated activities for 2006-2010. These activities include launching DOTS-Plus at penitentiaries, monitoring the long-term treatment of patients with multi-drug- resistant forms of tuberculosis, and developing the Automated Informational System for Monitoring and Follow-Up of Tuberculosis Patients. The prevention of tuberculosis in children is ensured by vaccinating newborns with BCG and revaccinating them at the age of 7 years, as well as promoting preventive treatment for children living in contact with tuberculosis patients. National Program for Combating HIV/AIDS. In 2001, the Government of Moldova adopted the 2001-2005 National Program for Combating HIV/AIDS and Sexually Transmitted Infections. The main objectives of the Program are: • To reduce the prevalence and incidence of HIV and sexually transmitted diseases (STD); and • To strengthen national commitment in conducting prevention activities, providing medical, social, psychological, legal, and rehabilitation assistance to infected persons, and coordinat- ing involvement of nongovernmental agencies in implementing the activities. Furthermore, the National Program cites eight priority strategies: • Formulation of a national policy regarding HIV/AIDS and STD; Introduction | 9 • Prevention of sexually transmitted HIV/AIDS and STD; • Prevention of new cases of HIV/AIDS among drug users; • Prevention of HIV/AIDS and STD among youth; • Prevention of perinatal and mother-to-child HIV transmission; • Health care provision and social support to HIV patients and members of their families; • Ensuring the safety of blood transfusions and medical interventions; • Epidemiological surveillance and monitoring of HIV/AIDS and STD. In order to improve treatment of HIV patients, in 2003, the Republican Dermatologic- Venereologic Dispensary opened a special hospital section with 35 beds, including 5 pediatric beds, for HIV patients. This hospital section follows modern protocols of care and examination of HIV patients and provides them with antiretroviral drugs as well as necessary supplies and equipment. On September 5, 2005, Government Regulation no. 948 approved the National Program of Prevention and Control of the HIV/AIDS Infection and STD for the years 2006-2010, in line with requirements of the European Union. Following this, cooperation between the Ministry of Health and Social Protection and the European Network of Epidemiologic Surveillance of HIV/AIDS was initiated. National Immunization Program. The prevention of transmissible diseases by vaccination is among the most important and cost-effective investments in public health. Timely immunization fosters health and reduces the medical, social, and economic setbacks caused by certain preventable diseases. The first National Immunization Program was approved in Moldova for the years 1994-2000. Its implementation has contributed to the abolishment of poliomyelitis, the halting of diphtheria and mumps epidemics, and to a substantial reduction of the incidence of viral hepatitis B, measles, and whooping cough. The implementation of the second National Immunization Program, for 2001-2005, has enforced wide vaccination coverage, guaranteed the distribution of necessary vaccines, improved the quality of immunization services, and has helped Moldova maintain the status of a polio-free country. In addition, the elimination of native cases of diphtheria, measles, rubella and neonatal tetanus has been achieved, the incidence of hepatitis B, whooping cough, and mumps has diminished significantly, and the incidence of tetanus in adults has been reduced to very few cases. These successes are attributed to the committed activity of medical employees, international assistance granted by entities such as UNICEF, WHO, the governments of the United States and Japan, the Global Alliance for Vaccines and Immunization, and the systematic increase of financial support granted by the Government of Moldova. The National Immunization Program for 2006-2010 guarantees children, and others at risk, immunizations free of charge against ten infectious diseases: poliomyelitis, diphtheria, tetanus, whooping cough, hepatitis B, measles, mumps, rubella, tuberculosis, and hemophilus influenza type B. The Program pursues the following objectives: • Ensuring over 95 percent vaccination coverage, at the national level and at the level of each district and municipality; 10 | Introduction • Maintaining Moldova as a poliomyelitis-free country, and a country free of cases of tetanus in newborns and congenital rubella; • Continued progress towards eliminating cases of measles, rubella, and diphtheria; • Reducing the incidence of: tetanus to less than 0.05 cases per 100,000 population; hepatitis B in children to less than 2 cases per 100,000 population; whooping cough to less than 1.5 cases per 100,000 population; and mumps to less than 6 cases per 100,000 population; • Limiting the cases of child tuberculosis to isolated cases; and • Reducing morbidity and mortality from septic meningitis and pneumonia caused by Hib infection in children under age three. 1.5 HEALTH INFORMATION SYSTEM The National Statistics Bureau is in charge of conducting decennial population censuses and maintaining vital registration data on the population, including births, deaths, marriages, and divorce. These statistics are kept updated by local civil registry offices and submitted regularly to regional statistical authorities. The latter transmits all documents to the National Statistics Bureau for automatic processing. Afterwards, aggregate statistical information is provided to users and to the general public. The Ministry of Informational Development is responsible for keeping records on international migration. The Ministry keeps track of international immigration and emigration during the intercensal period. This information is used by the National Statistics Bureau for population projections and other demographic estimates. Health information is collected by means of regional reports that compile health statistics at regular intervals, from which information is transmitted to the Scientific and Practical Center of Public Health and Health Management (SPCPHHM) of the Ministry Health and Social Protection. The SPCPHHM compiles and analyses these data for publication in annual reports entitled “Public Health in Moldova.” These reports contain morbidity data by type of disease, mortality data by cause of death, infant mortality, including perinatal and neonatal mortality, maternal mortality by cause of death, indicators related to maternal and child health, medical institutions, medical personnel, and average time of hospitalization. These data are tabulated at the national level and by regions. In addition, reports on the incidence of infectious diseases and the administration of vaccinations are submitted and analyzed monthly. The State Sanitary Epidemiologic Service (SSES) issues a separate annual report entitled “Sanitary hygienic and epidemiologic situation in the Republic of Moldova according to the statistic reports of SSES authorities and institutions.” The report addresses activities related to disease prevention and the monitoring and supervision (including laboratory supervision) of the spread of infectious diseases. 1.6 OBJECTIVES AND ORGANIZATION OF THE SURVEY This survey, Moldova’s first Demographic and Health Survey (MDHS), was carried out by the National Scientific and Applied Center for Preventive Medicine (NCPM), of the Ministry of Health and Social Protection. ORC Macro provided technical assistance for the MDHS through the USAID-funded MEASURE DHS program. Local costs of the survey were also supported by USAID, with additional local funding received from the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), and in-kind contributions from the NSACPM. Introduction | 11 Data collection was conducted from June 13 to August 18, 2005. Data were collected from a nationally representative sample of over 11,000 households. All women age 15-49 in these households and all men age 15-59 in a subsample of one-third of the households were eligible to be individually interviewed. In addition to the data collected through interviews with these women and men, capillary blood samples were collected from all women age 15-49 and all children age 6-59 months for anemia testing. The 2005 MDHS is designed to provide data to monitor the population and health situation in Moldova. Specifically, the 2005 MDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections. Additional features of the 2005 MDHS include the collection of information on international emigration, domestic violence, and hemo- globin testing to detect the presence of anemia. The information collected in the 2005 MDHS provides updated estimates of an array of demographic and health indicators that will assist in the development of appropriate policies and programs to address the most important health issues in Moldova. 1.6.1 Sample Design and Implementation The 2005 Moldova Demographic and Health Survey is based on a representative probability sample of over 11,000 households. This sample was designed in such a manner as to allow separate urban and rural estimates for key population and health indicators, e.g., fertility, contraceptive prevalence, and infant mortality for children under five. Transnistria, the semiautonomous region in the eastern part of the country accounting for approximately 15 percent of Moldova’s population, is not included in the sample. The 2005 MDHS utilized a two-stage sample design. The first stage involved selecting a sample of cluster sectors from an updated master sampling frame constructed from the 2004 Moldova Population and Housing Census. A total of 400 clusters in Moldova were selected from the master sampling frame. Clusters for urban and rural domains (233 urban and 167 rural) were selected using systematic sampling with probabilities proportional to their size. The distribution of clusters between urban and rural domains is not proportional to the 2004 census distribution, and consequently neither is the final household distribution. The 2005 MDHS is, therefore, not a self-weighted household sample. A final weighting adjustment procedure was carried out to provide estimates at the national level. A complete household listing operation was carried out from early April to late May 2005 in all of the selected clusters in order to provide a sampling frame for the second stage selection of households. The second stage selection involved the systematic selection of households from a complete listing of all households in each of the 400 clusters. The sample “take” in both urban and rural clusters was 30 households. All women age 15-49 in the total sample of households, and all men age 15-59 in a subsample of one-third of households, who were either usual residents of the households in the MDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed in the survey. 1.6.2 Questionnaires Three questionnaires were used for the 2005 MDHS: the Household Questionnaire, the Women’s Questionnaire and the Men’s Questionnaire. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program. 12 | Introduction Consultations with partners were held in Chisinau to obtain input from various national and international experts on a broad array of issues. Based on these consultations, the DHS model question- naires were modified to reflect issues relevant in Moldova concerning population, women and children’s health, family planning, and other health issues. After approval of the final content by the steering committee, these questionnaires were translated from English into Romanian and Russian. The Household Questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Basic information was collected on the characteristics of each person listed, including their age, sex, education, and relationship to the head of the household. In addition, a separate listing and basic information on former household members who had emigrated abroad was collected. The Household Questionnaire was also designed to collect information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, etc. Finally, height and weight measurements, and the results of hemoglobin measure- ments for consenting women age 15-49 years and children age 6-59 months were recorded in the Household Questionnaire. The Women’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: • background characteristics (education, residential history, media exposure, etc.); • reproductive history; • knowledge and use of family planning methods; • fertility preferences; • antenatal and delivery care; • breastfeeding and infant feeding practices; • vaccinations and childhood illnesses; • marriage and sexual activity; • woman’s work and husband’s background characteristics; • infant and child feeding practices; • childhood mortality; and • awareness and behavior about AIDS and other sexually transmitted infections (STIs). The Women’s Questionnaire had a number of important additions to the DHS model questionnaire. First, a series of questions were incorporated to obtain information on women’s experience of domestic violence. These questions were administered to one woman per household. In households with two or more eligible women, special procedures were followed in order to ensure that there was random selection of the women to be interviewed with these questions. Another addition to the Women’s Questionnaire was a vaccination module for each child under the age of five years to be completed at the local health clinic. According to child health experts, immunization information is more frequently kept at the health clinic than on a health card in the mother’s possession. The purpose of this module was, therefore, to collect information on immunizations from the local health clinic in addition to that collected during the woman’s interview. The vaccination module provides better quality immunization indicators because information gathered during the interview is augmented with information from the local health clinic. Closely related to the Women’s Questionnaire is the caretaker module. This separate module contains the same set of child health questions as those in the Women’s Questionnaire regarding immunizations, childhood illnesses such as fever and diarrhea, and nutrition. The purpose of this module is to gather information on children under age 5 years whose mother does not live in the selected household or is not available to be interviewed. This is important because of the large number of young Introduction | 13 women emigrating and leaving behind a significant number of children to be cared for by another caretaker. The Men’s Questionnaire was administered to all men age 15-59 living in every third household in the MDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, and domestic violence. All aspects of the MDHS data collection were pretested in April 2005. Twenty-six people with medical backgrounds and other specialties were trained for two weeks and then dispatched to conduct interviews in Romanian and Russian, carry out hemoglobin testing, and take height and weight measure- ments. Over 200 households in urban and rural areas were interviewed in the pretest. The lessons learned from the pretest were used to finalize the survey instruments and logistical arrangements. The major changes as a result of the pretest were incorporation of the caretaker module described above and soliciting the assistance of local medical personnel in each cluster to introduce field personnel to selected households. The latter served to improve household response rates, especially in urban areas. 1.6.3 Field Staff and Fieldwork Training of fieldwork staff began on May 16, 2005 in Chisinau and lasted three weeks. A total of 96 training participants were trained as field staff supervisors, editors, and interviewers. In addition, 12 data entry operators and two office editors attended the training. All field staff were also trained as technicians to conduct hemoglobin testing. Most of the participants had a medical background and several had prior experience as interviewers for the UNICEF Multiple Indicator Survey (MICS 2000). Interviewer training was conducted mostly in Romanian by senior staff from NCPM with technical input from ORC Macro. In addition, resource persons from other agencies made presentations on Moldova’s program for family planning, maternal and child health, HIV/AIDS, and gender issues including domestic violence. All participants were trained on interviewing techniques and the contents of the MDHS questionnaires. The training was conducted following the standard DHS training procedures, including class presentations, mock interviews, and written tests. All of the participants were trained on how to complete the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. In addition to in-class training, participants practiced taking anthropometric measures and conducting anemia testing on consenting women and children at local health clinics. They also spent several days in practice field sites interviewing in both languages and carrying out all fieldwork activities. While both female and male interviewers interviewed respondents for the Household Questionnaire, only female interviewers interviewed respondents eligible for the Women’s Questionnaire and only male interviewers for the Men’s Questionnaire. Participants selected as field supervisors and editors were given an additional two days of training on how to supervise fieldwork and edit questionnaires. Fifteen teams were organized for fieldwork. Each team was made up of a field supervisor, an editor, three female interviewers, and one male interviewer. The field staff was selected on the basis of assessments of in-class participation, field practice, fluency in languages, and capacity to conduct interviews as well as anemia testing. The most experienced participants, namely those who had partici- pated in the pretest and those who did very well in the main survey training, were selected to be supervisors and editors. Senior staff from the NCPM coordinated and supervised all aspects of fieldwork activities. ORC Macro followed fieldwork progress by receiving approximately every two weeks a standard set of quality control tables generated from the most recent accumulation of data. Data collection took place for just over two months, from June 13 to August 18, 2005. On average, each team completed one cluster over two full days, taking advantage of early mornings and late evenings to find respondents at home. 14 | Introduction 1.6.4 Data Processing The processing of the MDHS results began shortly after the fieldwork commenced. Completed questionnaires were returned weekly from the field to the NCPM headquarters in Chisinau, where they were entered and edited by data processing personnel who were specially trained for this task. Data were entered using CSPro, a program specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data with ongoing data collection was a distinct advantage for data quality since NCPM had the opportunity to advise field teams of problems detected during the data entry. The data entry and editing phase of the survey was completed in late August 2005. 1.6.5 Response Rates Table 1.1 presents household and individual response rates for the survey. A total of 12,206 households were selected for the sample, of which 11,649 were occupied at the time of fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. Of the occupied households, 95 percent were successfully interviewed. Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence, Moldova 2005 Residence Result Urban Rural Total Household interviews Households selected 7,104 5,102 12,206 Households occupied 6,707 4,942 11,649 Households interviewed 6,227 4,868 11,095 Household response rate 92.8 98.5 95.2 Individual interviews: women Number of eligible women 4,602 3,224 7,826 Number of eligible women interviewed 4,301 3,139 7,440 Eligible women response rate 93.5 97.4 95.1 Individual interviews: men Number of eligible men 1,698 1,199 2,897 Number of eligible men interviewed 1,417 1,091 2,508 Eligible men response rate 83.5 91.0 86.6 In the households interviewed in the survey, a total of 7,826 eligible women age 15-49 were identified; interviews were completed with 7,440 of these women, yielding a response rate of 95 percent. In a subsample of one-third of households in the MDHS sample, a total of 2,897 eligible men were identified and interviews were completed with 2,508 of these men, yielding a male response rate of 87 percent. As is typically found in other surveys, the response rates are lower for the urban than for the rural sample, and lower among men than women. The principal reason for nonresponse among both eligible women and men was the failure to find individuals at home despite repeated visits to the household. Household Population and Housing Characteristics | 15 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 This chapter presents information on the social, economic, and demographic characteristics of the household population, focusing mainly on such background characteristics as age, sex, educational attendance and attainment, place of residence, and socioeconomic conditions of households. The information provided is intended to facilitate interpretation of the key findings in the 2005 MDHS as well as to assist in assessing the representativeness of the survey. A household is defined as a person or group of related and/or unrelated persons who live together in the same dwelling unit, or in connected premises, who acknowledge one adult member as head of the household, and who have common arrangements for preparing and eating their food. The questionnaire for the MDHS distinguishes between the de jure population (persons who usually live in a selected household) and the de facto population (persons who stayed in the household the night before the interview). According to the results, however, the difference between these populations is small. Tabulations based on household data presented in this chapter include both de jure and de facto populations, whereas tabulations in the remainder of the chapters are based primarily on the de facto population. Because of how the sample was designed, weighting procedures were used to ensure that results presented throughout the report are nationally representative, and representative for each study domain (see Appendix A). The numbers in the tables, therefore, reflect weighted numbers. However, the statistical precision of results depends on the actual number of cases covered in the survey, or the unweighted number of cases. When unweighted numbers are insufficient to ensure a high degree of statistical reliability, the values calculated from these numbers are flagged: for example, percentages or proportions based on 25 to 49 unweighted cases are shown in parentheses, and percentages based on fewer than 25 unweighted cases are suppressed with an asterisk. One of the background characteristics used throughout many tables in this report is an index of socioeconomic status, presented as a wealth quintile. This index was developed and tested in a large number of countries in relation to inequities in household income, use of health services, and health outcomes (Rutstein et al., 2000). It is an indicator of the level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The wealth index was constructed by employing a principal components analysis using household asset data. The asset information was collected through the Household Questionnaire of the MDHS 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 for flooring. Each asset was assigned a weight (factor score), generated from the principal components analysis, and the resulting asset scores were standardized in relation to a normal distribution with a mean of zero and standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from one (lowest) to five (highest). A single asset index was developed for the whole sample; separate indices were not prepared for the urban and rural populations. 16 | Household Population and Housing Characteristics 2.1 HOUSEHOLD POPULATION BY AGE AND SEX Age and sex variables are the primary basis of demographic classification in vital statistics, censuses, and surveys. Table 2.1 presents the distribution of the de facto population by five-year age groups, according to urban-rural residence and sex. The information is used to construct the population pyramid shown in Figure 2.1. The total de facto population in households included in the MDHS is 30,491. The data show that 53 percent of the population is female. In absolute numbers, females outnumber males from age 20 onward, and the gender disparity is most pronounced beginning at age 50. The reasons for this imbalance may be attributed to out-migration of men since the early 1990s (see Chapter 15), as well as higher mortality rates of adult men compared with adult women. Table 2.1 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Moldova 2005 Urban Rural Total Age Male Female Total Male Female Total Male Female Total <5 6.1 4.6 5.3 6.4 5.6 6.0 6.3 5.2 5.7 5-9 5.2 4.2 4.7 7.2 6.5 6.8 6.4 5.6 6.0 10-14 7.0 6.5 6.7 10.4 9.0 9.7 9.1 8.0 8.5 15-19 10.2 8.9 9.5 9.2 8.8 9.0 9.6 8.8 9.2 20-24 9.3 9.1 9.2 6.6 6.0 6.3 7.6 7.2 7.4 25-29 8.6 7.0 7.7 5.7 5.3 5.5 6.8 6.0 6.4 30-34 7.2 6.5 6.8 5.1 5.2 5.2 5.9 5.7 5.8 35-39 6.1 6.1 6.1 5.7 5.0 5.3 5.9 5.4 5.6 40-44 6.7 7.0 6.9 6.3 5.9 6.1 6.4 6.3 6.4 45-49 8.0 7.9 8.0 7.3 6.9 7.1 7.6 7.3 7.4 50-54 7.7 8.9 8.4 7.6 7.9 7.8 7.7 8.3 8.0 55-59 5.5 6.7 6.1 6.2 6.5 6.4 5.9 6.6 6.3 60-64 4.2 4.4 4.3 4.3 4.8 4.6 4.3 4.7 4.5 65-69 3.3 4.5 3.9 4.4 5.5 4.9 3.9 5.1 4.6 70-74 2.2 3.1 2.7 3.6 4.6 4.1 3.1 4.0 3.6 75-79 1.6 2.6 2.2 2.4 3.8 3.2 2.1 3.4 2.8 80 + 1.0 2.0 1.5 1.5 2.6 2.1 1.3 2.4 1.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 5,417 6,217 11,637 8,861 9,993 18,854 14,278 16,210 30,491 Sixty-seven percent of household members comprise the economically active population (between ages 15 and 64). This proportion is significantly higher in urban areas (73 percent) than in rural areas (63 percent). The disparity is at least partially explained by rural to urban migration of youth in search of higher education and better job prospects in the city. The remainder of the population that is not economically active, including the younger population under age 15 and the elderly population age 65 and older, constitutes the economically dependent population. Children under age 15 make up 20 percent of the population. Lower fertility levels in the cities ultimately result in a smaller share of children in urban areas: only 17 percent of the population in urban areas is under age 15, versus 23 percent under age 15 in rural areas. Elderly people age 65 and older make up 13 percent of the population. Lower mortality rates for women result in a greater share of elderly women than elderly men: 15 percent of women are age 65 and above, versus only 10 percent of men. Household Population and Housing Characteristics | 17 At a glance, Figure 2.1 reveals a couple of noteworthy patterns. First, relatively large proportions of the population are between age 45 and 55, and between age 10 to 19. The older bulge in the pyramid is evidence of the baby boom generation—those people born in the period of economic prosperity in industrialized countries after World War II. The younger bulge in the pyramid represents, for the most part, the children of the baby boomers. The second notable trend is population aging, obvious from the shape of the pyramid. Compared with previous decades, the so-called pyramid reflecting the present population structure has a smaller base and a less tapered top, thus resembling a rectangular form more than a pyramid. This is evidence of population aging, which is the predominant trend in most countries in Europe, especially in Eastern Europe. Given persistently low fertility, below replacement level and, to a lesser extent, increases in average life expectancy,1 it is likely that the proportion of elderly will continue to become larger and eventually surpass the proportion of young people. The effect of out-migration, which is selective of young people in their reproductive years, serves to speed the aging process of the overall population structure still further. 2.2 HOUSEHOLD COMPOSITION Table 2.2 presents the distribution of households by sex of the head of household and by the household size, for urban and rural areas. The characteristics are of interest because they are often associated with differences in household socioeconomic levels. For example, female-headed households are frequently poorer than households headed by males. Indeed, official data from the Moldova State Department of Statistics reports that, in 2004, 76 percent of households headed by men had a good or satisfactory level of living, compared with 67 percent of households headed by women (MSDS, 2005). 1 Official estimates of life expectancy in 2000 were 71 years for women and 64 years for men; in 2004, they were 72 years for women and 65 years for men (MSDS, 2005). Moldova 2005 Figure 2.1 Population Pyramid 80 + 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 <5 Age 0246810 0 2 4 6 8 10 Males Females Percent 18 | Household Population and Housing Characteristics Data from the MDHS show that, at the national level, women head 34 percent of Moldovan households; this percentage differs modestly be- tween urban and rural areas (38 percent and 31 percent, respectively). Results further show that the average household size in Moldova is 2.8, and that there is little difference in the average size of urban households and rural households. 2.3 CHILDREN’S LIVING ARRANGEMENTS Children not living with their natural parents are more likely to be disadvantaged compared with those who do live with their parents; they may be at increased risk of impoverishment, deprived of prop- erty rights and other rights, and at increased risk of abuse, neglect, and exploitation. The MDHS col- lected detailed information on children’s living ar- rangements. Table 2.3 shows the percent distribution of children under age 15 by their living arrange- ments and survival status of parents, according to background characteristics. Just over two-thirds (69 percent) of children under age 15 live with both parents. Fifteen percent live with just their mother although their father is alive, 5 percent live with just their father although their mother is alive, and 7 percent live with neither parent although both are alive. These children are “social orphans,” that is, their biological parents are still alive but they have been voluntarily left in the care of another person, or persons.2 Results show that just 3 percent of children under age 15 have lost their father only, 1 percent have lost their mother only, and only a tiny fraction have lost both biological parents. Altogether, 3 percent of children under age 15 have at least one parent who died. 2 These indicators do not take into account children who live outside the household—for example, in institutions or on the street—because the MDHS includes only households in its sample. Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, according to residence, Moldova 2005 Residence Characteristic Urban Rural Total Sex of head of household Male 61.8 69.2 66.3 Female 38.1 30.8 33.7 Total 100.0 100.0 100.0 Number of usual members 1 18.7 20.8 20.0 2 27.4 27.0 27.1 3 26.4 19.2 22.0 4 18.8 18.1 18.4 5 5.5 9.2 7.7 6+ 2.7 5.6 4.5 Missing 0.5 0.1 0.3 Total 100.0 100.0 100.0 Number of households 4,444 6,651 11,095 Mean size 2.7 2.9 2.8 Note: Table is based on de jure members, i.e., usual residents. Household Population and Housing Characteristics | 19 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, Moldova 2005 Not living with either parent Living with mother but not father Living with father but not mother Background characteristic Living with both parents Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing information on father/ mother Total Number of children Age <2 81.7 13.8 0.2 0.7 0.3 2.7 0.0 0.0 0.0 0.6 100.0 684 2-4 70.3 16.5 0.9 3.0 0.2 7.9 0.1 0.0 0.0 1.0 100.0 1,019 5-9 66.1 16.3 1.8 4.4 0.3 8.3 0.3 0.4 0.1 1.9 100.0 1,817 10-14 66.8 13.8 3.4 6.0 0.6 6.1 0.4 0.6 0.3 2.0 100.0 2,622 Sex Male 67.7 16.2 2.5 5.0 0.6 5.8 0.2 0.1 0.2 1.8 100.0 3,143 Female 70.1 13.7 1.8 3.9 0.2 7.6 0.4 0.6 0.1 1.6 100.0 3,000 Residence Urban 67.0 17.7 2.4 3.9 0.3 5.5 0.1 0.4 0.1 2.5 100.0 2,061 Rural 69.8 13.6 2.0 4.7 0.4 7.3 0.4 0.4 0.2 1.3 100.0 4,082 Region North 68.6 15.7 2.3 4.3 0.2 6.9 0.3 0.5 0.2 1.0 100.0 1,792 Center 69.6 13.1 2.2 4.6 0.8 7.9 0.2 0.2 0.2 1.1 100.0 1,881 South 67.7 14.3 1.8 5.4 0.2 7.1 0.6 0.6 0.1 2.0 100.0 1,334 Chisinau 69.4 17.6 2.0 3.3 0.3 3.7 0.1 0.3 0.1 3.3 100.0 1,135 Wealth quintile Lowest 72.6 14.1 2.3 2.6 1.1 4.9 0.2 0.7 0.2 1.2 100.0 1,322 Second 66.8 14.2 2.5 5.1 0.2 8.4 0.7 0.4 0.2 1.5 100.0 1,241 Middle 67.0 13.9 2.1 6.3 0.1 8.2 0.1 0.4 0.3 1.6 100.0 1,346 Fourth 65.7 16.5 1.9 4.9 0.3 7.9 0.4 0.2 0.1 2.1 100.0 1,193 Highest 72.7 16.6 1.8 3.1 0.1 3.5 0.1 0.2 0.0 2.0 100.0 1,041 Total 68.9 15.0 2.1 4.5 0.4 6.7 0.3 0.4 0.2 1.7 100.0 6,143 Table 2.4 presents information on residence of mothers and fathers who live separately from their children under age 15. Figure 2.2 shows that three-quarters of mothers of children under 15 who are not living in the same household as their child(ren) are living abroad (76 percent). About one-fifth of mothers live in another household in Moldova (19 percent). Figure 2.2 also shows that about half of fathers who are not living in the same household as their child(ren) are living abroad (46 percent), and about the same proportion are living in another household in Moldova. It should be kept in mind, however, that in absolute numbers, almost twice as many fathers as mothers do not live with their children. Therefore, although a smaller proportion of fathers live abroad than mothers, the number of fathers living abroad surpasses the number of mothers living abroad. Table 2.4 Parental residence apart from children Among children under age 15 whose mothers and fathers are alive but not living in the same household, percent distribution by residence of parent, Moldova 2005 Residence Mother Father Abroad 75.9 45.7 In other household in Moldova 19.3 46.4 Institution 0.0 0.9 Don't know 2.2 4.7 Missing 2.6 2.3 Total 100.0 100.0 Number 720 1,341 20 | Household Population and Housing Characteristics Compared to living arrangements of children in 2000, the proportion of children not living with their parents has increased. In 2000, 84 percent of children under age 15 lived with both parents. Ten percent lived with just their mother, although their father was alive; 3 percent lived with just their father, although their mother was alive; and 2 percent lived with neither parent. Altogether, 4 percent of children under age 15 had at least one parent who had died (MICS 2000). Although the values from 2000 were estimated from a sample including the region of Transnistria, the differences are large enough to at least conclude an increase, and probably a substantial one, in the proportion of children not living with their parents. Further research, as well as program development for children in Moldova who are left behind by migrating parents, is under way; because this trend appears to be on the rise, it merits close attention (see, for example, Bacalu, 2004; Dubrovschi, 2004; Ghencea and Gugumac, 2004; Gonta, 2004; and Salaru, 2004). Not only have children’s living arrangements deteriorated since 2000, but they are also among the worst in the region. Compared with estimates from recent Demographic and Health Surveys conducted in other countries in Eastern Europe and Eurasia, fewer children live with both of their parents in Moldova than in other countries in the region: in Armenia (1999), 10 percent of children age 0-15 are not living with both mother and father; in Kazakhstan (1999), 19 percent; in Kyrgyz Republic (1997), 15 percent; in Turkmenistan (2000), 12 percent; and in Uzbekistan, 7 percent (ORC Macro, 2005). 2.4 EDUCATIONAL ATTAINMENT OF HOUSEHOLD MEMBERS Moldova’s education system, until independence in 1991, followed the same structure as the Soviet educational system. In the past 15 years, however, the system has undergone several reforms, making the analysis of education data across a wide range of ages challenging. Basically, Moldova’s primary and secondary educational system has three components. The first component is primary school and comprises grades 1-4 (usually children age 8 to 11, but some children start younger). The second component is secondary school and comprises grades 5-9 (usually children age 12 to 16, but some children start younger), or grades 5-12. Students who have completed a total of at least 9 grades are considered to have fully completed compulsory education. The third component is secondary special Figure 2.2 Living Arrangements of Mothers and Fathers Not Living in Household Interviewed MDHS 2005 MOTHER FATHER Abroad 76% Missing 3% Other household 19% Don’t know 2% Abroad 46% Institution 1% Missing 2% Don’t know 5% Other household 46% Household Population and Housing Characteristics | 21 education. Secondary special education is an alternative for students who have completed a total of at least 9 years of schooling; at this stage, a student may opt to follow secondary special education that is specialized technical training in a specific field such as nursing, agriculture, construction, etc. Secondary special education usually lasts 2-3 years and, when successfully completed, the student is considered qualified to work in that specific field. Students who have successfully completed a total of 12 years of schooling (primary and secondary education), or who have completed primary schooling plus a secondary special education, are qualified to attend university. Table 2.5 shows the percent distribution of the female and male household population age 7 and older, by highest level of education attained and according to background characteristics. Only a tiny fraction have no education. Furthermore, by age group 15-19, virtually all females and all males have attended or completed secondary or secondary special education. In the oldest age groups, age 65 and above, about one-third have attended or completed only primary education. This finding—that education levels are significantly lower amongst those age 65 and above—provides evidence of the rapid improve- ments in the education system following the Second World War. Overall, relatively more people have opted to pursue secondary education (65 percent of males and 56 percent of females) versus secondary special education (10 percent of males and 15 percent of females). This is especially the case for the age group 15-19, where, for both sexes, 86 percent have reached secondary school versus only about 5 percent who have attended secondary special school. In terms of the highest level of education, the data show that women are slightly more likely than men to attend university. Overall, 13 percent of males and 15 percent of females have at least some university education. This difference is largest in younger generations; for example, for the age group 20-24, 40 percent of women versus 30 percent of men have at least some higher education. 22 | Household Population and Housing Characteristics Table 2.5 Educational attainment of household population Percent distribution of the de facto female and male household population by highest level of education attended or completed, according to background characteristics, Moldova 2005 Background characteristic No education Primary Secondary Secondary special Higher Total Number MALE Age 7-9 1.0 97.6 1.2 0.2 0.0 100.0 382 10-14 1.8 31.3 66.8 0.1 0.0 100.0 1,302 15-19 1.0 2.2 86.2 5.3 5.3 100.0 1,370 20-24 0.4 1.6 61.6 6.8 29.6 100.0 1,090 25-29 0.8 0.2 64.6 9.5 24.8 100.0 976 30-34 0.9 0.4 66.5 15.4 16.5 100.0 842 35-39 0.3 0.1 70.8 14.5 14.1 100.0 836 40-44 0.7 0.3 67.5 15.8 15.3 100.0 921 45-49 0.5 0.4 70.1 15.0 13.9 100.0 1,084 50-54 0.5 0.5 67.3 16.2 15.5 100.0 1,094 55-59 0.3 1.1 65.9 17.8 14.8 100.0 849 60-64 0.6 5.1 63.8 13.6 16.7 100.0 610 65+ 3.0 30.3 49.2 8.1 9.5 100.0 1,486 Residence Urban 0.8 6.3 53.1 14.3 25.5 100.0 4,916 Rural 1.2 13.0 71.9 7.9 5.9 100.0 7,926 Region North 1.4 11.7 66.3 11.5 8.8 100.0 3,913 Center 1.0 11.4 71.9 7.4 8.3 100.0 3,619 South 0.9 12.6 68.6 9.9 8.0 100.0 2,564 Chisinau 0.5 5.3 49.2 13.1 31.7 100.0 2,746 Wealth quintile Lowest 1.8 17.5 76.0 3.5 1.2 100.0 2,607 Second 1.6 13.4 74.7 7.2 3.1 100.0 2,565 Middle 0.9 9.1 70.1 11.1 8.7 100.0 2,575 Fourth 0.5 7.6 57.4 15.8 18.5 100.0 2,550 Highest 0.2 4.3 44.8 14.3 36.1 100.0 2,545 Total1 1.0 10.4 64.7 10.4 13.4 100.0 12,842 FEMALE Age 7-9 0.9 98.8 0.2 0.0 0.0 100.0 376 10-14 0.4 31.7 67.9 0.1 0.0 100.0 1,302 15-19 0.5 0.2 85.9 5.6 7.9 100.0 1,434 20-24 0.4 0.5 49.4 10.0 39.7 100.0 1,166 25-29 0.8 0.5 60.1 13.1 25.3 100.0 968 30-34 0.4 0.7 54.9 23.0 21.0 100.0 926 35-39 0.5 0.4 52.9 27.4 18.7 100.0 878 40-44 0.1 0.4 55.1 25.0 19.3 100.0 1,027 45-49 0.0 0.2 58.5 25.0 16.2 100.0 1,186 50-54 0.6 0.7 61.6 23.4 13.5 100.0 1,339 55-59 0.6 1.6 58.5 23.0 16.1 100.0 1,067 60-64 0.9 10.9 63.6 12.5 12.0 100.0 755 65+ 11.6 39.3 34.1 7.9 6.5 100.0 2,411 Residence Urban 1.5 7.5 46.0 19.4 25.3 100.0 5,790 Rural 2.8 15.9 61.8 11.6 7.8 100.0 9,047 Region North 3.3 15.1 56.3 14.9 10.3 100.0 4,772 Center 2.1 13.8 62.9 12.3 8.9 100.0 3,994 South 2.7 14.2 59.1 13.7 10.1 100.0 2,821 Chisinau 0.8 6.0 42.8 18.1 32.1 100.0 3,250 Wealth quintile Lowest 4.6 21.6 66.9 5.1 1.6 100.0 3,000 Second 3.5 16.8 65.0 10.0 4.5 100.0 3,044 Middle 1.8 11.3 58.4 16.9 11.4 100.0 2,926 Fourth 1.1 7.9 48.8 21.0 21.0 100.0 2,983 Highest 0.3 5.0 38.3 20.7 35.6 100.0 2,884 Total1 2.3 12.6 55.6 14.7 14.6 100.0 14,837 Note: Primary school includes grades 1-4; secondary school includes grades 5-12. 1 Totals include undetermined/missing cases Household Population and Housing Characteristics | 23 2.5 HOUSING CHARACTERISTICS To assess the socioeconomic conditions under which the population lives, respondents were asked to give specific information about their house- hold environment. Some of these characteristics, such as housing construction material, water source, and sanitation facilities, are used to calculate the wealth index (see beginning of this chapter). Table 2.6 presents some of the major household character- istics, by urban and rural residence. Access to electricity is almost universal for households in Moldova. In terms of construction material, the largest share of households in rural and urban areas have polished wooden (parquet) floors, and a further 11 percent in urban areas and one- quarter of households in rural areas have wooden planks on the floor. The next most common floor material is vinyl or asphalt strips in urban households (33 percent) and ceramic tiles or cement in rural households (11 percent). The main roofing material is calamine/cement fiber, followed by cement, which together accounts for 92 percent of all households. The material most often used for walls in urban areas is cement or limestone (80 percent), and almost half of all households in rural areas are constructed using adobe with sod (47 percent). Overcrowding in households does not seem to be a problem in Moldova since 92 percent of households sleep only one or two persons per room. Gas is the main cooking fuel used. About 40 percent of all households use bottled gas and almost as many use natural gas, with urban households using mainly natural gas (75 percent) and rural households using mainly bottled gas (60 percent). Safe drinking water is a basic necessity for good health. Thirty percent of households in Moldova have water piped directly to their household (another 6 percent have water piped to their yard), and about half of households in Moldova obtain water from a protected well (48 percent). Large discrepancies are noted between urban and rural households; two-thirds of urban households have water piped directly into the home, while over two- thirds of rural households have water from a protected well. Table 2.6 Household characteristics Percent distribution of households by household character- istics, according to residence, Moldova 2005 Residence Household characteristic Urban Rural Total Electricity Yes 99.4 98.0 98.6 No 0.5 1.9 1.3 Total1 100.0 100.0 100.0 Main floor material Earth, sand 0.9 8.4 5.4 Wood planks 11.4 24.0 19.0 Parquet, polished wood 46.8 45.3 45.9 Vinyl, asphalt strips 33.3 8.0 18.1 Ceramic tiles/cement 4.1 11.2 8.3 Carpet 3.3 3.0 3.1 Total1 100.0 100.0 100.0 Main roof material Calamine/cement fiber 40.8 87.8 69.0 Cement 54.1 1.9 22.8 Ceramic tiles 2.8 6.6 5.1 Metal 0.9 2.6 1.9 Other 1.1 1.0 1.0 Total1 100.0 100.0 100.0 Main wall material Cement 36.2 2.5 16.0 Stone with lime/cement 43.9 32.3 36.9 Adobe with sod 12.3 46.9 33.1 Bricks 4.7 4.6 4.7 Cement blocks 2.1 11.9 8.0 Other 0.4 9.8 1.2 Total1 100.0 100.0 100.0 Persons per sleeping room 1-2 90.7 92.5 91.8 3-4 8.2 6.3 7.0 5+ 0.5 0.6 0.6 No bedrooms/missing 0.6 0.7 0.7 Total 100.0 100.0 100.0 Mean number of persons per sleeping room 1.4 1.3 1.4 Type of cooking fuel Electricity 5.3 1.2 2.9 Bottled gas (LPG) 18.3 59.7 43.1 Natural gas 74.8 14.9 38.9 Wood 0.8 14.0 8.7 Straw/shrubs/grass 0.2 4.5 2.8 Agricultural crop 0.1 5.0 3.0 Other 0.3 0.8 0.6 Total1 100.0 100.0 100.0 Source of drinking water Piped into dwelling 66.7 4.9 29.6 Protected well 16.3 69.4 48.1 Piped to yard/plot 6.2 6.5 6.4 Unprotected well 0.9 7.3 4.8 Bottled water 5.7 0.4 2.5 Protected spring 1.5 4.3 3.1 Other 2.5 7.3 5.4 Total1 100.0 100.0 100.0 Continued. 24 | Household Population and Housing Characteristics The population accessing safe drinking water is represented by the following sources: piped into the dwelling or yard; protected well; protected spring; and bottled water. Overall, 90 percent of the population has access to safe drinking water, with 86 percent in rural areas and 96 percent in urban areas. About 92 percent of households reported having suf- ficiently available potable water last year. Adequate personal hygiene and disposal of human excreta is associated with less risk of contact- ing certain diseases such as diarrhea and worms. Adequate means of excreta disposal include the following: flush toilets connected to a sewage system or septic tank, other flush toilets, and improved pit latrines (with ventilation and/or a concrete slab). Overall, 77 percent of households in Moldova have adequate means of sanitary disposal, with 91 percent of households in urban areas and only 67 percent in rural areas. Six percent of households share their sanitary facility with another household. As expected, ownership of arable land is more common in rural areas than in urban areas—90 percent of households in rural areas versus 34 percent in urban areas. Among households in urban areas that own land, most own 10 ari or less. In contrast, land owners from rural areas own much larger plots. Households in rural areas are also more likely to own livestock or farm animals (87 percent) than are urban households (23 percent). Twelve percent of households reported hav- ing a bank account, but about four times as many households in urban areas as in rural areas have bank accounts (21 percent and 6 percent, respectively). The distribution of households by wealth quintiles shows that a small share of households in the lowest and second wealth quintile are located in urban areas (7 percent), and an even smaller share of households in rural areas are located in the highest wealth quintile (about 1 percent). 2.6 HOUSEHOLD DURABLE GOODS The possession of durable goods is a rough measure of household socioeconomic status. Table 2.7 shows the percentage of households possessing various durable goods by urban-rural residence. The most commonly possessed items from the list of 18 items are a sofa and armoire (98 percent for both items). Roughly three-quarters of households have a radio (72 percent) and/or refrigerator (76 percent); about two-thirds have a color television (69 percent) and/or fixed telephone (67 percent); and about one- Table 2.6—Continued Residence Household characteristic Urban Rural Total Sufficient potable water last year Yes 92.2 91.4 91.7 No 7.7 8.4 8.1 Water source too far 2.0 4.5 3.5 Costs too much 0.4 0.4 0.4 Limited quantity available/water rationed 4.5 2.7 3.4 Drought 0.1 0.3 0.2 Other 0.7 0.5 0.6 Total1 100.0 100.0 100.0 Sanitation facility Flush - to piped sewer system 70.3 3.8 30.4 Pit latrine - ventilated improved pit (VIP) 11.3 31.2 23.2 Pit latrine - with slab 9.5 32.4 23.2 Pit latrine - without slab / open pit 7.7 21.8 16.1 Composting toilet 0.8 9.7 6.1 Other 0.4 1.2 0.8 Total1 100.0 100.0 100.0 Share toilet with other households Yes 8.0 5.4 6.4 No 91.7 93.3 92.6 Total1 100.0 100.0 100.0 Land usable for agriculture Does not own any land 65.7 10.1 32.4 1-9 ari 18.8 3.1 9.4 10-49 ari 9.8 37.9 26.6 50-99 ari 1.0 12.0 7.6 1-9 hectares 3.9 36.0 23.1 10+ hectares 0.2 0.5 0.4 Total1 100.0 100.0 100.0 Livestock, herds, or farm animals Yes 23.2 87.2 61.6 No 76.7 12.7 38.3 Total1 100.0 100.0 100.0 Bank account Yes 21.0 6.1 12.1 No 78.4 93.4 87.4 Total1 100.0 100.0 100.0 Wealth quintile Lowest 1.8 33.9 21.1 Second 5.6 32.0 21.4 Middle 11.1 22.5 18.0 Fourth 34.3 10.3 19.9 Highest 47.1 1.3 19.6 Total 100.0 100.0 100.0 Number of households 4,444 6,651 11,095 1 Totals include the undetermined cases. Household Population and Housing Characteristics | 25 third (31 percent) have a mobile telephone. Over half of households have a washing machine, while 41 percent have a vacuum cleaner and the same proportion have a bathtub or shower. Roughly one-quarter of households own a VCR/DVD (27 percent), bicycle (27 percent), and/or a car or truck (23 percent). Fewer than 10 percent of households have a computer (7 percent) and a microwave (9 percent), although these percentages are higher in urban areas (15 percent and 13 percent, respectively). The share of households possessing any durable good is almost always higher in urban areas than rural areas, except for black and white television, radio, bicycle, and motorcycle. It is possible that, in lower income households, these items are owned instead of a color television or a car or truck. Fewer than 1 percent of households have none of the items mentioned. Table 2.7 Household durable goods Percentage of households possessing various durable consumer goods, by residence, Moldova 2005 Residence Durable consumer goods Urban Rural Total Radio 70.4 73.0 72.0 Television 86.4 58.1 69.4 Black-white TV 13.1 27.8 21.9 VCR/DVD 37.3 19.6 26.7 Fixed telephone 87.5 52.7 66.7 Mobile telephone 50.7 17.5 30.8 Computer 14.5 2.1 7.0 Refrigerator 91.2 65.0 75.5 Microwave 13.2 6.3 9.0 Vacuum cleaner 67.7 23.3 41.1 Washing machine 72.5 45.6 56.4 Water heat 29.3 6.6 15.7 Bathtub/shower 73.3 20.1 41.4 Sofa 98.9 96.6 97.5 Armoire 98.7 96.7 97.5 Bicycle 25.5 28.3 27.2 Motorcycle 2.7 7.9 5.8 Car/truck 28.2 18.7 22.5 None of the above 0.2 0.7 0.5 Number of households 4,444 6,651 11,095 Characteristics of Respondents | 27 CHARACTERISTICS OF SURVEY RESPONDENTS 3 3.1 BACKGROUND CHARACTERISTICS OF RESPONDENTS Information on the basic characteristics of women and men interviewed in the survey is important for interpreting findings presented later in the report. Background characteristics of the 7,440 women and 2,508 men interviewed in the Moldova Demographic and Health Survey (MDHS) are presented in Table 3.1. For both sexes, there are proportionally more respondents in age groups 15-19 and 45-49 (and also 45-54 for men), whereas there are proportionally fewer respondents in age groups 25-44. This U-shaped distribution of the MDHS sample reflects the aging baby boom cohort following World War II (the youngest of the baby boomers are now in their mid-40s), and their children, who are now mostly in their teens and 20s. The lower proportions of women and men in the middle age groups reflect the smaller cohorts following the baby boom generation and preceding the generation of baby boomer’s children. To some degree, it also reflects the disproportionately higher emigration of the working age population (see Chapter 15). More women and men live in rural areas than urban areas, and there is little difference in the distribution of women and men by urban-rural residence (57 percent of women and 58 percent of men live in rural areas). The smallest proportion of women and men, about one-fifth, are from the South region. Two-thirds of women and men are married or living together (66 percent). Because men tend to marry later in life than women, 29 percent of the surveyed men age 15-59 have never married, compared to a quarter of the women age 15-49. On the other hand, women are more likely than men to be divorced or separated (7 percent versus 4 percent). Very few women (2 percent) and men (1 percent) are widowed. Women and men in Moldova are universally well educated, with virtually 100 percent having at least some secondary or higher education: 79 percent of women and 83 percent of men have only a secondary or secondary special education,1 and the remainder pursue a higher education. More women (21 percent) than men (16 percent) pursue higher education. While most respondents in the MDHS are ethnic Moldovans and follow the Orthodox religion, there is more variation in ethnicity than in religion. Most women and men in Moldova are ethnic Moldovans (77 percent and 76 percent, respectively), followed by Ukrainians (8 percent of women and 9 of percent men), Russians (6 percent of women and men), and Gagauzans (4 percent of women and 5 percent of men). Romanians and Bulgarians account for 2 to 3 percent of women and men. The overwhelming majority of Moldovans, about 95 percent, report Orthodox as their religion. Between 1 and 4 percent of women and men are Jewish, Protestant, or another religion. 1 “Secondary special” education is specialized technical training in a specific field such as nursing, agriculture, construction, etc. 28 | Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men, by selected background characteristics, Moldova 2005 Women Men Background characteristic Weighted percent Weighted Unweighted Weighted percent Weighted Unweighted Age 15-19 19.0 1,417 1,403 16.4 411 411 20-24 15.1 1,124 1,145 11.0 275 287 25-29 13.0 964 964 9.3 234 241 30-34 12.4 924 918 8.9 224 228 35-39 11.5 855 859 9.9 248 247 40-44 13.5 1,007 1,001 9.9 247 242 45-49 15.4 1,149 1,150 13.9 349 340 50-54 na na na 11.8 296 293 55-59 na na na 8.9 224 219 Marital status Never married 25.0 1,862 1,884 29.1 730 745 Married 61.4 4,565 4,486 62.7 1,573 1,561 Living together 5.0 372 406 3.4 85 83 Divorced/separated 6.8 509 532 3.9 98 99 Widowed 1.8 132 132 0.9 22 20 Residence Urban 42.9 3,194 4,301 42.0 1,055 1,417 Rural 57.1 4,246 3,139 58.0 1,453 1,091 Region North 29.7 2,207 2,065 30.2 756 700 Center 27.3 2,033 1,805 28.0 702 633 South 18.9 1,402 1,443 19.8 496 518 Chisinau 24.2 1,798 2,127 22.1 554 657 Education No education/primary 0.6 49 49 0.6 16 14 Secondary 60.9 4,534 4,332 71.3 1,788 1,713 Secondary special 17.8 1,327 1,372 12.0 302 317 Higher 20.6 1,530 1,686 16.1 403 464 Religion Orthodox 94.5 7,030 6,991 93.7 2,351 2,341 Protestant (ex. Evangelical, Baptist, Jehovah witness) 2.9 217 245 1.9 47 48 Jewish 0.5 40 37 3.7 94 100 Other 2.0 152 165 0.7 16 18 Ethnic group Moldovan 77.0 5,727 5,515 75.6 1,896 1,830 Romanian 2.2 167 178 2.5 62 74 Ukrainian 7.9 586 597 8.5 212 207 Russian 6.1 457 563 5.6 140 168 Gagauzan 3.8 283 329 4.5 114 134 Bulgarian 1.9 144 166 2.1 53 62 Other 1.0 77 92 1.1 29 33 Total 100.0 7,440 7,440 100.0 2,508 2,508 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Respondents | 29 3.2 EDUCATIONAL LEVEL OF RESPONDENTS Tables 3.2.1 and 3.2.2 present the distributions of female and male respondents, respectively, by the highest level of education attended, according to age, urban-rural residence, region, and wealth quintile. Virtually 100 percent of men and women interviewed have attended secondary school. The great majority of women and men have only attended secondary or secondary special schools (79 percent of women and 83 percent of men); however, secondary special education has become a much less popular option for the youngest respondents (age 15-24). The youngest respondents are also more likely to attend university than respondents in older cohorts: in age group 20-24, 40 percent of women and 32 percent of men have at least some university education, compared with 12 to 25 percent for respondents in every other age category. Table 3.2.1 Educational attainment by background characteristics: women Percent distribution of women by highest level of schooling attended or completed, and median number of years of schooling completed, according to background characteristics, Moldova 2005 Educational attainment Background characteristic No education Primary Secondary Secondary special Higher Total Number Median years of schooling Age 15-19 0.1 0.2 86.7 5.4 7.7 100.0 1,417 9.3 20-24 0.1 0.5 49.6 9.4 40.4 100.0 1,124 11.0 25-29 0.5 0.5 60.3 13.7 25.0 100.0 964 10.6 30-34 0.1 1.1 54.0 23.8 21.1 100.0 924 11.0 35-39 0.2 0.2 52.9 27.9 18.9 100.0 855 11.0 40-44 0.5 0.5 55.0 25.5 18.6 100.0 1,007 10.7 45-49 0.3 0.2 57.5 26.1 16.0 100.0 1,149 10.3 Residence Urban 0.3 0.4 47.1 20.2 32.0 100.0 3,194 11.4 Rural 0.2 0.5 71.4 16.1 11.9 100.0 4,246 9.8 Region North 0.5 0.4 62.7 20.2 16.2 100.0 2,207 10.2 Center 0.2 0.5 71.1 14.9 13.2 100.0 2,033 9.8 South 0.1 0.4 66.3 18.9 14.3 100.0 1,402 10.0 Chisinau 0.1 0.3 43.1 17.4 39.1 100.0 1,798 11.8 Wealth quintile Lowest 0.3 0.8 88.6 7.5 2.8 100.0 1,243 9.2 Second 0.4 0.7 77.6 14.2 7.1 100.0 1,234 9.6 Middle 0.4 0.2 64.0 20.2 15.2 100.0 1,511 10.2 Fourth 0.1 0.4 50.0 23.3 26.2 100.0 1,672 11.2 Highest 0.0 0.2 37.7 20.5 41.5 100.0 1,780 12.2 Total 0.2 0.4 60.9 17.8 20.6 100.0 7,440 10.3 In general, respondents of either sex who opted to attend secondary school are mostly from rural areas, while those who attended secondary special school are mostly from urban areas. Roughly three times as many urban than rural respondents have attended university and at least 40 percent of those from households in the wealthiest quintile have attended university (42 percent of women and 40 percent of men). 30 | Characteristics of Respondents Table 3.2.2 Educational attainment by background characteristics: men Percent distribution of men by highest level of schooling attended or completed, and median number of years of schooling completed, according to background characteristics, Moldova 2005 Educational attainment Background characteristic No education Primary Secondary Secondary special Higher Total Number Median years of schooling Age 15-19 0.0 1.7 86.7 4.9 6.7 100.0 411 9.1 20-24 0.0 0.0 61.7 6.4 31.9 100.0 275 10.4 25-29 0.0 0.0 63.8 10.5 25.7 100.0 234 10.8 30-34 0.3 0.4 68.6 16.9 13.8 100.0 224 10.7 35-39 0.0 0.0 73.3 10.9 15.8 100.0 248 10.2 40-44 0.6 0.6 66.7 16.4 15.6 100.0 247 10.8 45-49 0.3 0.5 73.6 13.1 12.4 100.0 349 10.0 50-54 0.0 0.2 69.7 16.7 13.5 100.0 296 10.2 55-59 0.0 0.5 66.4 17.3 15.7 100.0 224 10.0 Residence Urban 0.1 0.3 56.1 14.8 28.8 100.0 1,055 11.0 Rural 0.2 0.7 82.3 10.0 6.8 100.0 1,453 9.7 Region North 0.1 0.5 76.2 12.8 10.5 100.0 756 9.9 Center 0.2 1.0 78.9 9.4 10.5 100.0 702 9.7 South 0.2 0.2 76.6 13.0 10.0 100.0 496 9.8 Chisinau 0.0 0.1 50.2 13.5 36.1 100.0 554 11.4 Wealth quintile Lowest 0.7 2.1 91.4 4.8 0.9 100.0 450 9.3 Second 0.0 0.0 87.1 9.2 3.7 100.0 470 9.6 Middle 0.0 0.4 78.5 13.1 8.0 100.0 464 10.0 Fourth 0.0 0.3 62.9 15.5 21.4 100.0 561 10.6 Highest 0.0 0.0 44.4 15.8 39.8 100.0 563 11.8 Total 0.1 0.5 71.3 12.0 16.1 100.0 2,508 10.0 The median number of years of school completed for women and men in Moldova is 10 years. Respondents from urban areas and Chisinau have an additional year of schooling, and respondents from the wealthiest households have the greatest educational advantage, with a median of 12 years of schooling. 3.3 EXPOSURE TO MASS MEDIA Access to information is essential in increasing people’s knowledge and awareness of what is taking place around them, and may eventually affect their perceptions and behavior. In the survey, exposure to media was assessed by asking respondents how often they read a newspaper, watched television, or listened to the radio. Knowing the types of persons who are more or less likely to be reached by the media is important for purposes of planning programs intended to spread information about health or other issues related to the general welfare of the population. Tables 3.3.1 and 3.3.2 show the percentage of female and male respondents, respectively, with access to the various media by age, urban-rural resi- dence, region, educational levels, and wealth quintile. Characteristics of Respondents | 31 Table 3.3.1 Exposure to mass media: women Percentage of women who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Moldova 2005 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week All three media No media Number Age 15-19 60.5 92.9 84.4 52.2 1.9 1,417 20-24 58.0 93.0 80.0 48.3 1.9 1,124 25-29 53.5 93.1 75.1 43.0 3.1 964 30-34 59.4 92.1 74.1 47.8 4.1 924 35-39 57.3 91.9 74.3 47.0 4.1 855 40-44 54.7 91.8 71.5 43.5 4.6 1,007 45-49 50.0 89.6 70.3 38.7 5.4 1,149 Residence Urban 64.9 95.6 76.4 52.5 1.6 3,194 Rural 49.8 89.4 76.0 41.1 4.9 4,246 Region North 55.1 92.6 76.5 43.9 2.6 2,207 Center 48.4 88.2 75.0 41.2 6.3 2,033 South 55.8 90.9 74.7 45.3 4.4 1,402 Chisinau 67.0 96.8 78.3 54.6 0.8 1,798 Education No education/primary (22.7) (74.0) (57.2) (17.0) (19.6) 49 Secondary 45.3 89.1 73.3 36.1 5.0 4,534 Secondary special 68.3 96.6 79.1 56.7 1.4 1,327 Higher 79.5 97.6 82.7 67.2 0.3 1,530 Wealth quintile Lowest 36.0 77.8 68.4 26.9 11.6 1,243 Second 44.2 88.8 75.1 35.5 4.1 1,234 Middle 56.8 95.6 77.1 47.2 2.3 1,511 Fourth 63.7 95.3 78.2 53.3 1.5 1,672 Highest 71.5 98.3 79.7 58.8 0.4 1,780 Total 56.3 92.1 76.2 46.0 3.5 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. About 95 percent of women and men in Moldova have exposure to media at least once a week. Television is the most popular media source and more than 90 percent of women and men watch it at least weekly. About an equal share of women and men listen to the radio, which is the second most popular media source (76 and 79 percent, respectively). Women, however, are more likely than men to read a newspaper once a week (56 and 41 percent, respectively). Overall, women have more exposure to media: 46 percent access all three sources at least once a week, versus 35 percent of men. 32 | Characteristics of Respondents Table 3.3.2 Exposure to mass media: men Percentage of men who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Moldova 2005 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week All three media No media Number Age 15-19 36.1 95.5 84.7 31.6 1.3 411 20-24 40.1 94.1 86.3 37.6 3.3 275 25-29 42.8 92.3 78.2 36.8 4.4 234 30-34 42.7 89.2 82.7 36.8 3.2 224 35-39 50.0 90.6 85.6 45.6 3.0 248 40-44 46.3 93.8 77.3 41.1 5.6 247 45-49 37.1 86.0 72.3 28.4 5.9 349 50-54 39.7 86.2 77.4 32.8 5.3 296 55-59 35.6 83.1 66.6 29.2 11.5 224 Residence Urban 52.2 95.7 81.5 45.2 1.4 1,055 Rural 32.2 86.4 77.6 27.6 6.9 1,453 Region North 34.0 91.3 78.1 28.6 3.9 756 Center 35.0 86.0 78.3 30.9 6.0 702 South 36.7 86.8 75.2 30.7 8.1 496 Chisinau 60.3 97.6 85.7 53.0 0.5 554 Education No education/primary * * * * * 16 Secondary 30.0 88.0 75.9 24.9 5.7 1,788 Secondary special 56.2 97.1 86.1 48.3 0.6 302 Higher 77.7 97.4 90.0 71.1 0.9 403 Wealth quintile Lowest 18.8 71.1 68.2 14.3 14.0 450 Second 28.9 86.0 75.2 23.8 7.6 470 Middle 36.0 96.2 79.0 30.6 2.0 464 Fourth 46.6 96.0 84.8 41.6 0.9 561 Highest 65.8 98.8 86.1 58.0 0.3 563 Total 40.6 90.3 79.3 35.0 4.6 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 3.3.1 Language Preferences for Print Media In addition to observing trends in exposure to various types of media, it is interesting to consider the language in which respondents prefer to access information in print. A very brief background on language evolution in Moldova should help to interpret the results presented in Table 3.4. The Moldovan language is a Romanian dialect that is native to the region. The main difference between the Moldovan and Romanian languages is that the former includes more words of Slavic origin because of the influence of a Russian- speaking population that has dominated much of the region for very long periods (United States Library of Congress, 1995). Moldovan was written in the Latin alphabet from the mid-19th century until 1940 when the script was changed to the Cyrillic alphabet. In 1989, the Moldovan Soviet Socialist Republic designated Moldovan as the state language of Moldova and changed the script back to the Latin Characteristics of Respondents | 33 alphabet. Russian was maintained as the language of interethnic communication. After independence, the 1994 Moldovan Constitution also designated Moldovan, written in the Latin script, as the state language (Article 13.1). The Constitution further recognizes and protects the right to maintain and develop Russian, and other languages, as functional languages of the state (Article 13.2). Table 3.4 presents language preferences for printed material, among women and men who read a newspaper at least once a week, according to background characteristics. Among women, preferences for language of reading material are about equal for Moldovan in the Latin alphabet (37 percent) and Russian (35 percent) languages. Among men, preference for Russian language (39 percent) is higher than for Moldovan in the Latin alphabet (25 percent). A substantial percentage of women and men reported equally preferring both Moldovan and Russian languages (27 and 32 percent, respectively). Preference for reading Moldovan in the Cyrillic alphabet is low (2 percent for women and 4 percent for men), but would no doubt be higher if the autonomous region of Transnistria were included in the sample.2 Table 3.4 Language preference for printed media Among men and women who read a newspaper at least once a week, percent distribution by preferred language of newspaper, according to background characteristics, Moldova 2005 Women Men Background characteristic Moldovan/ Latin charac. Moldovan/ Cyrillic charac. Russian Moldovan and Russian Other Total Number Moldovan/ Latin charac. Moldovan/ Cyrillic charac. Russian Moldovan and Russian Other Total Number Age 15-19 57.4 0.6 23.0 18.7 0.2 100.0 857 51.2 2.1 24.6 22.0 0.0 100.0 148 20-24 43.3 0.5 29.0 27.2 0.0 100.0 652 39.0 0.7 32.7 27.6 0.0 100.0 110 25-29 34.4 0.6 37.5 27.4 0.1 100.0 516 19.8 0.9 43.0 36.4 0.0 100.0 100 30-34 27.2 2.0 38.6 31.7 0.4 100.0 549 19.9 0.0 40.6 38.8 0.7 100.0 96 35-39 27.3 3.3 36.6 31.8 0.9 100.0 490 18.6 6.0 39.0 34.5 1.9 100.0 124 40-44 27.5 3.8 41.9 26.6 0.1 100.0 551 12.4 3.8 46.5 37.3 0.0 100.0 114 45-49 24.6 3.7 43.1 28.1 0.5 100.0 575 8.8 8.0 50.0 31.5 1.8 100.0 129 50-54 na na na na na na na 19.7 6.5 37.4 36.4 0.0 100.0 117 55-59 na na na na na na na 26.4 1.5 37.6 30.8 3.7 100.0 80 Residence Urban 27.6 1.0 48.3 22.8 0.3 100.0 2,073 19.3 3.5 47.4 29.6 0.3 100.0 551 Rural 45.2 2.9 21.1 30.4 0.4 100.0 2,115 30.8 3.6 28.5 35.7 1.5 100.0 469 Region North 34.1 2.4 35.5 27.8 0.1 100.0 1,216 27.3 2.3 39.8 30.6 0.0 100.0 257 Center 53.1 2.7 15.5 28.2 0.5 100.0 985 29.5 4.4 24.9 39.8 1.3 100.0 246 South 28.6 1.9 40.2 28.7 0.6 100.0 783 16.7 2.8 40.3 37.4 2.8 100.0 182 Chisinau 30.4 0.9 45.6 23.0 0.1 100.0 1,205 23.1 4.2 47.1 25.6 0.0 100.0 335 Education No education/ primary * * * * * * 11 * * * * * * 1 Secondary 40.9 3.1 30.3 25.4 0.3 100.0 2,054 24.7 5.4 39.1 30.0 0.9 100.0 536 Secondary special 30.7 1.2 40.0 27.9 0.2 100.0 906 23.6 3.2 38.2 34.6 0.4 100.0 170 Higher 33.5 0.6 37.4 28.2 0.4 100.0 1,216 24.5 0.6 38.5 35.5 0.9 100.0 313 Wealth quintile Lowest 52.9 5.5 12.4 28.9 0.3 100.0 447 38.6 4.9 21.5 35.0 0.0 100.0 85 Second 49.1 2.6 18.5 29.8 0.0 100.0 545 29.6 2.8 32.8 34.0 0.9 100.0 136 Middle 40.2 2.1 28.5 28.8 0.4 100.0 859 27.5 3.3 31.3 35.9 2.0 100.0 167 Fourth 33.5 1.3 34.9 29.8 0.5 100.0 1,065 22.9 4.5 36.8 34.4 1.5 100.0 261 Highest 25.3 0.9 53.1 20.5 0.2 100.0 1,272 19.4 2.9 49.5 28.3 0.0 100.0 371 Total 36.5 1.9 34.6 26.7 0.3 100.0 4,189 24.6 3.5 38.7 32.4 0.8 100.0 1,019 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 2 In the autonomous region of Transnistria, the Moldovan language is still written in the Cyrillic alphabet. It is a co- official language, along with Ukrainian and Russian. 34 | Characteristics of Respondents Compared with older respondents, those in the youngest age group show a marked increase in the preference for reading in Moldovan in the Latin alphabet, and a simultaneous decrease in the preference for reading in Russian. This trend corresponds with the period following independence, when the Moldovan language was designated the official national language. From age 25 on the largest share of female and male respondents in every age group prefers to read in the Russian language. The preference for reading in Russian, or an equal preference for reading in Russian or Moldovan, is higher for men than women in all age groups. The latter may be explained by their military training, which was carried out in Russian and, during the Soviet period, was obligatory for males. By place of residence and region, similar patterns are noted for women and men. Respondents in rural areas, of both sexes, prefer reading Moldovan in the Latin alphabet about one and a half times more than those in urban areas, while respondents in urban areas have a preference as strong or stronger for reading in Russian; for example, more than twice as many females in urban areas prefer to read in Russian than females in rural areas. Females and males in rural areas are more likely than those in urban areas to prefer both Moldovan and Russian equally. By region, the strongest preference for Russian is in Chisinau, while Russian language is least preferred in the Center region (outside of Chisinau). The relationship between language preference and educational attainment is less clear than for other background characteristics, and the pattern differs by sex. For example, women who attained secondary education prefer to read the Moldovan language in the Latin alphabet and those who attained secondary special or higher education prefer Russian. There is no such pattern for men. In terms of wealth quintiles, for both women and men there is a monotonic increase for a preference in Russian language from the lowest to the highest wealth quintile, and a simultaneous decrease in a preference for Moldovan language. An equal preference for both languages does not vary substantially by quintile, but overall a larger proportion of men than women have an equal preference for the two languages. 3.4 EMPLOYMENT 3.4.1 Employment Status The MDHS asked respondents whether they were employed at the time of the survey and, if not, whether they were employed at all in the 12 months preceding the survey. Tables 3.5.1 and 3.5.2 show the distribution of women and men by employment status, respectively, by background characteristics. Fifty- one percent of women and 58 percent of men are currently employed, and a further 4 percent and 8 percent, respectively, were employed in the 12 months preceding the survey but were no longer employed at the time of the survey. For women, the data show a strong positive association between percent currently employed and age, and between percent currently employed and wealth quintile; for men, the relationship is also positive, but with some exceptions. For example, men in age groups 50-54 and 55-59 are less likely than men age 25-49 to be employed. Men in the older age groups (and probably women also, although data were not collected for women over age 49) are likely to have been the most dramatically affected by economic upheavals during the transition period. These cohorts would have been middle-aged in the 1990s, and probably less likely than their younger counterparts to adapt their career to the new and quickly changing postsocialist economic environment. Characteristics of Respondents | 35 Men who are married are most likely to be employed (70 percent), while among women, the women who were previously married (that is, separated, divorced and widowed women) are the most likely to be employed (67 percent). Since previously married women are likely to be single mothers, they, along with married men, may represent heads of households and be the main income earner in the family. Respondents are more likely to be employed if they live in Chisinau or other urban areas, and are least likely to be employed if they live in the Center region (outside of Chisinau). Current employment is higher for respondents who attained secondary special or higher education (over 60 percent) versus those who attended secondary education. Table 3.5.1 Employment status: women Percent distribution of women by employment status, according to background characteristics, Moldova 2005 Employed in the 12 months preceding the survey Background characteristic Currently employed Not currently employed Not employed in the 12 months preceding the survey Missing/ don't know Total Number of women Age 15-19 14.6 2.8 82.6 0.0 100.0 1,417 20-24 38.2 5.0 56.7 0.0 100.0 1,124 25-29 52.2 4.7 43.1 0.0 100.0 964 30-34 62.9 4.9 32.1 0.1 100.0 924 35-39 68.3 3.6 27.9 0.2 100.0 855 40-44 70.4 4.3 25.1 0.2 100.0 1,007 45-49 70.9 3.1 25.9 0.1 100.0 1,149 Marital status Never married 23.4 3.2 73.3 0.0 100.0 1,862 Married or living together 59.9 4.0 36.0 0.1 100.0 4,937 Divorced/separated/ widowed 67.4 6.3 26.1 0.2 100.0 641 Number of living children 0 30.8 4.1 65.1 0.0 100.0 2,456 1-2 62.1 4.0 33.9 0.0 100.0 3,918 3-4 60.8 3.7 35.1 0.4 100.0 965 5+ 50.3 4.1 45.6 0.0 100.0 101 Residence Urban 59.3 3.7 37.0 0.1 100.0 3,194 Rural 45.5 4.2 50.2 0.1 100.0 4,246 Region North 48.9 3.9 47.2 0.0 100.0 2,207 Center 44.8 3.9 51.1 0.1 100.0 2,033 South 51.0 4.0 44.9 0.1 100.0 1,402 Chisinau 62.4 4.1 33.4 0.0 100.0 1,798 Education No education/primary (32.8) (0.0) (67.2) (0.0) (100.0) 49 Secondary 44.0 4.4 51.5 0.1 100.0 4,534 Secondary special 65.2 3.4 31.3 0.1 100.0 1,327 Higher 62.1 3.3 34.6 0.0 100.0 1,530 Wealth quintile Lowest 43.6 5.3 50.8 0.2 100.0 1,243 Second 44.3 4.4 51.3 0.0 100.0 1,234 Middle 47.4 3.5 49.0 0.1 100.0 1,511 Fourth 54.3 3.3 42.3 0.1 100.0 1,672 Highest 62.6 3.8 33.6 0.0 100.0 1,780 Total 51.4 4.0 44.5 0.1 100.0 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. 36 | Characteristics of Respondents Table 3.5.2 Employment status: men Percent distribution of men by employment status, according to background characteristics, Moldova 2005 Employed in the 12 months preceding the survey Background characteristic Currently employed Not currently employed Not employed in the 12 months preceding the survey Missing/ don't know Total Number of men Age 15-19 14.7 6.2 77.4 1.7 100.0 411 20-24 47.9 12.1 40.0 0.0 100.0 275 25-29 71.2 11.9 16.6 0.3 100.0 234 30-34 71.6 10.1 18.3 0.0 100.0 224 35-39 76.1 5.5 18.5 0.0 100.0 248 40-44 73.7 8.8 17.5 0.0 100.0 247 45-49 71.8 7.3 20.9 0.0 100.0 349 50-54 60.7 7.1 32.2 0.0 100.0 296 55-59 55.5 7.0 37.5 0.0 100.0 224 Marital status Never married 30.0 7.4 61.8 0.8 100.0 730 Married or living together 69.9 8.3 21.8 0.1 100.0 1,657 Divorced/separated/ widowed 55.6 12.8 31.6 0.0 100.0 120 Residence Urban 61.4 7.0 31.1 0.4 100.0 1,055 Rural 54.8 9.1 35.9 0.2 100.0 1,453 Region North 55.2 6.7 37.9 0.1 100.0 756 Center 53.0 9.8 37.0 0.1 100.0 702 South 59.3 9.6 30.9 0.3 100.0 496 Chisinau 65.1 7.1 27.0 0.8 100.0 554 Education No education/primary * * * * * 16 Secondary 54.3 9.0 36.4 0.3 100.0 1,788 Secondary special 66.1 8.5 25.1 0.3 100.0 302 Higher 66.4 4.7 28.7 0.2 100.0 403 Wealth quintile Lowest 52.7 8.5 38.8 0.0 100.0 450 Second 52.4 9.8 37.7 0.2 100.0 470 Middle 60.9 8.6 30.0 0.5 100.0 464 Fourth 54.7 7.9 36.9 0.5 100.0 561 Highest 65.9 6.8 27.0 0.3 100.0 563 Total 57.6 8.2 33.9 0.3 100.0 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 3.4.2 Occupation The distributions of women and men employed in the 12 months preceding the survey, by occupation and other background characteristics, are shown in Tables 3.6.1 and 3.6.2, and Figure 3.1. About one-fifth of women (20 percent) and men (23 percent) work in the agricultural sector. There are substantial differences between women and men’s occupations outside of agriculture, however. For example, more than 50 percent of females are engaged in professional/technical/managerial work and sales and services (33 percent and 24 percent, respectively), while another 18 percent are engaged in skilled manual labor. In contrast, the majority of men are engaged in manual labor—45 percent in skilled manual labor and 8 percent in unskilled manual labor. Clerical and domestic occupations represent minor occupational options in Moldova. Characteristics of Respondents | 37 Table 3.6.1 Occupation: women Percent distribution of women employed in the 12 months preceding the survey by occupation, according to background characteristics, Moldova 2005 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of women Age 15-19 9.1 3.4 40.5 23.5 0.0 2.6 20.0 1.1 100.0 217 20-24 31.8 6.1 27.2 21.0 0.5 2.0 10.8 0.6 100.0 473 25-29 34.7 3.3 26.5 16.8 0.5 1.0 16.6 0.6 100.0 546 30-34 36.5 3.5 23.0 19.6 0.0 0.7 16.6 0.0 100.0 627 35-39 34.1 2.9 23.6 17.4 0.0 1.7 20.1 0.1 100.0 615 40-44 35.1 2.4 22.5 14.9 0.3 1.3 23.2 0.5 100.0 752 45-49 33.3 2.2 19.5 17.2 0.4 0.8 26.1 0.5 100.0 848 Marital status Never married 31.8 6.5 29.7 18.1 0.0 1.3 12.2 0.5 100.0 459 Married or living together 33.6 2.7 23.2 17.1 0.3 1.4 21.3 0.5 100.0 3,147 Divorced/separated/ widowed 29.9 3.2 25.4 22.7 0.5 0.9 17.5 0.0 100.0 471 Number of living children 0 34.5 5.2 28.4 18.0 0.4 1.0 12.0 0.4 100.0 814 1-2 36.3 3.3 24.5 18.5 0.1 1.3 15.7 0.3 100.0 2,585 3-4 19.6 0.6 18.0 15.7 0.6 1.8 43.3 0.4 100.0 622 5+ (5.7) (0.0) (16.2) (9.8) (0.0) (1.5) (62.9) (3.9) (100.0) 55 Residence Urban 40.6 5.2 30.0 21.3 0.3 1.1 1.2 0.3 100.0 1,969 Rural 25.8 1.4 18.7 14.7 0.2 1.5 37.2 0.5 100.0 2,108 Region North 29.1 1.7 23.7 15.6 0.2 0.8 28.6 0.3 100.0 1,163 Center 28.0 2.4 21.9 18.1 0.3 1.8 27.2 0.4 100.0 991 South 29.9 2.7 20.7 17.9 0.4 2.2 25.5 0.8 100.0 770 Chisinau 43.2 5.8 28.9 19.9 0.2 0.7 0.9 0.3 100.0 1,153 Education No education/primary * * * * * * * * * 16 Secondary 5.5 1.9 30.9 25.8 0.4 2.1 32.9 0.5 100.0 2,174 Secondary special 50.9 3.6 20.6 15.0 0.2 0.8 8.6 0.4 100.0 906 Higher 77.4 5.8 12.6 3.2 0.0 0.0 0.7 0.3 100.0 980 Wealth quintile Lowest 8.4 0.2 13.3 9.6 0.5 2.0 65.4 0.5 100.0 608 Second 17.9 1.4 20.6 17.6 0.3 1.1 40.8 0.4 100.0 600 Middle 31.7 2.8 24.0 22.4 0.2 1.8 16.7 0.3 100.0 768 Fourth 40.8 3.9 28.9 21.1 0.1 1.2 3.5 0.5 100.0 950 Highest 48.2 5.4 28.0 16.7 0.3 0.7 0.3 0.3 100.0 1,150 Total 33.0 3.2 24.2 17.9 0.3 1.3 19.8 0.4 100.0 4,077 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. 38 | Characteristics of Respondents Table 3.6.2 Occupation: men Percent distribution of men employed in the 12 months preceding the survey by occupation, according to background characteristics, Moldova 2005 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of men Age 15-19 2.2 0.0 7.4 58.4 10.0 0.0 20.5 1.4 100.0 77 20-24 9.5 1.4 11.6 56.2 8.1 0.8 11.7 0.7 100.0 162 25-29 16.5 2.4 12.7 45.2 6.0 0.0 17.2 0.0 100.0 195 30-34 13.1 0.6 15.1 46.1 7.1 0.0 17.2 0.8 100.0 183 35-39 9.3 0.8 12.5 45.1 3.1 0.0 28.7 0.5 100.0 202 40-44 12.9 0.3 7.8 47.7 9.2 0.0 22.1 0.0 100.0 204 45-49 12.4 0.0 5.6 42.0 6.8 0.0 32.7 0.5 100.0 276 50-54 20.0 0.3 5.8 35.3 15.0 0.0 23.7 0.0 100.0 200 55-59 20.1 1.3 2.9 37.6 11.7 0.0 25.1 1.4 100.0 140 Marital status Never married 8.6 1.6 9.4 52.5 9.5 0.5 16.9 1.0 100.0 264 Married or living together 14.6 0.7 9.5 42.8 7.7 0.0 24.4 0.4 100.0 1,292 Divorced/separated/ widowed 11.7 0.0 2.3 54.2 12.5 0.0 19.3 0.0 100.0 82 Residence Urban 22.2 1.3 13.8 52.5 7.4 0.2 2.2 0.4 100.0 710 Rural 6.8 0.4 5.5 39.1 8.9 0.0 38.7 0.5 100.0 929 Region North 10.4 0.5 8.3 41.6 10.3 0.0 28.4 0.4 100.0 468 Center 7.9 0.2 8.6 47.1 6.5 0.0 29.0 0.8 100.0 441 South 10.5 0.7 5.0 41.5 10.9 0.0 31.4 0.0 100.0 341 Chisinau 26.0 1.8 14.3 49.4 5.6 0.3 1.9 0.7 100.0 388 Education No education/primary * * * * * * * * * 9 Secondary 2.4 0.1 5.5 51.7 10.5 0.1 29.1 0.5 100.0 1,124 Secondary special 16.5 1.9 13.0 48.6 5.1 0.0 14.4 0.4 100.0 224 Higher 55.4 2.5 20.4 15.9 2.1 0.0 3.4 0.5 100.0 282 Wealth quintile Lowest 1.5 0.0 1.7 30.0 13.3 0.0 52.8 0.6 100.0 275 Second 4.8 0.5 4.9 40.3 8.9 0.0 40.5 0.1 100.0 292 Middle 7.3 1.1 6.2 50.3 8.9 0.0 25.1 1.1 100.0 322 Fourth 16.9 0.4 13.1 53.6 8.3 0.0 7.8 0.0 100.0 350 Highest 30.0 1.6 16.1 46.6 3.9 0.3 0.9 0.7 100.0 399 Total 13.5 0.8 9.1 44.9 8.3 0.1 22.9 0.5 100.0 1,639 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. A closer examination of respondents engaged in agricultural occupations shows little difference between background characteristics by sex. For example, 20 to 33 percent of employed women and men in age groups 35-39 and over work in agriculture. Agricultural workers are most likely to have the following characteristics: to live in rural areas, to have a secondary education (versus secondary special or higher education), and to come from households in the lowest two wealth quintiles. Outside of Chisinau region, a roughly equal proportion of employed respondents in North, South, and Center regions are engaged in agricultural occupations. Characteristics of Respondents | 39 The greatest share of women who are currently employed work in a professional/technical/ managerial jobs (33 percent). There is little variation in the percentage of professional women from each age group over 15-19. Not surprisingly, relatively more professional women live in urban areas, have attended secondary special school or university, and come from households in the two upper wealth quintiles. The second largest share of women is engaged in sales and services activities (24 percent). Unlike professional women, a relatively larger percentage of women in sales and service are from the youngest age group (15-19) and have attended secondary school. The greatest percentage of male respondents earn their living doing skilled manual labor (45 percent). A relatively larger percentage of these men are in younger age groups, 15-19 and 20-24, live in an urban area, and come from households in the middle or fourth wealth quintiles. In contrast, among the 14 percent of males who are engaged in professional/technical/managerial livelihoods, a greater share of them are in older age groups, 50-54 and 55-59, also live in an urban area, and come from the highest wealth quintile. Figure 3.1 Percent Distribution of Women and Men Who Are Currently Employed, by Occupation WOMEN MEN Note: Totals may not add to 100 because of rounding. MDHS 2005 Agriculture 20% Domestic service/ clerical 5% Skilled manual 18% Sales and services 24% Professional/ technical managerial 33% Professional/ technical managerial 14% Agriculture 23% Domestic service/ clerical 1% Unskilled manual 8% Skilled manual 45% Sales and services 9% 3.4.3 Use of Earnings Married women who are employed and receive cash earnings were asked who the primary decisionmaker is regarding how their earnings are spent. This information allows for the assessment of women’s control over their own earnings. Table 3.7 shows how women’s control over their earnings varies by background characteristics. Among women receiving cash earnings, about two-thirds decide jointly with their husband or with someone else how to use their income (62 percent), almost a third (30 percent) decide by themselves, and for a small minority (2 percent), someone else makes decisions about how their earnings are used. 40 | Characteristics of Respondents There is not a lot of variation by background characteristics for the type of decision made, independently or jointly. In general, however, women who make independent decisions about their earnings are more likely to be in the oldest age group, from urban areas especially Chisinau, and from households in the highest wealth quintile. In contrast, women who make joint decisions with their spouse or someone else are more likely in the youngest age groups, from rural areas, from the South region, and from households in the lowest wealth quintile. Table 3.7 Decision on use of earnings Percent distribution of married women employed in the 12 months preceding the survey receiving cash earnings by person who decides how earnings are to be used, according to background characteristics, Moldova 2005 Person who decides how earnings are used Background characteristic Self only Jointly1 Someone else only2 Missing Total Number of women Age 15-19 (25.3) (72.7) (2.0) (0.0) (100.0) 33 20-24 24.1 72.0 3.3 0.6 100.0 252 25-29 27.0 70.3 2.4 0.4 100.0 387 30-34 27.4 70.3 1.8 0.5 100.0 488 35-39 28.9 68.3 2.8 0.0 100.0 478 40-44 30.4 67.8 1.7 0.1 100.0 552 45-49 35.5 61.9 2.0 0.5 100.0 596 Number of living children 0 33.4 62.3 3.8 0.5 100.0 284 1-2 29.8 67.9 2.0 0.3 100.0 2,026 3-4 27.3 70.3 2.3 0.1 100.0 441 5+ (19.4) (79.2) (1.4) (0.0) (100.0) 34 Residence Urban 34.3 62.9 2.4 0.4 100.0 1,414 Rural 24.8 73.0 2.0 0.2 100.0 1,371 Region North 28.2 69.5 1.9 0.4 100.0 775 Center 27.2 70.3 2.4 0.1 100.0 663 South 23.2 74.6 2.1 0.1 100.0 543 Chisinau 37.3 59.7 2.5 0.6 100.0 804 Education No education/primary * * * * * 12 Secondary 29.9 66.8 2.9 0.4 100.0 1,362 Secondary special 27.6 70.2 2.0 0.2 100.0 693 Higher 31.2 67.5 1.1 0.2 100.0 717 Wealth quintile Lowest 23.2 73.1 3.2 0.5 100.0 294 Second 25.6 71.9 2.3 0.2 100.0 380 Middle 27.5 70.0 2.2 0.3 100.0 575 Fourth 29.9 67.6 2.3 0.2 100.0 705 Highest 34.9 62.9 1.8 0.4 100.0 832 Total 29.6 67.8 2.2 0.3 100.0 2,785 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 With husband or someone else 2 Includes husband Characteristics of Respondents | 41 3.5 WOMEN’S EMPOWERMENT In addition to information on women’s education, employment status, and control over earnings, the MDHS collected information from both women and men on other measures of women’s autonomy and status. In particular, questions were asked about women’s roles in making household decisions, on tolerance of wife beating, and on their opinions about when a wife is justified in refusing to have sex with her husband. Such information provides insight into women’s control over their environment as well as attitudes toward gender roles. 3.5.1 Women’s Participation in Decisionmaking To assess women’s decisionmaking authority, the MDHS collected information on married women’s participation in four different types of household decisions: on the respondents’ own health care; on making large household purchases; on making household purchases for daily needs; and on visits to family or relatives. Table 3.8 shows the percent distribution of married women according to who usually has the final say in each of these decisions. The autonomy of women in this case would be gauged by either their making such decisions independently or jointly. Table 3.8 Women's participation in decisionmaking Percent distribution of currently married women by person who has the final say in making specific decisions, according to type of decision, Moldova 2005 Currently married or living together Decision Self only Jointly with husband Husband only Someone else only Missing/ other Total Number of women Own health care 51.6 45.4 2.4 0.3 0.4 100.0 4,937 Large household purchases 19.0 76.8 3.4 0.4 0.4 100.0 4,937 Daily household purchases 64.0 32.5 2.7 0.5 0.3 100.0 4,937 Visits to family or relatives 19.8 77.1 2.3 0.3 0.4 100.0 4,937 Among currently married women, independence in making decisions ranges from one-fifth for making large household purchases and visiting family or relatives, to 64 percent for making daily household purchases. Husbands (or partners) rarely make any of these decisions without their wife’s input; decisions that are not made solely by the woman are most likely to be made jointly by the woman and her husband. Overall, married women in Moldova have a lot of say in specific household decisions, and Table 3.9 shows that participation in decisionmaking varies little by background characteristics. In all four types of decisions, 96 to 97 percent of married women are influential in making specific decisions, either by themselves or jointly. Ninety-two percent reported having a say in all four decisions, and only among the youngest women (age 15-19) did substantially fewer (81 percent) have a say in all four decisions. Women with five or more children and women employed but not for cash had a slight advantage over other women in having a say in final decisions (96 percent). 42 | Characteristics of Respondents Table 3.9 Women's participation in decisionmaking by background characteristics Percentage of currently married women who say that they alone or jointly have the final say in specific decisions, by background characteristics, Moldova 2005 Alone or jointly has final say in: Background characteristic Own health care Making large purchases Making daily purchases Visits to family or relatives All specified decisions None of the specified decisions Number of women Age 15-19 92.7 92.6 90.1 89.7 80.7 2.6 136 20-24 95.5 93.7 95.6 95.7 88.2 1.2 629 25-29 97.0 95.6 96.3 96.6 89.9 0.7 794 30-34 97.7 96.3 96.5 97.1 91.6 0.6 810 35-39 98.1 96.4 97.7 98.4 93.1 0.4 746 40-44 97.1 96.9 98.0 98.3 93.3 0.7 869 45-49 97.4 97.0 96.8 97.5 93.6 0.9 953 Number of living children 0 93.5 94.0 93.4 94.9 86.5 1.8 534 1-2 97.4 96.0 97.0 97.4 91.4 0.6 3,435 3-4 98.0 97.0 97.3 97.4 94.4 0.7 875 5+ 96.1 96.1 97.1 97.1 96.1 2.9 93 Residence Urban 96.4 94.5 95.0 96.6 88.6 1.0 2,045 Rural 97.5 97.0 97.8 97.4 93.6 0.6 2,892 Region North 97.8 97.1 97.6 97.6 93.3 0.6 1,515 Center 96.4 95.9 96.4 96.7 91.3 1.0 1,336 South 98.1 97.6 98.6 97.7 93.9 0.2 958 Chisinau 95.9 93.4 94.2 96.4 87.4 1.4 1,127 Education No education/primary (86.1) (82.0) (82.0) (82.6) (80.5) (13.9) 41 Secondary 97.1 96.7 96.9 96.9 92.1 0.8 2,884 Secondary special 97.7 95.9 97.8 98.6 93.1 0.3 1,046 Higher 96.8 94.6 95.3 96.8 88.5 0.7 966 Employment Not employed 96.7 94.9 95.9 95.6 89.9 1.2 1,965 Employed for cash 97.2 96.5 96.9 98.0 92.2 0.6 2,644 Employed not for cash 98.4 99.0 99.7 98.8 96.4 0.0 313 Wealth quintile Lowest 97.1 95.6 96.8 96.2 92.4 1.4 839 Second 97.8 97.4 97.8 96.8 93.8 0.6 834 Middle 97.2 97.3 97.7 97.7 93.3 0.5 1,029 Fourth 96.6 95.9 96.5 98.4 91.1 0.6 1,081 Highest 96.8 94.3 95.0 96.3 88.0 0.9 1,154 Total 97.1 96.0 96.7 97.1 91.5 0.8 4,937 Note: Figures in parentheses are based on 25-49 unweighted cases. Characteristics of Respondents | 43 3.5.2 Women’s and Men’s Attitudes toward Wife Beating Violence against women is an area increasingly being recognized as a serious human rights issue. If violence against women is tolerated in society, eradicating it is made more difficult. To gauge the acceptability of domestic violence, women and men interviewed in the MDHS were asked whether they thought a husband would be justified in hitting or beating his wife in each of the following five situations: if she burns the food; if she argues with him; if she goes out without telling him; if she neglects the children; and if she refuses to have sex with him.3 Tables 3.10.1 and 3.10.2 show that women and men think there is little justification for a husband to beat his wife. Although 21 percent of women and 22 percent of men agree with at least one specified reason for wife beating, results show that neglecting the children is the only widely accepted reason, cited by 18 percent of both women and men. Fewer than 10 percent feel that wife beating is justified for any of the other reasons asked about. A relatively large proportion of men and women who agree with at least one specified reason for beating a wife are from households in the two lowest wealth quintiles, are among those employed not for cash, and are among those who attended secondary school (versus secondary special or higher). In addition, women with three or more children were more likely to agree with at least one reason that a husband is justified in hitting or beating his wife. 3 The MDHS also included questions on the actual prevalence of gender violence (see Chapter 14). 44 | Characteristics of Respondents Table 3.10.1 Women's attitudes toward wife beating Percentage of women who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Moldova 2005 Husband is justified in hitting or beating his wife if she: Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sex with him Agrees with at least one specified reason Number Age 15-19 4.1 4.9 6.7 20.8 2.9 23.7 1,417 20-24 4.2 4.1 5.4 16.6 1.7 18.6 1,124 25-29 4.0 5.6 7.1 17.4 2.3 20.1 964 30-34 4.3 3.8 6.7 17.2 3.5 20.4 924 35-39 4.5 5.6 8.0 17.6 4.0 20.3 855 40-44 3.9 5.1 8.8 17.9 3.8 21.2 1,007 45-49 4.7 6.5 8.5 16.9 3.1 20.4 1,149 Marital status Never married 3.3 3.6 4.8 17.3 2.2 19.6 1,862 Married or living together 4.6 5.7 8.3 18.2 3.4 21.4 4,937 Divorced/separated/ widowed 4.7 4.4 6.4 17.8 2.3 19.5 641 Number of living children 0 3.6 4.0 5.8 16.9 2.4 19.6 2,456 1-2 3.6 4.6 6.3 16.6 2.6 19.2 3,918 3-4 8.5 9.5 14.2 25.5 6.2 29.3 965 5+ 4.1 9.2 14.3 24.6 4.6 30.6 101 Residence Urban 1.9 2.7 3.1 12.0 1.7 13.8 3,194 Rural 6.0 6.9 10.4 22.3 4.0 26.1 4,246 Region North 5.5 5.8 8.3 21.0 4.0 24.4 2,207 Center 4.9 5.9 9.1 20.6 3.2 23.6 2,033 South 3.8 5.4 8.2 17.5 2.5 20.5 1,402 Chisinau 2.3 3.0 3.2 11.3 2.0 13.5 1,798 Education No education/primary (12.2) (22.4) (20.4) (30.6) (16.3) (36.7) 49 Secondary 5.8 7.0 10.2 23.7 4.1 27.5 4,534 Secondary special 2.1 2.7 3.5 11.0 1.6 13.3 1,327 Higher 1.3 1.0 1.5 6.3 0.7 7.0 1,530 Employment Not employed 4.6 5.5 7.8 19.6 3.0 22.5 3,598 Employed for cash 3.6 4.3 5.9 15.0 2.6 17.9 3,439 Employed not for cash 5.7 7.9 13.6 27.4 6.6 31.1 382 Wealth quintile Lowest 11.0 10.1 16.8 32.9 6.7 38.2 1,243 Second 5.2 7.8 10.3 23.8 4.1 27.3 1,234 Middle 3.5 5.3 7.4 17.1 2.7 20.0 1,511 Fourth 2.3 2.9 3.5 12.8 1.6 14.9 1,672 Highest 1.3 1.5 2.0 8.9 1.3 10.4 1,780 Total 4.2 5.1 7.3 17.9 3.0 20.8 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. Characteristics of Respondents | 45 Table 3.10.2 Men's attitudes toward wife beating Percentage of men who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Moldova 2005 Husband is justified in hitting or beating his wife if she: Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sex with him Agrees with at least one specified reason Number Age 15-19 3.4 9.2 9.1 20.6 5.1 24.7 411 20-24 3.8 6.8 7.9 21.2 2.1 23.8 275 25-29 0.5 5.7 8.6 13.6 2.1 15.4 234 30-34 2.8 5.2 8.6 19.5 3.3 21.8 224 35-39 3.2 8.4 11.1 21.0 4.9 24.7 248 40-44 0.7 6.2 7.9 18.5 2.8 22.4 247 45-49 3.2 9.8 15.1 15.0 3.7 23.9 349 50-54 1.8 7.0 9.1 12.6 4.5 18.7 296 55-59 3.5 6.7 8.2 14.9 3.9 16.5 224 Marital status Never married 3.0 8.1 8.8 22.0 3.6 25.2 730 Married or living together 2.2 7.0 9.4 14.8 3.5 19.3 1,657 Divorced/separated/ widowed 6.5 11.2 19.0 27.6 7.0 34.4 120 Residence Urban 2.1 5.1 4.7 12.4 2.5 15.0 1,055 Rural 3.0 9.2 13.4 21.2 4.6 26.5 1,453 Region North 2.2 6.5 9.5 16.0 3.0 19.5 756 Center 2.9 9.7 11.6 19.5 3.6 25.3 702 South 2.5 8.8 13.6 19.7 5.5 24.8 496 Chisinau 2.9 4.8 4.1 15.1 3.1 17.4 554 Education No education/primary * * * * * * 16 Secondary 3.3 9.3 12.0 20.9 4.8 25.7 1,788 Secondary special 0.2 3.3 6.5 11.7 0.8 14.9 302 Higher 0.9 2.0 2.1 6.5 0.5 8.8 403 Employment Not employed 2.9 7.9 10.4 17.9 4.0 22.6 1,351 Employed for cash 2.2 7.0 8.4 16.6 2.7 19.7 1,031 Employed not for cash 2.8 7.3 13.7 22.1 8.6 28.6 122 Wealth quintile Lowest 4.0 11.1 15.9 23.9 6.0 31.9 450 Second 3.7 10.2 16.5 22.4 4.6 27.3 470 Middle 2.1 8.6 7.7 18.6 4.1 22.5 464 Fourth 2.1 5.7 7.9 14.0 2.7 16.9 561 Highest 1.6 3.2 2.6 11.0 1.7 13.0 563 Total 2.6 7.5 9.7 17.5 3.7 21.7 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 46 | Characteristics of Respondents 3.5.3 Women’s and Men’s Attitudes toward Wife Refusing Sex with Husband The MDHS asked women and men respondents whether they thought a wife is justified in refusing to have sex with her husband in the following three circumstances: when she knows that her husband has a sexually transmitted disease; when she knows that her husband has sex with other women; and when she is tired or not in the mood. Tables 3.11.1 and 3.11.2 show the responses of women and men, respectively. Overall, women’s sexual autonomy is high in Moldova. Seventy-one percent of women and 68 percent of men agree that all of the above reasons are rational justifications for a woman to refuse to have sexual relations with her husband. Only 7 percent of both women and men agree with none of the reasons. The most accepted reason for refusing to have sex, for both sexes, is if the wife knows that the husband has a sexually transmitted disease (91 percent of both women and men). Seventy-seven percent of both women and men think that a woman’s being tired or not in the mood justifies not having sex. The largest disparity between women and men’s attitudes is when a woman knows that her husband has sex with other woman: 85 percent of women believe this is justification to refuse sex, while only 76 percent of men believe this is a justifiable reason. The tables also show attitudes towards refusing to have sex by background characteristics. The differences are not large, but there is a distinct pattern that is similar for both men and women. That is, the percentages of those who do not agree with any specified reason for refusing sex are higher for the youngest age groups (15-19), for those never married, for those who show a higher tolerance for wife beating, and for those in the lowest wealth quintiles. The percentage is also higher for women who have five or more children. Characteristics of Respondents | 47 Table 3.11.1 Women's attitudes toward a wife refusing sex with husband Percentage of women who believe that a wife is justified in refusing to have sex with her husband for specific reasons, by background characteristics, Moldova 2005 Wife is justified in refusing sex with husband if she: Background characteristic Knows husband has a sexually transmitted disease Knows husband has sex with other women Is tired or not in the mood Agrees with all of the specified reasons Agrees with none of the specified reasons Number Age 15-19 85.3 80.2 73.2 68.2 12.2 1,417 20-24 93.0 88.1 79.6 74.1 4.7 1,124 25-29 93.6 88.6 79.5 74.4 4.1 964 30-34 93.2 86.3 77.8 71.9 4.8 924 35-39 93.9 87.2 79.3 73.0 3.5 855 40-44 91.7 84.6 77.3 71.5 6.2 1,007 45-49 88.4 80.1 75.0 67.8 9.3 1,149 Marital status Never married 87.2 81.6 73.5 68.4 10.6 1,862 Married or living together 92.5 86.0 78.8 72.6 5.2 4,937 Divorced/separated/ widowed 89.1 82.5 74.7 69.3 8.7 641 Number of living children 0 88.5 82.9 74.6 69.2 9.0 2,456 1-2 93.0 86.8 79.7 73.5 4.8 3,918 3-4 89.2 81.1 74.5 68.9 8.8 965 5+ 80.1 75.2 62.3 57.4 16.2 101 Residence Urban 93.0 86.6 78.8 72.8 4.8 3,194 Rural 89.2 83.1 75.8 70.1 8.4 4,246 Region North 92.3 85.6 77.9 72.0 5.7 2,207 Center 88.3 82.7 75.5 69.9 9.2 2,033 South 91.0 85.5 77.7 73.1 6.6 1,402 Chisinau 91.9 84.9 77.4 70.6 5.6 1,798 Education No education/primary (73.1) (59.7) (51.9) (43.4) (22.3) 49 Secondary 88.4 82.8 76.0 70.5 8.9 4,534 Secondary special 94.8 87.4 81.2 74.9 3.6 1,327 Higher 95.3 88.3 77.6 71.3 3.0 1,530 Employment Not employed 89.6 83.7 77.3 71.3 8.1 3,598 Employed for cash 92.0 85.7 76.7 71.0 5.5 3,439 Employed not for cash 92.7 84.0 78.3 73.6 6.5 382 Number of reasons wife beating is justified 0 91.6 85.3 78.1 72.5 6.4 5,891 1-2 91.0 84.4 76.3 69.7 5.5 1,205 3-4 80.7 76.4 63.0 58.0 15.5 271 5 66.6 62.4 58.2 47.2 29.3 73 Wealth quintile Lowest 86.4 80.6 73.3 68.5 10.9 1,243 Second 87.9 81.8 76.5 70.9 10.2 1,234 Middle 91.6 86.0 78.4 73.3 6.3 1,511 Fourth 92.2 85.3 76.6 69.7 5.4 1,672 Highest 94.2 87.6 79.6 73.3 3.4 1,780 Total 90.8 84.6 77.1 71.3 6.8 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. 48 | Characteristics of Respondents Table 3.11.2 Men's attitudes toward a wife refusing sex with husband Percentage of men who believe that a wife is justified in refusing to have sex with her husband for specific reasons, by background characteristics, Moldova 2005 Wife is justified in refusing sex with husband if she: Background characteristic Knows husband has a sexually transmitted disease Knows husband has sex with other women Is tired or not in the mood Agrees with all of the specified reasons Agrees with none of the specified reasons Number Age 15-19 85.6 70.7 70.9 58.7 10.4 411 20-24 94.0 78.5 77.2 70.7 4.6 275 25-29 93.3 75.7 75.6 67.6 5.4 234 30-34 91.4 75.1 80.9 68.0 5.2 224 35-39 94.5 81.7 83.3 74.1 3.2 248 40-44 88.9 73.5 81.6 70.6 8.4 247 45-49 93.2 77.3 78.7 68.9 5.0 349 50-54 92.8 75.2 77.2 68.0 4.7 296 55-59 88.3 74.6 75.2 69.9 10.1 224 Marital status Never married 87.5 70.7 71.4 60.4 9.4 730 Married or living together 93.0 78.0 80.3 71.5 4.9 1,657 Divorced/separated/ widowed 87.7 71.8 74.3 63.6 11.3 120 Residence Urban 93.0 77.1 78.1 69.1 5.4 1,055 Rural 89.8 74.4 76.9 67.0 7.3 1,453 Region North 91.0 79.3 79.8 71.8 5.9 756 Center 92.9 72.8 75.5 67.0 6.4 702 South 89.2 75.2 77.6 65.3 6.2 496 Chisinau 90.7 74.3 76.5 65.9 7.6 554 Education No education/primary * * * * * 16 Secondary 89.4 73.6 75.1 65.1 7.6 1,788 Secondary special 97.0 79.5 84.1 75.7 2.6 302 Higher 96.0 82.9 83.7 75.8 3.2 403 Employment Not employed 91.7 74.4 77.2 67.0 5.9 1,351 Employed for cash 90.5 76.9 77.2 68.6 7.4 1,031 Employed not for cash 89.5 77.4 82.2 72.3 5.3 122 Number of reasons wife beating is justified 0 91.3 76.1 78.6 68.6 6.2 1,929 1-2 90.5 74.7 75.1 66.4 7.4 457 3-4 87.1 68.4 66.3 59.8 9.7 94 5 (100.0) (74.2) (75.1) (69.6) (0.0) 27 Wealth quintile Lowest 84.9 68.8 70.1 60.6 10.9 450 Second 87.5 72.8 76.2 65.3 9.0 470 Middle 94.6 80.0 81.0 73.0 3.9 464 Fourth 94.0 78.6 79.8 70.5 3.8 561 Highest 93.3 76.6 79.1 69.1 5.6 563 Total 91.1 75.6 77.4 67.9 6.5 2,508 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. Fertility, Levels, Trends, and Differentials | 49 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 4 4.1 INTRODUCTION Fertility is one of the three principal components of population dynamics, the others being mortality and migration (United Nations, 1973). The factors that determine fertility can be placed into two major categories—biological and social. The biological component refers to the capacity to reproduce, usually called “fecundity.” A woman’s fecundity varies with age; her fecundity begins to increase from menarche (the onset of menstruation), peaks in her twenties, and then declines to menopause (the time when a woman ceases to ovulate and menstruate). The biological component is necessary but is not on its own a sufficient condition for fertility. Given the capacity to reproduce, the social environment in which people live largely determines whether couples will actually have children, and if so, how many and with what degree of spacing. Demographers use the term “fertility” to refer to the actual production of live offspring or live births. The definition of a live birth was developed by the World Health Organization in 1950: “The complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of the pregnancy, which, after such separation, breathes or shows any other evidence of life, such as beating of the heart, pulsation of the umbilical cord, or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached (WHO, 1992).” The MDHS data are used to calculate several measures of fertility. Age-specific fertility rates (ASFRs) are expressed by the number of births to women of a given age interval per 1,000 women in that age interval. In this survey, the ASFR for any specific 5-year age interval is calculated by dividing the number of births of women in the age interval during the period 1 to 36 months preceding the survey by the number of years lived by women in that age interval during the same period of 1 to 36 months. The total fertility rate (TFR) is based on the ASFRs and is one of the most commonly used summary indicators of fertility. The TFR is interpreted as the average number of children that would be born to a woman during her lifetime if she were to experience the currently observed age-specific fertility rates throughout her reproductive years. The TFR is calculated by adding the current age-specific fertility rates, multiplying by 5 (because five-year age groups of women are used), then dividing by 1,000. An important property of the total fertility rate is that it is not affected by the age distribution of the population. All women who were interviewed in the MDHS were asked to give a complete reproductive history. In collecting these histories, each woman was first asked about the total number of pregnancies that had ended in live births, induced abortions, miscarriages, and stillbirths. After obtaining these aggregate data, an event-by-event pregnancy history was collected. For each pregnancy, the duration, the month and year of termination, and the result of the pregnancy were recorded. The result of each pregnancy was classified as a live birth, stillbirth, miscarriage, or induced abortion. Information was collected about the most recent completed pregnancy, then the next-to-last, etc. For each live birth, information was collected on the sex of the child, survival status, and age (for surviving children) or age at death (for deceased children). 50 | Fertility Levels, Trends, and Differentials From the information collected in the reproductive histories, it is possible to estimate current fertility levels and trends, fertility differentials, number of children ever born and living, birth intervals, age at first birth, teenage pregnancy, and motherhood. 4.2 CURRENT FERTILITY LEVELS Table 4.1 and Figure 4.1 present the ASFRs and the TFRs for the three years preceding the survey, which corre- sponds to the period mid-2002 to mid-2005. The three-year period, rather than a longer or shorter period, was chosen for calculating these rates in order to provide the most current information, to reduce sampling error, and to avoid problems of the displacement of births.1 Table 4.1 shows a TFR of 1.7 children per woman for the three-year period preceding the 2005 MDHS. (The corresponding 95% confidence interval is 1.6 and 1.8.) This means that, on average, a woman in Moldova who is at the beginning of her childbearing years will give birth to 1.7 children by the end of her reproductive period if fertility levels remain constant at the level observed in the three-year period. This level is below replacement level fertility (which is slightly higher than 2.0). 1 The displacement of births is a potential bias introduced into the data when, during data collection, some inter- viewers displace a child’s date of birth from the true age of under five years to some age older than five years old. Interviewers may illicitly do this in order to avoid having to fill the lengthy questionnaire section on the health of children under age five and thus complete the interview more quickly. Table 4.1 Current fertility Age-specific fertility rates, the total fertility rate, the general fertility rate, and the crude birth rate for the three years preceding the survey, by urban-rural residence, Moldova 2005 Residence Age group Urban Rural Total 15-19 26 39 34 20-24 110 153 132 25-29 91 98 95 30-34 54 59 57 35-39 17 16 17 40-44 2 4 3 45-49 0 0 0 TFR 1.5 1.8 1.7 GFR 51 59 55 CBR 12.5 11.7 12.0 ASFR: Age-specific fertility rate (number of births to women in a specific age group divided by the number of woman-years lived during a given period) TFR: Total fertility rate for ages 15-49, expressed per woman GFR: General fertility rate (births divided by the number of women age 15-44), expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population � � � � � � � � � � � � 15-19 20-24 25-29 30-34 35-39 40-44 Age group 0 20 40 60 80 100 120 140 160 Births per 1,000 women Urban Rural Total� � Figure 4.1 Age-Specific Fertility Rates (ASFR), by Residence MDHS 2005 Fertility, Levels, Trends, and Differentials | 51 The TFR for rural areas (1.8 births) is higher than that for urban areas (1.5 births). Figure 4.1 shows that this urban-rural difference in childbearing rates can be attributed almost exclusively to younger age groups. Although peak fertility occurs sharply at age 20-24 in both urban and rural areas, the greatest absolute difference in ASFR (43) is in the age 20-24 group. Compared to fertility estimates from recent Reproductive Health Surveys and Demographic and Health Surveys conducted in other countries in Eastern Europe and Eurasia, fertility in Moldova in 2005 is: higher than in neighboring Romania (1.3 in 1999) and Ukraine (1.4 in 1999); similar to fertility in the Caucasus region (Armenia 1.7 in 2000, Azerbaijan 2.1 in 1999, and Georgia 1.7 in 1999); and lower than fertility in Central Asia (Kazakhstan 2.1 in 1999, Kyrgyz Republic 3.4 in 1997, Turkmenistan 2.9 in 2000, and Uzbekistan 3.3 in 1996) (CDC and ORC Macro, 2003). According to information from official sources in Moldova, fertility appears to have decreased throughout the 1990s and into the present decade. Prior to independence, the estimated fertility rate for the Republic of Moldova was 2.4 in 1990 (UNFPA, 2003).2 Subsequent government estimates, which exclude the Transnistria region, indicate further declines in fertility in the 1990s, from a TFR of 1.8 in 1995, to 1.4 in 1999 (Departamentul Analize Statistice si Sociologice al Republicii Moldova, 2000), to 1.3 in 2002 (UNFPA, 2003). The 1997 Reproductive Health Survey estimated the TFR among all women, for the three-year period from 1994-1997, to be 1.8 (Serbanescu et al., 1998). However, this latter rate includes the Transnistria region, which, with a TFR of 1.3, tends to pull the overall average down (implying that without Transnistria the rate for the rest of Moldova in 1994-1997 may have been about 1.9 or 2.0). From these point estimates, it can reasonable be concluded that most fertility decline took place in the first half of the 1990s, rates plateaued in the mid- to late 1990s, and then began dropping again after the late 1990s into the early 2000s. In light of these estimates indicating a decline in fertility, the TFR of 1.7 for all women calculated from the 2005 MDHS suggests fertility may have increased in recent years (since the last official estimate in 2002). The apparent increase is also supported by estimates from international agencies monitoring population trends. The International Program Center of the U.S. Census Bureau (2005), for example, estimated an increase in fertility starting after 2000: from a TFR of 1.6 in 2000 to 1.8 in 2005. Whether this resurgence in fertility represents a real upward trend should not be concluded definitively without 1) examining related social and economic factors at play e.g., changes in family composition, selective emigration, changing social policies related to maternity leave, child allowances, etc., and 2) tracking future fertility estimates to determine if the apparent increase evolves into a long-term trend or simply represents a blip in otherwise decreasing or plateauing fertility. 4.3 FERTILITY DIFFERENTIALS BY BACKGROUND CHARACTERISTICS Table 14.2 shows the total fertility rate by background characteristics. As expected, fertility is lowest in Chisinau (1.4) where women are almost exclusively urban, and highest in the Center region (2.0) where most women are rural.3 The other regions have approximately the same level of fertility as women in the whole of Moldova (1.7 in the North region and 1.8 in the South region). 2 Although not stated explicitly, this estimate probably includes the region of Transnistria with the reason being that the region did not formally claim to be separate until after independence in 1991. 3 Chisinau is a major urban settlement located in the Center region, but it is considered a separate study domain. 52 | Fertility Levels, Trends, and Differentials In accordance with patterns observed in most other countries, a negative association between fertility and education is observed. The TFR decreases from 1.9 for women with secondary education, to 1.4 for women with secondary special or higher education. Similarly, a negative association between wealth and fertility is observed—women in the poorest households give birth to about 50 per- cent more children than women in the richest households (2.1 and 1.4, respectively). Table 4.2 also presents a crude assess- ment of trends in fertility in the various sub- groups by comparing current fertility with a measure of completed fertility, the mean number of children ever born to women age 40-49. Current fertility falls significantly below lifetime fertility in every subgroup, indicating that the general trend has been declining fertility. Over- all, the table shows that fertility has fallen by about half a child. Table 4.2 indicates that about 2 percent of women were pregnant at the time of the survey. This is likely to be an underestimate, as women in the early stages of pregnancy may be unaware or unsure that they are pregnant, while some may be reluctant to declare that they are pregnant. Differentials in pregnancy rates are generally consistent with the pattern depicted by fertility across the various subgroups. 4.4 FERTILITY TRENDS The MDHS data allow for a direct examination of fertility trends over the 20 years preceding the survey.4 Table 4.3 presents age-specific fertility rates for five-year periods preceding the survey using data on live births from respondents’ pregnancy histories. With the exception of an increase in teenage fertility following independence from the Soviet Union, there is a monotonic decline in fertility for every 5-year period in the youngest age groups. However, from 5-9 to 0-4 years prior to the survey, there is a slight increase in fertility for women age 25-29 and 30-34, as well as an abrupt deceleration in the decrease in fertility for women age 20-24 years. This recent trend of increased fertility in older ages may account for the apparent increase in fertility suggested above in section 4.2. Figure 4.2 provides a graphical representation of these declines. 4 Truncation progressively limits how far into the past fertility rates can be calculated. For example, rates cannot be calculated for women age 40-44 for the period 10-14 years before the survey because these women would have been over age 50 years at the time of the survey and thus not interviewed. Partial rates (based on partial exposure time) can be calculated for women age 40-44 for the period 5-9 years before the survey because some of these women were age 45-49 at the time of the survey and therefore included for interview. Partial rates that are subject to truncation are shown in brackets in Table 4.3. 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 years, by background characteristics, Moldova 2005 Background Characteristic Total fertility rate1 Percentage currently pregnant1 Mean number of children ever born to women age 40-49 Residence Urban 1.5 2.3 1.9 Rural 1.8 2.5 2.6 Region North 1.7 2.6 2.2 Center 2.0 2.1 2.7 South 1.8 2.5 2.6 Chisinau 1.4 2.4 1.8 Education No education/primary * * * Secondary 1.9 2.5 2.6 Secondary special/higher 1.4 2.3 2.0 Wealth quintile Lowest 2.1 2.2 3.0 Second 1.9 3.0 2.7 Middle 1.8 2.7 2.4 Fourth 1.5 2.1 2.1 Highest 1.4 2.2 1.8 Total 1.7 2.4 2.3 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Women age 15-49 years Fertility, Levels, Trends, and Differentials | 53 Table 4.3 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, Moldova 2005 Number of years preceding survey (corresponding period) Mother's age at birth 0-4 (2000-2005) 5-9 (1995-1999) 10-14 (1990-1994) 15-19 (1985-1989) 15-19 34 55 71 56 20-24 132 141 192 214 25-29 92 86 117 152 30-34 46 37 62 [85] 35-39 13 19 [23] 40-44 4 [3] 45-49 [0] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. 4.5 CHILDREN EVER BORN AND LIVING Table 4.4 presents the distribution of all women and currently married women by number of children ever born and mean number of living children. Almost all women age 15-19 (95 percent) have never given birth. This proportion declines rapidly to 4-5 percent among women age 35 and older. Therefore, despite low fertility in Moldova, childbearing is still almost universal. On average, women in Moldova have given birth to 1.4 children per woman at the end of their childbearing years. This is slightly less than the total fertility rate (1.7), the difference indicating that fertility in the past three years is slightly higher than the accumulation of births over the past 30 years. � � � � � � � � � � � � � 15-19 20-24 25-29 30-34 35-39 40-44 Age group 0 50 100 150 200 250 Births per 1,000 women 0-4 5-9 10-14 15-19� � � Figure 4.2 Trends in Age-Specific Fertility Rates 54 | Fertility Levels, Trends, and Differentials Table 4.4 Children ever born and mean number of living children Percent distribution of all women and currently married women by number of children ever born, and mean number of children ever born and mean number of living children, according to age group, Moldova 2005 Number of children ever born Age group 0 1 2 3 4 5 6+ Total Number of women Mean number of children ever born Mean number of living children ALL WOMEN 15-19 95.2 4.6 0.2 0.0 0.0 0.0 0.0 100.0 1,417 0.05 0.05 20-24 59.7 31.2 7.9 1.0 0.1 0.0 0.0 100.0 1,124 0.51 0.50 25-29 22.1 39.9 31.9 4.5 1.2 0.4 0.0 100.0 964 1.24 1.21 30-34 7.6 32.1 45.7 10.2 3.5 0.8 0.0 100.0 924 1.72 1.68 35-39 5.2 21.2 48.4 16.1 6.0 2.2 0.9 100.0 855 2.08 2.01 40-44 3.9 14.7 47.4 22.1 7.5 3.3 1.1 100.0 1,007 2.30 2.18 45-49 4.4 13.4 44.2 23.6 8.1 4.3 2.0 100.0 1,149 2.39 2.26 Total 32.8 21.3 29.8 10.5 3.6 1.5 0.6 100.0 7,440 1.38 1.33 CURRENTLY MARRIED WOMEN 15-19 57.7 40.5 1.8 0.0 0.0 0.0 0.0 100.0 136 0.44 0.44 20-24 32.9 51.2 13.9 1.9 0.2 0.0 0.0 100.0 629 0.85 0.84 25-29 14.3 42.4 36.8 4.8 1.3 0.3 0.0 100.0 794 1.37 1.35 30-34 4.8 31.2 48.1 10.9 4.0 0.9 0.0 100.0 810 1.81 1.76 35-39 2.9 18.4 51.7 17.5 6.3 2.3 0.9 100.0 746 2.17 2.11 40-44 3.5 11.8 48.4 23.4 8.0 3.8 1.1 100.0 869 2.37 2.24 45-49 3.2 11.6 45.1 25.0 8.9 4.0 2.2 100.0 953 2.46 2.33 Total 10.6 26.7 40.7 14.4 5.0 2.0 0.7 100.0 4,937 1.86 1.79 The same pattern is replicated for currently married women, except that childbearing commences much earlier: only 58 percent of currently married women age 15-19 have never given birth compared with 95 percent of all women. And, similar to the data for all women, this proportion declines rapidly to 5 percent or less for women in their thirties. The overall difference between married women and all women in the mean number of children ever born (and the mean number living) is about 0.5 children, and this difference is mainly due to younger age groups where unmarried women are less exposed to pregnancy. The smaller differences at older ages are evidence of the general fertility-reducing impact of marital dissolution (divorce or widowhood). Note that the number of children ever born rises monotonically with age, thus presupposing minimal or no recall lapse, and serves to heighten confidence in birth history reports. 4.6 BIRTH INTERVALS A birth interval, defined as the length of time between two live births, provides information about birth spacing patterns. Research has shown that short birth intervals are more likely to adversely affect maternal health and children’s chances of survival. Children born too close to a previous birth, especially if the interval between the births is less than two years, are at increased risk of health problems and dying at an early age. Longer birth intervals, on the other hand, contribute to the improved health status of both mother and child. Fertility, Levels, Trends, and Differentials | 55 Table 4.5 shows the birth intervals of children born in the five years preceding the survey, by background characteristics. The median birth interval is 56 months, with the greatest difference in interval length seen between children born to mothers in their twenties (39 months) and children born to mothers in their thirties (77 months). The interval is significantly shorter for children born to mothers in rural areas (51 months) compared with urban areas (74 months). Among regions, children born to mothers in the South region have the shortest birth interval (47 months), while those born to mothers in Chisinau have the longest birth interval (77 months). Table 4.5 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, Moldova 2005 Months since preceding birth Background characteristic 7-17 18-23 24-35 36-47 48+ Total Number of non-first births Median number of months since preceding birth Age 15-19 * * * * * * 2 * 20-29 10.0 12.4 23.2 14.8 39.6 100.0 388 39.3 30-39 5.1 4.4 8.3 7.3 74.8 100.0 350 77.2 40-49 (5.6) (1.7) (15.4) (6.1) (71.1) (100.0) 37 (110.2) Birth order 2-3 7.8 7.5 15.7 10.9 58.0 100.0 684 56.2 4-6 6.5 11.7 18.2 9.7 53.9 100.0 86 51.9 7+ * * * * * * 7 * Sex of preceding birth Male 7.5 8.1 15.2 11.2 58.0 100.0 404 58.4 Female 7.6 8.7 17.0 10.7 56.0 100.0 374 54.1 Survival of preceding birth Living 6.9 8.4 16.2 10.7 57.7 100.0 752 56.0 Dead * * * * * * 26 * Residence Urban 6.0 4.6 11.7 10.5 67.3 100.0 245 73.8 Rural 8.3 10.1 18.1 11.2 52.3 100.0 533 50.9 Region North 3.5 5.4 16.2 13.1 61.7 100.0 221 57.2 Center 10.5 10.5 16.9 9.5 52.5 100.0 253 50.9 South 7.5 12.8 18.4 12.4 48.8 100.0 173 46.5 Chisinau 8.6 3.5 11.3 8.2 68.5 100.0 131 77.3 Education No education/primary * * * * * * 12 * Secondary 8.4 9.8 18.7 12.4 50.6 100.0 535 48.8 Secondary special 4.5 5.2 9.1 7.8 73.5 100.0 126 69.3 Higher 7.1 3.9 12.1 6.7 70.3 100.0 106 73.2 Wealth quintile Lowest 10.5 13.4 18.2 9.5 48.4 100.0 193 43.9 Second 8.3 5.0 21.1 17.4 48.2 100.0 155 47.4 Middle 6.0 12.2 14.7 10.7 56.3 100.0 173 54.6 Fourth 4.1 4.9 13.7 8.4 69.0 100.0 135 66.0 Highest 7.8 3.0 10.9 8.5 69.7 100.0 121 77.4 Total 7.6 8.4 16.1 11.0 57.0 100.0 778 55.6 Note: First births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. 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. 56 | Fertility Levels, Trends, and Differentials The associations between birth interval and education, and birth interval and wealth status, are in the expected directions: that is, the length of the birth interval increases with the level of mothers’ education and with wealth status. With the wealth quintiles, there is a monotonic increase in the length of the interval from 44 months in the lowest wealth quintile, to 77 months in the highest quintile. Overall, 16 percent of children are born less than 24 months after a previous birth, an interval perceived to be “too short.” A relatively large proportion of these births are to women in their twenties (22 percent), to women in the Center and South regions (41 percent), and to women in the poorest households (24 percent). 4.7 AGE AT FIRST BIRTH The onset of childbearing has a direct bearing on fertility. Early initiation into childbearing lengthens the reproductive period and subsequently increases fertility. Conversely, a late start in childbearing shortens the reproductive period and thus decreases fertility. Table 4.6 shows median age at first birth as well as the percentage of women who gave birth by a given exact age, by five-year age groups. The youngest cohort of women for whom median age at first birth can be calculated is 25-29 years (the medians for groups age 15-19 and 20-24 cannot be determined since less than half of the women had a birth before reaching the lowest age of the age group). Table 4.6 Age at first birth Among all women, percentage who gave birth by exact age, and median age at first birth, by current age, Moldova 2005 Percentage who gave birth by exact age Current age 15 18 20 22 25 Percentage who have never given birth Number of women Median age at first birth 15-19 0.1 na na na na 95.2 1,417 a 20-24 0.1 4.8 17.3 na na 59.7 1,124 a 25-29 0.4 8.5 28.6 47.2 68.8 22.1 964 22.3 30-34 0.2 6.0 28.1 57.4 78.3 7.6 924 21.4 35-39 0.1 3.9 24.3 55.9 82.3 5.2 855 21.6 40-44 0.2 2.1 19.1 51.2 79.4 3.9 1,007 21.9 45-49 0.2 2.3 17.0 47.1 77.2 4.4 1,149 22.2 na = Not applicable a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group The MDHS findings indicate that childbearing begins relatively late in Moldova; the majority of women age 20-24 years have never given birth. Between age 30 and 34, however, over 90 percent of women have given birth. The median age at first birth for women age 25 and older is 21 or 22 years, with little variation between age groups. Further insights into the onset of childbearing can be discerned by examining the percentage of women who had a first birth by the given exact ages for various age groups of women. While these percentages increase progressively by increasing ages of first birth, as expected, the proportions of women having their first birth by age 18, for example, are slightly higher for younger women age 25-34 years, than for women age 35 and older. A similar trend is seen for women having their first birth by age 20. Fertility, Levels, Trends, and Differentials | 57 Table 4.7 Median age at first birth by background characteristics Median age at first birth among women age 25-49 years, by current age and background characteristics, Moldova 2005 Current age Background characteristic 25-29 30-34 35-39 40-44 45-49 Women age 25-49 Residence Urban 23.8 22.3 22.1 22.3 22.7 22.6 Rural 21.4 20.8 21.3 21.7 21.9 21.5 Region North 21.7 20.7 21.3 21.6 21.9 21.5 Center 21.6 21.1 21.7 21.9 22.2 21.8 South 21.9 21.1 21.1 21.8 21.7 21.6 Chisinau 24.9 22.6 22.3 22.7 23.3 23.0 Education No education/primary * * * * * * Secondary 21.0 20.7 21.0 21.4 21.8 21.2 Secondary special 22.7 21.3 21.9 22.3 22.1 22.0 Higher 24.9 23.7 22.9 23.3 23.6 23.7 Wealth quintile Lowest 20.7 20.4 20.7 21.7 21.6 21.0 Second 21.3 20.9 21.3 21.7 21.8 21.5 Middle 22.0 21.2 21.8 21.9 21.8 21.7 Fourth 22.2 21.3 21.7 22.0 22.4 21.9 Highest 24.3 22.8 22.2 22.3 23.1 22.9 Total 22.3 21.4 21.6 21.9 22.2 21.9 Note: The medians for cohorts 15-19 and 20-24 could not be determined because at least half the women have not yet had a birth. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Table 4.7 shows the differential patterns in the median age at first birth among women age 25-49 by current age, according to background characteristics. As expected, the median age at first birth shows an inverse relationship with educational attainment and with wealth status. Women in Chisinau have the highest median age at first birth compared to women in any other region; women in urban areas, in general, have relatively higher median ages at first birth than women in rural areas. 4.8 TEENAGE PREGNANCY AND MOTHERHOOD It is well known that adolescent pregnancy, early childbearing, and motherhood have negative socioeconomic and health consequences. Adolescent mothers are more likely to have complications during labor, which result in higher morbidity and mortality for themselves and their children. Moreover, childbearing during the teenage years frequently has adverse social consequences, particularly on female educational attainment, since women who become mothers in their teens are more likely to curtail education and subsequently compromise their prospects for good careers. Table 4.8 shows the percentage of women age 15-19 who are mothers or who were pregnant with their first child at the time of the MDHS, by selected background characteristics. Only 6 percent of teenagers have begun childbearing, including about 5 percent who are already mothers. As expected, the proportion of young women who have begun childbearing increases rapidly with age, from 0 percent among women age 15, to 17 percent of women age 19. 58 | Fertility Levels, Trends, and Differentials Teenage fertility varies by background factors presented in Table 4.8. With regards to residence, about twice as many young women in rural areas than in urban areas have begun childbearing. Teenagers in the North region are about 5 times more likely than those in Chisinau to start childbearing by age 19. The proportion of early childbearing decreases with educational attainment, and for wealth status, teenagers in the fourth and highest wealth quintiles are by far the least likely to have a child during their teenage years. Table 4.8 Pregnancy and motherhood among teenage women Percentage of women age 15-19 who are mothers or pregnant with their first child, by background characteristics, Moldova 2005 Percentage who are: Background characteristic Mothers Pregnant with first child Percentage who have begun childbearing Number of women Age 15 0.0 0.0 0.0 262 16 1.5 1.3 2.7 290 17 1.6 1.7 3.3 295 18 7.0 1.3 8.3 308 19 14.2 2.4 16.6 262 Residence Urban 2.7 1.1 3.9 547 Rural 6.1 1.5 7.6 870 Region North 7.7 1.8 9.5 398 Center 4.6 1.5 6.1 456 South 4.3 1.8 6.1 268 Chisinau 1.6 0.0 1.6 295 Education No education/primary * * * 4 Secondary 5.0 1.4 6.4 1,229 Secondary special 2.8 0.9 3.7 76 Higher 2.0 0.7 2.7 109 Wealth quintile Lowest 7.7 0.5 8.3 272 Second 8.8 2.6 11.3 242 Middle 5.6 2.2 7.8 306 Fourth 1.8 1.2 3.0 315 Highest 1.0 0.2 1.3 282 Total 4.8 1.3 6.1 1,417 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Family Planning | 59 FAMILY PLANNING 5 5.1 KNOWLEDGE OF CONTRACEPTIVE METHODS One major objective of the 2005 MDHS was to assess the level of knowledge about family plan- ning methods. Individuals who have adequate information about the available methods of contraception are better able to develop a rational approach to planning their families. Information on knowledge of contraception was collected during the survey by asking respondents to name ways or methods by which a couple could delay or avoid pregnancy. If the respondent failed to mention a particular method spon- taneously, the interviewer described the method and asked whether the respondent recognized it. In this manner, information was collected about eleven modern methods (female sterilization, male sterilization, the pill, intrauterine device [IUD], injectables, implants, male condoms, diaphragm, foam/jelly, lactational amenorrhea and emergency contraception) and two traditional methods (periodic abstinence and withdrawal). Provision was also made in the questionnaire to record any other methods named spontaneously by the respondent. Table 5.1 shows data on knowledge of contraceptive methods among all women age 15-49, as well as for those who are currently married and unmarried. Knowledge of family planning is nearly universal, with 99 percent of all women age 15-49 knowing at least one method. 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 experience who know any contraceptive method, by specific method, Moldova 2005 Unmarried women who ever had sex Method All women Currently married women Sexually active1 Not sexually active2 Unmarried women who never had sex Any method 98.9 99.5 99.2 98.6 96.6 Any modern method 98.6 99.2 99.2 98.4 96.5 Female sterilization 66.0 70.9 68.0 64.9 49.2 Male sterilization 42.9 46.6 50.2 42.8 28.2 Pill 89.3 90.3 94.6 88.3 85.2 IUD 93.8 97.2 95.7 92.8 81.7 Injectables 49.3 52.2 52.6 48.6 38.7 Implants 17.9 18.9 23.4 18.1 13.0 Male condom 96.4 96.5 98.6 96.3 95.5 Diaphragm 20.4 20.2 29.5 23.3 17.3 Foam/jelly 43.8 45.6 56.9 45.3 34.0 Lactational amenorrhea (LAM) 54.0 66.0 40.2 52.7 15.6 Emergency contraception 38.1 38.6 53.0 41.1 31.4 Any traditional method 86.5 93.8 92.6 89.6 57.8 Periodic abstinence 58.7 63.3 66.3 60.0 40.1 Withdrawal 83.4 92.3 89.1 85.7 49.7 Folk method 3.2 3.7 4.4 4.3 0.5 Mean number of methods known 7.6 8.0 8.2 7.6 5.8 Number of women 7,440 4,937 305 783 1,415 1 Women who had sexual intercourse in the month preceding the survey 2 Women who did not have sexual intercourse in the month preceding the survey 60 | Family Planning Modern methods are more widely known than traditional methods. For example, 99 percent of all women have heard of at least one modern method, while only 87 percent know of a traditional method. Among all women, the male condom, IUD, the pill, and withdrawal are the most widely known methods of family planning, with over 80 percent of all women saying they had heard of these methods. Female sterilization is known by two-thirds of women, while periodic abstinence (rhythm method) is recognized by almost six in ten women. Just over half of women have heard of the lactational amenorrhea or LAM method, while around 40-50 percent of all women have heard of injectables, male sterilization, and foam/jelly. The least widely known methods are emergency contraception, diaphragm, and implants. As expected, contraceptive knowledge is slightly higher among currently married women and sexually active unmarried women than among all women. The mean number of methods recognized by all women is 7.6, compared to 8.0 among married women and 8.2 among sexually active unmarried women. Unmarried women who have ever had sex but were not sexually active in the month prior to the survey have heard of an average of 7.6 methods. Unmarried women who have never had sexual intercourse are the least likely to have heard of every contraceptive method; nevertheless, they have heard of an average of 5.8 methods. The gap in knowledge between unmarried women who have never had sex and all other groups of women is most apparent for permanent methods (i.e., sterilization) and LAM. 5.2 EVER USE OF CONTRACEPTION All women interviewed in the 2005 MDHS who said that they had heard of a method of family planning were asked whether they had ever used that method. Table 5.2 shows the percentage of all women, currently married women, and sexually active unmarried women who have ever used specific methods of family planning, by age. The data show that 91 percent of currently married women have ever used a contraceptive method, 81 percent have used a modern method, and 68 percent have used a traditional method. The methods most commonly ever used by married women are withdrawal (63 percent), the IUD (52 percent), and male condom (38 percent). Nineteen to 30 percent of married women have used LAM, the pill, and periodic abstinence. Ever use of other methods does not exceed 10 percent. Sexually active unmarried women are as likely to have ever used family planning as currently married women; however, the level of ever use is lower among all women (73 percent), largely because this group includes women who are not sexually active and therefore not in need of contraception. Sexually active unmarried women are much more likely (68 percent) than either all women or currently married women to have used the male condom. However, they are less likely than other women to have used long-term methods such as the IUD or sterilization. Family Planning | 61 Table 5.2 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 and age, Moldova 2005 Modern method Traditional method Age Any method Any modern method Female sterili- zation Male sterili- zation Pill IUD Male con- dom Foam/ jelly LAM Emer- gency contra- ception Other Any tradi- tional method Periodic absti- nence With- drawal Folk method Number of women ALL WOMEN 15-19 17.1 13.9 0.0 0.0 2.3 1.2 11.8 0.8 2.0 0.9 0.2 10.0 1.5 9.6 0.4 1,417 20-24 68.8 58.8 0.1 0.1 14.5 15.5 43.6 4.7 16.2 3.6 0.4 48.8 11.7 45.7 1.2 1,124 25-29 88.9 80.0 1.8 0.7 28.6 38.0 48.9 8.8 30.6 4.8 1.2 65.6 19.2 60.9 1.9 964 30-34 90.8 84.2 3.7 0.3 27.2 54.7 44.2 8.3 30.5 6.0 2.1 66.3 20.9 60.1 2.4 924 35-39 91.4 83.1 6.4 0.0 23.4 61.0 36.6 7.1 26.9 3.4 1.8 68.2 21.0 61.8 2.1 855 40-44 91.0 80.9 7.4 0.3 18.0 62.4 27.3 5.2 29.6 2.2 1.7 66.7 21.7 60.1 3.1 1,007 45-49 87.2 72.7 6.4 0.0 10.8 54.5 22.1 3.8 25.7 1.8 2.1 66.5 19.5 60.8 3.7 1,149 Total 72.7 64.1 3.4 0.2 16.5 38.2 32.0 5.1 21.6 3.0 1.3 53.1 15.5 48.7 2.0 7,440 CURRENTLY MARRIED WOMEN 15-19 75.6 58.6 0.0 0.0 12.6 11.6 41.9 5.4 19.8 2.9 1.0 45.9 5.1 45.9 2.0 136 20-24 89.4 76.7 0.3 0.1 19.0 26.2 51.2 5.5 28.2 3.6 0.6 64.1 14.8 60.7 1.2 629 25-29 92.7 83.8 2.1 0.7 29.5 42.7 50.0 8.6 34.2 4.7 1.3 70.2 20.1 65.1 1.9 794 30-34 92.9 86.7 3.9 0.3 28.7 57.3 44.7 8.7 32.6 6.2 2.4 68.4 21.2 62.2 2.2 810 35-39 93.0 84.6 7.3 0.0 23.8 63.6 35.9 6.9 27.2 3.2 2.0 69.6 20.1 64.0 2.1 746 40-44 92.4 82.2 7.3 0.3 18.7 64.1 27.6 5.2 30.2 2.0 1.7 68.2 21.9 62.8 2.9 869 45-49 89.1 74.1 6.5 0.0 10.2 57.1 21.7 3.9 25.9 1.5 1.6 68.3 19.5 62.7 3.5 953 Total 91.1 80.6 4.7 0.2 21.1 51.8 37.5 6.4 29.4 3.4 1.6 67.7 19.4 62.5 2.4 4,937 SEXUALLY ACTIVE UNMARRIED WOMEN1 15-19 86.4 75.0 0.0 0.0 12.1 1.1 68.0 4.1 1.1 10.1 1.3 57.6 9.3 56.5 2.8 73 20-24 91.8 76.9 0.0 0.0 19.5 1.3 73.0 10.2 1.1 9.3 0.0 68.1 19.5 62.6 3.0 109 25-29 (96.1) (85.0) (2.4) (0.0) (56.6) (20.3) (64.7) (18.4) (13.4) (8.9) (0.0) (62.6) (23.7) (60.1) (0.0) 36 30-34 (87.8) (78.0) (0.0) (0.0) (20.8) (54.6) (63.5) (8.5) (19.1) (0.0) (0.0) (54.7) (19.9) (47.1) (0.0) 27 35-39 * * * * * * * * * * * * * * * 18 40-44 (94.2) (94.2) (12.7) (0.0) (5.9) (50.8) (38.8) (0.0) (23.1) (3.4) (0.0) (56.9) (7.9) (49.0) (0.0) 23 45-49 * * * * * * * * * * * * * * * 18 Total 91.3 80.8 1.4 0.0 23.8 17.7 67.5 9.1 7.9 8.9 0.3 63.6 19.6 58.7 3.3 305 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. LAM = Lactational amenorrhea method 1 Unmarried women who had sexual intercourse in the month preceding the survey 5.3 CURRENT USE OF CONTRACEPTIVE METHODS Over two-thirds of currently married women (68 percent) in Moldova are using some method of contraception (Table 5.3). Modern methods are more commonly used than traditional methods; 44 percent of married women use modern methods, while 24 percent use traditional methods. As expected, contraceptive use is lower among all women (50 percent) than among married women and sexually active unmarried women, since the former include women who are not married or sexually active and therefore are not in need of family planning. 62 | Family Planning Table 5.3 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, Moldova 2005 Modern method Traditional method Age Any method Any modern method Female sterili- zation Male sterili- zation Pill IUD Male con- dom LAM Other Any tradi- tional method Periodic absti- nence With- drawal Folk method Not currently using Total Number of women ALL WOMEN 15-19 11.5 7.5 0.0 0.0 0.6 1.1 5.3 0.4 0.1 4.0 0.6 3.4 0.1 88.5 100.0 1,417 20-24 45.1 29.8 0.1 0.0 3.9 10.2 12.7 1.9 1.0 15.3 1.5 13.8 0.1 54.9 100.0 1,124 25-29 63.1 45.5 1.8 0.0 4.9 23.5 10.7 2.3 2.4 17.6 1.8 15.0 0.8 36.9 100.0 964 30-34 69.5 49.4 3.7 0.0 5.2 29.0 8.7 1.2 1.6 20.2 3.9 15.7 0.6 30.5 100.0 924 35-39 71.2 48.6 6.4 0.0 3.5 31.0 5.6 0.4 1.8 22.6 3.8 18.0 0.8 28.8 100.0 855 40-44 67.2 42.6 7.4 0.2 2.7 27.9 3.2 0.0 1.2 24.5 3.7 19.7 1.1 32.8 100.0 1,007 45-49 43.5 22.4 6.4 0.0 0.2 13.1 1.7 0.0 1.0 21.1 3.5 16.3 1.3 56.5 100.0 1,149 Total 49.8 32.8 3.4 0.0 2.8 17.7 6.7 0.8 1.2 17.0 2.5 13.9 0.6 50.2 100.0 7,440 CURRENTLY MARRIED WOMEN 15-19 58.4 33.9 0.0 0.0 4.2 11.0 13.6 4.4 0.7 24.5 2.3 22.2 0.0 41.6 100.0 136 20-24 63.1 41.5 0.3 0.0 4.7 17.2 14.4 3.4 1.5 21.7 1.9 19.8 0.0 36.9 100.0 629 25-29 70.7 50.9 2.1 0.0 5.3 26.9 11.3 2.7 2.5 19.9 2.1 17.0 0.8 29.3 100.0 794 30-34 74.9 52.6 3.9 0.0 5.6 30.9 8.9 1.3 1.8 22.3 4.1 17.6 0.6 25.1 100.0 810 35-39 78.3 53.1 7.3 0.0 3.6 34.0 5.9 0.4 1.9 25.2 3.9 20.5 0.8 21.7 100.0 746 40-44 73.5 45.3 7.3 0.2 2.9 30.0 3.6 0.0 1.4 28.2 4.2 22.7 1.3 26.5 100.0 869 45-49 50.2 25.0 6.5 0.0 0.2 15.1 1.9 0.0 1.2 25.3 4.2 19.5 1.5 49.8 100.0 953 Total 67.8 43.8 4.7 0.0 3.6 25.2 7.4 1.3 1.7 23.9 3.5 19.6 0.9 32.2 100.0 4,937 SEXUALLY ACTIVE UNMARRIED WOMEN 1 15-19 76.5 52.2 0.0 0.0 1.6 1.1 48.2 0.0 1.2 24.3 3.6 19.6 1.1 23.5 100.0 73 20-24 69.4 45.1 0.0 0.0 9.7 0.2 33.7 0.0 1.4 24.3 2.8 20.8 0.7 30.6 100.0 109 25-29 (58.6) (37.9) (2.4) (0.0) (11.2) (9.4) (10.5) (0.0) (4.5) (20.7) (2.6) (18.2) (0.0) (41.4) (100.0) 36 30-34 (64.0) (51.0) (0.0) (0.0) (1.8) (25.8) (23.4) (0.0) (0.0) (13.0) (3.0) (10.1) (0.0) (36.0) (100.0) 27 35-39 * * * * * * * * * * * * * * * 18 40-44 (70.9) (60.6) (12.7) (0.0) (3.4) (36.7) (7.7) (0.0) (0.0) (10.3) (4.8) (5.5) (0.0) (29.1) (100.0) 23 45-49 * * * * * * * * * * * * * * * 18 Total 66.8 46.1 1.4 0.0 6.1 8.3 28.5 0.0 1.8 20.6 3.7 16.3 0.7 33.2 100.0 305 Note: If more than one method is used, only the most effective method is considered in this tabulation. 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. LAM = Lactational amenorrhea method 1 Women who had sexual intercourse in the month preceding the survey The IUD is the most widely used method, being used by 25 percent of married women (Figure 5.1). The next most widely used method is withdrawal, used by 20 percent of married women. Male condoms are used by about 7 percent of married women, especially younger women. Five percent of married women have been sterilized and 4 percent each are using the pill and periodic abstinence (rhythm method). Sexually active unmarried women are far more likely to use male condoms and far less likely to use the IUD than either married women or all women. Family Planning | 63 Figure 5.1 Contraceptive Use among Currently Married Women MDHS 2005 Not using 32% Female sterilization 5% Pill 4% IUD 25% Condom 7% Withdrawal 20% Rhythm 4% Other 4% Note: Totals may not add to 100 because of rounding. Use of any contraceptive method rises with age, from 58 percent among married women age 15-19, to a peak of 78 percent at age 35-39, and then declines to 50 percent at age 45-49. Younger married women are more likely to use condoms than older women and less likely to use long-term or permanent methods like the IUD and sterilization. Use of traditional methods is stable across age groups (20 to 28 percent). 5.4 TRENDS IN CONTRACEPTIVE USE Contraceptive use appears to have decreased slightly since 1997, from 74 to 72 percent of married women age 15-44.1 The proportion of women using modern methods has also decreased slightly from 50 to 48 percent. Use of the IUD has dropped considerably, from 38 percent of married women age 15-44 in 1997 to 28 percent of those age 15-44 in 2005. This decline has been partially offset by slight increases in use of condoms (from 6 to 9 percent of married women age 15-44), the pill (from 2 to 4 percent), and other methods like LAM and female sterilization. Use of traditional methods has remained steady. Compared with other countries in Eastern Europe and Eurasia, contraceptive use among married women age 15-44 in Moldova (72 percent) appears to be higher than that in Romania (64 percent in 1999), Ukraine (68 percent in 1999), Armenia (58 in 2005), Azerbaijan (55 percent in 2001), Georgia (41 percent in 1999), Kazakhstan (62 percent in 1999), Kyrgyz Republic (60 percent in 1997), Turkmenistan (55 percent in 2000), and Uzbekistan (70 percent in 2002) (AIC, 2004; CDC and ORC Macro, 2003; NSS, 2006). 1 The 1997 MRHS data refer to married women age 15-44; consequently the data from the 2005 MDHS were re- computed for the same age group. Interpretation of trends is also hampered by the fact that the 1997 survey included Transnistria, whereas the 2005 survey did not. 64 | Family Planning 5.5 DIFFERENTIALS IN CONTRACEPTIVE USE BY BACKGROUND CHARACTERISTICS As shown in Table 5.4, some women in Moldova are more likely to use contraceptives than others. Although the level of any contraceptive use is about the same for married women in urban and rural areas (67-68 percent), urban women are more likely than rural women to use modern methods (48 and 41 percent, respectively) and conversely, rural women are more likely than urban women to use traditional methods (27 percent versus 19 percent, respectively). In terms of region, married women use contraception to about the same extent in all regions, ranging from 67 to 69 percent, although in Chisinau, women are much more likely to use modern methods (51 percent) than women in other regions (41-43 percent). Table 5.4 Current use of contraception by background characteristics Percent distribution of currently married women by contraceptive method currently used, according to background characteristics, Moldova 2005 Modern method Traditional method Background characteristic Any method Any modern method Female sterili- zation Male sterili- zation Pill IUD Male con- dom LAM Other Any tradi- tional method Periodic absti- nence With- drawal Folk method Not currently using Total Number of women Residence Urban 67.2 47.8 4.6 0.0 5.0 21.6 12.9 0.9 2.8 19.4 4.9 13.7 0.8 32.8 100.0 2,045 Rural 68.2 41.0 4.7 0.1 2.6 27.8 3.5 1.5 0.9 27.2 2.4 23.8 0.9 31.8 100.0 2,892 Region North 69.0 41.5 4.8 0.1 3.4 26.0 5.2 1.0 0.9 27.5 3.4 23.4 0.7 31.0 100.0 1,515 Center 66.7 41.1 4.8 0.0 2.2 27.9 3.5 1.5 1.1 25.6 3.0 21.7 1.0 33.3 100.0 1,336 South 67.3 43.1 4.9 0.0 3.0 28.5 3.8 1.7 1.2 24.2 2.0 21.7 0.5 32.7 100.0 958 Chisinau 67.9 51.0 4.0 0.0 5.9 18.3 17.9 1.0 3.9 16.9 5.3 10.3 1.2 32.1 100.0 1,127 Education No education/ primary (61.2) (38.3) (5.5) (0.0) (1.1) (17.6) (10.6) (3.5) (0.0) (22.9) (0.0) (22.9) (0.0) (38.8) 100.0 41 Secondary 65.3 40.2 5.2 0.0 2.6 25.6 4.7 1.5 0.7 25.2 1.7 22.5 1.0 34.7 100.0 2,884 Secondary special 70.7 47.7 5.6 0.0 4.3 28.5 6.3 0.9 2.0 23.0 4.6 17.7 0.6 29.3 100.0 1,046 Higher 72.2 50.9 2.0 0.2 5.9 21.1 16.4 1.0 4.3 21.3 7.7 12.8 0.7 27.8 100.0 966 Number of living children 0 35.7 22.2 0.5 0.0 3.5 0.9 15.8 0.0 1.4 13.5 2.1 11.0 0.4 64.3 100.0 534 1-2 71.3 48.0 4.7 0.0 4.0 28.2 7.6 1.5 2.0 23.3 4.3 18.3 0.7 28.7 100.0 3,435 3-4 74.0 42.3 6.5 0.2 2.2 29.3 1.9 1.2 1.0 31.7 1.5 28.5 1.7 26.0 100.0 875 5+ 64.2 29.2 8.4 0.0 2.2 17.4 0.0 1.2 0.0 34.9 0.0 34.9 0.0 35.8 100.0 93 Wealth quintile Lowest 66.9 36.6 4.6 0.0 2.4 25.4 1.5 2.7 0.0 30.3 0.2 29.2 1.0 33.1 100.0 839 Second 66.1 38.6 5.3 0.2 1.8 26.5 2.9 1.3 0.5 27.6 2.3 24.3 0.9 33.9 100.0 834 Middle 68.5 43.0 3.9 0.0 2.8 29.7 4.0 1.2 1.3 25.5 2.9 22.1 0.5 31.5 100.0 1,029 Fourth 66.9 46.4 5.4 0.0 4.1 25.1 8.9 0.9 2.0 20.5 4.8 14.8 0.9 33.1 100.0 1,081 Highest 69.8 51.3 4.2 0.0 6.0 20.4 16.3 0.6 3.8 18.5 5.9 11.6 1.0 30.2 100.0 1,154 Total 67.8 43.8 4.7 0.0 3.6 25.2 7.4 1.3 1.7 23.9 3.5 19.6 0.9 32.2 100.0 4,937 Note: If more than one method is used, only the most effective method is considered in this tabulation. Figures in parentheses are based on 25-49 unweighted cases. LAM = Lactational amenorrhea method Family Planning | 65 Contraceptive use increases with level of education. For example, 72 percent of married women with higher education are using a method of contraception, compared with 65 percent of women with secondary education. Use also tends to increase with the number of living children—from 36 percent among married women with no children to 74 percent among married women with 3 or 4 children. Although there is almost no difference in use of any contraceptive method by wealth index, there is a steady rise in use of modern methods as wealth increases. For example, 37 percent of married women in the lowest wealth quintile are using a modern contraceptive method, compared to 51 percent of those in the highest wealth quintile. 5.6 CURRENT USE OF CONTRACEPTIVES BY WOMEN’S STATUS Table 5.5 shows the level of current use of contraceptive methods by various women’s status indicators. Current use of a modern contraceptive method increases with the number of decisions in which a woman has a final say, from 30 percent among married women with no say in any decision to 44 percent among women who participate in 3-4 decisions. However, interpretation of the data is hampered by the fact that very few women interviewed did not participate in at least three of the decisions. Table 5.5 Current use of contraception by women's status Percent distribution of currently married women by contraceptive method currently used, according to selected indicators of women's status, Moldova 2005 Modern method Traditional method Women's status indicators Any method Any modern method Female sterili- zation Pill IUD Male con- dom LAM Other Any tradi- tional method Periodic absti- nence With- drawal Folk method Not currently using Total Number of women Number of decisions in which woman has final say1 0 (60.1) (29.8) (6.3) (2.0) (15.2) (6.4) (0.0) (0.0) (30.3) (2.2) (28.1) (0.0) (39.9) 100.0 39 1-2 66.7 38.9 3.1 1.8 21.4 10.8 0.9 0.8 27.9 6.5 18.7 2.7 33.3 100.0 91 3-4 67.9 44.1 4.7 3.6 25.4 7.3 1.3 1.7 23.8 3.4 19.6 0.8 32.1 100.0 4,807 Number of reasons to refuse sex with husband 0 53.4 32.6 3.2 0.7 23.5 4.1 1.2 0.0 20.8 1.9 18.6 0.3 46.6 100.0 255 1-2 69.3 44.0 4.9 4.0 24.8 7.1 1.0 2.3 25.2 4.3 19.8 1.2 30.7 100.0 1,098 3-4 68.3 44.6 4.7 3.7 25.5 7.7 1.4 1.6 23.8 3.3 19.6 0.8 31.7 100.0 3,584 Number of reasons wife beating is justified 0 68.9 45.3 4.8 3.8 25.2 8.3 1.2 1.9 23.7 4.0 19.0 0.7 31.1 100.0 3,878 1-2 64.1 40.2 4.5 3.1 26.8 3.9 1.1 0.9 23.9 1.3 20.9 1.7 35.9 100.0 800 3-4 62.7 35.0 3.8 2.2 22.4 3.8 2.0 0.9 27.7 1.7 24.5 1.5 37.3 100.0 209 5 (57.8) (27.5) (2.5) (0.0) (14.6) (4.5) (6.0) (0.0) (30.2) (4.5) (25.7) (0.0) (42.2) 100.0 49 Total 67.8 43.8 4.7 3.6 25.2 7.4 1.3 1.7 23.9 3.5 19.6 0.9 32.2 100.0 4,937 Note: If more than one method is used, only the most effective method is considered in this tabulation. Figures in parentheses are based on 25-49 unweighted cases. LAM = Lactational amenorrhea method 1 Either by herself or jointly with others 66 | Family Planning Married women who do not think that a woman is justified in refusing to have sex with her husband for any of the reasons cited are less likely to be using contraception than women who think refusal is justified in some situations. Current use of modern contraceptive methods rises from 33 percent among married women who believe there is no justifiable reason for refusing sex with a husband to 45 percent among women who agree with three or four reasons for refusing to have sex with a husband. Married women who do not believe that there is any reason to justify wife beating are more likely to be using contraception than those who feel that wife beating is justified. Current use of contraception decreases from 69 percent among women who do not agree with any of the reasons to justify wife beating to 63 percent among women who agree with 3 or 4 reasons to justify wife beating. 5.7 TIMING OF FIRST USE OF CONTRACEPTION Table 5.6 shows the distribution of women by current age and the number of living children at the time they first used contraception. The results imply that Moldovan women are adopting family planning at lower parities (i.e., when they have fewer children) than in the past. Among younger women (age 20-24), almost half (49 percent) used contraception before having any children, compared with only 12 percent of women age 45-49. Table 5.6 Number of children at first use of contraception Percent distribution of women by number of living children at the time of first use of contraception, according to current age, Moldova 2005 Number of living children at time of first use of contraception Current age Never used contraception 0 1 2 3 4+ Missing Total Number of women 15-19 82.9 14.6 2.3 0.0 0.0 0.0 0.2 100.0 1,417 20-24 31.2 48.8 17.5 2.1 0.3 0.0 0.1 100.0 1,124 25-29 11.1 41.5 35.0 10.0 1.6 0.3 0.4 100.0 964 30-34 9.2 27.4 42.6 16.7 2.9 1.0 0.2 100.0 924 35-39 8.6 18.3 44.1 22.4 4.2 2.1 0.3 100.0 855 40-44 9.0 14.6 44.2 23.6 5.3 3.2 0.2 100.0 1,007 45-49 12.8 12.3 42.5 21.7 7.9 2.7 0.1 100.0 1,149 Total 27.3 24.9 30.5 12.8 3.0 1.3 0.2 100.0 7,440 5.8 KNOWLEDGE OF THE FERTILE PERIOD An elementary knowledge of reproductive physiology provides a useful background for success- ful practice of coitus-related methods, such as the calendar or rhythm method, the Billings method, and other methods collectively called “periodic abstinence.” The successful use of such methods depends in part on an understanding of when, during the ovulatory cycle, a woman is most likely to conceive. Women and men were asked, “From one menstrual period to the next, are there certain days when a woman is more likely to get pregnant if she has sexual relations?” If the answer was “yes,” they were further asked whether that time was just before her period begins, during her period, right after her period has ended, or halfway between two periods. Table 5.7 provides the results for all women and men, as well as for those who report that they are currently using the periodic abstinence and those who are not. Family Planning | 67 Table 5.7 Knowledge of fertile period Percent distribution of women and men by knowledge of the fertile period during the ovulatory cycle, according to current use/non use of periodic abstinence, Moldova 2005 Perceived fertile period Users of periodic abstinence Nonusers of periodic abstinence All women/ men WOMEN Just before her period begins 0.6 4.4 4.4 During her period 0.8 1.0 1.0 Right after her period has ended 7.8 11.4 11.3 Halfway between two periods 85.0 45.8 46.8 Other 0.0 0.0 0.0 No specific time 3.5 6.8 6.7 Don't know 1.1 30.3 29.6 Missing 1.2 0.2 0.2 Total 100.0 100.0 100.0 Number of women 188 7,252 7,440 MEN Just before her period begins 4.2 3.3 3.5 During her period 2.1 1.1 1.3 Right after her period has ended 14.9 6.8 8.9 Halfway between two periods 55.6 16.1 26.8 Other 0.8 0.3 0.4 No specific time 3.0 28.5 21.6 Don't know 19.3 43.6 37.0 Missing 0.2 0.4 0.3 Total 100.0 100.0 100.0 Number of men 680 1,828 2,508 Among all women, just under half (47 percent) understand that a woman is most likely to conceive halfway between her menstrual periods. Thirty percent say they do not know when the fertile period falls, 11 percent wrongly believe that the fertile period is right after a woman’s period has ended, and 7 percent believe that there is no specific fertile time. As expected, users of periodic abstinence are much more likely than nonusers to know that the fertile time in a woman’s menstrual cycle is halfway between periods (85 percent versus 46 percent). The same questions were asked of men and the results indicate that they are less knowledgeable than women about the ovulatory cycle. Only 27 percent of men know that a woman is most likely to conceive if she has sex halfway between her menstrual periods. Almost 40 percent of men say they don’t know when the fertile period is, while 22 percent say there is no specific fertile time. As with women, men who say they are using periodic abstinence are far more likely to know about women’s ovulatory cycle than those who are not using the method. 5.9 SOURCE OF CONTRACEPTION Information on where women obtain their contraceptives is useful for family planning program managers and implementers for planning logistics. In the 2005 MDHS, women who reported using a modern contraceptive method at the time of the survey were asked where they obtained the method the last time they acquired it. Since some women may not exactly know in which category the source they use falls (e.g., government versus private hospital), interviewers were instructed to note the full name of the source or facility. Supervisors and field editors were instructed to verify that the name and source type 68 | Family Planning were consistent, asking informants in the clusters for the names of local family planning outlets, if necessary, in order to improve the accuracy of source reporting. Table 5.8 shows that public (government) facilities provide contraceptives to more than two in three users (69 percent), while 28 percent of users are supplied through private medical sources, and 3 percent through other private sources (e.g., shops). The most common single source of contraceptives in Moldova is government hospitals, which supply one-third of all users of modern methods. Family doctors and pharmacies each supply about one-quarter of users. Government family planning offices only supply 7 percent of users with their methods. Private hospitals and clinics and private doctors also account for only a very small share (2 percent) of contraceptive provision. Government sources supply almost all users of long-term methods, such as female sterilization (99 percent) and IUD (95 percent). However, the large majority of pill and condom users get their methods from private sources, especially pharmacies. Nevertheless, one-third of pill users get their supplies from government sources. Table 5.8 Source of contraception Percent distribution of current users of modern contraceptive methods by most recent source of method, according to specific method, Moldova 2005 Source Female sterili- zation Pill IUD Male condom Other Total Public sector 99.3 33.3 94.6 8.1 16.0 68.6 Government hospital 96.1 8.7 37.8 1.6 4.0 32.8 Family doctor 3.2 17.3 46.6 3.8 9.4 28.9 Family planning office 0.0 7.3 9.7 2.7 2.5 6.7 Other public 0.0 0.0 0.6 0.0 0.0 0.3 Private medical sector 0.4 65.2 4.7 78.1 79.1 27.7 Private hospital, clinic 0.4 3.6 2.3 0.4 4.1 1.9 Pharmacy 0.0 61.3 2.3 77.5 73.9 25.7 Private doctor's office 0.0 0.2 0.1 0.3 1.1 0.2 Other private 0.0 1.0 0.5 12.2 3.7 3.1 Shop 0.0 0.0 0.0 3.1 0.0 0.7 Friend/relative 0.0 1.0 0.5 9.0 3.7 2.4 Other/missing 0.3 0.5 0.2 1.6 1.2 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 256 207 1,320 501 84 2,377 Note: Table excludes lactational amenorrhea method (LAM). 5.10 INFORMED CHOICE Current users of modern methods who are well informed about the side effects and problems associated with methods and who know of a range of method options are better able to make an informed choice about the method they would like to use. Current users of various modern contraceptive methods were asked whether at the time they started using the method, they were informed about side effects or problems that they might have with the method. Table 5.9 shows the percentage of current users of modern methods who were informed about side effects or problems of the method used, informed of other methods they could use, and informed that sterilization is a permanent method; these are broken down by method type and the place where current users obtained the method. Family Planning | 69 Table 5.9 Informed choice Among current users of modern contraceptive methods who adopted the current method in the five years preceding the survey, percentage who were informed about the side effects of the method used, percentage who were informed what to do if side effects were experienced, and percentage who were informed of other methods that could be used for contraception, percentage of women who were sterilized in the five years preceding the survey who were informed that they would not be able to have any more children, by specific method and initial source of method, Moldova 2005 Method/Source Informed about side effects or problems of method used1 Informed what to do if experienced side effects1 Informed of other methods that could be used Informed that sterilization is permanent2 Method Female sterilization 33.6 30.6 21.6 87.4 Pill 60.3 57.6 58.9 na IUD 45.2 44.0 34.5 na Initial source of method3 Public sector 71.8 68.7 56.2 91.7 Government hospital 68.6 64.6 54.6 91.1 Government health center 73.0 70.8 53.9 na Family planning clinic 78.9 75.5 68.8 na Private medical sector 63.8 61.6 58.1 na Total 45.4 43.8 37.1 87.4 na = Not applicable 1 Among users of female sterilization, pill, and IUD 2 Sterilized women who were told that they would not be able to have any more children 3 Source at start of current episode of use Forty-five percent of users of modern contraceptives were informed about the side effects or health problems of the method they were provided and 44 percent were informed of what to do if they experienced such side effects. Only 37 percent of women who are using a modern method said they were told about other methods that they could use. Almost all women (87 percent) who were sterilized during the five-year period preceding the survey were informed that they would not be able to have any more children. The results indicate that pill users are more likely to be informed of side effects than users of the IUD or female sterilization. They are also more likely to be told about other methods they could use. Differences in informed choice by source of method are not large. 5.11 CONTRACEPTIVE DISCONTINUATION A prominent concern for managers of family planning programs is the discontinuation of methods. In the 2005 MDHS “calendar” section, all segments of contraceptive use between January 2000 and the date of interview were recorded, along with reasons for any discontinuation. One-year contraceptive discontinuation rates based on the calendar data are presented in Table 5.10.2 2 The discontinuation rates presented here include only those segments of contraceptive use that began since January 2000. The rates apply to the 3-63 month period prior to the survey; exposure during the month of interview and the two months prior are excluded to avoid the biases that may be introduced by unrecognized pregnancies. These cumulative discontinuation rates represent the proportion of users discontinuing a method within 12 months after the start of use. The rates are calculated by dividing the number of women discontinuing a method by the number exposed at that duration. The single-month rates are then cumulated to produce a one-year rate. In calculating the rate, the various reasons for discontinuation are treated as competing risks. 70 | Family Planning Table 5.10 First-year contraceptive discontinuation rates Percentage of contraceptive users who discontinued use of a method within 12 months after beginning its use, by reason for discontinuation and specific method, Moldova 2005 Reason for discontinuation Method Method failure Desire to become pregnant Switched to another method1 Other reason Total Pill 5.1 10.8 20.8 13.0 49.8 IUD 1.3 0.6 2.9 1.8 6.6 Male condom 5.0 6.7 14.6 12.5 38.8 LAM 4.4 2.2 67.5 17.2 91.3 Periodic abstinence 11.4 4.0 12.5 6.9 34.8 Withdrawal 12.9 5.1 12.3 6.7 37.1 All methods 6.6 4.4 17.9 8.8 37.8 Note: Table is based on episodes of contraceptive use that began 3 to 59 months prior to the survey. LAM = Lactational amenorrhea method 1 Used a different method in the month following discontinuation or said they wanted a more effective method and started another method within two months of discontinuation. The data show that more than one-third (38 percent) of family planning users in Moldova discontinue using a contraceptive method within 12 months of starting its use. Seven percent of users stop using as a result of method failure (i.e., unintended pregnancy), while 4 percent discontinue because of a desire to become pregnant, and 18 percent switch to another method. Discontinuation rates are highest for users of lactational amenorrhea method (91 percent), presumably because it is only usable immediately after giving birth and its effectiveness declines sharply after six months. Discontinuation rates are also high for pill users—half of whom stop using within 12 months after starting—and for users of condoms (39 percent), withdrawal (37 percent), and periodic abstinence (35 percent). On the other hand, very few IUD users (7 percent) discontinue using their method within a year. For all methods, the most common reason for discontinuation was to switch to another method. Table 5.11 also presents reasons for discontinuation, but from a different perspective. All of the almost 4000 contraceptive discontinuations occurring in the five years preceding the survey, regardless of duration of use, are distributed by the main reason for discontinuation, according to method. Method failure (became pregnant while using) is the most prominent reason for discontinuation (19 percent), followed closely by wanting a more effective method (18 percent) and the desire to become pregnant (16 percent). Periodic abstinence (rhythm method) and withdrawal appear to be relatively ineffective, given that about one-third of discontinuations of these two methods are due to failure of the method, causing unintended pregnancies. The LAM method and periodic abstinence contribute disproportionately to discontinuation because of wanting a more effective method, while discontinuations of IUD use are heavily concentrated in the health concerns category. Family Planning | 71 Table 5.11 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason for discontinuation, according to specific method, Moldova 2005 Reason Pill IUD Condom Foam/ jelly LAM Periodic abstinence With- drawal All methods Became pregnant while using 12.3 6.5 15.1 15.9 4.9 32.2 34.5 19.0 Wanted to become pregnant 21.4 15.9 20.5 19.2 3.2 14.6 15.6 15.5 Husband disapproved 0.8 0.2 3.8 0.6 0.3 0.8 2.4 1.6 Side effects 13.5 7.7 0.3 2.4 0.2 0.0 0.3 3.1 Health concerns 12.5 42.7 2.0 10.2 1.7 1.8 2.3 11.4 Access/availability 0.9 0.0 0.7 0.0 0.3 0.0 0.1 0.3 Wanted a more effective method 9.1 3.2 15.9 17.1 43.0 23.0 19.3 17.6 Inconvenient to use 4.6 1.6 8.3 2.9 0.8 2.9 2.2 3.2 Infrequent sex/husband away 8.5 6.2 15.4 7.0 3.1 13.1 9.4 9.0 Cost too much 2.9 0.0 3.9 12.4 0.3 0.0 0.0 1.3 Fatalistic 0.2 0.0 0.0 0.0 1.7 0.0 0.1 0.3 Difficult to get pregnant/ menopausal 1.1 3.8 0.4 0.0 0.0 2.1 3.2 2.1 Marital dissolution/separation 0.1 0.5 1.5 1.1 0.0 0.0 0.8 0.7 Other 2.4 6.3 0.6 2.9 3.2 0.9 0.7 2.3 Don't know 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 Missing 9.5 5.3 11.4 8.4 37.6 8.6 9.2 12.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of discontinuations 397 785 683 92 515 180 1,283 3,981 Note: Total includes 47 discontinuations of other methods. LAM = Lactational amenorrhea method 5.12 FUTURE USE OF CONTRACEPTION An important indicator of the changing demand for family planning is the extent to which non- users of contraception plan to use family planning in the future. Women who were not currently using a method of contraception were asked about their intention to use family planning in the future. The results are presented in Table 5.12. Less than one-third (32 percent) of currently married nonusers say that they intend to use family planning in the future, 55 percent do not intend to use, and 11 percent are unsure. Surprisingly, the proportion of those intending to use generally decreases as the number of living children increases and the proportion who say they do not intend to use is highest among those with four or more children. This pattern is contrary to expectations and is mainly due to the fact that nonusers with more children are also more likely to be older and infertile (see next section). 72 | Family Planning Table 5.12 Future use of contraception Percent distribution of currently married women who are not using a contraceptive method by intention to use in the future, according to number of living children, Moldova 2005 Number of living children1 Intention 0 1 2 3 4+ Total Intends to use 33.2 42.4 29.6 20.7 14.8 32.2 Unsure 18.4 12.9 7.0 11.5 10.1 11.4 Does not intend to use 48.0 43.9 61.7 67.6 75.0 55.4 Missing 0.4 0.8 1.7 0.3 0.0 1.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 264 492 547 189 99 1,591 1 Includes current pregnancy 5.13 REASONS FOR NOT INTENDING TO USE Table 5.13 presents the main reasons for not using contraception as reported by currently married nonusers who do not intend to use a contraceptive method in future. Fertility-related reasons (72 percent), especially being sub- fecund/infecund (infertile) or menopausal, are by far the most common reasons for not intending to use contra- ception, followed by method-related reasons (15 percent). Only 4 percent of nonusers said they do not intend to use because they are opposed to using family planning. The most common single reasons for not intending to use are subfecund/infecund (35 percent), menopause/hysterecto- my (21 percent), and health concerns (10 percent). Among women under age 30, the most frequently cited reasons for not intending to use contraception are a desire to have as many children as possible (30 percent), followed by subfecundity/infecundity (27 percent). The most important reasons among nonusers 30 years and above are subfecundity and infecundity (36 percent) and menopause (24 percent). Table 5.13 Reason for not intending to use contraception Percent distribution of currently married women who are not using a contraceptive method and who do not intend to use in the future by main reason for not intending to use, according to age, Moldova 2005 Age Reason 15-29 30-49 Total Fertility-related reasons 57.8 73.3 71.5 Infrequent sex/no sex 1.2 9.4 8.4 Menopausal/hysterectomy 0.0 23.8 21.1 Subfecund/infecund 26.5 35.6 34.6 Wants as many children as possible 30.1 4.5 7.4 Opposition to use 11.3 3.3 4.2 Respondent opposed 5.4 1.8 2.2 Husband/partner opposed 1.4 0.4 0.5 Religious prohibition 4.4 1.1 1.5 Method-related reasons 18.2 14.1 14.6 Health concerns 8.1 9.9 9.7 Fear of side effects 7.4 1.6 2.3 Costs too much 0.0 0.5 0.4 Inconvenient to use 0.0 0.3 0.3 Interferes with body's normal processes 2.7 1.8 1.9 Other 1.2 7.3 6.6 Don’t know 11.5 2.0 3.1 Total 100.0 100.0 100.0 Number of women 101 781 882 Family Planning | 73 5.14 PREFERRED METHOD FOR FUTURE USE Demand for specific methods can be assessed by asking nonusers which method they intend to use in the future. Table 5.14 presents information on method pref- erences for married women who are not using contraception but say they intend to use in the future. The largest percentage of prospective users report the IUD as their preferred method (45 percent), with 15 percent citing the pill, and 12 percent favoring withdrawal. Method preference among women under age 30 and those over 30 years is similar, except that older women are more likely than younger women to prefer withdrawal and condoms, while younger women are more likely to be unsure of the method they prefer to use. 5.15 EXPOSURE TO FAMILY PLANNING MESSAGES Information on the level of public exposure to a particular type of media allows policymakers to use the most effective media for various target groups in the population. To assess the effectiveness of such media on the dissemi- nation of family planning information, the 2005 MDHS asked all female and male respondents whether they had heard about family planning on the radio or television, read about it in a newspaper or magazine or in a pamphlet or brochure, or heard about it at a community event in the past few months. Table 5.15.1 shows that almost half of women say they have seen a family planning message on the television, while about one-third say they heard about family planning on the radio or read about it in a newspaper or magazine in the past few months. Only about one in four women said they heard about family planning in a pamphlet/brochure or at a community event. A relatively high proportion—almost four in ten women—were not exposed to family planning messages in any of these media. Men are far less likely than women to say they have been exposed to family planning information (Table 5.15.2). Less than one-third of men heard about family planning on the television, while less than one-quarter were exposed to information through the radio, newspaper or magazines, and only about 10 percent through pamphlets/brochures or community events. Almost two-thirds of men said they had not heard anything about family planning through these five sources in the past few months. Generally, older respondents and in some cases the youngest respondents are less likely to have heard or seen a family planning message than those in the middle age groups. Exposure to family planning information is somewhat higher among urban than rural respondents and among those in Chisinau than in other regions. It also rises with the level of education and with the wealth index. In the 2005 MDHS, women who were not using any family planning method were asked whether they had visited a health facility in the previous 12 months for care for themselves or their children. If so, they were then asked whether any staff member at the health facility spoke to them about family planning methods. The purpose of the questions was to assess the extent of “missed opportunities” to disseminate information about contraception. The results show that the vast majority (89 percent) of non-users either did not visit a health facility or if so, did not discuss family planning (data not shown). Table 5.14 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, Moldova 2005 Age Method 15-29 30-49 Total Female sterilization 2.3 0.6 1.7 Pill 14.4 15.6 14.8 IUD 47.8 40.5 45.3 Condom 6.9 11.0 8.3 Foam/jelly 0.4 3.9 1.6 Periodic abstinence 0.7 1.4 1.0 Withdrawal 9.9 16.5 12.1 Injectables/implants/ diaphragm/other 2.1 1.5 1.9 Unsure 15.5 9.0 13.3 Total 100.0 100.0 100.0 Number of women 338 173 512 74 | Family Planning Table 5.15.1 Exposure to family planning messages : women Percentage of women who heard or saw a family planning message on the radio or television, or in a newspaper/magazine or in a pamphlet/brochure or at a community even in the past few months, according to background characteristics, Moldova 2005 Background characteristic Radio Television Newspaper/ magazine Pamphlets/ brochures Community events None of these five media sources Number of women Current age 15-19 29.5 39.0 32.7 24.3 28.0 41.7 1,417 20-24 36.7 51.2 36.2 29.4 30.1 33.5 1,124 25-29 36.7 53.0 33.3 27.4 28.4 32.7 964 30-34 42.6 56.2 40.5 32.1 32.7 29.7 924 35-39 41.7 54.2 36.3 25.7 28.8 35.1 855 40-44 35.9 49.4 33.8 24.7 28.9 37.4 1,007 45-49 30.4 42.0 28.8 22.7 24.9 48.2 1,149 Residence Urban 36.1 55.4 39.2 31.5 28.8 31.6 3,194 Rural 35.1 43.1 30.5 22.6 28.6 41.9 4,246 Region North 33.9 45.6 31.0 24.4 26.5 40.2 2,207 Center 37.5 44.4 32.6 25.2 28.7 39.9 2,033 South 30.0 45.7 33.5 25.9 27.6 42.5 1,402 Chisinau 39.7 58.5 40.6 30.6 32.1 27.5 1,798 Education No education/primary 21.7 28.2 16.7 16.0 13.0 68.3 49 Secondary 29.8 39.8 25.9 19.7 24.7 45.6 4,534 Secondary special 44.6 60.6 45.2 35.0 34.6 26.6 1,327 Higher 45.2 63.9 49.9 39.2 35.8 21.7 1,530 Wealth quintile Lowest 26.0 30.3 21.2 14.7 24.6 53.3 1,243 Second 32.0 37.4 25.2 21.0 23.1 48.0 1,234 Middle 37.6 49.5 35.1 26.3 29.8 37.9 1,511 Fourth 39.0 55.3 39.9 30.5 30.7 30.1 1,672 Highest 39.7 61.3 43.6 34.5 32.6 25.7 1,780 Total 35.5 48.4 34.2 26.4 28.7 37.5 7,440 Family Planning | 75 Table 5.15.2 Exposure to family planning messages: men Percentage of men who heard or saw a family planning message on the radio or television, or in a newspaper/magazine or in a pamphlet/brochure or at a community event in the past few months, according to background characteristics, Moldova 2005 Background characteristic Radio Television Newspaper/ magazine Pamphlets/ brochures Community events None of these five media sources Number of men Current age 15-19 18.4 23.8 12.7 10.1 14.5 63.2 411 20-24 26.2 36.9 20.6 14.6 19.6 50.8 275 25-29 24.6 36.4 20.8 11.6 14.4 53.6 234 30-34 27.9 34.9 20.0 16.4 15.2 55.5 224 35-39 27.6 35.0 23.5 12.8 14.3 55.6 248 40-44 19.0 30.1 17.0 7.5 9.0 62.8 247 45-49 22.2 27.2 17.5 8.1 6.4 67.5 349 50-54 22.5 24.8 16.9 9.3 9.1 71.0 296 55-59 21.5 25.7 17.1 6.4 5.2 69.2 224 Residence Urban 26.6 36.3 23.2 15.8 15.0 53.8 1,055 Rural 20.3 25.3 14.3 6.9 9.8 67.1 1,453 Region North 19.5 25.8 14.3 8.7 10.7 66.9 756 Center 23.6 29.6 16.1 9.9 10.6 62.2 702 South 21.9 28.4 18.8 8.2 10.8 63.9 496 Chisinau 27.6 37.1 25.0 16.1 16.3 51.2 554 Education No education/primary 3.7 3.7 0.0 0.0 0.0 96.3 16 Secondary 16.7 23.4 11.7 6.0 8.3 69.3 1,788 Secondary special 28.4 36.1 21.2 14.5 14.6 53.4 302 Higher 47.3 55.0 44.6 28.4 26.7 31.9 403 Wealth quintile Lowest 14.4 16.9 8.4 3.3 6.0 76.0 450 Second 17.9 21.8 10.7 6.4 6.5 72.6 470 Middle 24.1 32.3 16.6 7.1 12.8 59.9 464 Fourth 27.0 34.1 22.3 14.1 14.0 56.7 561 Highest 29.0 41.0 28.8 19.4 18.6 46.8 563 Total 22.9 29.9 18.0 10.6 12.0 61.5 2,508 5.16 ATTITUDES OF RESPONDENTS TOWARDS FAMILY PLANNING Use of effective contraceptive methods is facilitated when couples have a positive attitude towards family planning and when men share the responsibility for contraception. In the MDHS, men were asked whether they agreed or disagreed with three statements about family planning use: 1) contraception is women’s business and a man should not have to worry about it; 2) women who use contraception may become promiscuous; and 3) a woman is the one who gets pregnant so she should be the one to get sterilized. Results are shown in Table 5.16. The data show that only 15 percent of men believe that contraception is women’s business only, while over one-quarter believe that women who use family planning may become promiscuous. Only 13 percent of men believe that women should be the ones to get sterilized, since they are the ones who get pregnant. Differences by background characteristics are not large. 76 | Family Planning Table 5.16 Men's attitudes toward contraception Percentage of men who agree with statements about contraceptive use, by background characteristics, Moldova 2005 Background characteristic Woman's business Woman may become promiscuous Woman is the one who becomes pregnant Number of men Current age 15-19 14.0 26.0 11.8 411 20-24 14.3 33.9 8.5 275 25-29 12.3 23.3 10.1 234 30-34 15.9 26.7 12.4 224 35-39 15.0 23.5 14.7 248 40-44 16.6 30.7 15.6 247 45-49 17.4 27.6 13.3 349 50-54 11.1 28.8 18.1 296 55-59 19.7 24.6 13.5 224 Marital status Never married 13.3 28.4 10.1 730 Married or living together 15.7 26.5 14.3 1,657 Divorced/separated/ widowed 15.9 32.7 14.9 120 Residence Urban 17.7 30.8 11.2 1,055 Rural 13.1 24.8 14.5 1,453 Region North 14.7 22.8 12.9 756 Center 11.4 23.7 12.4 702 South 18.5 31.1 13.2 496 Chisinau 17.0 34.7 14.1 554 Education No education/primary * * * 16 Secondary 15.6 25.0 14.3 1,788 Secondary special 13.8 29.8 14.6 302 Higher 13.3 36.1 6.6 403 Wealth quintile Lowest 11.7 18.4 16.2 450 Second 21.3 27.7 15.0 470 Middle 12.1 24.7 11.5 464 Fourth 14.9 31.4 13.2 561 Highest 15.1 32.3 10.3 563 Total 15.0 27.3 13.1 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Abortion | 77 ABORTION 6 Reliance on induced abortion was the primary means of fertility control throughout the former Soviet Union, including the former Soviet Republic of Moldova. In the decade after Moldova’s inde- pendence in 1991, abortion rates began to decrease as the practice of modern contraception became more widespread. This decreasing trend, however, has stagnated since 2000 mainly because older women still rely on abortion to limit their child bearing. Thus, abortion still remains an important determinant in Moldova’s reproductive trends. Like other countries in East and Central Europe and the former Soviet Union, Moldova’s abortion laws are among the most liberal in the world. They allow women to obtain an abortion upon request up to the 12th week of pregnancy, and up to 22 weeks for socioeconomic and medical reasons (Center for Reproductive Rights, 2000). Because induced abortion can adversely affect a woman’s health, reduce her chances for further childbearing, and contribute to maternal and perinatal mortality, the Moldova Ministry of Health, along with assistance from UNFPA and other partners, aims to reduce the number of abortions by improving reproductive health services and family life education (UNFPA, 2006). Information about induced abortion was collected through a detailed reproductive history section in the Women’s Questionnaire. In collecting the histories, each woman was first asked about the total number of pregnancies that had ended in live births, induced abortions, miscarriages and stillbirths. After obtaining these aggregate data, an event-by-event pregnancy history was recorded. For each pregnancy, the duration, the month and year of termination, and the outcome of the pregnancy was recorded.1 6.1 PREGNANCY OUTCOMES Table 6.1 shows the percent distribution of the outcome of all pregnancies that ended during the three-year period preceding the survey (approximately mid-2002 to mid-2005). In Moldova, slightly more than half of pregnancies end in a live birth (55 percent). The majority of pregnancy losses are due to induced abortions (34 percent of pregnancies), followed by miscarriages (10 percent) and stillbirths (less than 1 percent). 1 The pregnancy history was structured to ensure as complete reporting of abortions as possible, especially for the period immediately before the survey. Data were collected in reverse chronological order (i.e., information was first collected about the most recent pregnancy, then about the next-to-last, and so on). This procedure was designed to yield a more complete reporting of events for the years immediately before the survey than collecting information in chronological order. At the end of the pregnancy history, interviewers were required to check the consistency between the aggregate data collected and the number of specific events reported in the pregnancy history. 78 | Abortion Table 6.1 Pregnancy outcome by background characteristics Percent distribution of pregnancies by pregnancy outcome, ending in the three-year period preceding the survey, according to background characteristics, Moldova 2005 Pregnancy outcome Background characteristic Live birth Induced abortion Miscarriage Stillbirth Total Number of pregnancies Residence Urban 50.5 39.0 10.2 0.3 100.0 801 Rural 58.2 30.5 10.5 0.8 100.0 1,043 Region North 55.4 33.4 11.1 0.1 100.0 530 Center 61.4 28.3 9.2 1.1 100.0 485 South 56.7 29.0 13.2 1.1 100.0 354 Chisinau 46.0 45.1 8.7 0.3 100.0 474 Education No education/primary (45.3) (43.3) (11.4) (0.0) 100.0 29 Secondary 57.0 32.4 9.7 0.9 100.0 1,176 Secondary special 48.5 40.4 11.1 0.0 100.0 275 Higher 53.4 34.5 11.9 0.2 100.0 365 Age (at pregnancy outcome) 15-19 67.3 16.9 15.8 0.0 100.0 200 20-24 62.9 26.5 9.6 1.1 100.0 648 25-34 52.5 38.3 9.0 0.3 100.0 793 35-44 26.6 59.8 12.7 0.9 100.0 201 45-49 * * * * 100.0 4 Pregnancy order First 77.4 9.5 11.9 1.2 100.0 492 Second 61.6 27.9 10.6 0.0 100.0 454 Third 46.0 42.9 10.5 0.5 100.0 316 Fourth 41.4 46.7 11.3 0.6 100.0 237 Fifth or higher 31.1 61.0 7.3 0.5 100.0 346 Wealth quintile Lowest 66.6 21.1 10.5 1.8 100.0 299 Second 56.4 31.9 11.4 0.4 100.0 340 Middle 57.1 30.0 12.5 0.5 100.0 375 Fourth 50.8 38.7 10.1 0.3 100.0 383 Highest 47.3 44.3 8.1 0.3 100.0 447 Total 54.8 34.2 10.4 0.6 100.0 1,845 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. Pregnancy outcomes for the three-year period prior to the 2005 MDHS show no improvement compared to the results of the 1997 Moldova Reproductive Health Survey (1997 MRHS) (corresponding to the five-year period from mid-1992 to mid-1997) (Serbanescu et al., 1998). The percentage of pregnancies ending in live births in the 1997 MRHS is 53 percent versus 55 percent in the 2005 MDHS, and the percentage of pregnancies ending in abortion is 37 percent versus 34 percent, respectively.2 Results from both surveys show about 10 percent of pregnancies ended in miscarriages (including ectopic pregnancies), and less than 1 percent ended in stillbirths. Likewise, patterns related to certain background characteristics have not changed: a greater percentage of pregnancies are still likely to end in abortions in urban versus rural areas, in Chisinau versus other regions, among women in older age groups, with more births, and of higher socioeconomic status. 2 Caution should be exercised in interpreting these levels. Although they imply a decline in induced abortion, the 1997 MRHS included women from Transnistria in the sample, whereas the 2005 MDHS did not. In the 1997 MRHS, the Transnistria region (and Chisinau) had the highest percentage of women who had an abortion in the three years prior to the survey. Excluding Transnistria from the 1997 MRHS sample would thus result in a lower overall percentage of women who had an abortion, and probably close the gap with results of the 2005 MDHS. Thus, according to this indicator, the abortion situation in Moldova looks about the same since the mid-1990s. Abortion | 79 6.2 LIFETIME EXPERIENCE WITH INDUCED ABORTION Table 6.2 shows women’s lifetime experience with abortion. The statistics on the proportion of women are based on all women age 15-49 irrespective of their exposure to the risk of pregnancy. Overall, more than a third of women (37 percent) of reproductive age have had at least one abortion. As expected, the percentage that have had an abortion increases rapidly with age which is also associated with increased exposure to pregnancy, since some women under age 20 have not even had sexual intercourse. Sixty-one percent of women age 35 and over have had at least one abortion. Similarly, the percentage of women with an abortion increases for up to three living children, and then it drops for women who apparently desire to have a larger family. There are no important differentials by residence or geographic region, indicating that, at least historically, abortion is a common means for women to regulate births regardless of where they live. Women of lowest socioeconomic status are less likely to report having an abortion (31 percent) than women in any other socioeconomic strata (36 to 41 percent). Table 6.2 Lifetime experience with induced abortion Percentage of women who have had at least one induced abortion, and among these women, percent distribution by number of abortions and the mean number of abortions, according to background characteristics, Moldova 2005 Distribution of women who have had an induced abortion, by number of abortions Background characteristic Percentage with an induced abortion Number of women 1 2-3 4-5 6+ Total Mean number of abortions Number of women with abortions Current age <20 1.1 1,417 * * * * 100.0 * 15 20-24 14.3 1,124 78.4 21.4 0.3 0.0 100.0 1.3 160 25-34 40.9 1,888 52.0 38.3 8.4 1.3 100.0 1.8 771 35+ 61.0 3,011 33.1 50.8 11.7 4.4 100.0 2.4 1,836 Number of living children 0 4.4 2,456 68.1 28.9 3.0 0.0 100.0 1.5 107 1 41.3 1,645 52.4 37.9 7.9 1.7 100.0 1.9 679 2-3 61.0 3,013 36.3 48.7 11.2 3.8 100.0 2.3 1,839 4+ 48.3 326 32.8 50.5 10.7 6.0 100.0 2.4 157 Residence Urban 39.0 3,194 38.4 46.8 11.5 3.4 100.0 2.2 1,245 Rural 36.2 4,246 43.6 44.3 8.9 3.2 100.0 2.1 1,538 Region North 39.1 2,207 42.2 44.4 10.9 2.5 100.0 2.1 864 Center 34.4 2,033 42.6 45.4 8.2 3.9 100.0 2.1 700 South 36.5 1,402 43.4 46.0 7.9 2.7 100.0 2.0 513 Chisinau 39.3 1,798 37.2 46.3 12.5 3.9 100.0 2.3 707 Education No education/primary (44.0) 49 * * * * 100.0 * 21 Secondary 34.4 4,534 42.1 44.0 10.5 3.5 100.0 2.2 1,559 Secondary special 51.5 1,327 37.7 49.4 8.8 4.1 100.0 2.2 684 Higher 33.9 1,530 43.7 44.6 10.5 1.2 100.0 2.0 518 Marital status Never married 1.7 1,862 (65.0) (30.2) (4.9) (0.0) 100.0 (1.6) 32 Married or living together 48.8 4,937 41.1 46.0 9.8 3.1 100.0 2.1 2,411 Divorced/separated/ widowed 52.9 641 40.3 42.7 12.1 4.9 100.0 2.3 339 Wealth quintile Lowest 30.8 1,243 42.9 47.6 6.8 2.8 100.0 2.0 383 Second 37.5 1,234 43.3 43.6 8.4 4.7 100.0 2.1 463 Middle 36.1 1,511 44.1 43.8 10.1 2.0 100.0 2.0 545 Fourth 39.7 1,672 40.8 46.0 10.8 2.4 100.0 2.1 664 Highest 40.9 1,780 37.4 46.2 12.1 4.3 100.0 2.3 727 Total 37.4 7,440 41.3 45.4 10.1 3.3 100.0 2.2 2,782 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. 80 | Abortion Table 6.2 also presents information on repeated use of induced abortion. Among women who have ever had an abortion, over half have had more than one (59 percent). Forty-five percent of women who have had an abortion reported having 2 to 3 abortions, and 13 percent had 4 or more. Patterns of repeat abortion are similar to patterns of experiencing any abortion. That is, where percentages of women who have ever had an abortion are relatively high, the percentages of women with more than one abortion also are likely to be higher. For example, women age 35 and older and women with four or more children are the most likely to have had an abortion, and also the least likely to have had only one abortion. The mean number of abortions among women who have had at least one abortion is 2.2. The 2005 MDHS data do not differ significantly from those from the 1997 MRHS in terms of the percentage of women who reported ever having had an abortion (37 percent and 39 percent, respectively). Among women who have ever had an abortion, however, results from the MDHS imply that women are slightly more likely to have repeat abortions compared with results from the 1997 MRHS: in the 1997 MRHS, 53 percent of these women had two or more abortions; in the 2005 MDHS, 59 percent of these women had two or more abortions. 6.3 RATES OF INDUCED ABORTION Table 6.3 shows rates of induced abortion for the three-year period preceding the survey (approximately mid- 2002 to mid-2005). Age-specific abortion rates (ASARs), which are shown per 1,000 women, express the number of abortions among women of a given age, divided by the total number of women-years in that age group. The total abortion rate (TAR), which is expressed per woman, is a summary measure of the ASARs. The TAR is interpreted as the number of abortions a woman would have in her lifetime if she experienced the currently observed age-specific abortion rates throughout her childbearing years. As shown in Table 6.3, at the national level, the ASARs for induced abortion increase rapidly after age 19, remain high from ages 20 to 35, and then drop sharply in older age groups. An unusual trend is noted when ASARs are examined by residence. For women in rural areas, the ASARs peak early, at ages 20 to 24, and are lower thereafter. For women in urban areas, they peak later, at ages 25 to 29, and remain significantly more elevated than those in rural areas for women in their 30s. Comparing national level abortion rates with the fertility rates, the pattern is such that fertility rates are significantly higher than abortion rates for women under age 30, then the rates crossover showing that older women are more likely to have an abortion than to bear a child (Figure 6.1). Table 6.3 Induced abortion rates Age-specific abortion rates (per 1,000 women) and total abortion rates for all women, in the three-year period preceding the survey, by selected background characteristics, Moldova 2005 Age-specific abortion rates Age Urban Rural Total 15-19 8 9 8 20-24 50 62 56 25-29 77 46 59 30-34 60 49 54 35-39 45 29 35 40-44 13 5 9 45-49 1 1 1 Rates TAR 15-491 1.3 1.0 1.1 TAR 15-441 1.3 1.0 1.1 GAR 2 39 31 35 1 TAR, the total abortion rate, is expressed per woman 2 GAR, the general abortion rate (abortions divided by number of women (15-44), is expressed per 1,000 women Abortion | 81 The lifetime total abortion rate for the three-year period prior to the survey (from mid-2002 to mid-2005) is 1.1 abortions per woman. The TAR is slightly higher in urban areas than rural areas (1.3 and 1.0, respectively). The TAR for only married women during the same time period is 1.3 abortions per married woman which is slightly higher than for all women (data not shown). This supports the finding that in the former Soviet republics, abortion was primarily used by married women to control fertility after one or two births, whereas in the United States and other Western countries abortions are associated more with first pregnancies and unmarried women (Westoff, 2005). Compared to other countries, the TAR for the most recent period in Moldova is lower than in neighboring Romania (2.2 in 1997-1999) and Ukraine (1.6 in 1997-1999), as well as other parts of the former Soviet Union including Russia (2.3 in 1996-1998), Armenia (2.6 in 1998-2000), Azerbaijan (3.2 in 1998-2000) and Georgia (3.7 in 1997- 1999). The TAR in Moldova is closer to those in Central Asia including Kazakhstan (1.4 in 1997-1999), Kyrgyz Republic (1.5 in 1995-1997), Turkmenistan Republic (0.8 in 1998-2000) and Uzbekistan (0.6 in 1994-1996) (CDC and ORC Macro, 2003). It should be noted that, in general, abortion rates have been declining all over the former Soviet Union as modern contraceptives are replacing abortion as a means of controlling childbearing (Westoff, 2005). This trend towards lower TARs should be taken into account when comparing this measure across the region. Table 6.4 Induced abortion by background characteristics Total induced abortion rate for the three-year period preceding the survey, by selected background characteristics, Moldova 2005 Background characteristic TAR1 Mean number of abortions among women age 40-49 Residence Urban 1.3 1.6 Rural 1.0 1.4 Region North 1.1 1.5 Center 1.0 1.4 South 1.0 1.4 Chisinau 1.4 1.7 Education No education/primary * * Secondary 1.2 1.4 Secondary special 1.0 1.7 Higher 1.0 1.5 Wealth quintile Lowest 0.7 1.1 Second 1.2 1.4 Middle 1.0 1.4 Fourth 1.1 1.6 Highest 1.4 1.8 Total 1.1 1.5 1 Women age 5-49 Figure 6.1 Age-Specific Fertility Rates (ASFR) and Age-Specific Abortion Rates (ASAR) � � � � � � �� � � � � � � 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group 0 20 40 60 80 100 120 140 ASAR ASFR� � MDHS 2005 Rates per 1,000 women 82 | Abortion Total abortion rates by background characteristics are shown in Table 6.4 and Figure 6.2. TARs do not vary drastically by residence, and education. The lowest TAR of 0.7 is seen for women in the poorest wealth quintile, while the highest TAR (1.4) is seen for women in the highest quintile and also for women in Chisinau. The women in the highest wealth quintile and the women in Chisinau are likely to be most of the same women because the wealthiest households are concentrated in urban areas, of which Chisinau is the largest (see Table 2.7). Higher rates of abortion among these women are probably due to the fact that because abortions are no longer provided by the state, women with adequate resources are more likely to have access to abortion and to be able to afford the procedure. This raises questions as to the means used to educate women about the potentially negative effects of abortion. If educational messages are being disseminated to the public, they may be reaching women of certain social strata but not across all social strata. These questions merit further research. 6.4 TRENDS IN INDUCED ABORTION Using the MDHS data, induced abortion trends can be assessed in several ways. One approach is to compare the total abortion rate at the time of the survey with the mean number of abortions to women who are completing their fertile years (age 40-49). On average, women who have come to the end of their reproductive years have had an average of 1.5 abortions (Table 6.4). Comparing this to the TAR of 1.1, a measure of the current level of induced abortion across all age groups, the level of induced abortion appears to have decreased over the long term. The decrease in abortion is consistent across all background characteristics. Another more sensitive approach for detecting abortion trends is to examine TARs and ASARs over a series of short, consecutive time intervals. Table 6.5 presents these abortion rates for four distinct three-year time periods prior to the survey. These data show no decline in the TAR for women age 15-44 since the mid-1990s. The reason for this stagnation is that ASARs have been steadily decreasing over time for younger age groups, but in the most recent time period, from 2003 to 2005, the ASARs have increased among women in their 30s (Figure 6.3). (Note that because women age 50 and above were not interviewed in the survey, the rates are truncated successively as the number of years prior to the survey 1.1 1.3 1.0 1.1 1.0 1.0 1.4 0.7 1.2 1.0 1.1 1.4 MOLDOVA RESIDENCE Urban Rural REGION North Center South Chisinau WEALTH QUINTILE Lowest Second Middle Fourth Highest 0.0 0.5 1.0 1.5 Abortions per woman Figure 6.2 Total Abortion Rate by Background Characteristics MDHS 2005 Abortion | 83 increases.) The general abortion rate (GAR), the number of abortions annually per 1,000 women age 15-44, likewise shows a modest decrease since 1997-1999, but no improvement since 2002. An indicator frequently associated with abortion is maternal mortality. The 2005 MDHS did not estimate maternal mortality because the sample size is not large enough to obtain a precise measure. However, the official estimate for 2002 was 28.0 maternal deaths per 100,000 live births, with abor- tion registered as the second major cause (first cause was indirect obstetrical risks and the third cause was direct obstetrical risks) (UNFPA, 2003). A reduction in abortion rates would reduce maternal mortality. Table 6.5 Abortion trends Age-specific abortion rates for three-year periods preceding the survey, Moldova 2005 Number of years preceding the survey Woman’s age at the time of the abortion 0-2 (2003- 2005) 3-5 (2000- 2002) 6-8 (1997- 1999) 9-11 (1994- 1996) 15-19 8 12 13 18 20-24 56 64 74 100 25-29 59 62 64 84 30-34 54 39 43 49 35-39 35 26 30 25 40-44 9 12 [14] [22] 45-49 [1] [3] - - Rates TAR 15-491 1.1 - - - TAR 15-441 1.1 1.1 1.2 - GAR2 35 34 41 - Note: the estimates in brackets are truncated. 1 TAR: Total abortion rate, expressed per woman 2 GAR: General abortion rate (abortions divided by number of women 15-44), expressed per 1,000 women Figure 6.3 Age-Specific Abortion Rates (ASAR) for Three-year Periods Prior to the 2005 MDHS � � � � � � � � � � � � � � � � � � � � � � 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group 0 20 40 60 80 100 120 140 2003-2005 2000-2002 1997-1999 1994-1996 � � � � MDHS 2005 Rates per 1,000 women 84 | Abortion For each pregnancy that ended in the three years prior to the survey, respondents were asked whether they were using a method of contraception at the time they became pregnant, and if so, which method. Table 6.6 shows the use of contraception at the time of conception. The majority of respondents who had an induced abortion were using a method of contraception at the time they became pregnant (60 percent). Thus, these unplanned pregnancies were the result of contraceptive failure. About thirty-nine percent of all induced abortions occurred after failure of a traditional contraceptive method, especially the withdrawal method. Twenty-one percent of induced abortions occurred after failure of a modern method, most commonly the condom and IUD. Forty percent of women were using no contraceptive and decided to terminate their pregnancy. Table 6.6 Use of contraception prior to pregnancy Percent distribution of pregnancies during the three years preceding the survey by contraceptive method used (if any) at the time of conception, according to pregnancy outcome, Moldova 2005 Pregnancy outcome Contraceptive method Live birth Induced abortion Miscarriage All pregnancies No contraception 77.6 39.6 70.4 63.9 Any method 22.4 60.4 29.6 36.1 Modern method 6.7 21.4 12.8 12.4 Pill 1.3 4.5 1.9 2.5 IUD 1.5 6.3 3.1 3.3 Condom 3.5 8.5 6.5 5.5 Female sterilization 0.0 0.2 0.0 0.1 Foam/jelly 0.4 1.9 1.2 1.0 Traditional method 15.7 39.0 16.8 23.8 Lactational amenorrhea 0.3 2.6 1.1 1.2 Rhythm 1.9 4.8 2.0 2.9 Withdrawal 13.2 30.8 13.7 19.2 Other 0.3 0.9 0.0 0.5 Total 100.0 100.0 100.0 100.0 Number of pregnancies 1,011 631 192 1,845 Note: Total includes 11 stillbirths (too few to show by separate contra- ceptive methods). Other Proximate Determinants of Fertility | 85 OTHER PROXIMATE DETERMINANTS OF FERTILITY 7 7.1 INTRODUCTION Research on fertility demonstrates that fertility levels in most populations can be explained by five key proximate determinants that define the risk of becoming pregnant. These are marriage, sexual intercourse, postpartum amenorrhea and abstinence from sexual relations, onset of menopause, and contraceptive use. This chapter addresses all of these determinants except contraception (see Chapter 5). In some countries like Moldova, induced abortion is another factor that affects fertility (see Chapter 6). Marriage is a principal indicator of women’s exposure to risk of pregnancy. Early age at marriage in a population is usually associated with a longer period of exposure to the risk of pregnancy and higher fertility levels. Sometimes, the early initiation of childbearing associated with early marriage may also adversely affect women’s and children’s health. The durations of postpartum amenorrhea and postpartum abstinence, both of which affect the length of time a woman is insusceptible to pregnancy, help determine the interval between births, as does the frequency of intercourse. The onset of menopause marks the end of a woman’s reproductive life cycle. Taken together, these factors in large measure determine the length and pace of reproduction, hence they are important in understanding fertility levels and differences. 7.2 MARITAL STATUS The distribution of women and men by marital status at the time of survey is presented in Table 7.1. In most of the rest of this report, the term “currently married” refers to those who are formally “married” as well as those who are “living together,” while those who are divorced, separated, or widowed are referred to as “formerly married.” The currently married and the formerly married combined gives the proportion ever married. One-quarter of women of childbearing age have never been married; 66 percent are either married or living together with a man; and the remaining 9 percent are either divorced, separated, or widowed. The low proportion (1 percent) of women in their 40s who have never been married indicates that marriage is still nearly universal in Moldova. Divorce and separation (7 percent) are not common in Moldova. Two percent of women age 15-49 are widowed. The proportion currently married or in a consensual union has declined very slightly from 69 percent of women in 1997 to 66 percent in 2005. A slightly higher proportion of men than women (29 percent) have never been married, while the proportion currently married is identical to that of women (66 percent). Only 5 percent of men are separated, divorced, or widowed. Although women enter into marriage earlier than men, by age 35-39, the proportions of women and men who have never been in a marital union have more or less converged. Women are also more likely than men to report living with a man, being separated, and being widowed. 86 | Other Proximate Determinants of Fertility Table 7.1 Current marital status Percent distribution of women and men by current marital status, according to age, Moldova 2005 Marital status Age Never married Married Living together Divorced Separated Widowed Total Number of women and men WOMEN 15-19 89.5 6.8 2.8 0.2 0.8 0.0 100.0 1,417 20-24 39.1 46.0 10.0 0.9 3.9 0.1 100.0 1,124 25-29 8.8 76.3 6.0 4.4 3.8 0.8 100.0 964 30-34 2.5 82.0 5.7 6.3 3.0 0.4 100.0 924 35-39 2.7 83.4 3.9 5.1 2.9 1.9 100.0 855 40-44 1.0 81.5 4.8 7.3 2.4 3.0 100.0 1,007 45-49 1.3 80.5 2.5 6.0 3.5 6.3 100.0 1,149 Total 25.0 61.4 5.0 4.0 2.8 1.8 100.0 7,440 MEN 15-19 98.4 0.7 0.5 0.0 0.4 0.0 100.0 411 20-24 76.1 19.4 3.8 0.0 0.6 0.0 100.0 275 25-29 25.4 67.6 3.4 2.7 0.9 0.0 100.0 234 30-34 10.6 77.0 6.1 4.3 2.0 0.0 100.0 224 35-39 3.7 87.6 4.0 4.1 0.6 0.0 100.0 248 40-44 2.8 84.3 4.5 5.3 1.9 1.2 100.0 247 45-49 1.8 88.6 3.4 4.4 0.4 1.4 100.0 349 50-54 2.7 87.3 2.5 5.0 1.3 1.1 100.0 296 55-59 1.1 86.0 4.7 3.3 0.0 4.8 100.0 224 Total 29.1 62.7 3.4 3.1 0.9 0.9 100.0 2,508 7.3 AGE AT FIRST MARRIAGE Marriage in most societies defines the onset of the socially acceptable time for childbearing. Women who marry early will have, on average, a longer period of exposure to pregnancy, often leading to a higher number of children ever born. Table 7.2 shows the percentage of women and men who have married by specific ages, according to current age group. Just over 40 percent of women enter marriage before their 20th birthday. Among women age 25-49, the median age at first marriage is 20.4 years. This corroborates the observations across the age cohorts in Table 7.2, which show the median age at marriage as more or less constant over time. The median age declines from 20.8 years among women age 45-49 to 20.3 among those age 25-29. The lower panel of Table 7.2 shows age at first marriage for men. Less than 10 percent of men marry before their 20th birthday, and less than one-third marry before age 22. The median age at marriage among men is 23.2 years, about 3 years higher than for women. As among women, the median age at first marriage for men is largely constant across the age cohorts. Other Proximate Determinants of Fertility | 87 Table 7.2 Age at first marriage Percentage of women and men who were first married by specified exact ages, and median age at first marriage, according to current age, Moldova 2005 Percentage of women who were first married by exact age: Current age 15 18 20 22 25 Percentage who were never married Number Median age at first marriage WOMEN 15-19 0.8 na na na na 89.5 1,417 a 20-24 0.5 18.9 39.6 na na 39.1 1,124 a 25-29 1.2 20.4 46.8 68.2 86.1 8.8 964 20.3 30-34 1.2 18.0 53.0 77.2 89.1 2.5 924 19.8 35-39 0.8 13.2 45.6 71.7 90.1 2.7 855 20.3 40-44 0.5 9.1 39.7 69.7 88.2 1.0 1,007 20.6 45-49 0.6 8.4 34.9 68.4 85.3 1.3 1,149 20.8 20-49 0.8 14.5 42.8 na na 9.9 6,023 a 25-49 0.8 13.5 43.5 70.9 87.6 3.2 4,899 20.4 MEN 15-19 0.0 na na na na 98.4 411 a 20-24 0.0 0.9 9.7 na na 76.1 275 a 25-29 0.0 3.0 12.5 29.9 60.7 25.4 234 24.0 30-34 0.0 3.1 13.5 37.2 65.0 10.6 224 23.0 35-39 0.0 2.7 5.4 29.9 72.1 3.7 248 23.0 40-44 0.0 1.5 6.8 36.4 70.2 2.8 247 23.0 45-49 0.0 1.9 7.9 29.5 73.8 1.8 349 23.0 50-54 0.0 1.6 4.8 30.2 74.1 2.7 296 23.4 55-59 0.0 1.6 9.4 27.3 74.0 1.1 224 23.2 20-59 0.0 2.0 8.6 na na 15.5 2,097 a 25-59 0.0 2.2 8.4 31.3 70.4 6.4 1,822 23.2 na = Not applicable a = Omitted because less than 50 percent of the women or men married for the first time before reaching the beginning of the age group Table 7.3 further examines the median age at first marriage for women age 25-49 and for men age 25-59 by background characteristics. Urban women tend to marry slightly later than their rural counterparts; the difference for men is almost imperceptible. Both women and men in Chisinau marry later than those in the other regions. The median age at first marriage increases with educational level for women and men; this also holds true for each age group of women. Age at marriage also generally increases as wealth increases; the relationship is stronger for women than for men. 88 | Other Proximate Determinants of Fertility Table 7.3 Median age at first marriage Median age at first marriage among women 25-49, and men age 25-59, by current age and background characteristics, Moldova 2005 Current age of women Background characteristic 25-29 30-34 35-39 40-44 45-49 Women age 25-49 Men age 25-59 Residence Urban 20.9 20.2 20.7 21.0 21.2 20.8 23.5 Rural 19.9 19.7 20.0 20.3 20.5 20.1 23.1 Region North 19.8 19.4 19.8 20.2 20.5 20.0 23.0 Center 19.8 20.0 20.7 20.6 20.8 20.5 23.2 South 20.5 19.8 19.9 20.5 20.6 20.3 23.3 Chisinau 21.3 20.4 20.8 21.5 21.5 21.1 23.8 Education No education/primary * * * * * * * Secondary 19.5 19.4 19.7 20.1 20.5 19.9 23.0 Secondary special 20.7 19.9 20.6 21.1 20.7 20.6 23.3 Higher 21.9 21.1 21.5 22.1 22.0 21.7 24.2 Wealth quintile Lowest 19.6 19.2 19.3 20.2 20.4 19.8 22.9 Second 19.7 19.7 20.0 20.3 20.3 20.0 23.2 Middle 20.4 20.0 20.6 20.7 20.6 20.5 23.0 Fourth 20.2 19.7 20.6 20.6 21.0 20.5 23.4 Highest 21.3 20.6 20.6 21.1 21.4 21.0 23.7 Total 20.3 19.8 20.3 20.6 20.8 20.4 23.2 Note: The medians for cohorts 15-19 and 20-24 could no be calculated because less than 50 percent of the respondents were married for the first time before reaching the lower age extreme of the age group. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 7.4 AGE AT FIRST SEXUAL INTERCOURSE Although age at marriage is often used as a proxy measure for the beginning of exposure to the risk of pregnancy, some women engage in sexual activity before marriage. The MDHS gathered information on the timing of the first sexual intercourse for both men and women. The percentage of women and men who had had sexual intercourse by exact ages is given in Table 7.4. Only a tiny fraction (less than 1 percent) of women report that they had sex before they were 15, while about half had their first sex by the time they turned 20. Older women are more likely to have had their first sexual encounter at a later age. This is further reflected in the median age at first sex, which is about 20.5 years for those in their 40s and about 19.5 for women under age 35. The data for the male respondents show an earlier age at first sex at most age groups, compared with female respondents. Almost one-third of men had sex before age 18, compared with only about 15 percent of women. The median age at first sex for men is 19 years, compared with 20 for women. As with women, age at first sex declines from older to younger cohorts. Other Proximate Determinants of Fertility | 89 Table 7.4 Age at first sexual intercourse Percentage of women and men who had first sexual intercourse by specified exact ages and median age at first intercourse, according to current age, Moldova 2005 Percentage who had first sexual intercourse by exact age: Current age 15 18 20 22 25 Percentage who never had sex Number Median age at first sex WOMEN 15-19 1.3 na na na na 78.1 1,417 a 20-24 0.8 22.7 55.1 na na 22.3 1,124 19.6 25-29 1.7 24.6 58.9 79.4 92.2 3.7 964 19.4 30-34 0.8 19.9 61.1 82.9 93.9 0.8 924 19.5 35-39 0.8 16.1 49.4 77.2 92.8 1.1 855 20.0 40-44 0.4 9.2 42.3 72.6 90.4 0.2 1,007 20.5 45-49 0.6 9.1 38.4 72.0 89.4 0.3 1,149 20.6 20-49 0.8 16.8 50.5 na na 5.1 6,023 20.0 25-49 0.8 15.4 49.4 76.5 91.6 1.2 4,899 20.0 MEN 15-19 9.0 na na na na 56.4 411 a 20-24 8.3 51.4 82.7 na na 7.0 275 17.9 25-29 9.0 52.4 79.9 92.7 95.3 2.0 234 17.8 30-34 2.7 38.4 67.9 82.8 92.4 0.3 224 18.5 35-39 4.4 32.4 64.8 84.4 94.6 0.5 248 18.7 40-44 2.2 24.5 57.9 82.0 91.2 1.0 247 19.1 45-49 2.2 23.4 47.9 74.4 89.4 0.0 349 20.1 50-54 3.3 17.9 43.9 70.9 85.0 0.0 296 20.4 55-59 0.7 13.7 39.3 68.1 85.3 0.3 224 20.5 20-59 4.1 31.3 59.9 na na 1.4 2,097 19.0 25-59 3.4 28.3 56.4 78.8 90.3 0.5 1,822 19.3 na = Not applicable a = Omitted because less than 50 percent of the respondents had intercourse for the first time before reaching the beginning of the age group Comparison of data from the 2005 MDHS with similar data from the 1997 MRHS shows little change in the percentage of young women who have never had sex. The percentage of women age 15-19 who have never had sex stayed steady at 79 percent in 1997 to 78 percent in 2005; the proportion of those age 20-24 who never had sex increased from 17 percent in 1997 to 22 percent in 2005. Table 7.5 shows the median age at first sex by background characteristics for women age 25-49 and men age 25-59 years. Women in the rural areas start sexual activity slightly earlier than their urban counterparts. With respect to education, women with higher education begin sexual activity about one year later than those with secondary education. Women from poor households tend to have intercourse for the first time somewhat earlier than those from wealthy households. 90 | Other Proximate Determinants of Fertility Table 7.5 Median age at first intercourse Median age at first sexual intercourse among women age 25-49, and men age 25-59, by current age and background characteristics, Moldova 2005 Current age of women Men ageBackground characteristic 25-29 30-34 35-39 40-44 45-49 Women age 25-49 25-59 Residence Urban 19.4 19.6 20.3 20.6 20.8 20.2 18.7 Rural 19.4 19.4 19.8 20.3 20.4 19.9 19.9 Region North 19.1 19.3 19.6 20.1 20.3 19.7 19.7 Center 19.5 19.7 20.3 20.5 20.5 20.1 19.8 South 19.8 19.5 19.8 20.6 20.7 20.2 19.2 Chisinau 19.3 19.6 20.5 20.9 21.0 20.3 18.5 Education No education/primary * * * * * * * Secondary 18.9 19.2 19.5 20.1 20.3 19.6 19.6 Secondary special 19.7 19.6 20.2 20.8 20.6 20.3 19.2 Higher 20.4 20.2 21.1 21.6 21.7 20.9 18.5 Wealth quintile Lowest 19.1 18.9 19.3 20.2 20.0 19.5 20.3 Second 19.2 19.4 20.0 20.3 20.4 19.9 20.0 Middle 19.9 19.7 20.2 20.5 20.5 20.2 19.4 Fourth 19.6 19.5 20.3 20.5 20.8 20.2 18.9 Highest 19.2 19.7 20.3 20.6 21.0 20.2 18.5 Total 19.4 19.5 20.0 20.5 20.6 20.0 19.3 Note: The medians for cohorts 15-19 and 20-24 could not be calculated because less than 50 percent of the respondents had had sexual intercourse before reaching the lower age extreme of the age group. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Interestingly, the data for men show a reverse pattern from that for women for each background characteristic. For example, rural men start sexual activity about one year later than urban men. Men in Chisinau have the lowest median age at first sex, while women in Chisinau have the highest. Unlike women, the median age at first sex among men decreases as the level of education and wealth quintile increase. 7.5 RECENT SEXUAL ACTIVITY In the absence of contraception, the chance of becoming pregnant is related to the frequency of sexual intercourse. Thus, information on sexual activity can be used to refine measures of exposure to pregnancy. Women and men were asked how long ago their last sexual activity occurred. The responses to this question allow for an assessment of recent sexual activity (in the four weeks preceding the survey). Tables 7.6.1 and 7.6.2 show the distribution of women and men, respectively, according to the timing of last sexual activity, by background characteristics. Nineteen percent of women age 15-49 and 15 percent of men age 15-59 have never had sexual intercourse. Eight and 7 percent of women and men, respectively, report that their last sexual encounter occurred more than one year before the survey. Fourteen percent of women and men had sex in the year preceding the survey, but not in the past month, while 58 percent of women and 65 percent of men had a recent sexual encounter. Other Proximate Determinants of Fertility | 91 Table 7.6.1 Recent sexual activity: women Percent distribution of women by timing of last sexual intercourse, according to background characteristics, Moldova 2005 Time since last sexual intercourse Background characteristic Within the past 4 weeks Within 1 year1 One or more years ago Never had sexual intercourse Total2 Number of women Age 15-19 14.1 5.4 1.4 78.1 100.0 1,417 20-24 55.4 17.3 3.4 22.3 100.0 1,124 25-29 70.2 18.5 6.1 3.7 100.0 964 30-34 77.5 14.8 6.2 0.8 100.0 924 35-39 74.7 13.9 8.8 1.1 100.0 855 40-44 70.2 16.0 12.5 0.2 100.0 1,007 45-49 63.9 17.7 17.1 0.3 100.0 1,149 Marital status Never married 10.6 8.5 3.7 76.0 100.0 1,862 Married or living together 80.8 15.3 3.2 0.0 100.0 4,937 Divorced/separated/ widowed 16.8 24.4 53.8 0.0 100.0 641 Marital duration3 Currently married: 0-4 years 82.8 13.7 2.2 0.0 100.0 794 5-9 years 80.6 16.5 1.8 0.0 100.0 749 10-14 years 84.6 12.5 2.2 0.0 100.0 732 15-19 years 80.9 15.1 3.9 0.0 100.0 707 20-24 years 78.1 17.4 3.9 0.0 100.0 721 25+ years 74.8 19.4 5.4 0.0 100.0 683 Married more than once 84.1 12.1 3.4 0.0 100.0 551 Residence Urban 59.8 13.2 8.2 17.4 100.0 3,194 Rural 56.1 15.2 7.3 20.2 100.0 4,246 Region North 57.2 15.1 8.0 18.6 100.0 2,207 Center 55.0 14.8 7.3 21.7 100.0 2,033 South 57.9 15.5 7.1 18.6 100.0 1,402 Chisinau 61.4 12.1 8.1 16.9 100.0 1,798 Education No education/primary (57.0) (23.2) (10.9) (7.7) 100.0 49 Secondary 53.6 13.9 7.4 23.9 100.0 4,534 Secondary special 68.3 14.7 9.7 6.4 100.0 1,327 Higher 60.7 15.2 6.7 15.9 100.0 1,530 Current contraceptive method Female sterilization 76.3 12.8 9.8 0.0 100.0 256 Pill 86.9 12.2 0.4 0.0 100.0 207 IUD 81.8 14.0 3.6 0.0 100.0 1,320 Condom 83.7 15.4 0.7 0.0 100.0 501 Rhythm 88.8 10.5 0.0 0.0 100.0 188 Other method 85.6 13.2 0.5 0.0 100.0 1,235 No method 32.0 15.1 13.1 37.9 100.0 3,732 Total 57.7 14.4 7.7 19.0 100.0 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes women who had sexual intercourse within the past 4 weeks 2 Total included missing cases 3 Excludes women who are not currently married 92 | Other Proximate Determinants of Fertility Table 7.6.2 Recent sexual activity: men Percent distribution of men by timing of last sexual intercourse, according to background characteristics, Moldova 2005 Time since last sexual intercourse Background characteristic Within the past 4 weeks Within 1 year1 One or more years Never had sexual intercourse Total2 Number of men Age 15-19 21.0 19.1 3.0 56.9 100.0 411 20-24 67.6 19.3 5.1 8.0 100.0 275 25-29 79.7 13.8 2.8 3.6 100.0 234 30-34 83.1 9.1 3.0 4.8 100.0 224 35-39 83.7 9.8 3.4 2.7 100.0 248 40-44 76.1 11.8 4.5 6.7 100.0 247 45-49 72.6 11.1 11.0 4.8 100.0 349 50-54 66.0 12.7 12.6 8.7 100.0 296 55-59 57.3 12.8 19.5 10.4 100.0 224 Marital status Never married 36.0 20.1 5.9 37.9 100.0 730 Married or living together 78.8 10.1 5.9 4.9 100.0 1,657 Divorced/separated/ widowed 39.7 24.1 30.3 5.4 100.0 120 Marital duration3 Currently married: 0-4 years 82.2 9.5 4.7 3.6 100.0 156 5-9 years 84.7 9.1 2.8 3.5 100.0 161 10-14 years 82.3 8.0 3.4 5.4 100.0 178 15-19 years 78.7 12.1 3.6 5.7 100.0 154 20-24 years 82.6 6.8 4.8 4.7 100.0 99 25+ years 65.9 14.8 12.2 7.0 100.0 329 Married more than once 80.5 8.0 6.9 4.0 100.0 210 Residence Urban 67.8 13.2 6.3 12.7 100.0 1,055 Rural 62.1 14.1 7.7 15.9 100.0 1,453 Region North 66.9 13.0 6.8 13.1 100.0 756 Center 58.2 14.7 8.6 18.3 100.0 702 South 63.1 14.8 7.9 13.7 100.0 496 Chisinau 70.4 12.4 4.8 12.4 100.0 554 Education No education/primary * * * * 100.0 16 Secondary 60.2 14.6 7.4 17.5 100.0 1,788 Secondary special 72.2 11.8 7.0 9.0 100.0 302 Higher 79.3 10.7 6.2 3.6 100.0 403 Total 64.5 13.7 7.1 14.5 100.0 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Excludes men who had sexual intercourse within the past 4 weeks 2 Total included missing cases 3 Excludes men who are not currently married Other Proximate Determinants of Fertility | 93 As expected, recent sexual activity is less common among the youngest age group, 15-19; three- quarters of women and over half of men in this age group have never had sex. Recent sexual activity is more common among the currently married, with about 80 percent of married women and men having had sex in the four weeks before the survey. Male-female differences are greatest for those who have never married and those formerly married. Among those who have never married, the proportion of males who report a recent sexual encounter is more than three times that of women (36 and 11 percent, respectively). There is a similar pattern among those who were formerly married (40 percent for men and 17 percent for women). The proportion of respondents who report having recent sexual activity tends to decrease among those married longer. Residents of Chisinau are slightly more likely to report recent sexual activity than those in other regions. The proportions reporting recent sexual activity do not differ very much across the other characteristics. However, women who report using no contraceptive method are less likely to have had a recent sexual encounter than women using contraception. This is not surprising because many of them have never had sex. 7.6 POSTPARTUM AMENORRHEA, ABSTINENCE, AND INSUSCEPTIBILITY Postpartum amenorrhea is defined as the period between childbirth and the return of ovula- tion, generally approximated by the resumption of menstruation following childbirth. This period is largely determined by the duration and intensity of breastfeeding. The risk of conception in this pe- riod is very low. The duration of the postpartum amenorrhea and the period of sexual abstinence following birth jointly determine the length of the insusceptibility period. Thus, women are consid- ered insusceptible if they are abstaining from sex following childbirth or are amenorrheic. Women who gave birth three years pre- ceding the survey were asked about the duration of their periods of amenorrhea and sexual absti- nence following each birth. The results are pre- sented in Table 7.7. Over three-quarters of women are insusceptible to pregnancy within the first three months following childbirth. After the third month, the contribution of abstinence is greatly reduced. At 8-11 months after birth, about 40 per- cent of women are still amenorrheic, but only 9 percent are abstaining. At 12-15 months post- partum, the proportion amenorrheic is only 12 percent. The principal determinant of the length of the period of insusceptibility is postpartum amenor- rhea. The median duration of amenorrhea is 5.8 months; of abstinence, 1.7 months; and insusceptibility, 6.3 months. Table 7.7 Postpartum amenorrhea, abstinence, and insusceptibility Percentage of births in the three years preceding the survey for which the mother is postpartum amenorrheic, abstaining, and insusceptible, by number of months since birth, and median and mean durations, Moldova 2005 Percentage of births for which the mother is: Months since birth Amenorrheic Abstaining Insusceptible Number of births < 3 71.4 38.3 77.0 101 4-7 50.8 7.0 53.2 98 8-11 39.0 8.5 43.3 113 12-15 12.1 7.3 17.8 136 16-19 4.4 2.5 5.9 119 20-23 3.7 5.1 8.9 105 24-27 2.1 5.8 8.0 106 28-31 4.3 1.7 5.4 118 32-35 2.8 0.0 2.8 110 Total 20.1 8.1 23.6 1,005 Median 5.8 1.7 6.3 na Mean 8.1 3.8 9.4 na Note: Estimates are based on status at the time of the survey. na = Not applicable 94 | Other Proximate Determinants of Fertility 7.7 TERMINATION OF EXPOSURE TO PREGNANCY One indicator of infecundity is the onset of menopause. Menopausal women are defined here as women who are neither pregnant nor postpartum amenorrheic, but who have not had a menstrual period in the six months before the survey. The prevalence of menopause increases with age, typically from around age 30. Table 7.8 presents the indicator for women age 30-49, which ranges from 1 percent for women in their 30s to 43 percent for women age 48-49. Table 7.8 Menopause Percentage of women age 30-49 in meno- pause, by age, Moldova 2005 Age Percentage of women in menopause1 Number of women 30-34 1.1 924 35-39 1.1 855 40-41 4.1 361 42-43 6.6 389 44-45 10.4 492 46-47 26.7 465 48-49 43.4 449 Total 11.0 3,934 1 Percentage of all women who are not pregnant and not postpartum amenor- rheic whose last menstrual period occurred six or more months preceding the survey or who report that they are menopausal. Fertility Preferences | 95 FERTILITY PREFERENCES 8 This chapter focuses on three indicators of need for contraception: whether or not the respondent wants another child and, if so, the preferred interval between children; the number of children considered to be ideal; and the level of unwanted and mistimed fertility. Analysis and interpretation of these issues reveal important implications for the planning and implementation of family planning programs. The underlying rationale of most family planning programs is to give couples the freedom and ability to bear the number of children they want and to achieve the spacing of births they want. The data are used to quantify fertility preferences and, in combination with information on contraceptive use, allow estimation of unmet need for family planning. 8.1 DESIRE FOR MORE CHILDREN Women and men in the 2005 MDHS sample were asked, “Would you like to have (a/another) child or would you prefer not to have any (more) children?” Respondents who said that they would like to have more children were asked, “How long would you like to wait from now before the birth of (a/another) child?” Responses to these questions are presented in Table 8.1 by the number of living children for both married women and men. Overall, 64 percent of married women either do not want another child or are sterilized, 28 percent want to have another child—12 percent soon (within two years), 14 percent later, and 3 percent undecided when—and the remaining 7 percent are either undecided or say they are unable to have another child (Figure 8.1). Fertility preferences among married men show a similar pattern to women, with an identical pro- portion (64 percent) either wanting no more children or sterilized. Men are slightly less likely than women to want another child (24 percent) and slightly more likely to be undecided. The data imply that Moldovan women and men generally want small families. A large majority of those with two children (77 percent of women and 74 percent of men) say they do not want any more, as do 83 percent of women and 82 percent of men with three children. Even among those with one child, over one-third do not want to have another. And surprisingly, 9 percent of women and 17 percent of men with no children say that they do not want any children. Comparison of data with the 1997 MRHS to assess trends in fertility preferences is hampered by differences in the sample coverage—the 1997 survey covered women age 15-44 only—and in the way questions were asked. Specifically, the 1997 survey asked whether the respondent intends to have another baby at some time, whereas the 2005 MDHS asked whether the respondent would like to have another child. Moreover the surveys tabulated results in different categories. Nevertheless, it appears that the proportion of married women who want no more children has remained more or less constant. 96 | Fertility Preferences Table 8.1 Fertility preferences by number of living children Percent distribution of currently married women and men by desire for children, according to number of living children, Moldova 2005 Number of living children1 Desire for children 0 1 2 3 4+ Total WOMEN Have another soon2 48.9 19.0 3.2 1.3 1.0 11.5 Have another later3 19.0 32.7 5.4 2.1 0.9 13.6 Have another, undecided when 11.0 4.4 1.7 1.0 1.3 3.2 Undecided 0.9 3.4 2.6 1.3 2.7 2.5 Want none/no more 8.6 33.4 76.8 83.3 81.2 59.4 Sterilized4 0.6 2.4 6.2 6.2 7.6 4.7 Declared infecund 10.1 4.1 4.0 4.9 4.0 4.7 Missing 0.9 0.6 0.2 0.0 1.2 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 455 1,394 2,094 692 302 4,937 MEN Have another soon2 39.8 18.1 4.5 2.7 0.0 10.1 Have another later3 8.3 21.1 5.9 0.7 0.9 8.3 Have another, undecided when 17.6 11.5 3.0 1.8 2.8 6.0 Undecided 5.6 6.5 6.3 4.0 0.7 5.4 Want none/no more 17.3 36.9 73.6 82.3 88.6 62.9 Sterilized4 0.6 1.1 1.7 1.4 0.0 1.3 Declared infecund 9.3 4.9 4.5 7.2 6.9 5.7 Missing 1.6 0.0 0.5 0.0 0.0 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 149 380 696 302 130 1,657 1 Includes current pregnancy 2 Wants next birth within 2 years 3 Wants to delay next birth for 2 or more years 4 Includes both female and male sterilization Figure 8.1 Fertility Preferences among Currently Married Women and Men Age 15-49 Wants child soon (within 2 years) 12% Want child later (after 2 years) 14% Wants child, undecided when 3% Undecided 3% Want no more 59% Sterilized 5% Declared infecund 5% Want no more 63% Undecided 5% Wants child, undecided when 6% Want child later (after 2 years) 8% Wants child soon (within 2 years) 10% Declared infecund 6% Sterilized 1% WOMEN MEN Note: Totals may not add to 100 because of rounding. MDHS 2005 Fertility Preferences | 97 The proportion of women who want to stop childbearing is shown in Table 8.2 by residence, region, education, and wealth quintile. Although, overall, a larger proportion of women in rural areas want no more children compared with women in urban areas (69 percent and 57 percent, respectively,. this is mainly because rural women already have more children than urban women; among women with 0, 1, etc. children, the proportion who want no more is almost the same for urban and rural women. Women in the North are generally more likely than women in other regions to want to stop childbearing. Women in Chisinau are the least likely to want no more children; however, among those with two or more children, the regional differences are smaller than among those with one child or no children. Similarly, educational differences in the proportion of women with two or more children who want no more children are slight. Overall, the differences by wealth quintile show a steady decline in the proportion of women who want no more children as wealth increases. However, the relationship is largely due to differences in the distribution of women by number of living children. When that is controlled for, the relationship either disappears of reverses. For example, among women with one child, the proportion who want no more children is almost identical at all wealth quintiles, while among women with two children, the proportion who want no more shows a very slight tendency to increase as wealth quintile increases. Table 8.2 Desire to limit childbearing Percentage of currently married women who want no more children, by number of living children and background characteristics, Moldova 2005 Number of living children1Background characteristic 0 1 2 3 4+ Total Residence Urban 8.7 35.6 84.1 87.4 88.9 56.8 Rural 10.1 36.0 82.2 90.0 88.9 69.3 Region North 11.6 45.9 86.0 92.8 89.2 70.2 Center 6.0 27.3 81.3 91.3 90.3 66.8 South 11.6 29.8 80.4 86.7 86.5 65.7 Chisinau 8.5 34.3 82.6 80.0 86.6 51.5 Education No education/primary * * * * * * Secondary 9.2 33.2 82.1 89.4 89.5 65.6 Secondary special 12.1 47.1 85.4 90.7 78.6 72.2 Higher 7.4 32.0 82.6 86.1 100.0 50.6 Wealth quintile Lowest 10.2 36.3 80.3 88.8 87.0 70.6 Second 10.9 37.8 81.8 94.7 90.3 69.6 Middle 8.4 36.1 82.4 88.8 97.1 67.5 Fourth 6.4 35.5 83.9 87.4 76.5 62.7 Highest 10.5 34.7 85.0 83.4 100.0 53.8 Total 9.2 35.8 83.0 89.5 88.9 64.1 Note: Women who have been sterilized are considered to want no more children. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes current pregnancy 98 | Fertility Preferences 8.2 NEED FOR FAMILY PLANNING SERVICES Women who are currently married and who say either that they do not want any more children or that they 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 who are using family planning methods are said to have a met need for family planning. Women with unmet need and met need constitute the total demand for family planning. Table 8.3 presents information for currently married women on unmet need, met need, and total demand for family planning, according to whether the need is for spacing or limiting births. Seven percent of currently married women in Moldova have an unmet need for family planning, 3 percent for spacing births and 4 percent for limiting. If all these women with unmet need were to join the 68 percent who already are using family planning (met need), the contraceptive prevalence rate could increase from the current level of 68 percent to 75 percent (total demand). The data in this table show that 91 percent of this total demand among married women is satisfied. Overall, unmet need is highest among the youngest married women (15-19) and decreases with age. However, while unmet need for spacing declines with age, unmet need for limiting increases slightly with age. Differences in unmet need for family planning by other background characteristics are small. Demand for family planning is also remarkably constant across background characteristics. One exception is age; total demand rises with age to a high of 84 percent among married women in their late 30s, after which it declines. Fertility Preferences | 99 Table 8.3 Need for family planning among currently married women 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, Moldova 2005 Unmet need for family planning1 Met need for family planning (currently using)2 Total demand for family planning3 Background characteristic For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Percentage of demand satisfied Number of women Age 15-19 11.4 1.5 12.9 47.6 10.8 58.4 62.5 12.2 74.7 82.8 136 20-24 8.0 3.6 11.6 48.6 14.5 63.1 58.7 18.1 76.8 84.9 629 25-29 5.0 3.1 8.1 37.6 33.2 70.7 44.1 36.5 80.6 90.0 794 30-34 1.8 4.0 5.9 24.6 50.3 74.9 26.6 54.4 81.0 92.8 810 35-39 0.2 4.8 5.0 7.6 70.7 78.3 8.0 75.5 83.5 94.1 746 40-44 0.1 5.6 5.7 2.5 71.0 73.5 2.6 76.7 79.3 92.8 869 45-49 0.2 4.2 4.3 0.4 49.8 50.2 0.6 54.0 54.6 92.0 953 Residence Urban 2.9 4.2 7.1 25.4 41.8 67.2 28.7 46.1 74.7 90.5 2,045 Rural 2.3 4.1 6.4 14.9 53.3 68.2 18.0 57.5 75.5 91.5 2,892 Region North 1.7 4.6 6.3 16.0 53.1 69.0 18.6 57.8 76.4 91.7 1,515 Center 3.0 4.1 7.1 16.2 50.5 66.7 19.8 54.6 74.4 90.5 1,336 South 2.1 4.6 6.7 15.8 51.5 67.3 18.5 56.1 74.6 91.0 958 Chisinau 3.4 3.3 6.7 30.3 37.6 67.9 34.0 41.0 75.0 91.0 1,127 Education No education/primary (5.0) (12.5) (17.5) (17.5) (42.5) (60.0) (22.5) (55.0) (77.5) (77.4) 40 Secondary 2.9 4.4 7.2 16.8 48.6 65.3 20.4 53.1 73.5 90.1 2,884 Secondary special 0.7 4.5 5.2 15.2 55.4 70.7 16.1 59.9 76.1 93.2 1,046 Higher 3.5 2.9 6.4 31.0 41.2 72.2 35.3 44.1 79.4 91.9 966 Wealth quintile Lowest 1.9 3.2 5.1 13.3 53.6 66.9 16.3 57.0 73.4 93.0 839 Second 2.4 5.3 7.6 14.8 51.4 66.1 18.0 56.8 74.8 89.8 834 Middle 2.7 5.0 7.8 16.3 52.2 68.5 19.4 57.2 76.6 89.9 1,029 Fourth 2.7 4.0 6.7 18.8 48.0 66.9 22.2 52.0 74.2 91.0 1,081 Highest 2.7 3.5 6.2 29.8 40.0 69.8 33.0 43.5 76.5 91.9 1,154 Total 2.5 4.2 6.7 19.3 48.5 67.8 22.4 52.8 75.2 91.1 4,937 Note: Figures in parentheses are based on 25-49 unweighted cases. 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 2 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 fecund women who are neither pregnant nor amenorrheic and who are not using any method of family planning and who want no more children. Excluded from the unmet need category are pregnant and amenorrheic women who became pregnant while using a method. 2 Using family planning for spacing is defined as women who are using some method of family planning and say they want to have another child or are undecided whether to have another. Using family planning 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 here. 3 Nonusers who are pregnant or amenorrheic and women whose pregnancy was the result of a contraceptive failure are not included in the category of unmet need, but are included in total demand for contraception (since they would have been using had their method not failed). 100 | Fertility Preferences 8.3 WANTED AND UNWANTED FERTILITY Interviewers asked women a series of questions regarding children born in the five years preceding the survey date and any current pregnancy to determine whether each birth/pregnancy was wanted then, wanted later, or not wanted at all. These questions provide a powerful indicator of the degree to which couples successfully control fertility. Also, the data can be used to gauge the effect of the prevention of unwanted births on fertility rates. Table 8.4 and Figure 8.2 show the percentage of births in the five years preceding the survey that were wanted by the mother at the time she got pregnant, wanted later, or not wanted. Table 8.4 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 and mother's age at birth, Moldova 2005 Planning status of birth Birth order and mother's age at birth Wanted then Wanted later Wanted no more Missing Total Number of births Birth order 1 87.0 10.1 2.7 0.2 100.0 888 2 77.7 15.4 6.6 0.2 100.0 590 3 65.4 13.5 21.1 0.0 100.0 193 4+ 42.5 11.1 46.4 0.0 100.0 99 Age at birth <20 76.6 16.5 6.8 0.0 100.0 231 20-24 81.5 13.8 4.5 0.2 100.0 721 25-29 80.6 11.7 7.4 0.3 100.0 495 30-34 76.0 7.3 16.7 0.0 100.0 236 35-39 65.2 4.7 30.2 0.0 100.0 65 40-44 * * * * 100.0 23 Total 79.0 12.3 8.5 0.2 100.0 1,769 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. The data indicate that 12 percent of births in Moldova are mistimed (wanted later) and almost 9 percent are unwanted. The percentage of births considered to have been unwanted is highest for births of order four and above, almost half of which were reported as not wanted at the time of conception. Similarly, a larger proportion of births to older women are reported as unwanted, compared with births to younger women. For example, only 5 percent of births to women age 20-24 are unwanted, compared with 30 percent among women age 35-39. Data from the 1997 MRHS imply that there has been an increase in unwanted and mistimed births. In 1997, among women age 15-44 whose most recent pregnancy ended in a live birth in the five years before the survey, 9 percent were mistimed and 4 percent were unwanted. This compares to 12 and 9 percent of all births in the five years preceding the 2005 survey. Slight changes in the wording of the questions, as well as the fact that the MDHS did not include Transnistria, could account for some of the increase; however, it is also likely that there has been a genuine increase in unplanned births. Fertility Preferences | 101 Figure 8.2 Distribution of Births in the Five Years Preceding the Survey by Fertility Planning Status MDHS 2005 Wanted then 79% Wanted later 12% Unwanted 9% Infant and Child Mortality | 103 INFANT AND CHILD MORTALITY 9 This chapter reports information on mortality among children under five years of age. The neonatal, postneonatal, infant, and child mortality rates provide information on the levels, trends, and differentials between population groups. Mortality statistics are useful in identifying segments of the population where children are at high risk so that programs can be designed to increase their chances of survival. Estimates of infant and child mortality also serve as a necessary parameter for population projections, particularly if the level of adult mortality can be inferred with reasonable confidence. Finally, childhood mortality rates are widely regarded as basic indicators of a country’s socioeconomic level and quality of life. 9.1 DEFINITIONS AND METHODOLOGY The primary causes of childhood mortality change as children age. A large component of early infant mortality consists of congenital diseases and other biological factors related to conditions in early infancy. Child mortality, on the other hand, is primarily due to environmental causes which are more susceptible to control, such as infectious diseases, malnutrition, and accidents. As under-five mortality declines over time, it is often observed that child mortality declines to a greater degree than infant mortality; this phenomenon is mainly due to improvements in children’s environments brought about by public health interventions or general improvements in living standards (Sullivan et al., 1994). In this chapter, age-specific mortality rates are defined as follows: Neonatal mortality (NN): the probability of dying within the first month of life; Postneonatal mortality (PNN): the difference between infant and neonatal mortality; Infant mortality (1q0): the probability of dying before the first birthday; Child mortality (4q1): the probability of dying between the first and fifth birthdays; and Under-five mortality (5q0): the probability of dying before the fifth birthday. All rates are expressed per 1,000 live births, except for child mortality, which is expressed as deaths per 1,000 children surviving to age one. The data needed for the calculations are collected in the pregnancy section of the Women’s Questionnaire. Respondents were asked to report the outcome of each pregnancy in terms of standard international definitions. A live birth was defined as any birth, irrespective of the duration of the pregnancy, that after separation from the mother, showed any sign of life (for example, breathing, beating of the heart, or movement of the voluntary muscles) (WHO, 1993). For each live birth reported in the pregnancy history, information was collected on the month and year of birth, sex, survival status, and current age at the time of the interview if the child was alive, or age at death if the child had died. Mortality rates for specific periods preceding the survey were calculated using direct estimation techniques. There are several methods that can be used for the direct calculation of infant and child mortality measures, including the period approach, true cohort approach, and synthetic cohort approach. It is beyond the scope of this chapter to describe the differences between the main approaches, but a technical explication can be found in the Guide to DHS Statistics (Rutstein and Rojas, 2003). In short, the DHS uses the synthetic cohort approach which calculates mortality probabilities for small age segments, and then combines these component probabilities for the full age segment of interest. The advantage of 104 | Infant and Child Mortality this method is that mortality rates can be calculated for time periods close to the survey date while still respecting the principle of correspondence.1 9.2 ASSESSMENT OF DATA QUALITY The accuracy of mortality estimates calculated from retrospective birth histories depends on two factors: the completeness and accuracy with which births and deaths are reported and recorded (i.e., non- sampling error) and sampling variability of the estimates. In a retrospective survey such as the MDHS, the most likely source of non-sampling error is the underreporting of deceased children. This may be the respondent’s conscious avoidance of recalling a tragic loss or, since women age 40 and over report birth and death information as long as 25-30 years ago, underreporting of deaths for time periods furthest from the survey date is likely due to forgetfulness. This report focuses on mortality rates for the 15-year period prior to the survey, thus eliminating estimates for the time periods most distant from the survey and susceptible to recall error. When omission of childhood deaths occurs, the impact is usually most severe for deaths in early infancy. If early neonatal deaths are selectively underreported, the result is an unusually low ratio of deaths occurring within seven days to all neonatal deaths, and an unusually low ratio of neonatal to infant deaths. Hence it is useful to examine these ratios for the 15-year period prior to the survey. Neonatal and infant mortality rates from the MDHS are shown in Table 9.1. The neonatal to infant mortality ratio for the periods 1990-1994, 1995-1999 and 2000-2004 are 0.60, 0.79 and 0.38, respectively. In other countries in the region where mortality levels are similar to Moldova, the ratios were between 0.54 and 0.91 which are substantially higher than that of the most recent period in MDHS.2 This comparison suggests that for the most recent 5-year period there may be some degree of underreporting for neonatal mortality. On the other hand, mortality estimates are low and survey estimates are subject to sampling variability. Sampling variability arises because a different sample of women, with different experience of child mortality, would have produced measurably different estimates. Sampling error is concerned with how different such estimates might be. The survey estimate of neonatal mortality for 2000-2004 (4.6 per 1,000) has a 95 percent confidence interval of 0.7 to 8.5 per 1,000. The survey estimate of infant mortality for 2000-2004 (12.8 per 1,000) has a 95 percent confidence interval of 6.8 to 18.9 per 1,000. Indeed, what appears to be underreporting for neonatal mortality could be an acceptable ratio given the range of sample variation. 1 The term “correspondence” means that if a child is included in the exposed-to-risk in the denominator, and he/she dies during the relevant time period, then his/her death must be included in the numerator corresponding to that period of risk. 2 For example, using mortality data from World Health Statistics 2005 (WHO, 2005) and the 2005 World Population Data Sheet (PRB, 2005), the ratio of neonatal mortality to infant mortality for other countries in the region were: Belarus (0.63), Bulgaria (0.69), Czech Republic (0.54), Hungary (0.91), Poland (0.88), Russia (0.54), Slovakia (0.75) and Ukraine (0.90). Infant and Child Mortality | 105 9.3 LEVELS AND TRENDS IN INFANT AND CHILD MORTALITY Table 9.1 presents early childhood mortality rates in Moldova for the three 5-year periods preceding the 2005 MDHS. These periods coincide approximately with 2000-2004, 1995-1999 and 1990- 1995.3 For the most recent 5-year period before the survey, the level of under-five mortality is 14 deaths per 1,000 births, implying that about 1 in every 70 children born in Moldova during that period died before reaching their fifth birthday. The infant mortality rate is 13 deaths per 1,000 lives births, indicating that most all early childhood deaths take place during the first year of life. Keeping in mind that these estimates are likely underreported to some degree (see section 9.2), they are probably closer to the official government estimates in 2002 of 18 deaths under age 5 years per 1,000 births (25 per 1,000 in 1990) and 15 infant deaths per 1,000 live births (19 per 1,000 in 1990) (UNFPA, 2003). Table 9.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods preceding the survey, Moldova 2005 Years preceding the survey Approximate calendar year1 Neonatal mortality (NN) Postneonatal mortality2 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) 0-4 2000-2004 5 8 13 1 14 5-9 1995-1999 23 6 29 9 38 10-14 1990-1994 12 9 20 7 27 1 Because survey fieldwork was conducted from May to July 2005, the rates for the five- year calendar periods actually apply to the mid-point of the years, e.g., from June 2000 to June 2005, June 1995 to June 2000, and June 1990-June 1995. 2 Computed as the difference between the infant and neonatal mortality rates Figure 9.1 shows trends in mortality rates for the three 5-year periods using data from the pregnancy history in the MDHS. While the neonatal mortality rate 0-4 years prior to the survey (2000- 2004) appears to be underreported, the neonatal mortality rate 5-9 years prior to the survey (1995-1999) is high relative to other periods. And consequently, since neonatal mortality is a component of infant mortality and under-five mortality, these rates are also higher relative to other periods. Official statistics from the Moldova Statistics and Sociology Department (1990-2002) also show that infant mortality and under-five mortality were elevated in the mid-1990s, from about 1993 to 1997 (Government of Moldova, 2004). While a more detailed analysis will be necessary to positively identify factors influencing mortality rates since independence, the data from the MDHS suggest that deterioration in mortality indicators was due to a crisis in delivery care since these are the services which specifically affect newborns’ survival chances. Indeed, in 2001, Moldova launched the “Making Pregnancy Safer Initiative” in an effort to strengthen midwifery (Stratulat et al., 2005). Determining how much of the improvement in neonatal mortality may be due to this initiative and how much may be due to underreporting is outside the scope of this report. 3 Note that because fieldwork was conducted in mid-2005, the exact periods to which rates correspond are mid-2000 to mid-2005, mid-1995 to mid-2000 and mid-1990 to mid-1995. 106 | Infant and Child Mortality Compared with estimates from recent Repro- ductive Health Surveys and Demographic and Health Surveys conducted in other countries in Eastern Europe and Eurasia, children’s survival probabilities in Moldova are relatively high. Table 9.2 shows the infant mortality estimates for the 0-4 year period preceding the date of the surveys (which correspond most closely with the 5-9 year period prior to the 2005 MDHS survey, i.e., 29 deaths per 1,000 live births). It should be noted that Moldova’s official estimates of infant mortality do not appear to be biased by underreporting to the extent they are in other countries in the region where estimates exceed official rates by 50 percent (Romania 1999) to 330 percent (Azerbaijan 2001). It is generally understood that official rates in those countries are underestimated due to not using the WHO (1993) standard definition of a live birth, as well as other defects in the registration system (Notzon et al., 1999). As another point of reference, the Population Reference Bureau publishes recent infant mortality rates for all countries, primarily from official country sources (PRB, 2005). The following PRB estimates for IMR estimates correspond to “some point in the late 1990s and early 2000s”: in Eastern Europe, the IMR in Romania is 17 deaths per 1,000 live births, in Russia 12, in Ukraine 10, in Belarus 8, in Hungary 7, and in Moldova 14; in the Caucasus, the IMR in Armenia is 36, in Azerbaijan 10 (keeping in mind the gross underreporting for this country, mentioned above), and in Georgia 25; and in Central Asia, the IMR in Kazakhstan is 61, in Kyrgyz Republic 55, in Tajikistan 89, in Turkmenistan 74, and in Uzbekistan 62. Table 9.2 Regional infant mortality rates that correspond closely with the 5-9-year period prior to the 2005 MDHS Country Time period of estimate Infant mortality rate (per 1,000 live births) MOLDOVA (2005) 1995-1999 29 Romania (1999) 1995-1999 32 Uzbekistan (1996) 1998-2002 34 Armenia (2000) 1996-2000 36 Georgia (1999) 1995-1999 42 Kazakhstan (1999) 1995-1999 62 Kyrgyz Republic (1997) 1993-1997 62 Azerbaijan (2001) 1996-2001 74 Turkmenistan (2000) 1996-2000 74 Source: CDC and ORC Macro 2003 5 8 13 1 14 23 6 29 9 38 12 9 20 7 27 Neonatal mortality Postneonatal mortality Infant mortality Child mortality Under-five mortality 0 10 20 30 40 50 Deaths per 1,000 live births 2000-2004 1995-1999 1990-1994 Figure 9.1 Early Childhood Mortality Rates for Three 5-Year Periods Prior to the 2005 MDHS 1 Deaths per 1,000 children surviving to age one. 1 Infant and Child Mortality | 107 9.4 SOCIOECONOMIC DIFFERENTIALS IN CHILDHOOD MORTALITY Mortality differentials by place of residence, region, educational level of the mother, and wealth index are presented in Table 9.3. In order to reduce sampling variability and to have a sufficient number of births to study mortality differentials across population subgroups, period-specific rates are presented for the ten-year period preceding the survey (mid-1995 to mid-2005). As is the case in most countries, mortality rates in infancy and early childhood are higher in rural areas than urban areas. In terms of infant mortality, rural rates (23 per 1,000) exceed urban rates (17 per 1,000) by a factor of about 1.4. All of this difference is due to neonatal mortality rates. In the case of under-five mortality, rural children have higher rates (30 per 1,000) than urban children (20 per 1,000)—a factor of 1.5. Infants in the South region have the highest mortality rates of all regions, and children in Chisinau have the best chances of survival in their first five years. Higher levels of educational attainment are usually associated with lower mortality rates, in part because education exposes mothers to information about better nutrition and adequate spacing between births, as well as better knowledge about childhood illness and treatment. In Moldova, however, the pattern is not so clear because virtually all women are well educated, having at least a secondary education. Mortality differentials by the mother’s level of education show that children of mothers with secondary special education generally fare better than children of mothers with secondary or higher education. Table 9.3 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the ten-year period preceding the survey, by background characteristics, Moldova 2005 Background characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Residence Urban 11 7 17 3 20 Rural 16 7 23 6 30 Region North 15 3 18 4 22 Center 11 8 19 8 27 South 20 11 31 7 38 Chisinau 11 7 18 1 19 Education Secondary 16 9 25 7 31 Secondary special 10 2 13 3 15 Higher 10 7 17 3 20 Wealth quintile Lowest 10 10 20 9 29 Second 13 7 21 8 28 Middle 20 9 29 5 33 Fourth 16 3 19 3 22 Highest 11 6 16 1 17 Note: There were no cases of under-five mortality in which the mother had no education or just primary education. 1 Computed as the difference between the infant and neonatal mortality rates 108 | Infant and Child Mortality Mortality estimates by wealth quintile show the expected differentials: infant and child mortality rates are lowest for the highest wealth quintile, followed by the fourth wealth quintile. Although there is not a monotonic deterioration in mortality rates for the lower wealth quintiles, overall, children in these poorer households do not fare as well as those in the highest wealth quintiles. The exception is neonatal mortality where infants in the poorest households share about the same risk as those in the richest households. 9.5 DEMOGRAPHIC DIFFERENTIALS IN CHILDHOOD MORTALITY Childhood mortality rates by sex of child, age of mother at birth, birth order, previous birth interval, and birth size are presented in Table 9.4. As was the case with socioeconomic differentials, the rates are shown for the 10-year period preceding the survey. Table 9.4 Early childhood mortality rates by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the ten-year period preceding the survey, by demographic characteristics, Moldova 2005 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Sex of child Male 17 9 25 7 32 Female 11 5 16 4 20 Mother's age at birth <20 (8) (4) (12) (2) (15) 20-29 16 8 24 6 30 30-39 12 8 20 6 25 Birth order 1 14 7 21 2 23 2-3 13 8 20 8 28 4+ * * * * * Previous birth interval2 <2 years * * * * * 2-3 years (9) (6) (14) (9) (23) 4+ years 13 5 17 3 20 Note: Figures in parentheses are based on 250-499 unweighted months of exposure. An asterisk indicates that a figure is based on fewer than 250 unweighted months of exposure and has been suppressed. 1 Computed as the difference between the infant and neonatal mortality rates 2 Excludes first-order births In Moldova, as in almost all populations, mortality for male children exceeds that of female children: the mortality rate for infant boys is 25 per 1,000, and for infant girls it is 16 per 1,000. Similarly, for under-five mortality, the mortality rate for boys is 32 per 1,000 and for girls it is 20 per 1,000. Infant and Child Mortality | 109 The relationship between mother’s age at birth and childhood mortality indicates that children are at higher risk of death for mothers age 20 to 29 years at birth. It should be noted, however, that the higher rates are driven by high neonatal mortality, and other- wise the data show no difference for mor- tality at other age groups. There is also a weak association for birth order, with data showing little difference in mortality levels for first-born children and for second to third born children. No clear association can be deduced for the length of the preceding birth interval and child mortality because too few non-first births occur after short birth inter- vals. 9.6 PERINATAL MORTALITY Perinatal mortality rates indicate the level of mortality from the time of prenatal viability (i.e., the late fetal period beginning at 28 weeks of gestation) through labor, delivery, and the early neonatal period (i.e., the first seven days of life). Pregnancies that terminate without signs of life after the 28th week are referred to as stillbirths. Stillbirths and early neonatal deaths share many of the same underlying causes leading to mortality (e.g., congenital malformations), and for this reason, these events are aggregated into the perinatal mortality rate. Perinatal mortality rates are reported for the five-year period preceding the survey (i.e., mid-2000 to mid-2005). It should be noted that data quality is always an issue when considering perinatal mortality rates, because both stillbirths and early neonatal deaths are susceptible to underreporting. Table 9.5 presents perinatal mortality rates per 1,000 pregnancies (of at least 7 months duration) for all Moldova as well as by background characteristics. The overall perinatal mortality rate is 19 per 1,000. Perinatal mortality rates are higher than average among women for whom the pregnancy was their first pregnancy (24 per 1,000), among urban women (24 per 1,000) and especially those in Chisinau (31 per 1,000). Table 9.5 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the five-year period preceding the survey, by background characteristics, Moldova 2005 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Number of pregnancies of 7+ months duration Mother's age at birth <20 5 0 * 216 20-29 14 7 20 1,104 30-39 4 0 14 264 40-49 0 0 * 22 Previous pregnancy interval in months First pregnancy 12 5 24 707 <15 0 1 * 137 15-38 6 0 (17) 344 39+ 5 2 17 417 Residence Urban 12 3 24 616 Rural 11 5 16 989 Region North 2 2 9 475 Center 8 2 21 470 South 4 2 19 321 Chisinau 9 2 31 339 Education No education/primary 0 0 * 19 Secondary 15 7 21 1,044 Secondary special 2 0 11 229 Higher 5 1 20 313 Wealth quintile Lowest 6 0 18 317 Second 4 3 23 307 Middle 4 0 12 341 Fourth 5 3 24 312 Highest 5 2 19 329 Total 23 7 19 1,605 Note: Figures in parentheses are based on 250-499 unweighted months of exposure. An asterisk indicates that a figure is based on fewer than 250 unweighted months of exposure and has been suppressed. 1 Stillbirths are fetal deaths in pregnancies lasting seven or more months. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months of duration. Maternal and Child Health | 111 MATERNAL AND CHILD HEALTH 10 This chapter presents findings from key areas in maternal and child health namely, antenatal, postnatal and delivery care, childhood vaccination coverage and common childhood illnesses and their treatment. The findings are valuable to policymakers and program implementers for developing policies and strengthening programs to ensure the health of mothers and young children in Moldova. Health care for mothers and children in Moldova is provided by means of outpatient health facilities at the primary health care level and, for more complicated medical needs, a network of consultative and specialized hospital establishments. The primary health care network is organized according to geographical-territorial criteria and includes a service package with costs covered by government mandated medical insurance. Since 1997, antenatal care has shifted from services provided by obstetrician-gynecologists to services provided by a general practitioner (family doctor). Pregnant women typically access antenatal care through primary health care facilities, namely, family doctor centers, health centers and family doctor’s offices. This reform in primary health care has contributed to improving access to primary health services by dedicating finances to pay for the services, the cost of which constitutes over 30 percent of the overall budget for medical care. Delivery care is provided by obstetrical-gynecology units and maternities located in district and municipal hospitals, as well as specialized (tertiary) health care establishments, such as the Institute for Scientific Research in the field of Mother and Child Health Care. The 2005 MDHS results provide an evaluation of the utilization of maternal and child health services, as well as information useful in assessing the need for service expansion. The findings presented in the following sections are based on data collected from mothers about live births that occurred in the five years preceding the survey. 10.1 ANTENATAL CARE Antenatal care delivered by a trained provider is valuable for monitoring pregnancy and reducing risks both for the mother and child during pregnancy and delivery. The quality of antenatal care is described by who provides the care, the number of antenatal care visits, gestation age at the first and last visit, and services and educational information provided during antenatal care visits. Antenatal care provider Table 10.1 shows the percent distribution of women who had a live birth in the five years preceding the survey by the type of provider for the most recent pregnancy. Interviewers recorded all persons a woman may have seen for antenatal care, but results in the table indicate only the provider with the highest qualification (if more than one person was seen). Results show that 97 percent of women in Moldova were provided antenatal care by a medical doctor and, in only rare cases (less than 1 percent), by another medical professional such as a nurse. The proportion of women who received antenatal care from a doctor did not vary significantly by background characteristics, although the proportion was slightly lower (94-95 percent) among women with 4 or more births, from the lowest wealth quintile, and living in the South region. Still, even in these cases, 4 percent or less of women did not receive any antenatal care provided by a health professional. 112 | Maternal and Child Health Table 10.1 Antenatal care Percent distribution of women who had a live birth in the five years preceding the survey by antenatal care (ANC) provider during pregnancy for the most recent birth, according to background characteristics, Moldova 2005 Background characteristic Doctor Nurse Other No one Total Number of women Age at birth <20 98.7 0.0 0.0 1.3 100.0 173 20-34 97.1 0.9 0.1 1.8 100.0 1,142 35-49 97.2 0.0 0.0 2.8 100.0 72 Birth order 1 97.5 0.6 0.1 1.8 100.0 677 2-3 97.6 0.8 0.0 1.4 100.0 629 4+ 93.7 2.1 0.0 4.2 100.0 81 Residence Urban 97.8 0.0 0.1 1.9 100.0 566 Rural 97.0 1.3 0.0 1.6 100.0 821 Region North 98.3 0.7 0.0 1.0 100.0 424 Center 97.5 0.0 0.0 2.3 100.0 386 South 95.2 2.7 0.0 1.8 100.0 264 Chisinau 97.6 0.0 0.3 2.1 100.0 313 Education No education/primary * * * * 100.0 14 Secondary 97.1 1.0 0.0 1.8 100.0 880 Secondary special 99.1 0.0 0.0 0.9 100.0 209 Higher 96.8 0.5 0.3 2.2 100.0 283 Wealth quintile Lowest 94.0 2.4 0.0 3.3 100.0 246 Second 98.5 0.7 0.0 0.8 100.0 260 Middle 97.2 0.9 0.0 1.9 100.0 290 Fourth 98.3 0.0 0.0 1.7 100.0 283 Highest 98.2 0.0 0.3 1.3 100.0 308 Total 97.3 0.7 0.1 1.8 100.0 1,387 Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Moldova generally has a good record in providing antenatal care. First, the 1997 Reproductive Health Survey also indicated high levels of antenatal care coverage that are not significantly different from levels indicated in this survey (Serbanescu et al., 1998). Second, compared with estimates from other Demographic and Health Surveys and Reproductive Health Surveys conducted recently in the region, Moldova is among the countries with the highest coverage of antenatal care provided by a trained provider. For example, levels of antenatal care coverage in other countries in the region include Romania (89 percent in 1999), Ukraine (90 percent in 1999), Armenia (92 percent in 2000), Azerbaijan (70 percent in 2001), Georgia (91 percent in 1999), Kazakhstan (95 percent in 1999), Kyrgyz Republic (97 percent in 1997), Turkmenistan (98 percent in 2000), and Uzbekistan (95 percent in 1996) (CDC and ORC Macro, 2003). Maternal and Child Health | 113 Number and timing of antenatal care visits Early examination of pregnant women and the use of educational and preventive measures to avoid possible complications during pregnancy and delivery are elements of quality antenatal care. A successful pregnancy and delivery has the greatest chance of being achieved when a pregnant woman has her first antenatal care visit within the first trimester, and thereafter respects the recommended number of antenatal care visits. For a normal pregnancy, i.e., one which is not considered at high risk for antenatal complications, the Ministry of Health and Social Protection recommends at least six antenatal care visits, two of which should be with an obstetrician-gynecologist. The WHO guidelines recommend at least four antenatal care visits for a normal pregnancy. Table 10.2 shows the average number of antenatal care visits and the timing of the first visit during the most recent pregnancy for women with a live birth in the five years preceding the survey. Almost three-quarters of women (72 percent) had their first antenatal visit in the first trimester, with no substantial differences by urban-rural residence; another 19 percent had their first visit at 4-5 months of gestation. The median gestation age at the first antenatal visit was 3.2 months. Nine of ten women (89 percent) had 4 or more visits to a doctor during pregnancy without significant differ- ences by urban-rural residence. Results similar to those in this survey were reported by the Service Quality Assessment Survey conducted in 20 maternities in Moldova in 2005, which showed an identical proportion of women having their first antenatal visit in the first 3 months of pregnancy (72 percent). According to that study, the average number of visits to a family doctor was 6.2, and to the obstetrician was 4.6. Means of transport to the last antenatal care visit An important factor in evaluating the overall quality of antenatal care is its accessibility. The MDHS gathered data on the distance to the last antenatal care provider as well as on the type of transport used to make the last visit. According to results in Table 10.3, 41 percent of respondents reported walking to see an antenatal care provider for their last antenatal appointment, 30 percent used public transport, and 25 percent used private transport. Antenatal care received at home was reported by only 2 percent of respondents. The highest proportion of women who walked to see an antenatal care provider was in the Center region (49 percent); this region also recorded the lowest proportion of women using private transport (20 percent). In Chisinau, the highest proportion of pregnant women used public transport for the last antenatal care visit (36 percent). The average time to arrive at a provider was 28 minutes, ranging from 23 minutes in Chisinau to 35 minutes in the South region. These differences do not show significant discrepancies in accessibility of antenatal services throughout the country. Table 10.2 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, Moldova 2005 Residence Number and timing of ANC visits Urban Rural Total Number of ANC visits None 1.9 1.6 1.8 1 0.8 0.3 0.5 2-3 4.3 4.7 4.5 4+ 88.0 89.4 88.8 Don't know/missing 5.0 4.0 4.4 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 1.9 1.6 1.8 <4 72.6 71.0 71.7 4-5 19.5 19.0 19.2 6-7 3.4 7.6 5.9 8+ 1.0 0.6 0.8 Don't know/missing 1.6 0.1 0.7 Total 100.0 100.0 100.0 Median months pregnant at first visit (for those with ANC) 3.1 3.3 3.2 Number of women 566 821 1,387 114 | Maternal and Child Health Table 10.3 Means of transport to last antenatal visit Percent distribution of women who had a birth in the five years preceding the survey by means of transport to last antenatal care visit, Moldova 2005 Region Means of transport North Center South Chisinau Total On foot 40.7 48.6 37.6 36.2 41.3 Donkey/horse cart 0.0 0.8 0.0 0.0 0.2 Public transport 28.3 27.3 29.4 36.0 30.0 Private vehicle 28.1 19.5 29.1 23.8 24.9 Home visit 2.0 1.3 1.9 1.9 1.7 Did not receive antenatal care 1.0 2.3 1.8 2.1 1.8 Total 100.0 100.0 100.0 100.0 100.0 Number of women 424 386 264 313 1,387 Mean minutes 30.0 25.7 34.7 22.8 28.2 Antenatal counseling Effective antenatal counseling includes components such as informing a pregnant woman about the evolution of her pregnancy, educating her about the consequences of potentially harmful substances for herself and the fetus such as smoking and alcohol consumption, alerting her to danger signs during pregnancy and how to seek timely care in case of emergency, and the advantages of breastfeeding the child. Table 10.4 shows 84 percent of respondents were informed during an antenatal care visit about the negative impact and the consequences of smoking and alcohol consumption on the intrauterine fetal development. No significant variations are observed by background characteristics. Most pregnant women were informed about the importance of breastfeeding for the child’s development (87 percent), actions to be taken in case of an emergency situation (83 percent), and the need for postnatal care (85 percent). A smaller proportion (76 percent) was informed about family planning methods to help avoid or plan the timing of future pregnancies. Women most likely to receive educational information during their pregnancy were age 20-34 at the time of delivery, those who delivered their second or third birth, women in rural areas, and those from the Center region. Women least likely to receive information were those who live in Chisinau, were age 35-49 at time of delivery, and who were delivering for the 4th or more time. A particularly interesting finding is that women from Chisinau, who tend to have higher education and to come from the highest wealth quintile, reported being least likely to have received information—a phenomenon that may be explained by higher expectations and exigencies concerning the quality of information. Maternal and Child Health | 115 Table 10.4 Antenatal care education received during antenatal visit Percentage of women with a live birth in the five years preceding the survey who during an antenatal care visit received specific information about care during pregnancy, by background characteristics, Moldova 2005 Women who received antenatal care who also received information on: Background characteristic Smoking during pregnancy Alcohol Breast- feeding Emergency delivery plans Family planning Postnatal care Number of women Age at birth <20 83.0 81.7 85.6 80.6 72.0 83.5 171 20-34 84.2 84.1 87.6 82.9 77.3 85.9 1,120 35-49 77.7 82.0 84.8 83.5 69.3 78.7 70 Birth order 1 84.1 83.6 86.3 80.4 75.4 83.6 665 2-3 85.4 85.6 89.6 86.3 78.4 88.6 619 4+ 66.4 68.6 75.7 73.0 65.4 72.9 77 Residence Urban 82.3 82.2 84.6 78.2 71.3 80.3 554 Rural 84.7 84.7 89.0 85.7 79.6 88.6 807 Region North 83.6 83.6 87.1 82.9 77.7 85.8 420 Center 85.1 85.0 91.4 88.4 80.2 88.3 376 South 82.3 82.0 84.3 80.8 77.3 83.9 259 Chisinau 83.4 83.5 84.6 76.8 68.4 81.9 307 Education No education/primary * * * * * * 15 Secondary 83.8 83.5 87.9 84.3 77.2 86.2 864 Secondary special 88.2 89.1 90.1 85.4 78.7 87.1 207 Higher 80.7 80.6 83.2 77.2 72.1 82.6 276 Wealth quintile Lowest 81.7 82.6 88.6 84.6 76.3 87.7 237 Second 82.4 82.0 87.0 84.1 77.2 85.6 258 Middle 87.0 86.8 88.4 86.2 82.3 88.7 285 Fourth 87.3 86.2 89.1 83.6 76.2 84.5 278 Highest 80.0 80.6 83.3 75.6 69.6 80.5 303 Total 83.7 83.7 87.2 82.6 76.2 85.3 1,361 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Women who had a live birth in the five years preceding the survey were also asked whether an antenatal care provider encouraged them to invite a companion, such as their husband or partner, a family member or a close friend, to attend the delivery of their most recent birth. Almost four in ten women reported being encouraged to do so, with the prevalence in urban areas slightly higher (46 percent) than in rural areas (40 percent) (Figure 10.1). 116 | Maternal and Child Health Components of antenatal care The components of care provided to a pregnant woman are an indicator of the quality of antenatal services. In Moldova, specific services during an antenatal visit include the taking of anthropometric measures, blood pressure, urine and blood samples, performing an ultrasound, and providing iron and folic acid supplements. Pregnant women suffering certain pathologies or who are exposed to higher risks of adverse pregnancy complications undergo additional tests and examinations. Another important component of antenatal care is the provision of educational information to the pregnant woman about normal pregnancy evolution and signs of complications. Table 10.5 shows the proportion of women who had a live birth in the five years preceding the survey, and who received antenatal care for the most recent birth, who were also informed about signs of pregnancy complications, had basic tests performed, and received iron and folic acid supplements. Three of four pregnant women receiving antenatal care were informed about danger signs in pregnancy. The proportion of pregnant women who underwent basic tests is almost universal: at least 97 percent of women had blood and urine samples taken, had their blood pressure measured, were weighed, and had an ultrasound. No significant variations by background characteristics were identified for these tests, except for the ultrasound examination which is less likely to be administered to women under age 20 and over age 35 (93-94 percent), women in rural areas (95 percent), women in the South region (94 percent), and women from the lowest wealth quintiles (93-95 percent). 46 40 0 10 20 30 40 50 Percent Urban Rural Figure 10.1 Proportion of Women Encouraged to Invite a Companion to Attend the Delivery MDHS 2005 Maternal and Child Health | 117 Table 10.5 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 tablets or syrup or folic acid tablets for the most recent birth, according to background characteristics, Moldova 2005 Antenatal care content among women who received antenatal care Background characteristic Informed of signs of pregnancy complications Weight measured Blood pressure measured Urine sample taken Blood sample taken Received ultrasound Number of women Received iron tablets or syrup Received folic acid tablets Number of women Age at birth <20 74.4 97.2 98.7 99.1 100.0 93.6 171 48.4 16.2 173 20-34 75.8 96.3 98.8 99.4 99.5 97.5 1,120 55.5 21.7 1,142 35-49 74.7 100.0 100.0 100.0 98.5 92.5 70 42.1 11.4 72 Birth order 1 74.5 96.2 99.0 99.0 99.5 97.5 665 57.0 24.1 677 2-3 77.4 96.7 98.9 99.8 99.5 96.0 619 53.6 18.3 629 4+ 70.0 100.0 98.3 100.0 100.0 96.0 77 31.0 6.2 81 Residence Urban 74.2 97.3 98.8 99.3 99.4 98.7 554 62.2 26.2 566 Rural 76.5 96.2 99.0 99.5 99.6 95.4 807 48.3 16.5 821 Region North 76.3 97.0 98.7 99.1 99.2 96.7 420 49.7 22.6 424 Center 75.3 96.1 99.3 99.8 99.8 96.5 376 49.2 12.0 386 South 77.0 96.8 99.5 100.0 100.0 94.0 259 46.5 15.8 264 Chisinau 73.7 96.6 98.2 99.0 99.2 99.4 307 71.8 32.0 313 Education No education/primary * * * * * * 15 * * 16 Secondary 75.6 96.2 99.0 99.4 99.5 95.9 864 45.0 14.9 880 Secondary special 80.6 98.0 99.1 100.0 99.7 97.9 207 65.8 29.4 209 Higher 73.6 97.3 98.2 99.2 99.7 99.1 276 74.3 31.6 283 Wealth quintile Lowest 74.7 94.4 98.1 99.3 99.6 92.6 237 35.5 9.4 246 Second 74.3 97.4 99.5 99.3 99.3 94.5 258 45.9 14.6 260 Middle 79.7 98.0 99.6 99.8 99.8 97.6 285 55.4 21.4 290 Fourth 75.0 97.4 98.7 100.0 100.0 99.3 278 59.3 21.8 283 Highest 74.0 95.7 98.5 98.7 98.9 98.9 303 69.2 32.1 308 Total 75.6 96.6 98.9 99.4 99.5 96.8 1,361 53.9 20.5 1,387 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Maternal anemia, especially iron deficient anemia, is a major cause of both maternal complications and neonatal complications. Taking iron supplements during pregnancy is an efficient way to prevent iron deficient anemia. In addition, taking folic acid during pregnancy is an important way to protect the fetus against congenital anomalies, namely spina bifida. In Moldova, iron and folic acid is given free of charge to women during their pregnancy. Table 10.5 shows that 54 percent of pregnant women receive iron supplements, and coverage varies by place of residence and education. For example, mothers living in urban areas (62 percent) and especially in Chisinau (72 percent) are more likely to take iron during their most recent pregnancy than those living in rural areas (48 percent). The prevalence also increases with a higher education level; 74 percent of women with higher education take iron supplements versus only 45 percent of women with only a secondary education. 118 | Maternal and Child Health In the MDHS only one out of five women reported taking folic acid during thir last pregnancy. The low coverage may be partially explained by the fact that only 39 percent of mothers had ever heard of folic acid (data not shown). The differences in prevalence by background characteristics are similar to those observed for iron supplements: women age 20-34 are more likely to take folic acid than either younger or older women; women having their first birth are more likely to take folic acid than those having had previous births; women in urban areas, especially in Chisinau, are more likely to take folic acid than women in rural areas; women with a higher level of education and from higher wealth quintiles are also more likely to take folic acid. The MDHS data on the administration of iron and folic acid supplements differ slightly from the data collected by the 2005 Perinatal Service Quality Survey in maternities, which estimated that 61 and 32 percent of women, respectively, took these supplements. Coverage of antenatal care cost Women who had a live birth in the five years preceding the survey were asked whether the government or some insurance company covered the expenses for antenatal care. According to Act no.161-XV (April 30, 2004), women who are pregnant, delivering, or post-partum have services paid for by the government. However, since the law was adopted only a year prior to data collection for this survey, not all women had the possibility to benefit from this coverage. Indeed, only 20 percent of women reported full coverage of antenatal care expenses by the government or some other insurer, 28 percent reported partial coverage, and 52 percent declared that no expenses were covered by the government or other insurance program (see Figure 10.2 below). This indicator does not vary by urban-rural residence. 20 28 52 0 10 20 30 40 50 60 Percent Costs fully covered Costs partially covered No costs covered Figure 10.2 Proportion of Costs Covered by the Government or by an Insurance Program for Antenatal Care MDHS 2005 Maternal and Child Health | 119 Tetanus toxoid immunization Tetanus is an infectious disease caused by anaerobe bacteria Clostridium tetani that most frequently live in soil containing animal feces. These bacteria grow in dead tissues such as in wounds or a newborn’s navel after the umbilical cord has been cut. In developing countries, neonatal tetanus represents one of the main causes of death among newborn children. A newborn may become infected with tetanus if the knife, blade, or other instrument used to cut the umbilical cord is contaminated. Infants and children may become infected when contaminated instruments are used for circumcision, scarification, or piercing. Almost all children who contract tetanus die. Women may also be exposed to tetanus disease from a postnatal uterus infection. In Moldova, newborn tetanus disease was eliminated four decades ago, thanks both to universal immunization of children and adults with tetanus toxoid, and to virtually all women delivering in a medical establishment. Administering tetanus toxoid vaccination to women before or during pregnancy represents one of the most efficient means of preventing neonatal tetanus, particularly in settings where the deliveries occur outside a health facility. If a pregnant woman has not previously been vaccinated against tetanus, the WHO recommends two doses of vaccine during pregnancy in order to assure effective child and mother protection. In the case where the pregnant woman has received only two tetanus toxoid vaccinations prior to her pregnancy, another dose of tetanus vaccine needs to be administered. In general, to assure sustainable protection against tetanus throughout life, at least five doses of vaccine are recommended (WHO, 2002). According to the requirements of the Moldova National Immunization Program, a person has the most complete protection against tetanus when he or she has had four doses of vaccine administered before the age of two, and subsequent revaccination at ages 7, 15, 20, 25, 30, 35, 40, and 50 years. When a pregnant woman is vaccinated according to the requirements of the aforementioned program, no additional doses are required during pregnancy. According to the most recent official data on immunization coverage published by the National Scientific and Practical Centre of Preventive Medicine, over 98 percent of children and adolescents and almost 80 percent of adults received immunization against tetanus according to the vaccination timetable (NSPCPM, 2004-2006). To estimate tetanus vaccine coverage during pregnancy, the 2005 MDHS asked women who had a live birth in the five years preceding the survey about the number of tetanus vaccinations they had received in their lifetime. The estimated prevalence may underestimate the actual level of protection against tetanus due to difficulties in recalling how many doses of vaccine were administered to women in their lifetime, particularly the doses administered during childhood. Findings in Table 10.6 show that 13 percent of mothers reported having received in total two or more injections against tetanus, and 70 percent reported having received at least one dose of vaccine but were unsure about the total number of injections. they had received. Women who gave birth only once, women over age 34, and women from the South region were more likely to be vaccinated against tetanus. No significant variations were registered for this indicator by place of residence, education level, or wealth quintile. 120 | Maternal and Child Health Table 10.6 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 ever received, according to background characteristics, Moldova 2005 Number of injections ever received Background characteristic None One injection Two or more injections At least one, but don’t know how many Total Number of women Age at birth <20 9.6 7.1 8.8 74.5 100.0 173 20-34 10.2 7.6 13.7 68.6 100.0 1,142 35-49 8.6 2.5 8.3 80.6 100.0 72 Birth order 1 10.6 5.2 12.1 72.2 100.0 677 2-3 8.6 9.5 13.6 68.3 100.0 629 4+ 16.3 6.6 12.8 64.3 100.0 81 Residence Urban 12.1 6.4 11.6 69.9 100.0 566 Rural 8.6 7.8 13.7 69.9 100.0 821 Region North 7.0 8.4 14.2 70.3 100.0 424 Center 11.9 5.3 13.9 68.9 100.0 386 South 5.9 9.4 9.9 74.8 100.0 264 Chisinau 15.1 6.2 12.0 66.6 100.0 313 Education No education/primary * * * * 100.0 16 Secondary 10.2 8.9 12.7 68.3 100.0 880 Secondary special 7.0 4.4 14.0 74.6 100.0 209 Higher 11.1 3.7 13.2 72.0 100.0 283 Wealth quintile Lowest 6.8 11.6 13.0 68.6 100.0 246 Second 10.0 5.4 13.1 71.5 100.0 260 Middle 8.3 7.4 11.5 72.8 100.0 290 Fourth 9.6 6.5 14.0 70.0 100.0 283 Highest 14.6 5.9 12.6 66.9 100.0 308 Total 10.0 7.2 12.8 69.9 100.0 1,387 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Pregnancy complications In the 2005 MDHS, women who had a live birth in the five years preceding the survey were asked if they had any of the following complications during the most recent pregnancy: risk of mis- carriage, excessive bleeding in the first or second trimester, high blood pressure, diabetes, heart disease, liver disease, urinary tract infection, risk for premature labor, rhesus-conflict (Rh izoimmynization), anemia or other complications. Maternal and Child Health | 121 Table 10.7 shows the proportion of women with complications during pregnancy. Overall, 61 percent of women reported at least one complication during their most recent pregnancy. Most frequently reported complications were anemia (38 percent), risk of miscarriage (25 percent), risk of premature delivery (13 percent), high blood pressure (11 percent), and a urinary tract infection (10 percent). Two to 6 percent of women reported having had a hemorrhage in the first or second trimester, heart disease, liver disease, or rhesus-conflict. Less than 1 percent of women reported diabetes and 4 percent reported other complications. The proportion of women reporting at least one complication was higher among women younger than age 34 years, with fewer than 3 live births, living in urban areas and particularly in Chisinau, having a higher level of education, and from the highest wealth quintiles. Table 10.7 Pregnancy complications Among of women with a live birth in the five years preceding the survey who received antenatal care, percentage who experienced specific complications during the last pregnancy, by background characteristics, Moldova 2005 Pregnancy complications Background characteristic Any compli- cation Risk of mis- carriage First trimester bleeding Second trimester bleeding High blood pressure Diabetes Heart disease Liver disease Urinary tract infection Risk of pre-term labor Rh izoimmy- nization Anemia Other Number of women Age at birth <20 59.1 20.5 2.8 1.8 11.4 0.4 6.1 1.6 13.8 9.6 2.6 35.1 4.0 171 20-34 61.3 26.4 6.1 3.9 11.3 0.5 4.3 2.3 10.0 14.0 4.5 38.8 4.0 1,120 35-49 52.6 18.4 2.9 0.0 9.0 1.4 5.9 0.0 4.1 6.4 3.5 32.5 2.5 70 Birth order 1 61.8 27.2 5.7 3.1 10.3 0.8 2.8 2.1 12.4 14.2 4.5 37.1 4.8 665 2-3 60.2 23.8 5.5 3.5 12.4 0.3 6.2 1.9 7.6 12.0 4.5 40.4 3.5 619 4+ 52.5 19.8 5.1 6.6 9.4 0.0 8.4 3.5 10.9 11.6 0.0 27.2 0.0 77 Residence Urban 67.2 33.2 8.1 4.1 12.9 1.0 3.4 2.0 13.1 16.8 7.0 42.7 6.4 554 Rural 56.0 19.8 3.8 3.0 10.0 0.2 5.5 2.1 8.1 10.4 2.4 34.8 2.2 807 Region North 59.1 24.4 5.3 3.3 13.0 0.9 6.8 2.5 11.1 13.9 4.3 33.6 2.6 420 Center 58.3 19.6 3.1 2.8 8.6 0.0 3.1 2.3 5.4 9.6 2.8 42.4 3.1 376 South 57.0 21.3 4.5 2.4 11.1 0.0 3.4 1.2 10.3 8.6 1.7 36.1 3.5 259 Chisinau 68.4 36.6 9.9 5.3 12.1 1.1 4.5 2.2 14.4 19.8 8.2 40.4 7.2 307 Education No education/ primary * * * * * * * * * * * * * 15 Secondary 55.8 20.9 4.5 3.5 10.9 0.1 5.4 2.5 9.2 11.7 3.2 33.5 2.5 864 Secondary special 63.3 27.0 6.6 1.9 11.4 0.9 3.1 1.2 9.0 11.6 5.7 41.0 3.1 207 Higher 73.6 38.0 8.0 4.6 12.2 1.6 3.4 1.4 13.3 18.4 6.6 50.2 9.1 276 Wealth quintile Lowest 51.3 12.6 2.2 2.5 13.3 0.0 7.8 1.6 7.1 9.5 0.6 31.0 2.3 237 Second 54.7 16.9 3.7 3.9 11.7 0.5 5.0 1.2 7.6 9.6 1.6 33.0 1.7 258 Middle 58.4 27.2 4.5 2.8 7.7 0.2 4.3 4.0 11.2 11.5 4.9 39.7 2.1 285 Fourth 65.4 27.7 7.4 2.8 9.6 0.3 1.8 1.6 10.5 14.7 4.5 43.5 4.8 278 Highest 70.4 38.2 9.2 5.0 13.9 1.3 4.8 2.0 13.3 18.5 8.5 41.2 8.0 303 Total 60.6 25.3 5.6 3.4 11.2 0.5 4.6 2.1 10.1 13.0 4.3 38.0 3.9 1,361 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 122 | Maternal and Child Health Coverage of costs related to treatment of adverse pregnancy outcomes Women who had a pregnancy in the five years preceding the survey and who reported at least one complication during the most recent pregnancy were asked whether they sought care for this complication, and if yes, what portion of expenses were covered by the government or some other insurance program. Figure 10.3 shows that only 20 percent of women who had complications during their most recent pregnancy reported full coverage of the cost of treatment, 18 percent declared that the cost of treatment was partially covered, and 62 percent reported that no costs related to a pregnancy complication were covered by the government or any insurance program. Women in urban areas were slightly less likely to report partial or entire coverage of costs (data not shown). 10.2 DELIVERY CARE Adequate care and hygienic conditions at the time of delivery reduce the risk of complications for both the mother and the infant. The 2005 MDHS collected information about the place of delivery for all children born in the five years preceding the survey, as well as data on the type of personnel attending to the delivery. Table 10.8 shows that 99 percent of deliveries in Moldova that occurred in the five years preceding the survey were in a medical establishment. The overwhelming majority took place in public health facilities, and less than 1 percent in private establishments or the home. Women in Chisinau and those from the highest wealth quintile were slightly more likely to give birth in a private medical institution (2 percent each). Women who delivered outside of any health facility were mainly those who had had 4 deliveries or more (9 percent), those in rural areas (2 percent), particularly in the Center and South regions (2 percent each), those who had between 1 and 3 antenatal visits (5 percent), and those mainly from the lowest wealth quintile (4 percent). 20 18 62 0 10 20 30 40 50 60 70 Percent Costs fully covered Costs partially covered No costs covered Figure 10.3 Proportion of Costs Covered by the Government or by an Insurance Program for Treatment of Pregnancy Complications MDHS 2005 Maternal and Child Health | 123 Table 10.8 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics, Moldova 2005 Health facility Background characteristic Public sector Private sector Home Other Total Number of births Mother's age at birth <20 99.7 0.3 0.0 0.0 100.0 212 20-34 98.1 0.6 0.9 0.2 100.0 1,301 35-49 98.9 0.0 1.1 0.0 100.0 78 Birth order 1 99.0 0.8 0.2 0.0 100.0 807 2-3 98.6 0.4 0.6 0.2 100.0 691 4+ 91.4 0.0 7.2 1.5 100.0 94 Residence Urban 98.5 1.3 0.0 0.0 100.0 611 Rural 98.3 0.1 1.3 0.3 100.0 980 Region North 99.4 0.0 0.0 0.6 100.0 473 Center 98.1 0.2 1.5 0.0 100.0 464 South 98.4 0.0 1.6 0.0 100.0 317 Chisinau 97.3 2.4 0.0 0.0 100.0 337 Mother's education No education/primary * * * * 100.0 19 Secondary 98.3 0.4 0.9 0.3 100.0 1,033 Secondary special 99.4 0.0 0.6 0.0 100.0 229 Higher 98.2 1.6 0.0 0.0 100.0 310 Antenatal care visits1 None (81.6) (3.0) (15.5) (0.0) (100.0) 24 1-3 94.8 0.0 5.2 0.0 100.0 70 4+ 98.8 0.6 0.4 0.2 100.0 1,232 Don't know/missing 98.6 0.0 0.0 0.0 100.0 61 Wealth quintile Lowest 96.1 0.0 2.7 0.9 100.0 311 Second 99.3 0.0 0.7 0.0 100.0 304 Middle 99.5 0.0 0.5 0.0 100.0 339 Fourth 99.5 0.5 0.0 0.0 100.0 309 Highest 97.5 2.3 0.0 0.0 100.0 328 Total 98.4 0.6 0.8 0.2 100.0 1,591 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes only the most recent birth in the five years preceding the survey Table 10.9 shows that virtually every delivery in Moldova is attended by a trained health professional. Almost 91 percent of deliveries were attended by a doctor while the rest were attended by a nurse or midwife. The differences in delivery care slightly vary with regard to maternal background characteristics, however, doctors were more likely to attend deliveries for women age 35-49 (94 percent), women who had their first birth (92 percent), women from urban areas (93 percent) and particularly in Chisinau (94 percent), those with higher education (96 percent) and those from the highest wealth quintile (95 percent). 124 | Maternal and Child Health Table 10.9 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, Moldova 2005 Background characteristic Doctor Nurse/ midwife/ auxiliary midwife Relative/ other No one Don't know/ missing Total Number of births Mother's age at birth <20 89.3 10.7 0.0 0.0 0.0 100.0 212 20-34 90.7 8.8 0.1 0.1 0.3 100.0 1,301 35-49 94.4 4.5 1.1 0.0 0.0 100.0 78 Birth order 1 92.3 7.6 0.0 0.0 0.1 100.0 807 2-3 89.4 9.6 0.3 0.3 0.4 100.0 691 4-5 83.3 16.7 0.0 0.0 0.0 100.0 78 6+ * * * * * * 15 Residence Urban 92.9 6.7 0.0 0.1 0.3 100.0 611 Rural 89.3 10.1 0.2 0.1 0.2 100.0 980 Region North 92.4 7.6 0.0 0.0 0.0 100.0 473 Center 88.5 10.6 0.4 0.3 0.2 100.0 464 South 87.8 11.6 0.0 0.2 0.4 100.0 317 Chisinau 94.0 5.5 0.0 0.0 0.5 100.0 337 Mother's education No education/primary * * * * * * 19 Secondary 88.3 11.0 0.2 0.2 0.3 100.0 1,033 Secondary special 93.7 6.3 0.0 0.0 0.0 100.0 229 Higher 96.3 3.5 0.0 0.0 0.3 100.0 310 Wealth quintile Lowest 82.5 16.7 0.4 0.2 0.3 100.0 311 Second 91.5 7.5 0.3 0.4 0.4 100.0 304 Middle 90.0 10.0 0.0 0.0 0.0 100.0 339 Fourth 94.1 5.7 0.0 0.0 0.2 100.0 309 Highest 95.3 4.4 0.0 0.0 0.3 100.0 328 Total 90.7 8.8 0.1 0.1 0.2 100.0 1,591 Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Indicators from Demographic and Health Surveys and Reproductive Health Surveys recently completed in other countries in Eastern Europe and Eurasia also show that delivery care is generally good: 95 percent of women countries surveyed in the region had births which were attended by a health professional and whose delivery was in a health facility. Azerbaijan (2001) is the main exception, where only 88 percent of women are assisted by a health professional and only 74 percent deliver in a medical establishment (CDC and ORC Macro, 2003). 10.3 DELIVERY CHARACTERISTICS The purpose of performing a caesarean section is to reduce maternal and perinatal mortality and morbidity. Official data from the Ministry of Health and Social Protection submitted to WHO for the last fifteen years reveals an increasing trend in the use of this intervention, from an average of 5 percent of all births from 1990 to 1994, to an average of 7 percent from 1995 to 1999, and up to 9 percent in 2004 (WHO, 2006). Maternal and Child Health | 125 In the 2005 MDHS, women who had live births in the five years preceding the survey were asked whether any delivery was by caesarean section. Table 10.10 shows that in the past five years 9 percent of children were born by caesarean section, thus corroborating the official reports. A caesarean section is slightly more likely to be performed on women having their first birth (10 percent), women in urban areas (11 percent), and women in Chisinau (13 percent), women with secondary special education (11 percent), and women in the highest wealth quintile (14 percent). Women in the South region, as well those from the poorest wealth quintile, are least likely to have a caesarean section (4 percent). Table 10.10 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, Moldova 2005 Birth weight Size of child at birth Background characteristic Delivery by C-section Less than 2.5 kg 2.5 kg or more Don't know/ missing Total Very small Smaller than average Average or larger Don't know/ missing Total Number of births Mother's age at birth <20 7.2 7.2 92.8 0.0 100.0 3.1 14.6 80.7 1.6 100.0 212 20-34 8.6 5.2 93.8 1.0 100.0 1.4 9.6 88.2 0.8 100.0 1,301 35-49 9.2 4.8 94.1 1.1 100.0 1.9 10.6 87.6 0.0 100.0 78 Birth order 1 9.9 6.5 93.1 0.5 100.0 1.7 12.3 84.7 1.3 100.0 807 2-3 7.0 4.5 94.3 1.2 100.0 1.4 7.9 90.2 0.6 100.0 691 4+ 7.4 4.2 94.8 0.9 100.0 2.8 11.3 85.8 0.0 100.0 94 Residence Urban 10.9 5.2 94.0 0.8 100.0 0.9 8.4 90.0 0.6 100.0 611 Rural 7.0 5.7 93.5 0.9 100.0 2.1 11.5 85.3 1.1 100.0 980 Region North 8.2 8.6 91.0 0.4 100.0 2.7 14.1 82.0 1.2 100.0 473 Center 8.6 3.7 95.6 0.7 100.0 1.2 8.6 89.3 0.8 100.0 464 South 4.2 4.9 94.0 1.2 100.0 1.6 11.1 86.1 1.2 100.0 317 Chisinau 12.7 4.1 94.7 1.2 100.0 0.7 6.6 92.3 0.5 100.0 337 Mother's education No education/primary * * * * * * * * * 100.0 19 Secondary 8.0 6.3 92.5 1.1 100.0 2.2 11.3 85.1 1.3 100.0 1,033 Secondary special 10.6 3.1 96.6 0.3 100.0 0.6 8.5 90.8 0.0 100.0 229 Higher 8.2 4.1 95.6 0.3 100.0 0.0 8.4 91.3 0.3 100.0 310 Wealth quintile Lowest 3.8 6.6 92.3 1.1 100.0 3.6 11.2 83.2 1.9 100.0 311 Second 9.2 7.6 91.1 1.3 100.0 2.0 12.3 84.3 1.4 100.0 304 Middle 7.6 2.4 97.3 0.3 100.0 0.7 11.1 87.7 0.5 100.0 339 Fourth 7.8 6.7 92.5 0.8 100.0 1.0 10.2 88.2 0.5 100.0 309 Highest 13.8 4.5 94.8 0.7 100.0 0.9 6.9 91.9 0.3 100.0 328 Total 8.5 5.5 93.7 0.8 100.0 1.6 10.3 87.1 0.9 100.0 1,591 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Low birth weight is associated with higher rates of morbidity and mortality; women in the MDHS were asked whether their baby was weighed at birth, and if so, what was the weight. A birth weight of 2,500 grams or more is considered normal, while the newborns with lower weight are considered small or underweight. Since mothers may not always know the baby’s weight at birth, they were also asked for their assessment of the size of the newborn baby—very large, larger than average, average, smaller than average, or very small. 126 | Maternal and Child Health Table 10.10 shows that less than 1 percent of infants did not have their weight recorded at birth. Ninety-four percent of infants had normal birth weight, and 6 percent were underweight. According to the mothers’ evaluations, 87 percent of children were average or larger than average, 10 percent were smaller than the average, and 2 percent were considered very small. Underweight infants are more likely to be born to mothers under age 20 years (7 percent), to those having their first birth (7 percent), to those living in the North region (9 percent), and to women with secondary education (6 percent). No significant variations in the proportion of underweight infants were seen by place of residence or wealth quintile. 10.4 POSTNATAL CARE Postnatal care obtained from a trained medical provider represents a key component of safe maternity. The postnatal examination plays an important role in assessing mother and child health status, diagnosis and treatment of postnatal complications, and counseling and support regarding early baby care. Since research has shown that most maternal and infant deaths occur within the first two days after delivery, postnatal care should be provided as soon as possible after birth, within this critical period. To evaluate the extent to which postnatal care is utilized, the 2005 MDHS asked women who had live births in the five years preceding the survey whether a health professional examined her after her last birth and about the timing of the given checkup. Figure 10.4 shows that most women benefit from a medical examination shortly after delivery. Eighty-nine percent of all women who had a live birth in the past five years received a medical checkup within two days of delivery of their last birth, and another 6 percent within the following six weeks. Only 4 percent of women reported not having had any sort of checkup in the postnatal period. The proportion of women not having a postnatal checkup is highest in the North region where 6 percent were not seen by a trained provider. Surprisingly, postnatal examinations are more frequent and are performed in a more timely manner, in rural areas than in urban areas. Total RESIDENCE Urban Rural REGION North Center South Chisinau 0 20 40 60 80 100 Percent 0-2 days after delivery 3-41 days after delivery No postnatal care Figure 10.4 Timeliness of Postnatal Examinations by a Trained Provider MDHS 2005 Maternal and Child Health | 127 Postnatal care coverage has improved significantly in Moldova since 1997, when only 74 percent of mothers reported having received a postnatal checkup (Serbanescu et al., 1998). Compared with estimates from other Demographic and Health Surveys and Reproductive Health Surveys conducted recently in Eastern Europe and Eurasia, Moldova reflects a better situation than other countries in the region with regards to postnatal care. In Romania (1999), 32 percent of mothers received postpartum care, in Ukraine (1999), 58 percent, in Azerbaijan (2001), 25 percent, and in Georgia (1999), 11 percent (CDC and ORC Macro, 2003) received a postnatal checkup. 10.5 WOMAN’S PERCEPTION OF ACCESS TO HEALTH CARE The 2005 MDHS included a series of questions aimed at assessing what women perceive as barriers to accessing health care. To collect this information, women were asked whether particular situations represented a big problem in obtaining health care. These situations included getting permission to go to a doctor; obtaining money to pay for the treatment; covering the distance to get to a medical facility; obtaining transport; and concerns with having to go alone or that there may not be a female provider available. Table 10.11 shows the percentage of women who reported having a big problem in accessing health care for themselves when they were sick, according to the type of problem. A high proportion of women cited at least one major problem that they perceive as a barrier to accessing health care (68 percent); that this includes the majority of women suggests that they frequently face obstacles in obtaining health care. Over half of women (56 percent) mentioned obtaining sufficient money to pay for health care as a big problem. The second most important problem (19 percent) was that a female medical provider may not be available to consult them. Furthermore, 16-17 percent of women identified obtaining transport and covering the distance to a health facility as a big problem. Eleven percent of women cited that it is a big problem to go alone to a medical provider, and for 7 percent it is a problem to get permission to go to a doctor. Characteristics of women who are more likely to mention having a big problem in accessing health care include those: under age 19 and over age 40; with 3 or more children; divorced, separated or widowed; living in rural areas, with secondary education only; unemployed or not receiving remuneration; and from the poorest wealth quintiles. Women in Chisinau cited a big problem in accessing health care (60 percent) less frequently than women in other regions (70-72 percent). Obtaining the necessary money is a problem that increases with the age of a woman and with the number of children. It is also a problem more frequently reported by women who are divorced, separated or widowed, who live in rural areas, who have only secondary education, who do not receive remuneration, and who are from the lowest wealth quintiles. Concerns about a female health professional not being available and a lack of desire to go alone were expressed mainly by women age 15-19 (39 and 23 percent, respectively), without children (34 and 19 percent, respectively), and never married (37 and 21 percent, respectively). Difficulties in finding transport and to cover the distance to the health facility were cited as big problems relatively more often by women age 40-49 years; with 3 and more children; divorced, separated or widowed; living in rural areas; with only secondary education; not receiving remuneration; and from the lowest wealth quintiles. Obtaining permission to seek treatment is a bigger problem for women age 15-19; never married; without children; living in rural areas; and from the poorest wealth quintile. 128 | Maternal and Child Health Table 10.11 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, Moldova 2005 Problems in accessing health care Background characteristic Getting permission to go for treatment Getting money for treatment Distance to health facility Having to take transport Not wanting to go alone Concern there may not be a female provider Any of the specified problems Number of women Age 15-19 11.1 46.2 12.5 14.0 23.4 39.2 69.6 1,417 20-29 5.5 50.8 14.4 16.2 12.4 18.9 64.8 2,088 30-39 6.7 58.8 16.4 17.4 7.0 11.8 67.0 1,778 40-49 6.2 66.6 18.3 19.5 5.6 11.2 71.0 2,156 Number of living children 0 8.5 46.7 12.6 14.1 19.4 33.5 68.1 2,456 1-2 6.1 57.4 15.1 16.5 7.5 11.6 65.3 3,918 3-4 7.2 74.3 24.1 25.0 6.4 12.8 77.5 965 5+ 7.8 82.1 31.0 33.9 4.5 4.5 82.8 101 Marital status Never married 9.2 46.5 12.2 14.0 21.1 37.0 68.7 1,862 Married or living together 6.1 58.5 16.5 17.8 7.9 12.6 66.6 4,937 Divorced/separated/ widowed 7.9 69.2 19.0 20.2 8.5 14.8 77.0 641 Residence Urban 5.7 47.6 7.4 9.2 12.4 18.4 61.3 3,194 Rural 8.1 63.1 21.8 22.9 10.3 19.2 73.0 4,246 Region North 6.5 61.4 18.8 20.9 10.3 19.8 71.6 2,207 Center 8.0 61.0 19.0 19.8 9.8 18.2 70.1 2,033 South 8.7 56.8 17.4 18.3 12.1 20.1 69.6 1,402 Chisinau 5.4 44.8 6.6 8.2 13.4 17.6 60.2 1,798 Education No education/primary (23.3) (63.0) (33.9) (34.4) (23.4) (30.7) (75.1) 49 Secondary 7.7 63.7 18.0 19.5 12.7 21.9 74.3 4,534 Secondary special 5.7 51.5 13.3 14.0 6.1 11.8 60.7 1,327 Higher 6.0 39.0 10.3 11.8 10.9 15.4 55.4 1,530 Employment Not employed 8.7 56.1 16.6 17.9 15.1 24.2 70.4 3,316 Working for cash 5.4 54.4 13.5 14.8 8.2 14.4 64.1 3,661 Not working for cash 8.7 75.9 26.1 28.5 7.4 15.9 83.2 457 Missing * * * * * * * 6 Wealth quintile Lowest 13.2 78.7 30.3 31.9 11.4 21.6 85.1 1,243 Second 7.0 68.4 21.8 24.0 9.6 19.5 75.8 1,234 Middle 5.6 55.1 16.2 17.0 10.5 19.4 66.8 1,511 Fourth 6.2 49.0 9.8 10.9 11.7 17.7 63.1 1,672 Highest 4.9 40.7 6.2 7.7 12.4 17.2 56.4 1,780 Total 7.1 56.4 15.7 17.1 11.2 18.9 68.0 7,440 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. Maternal and Child Health | 129 10.6 IMMUNIZATION COVERAGE According to World Health Organization, a child is considered fully vaccinated if he/she has received the following vaccinations: one dose of BCG, one dose of measles, and three doses each of DPT (diphtheria-pertussis-tetanus) and polio. The immunization calendar for Moldova, approved by the National Immunization Program for the years 2001 to 2005 includes all of the above-mentioned vaccines, as well as three doses of hepatitis B (HepB) vaccine and one dose of vaccination for mumps and rubella. The vaccines against measles, mumps, and rubella are now usually administered as one injection (MMR), whereas before they were administered separately. All vaccines on the calendar should be administered within the first year of life, except MMR which is administered at the age of 12 months. Taking into account this country-specific vaccination timetable, the MDHS examines full coverage of immunizations for the cohort of children age 15-26 months, thus allowing for a reasonable three-month interval for children to receive their MMR vaccine. Information on children’s vaccination coverage was obtained for all children under five years. In Moldova, child-specific information about the vaccines they received are registered in the Child’s Medical Development Card (Fiúa medicală de dezvoltare a copilului [Form 112/e]), or on an immunization card, or in a log (Forms 063/e or 063-1/e)—any of which can usually be found at the child’s family doctor in the local primary health facility. In addition, an “immunization certificate” has come into use since distribution began in 2002. It has a record of vaccinations and is kept by the child’s parent or caregiver. The MDHS collected vaccination data from both sources—from the forms kept at the local health facility and from the immunization certificate kept by the parents or caregiver—as well as from the mother’s verbal report. All mothers of children under age five were asked to show to the interviewer the immunization certificate or any other written record of the child’s vaccines. If the immunization certificate or another medical record were available, the interviewer copied the date that each vaccine was received into the questionnaire. Then, the interviewer asked the mother if the child had received any of the following vaccines: polio, DTP, BCG, measles, mumps and/or rubella, and how many doses of each vaccine were administered. After completing the household interview, when information about the local health facility’s address was noted, an interviewer visited that health facility to obtain vaccine information from that source. Information on vaccines from immunization certificates kept at home was collected for 13 percent of children, while immunization information from sources at local health facilities was collected for 86 percent of children. The combined information from the immunization certificates and records kept at the health facilities was available for 90 percent of children (in some cases both sources were available). Table 10.12 shows results of vaccination coverage for children age 15-26 months, including the vaccination coverage for each of the nine preventable childhood infections. The estimates are based on information from written sources (at the home or/and the local health facility), and in cases where written sources were not available, data were completed with information reported verbally by the mother. The upper part of Table 10.12 shows the percentages of children age 15-26 months vaccinated any time before the survey. The bottom line of the table shows the percentage children vaccinated in the first year of life. For children not having an available written source of vaccination dates, the proportion of those vaccinated before the first birthday (or before the age of 15 months for measles, mumps and rubella) was considered identical to that of children with an immunization document. 130 | Maternal and Child Health Table 10.12 Vaccinations by source of information Percentage of children age 15-26 months who received specific vaccines at any time before the survey, by source of information (vaccination card at home or at the health facility, or mother's report), and percentage vaccinated by 15 months of age (or by 24 months of age for measles, mumps and rubella), Moldova 2005 Percentage of children who received: Hepatitis B Diphtheria- pertussis-tetanus Polio MMR1 BCG B1 B2 B3 1 2 3 1 2 3 Measles Mumps Rubella Fully vacci- nated2 No vacci- nations Number of children Vaccinated at any time before survey Vaccination card 89.7 89.3 89.0 87.8 88.7 87.7 86.4 89.3 88.6 87.7 84.9 83.0 82.8 81.6 0.0 295 Mother's report 10.1 8.4 7.9 6.7 9.5 9.2 7.1 9.8 9.4 7.1 5.7 6.4 5.9 3.7 0.0 34 Either source 99.7 97.7 96.9 94.5 98.3 96.9 93.5 99.1 98.1 94.8 90.6 89.4 88.7 85.3 0.0 329 Vaccinated by 15 months of age3 99.7 97.7 96.5 92.8 96.9 95.3 89.9 98.5 96.8 92.7 89.5 88.8 87.9 81.6 0.5 329 1 Children under five years of age who received this vaccine by 24 months of age 2 Including one dose of BCG, three doses of HepB, three doses of DPT, three doses of polio, and one dose of measles, mumps and rubella. 3 For children whose information was based on the mother's report, the percentage of vaccinations given during the first 14 months of life (or during the first 23 months of life for measles, mumps and rubella) was assumed to be the same as for children with a written record of vaccination. Overall, 85 percent of children age 15-26 months are fully immunized with the 9 antigens stipulated by the National Immunization Program. No children were identified as not having received any vaccine. The highest rate of specific immunization coverage (over 99 percent) was identified for the BCG vaccine. More than 98 percent of children were vaccinated with the first doses of HepB, DTP, and polio, confirming the high access of children to immunization services in the Moldova. The coverage with subsequent doses is slightly less, however, with 95 percent of children receiving the three recommended doses of HepB and polio and 94 percent receiving the three recommended doses of DTP vaccine. The decrease in coverage with subsequent doses reflects immunization drop out rates. Drop out rates represent the proportion of children who received the first dose of vaccine but who do not follow through with receiving the third dose. The drop out rates are 5 percent for DTP, 4 percent for polio and 3 percent for HepB. The proportion of children vaccinated against measles is 91 percent and the proportion of those vaccinated against mumps and rubella is 89 percent (Figure 10.5). Timely and complete immunization coverage of children in the first year of life is important to provide protection before they might become exposed to diseases. Overall, 76 percent of children were immunized against the nine infections in the first year of life (or before age 15 months for measles, mumps, and rubella). While the data on the timely coverage for BCG, MMR, and the first doses of HepB, polio and DTP do not vary significantly from rates of vaccination at any time before the survey, complete coverage including the third doses of HepB, polio, and DTP within the first year of life is less: 91 percent versus 95 percent for HepB, 89 percent versus 95 percent for polio, and 87 percent versus 94 percent for the DTP vaccines. Maternal and Child Health | 131 Comparing results on the immunization coverage from the 2000 Multiple Indicator Cluster Survey (MICS 2000), excluding Transnistria, similar coverage rates are observed for the same age group (age 15-26 months) vaccinated any time before the survey. Moreover, there has been a significant effort to increase the prevalence of fully immunized children before their first birthday, including all antigens stipulated by the National Immunization Program. It is also notable that since 2000, there has been a reduction to under 1 percent of children who have not received any of the recommended vaccines, as well as the successful implementation of immunization against rubella (Figure 10.6). 98 99 98100 97 98 97 91 89 89 85 0 94 95 95 BCG DPT Polio HepB Measles Mumps Rubella Fully immunized No vaccine 0 20 40 60 80 100 Dose 1 Dose 2 Dose 3 Figure 10.5 Percentage of Children Age 15-26 Months Vaccinated Against Childhood Diseases at Any Time Preceding the Survey MDHS 2005 Percent 5 56 0 62 82 88 94 87 93 89 93 93 1 76 81 82 83 89 98 87 96 91 97 99 No vaccines Fully vaccinated Rubella Mumps Measles Polio 3 Polio 1 DTP 3 DTP 1 HepB 3 HepB1 BCG 0 20 40 60 80 100 MICS 2000 MDHS 2005 Figure 10.6 Proportion of Children Age 15-26 Months Who Have Received Recommended Vaccines Before Their First Birthday MDHS 2005 132 | Maternal and Child Health Table 10.13 presents results of children’s vaccination coverage by background characteristics. These data show no significant differences in immunization coverage according to sex, birth order and mothers’ education. However, the proportion of fully immunized children decreases below 80 percent for children in urban areas, in particular in Chisinau, and those from the fourth wealth quintile. Table 10.13 Vaccinations by background characteristics Percentage of children age 15-26 months who received specific vaccines at any time before the survey (according to a vaccination card at home or at a health facility, or the mother’s report), and percentage with a vaccination card, by background characteristics, Moldova 2005 Percentage of children who received: Hepatitis B Diphtheria-pertussis- tetanus Polio MMR1 Background characteristic BCG B1 B2 B3 1 2 3 1 2 3 Measles Mumps Rubella Fully vacci- nated2 Percent- age with a vacci- nation card at home or health facility Number of children Sex Male 100.0 97.8 96.7 93.9 99.4 98.5 96.0 99.4 99.1 96.3 90.8 90.9 89.4 85.9 89.8 159 Female 99.5 97.7 97.0 95.1 97.3 95.4 91.2 98.9 97.1 93.4 90.3 88.0 88.0 84.8 89.5 170 Birth order 1 99.4 96.3 95.2 93.7 96.9 96.0 93.7 98.8 98.0 95.4 91.2 89.9 89.4 85.6 86.7 152 2-3 100.0 98.9 98.1 94.9 99.3 97.2 92.7 99.3 97.8 93.8 91.2 90.2 89.2 86.2 90.9 152 4+ * * * * * * * * * * * * * * * 24 Residence Urban 100.0 100.0 97.8 92.9 98.6 95.0 90.7 99.2 97.4 93.3 88.1 85.9 85.2 79.7 90.4 128 Rural 99.6 96.3 96.3 95.6 98.1 98.1 95.3 99.1 98.5 95.8 92.1 91.6 90.9 88.9 89.2 201 Region North 100.0 94.7 94.7 92.5 97.7 96.8 93.1 97.7 97.3 94.0 91.5 91.5 91.5 86.4 85.3 102 Center 99.2 98.0 96.9 96.9 98.0 97.4 94.5 100.0 98.2 95.4 90.9 88.5 88.5 87.0 93.1 104 South 100.0 100.0 98.6 97.6 100.0 100.0 96.6 100.0 100.0 95.2 94.7 94.7 94.7 89.9 91.5 54 Chisinau 100.0 100.0 98.7 91.6 98.1 93.8 90.1 99.2 97.5 94.8 85.4 83.4 80.1 77.6 89.5 69 Education No education/ primary * * * * * * * * * * * * * * * 3 Secondary 99.6 97.0 96.5 94.6 98.2 96.9 94.1 98.6 97.5 95.0 90.2 88.5 88.1 85.4 92.8 210 Secondary special (100.0) (100.0) (100.0) (97.1) (100.0) (100.0) (94.3) (100.0) (100.0) (94.3) (91.7) (91.7) (91.7) (87.7) (84.9) 51 Higher 100.0 98.2 95.7 92.2 97.0 94.4 90.7 100.0 98.2 94.4 91.4 91.0 88.8 83.8 83.7 66 Wealth quintile Lowest (100.0) (97.2) (97.2) (97.2) (100.0) (100.0) (93.3) (100.0) (100.0) (94.7) (90.8) (88.6) (88.6) (85.8) (94.7) 62 Second 100.0 97.4 96.7 95.9 96.7 95.3 93.9 96.7 96.0 94.6 93.5 90.1 90.1 87.3 89.6 70 Middle 100.0 97.2 96.3 95.2 100.0 99.0 97.0 100.0 99.0 97.0 96.3 96.3 96.3 92.3 86.0 67 Fourth 100.0 98.2 95.7 87.1 97.4 94.3 89.8 99.2 95.6 89.3 81.0 82.1 79.8 75.3 85.8 66 Highest 98.6 98.6 98.6 97.5 97.4 96.1 93.6 100.0 100.0 98.6 91.0 89.8 88.5 85.9 92.6 64 Total 99.7 97.7 96.9 94.5 98.3 96.9 93.5 99.1 98.1 94.8 90.6 89.4 88.7 85.3 89.7 329 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Children under five years of age who received this vaccine by 24 months of age 2 Including one dose of BCG, three doses of HepB, three doses of DPT, three doses of polio, and one dose of measles, mumps and rubella. Maternal and Child Health | 133 The highest rates of vaccine interruption with DTP (5-8 percent) are registered for girls, children in urban areas, in Chisinau and the North region, and children of mothers with higher education, and those in the first and fourth wealth quintiles. This emphasizes a weak link in providing sustained services to these population categories. Table 10.14 presents vaccination coverage results for children from age one to five years, by one- year age groups (12-23 months, 24-35 months, 36-47 months, and 48-59 months). The results show vaccine-specific coverage in the first year of life, except for vaccines against measles, rubella, and mumps for which coverage is estimated in the first 15 months of life. Estimates in the table do not show significant variations in immunization coverage among age groups. The low immunization coverage for rubella, at 52 percent among children age 48-59 months, is due to the fact that not all children in this age group had the chance to be vaccinated because the rubella immunization was only implemented since January 2002. Table 10.14 Vaccinations in first 15 months of life Percentage of children under five years of age at the time of the survey who received specific vaccines by 15 months of age (or by 24 months for measles, mumps and rubella), and percentage with a vaccination card, by current age of child, Moldova 2005 Percentage of children who received: Hepatitis B Diphtheria- pertussis-tetanus Polio MMR1 Current age of child in months BCG B1 B2 B3 1 2 3 1 2 3 Measles Mumps Rubella Fully vacci- nated2 No vacci- nations Percent- age with a vaccina- tion card at home or health facility Number of children 12-23 99.8 97.9 96.3 92.8 98.0 95.6 89.9 99.1 97.3 93.2 84.7 83.6 82.7 77.9 0.0 89.6 355 24-35 98.8 97.9 96.5 93.3 96.8 95.5 91.8 97.5 96.5 92.0 92.3 89.1 88.7 81.7 1.2 93.1 328 36-47 99.0 96.9 95.8 90.7 97.0 95.3 90.3 97.3 96.9 92.2 93.6 92.3 91.3 83.2 0.8 94.2 299 48-59 98.9 96.4 95.6 93.2 96.4 95.4 88.7 97.4 96.4 92.3 90.8 90.2 60.4 51.9 0.5 90.2 273 Total 99.1 97.3 96.1 92.5 97.1 95.4 90.2 97.9 96.8 92.4 90.1 88.5 81.4 74.3 0.6 91.7 1,255 Note: Information was obtained from the vaccination card at home or at the health facility, or if there was no written record, then from the mother’s report. For children whose information was based on the mother's report, the percentage of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccinations. 1 Children under five years of age who received this vaccine by 24 months of age 2 Including one dose of BCG, three doses of HepB, three doses of DPT, three doses of polio, and one dose of measles, mumps and rubella. 10.7 ACUTE RESPIRATORY INFECTIONS AND FEVER Acute respiratory infections (ARI) and fever constitute the major reasons mothers with children under five seek a doctor’s advice. ARI in Moldova ranks third among the causes of death among children under five (preceded by perinatal causes and congenital malformations). However, ARI ranks first in deaths in the home. Emergency and adequate health care provided to children with ARI symptoms and fever is, therefore, crucial for improving well-being of children and reduced deaths among children under age five. Fever is a characteristic symptom of malaria in malaria endemic areas. However, because Moldova is not in a malaria endemic region, fever is regarded as a sign of childhood infection other than malaria. To obtain information about ARI and fever frequency, mothers were asked (for each child under five years) whether in the two weeks preceding the survey the child coughed and had difficulty breathing (short or frequent breaths), and whether the child had a fever. 134 | Maternal and Child Health Table 10.15 shows that 7 percent of children under age 5 years exhibited signs of ARI in the two weeks preceding the survey. Results show that the most frequent cases of ARI are observed in the age group 6-11 months (9 percent), 36-47 months (9 percent), and 12-23 months (8 percent). In urban areas, the prevalence of ARI symptoms in children is considerably higher and accounts for 9 percent of children under age five versus 6 percent in rural areas. ARI prevalence is highest in Chisinau (11 percent) and lowest in the South region (4 percent). It is notable that there is the significantly higher prevalence of ARI among children of women with higher education (9 percent) and women in the highest wealth quintile (10 percent). Table 10.15 Prevalence and treatment of symptoms of ARI and fever Percentage of children under five years who had a cough accompanied by short, rapid breathing (symptoms of ARI) and percentage of children who had fever in the two weeks preceding the survey, and percentage of children with symptoms of ARI and/or fever for whom treatment was sought from a health facility or provider, by background characteristics, Moldova 2005 Prevalence of ARI and fever in past two weeks: Among children with symptoms of ARI and/or fever Background characteristic Percentage of children with symptoms of ARI Percentage of children with fever Number of children Percentage who sought treatment from a health facility/ provider1 Number of children Child’s age in months <6 0.8 6.0 157 * 9 6-11 9.4 14.9 159 (57.5) 30 12-23 8.3 17.1 355 64.5 74 24-35 6.4 19.5 328 48.0 66 36-47 9.1 15.8 299 62.8 55 48-59 6.0 14.2 273 (31.8) 45 Sex Male 6.8 13.5 810 54.7 129 Female 7.3 17.6 761 54.2 151 Residence Urban 9.3 19.7 604 60.2 139 Rural 5.6 12.9 966 48.7 140 Region North 6.6 14.3 468 53.9 80 Center 6.4 12.5 458 52.9 64 South 4.1 12.6 311 (39.0) 42 Chisinau 11.1 24.1 333 62.9 94 Mothers education No education/primary * * 19 * 6 Secondary 6.6 12.5 1,015 46.2 152 Secondary special 5.7 17.5 229 (64.5) 43 Higher 9.4 23.0 307 63.9 77 Wealth quintile Lowest 5.1 10.7 307 (31.0) 37 Second 5.9 10.3 298 (41.2) 37 Middle 7.0 16.3 336 59.6 62 Fourth 6.6 17.5 306 54.8 59 Highest 10.3 22.1 324 66.7 83 Total 7.0 15.5 1,571 54.4 279 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. ARI = Acute Respiratory Infection na = Not applicable 1 Excludes pharmacy, shop and treatment from a non-professional provider Maternal and Child Health | 135 Table 10.15 also shows that 16 percent of children had a fever in the 2 weeks preceding the survey. A fever was more likely to occur among children older than 6 months, but otherwise without substantial variations by age groups. Unlike ARI, a fever was more frequently present in girls (18 percent) than boys (14 percent). However, similar to ARI, fever was more frequently reported in urban areas (20 percent) than rural areas (13 percent). The highest prevalence of children with fever is observed in Chisinau (24 percent) versus 13-14 percent in other regions. Fever prevalence was also higher among children of women with higher education and from the wealthiest quintiles. Overall, 54 percent of mothers sought care at a health facility for their children with ARI symptoms and/or fever. Because of the limited number of ARI and/or fever cases, comparisons between children’s age groups is not reliable. There is no significant difference between girls and boys for care being sought, but care was more often sought in urban settings (60 percent) than rural settings (49 percent), espe- cially in Chisinau (63 percent), among children of women with higher education (64 percent), and among those in the highest wealth quintile (67 percent). Regarding the unexpected pattern of the prevalence of ARI symptoms and fever, as well as the levels of care— higher among urban children, among children whose mothers have higher education, and among those in the wealthiest quintiles—the pattern may simply mirror greater maternal concern in these categories, rather than higher morbidity rates. 10.8 DIARRHEA Diarrhea is an important cause of morbidity in chil- dren under five years. Treatment of diarrhea includes mothers who seek care for their children from a health professional, as well as rehydration therapies initiated at home. Table 10.16 shows that 7 percent of children under age five had diarrhea in the 2 weeks preceding the survey. A considerably higher prevalence is seen in children 6-11 months and 12-23 months (13 and 11 percent, respectively). Girls were more likely to have diarrhea (9 percent) than boys (6 percent). It is somewhat surprising to find that children in urban areas (12 percent), including Chisinau (11 percent), children of mothers with higher education (11 percent), children in the fourth and fifth wealth quintile (9 and 12 per- cent, respectively), and children living in the households that use piped water as the main source of potable water (11 per- cent) are more likely than children in other categories to have diarrhea. This may again reflect a higher level of concern by mothers of children in these categories. Table 10.16 Prevalence of diarrhea Percentage of children under five years with diarrhea in the two weeks preceding the survey, by background characteristics, Moldova 2005 Background characteristic Diarrhea in the two weeks preceding the survey Number of children Child’s age in months <6 8.1 157 6-11 13.0 159 12-23 11.2 355 24-35 6.5 328 36-47 4.1 299 48-59 3.8 273 Sex Male 5.8 810 Female 9.2 761 Residence Urban 11.6 604 Rural 4.8 966 Region North 8.1 468 Center 4.9 458 South 5.9 311 Chisinau 11.4 333 Mother's education No education/primary * 19 Secondary 6.2 1,015 Secondary special 6.4 229 Higher 10.5 307 Source of drinking water Piped 10.6 553 Protected well 5.0 861 Open well * 20 Other/missing 9.6 137 Wealth quintile Lowest 7.4 307 Second 2.2 298 Middle 6.3 336 Fourth 9.4 306 Highest 11.7 324 Total 7.4 1,571 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 136 | Maternal and Child Health On the other hand, diarrhea is less likely to occur among children older than 36 months (4 percent), in rural areas (5 percent), and particularly in the Center and South regions (5 and 6 percent, respectively), living in households using protected wells as the main source of drinking water (5 percent), and in the second wealth quintile (2 percent). Oral administration of solutions prepared from oral rehydration salts (ORS) in the case of diarrhea represents a simple and effective method to treat diarrhea in young children. In Moldova, mothers are encouraged to use commercially packaged ORS, distributed under the label “Rehidron.” To prevent undernutrition in cases of diarrheal disease, increased feeding is also recommended. Table 10.17 shows information regarding the proportion of mothers that know about ORS. Overall, 61 percent of mothers know about ORS. The level of awareness generally increases with the mother’s age, her education level, and the wealth quintile of the household. There are significant differences in knowledge between mothers from rural areas (55 percent) and those from urban areas (70 percent). Geographically, the highest level of knowledge is noted among mothers in Chisinau (76 percent), and the lowest level among mothers from the South region (53 percent). Lower levels of awareness about ORS are noted in younger mothers age 15-19 (42 percent), as well as among mothers in the poorest wealth quintile (45 percent), and mothers with secondary education (52 percent). Table 10.17 Knowledge of ORS packets Percentage of mothers with births in the five years preceding the survey who know about ORS packets for treatment of diarrhea, by background characteristics, Moldova 2005 Background characteristic Percentage of mothers who know about ORS packets Number of mothers Age 15-19 42.4 68 20-24 51.3 423 25-29 64.8 473 30-34 70.5 283 35-49 65.6 140 Residence Urban 70.0 566 Rural 54.5 821 Region North 57.6 424 Center 57.1 386 South 53.3 264 Chisinau 76.1 313 Education No education/primary * 16 Secondary 51.9 880 Secondary special 73.4 209 Higher 80.0 283 Wealth quintile Lowest 45.0 246 Second 51.0 260 Middle 55.2 290 Fourth 70.6 283 Highest 78.2 308 Total 60.8 1,387 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. ORS = Oral rehydration salts Maternal and Child Health | 137 Table 10.18 shows information about the quantity of liquids and food received by children with diarrhea, as reported by the mother. In most cases, mothers offer a larger quantity of liquids (43 percent) or the same quantity as usual (39 percent) to their child with diarrhea. Only 7 percent of mothers reported offering less liquid than usual to their child with diarrhea, and 5 percent gave much less liquid than usual. Feeding practices in the case of diarrhea vary greatly from those of liquid administration (Figure 10.7). Fifty percent of mothers offer the usual amount of food to a child with diarrhea and only five percent offer a larger amount than usual. Furthermore, 27 percent of children with diarrhea were offered a slightly smaller amount of food than usual, and 10 percent were offered much less than usual. Offer- ing less food could lead to acute malnutrition, consequently worsen- ing the child’s condition. These results indicate the need to strengthen mothers’ knowledge in managing common childhood illnesses. Table 10.18 Feeding practices during diarrhea Percent distribution of children under five years who had diarrhea in the two weeks preceding the survey, by amount of liquids and food offered compared with normal practice, Moldova 2005 Feeding practice Percent Amount of liquids offered Same as usual 38.6 More 43.0 Somewhat less 7.4 Much less 5.2 None 1.2 Don't know/missing 4.5 Total 100.0 Amount of food offered Same as usual 50.0 More 5.4 Somewhat less 27.1 Much less 10.4 None 4.4 Never gave food 0.7 Don't know/missing 2.2 Total 100.0 Number of children 117 39 43 7 5 6 50 5 27 10 7 Usual amount More than usual Somewhat less than usual Much less than usual Other 0 10 20 30 40 50 60 Percent Quantity of liquid Quantity of food Figure 10.7 Amount of Food and Liquid Offered to Children Under Five with Diarrhea MDHS 2005 Nutrition | 139 NUTRITION 11 Nutrition is a critical component in laying a solid foundation for good health and development. Good nutrition builds up the immune system, strengthens the body, and plays an essential role in a healthy and productive lifestyle. This chapter looks at several aspects of the nutritional status of children and women in Moldova. It covers the following topics: infant feeding practices, including breastfeeding and complementary feeding patterns and the prevalence of bottle-feeding; iodization of salt used in the household; children’s levels of consumption of foods rich in vitamin A; micronutrient intake among mothers; prevalence of anemia in women and children; and the nutritional status of women and children under age five based on anthropometric data (height and weight) collected during the survey. 11.1 BREASTFEEDING AND SUPPLEMENTATION Early feeding practices play a pivotal, if not vital, role in the physical development of infants. Optimal infant feeding is defined by WHO and UNICEF as follows (UNICEF, 1990): • Initiation of breastfeeding within the first hour of birth; • Exclusive breastfeeding for the first six months, that is, the infant receives breast milk only, without additional food or drink (not even plain water); • Breastfeeding day and night on demand, and increased breastfeeding during illness and recovery; and • Complementary feeding with adequate and safe foods starting at six months, with continued breastfeeding up to two years of age or beyond. Initiation of Breastfeeding The early initiation of breastfeeding is important for a number of reasons. First, it takes advantage of the newborn’s suckling reflex and alertness immediately after birth. Early suckling also benefits mothers because it stimulates breast milk production and releases a hormone that helps the uterus to contract and reduce postpartum blood loss. The first breast milk contains colostrum, which is highly nutritious and has antibodies that protect the newborn from diseases. Early breastfeeding also fosters mother and child bonding and enhances the socialization experience of an infant. Table 11.1 shows that 97 percent of children born in the five years preceding the survey were breastfed. There is little variation between background characteristics. Overall, among children who were ever breastfed, most were taken to the breast within the first day of life (91 percent). Two-thirds of breastfed infants were breastfed within one hour of birth, but this percentage is substantially lower for infants in Chisinau (57 percent) and for those whose mothers come from households in the highest wealth quintile (53 percent). Prelacteal feeding is the practice of giving other liquids to an infant during the period after birth before the mother’s milk is flowing freely. Overall, 8 percent of breastfed children were given a prelacteal feed. Not surprisingly, infants in Chisinau and from wealthy households who were least likely to begin breastfeeding in the first hour were most likely to have a prelacteal feed. 140 | Nutrition Table 11.1 Initial breastfeeding Percentage of children born in the five years preceding the survey who were ever breastfed, and among children ever breastfed, percentage who started breastfeeding within one hour and within one day of birth and percentage who received a prelacteal feed, by background characteristics, Moldova 2005 Among children ever breastfed, percentage who started breastfeeding: Background characteristic Percentage ever breastfed Number of children Within 1 hour of birth Within 1 day of birth1 Percentage who received a prelacteal feed2 Number of children ever breastfed Child’s sex Male 96.1 819 61.5 91.5 7.0 787 Female 96.9 772 67.6 90.2 8.8 748 Residence Urban 95.6 611 61.7 88.0 11.9 584 Rural 97.1 980 66.2 92.6 5.4 952 Region North 95.6 473 62.2 88.3 9.1 452 Center 97.0 464 68.1 95.3 3.1 450 South 97.5 317 70.3 91.3 6.9 309 Chisinau 96.2 337 57.1 87.6 13.7 324 Mother's education No education/primary * 16 * * * 16 Secondary 95.5 1,033 64.1 90.7 6.7 987 Secondary special 98.4 229 69.9 92.8 7.1 225 Higher 98.4 310 61.3 89.3 12.5 305 Wealth quintile Lowest 96.4 311 65.2 91.9 4.0 300 Second 95.0 304 67.0 91.4 7.4 289 Middle 99.2 339 67.3 94.0 4.4 336 Fourth 95.6 309 70.6 90.1 9.6 295 Highest 96.1 328 52.7 86.6 14.1 315 Total 96.5 1,591 64.5 90.8 7.9 1,536 Note: Table is based on all births whether the children are living or dead at the time of interview. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes children who started breastfeeding within one hour of birth. 2 Children given something other than breast milk during the first three days of life before the mother started breastfeeding regularly. Breastfeeding Patterns Exclusive breastfeeding, defined as breast milk as the only source of infant food or liquid, meets nutritional requirements (Cohen et al., 1994) and protects against illness (Huffman and Combest, 1990) for about the first six months of life. Children who received only breast milk in the 24 hours before the survey are defined as being exclusively breastfed, and children who are fully breastfed received only plain water in addition to breast milk. Exclusive breastfeeding is recommended for the first six months after birth because breast milk is uncontaminated and contains all the nutrients necessary for children in the first few months of life. In addition, the mother’s antibodies in breast milk provide immunity to disease. Early supplementation is discouraged for several reasons. First, it exposes infants to pathogens and Nutrition | 141 increases their risk of infection, especially diarrheal disease. Second, it decreases infants’ intake of breast milk and therefore suckling, which reduces breast milk production. Third, supplementary food is often nutritionally inferior to mother’s milk. Table 11.2 shows the breastfeeding practices of mothers of children under three years of age. Eighty-five percent of children 0-6 months in Moldova are breastfed, as are 77 percent of children 6-9 months. These are larger percentages compared to those estimated in 1996-2000 by UNICEF and MOH (2002), thus suggesting recent improvements in breastfeeding habits. The duration of breastfeeding, however, is not long; already at 12-15 months, well over half of children (59 percent) covered in the MDHS are not being breastfed. By 20-23 months, almost all children have been weaned. Table 11.2 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, Moldova 2005 Breastfeeding and consuming: Age in months Not breast- feeding Exclusively breastfed Plain water only Water- based liquids/ juice Other milk Comple- mentary foods Other liquid/ food Total Number of children Percentage using a bottle with a nipple1 Number of children <4 11.8 57.2 6.1 2.9 3.9 5.3 12.8 100.0 101 29.3 101 4-7 19.6 20.1 2.4 2.7 2.5 21.3 31.4 100.0 97 47.1 100 8-11 27.8 1.5 0.5 0.9 0.0 15.4 53.9 100.0 113 47.4 115 12-15 59.2 0.0 0.0 0.0 0.0 11.3 29.5 100.0 132 45.8 134 16-19 81.3 1.7 0.0 0.0 0.0 2.8 14.1 100.0 113 36.1 116 20-23 97.6 0.0 0.0 0.0 0.0 1.4 1.0 100.0 94 17.4 105 24-27 97.3 0.0 0.0 0.0 0.0 2.1 0.7 100.0 96 8.7 106 28-31 97.0 0.0 0.0 0.0 0.0 1.4 1.7 100.0 106 4.7 115 32-35 100.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 88 11.2 107 <6 14.6 45.5 4.9 2.5 4.0 9.7 18.8 100.0 157 35.4 157 6-9 22.5 7.1 0.8 2.7 0.0 17.8 49.1 100.0 104 50.1 108 Note: Breastfeeding status refers to a "24-hour" period (the day and night) preceding the interview. Children classified as breastfeeding and consuming plain water only consume no supplements. The categories of not breastfeeding, exclusively breastfed, breastfeeding and consuming plain water, water-based liquids/juice, other milk, and complementary foods (solids and semi-solids) are hierarchical and mutually exclusive, and their percentages add to 100 percent. Thus children who receive breast milk and 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 Exclusive breastfeeding is less common than day feeding, and supplementary feeding begins early. Only 57 percent of children less than 4 months are exclusively breastfed, as are 46 percent under six months. The remainder of breastfed children also consume plain water, water-based liquids or juice, other milk in addition to breast milk, and complementary foods. By age 6-9 months, at least 18 percent of children are receiving complementary foods in addition to breast milk and other liquids. It should be noted that the percentage of children receiving complementary foods is probably higher than 18 percent, given that 49 percent of children consume “other liquids and foods,” for which details are not known but which are understood to include commercially produced infant formula and fortified baby foods. Bottle feeding is fairly widespread in Moldova; almost one-third (29 percent) of infants under 4 months old are fed with a bottle with a nipple. This proportion climbs to 47 percent for children age 4-11 months before beginning to drop off. 142 | Nutrition UNICEF and the Moldova Ministry of Health (2002) reported on the status of nutrition from 1996-2000. These results revealed that almost all children under age 5 in Moldova were breastfed at birth, 60 percent were breastfed until 6 months, and 40 percent breastfed up until their first birthday. The report also found that exclusive breastfeeding was rare and that the majority of children received complementary foods between age 3-6 months. These indicators for 2005 are shown in the MDHS results, however, they are not entirely comparable because of the difference in age reporting. Although the MDHS collected information from mothers on breastfeeding status and feeding patterns (including what other liquids or solids, if any, are given) of all children under the age of five in the 24-hour period before the survey, the relevant tables are restricted to children born in the three years prior to the survey (whereas the UNICEF/MOH data are for children under five). This three-year period provides breastfeeding estimates for a more recent cohort of children and, since most children are weaned by age three, the period is sufficiently long to identify patterns associated with the transition to solid foods. Supplemental Foods Given that babies need nutritious food in addition to breast milk from the age of six months, it is recommended that they begin receiving complementary foods at this age. The MDHS collected data on breastfeeding and nonbreastfeeding children. Table 11.3 presents information on types of complementary (weaning) foods received by children less than three years of age in the day and night preceding the survey. As observed here, 13 percent of breastfeeding children under six months also receive commercially produced infant formula. Table 11.3 Foods consumed by children in the day and night preceding the interview Percentage of youngest children under three years of age living with the mother who consumed specific foods in the day and night preceding the interview, by breastfeeding status and age, Moldova 2005 Solid or semi-solid foods Liquids Age in months Infant formula Other milk1 Other liquids2 Forti- fied baby foods Milk-based proteins such as cheese/ other non- liquid milk products Food made from grains3 Fruits and vege- tables rich in vitamin A4 Other fruits/ vege- tables Food made from roots/ tubers Food made from legumes and nuts Meat/ fish/ shell- fish/ poultry/ eggs Any solid or semi- solid food Food made with oil/fat/ butter Sugary foods Number of children BREASTFEEDING CHILDREN <4 7.6 6.6 14.1 10.1 0.0 0.0 0.0 0.0 1.5 0.0 0.0 13.3 0.0 1.8 89 4-7 25.6 23.9 40.2 40.5 13.4 27.0 20.3 11.0 31.9 1.6 13.5 58.7 13.1 22.9 78 8-11 30.8 45.3 86.6 78.4 70.4 79.4 82.6 54.7 84.7 13.6 68.8 95.9 59.3 67.8 82 12-35 25.6 56.0 86.5 68.9 61.8 90.2 91.2 79.2 92.4 22.2 80.4 97.7 75.0 79.7 83 <6 13.3 9.2 19.8 17.4 1.0 5.3 5.2 2.2 6.8 0.0 1.0 25.6 2.4 5.3 134 6-9 28.8 38.6 73.9 67.7 51.1 63.6 59.7 41.4 71.4 8.0 51.8 84.8 42.8 53.5 81 NONBREASTFEEDING CHILDREN 12-15 41.9 78.9 91.0 85.9 82.5 96.8 86.0 76.8 88.9 31.6 82.1 99.3 69.8 84.1 78 16-19 31.2 70.2 90.1 75.8 79.5 88.5 91.9 73.9 91.7 23.9 81.1 98.4 75.5 85.5 92 20-23 23.7 68.4 87.0 73.6 70.2 94.0 93.1 78.1 84.2 21.3 86.6 96.7 86.3 82.1 91 24-35 16.7 59.5 90.3 70.9 67.9 91.9 90.5 75.5 84.2 24.2 84.8 96.7 78.6 82.9 285 Note: Breastfeeding status and food consumed refer to a "24-hour" period (the day and night) preceding the survey. 1 Other milk includes fresh, tinned and powdered milk, and liquid yoghurt 2 Does not include plain water 3 Includes bread, rice, noodles, biscuits, hrishka, mamaliga; does not include fortified baby foods 4 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 Nutrition | 143 Twenty-six percent of breastfeeding children under 6 months receive solid or semisolid foods, with the most commonly consumed complementary foods being fortified baby foods (17 percent). At 4-7 months, more than half of breastfeeding children are weaned. Their diet consists mostly of fortified baby food (41 percent), but also foods made from roots and tubers (32 percent) and grains (27 percent); one- fifth receive fruits and vegetables rich in vitamin A. After age 8-11 months, children start receiving less fortified baby foods and milk-based products, and more of a variety of foods from other sources. For example, by age 12-35 months, protein-rich foods (meat, fish, poultry, and eggs) figure prominently in their diet (80 percent). 11.2 IODINE INTAKE AND VITAMIN A CONSUMPTION Disorders caused by dietary iodine deficiency constitute a major global nutritional concern. A lack of sufficient iodine in the diet may result in health disorders such as goiter, hypothyroidism and diminished mental function. Iodine deficiency in the fetus can lead to increased risks of miscarriages, stillbirths, congenital anomalies, cretinism, and psychomotor defects. Iodine deficiency can be avoided by using salt that has been fortified with iodine.1 As part of the MDHS, cooking salt in households was tested with a solution that detects potassium iodate, using relatively simple test kits furnished by MBI Kits International. Data presented in Table 11.4 show the results of household salt samples that were tested in 97 percent of households. Overall, 60 percent of Moldovan households consume adequately iodized salt (15+ ppm), and households in urban areas are much more likely to consume adequately iodized salt than in rural areas (77 percent and 49 percent, respectively). The level of iodization is greatest in Chisinau, where 84 percent of households use iodized salt in their diet, and least in the South region where only 44 percent of households consume iodized salt. National coverage has improved since 2000 when only 33 percent of households in Moldova, including Transnistria, consumed adequately iodized salt (MICS 2000). Table 11.4 Iodization of household salt Percent distribution of households with salt tested for iodine content by level of iodine in salt (parts per million), percentage of households tested, and percentage of households with no salt, according to background characteristics, Moldova 2005 Level of iodine in salt (ppm) among households tested: Background characteristic 0 ppm Inadequate (<15 ppm) Adequate (15+ ppm) Total Number of households tested Percentage of households tested Number of households Residence Urban 21.6 1.4 77.0 100.0 4,288 96.5 4,444 Rural 50.5 1.0 48.5 100.0 6,481 97.4 6,651 Region North 45.4 0.9 53.7 100.0 3,524 97.5 3,614 Center 41.0 0.9 58.1 100.0 2,910 97.5 2,985 South 54.9 1.3 43.8 100.0 1,951 96.3 2,026 Chisinau 14.2 1.6 84.2 100.0 2,385 96.6 2,469 Wealth quintile Lowest 62.3 0.9 36.8 100.0 2,258 96.5 2,339 Second 52.0 0.7 47.2 100.0 2,313 97.4 2,374 Middle 41.1 0.8 58.1 100.0 1,946 97.7 1,993 Fourth 24.0 1.8 74.2 100.0 2,154 97.5 2,209 Highest 13.2 1.5 85.3 100.0 2,097 96.2 2,180 Total 39.0 1.1 59.8 100.0 10,769 97.1 11,095 ppm = Parts per million 1 See UNICEF and MOH (2002) for a detailed description of policy and program interventions, such as universal iodization of salt, which the Moldova Ministry of Health is implementing to eradicate iodine deficiency. 144 | Nutrition Several detailed questions were asked about the use of salt in the household, including knowledge about whether the salt used for daily preparation of food was iodized or not. Households in both urban and rural areas reported higher levels of iodized salt use than actual observed: 84 percent of urban households reported using iodized salt versus 77 percent that actually tested positive for adequately iodized salt; and 63 percent of rural households reported using it versus 49 percent that tested positive (Figure 11.1). Similarly, fewer households reported not using iodized salt in food preparation than the actual observed prevalence of salt with 0 ppm: 16 percent of urban households reported that they did not use iodized salt (or did not know if they did or not) versus 22 percent where salt tested negative for iodate; 37 percent of rural households reported not using it (or did not know if they did or not) versus 51 percent that tested negative. Regardless of whether households use iodized salt in daily preparation of food, the majority of households in both urban and rural areas report not using it for pickling their foods (Figure 11.2). Figure 11.1 Type of Salt Used in Daily Food Preparation, Reported Versus Observed Use 84 77 16 22 63 49 37 51 71 60 29 39 Iodized (reported) Iodized (observed) Not iodized/ Don't know (reported) Not iodized/ Don't know (observed) 0 20 40 60 80 100 Percent Urban Rural Total MDHS 2005 Nutrition | 145 Most households purchase salt in quantities of 1 kg or less (63 percent total, 79 percent in urban areas and 53 percent in rural areas) or 2 kg (17 percent total, 14 percent in urban areas, and 20 percent in rural areas) (data not shown). The remaining 19 percent purchase salt in larger quantities. The type of packaging of salt does not differ significantly between urban and rural residence: 46 percent of salt is purchased in a sack and 21 percent in a box. Only 1 percent of purchases reported purchased in a package with no label. Most households purchase salt at the store (88 percent total) or market (11 percent), and this does not vary substantially between urban or rural residence (data not shown). In areas where foods rich in vitamin A are not consumed regularly, deficiencies that pose serious health problems for young children can result. Children affected by vitamin A deficiency suffer increased risk of death, blindness, and illness such as measles and diarrhea. The UN Special Session on Children in 2002 set as one of its goals the elimination of vitamin A deficiency and its consequences by 2010. The WHO recommends vitamin A supplementation starting at 9 months of age in areas where infants and children are prone to deficiencies (WHO, 2003). In order to identify children who are potentially at risk of vitamin A deficiency, the MDHS collected information on the consumption of fruits and vegetables rich in vitamin A by infants and children under three years. Table 11.5 shows the distribution of children under age three and their consumption of vitamin A foods and access to iodized salt. MDHS results reveal that most young children in Moldova have a diet in which fruits and vegetables rich in vitamin A are consumed regularly. However, it should be kept in mind that data collection took place in the summer, the season when these foods are more likely to be widely available. Table 11.5 shows that seventy-three percent of children under age three consume foods rich in vitamin A, and at least 90 percent of children age 12-35 months, including those breastfed and those not breastfed, have a diet that includes fruits and/or vegetables rich in vitamin A (see Table 11.3 above). A vitamin A supplementation program does not emerge as a priority in Moldova. Other sources of data should be consulted, however, that reflect dietary habits outside of the summer season when fresh fruits and vegetables are likely to be scarcer. Figure 11.2 Type of Salt Used For Pickling 18 72 98 83 1012 79 10 Iodized Not iodized Don't know 0 20 40 60 80 100 Percent Urban Rural Total MDHS 2005 146 | Nutrition The percentage of children in house- holds where iodized salt is consumed is not very different from the overall prevalence of households where adequately iodized salt is consumed (64 percent versus 60 percent). The largest discrepancy between groups of children’s access to salt is seen in the wealth status variable: a substantially smaller pro- portion of children in the poorest households have iodized salt in their diet compared with children in the richest households (43 per- cent and 88 percent, respectively). More- over, children in rural areas and those in the South region fare worse than children in other parts of the country. 11.3 MICRONUTRIENT INTAKE A mother’s nutritional status during pregnancy is important both for the child’s intrauterine development and for protection against maternal morbidity and mortality. Night blindness is an indicator of vitamin A deficiency that pregnant women are espe- cially prone to experience. Table 11.6 shows that 5 percent of women with a recent birth report that they experienced night blindness during the pregnancy. After adjusting for women who also reported vision problems during the day, an estimated 1 percent of women suffer from night blindness. Pregnant women are among the groups in greatest need of iron, and are most likely to benefit from iron supplements. Iron requirements for pregnant women are approximately double that of nonpregnant women because of increased blood volume during pregnancy and blood loss during delivery. Several major health organizations recommend iron supplementation from the first prenatal visit for pregnant women to meet their increased iron requirements (e.g., U.S. Centers for Diseases Control and Pre- vention and the National Academy of Sciences). Table 11.5 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 24 hours preceding the survey, and percentage of children under five living in households using adequately iodized salt, by background characteristics, Moldova 2005 Background characteristic Consumed fruits and vegetables rich in vitamin A1 Number of children Percentage living in households using adequately iodized salt2 Number of children Age in months <6 6.6 157 66.9 153 6-9 64.9 104 57.5 105 10-11 84.3 50 67.3 49 12-23 90.6 339 65.6 345 24-35 90.7 290 63.5 323 36-47 na na 63.8 291 48-59 na na 63.2 265 Sex Male 74.6 476 64.9 787 Female 72.2 465 63.1 745 Birth order 1 74.4 456 66.5 778 2-3 73.7 426 63.5 664 4+ 64.1 59 46.4 89 Breastfeeding status Breastfeeding 48.0 332 63.8 336 Not breastfeeding 87.2 607 64.1 1,193 Residence Urban 72.7 389 79.5 593 Rural 73.9 551 54.3 939 Region North 76.8 277 57.4 455 Center 71.0 269 62.2 447 South 74.1 186 50.2 303 Chisinau 71.3 208 88.5 326 Mother's education No education/ primary * 13 * 18 Secondary 71.2 611 57.0 990 Secondary special 81.3 128 72.5 226 Higher 75.3 189 82.9 297 Mother's age at birth <20 74.8 116 57.5 207 20-24 70.0 379 63.3 636 25-29 74.4 252 69.6 414 30-34 77.6 142 62.1 200 35-49 79.2 51 62.8 74 Wealth quintile Lowest 71.2 173 42.7 302 Second 74.7 177 54.8 286 Middle 75.4 200 58.6 326 Fourth 70.5 187 75.3 300 Highest 74.9 204 87.9 317 Total 73.4 940 64.0 1,531 Note: Information on vitamin A supplements is based on mother's recall. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, green leafy vegetables, mango, papaya, and other locally available 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. Nutrition | 147 Table 11.6 presents data on the number of days that pregnant women in Moldova took iron supplementation in the form of tablets or syrup during the pregnancy leading to the most recent birth in the five years preceding the survey. Forty-nine percent of women took supplements during their pregnancy, and among them, 72 percent reported taking supplements for less than 60 days. Less than 10 percent of pregnant women take iron supplements for more than 90 days, thus falling short of the amount recommended by major health organizations. Among women who took supplements for 90 days or more, proportionally more were younger women age 20-24, women giving birth to their first child, and women living in Chisinau or another urban setting. These mothers were also more likely to have at least some university education and to be from households in the highest wealth quintile. Table 11.6 also shows that 21 percent of mothers take folic acid during pregnancy; background characteristics for mothers taking folic acid show generally reveal the same pattern as for those taking iron supplements except that by age group the highest level is among women age 30-34 (24 percent). Table 11.6 Micronutrient intake among mothers Percentage of women with a birth in the five years preceding the survey who experienced night blindness during pregnancy, percentage who took folic acid and iron supplements for specific number of days, and percentage who live in households using adequately iodized salt, by background characteristics, Moldova 2005 Number of days iron tablets/syrup taken during pregnancy Background characteristic Mother reported night blindness during pregnancy Reported night blindness adjusted1 Percent who took folic acid during pregnancy None <60 60-89 90+ Don’t know/ missing Number of women Percent living in households using adequately iodized salt2 Number of women Age at birth <20 6.6 2.6 16.2 51.6 35.1 5.9 2.4 5.0 173 58.2 169 20-24 3.7 0.9 20.5 43.5 34.4 5.1 10.1 7.0 564 65.0 551 25-29 6.0 1.3 22.3 43.3 37.1 5.7 8.9 5.1 389 70.5 378 30-34 5.6 1.8 23.9 43.7 34.9 6.4 9.7 5.3 189 64.1 185 35-49 6.5 1.7 11.4 57.9 31.1 2.8 5.6 2.6 72 63.8 71 Number of children ever born 1 4.6 1.5 24.1 41.9 35.5 5.7 10.1 6.8 677 68.5 663 2-3 5.5 1.1 18.3 45.9 36.3 5.4 7.2 5.1 629 64.2 613 4+ 6.4 2.6 6.2 67.2 22.6 2.9 4.7 2.6 81 50.6 78 Residence Urban 6.0 1.5 26.2 37.0 36.5 7.1 13.5 5.9 566 80.3 554 Rural 4.4 1.3 16.5 50.9 34.2 4.3 5.0 5.6 821 55.2 800 Region North 4.9 1.8 22.6 49.3 36.3 5.0 4.4 5.0 424 58.5 413 Center 4.9 0.9 12.0 49.5 36.6 3.3 5.7 4.9 386 64.4 378 South 4.5 1.4 15.8 52.9 28.2 5.9 5.6 7.4 264 50.7 257 Chisinau 6.1 1.4 32.0 28.0 37.6 8.1 19.9 6.4 313 88.7 307 Education No education/primary * * * * * * * * 16 * 15 Secondary 4.0 1.1 14.9 54.1 31.0 4.6 4.7 5.5 880 58.7 861 Secondary special 6.2 1.7 29.4 33.6 43.7 5.8 11.2 5.7 209 72.2 205 Higher 7.7 2.3 31.6 25.0 42.1 7.8 18.7 6.4 283 83.2 274 Wealth quintile Lowest 3.6 1.3 9.4 64.5 28.1 4.5 1.4 1.5 246 44.6 242 Second 3.2 1.1 14.6 53.1 35.9 3.5 3.0 4.6 260 55.3 251 Middle 4.6 1.0 21.4 43.4 34.7 5.8 7.0 9.1 290 58.3 284 Fourth 6.3 1.6 21.8 39.3 37.5 6.0 9.6 7.6 283 75.6 278 Highest 7.2 2.0 32.1 30.3 38.3 6.8 19.2 5.3 308 88.2 301 Total 5.1 1.4 20.5 45.2 35.1 5.4 8.5 5.8 1,387 65.5 1,354 Note: For women with two or more live births in the five-year period, data refer to the most recent birth. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Women who reported night blindness but did not report difficulty with vision during the day 2 Salt containing 15 ppm of iodine or more. Excludes women in households in which salt was not tested. 148 | Nutrition Finally, Table 11.6 shows the distribution of women who gave birth in the past five years and their access to iodized salt. Overall, the percentage of these women in households where iodized salt is consumed is not very different from the overall prevalence of households where adequately iodized salt is consumed (66 percent versus 60 percent). However, like for children, the largest discrepancy is seen in the wealth status variable: a significantly smaller percentage of women in the poorest households have iodized salt in their diet compared with women in the richest households (45 percent and 88 percent, respectively). And, like for children, women in rural areas and those in the South region fare worse than women in other parts of the country. 11.4 ANEMIA Anemia is a condition characterized by a reduction in the red blood cell volume and a decrease in the concentration of hemoglobin in the blood. Hemoglobin is necessary for transporting oxygen to tissues and organs in the body. The reduction in oxygen available to organs and tissues when hemoglobin levels are low is responsible for many of the symptoms experienced by anemic persons. The symptoms of anemia include general body weakness, frequent tiredness, and lowered resistance to disease. About half of the global burden of anemia is due solely to iron deficiency. Iron deficiency, in turn, is largely due to an inadequate dietary intake of bioavailable iron, increased iron requirements during rapid growth periods, such as pregnancy and infancy, and increased blood loss due to hookworm or schistosome infestation. Nutritional anemia includes the anemic burden due to deficiency in iron plus deficiencies in folate, vitamins B and B12, and certain trace elements involved with erythropoiesis, or red blood cell production. Nonnutritional causes of anemia are largely due to hookworm and malaria infections, and HIV, particularly in sub-Saharan Africa. Anemia can be a particularly serious problem for pregnant women, leading to premature delivery and low birth weight. With regards to its impact on children, iron-deficiency anemia has been demonstrated to be associated with impaired cognitive performance, motor development, coordination, language development, and scholastic achievement (Lozoff, 1991; Scrimshaw, 1984). Iron deficiency also increases the susceptibility of children to poisoning from heavy metals, including lead. Anemia increases morbidity from infectious diseases because of its adverse impact on the immune system. Iron deficiency is the leading micronutrient deficiency in the world. In industrialized countries, where iron deficiency is the primary cause of anemia, most estimates of iron deficiency are based on the prevalence of anemia. The MDHS, therefore, included anemia testing of children 6-59 months old and women age 15-49. Anemia levels were determined by measuring the level of hemoglobin in the blood, with a decreased concentration characterizing anemia. For hemoglobin measurements, a drop of capillary blood was taken with a finger prick (using sterile, disposable instruments). Hemoglobin concentration was measured using the HemoCue photometer system. As described in Chapter 1, medically trained personnel on each MDHS interviewing team performed the testing procedures on eligible, consenting respondents. Nutrition | 149 Prevalence of Anemia in Children Table 11.7 presents anemia preva- lence for children 6-59 months. A total of 1,573 children were eligible to be tested (see Appendix C). The results presented here are based on test results of 1,364 children who were present at the time of testing, whose parents consented to their being tested, and whose hemoglobin results represented plausible data. Anemia levels are classified as severe, moderate, or mild, according to criteria developed by the World Health Organization (DeMaeyer et al., 1989). Over- all, about one-third of children 6-59 months in Moldova have some level of anemia, in- cluding 22 percent of children who are mild- ly anemic (10.0-11.9 g/dl), 10 percent who are moderately anemic (7.0-9.9 g/dl), and no children with serious anemia. Children most likely to have a higher prevalence of anemia are in the youngest age groups: 45 to 60 percent of children age 6-9 months through 12-23 months have some level of anemia; prevalence declines to 15 percent for ages 48-59 months (Figure 11.3). This age pattern suggests that infants at the age of weaning are at increased risk for iron deficiency. Children of birth order four or more are more likely to have anemia (48 percent) than children with fewer siblings, as are children of young mothers age 20-24 (38 percent), and probably also age 15-19, although a small number of unweighted cases means results should be interpreted cautiously. Children from households in the lowest wealth quintile are substantially more susceptible to mild or moderate anemia than children in the wealth- iest quintile (39 percent and 23 percent, re- spectively). In a national nutritional status study carried out by the Moldova Ministry of Health in 1996-1999 (UNICEF and MOH, 2002), 28 percent of children 6-59 months had anemia, and 47 percent between 6-12 months were anemic. These levels, which do not differ substantially from levels found in the MDHS, are considered by the World Health Organization to be a medium-level Table 11.7 Prevalence of anemia in children Percentage of children age 6-59 months classified as having anemia, by background characteristics, Moldova 2005 Anemia status Background characteristic Any anemia Mild (10.0-11.9 g/dl) Moderate (7.0-9.9 g/dl) Number of children Age in months 6-9 44.8 33.1 11.8 87 10-11 59.8 34.9 24.9 48 12-23 44.6 28.9 15.7 342 24-35 33.3 21.3 12.0 313 36-47 24.8 18.3 6.5 293 48-59 14.7 11.9 2.9 281 Sex Male 35.0 23.7 11.2 691 Female 29.3 19.9 9.4 672 Birth order1 1 32.8 21.9 10.9 585 2-3 30.9 21.3 9.7 529 4+ 47.7 26.0 21.7 74 Birth interval in months1,2 First birth 32.2 21.4 10.7 925 <24 (45.6) (28.2) (17.5) 46 24-47 32.9 18.9 14.1 75 48+ 33.6 24.5 9.2 142 Residence Urban 26.8 18.4 8.4 432 Rural 34.7 23.5 11.2 932 Region North 35.3 24.6 10.8 443 Center 31.1 20.5 10.7 432 South 35.7 23.8 12.0 281 Chisinau 22.7 16.4 6.4 208 Mother's education3 No education/primary * * * 12 Secondary 35.0 22.3 12.7 816 Secondary special 27.7 18.9 8.9 171 Higher 26.0 19.7 6.3 209 Mother's age3 15-19 (48.2) (35.1) (13.1) 50 20-24 37.6 23.5 14.1 360 25-29 27.9 18.8 9.2 423 30-34 28.8 20.7 8.1 250 35-49 35.2 23.1 12.1 124 Children of interviewed mothers 32.9 21.9 11.0 1,188 Wealth quintile Lowest 39.2 25.4 13.8 294 Second 34.1 22.1 12.0 293 Middle 30.4 22.0 8.4 327 Fourth 32.2 22.4 9.8 230 Highest 22.7 16.0 6.7 220 Total 32.2 21.8 10.3 1,364 Note: Table is based on children who stayed in the household the night before the interview. Prevalence is adjusted for altitude using CDC formulas (CDC, 1998). 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. g/dl = grams per deciliter 1 Excludes children whose mothers were not interviewed 2 First born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval. 3 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the household schedule. 150 | Nutrition public health concern.2 Compared with estimates from recent Reproductive Health Surveys and Demographic and Health Surveys conducted in other countries in Eastern Europe and Eurasia, the prevalence of any anemia among children in Moldova is about the same as for children in Armenia (31 percent in 2000) and Azerbaijan (32 percent in 2001). Children in Central Asia have higher prevalence of anemia: in Kazakhstan (1999), 48 percent; in Kyrgyz Republic (1997), 50 percent; in Turkmenistan (2000), 44 percent; and in Uzbekistan (1996), 61 percent. Prevalence of Anemia in Women Table 11.8 presents anemia prevalence for women. Among 7,585 women who were eligible for testing, 7,138 were present at the time of testing, consented to having the test, and had test results that yielded plausible data (see Appendix C). Twenty-eight percent of women in Moldova have some level of anemia. The great majority of women with anemia have a mild form of anemia (23 percent out of 28 percent), and the remainder have moderate anemia (4 percent) and severe anemia (less than 1 percent). Examining the prevalence of anemia by background characteristics reveals important patterns. As expected, mild or moderate anemia prevalence is significantly higher—about 50 percent higher—among pregnant women than among those who are neither pregnant nor breastfeeding. It is about 20 percent higher among women using an IUD, a difference that can be explained by the increased menstrual blood loss caused by using an IUD which can lead to iron depletion (INACG, 1989, NIH, 206). Women living in rural areas and those with four or more children are more likely to have mild anemia than other women. Women with these background characteristics would benefit the most from an iron supplementation program. 2 WHO considers anemia prevalence of over 40 percent in a population as a major public health problem, from 10- 40 percent is considered a medium-level public health problem, and 1-9.9 percent is a mild public health problem (UNICEF and MOH, 2002). Figure 11.3 Percentage of Children with Anemia, by Severity of Anemia and Age 6-9 10-11 12-23 24-35 36-47 48-59 Age in months 0 10 20 30 40 50 60 70 Percent Mild (10.0-10.9 g/dl) Moderate (7.0-9.9 g/dl) MDHS 2005 Nutrition | 151 Table 11.8 Prevalence of anemia in women Percentage of women age 15-49 with anemia, by background characteristics, Moldova 2005 Anemia status Background characteristic Any anemia Mild (10.0- 11.9 g/dl) Moderate (7.0- 9.9 g/dl) Severe (<7.0 g/dl) Number of women Age1 15-19 23.9 21.7 2.1 0.1 1,377 20-24 26.0 22.5 3.5 0.1 1,073 25-29 28.8 25.0 3.2 0.6 926 30-34 29.4 24.3 5.0 0.0 875 35-39 28.0 22.7 4.8 0.5 819 40-44 31.5 24.7 6.6 0.1 959 45-49 29.4 23.0 5.9 0.5 1,109 Children ever born2 None 22.8 20.6 2.1 0.1 2,324 1 27.4 22.0 5.2 0.2 1,507 2-3 30.8 25.0 5.5 0.4 2,897 4+ 37.4 31.5 5.3 0.7 410 Pregnancy and breast- feeding status2 Pregnant 40.4 28.0 12.5 0.0 168 Breastfeeding only 30.7 27.3 3.4 0.0 333 Neither 27.4 23.0 4.2 0.3 6,637 Using IUD Yes 32.9 26.0 6.5 0.4 1,281 No 26.7 22.7 3.8 0.2 5,857 Residence Urban 24.6 21.3 3.1 0.3 2,962 Rural 30.1 24.7 5.2 0.2 4,176 Region North 31.6 25.1 6.3 0.2 2,164 Center 25.8 22.3 3.3 0.3 1,992 South 31.4 26.6 4.6 0.2 1,367 Chisinau 22.3 19.3 2.7 0.2 1,616 Education1 No education/ Primary (22.1) (14.7) (7.4) (0.0) 49 Secondary 28.8 24.4 4.1 0.2 4,389 Secondary special 27.3 21.3 5.6 0.5 1,267 Higher 25.8 22.0 3.7 0.1 1,434 Wealth quintile Lowest 31.9 26.5 5.1 0.3 1,225 Second 30.2 24.3 5.5 0.4 1,213 Middle 29.7 24.8 4.7 0.2 1,483 Fourth 26.7 23.0 3.6 0.2 1,598 Highest 22.5 19.1 3.2 0.2 1,619 Total 27.9 23.3 4.3 0.3 7,138 Note: Table is based on women who stayed in the household the night before the interview. Prevalence is adjusted for altitude using CDC formulas (CDC, 1998). Women with <7.0 g/dl of hemoglobin have severe anemia, women with 7.0-9.9 g/dl have moderate anemia, and pregnant women with 10.0-10.9 g/dl and nonpregnant women with 10.0-11.9 g/dl have mild anemia. Figures in parentheses are based on 25-49 unweighted cases. g/dl = grams per deciliter 1 For women who are not interviewed, information is taken from the Household Questionnaire. 2 Excludes women who were not interviewed. 152 | Nutrition The level of anemia in pregnant women is considered a moderate public health problem. Among the national strategies proposed to improve the situation is an iron supplement program that would target groups most vulnerable to iron deficiency, and the enrichment of flour with iron for consumption by the general public (UNICEF and MOH, 2002). Compared with women in most other parts of the region, women in Moldova are less likely to have anemia: 40 percent of women in Azerbaijan (2001) have some level of anemia; 36 percent in Kazakhstan (1999); 38 percent in Kyrgyz Republic (1997); 47 percent in Turkmenistan (2000); and 60 percent in Uzbekistan (1996). Prevalence among women in Armenia (2000) is the exception, where only 12 percent have some level of anemia (CDC and ORC Macro, 2003). Table 11.9 shows a positive but not a strong relationship between children having anemia and their mother also having anemia. For example, overall, 33 percent of children (who were tested for anemia and whose mothers were also tested for anemia) have some level of anemia; these children are slightly more likely to have anemia if their mothers have some level of anemia than if their mother has no anemia (37 percent and 31 percent, respectively). In addition, children with mild anemia (22 percent) are slightly more likely to have mild anemia if their mothers have some level of anemia than if they have no anemia (25 percent and 20 percent, respectively). Table 11.9 Prevalence of anemia in children by anemia status of mother Percentage of children age 6-59 months classified as having anemia, by anemia status of mother, Moldova 2005 Anemia status of child Anemia status of mother Any anemia Mild (10.0- 11.9 g/dl) Moderate (7.0-9.9 g/dl) Number of children No anemia 30.8 20.3 10.5 787 Any anemia 37.2 25.0 12.1 401 Anemia status Mild anemia 35.4 23.9 11.5 343 Moderate anemia (47.1) (29.9) (17.3) 53 Severe anemia * * * 5 Total 32.9 21.9 11.0 1,188 Note: Table is based on children who stayed in the household the night before the interview. Prevalence is adjusted for altitude using CDC formulas (CDC, 1998). Table includes only cases with anemia measurements for both mothers and 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. g/dl = grams per deciliter 11.5 NUTRITIONAL STATUS OF CHILDREN The growth patterns of healthy, well-fed children are reflected in positive changes in their height and weight. Inadequate food supply, among other factors, often leads to malnutrition, resulting in serious consequences on the physical and mental growth and development of children (Brozek and Schurch, 1984; Pelletier et al., 1993). Nutrition indicators are monitored for national tracking purposes as well as to provide information on the progress towards achieving the Millennium Development Goals (MDGs).3 3 One of the eight UN Millennium Development Goals adopted in 2000 is to eradicate extreme poverty and hunger, with the target to reduce by half the proportion of malnourished children by 2015. Nutrition | 153 The nutrition indicators presented below are the first available since MDGs were adopted in 2000, thus providing an important source of baseline data for a representative population (UNDP, 2003). In addition to questions about infant and young children’s feeding practices, the MDHS included an anthropometric component, in which height and weight measurements were obtained for all children born in the five years preceding the MDHS. Each interviewing team carried a scale and measuring board. The scales were lightweight, bathroom-type scales with a digital screen designed and manufactured under the authority of UNICEF. The measuring boards were specially produced by Shorr Productions for use in survey settings. Children younger than 24 months were measured lying down on the board (recumbent length), while standing height was measured for older children. 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. In any large population, there is variation in height and weight; this variation approximates a normal distribution. Use of a standard reference population as a point of comparison facilitates the examination of differences in the anthropometric status of subgroups in a population and of changes in nutritional status over time. 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. The use of this reference population is based on the finding that young children of all population groups have similar genetic potential for growth. Three standard indices of physical growth that describe the nutritional status of children are presented: • Height-for-age (stunting) • Weight-for-height (wasting) • Weight-for-age (underweight) Each of the three nutritional indicators is expressed in standard deviations (Z-scores) from the mean of the reference population (or from the median of the reference population, since the mean and median coincide in a standardized normal distribution). Deviations of the indicators below -2 standard deviations (SD) indicate that the children are moderately and severely affected, while deviations below -3 SD indicate that the children are severely affected. It is helpful to keep in mind that, in the reference population, 2.3 percent of children fall below -2 SD of the mean for each of these indices (and the same percentage above -2 SD).4 A total of 1730 (weighted) children under age five were eligible to be weighed and measured (see Appendix C). Information for 13 percent of eligible children was not used in calculating the nutrition indicators either because some children were not weighed or measured, or the weight and/or height information for those measured was out of range of plausible values, or because age information was incomplete. The following analysis focuses on 1,498 children under five for whom complete and plausible anthropometric data were collected. 4 In a population where values are assumed to be normally distributed, such as height and weight values in the standard reference population, then the “Empirical rule” may be applied: 68.3 percent of values are within one standard deviation from the mean, 95.4 percent of values are within two standard deviations, and about 99.7 percent are within three standard deviations. 154 | Nutrition Stunting Height-for-age is a measure of linear growth. A child who is below -2 SD from the median of the NCHS reference population in terms of height-for-age is considered short for his/her age, or “stunted,” a condition reflecting the cumulative effect of chronic malnutrition. If the child is below -3 SD from the reference median, then the child is considered to be severely stunted. A child between -2 and -3 SD is considered to be moderately stunted. Stunting reflects failure to receive adequate nutrition over a long period of time and may also be caused by recurrent and chronic illness. Height-for-age, therefore, represents a measure of the long-term effects of malnutrition in a population and does not vary appreciably according to the season of data collection. Stunted children are not immediately obvious in a population; a stunted three-year-old child could look like a well-fed two-year-old. Table 11.10 shows the nutritional status of children under five as measured by the stunting (height-for-weight) indicator and various background characteristics. At the national level, about 8 percent of children under five are moderately stunted—several percentage points higher than the 2.3 percent in the national reference population—while the proportion severely stunted is about 2 percent. Analysis of the indicator by various background characteristics shows children who are the most likely to be moderately stunted are those of birth order four or more (15 percent), followed by children who were considered small at the time of birth (14 percent), and those from households in the lowest wealth quintile (14 percent). Children in the two highest wealth quintiles, on the other hand, demonstrate less stunting (4 percent and 6 percent, respectively). There are no strong differences between subgroups. Compared with estimates from recent Reproductive Health Surveys and Demographic and Health Surveys conducted in other countries in Eastern Europe and Eurasia, the prevalence of stunting is lower for children in Moldova than for children in other countries in the region: 11 percent of children under age five were stunted in Armenia (1999); 13 percent (of children 3-59 months) in Azerbaijan (2001); 10 percent in Kazakhstan (1999); 25 percent in Kyrgyz Republic (1997); 24 percent in Turkmenistan (2000); and 31 percent in Uzbekistan (1996) (CDC and ORC Macro, 2003). Wasting Weight-for-height measures body mass in relation to body length and describes current nutritional status. A child who is below -2 SD from the reference median for weight-for-height is considered to be too thin for his/her height, or “wasted,” a condition reflecting acute malnutrition. Wasting represents the failure to received adequate nutrition in the period immediately preceding the survey and may be the result of inadequate food intake or recent episodes of illness causing loss of weight and the onset of malnutrition. As with stunting, wasting is considered severe if the child is below -3 SD from the reference mean. Severe wasting is closely linked to an elevated risk of mortality. Prevalence of wasting may vary considerably by season. Table 11.10 also shows the prevalence of wasting among children under age five. Nationally, 4 percent of children are wasted (about 2 percentage points higher than the national reference population), and the proportion severely wasted is about 1 percent. Overall, this is a small proportion and it does not vary more than one or two percentage points by background characteristics. Nutrition | 155 Table 11.10 Nutritional status of children 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 background characteristics, Moldova 2005 Height-for-age Weight-for-height Weight-for-age Background characteristic Percentage below -3 SD Percentage below -2 SD 1 Mean Z-score (SD) Percentage below -3 SD1 Percentage below -2 SD Mean Z-score (SD) Percentage below -3 SD1 Percentage below -2 SD Mean Z-score (SD) Number of children Age in months <6 2.5 6.5 0.1 1.6 2.2 0.4 0.0 0.9 0.5 116 6-9 0.7 6.4 0.2 0.9 7.0 0.1 0.0 2.7 0.2 93 10-11 (1.8) (9.2) 0.5 (2.9) (2.9) 0.1 (1.7) (1.7) 0.4 44 12-23 1.5 12.2 0.4 0.6 4.1 0.1 0.7 4.1 0.2 335 24-35 2.2 7.0 0.0 1.0 3.6 0.0 0.0 4.4 0.1 319 36-47 1.2 6.0 0.2 0.8 4.7 0.1 0.8 5.0 0.3 300 48-59 1.9 9.2 0.3 0.0 3.0 0.1 0.8 5.9 0.2 292 Sex Male 1.5 8.1 0.2 0.9 3.9 0.1 0.8 3.4 0.1 764 Female 1.9 8.6 0.2 0.6 3.8 0.1 0.2 5.2 0.1 734 Birth order2 1 1.8 7.7 0.1 0.3 3.7 0.1 0.3 3.3 0.1 654 2-3 1.7 8.7 0.2 0.9 4.5 0.1 0.7 4.9 0.1 582 4+ 1.1 14.9 0.6 1.3 2.9 0.2 0.0 8.7 0.3 83 Birth interval in months2 First birth3 1.7 7.7 0.1 0.5 4.0 0.1 0.2 3.3 0.1 1,028 <24 (0.0) (19.8) 0.9 (0.0) (3.1) 0.1 (0.0) (8.4) 0.6 46 24-47 2.3 11.4 0.6 0.0 3.0 0.1 1.0 9.0 0.3 83 48+ 1.6 9.8 0.4 1.7 4.7 0.1 1.9 7.7 0.3 161 Size at birth2 Very small * * * * * * * * * 15 Small 1.9 13.5 0.7 1.2 5.5 0.3 1.7 9.7 0.7 143 Average or larger 1.5 7.7 0.1 0.5 3.8 0.1 0.3 3.5 0.0 1,154 Residence Urban 1.9 6.7 0.1 0.9 4.0 0.2 0.3 2.6 0.2 497 Rural 1.6 9.2 0.3 0.7 3.8 0.0 0.6 5.1 0.3 1,001 Region North 1.5 6.3 0.2 0.4 3.9 0.1 0.6 2.4 0.1 460 Center 1.1 10.2 0.3 1.2 4.9 0.0 0.5 6.5 0.3 462 South 2.6 11.0 0.4 0.2 3.2 0.0 0.5 5.6 0.3 314 Chisinau 1.9 5.8 0.3 1.3 2.9 0.2 0.3 2.2 0.3 262 Mother's education4 No education/primary * * * * * * * * * 14 Secondary 1.8 9.5 0.3 0.5 3.9 0.0 0.4 5.6 0.3 906 Secondary special 2.0 6.9 0.0 0.4 3.9 0.2 0.0 1.1 0.1 183 Higher 0.6 5.1 0.2 1.1 4.2 0.2 1.0 2.3 0.3 235 Mother's age4 15-19 0.0 5.0 0.3 0.0 3.0 0.1 0.0 0.0 0.1 55 20-24 2.0 9.1 0.2 0.2 3.1 0.1 0.2 3.7 0.2 411 25-29 2.0 9.7 0.1 0.8 5.2 0.0 0.7 4.3 0.1 468 30-34 1.2 6.8 0.2 1.3 3.9 0.1 0.5 5.6 0.1 268 35-49 1.3 7.5 0.3 0.0 2.5 0.0 0.6 5.7 0.2 134 Children of interviewed mothers 1.7 8.6 0.2 0.6 4.0 0.1 0.5 4.4 0.1 1,319 Children of non- interviewed mothers Mother in the household * * * * * * * * * 18 Mother not in the household5 1.9 7.4 0.2 2.2 3.4 0.2 0.9 4.1 0.0 162 Wealth quintile Lowest 1.3 13.5 0.6 0.8 3.6 0.0 0.7 7.2 0.4 323 Second 2.7 7.2 0.4 1.2 3.4 0.0 1.0 6.6 0.3 316 Middle 1.1 9.6 0.1 0.6 4.7 0.1 0.0 2.8 0.1 342 Fourth 1.6 4.0 0.0 0.4 5.0 0.1 0.9 2.8 0.0 259 Highest 2.0 6.1 0.3 0.9 2.5 0.3 0.0 1.2 0.3 258 Total 1.7 8.4 0.2 0.8 3.9 0.1 0.5 4.3 0.1 1,498 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 Population (-3 SD and -2 SD) are shown according to background 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. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes children who are below -3 standard deviations (SD) 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. 4 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the household schedule. 5 Includes children whose mothers are deceased 156 | Nutrition Underweight Weight-for-age is a composite index of height-for-age and weight-for-age and therefore does not distinguish between acute malnutrition (wasting) and chronic malnutrition (stunting). A child can be underweight for his age because he is stunted, wasted, or both. Weight-for-age is a useful tool in clinical settings for continuous assessment of nutritional progress and growth. Children whose weight-for-age is below -2 SD from the median of the reference population are classified as “underweight.” Again, in the reference population, 2.3 percent of children fall below -2 SD of the mean for each of these indices (and the same percentage above -2 SD). As shown in Table 11.10, about 4 percent of children are underweight. The proportion of severely underweight is less than 1 percent. Children most likely to be underweight are those who were considered small at birth (10 percent), those from households in the lowest wealth quintiles (7 percent in the lowest and second quintiles), and somewhat surprisingly, those with longer birth intervals (9 percent of children born 24-47 months after an older sibling). 11.6 NUTRITIONAL STATUS OF WOMEN The MDHS collected anthropometric data on all women age 15-49. Women’s nutritional status is important both as an indicator of overall health and as a predictor of pregnancy outcome for both mother and child. The data are used to derive two measures of nutritional status: height and body mass index (BMI). A woman’s height can be used to predict the risk of having difficulty in pregnancy, given the relationship between height and pelvic size. The cutoff point at which mothers can be considered at risk because of short stature is normally taken to be between 140 and 150 centimeters. The BMI or Quetelet index is used to measure thinness or obesity. It is defined as weight in kilograms divided by height in meters squared (kg/m2). A BMI of less than 18.5 is considered an indication of chronic energy deficiency among nonpregnant women, based on cutoffs set by the World Health Organization (WHO, 1995). Values of 25.0 to 29.9 indicate that a person is overweight, while values of 30.0 and higher indicate obesity. Table 11.11 shows nutritional indicators for women by various background characteristics. At the national level, the mean height for women is 161 cm, with less than 1 percent of women falling below the cutoff of 145 cm. The mean BMI for women age 15-49 is 25. Analysis by background characteristics shows that the mean BMI varies very little between subgroups, except for women’s age where those in the youngest age groups (15-19 and 20-24) have BMIs of only 21 and 22, respectively, and those in the oldest age groups (40-44 and 45-49) have a BMI of 29. At the national level, the proportion of severely thin women stands at less than 1 percent (BMI <16). The proportion of overweight or obese women, however, stands at about 42 percent. The proportion of overweight or obese women is positively correlated with the woman’s age. Thus, women age 45-49 have the highest proportion (74 percent) of overweight or obese women, while those age 15-19 have the lowest proportion (8 percent). Nutrition | 157 Table 11.11 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, Moldova 2005 Height BMI (kg/m2)1 Background characteristic Mean height in cm Percent- age below 145 cm Number of women Mean BMI 18.5- 24.9 (normal) <18.5 (thin) 17.0- 18.4 (mildly thin) 16.0- 16.9 (moder- ately thin) <16.0 (severely thin) >25.0 (over- weight or obese) 25.0- 29.9 (over- weight) >30.0 (obese) Number of women Age 15-19 161.8 0.2 1,403 21.0 75.6 16.3 12.0 3.2 1.1 8.2 7.3 0.9 1,378 20-24 162.3 0.4 1,099 22.4 73.2 9.2 7.3 1.3 0.5 17.6 13.1 4.5 1,011 25-29 161.7 0.6 945 24.0 63.3 5.4 4.4 0.7 0.4 31.3 20.9 10.4 881 30-34 161.8 0.3 901 25.3 51.7 3.5 2.7 0.7 0.1 44.8 29.4 15.4 869 35-39 160.8 1.2 830 26.9 42.3 1.2 1.0 0.2 0.0 56.5 31.5 25.0 820 40-44 160.9 0.3 985 28.6 29.9 0.3 0.2 0.1 0.0 69.8 34.0 35.7 980 45-49 160.0 0.5 1,123 29.0 25.3 1.0 0.7 0.1 0.2 73.7 34.1 39.5 1,123 Residence Urban 162.2 0.2 3,069 24.8 54.1 6.6 4.8 1.3 0.5 39.4 22.9 16.5 2,980 Rural 160.7 0.7 4,217 25.4 51.5 5.5 4.3 0.9 0.3 43.0 23.7 19.4 4,082 Region North 161.5 0.5 2,185 25.5 50.1 6.0 4.9 0.8 0.3 43.9 23.9 20.0 2,111 Center 160.9 0.6 2,010 25.0 54.1 5.3 3.9 1.1 0.3 40.6 23.6 17.0 1,954 South 160.1 0.6 1,386 25.7 50.9 4.7 3.5 1.0 0.2 44.4 22.9 21.4 1,345 Chisinau 162.6 0.2 1,705 24.4 55.3 7.6 5.5 1.4 0.6 37.1 22.7 14.4 1,652 Education No education/ primary 159.4 2.5 48 26.7 36.1 3.0 1.3 1.6 0.0 60.9 27.4 33.6 48 Secondary 160.7 0.6 4,466 25.0 53.3 6.7 5.1 1.2 0.4 39.9 22.0 17.9 4,325 Secondary special 161.5 0.3 1,291 26.6 42.0 2.8 2.3 0.3 0.1 55.3 31.1 24.2 1,264 Higher 163.2 0.1 1,480 24.2 60.3 6.4 4.8 1.1 0.5 33.4 20.5 12.9 1,423 Wealth quintile Lowest 159.8 1.4 1,233 25.2 52.4 5.4 4.1 1.0 0.3 42.2 24.9 17.3 1,198 Second 160.6 0.7 1,226 25.6 50.7 4.8 3.7 1.0 0.2 44.5 23.2 21.3 1,181 Middle 161.1 0.2 1,501 25.3 51.8 6.0 4.7 0.8 0.5 42.2 22.8 19.5 1,451 Fourth 161.7 0.2 1,632 25.1 52.0 6.0 4.6 1.1 0.3 41.9 23.1 18.9 1,584 Highest 162.8 0.1 1,694 24.5 55.3 7.0 5.2 1.4 0.4 37.7 23.1 14.6 1,648 Total 161.3 0.5 7,285 25.1 52.6 5.9 4.5 1.0 0.4 41.5 23.3 18.2 7,062 1 Excludes pregnant women and women with a birth in the preceding 2 months Adult Health | 159 ADULT HEALTH 12 12.1 HEALTH INSURANCE The population of the Republic of Moldova benefits from a system of compulsory health care insurance implemented on January 1, 2004. This system is comprised of an annually approved set of medical services for which costs are covered in a single health insurance package. Furthermore, there are health insurance schemes offered by private insurance companies, as well as services provided by licensed private medical institutions. Within the system of compulsory health insurance, the state finances the costs of health insurance through the Health Insurance Fund. The Fund covers health care costs for all children under 18, for students enrolled in public and private colleges and universities, and for retired and disabled persons. The cost of providing this health insurance is met by means of employers paying a 2 percent tax from the total salary fund and 2 percent from the employee’s salary. Persons employed independently may purchase a health insurance policy on their own, costing about 816 MDL (64 USD) in 2006. The MDHS evaluated the availability of any kind of health insurance for females age 15-49 and males age 15-59. Altogether, 52 percent of females and 50 percent of males indicate that they have some type of health insurance and only 1-2 percent has privately acquired health insurance (Table 12.1). With only about half of the adult population having some kind of health insurance, attention should be focused on those adults who are not covered. Further research is needed to determine how the health care needs of these people are being provided, if at all. The proportion of people having any kind of health insurance varies depending on age, with the lowest level recorded among young adults—females age 25-29 (43 percent) and males age 20-24 (42 per- cent). The highest level of coverage is among females age 40-44 (57 percent) and males age 50-59 (55 percent). The level of health insurance coverage is higher among the urban population, where 61-62 percent of females and males have medical insurance, compared with the rural population where coverage reaches only 46 and 41 percent, respectively. Geographically, the highest percentage of insured persons is in Chisinau (63 percent of females and 64 percent of males), whereas the lowest percentage is among females in the Center region (46 percent) and among males in the North region (44 percent). There is a positive correlation between insurance coverage and education, and insurance coverage and wealth quintile. Both for females and males, insurance coverage varies greatly by educational attainment—from 42 percent among the population with secondary education to 78 percent among people with higher education. The proportion of female and male health insurance holders males in the wealthiest quintile is approximately twice as high (64 percent and 69 percent, respectively) as in the poorest quintile (35 percent and 29 percent, respectively). 160 | Adult Health Table 12.1 Type of health insurance coverage Percentage of adults with health insurance coverage, by background characteristics, Moldova 2005 Women Men Background characteristic Percent- age with any health insur- ance No health insur- ance Health insurance through employer/ education institute Social security Other privately purchased commercial health insurance Total1 Number of women Percent- age with any health insur- ance No health insur- ance Health insurance through employer/ education institution Social security Other privately purchased commercial health insurance Total1 Number of men Age 15-19 54.8 45.2 18.8 35.1 0.3 100.0 1,417 52.1 47.9 18.6 32.6 1.4 100.0 411 20-24 51.8 48.2 33.4 17.8 0.7 100.0 1,124 42.1 57.9 32.4 8.6 1.7 100.0 275 25-29 43.1 56.9 35.9 6.1 1.2 100.0 964 48.1 51.9 41.1 5.8 1.8 100.0 234 30-34 52.9 47.1 45.9 5.4 1.8 100.0 924 44.4 55.6 39.4 2.3 2.7 100.0 224 35-39 50.9 49.1 45.2 4.8 1.0 100.0 855 50.5 49.5 44.0 4.1 2.4 100.0 248 40-44 56.6 43.4 50.0 5.4 1.3 100.0 1,007 52.1 47.9 43.1 7.0 2.0 100.0 247 45-49 54.6 45.4 46.4 6.2 1.7 100.0 1,149 48.5 51.5 40.7 5.6 2.0 100.0 349 50-54 na na na na na na na 55.1 44.9 40.2 12.5 2.7 100.0 296 55-59 na na na na na na na 55.0 45.0 35.7 17.6 1.7 100.0 224 Residence Urban 61.4 38.6 47.9 12.3 1.2 100.0 3,194 62.2 37.8 48.5 11.8 2.2 100.0 1,055 Rural 45.6 54.4 30.7 13.7 1.0 100.0 4,246 41.0 59.0 27.1 12.1 1.8 100.0 1,453 Region North 49.7 50.3 34.3 14.2 1.1 100.0 2,207 43.6 56.4 30.0 12.1 1.5 100.0 756 Center 45.9 54.1 31.8 13.1 0.6 100.0 2,033 46.3 53.7 29.8 15.1 1.5 100.0 702 South 52.3 47.7 38.0 12.8 1.6 100.0 1,402 48.8 51.2 36.2 10.3 2.6 100.0 496 Chisinau 63.1 36.9 50.0 11.9 1.2 100.0 1,798 64.1 35.9 52.5 9.2 2.9 100.0 554 Education No education/ primary (31.8) (68.2) (15.2) (13.2) (3.3) 100.0 49 * * * * * 100.0 16 Secondary 41.5 58.5 26.0 14.4 1.0 100.0 4,534 42.0 58.0 28.2 12.0 1.8 100.0 1,788 Secondary special 61.8 38.2 52.2 7.8 1.7 100.0 1,327 60.1 39.9 46.9 10.5 2.7 100.0 302 Higher 76.9 23.1 62.5 13.8 0.8 100.0 1,530 77.6 22.4 64.1 12.3 2.3 100.0 403 Wealth quintile Lowest 35.3 64.7 20.1 14.0 1.1 100.0 1,243 29.2 70.8 18.9 9.5 0.8 100.0 450 Second 43.3 56.7 29.3 13.8 0.2 100.0 1,234 37.2 62.8 24.0 11.7 1.7 100.0 470 Middle 50.9 49.1 36.6 13.0 1.1 100.0 1,511 50.5 49.5 34.5 14.6 1.3 100.0 464 Fourth 60.4 39.6 44.7 14.2 1.4 100.0 1,672 57.2 42.8 40.9 13.2 3.3 100.0 561 Highest 64.3 35.7 51.9 11.0 1.4 100.0 1,780 69.3 30.7 56.6 10.7 2.5 100.0 563 Total 52.4 47.6 38.1 13.1 1.1 100.0 7,440 49.9 50.1 36.1 12.0 2.0 100.0 2,508 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. na = Not applicable 1 Total includes less than 1 percent of cases with other source of health insurance 12.2 TOBACCO USE Smoking has a powerful negative impact on the population’s health. It causes cardiovascular diseases, lung cancer, and other pathologies, both among smokers and people exposed to secondary cigarette smoke. In the Republic of Moldova, the death rate due to smoking-related causes is one of the highest in the CIS states and the European Union (WHO, 2006). Estimates show that for every one Euro that consumers spend on tobacco products, there is 0.3 Euros spent on the treatment of diseases related to the use of tobacco (Ursu-Moraru, 2006). Because smoking is a conscious choice made by an individual, it follows that morbidity and mortality caused by the use of tobacco products could be prevented. Over recent years, the WHO has invested efforts in the development of a Framework Convention on Tobacco Control (WHO FCTC), a convention signed by 156 countries and ratified already by 119 countries. The Republic of Moldova is among the countries in the process of ratifying the Convention. The National Health Policy recently Adult Health | 161 drawn up by the Ministry of Health and Social Protection also contains a separate chapter dedicated to combating tobacco addiction—yet another acknowledgement of this issue being one of high priority in Moldova. Traditionally, smoking was not widespread in the Moldova. However, probably because of fashion and the relatively low price of cigarettes, access to tobacco products and their use has been on the rise. People in Moldova use tobacco almost exclusively in the form of cigarettes. Results of the 2005 MDHS in Tables 12.2.1 and 12.2.2 show a significant difference in the prevalence of smoking between males and females: 51 percent of men and 7 percent of women report that they currently smoke cigarettes. Smoking among women is much more common in urban areas (14 percent) than rural areas (2 percent). In males, the difference by urban-rural residence is reversed: 49 percent in urban areas and 53 percent in rural areas. Table 12.2.1 Use of tobacco: women Percentage of women who smoke cigarettes or use other tobacco, and percent distribution of cigarette smokers by number of cigarettes smoked in preceding 24 hours, according to background characteristics and maternity status, Moldova 2005 Tobacco use Number of cigarettes smoked in preceding 24 hours: Background characteristic Percent- age of women who smoke cigarettes Percent- age of women who use other tobacco Number of women 1-2 3-5 6-9 10+ Don't know/ missing Total Number of cigarette smokers Age 15-19 4.3 0.0 1,417 18.1 32.4 11.9 34.5 3.1 100.0 62 20-34 9.8 0.0 3,012 16.1 25.8 12.5 40.7 4.9 100.0 294 35-49 5.8 0.0 3,011 16.4 24.2 17.6 40.7 1.1 100.0 176 Residence Urban 13.6 0.0 3,194 16.2 24.7 14.0 42.6 2.6 100.0 434 Rural 2.3 0.0 4,246 17.5 32.2 14.8 28.5 7.1 100.0 98 Region North 4.3 0.0 2,207 17.6 30.6 16.6 33.3 1.9 100.0 94 Center 3.5 0.0 2,033 19.9 26.1 11.1 34.0 8.8 100.0 71 South 3.8 0.1 1,402 27.9 24.3 14.8 30.5 2.5 100.0 53 Chisinau 17.4 0.0 1,798 13.3 25.0 14.0 44.9 2.8 100.0 313 Education No education/primary (18.2) (0.0) 49 * * * * * 100.0 9 Secondary 5.7 0.0 4,534 14.2 27.4 15.8 39.9 2.8 100.0 257 Secondary special 7.0 0.0 1,327 19.5 23.7 15.0 40.1 1.7 100.0 93 Higher 11.3 0.0 1,530 18.1 24.3 11.9 40.2 5.5 100.0 173 Maternity status Pregnant 0.8 0.0 178 * * * * * 100.0 1 Breastfeeding (not pregnant) 2.3 0.0 339 * * * * * 100.0 8 Neither 7.5 0.0 6,923 16.1 26.3 14.4 39.9 3.4 100.0 522 Wealth quintile Lowest 1.2 0.0 1,243 * * * * * 100.0 14 Second 2.4 0.0 1,234 (13.3) (37.6) (12.3) (32.0) (4.9) (100.0) 30 Middle 3.1 0.0 1,511 20.7 30.3 14.3 29.5 5.2 100.0 47 Fourth 8.4 0.0 1,672 19.3 22.7 14.9 39.1 3.9 100.0 141 Highest 16.8 0.0 1,780 15.4 25.5 13.8 42.6 2.6 100.0 300 Total 7.1 0.0 7,440 16.4 26.1 14.1 40.0 3.4 100.0 531 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. 162 | Adult Health Table 12.2.2 Use of tobacco: men Percentage of men who smoke cigarettes or use other tobacco, and percent distribution of cigarette smokers by number of cigarettes smoked in preceding 24 hours, according to background characteristics, Moldova 2005 Tobacco use Number of cigarettes smoked in preceding 24 hours: Background characteristic Percent - age of men who smoke cigarettes Percent- age of men who use other tobacco Number of men 1-2 3-5 6-9 10+ Don't know/ missing Total Number of cigarette smokers Age 15-19 30.0 0.2 411 5.4 13.7 15.4 64.8 0.8 100.0 123 20-34 59.1 0.1 733 3.8 8.0 5.1 82.8 0.3 100.0 434 35-59 53.2 0.3 1,363 1.9 5.2 3.2 89.1 0.6 100.0 725 Residence Urban 48.9 0.4 1,055 3.3 7.4 4.8 83.9 0.6 100.0 515 Rural 52.7 0.1 1,453 2.6 6.7 5.1 85.2 0.5 100.0 767 Region North 56.8 0.2 756 2.5 6.3 5.5 85.5 0.2 100.0 429 Center 48.9 0.3 702 4.1 7.3 5.2 82.7 0.6 100.0 343 South 48.9 0.3 496 1.8 6.5 4.3 86.5 0.8 100.0 242 Chisinau 48.2 0.2 554 2.8 8.1 4.4 84.1 0.6 100.0 267 Education No education/primary * * 16 * * * * * * 8 Secondary 54.1 0.3 1,788 2.2 6.6 5.1 85.7 0.4 100.0 967 Secondary special 49.1 0.3 302 2.7 5.9 3.8 86.0 1.6 100.0 148 Higher 39.6 0.3 403 7.1 10.7 5.2 77.0 0.0 100.0 159 Wealth quintile Lowest 60.0 0.3 450 1.9 6.2 6.5 84.0 1.3 100.0 270 Second 56.5 0.0 470 3.2 4.4 4.5 87.9 0.0 100.0 266 Middle 49.2 0.3 464 2.3 9.5 4.0 83.9 0.3 100.0 228 Fourth 46.8 0.2 561 2.6 7.3 5.0 84.8 0.2 100.0 262 Highest 45.4 0.0 563 4.3 7.9 4.7 82.5 0.6 100.0 255 Total 51.1 0.1 2,508 2.9 7.0 5.0 84.6 0.5 100.0 1,282 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Age is also a characteristic associated with smoking. People in the age group 20-34 are the most likely to smoke. The percentage of cigarette smokers in the three age groups is shown by sex (Figure 12.1). Figure 12.1 Percentage of Cigarette Smokers, by Age Group and Sex 4 10 6 30 59 53 15-19 20-34 35-49 (F) 35-59 (M) 0 20 40 60 80 100 Percent Female Male MDHS 2005 Age Adult Health | 163 The share of smokers also depends on wealth status; however, the influence of this factor differs between females and males. The proportion of female smokers in the poorest households is only 1 percent, compared with 17 percent of women in the wealthiest households. An inverse phenomenon is observed in males: the prevalence of smoking is 60 percent in the poorest households and decreases to 45 percent in the wealthiest households. A similar pattern is observed between smoking and the level of education—smoking is less prevalent among males with higher education, while women with higher education smoke more frequently than those having a lower level of education. Among males who smoke, 90 percent smoke 6 or more cigarettes per day (Table 12.2.2). By comparison, only 54 percent of female smokers consume as many cigarettes. The prevalence of smoking among males is highest in the North region (57 percent) compared with 48-49 percent in other regions. The prevalence of female smokers, unlike that of males, is more than four times higher in Chisinau than in other regions. 12.3 ALCOHOL CONSUMPTION Alcohol abuse is a serious problem in many countries in Europe. This region registers the highest alcohol consumption in the world, and alcohol consumption is considered to be the third highest risk factor for death and disability. Potential consequences of alcohol abuse include increased risk of accidents, cirrhosis, hypertension, psychological illnesses, and congenital malformations. Moreover, alcohol consumption aggravates the risk of family problems as well as other social and employment issues such as alcohol addiction, accidents, criminal behavior, inadvertent injuries, violence, homicide and suicide, road traffic problems, etc. In particular, damages brought about by alcohol abuse rank the highest in the eastern European region, accounting for the increased rate of cardiovascular diseases and shortened life expectancy. In these societies, the total cost related to alcohol abuse is estimated to be 1-3 percent of the gross national product (WHO, 2001). The Republic of Moldova has an agrarian economy, in which the cultivation of grapes and the production of wine accounts for a major portion of the country’s income. Also, traditionally, large quantities of wine are consumed. According to estimates, the average annual per capita consumption of pure alcohol among the population age 15 and over exceeds 12 liters, which is higher than the average of countries of the European Union and approximately twice as high as the average in the Community of Independent States (CIS). Consequently, the death rate in the Republic of Moldova for alcohol-related causes is about 222 per 100,000 persons, which is more than times higher than countries of the European Union and approximately 40 percent higher than in the CSI countries (WHO, 2006). In the 2005 MDHS, respondents were asked how many alcoholic beverages they had consumed during the previous month, on the days when they had consumed alcohol. A bottle or a mug of beer (330- 500 ml), a glass of wine (50-200 ml), a glass of liqueur, and vodka or whiskey (50 ml) were considered standard beverages. Results in Table 12.3.1 show that 59 percent of women consumed at least one alcoholic beverage in the month prior to the interview. The consumption increases from 42 percent in the age group 15-19 to 68 percent in the age group 45-59. Women in urban areas consume alcohol more frequently than those in rural areas (62 and 57 percent, respectively). The highest consumption (64 percent) is in the South region and in Chisinau. The level of alcohol consumption increases somewhat along with the level of education and with the wealth quintile. 164 | Adult Health Table 12.3.1 Use of alcohol: women Percentage of women who have had at least one alcoholic drink in the past month, and the usual frequency of drinking alcohol in a month, by background characteristics, Moldova 2005 Frequency of drinking in a month Background characteristic Has had at least one drink in the past month Every day Almost every day 1-2 times per week 2-3 times per month Once a month Less than once a month Number of women Age 15-19 41.6 0.2 0.7 5.6 9.1 15.2 10.7 1,417 20-24 54.2 0.5 1.2 10.3 14.2 17.2 10.9 1,124 25-29 63.6 0.6 2.1 12.0 15.4 23.5 9.9 964 30-34 63.7 0.6 2.3 12.2 16.6 20.8 11.1 924 35-39 66.5 0.9 2.4 14.0 17.2 20.9 11.1 855 40-44 66.1 1.0 2.0 14.4 16.4 18.4 13.8 1,007 45-49 67.5 1.1 2.8 13.7 18.4 21.2 10.4 1,149 Residence Urban 62.2 0.3 1.6 10.9 16.0 21.4 12.0 3,194 Rural 57.1 0.9 2.1 11.7 14.2 17.7 10.4 4,246 Region North 50.5 0.3 0.9 7.6 11.3 17.6 12.8 2,207 Center 61.6 1.1 3.1 13.6 16.9 17.5 9.4 2,033 South 64.4 1.0 2.3 15.1 17.4 20.0 8.7 1,402 Chisinau 63.5 0.3 1.3 10.6 15.6 22.9 12.9 1,798 Education No education/primary (63.8) (3.0) (4.9) (16.4) (6.6) (22.5) (10.4) 49 Secondary 57.4 0.7 2.0 11.6 14.5 18.2 10.4 4,534 Secondary special 62.1 0.6 2.1 11.9 15.4 20.1 12.0 1,327 Higher 62.2 0.5 1.0 10.2 16.5 21.5 12.5 1,530 Wealth quintile Lowest 58.0 1.5 3.6 13.7 15.5 15.4 8.3 1,243 Second 53.1 0.6 2.1 11.5 13.8 16.6 8.5 1,234 Middle 57.1 0.7 1.1 10.3 13.0 20.2 11.7 1,511 Fourth 60.8 0.3 1.6 11.1 15.2 19.2 13.3 1,672 Highest 64.8 0.4 1.3 10.7 17.0 23.1 12.3 1,780 Total 59.3 0.7 1.9 11.4 15.0 19.3 11.1 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. In general, women do not consume alcohol frequently—daily or almost daily consumption is reported by only about 3 percent, and alcohol consumption 1-2 times per week is reported by 11 percent of women. Nevertheless, women in the Center and South regions and those belonging to the less wealthy quintiles are the most likely to report daily or almost daily consumption of alcohol. One in ten females consumes alcohol less frequently than once in a month, without significant variations in background characteristics. Not only is the proportion of men who consume alcohol much higher than the proportion of women, but men who drink also tend to drink more frequently than women. For example, among the 81 percent of males that had an alcoholic drink in the month preceding the survey, practically none report consuming alcohol less frequently than once a month (Table 12.3.2). For females, however, among the 59 percent who report having had an alcoholic drink in the month preceding the survey, 11 percent of them usually consume alcohol less than once a month (Table 12.3.1). Adult Health | 165 Table 12.3.2 Use of alcohol: men Percentage of men who have had at least one alcoholic drink in the past month, and the usual frequency of drinking alcohol in a month, by background characteristics, Moldova 2005 Frequency of drinking in a month Background characteristic Has had at least one drink in the past month Every day Almost every day 1-2 times per week 2-3 times per month Once a month Less than once a month Number of men Age 15-19 69.2 2.1 3.6 28.7 21.6 13.2 0.0 411 20-24 78.2 2.1 7.6 42.4 16.3 9.8 0.0 275 25-29 82.5 3.0 13.7 43.6 17.0 5.2 0.0 234 30-34 84.3 2.0 11.8 45.3 16.5 8.8 0.0 224 35-39 82.8 3.4 14.0 46.2 16.5 2.2 0.4 248 40-44 87.6 5.3 14.9 45.3 16.6 5.4 0.0 247 45-49 87.4 3.7 19.3 43.6 14.0 6.7 0.0 349 50-54 81.9 6.3 17.0 38.3 13.7 6.6 0.0 296 55-59 78.6 7.8 15.4 40.5 10.7 4.2 0.0 224 Residence Urban 80.3 3.3 8.7 40.7 18.5 9.1 0.0 1,055 Rural 81.2 4.2 15.6 40.7 14.5 6.1 0.1 1,453 Region North 78.0 2.9 11.0 41.6 14.7 7.8 0.0 756 Center 82.2 4.7 17.5 38.0 14.8 7.1 0.1 702 South 83.3 3.6 15.9 43.8 15.6 4.5 0.0 496 Chisinau 80.5 4.2 6.0 40.2 20.4 9.7 0.0 554 Education No education/primary * * * * * * * 16 Secondary 80.5 3.9 13.6 41.3 15.2 6.5 0.1 1,788 Secondary special 80.5 4.2 14.0 37.0 18.0 7.4 0.0 302 Higher 82.0 3.5 8.0 40.4 19.3 10.8 0.0 403 Wealth quintile Lowest 83.8 4.3 14.4 46.7 12.7 5.6 0.0 450 Second 81.5 4.0 17.6 40.7 13.4 5.6 0.2 470 Middle 81.8 3.5 16.8 39.1 16.4 6.1 0.0 464 Fourth 77.9 4.2 11.7 38.4 15.8 7.7 0.0 561 Highest 79.8 3.3 4.7 39.5 21.4 10.9 0.0 563 Total 80.8 3.8 12.7 40.7 16.2 7.4 0.0 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. For males, alcohol consumption increases rapidly from 69 percent in the age group 15-19 to 83 percent in the age group 25-29, then registers a plateau with relatively little variation (83-88 percent) through age 50, and finally decreases gradually to 79 percent at age 55-59. Unlike females, there are no significant differences in alcohol consumption by residence, region, education, or wealth quintile. Males consume alcohol with greater frequency than females: 17 percent of males report daily or almost daily consumption and 41 percent have alcoholic drinks at least once a week. Daily or almost daily alcohol consumption increases with age and is much higher in rural areas than urban areas (20 percent and 12 percent, respectively) as well as in the Center and South regions. Males with higher education and those in the wealthiest quintile consume alcohol less frequently compared with other men. 166 | Adult Health Quantity of Alcohol Consumed Among respondents who consumed alcohol in the month prior to the survey, the average number of drinks consumed on a typical “drinking occasion” is about 2 drinks for females and 3 drinks for males, with no substantial difference by urban-rural residence. Males, therefore, consume approximately 50 percent more alcohol than females on such occasions (Figure 12.2). Frequency of Alcohol Use Female and male respondents were asked whether there had been any occasions in the 3 months preceding the survey when they had drunk more alcohol than usual, and if yes, how frequently they had con- sumed greater than usual quantities. Only 1 percent of females and less than 1 per- cent of males reported increased alcohol consumption daily or almost daily. Males, however, show a stronger tendency towards alcohol binging than females: 33 per- cent of males and 18 percent of females consume more than usual amounts of alcohol 1-2 times a week or 2-3 times a month. Eighty percent of females and 66 percent of males reported an increased consumption of alcohol once a month or less frequently. 12.4 TUBERCULOSIS Tuberculosis is caused by a bacterium called Mycobacterium Tuberculosis. The disease commonly affects the respiratory system but can strike other organisms in the body as well. When properly treated, tuberculosis is curable in most cases. If left untreated, however, the disease may have serious consequences and even ends in fatality for more than half of those affected. Tuberculosis is usually spread by the inhalation of tiny droplets containing the tuberculosis bacilli, discharged into the air by infected persons when coughing. Table 12.4 Drinking more alcohol than usual Percent distribution of women and men who drank more alcohol than usual on occasions in the past three months, by frequency of alcohol use, Moldova 2005 Women Men Number Every day/almost every day 1.1 0.5 0.8 1-2 times a week 3.9 7.5 5.9 2-3 times a month 14.5 25.6 20.7 Once a month 41.4 36.9 38.9 Less often 39.0 29.4 33.7 Total 100.0 100.0 100.0 Number 690 866 1,556 Figure 12.2 Average Number of Alcoholic Beverages Consumed by Females and Males on a Typical Drinking Occasion, by Residence 1.7 2.7 1.8 2.8 Females Males 0 1 2 3 Number of beverages Urban Rural MDHS 2005 Adult Health | 167 Tuberculosis is a major public health issue, accounting for over 3 million deaths annually worldwide (WHO, 1998). In 1993, the WHO declared tuberculosis a global emergency, and in 1994 it developed the DOTS strategy to combat the infection. According to WHO estimates, the European region accounts for approximately 6 percent of all cases of tuberculosis worldwide. While the incidence of tuberculosis in the western European countries continues to gradually diminish, the countries in Eastern Europe have seen tuberculosis morbidity double in the past 10 years; these countries account for over three-quarters of the total incidence in the region (WHO, 2002). High prevalence rates of the disease are associated with the socioeconomic crisis during the transition period, deterioration of the health system, co-infection with HIV/AIDS, the spread of multi-drug resistant infections, and deficiencies in combating tuberculosis among vulnerable sub-populations (de Colombani et al., 2003). Tuberculosis is a major public health problem for the Republic of Moldova due to high rates of morbidity and mortality, the continued tendency of tuberculosis infection rates to increase, and the unprecedented spread of multi-drug resistant strains detected in approximately 40 percent of the persons infected with tuberculosis (Crudu et al., 2003). According to medical statistics, in 2005, the occurrence of new cases was 107 cases per 100,000 persons, an increase of 2.5 times the incidence in 1992, the first full year of independence of the Republic of Moldova. Mortality over the same period has increased 2.8 times (from 6.3 per 100,000 persons in 1992 to 17.6 per 100,000 in 2005). The implementation of the DOTS strategy in 2001 has yet to result in an improvement or even a stabilization of the situation; the incidence has grown by one-third over the past five years. An important indicator that reveals the worsening of the epidemiologic situation during the period 2001-2005 is the increasing incidence of tuberculosis among youth age 12 to 29 years. Furthermore, the average incidence of tuberculosis in the past five years among those living in urban areas is 45 percent higher than among those living in rural locations. Among newly infected persons in 2005, 50 percent were able-bodied unemployed persons, 21 percent were employed, 12 percent were retired persons, and 7 percent were school children and students. In the MDHS, women and men were asked a series of questions related to the knowledge of tuberculosis symptoms, its means of transmission, its treatment, and the degree of stigma associated with the disease, i.e., the desire to conceal the fact that a family member is infected with tuberculosis. Awareness of Tuberculosis and its Means of Transmission Women and men were asked whether they had ever heard of the disease called tuberculosis or TB, and if yes, how they thought tuberculosis was spread from one person to another. Results related to awareness of tuberculosis and the means of transmission of the infection are presented in Table 12.5. There is a high degree of awareness of TB among the population: 98 percent of female and male respondents indicate that they have heard of tuberculosis. There are no significant differences for this indicator in terms of sex, age, residence, region, and level of education. Women and men from the poorest quintile, however, are slightly less informed about tuberculosis (96 and 94 percent, respectively). Despite the virtually universal degree of awareness, only 75 percent of female and 67 percent of male respondents who have heard of tuberculosis were able to name correctly the most prevalent way of transmission, that is, through the air which carries the virus that an infected person emits by coughing. Unlike the high degree of awareness of the disease, both women and men showed significant variations in their knowledge of the main way of transmitting tuberculosis depending on background characteristics. 168 | Adult Health Table 12.5 Knowledge of tuberculosis and its transmission modes Percentage of women and men who have heard of tuberculosis, and percentage who know tuberculosis modes of transmission, by background characteristics, Moldova 2005 Women Men Modes of transmission Modes of transmission Background characteristic Has heard of TB Through the air when coughing Reported other ways that TB spreads Don't know how TB spreads Number of women Has heard of TB Through the air when coughing Reported other ways that TB spreads Don't know how TB spreads Number of men Age 15-19 97.3 69.5 47.2 16.7 1,417 96.4 63.7 42.3 18.1 411 20-24 98.5 76.8 51.4 12.3 1,124 98.3 68.9 48.4 13.5 275 25-29 97.9 74.5 53.9 12.3 964 98.8 67.8 53.5 14.1 234 30-34 98.5 77.1 58.2 10.3 924 99.4 70.1 53.2 13.1 224 35-39 99.2 80.8 62.2 7.3 855 99.0 73.2 49.8 13.5 248 40-44 98.4 76.1 59.1 9.5 1,007 99.3 69.3 52.3 14.4 247 45-49 98.5 72.9 62.1 12.8 1,149 98.7 66.2 50.6 15.8 349 50-54 na na na na na 98.1 60.5 49.1 17.3 296 55-59 na na na na na 98.3 63.8 51.3 17.3 224 Residence Urban 99.2 83.2 54.9 8.4 3,194 99.7 77.6 51.5 10.1 1,055 Rural 97.6 68.7 56.3 14.7 4,246 97.4 58.8 48.0 19.4 1,453 Region North 98.6 73.7 55.2 13.8 2,207 97.6 64.9 47.5 18.8 756 Center 96.9 69.3 56.6 12.6 2,033 98.5 66.6 58.0 11.5 702 South 98.5 70.2 56.5 16.0 1,402 97.5 52.9 46.3 24.6 496 Chisinau 99.2 86.4 54.7 6.1 1,798 99.8 81.6 44.3 7.8 554 Education No education/primary (82.4) (53.1) (47.7) (22.2) 49 * * * * 16 Secondary 97.6 66.9 53.1 16.6 4,534 97.9 60.0 48.2 19.5 1,788 Secondary special 99.6 86.1 62.8 5.2 1,327 99.8 77.5 53.9 6.8 302 Higher 99.6 89.5 57.5 4.1 1,530 99.9 90.0 52.9 2.4 403 Wealth quintile Lowest 95.7 59.6 51.1 20.0 1,243 94.3 46.0 51.9 23.2 450 Second 97.1 67.7 56.9 15.4 1,234 97.7 55.2 46.7 22.3 470 Middle 98.9 72.7 58.6 13.0 1,511 99.6 68.8 52.3 14.6 464 Fourth 99.0 80.0 56.7 9.5 1,672 99.4 74.7 51.1 12.9 561 Highest 99.6 87.7 54.7 5.7 1,780 100.0 83.1 45.8 6.9 563 Total 98.3 74.9 55.7 12.0 7,440 98.3 66.7 49.5 15.5 2,508 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. na = Not applicable For example, female and male respondents age 35-39 years were most likely to correctly state the means of transmission; the youngest respondents, age 15-19, were least likely to identify the correct means of transmission. Females and males in urban areas (83 percent and 78 percent, respectively) are more aware of tuberculosis transmission than respondents in rural areas (69 percent and 59 percent, respectively). The level of awareness of the spread of tuberculosis increases with level of education and wealth quintile. Approximately 6 in 10 females and 5 in 10 males mentioned other ways of contracting tuberculosis, while 12 percent of female and 16 percent of male respondents said they had no knowledge of the ways tuberculosis is transmitted. Knowledge of the Symptoms of Tuberculosis Respondents who were aware of tuberculosis were subsequently asked what signs or symptoms suggest that a person might be infected with tuberculosis. Adult Health | 169 Tables 12.6.1 and 12.6.2 show that among those who have heard of tuberculosis and mentioned at least one symptom, 60 percent of females and 64 percent of males reported the nonspecific cough as a symptom; 29 percent and 22 percent, respectively, mentioned cough with sputum, and 20 percent and 17 percent, respectively, stated persistent cough over several weeks as a symptom. Other symptoms of tuberculosis most frequently mentioned by the female respondents were fever (20 percent), loss of body weight (20 percent), and lethargy (19 percent), while the male respondents named the loss of body weight (21 percent), fatigue (18 percent), and fever (15 percent). Among the symptoms least mentioned by both women and men were perspiration during the night (6 percent and 4 percent, respectively), thoracic pains (7 percent for both sexes), and loss of appetite (9 percent and 8 percent, respectively). Table 12.6.1 Knowledge of symptoms of tuberculosis: women Percentage of women who have heard of tuberculosis and know at least one symptom, by background characteristics, Moldova 2005 Knowledge of TB symptoms Background characteristic Non- specific coughing Coughing with sputum Coughing for several weeks Fever Blood in sputum Loss of appetite Night- sweating Pain in chest Tiredness/ fatigue Weight loss Lethargy Other Number of women Age 15-19 58.6 23.1 17.2 15.8 9.7 7.7 3.3 4.8 10.2 15.5 16.8 7.0 1,380 20-24 61.7 27.7 19.2 22.0 11.4 8.7 5.9 7.9 11.7 20.2 19.3 6.4 1,107 25-29 63.0 27.4 20.4 21.8 9.8 8.5 6.9 6.7 12.8 18.9 15.4 6.9 944 30-34 61.4 32.8 22.4 21.9 13.3 8.9 7.1 6.8 12.8 21.4 19.7 7.3 910 35-39 59.0 33.0 22.8 22.2 10.7 8.8 5.0 8.8 14.6 22.4 21.3 8.7 848 40-44 59.8 31.3 21.4 18.8 10.6 8.3 4.8 7.2 13.7 21.4 21.0 7.2 991 45-49 59.7 30.1 19.0 20.5 10.8 8.9 6.3 7.2 14.1 22.7 19.4 7.1 1,131 Residence Urban 61.6 32.9 22.2 22.4 12.7 8.3 7.3 6.9 15.3 22.8 17.8 5.8 3,168 Rural 59.4 25.8 18.5 18.5 9.4 8.6 4.1 7.0 10.7 18.0 19.6 8.2 4,142 Region North 60.8 26.7 19.0 18.8 9.8 8.4 4.0 7.7 12.1 20.0 20.6 9.6 2,176 Center 59.7 27.0 19.8 21.5 11.6 9.7 5.4 5.8 10.8 17.2 19.4 6.1 1,969 South 58.3 29.0 18.0 14.1 8.5 6.2 3.5 6.1 10.6 20.2 13.7 7.7 1,381 Chisinau 62.2 33.6 23.3 25.1 13.0 9.2 9.0 7.8 17.1 23.3 20.0 5.0 1,784 Education No education/primary (48.5) (24.9) (15.6) (21.7) (14.3) (8.0) (1.6) (0.0) (14.8) (6.6) (14.6) (0.0) 40 Secondary 58.3 24.0 17.0 15.9 9.3 7.2 3.0 5.5 10.2 16.3 15.9 6.8 4,423 Secondary special 62.7 37.0 24.8 26.9 13.4 11.2 8.2 10.0 16.6 26.2 23.9 7.5 1,322 Higher 64.7 36.2 24.9 26.6 13.0 10.0 10.6 8.4 16.5 26.2 23.3 8.3 1,524 Wealth quintile Lowest 58.1 20.1 14.7 14.1 6.3 5.6 2.7 4.8 8.1 13.1 17.7 8.9 1,190 Second 58.0 27.2 18.1 16.3 9.6 8.0 3.4 7.0 10.3 18.0 21.6 8.4 1,199 Middle 58.9 28.9 21.2 21.2 11.8 9.7 4.3 8.7 11.2 19.0 18.4 7.3 1,495 Fourth 61.1 31.9 22.1 22.1 11.3 9.1 6.5 6.1 14.2 21.8 19.0 6.7 1,655 Highest 64.0 33.0 22.1 24.2 13.4 9.3 8.8 7.5 17.2 25.6 17.9 5.5 1,772 Total 60.4 28.9 20.1 20.2 10.8 8.5 5.5 6.9 12.7 20.1 18.9 7.2 7,311 Note: Figures in parentheses are based on 25-49 unweighted cases. 170 | Adult Health Table 12.6.2 Knowledge of symptoms of tuberculosis: men Percentage of men who have heard of tuberculosis and know at least one symptom, by background characteristics, Moldova 2005 Knowledge of TB symptoms Background characteristic Non- specific coughing Coughing with sputum Coughing for several weeks Fever Blood in sputum Loss of appetite Night- sweating Pain in chest Tiredness/ fatigue Weight loss Lethargy Other Number of men Age 15-19 60.9 19.8 17.1 15.8 10.6 7.0 3.6 8.7 17.1 16.4 1.5 4.8 397 20-24 68.9 20.9 14.3 19.4 13.0 10.8 2.4 4.8 17.9 21.3 1.0 3.9 270 25-29 67.2 24.4 16.1 21.9 10.1 6.9 5.6 7.4 17.8 21.3 1.0 4.5 231 30-34 69.6 23.8 15.5 10.5 12.6 8.2 5.8 7.1 16.9 23.3 2.3 4.5 223 35-39 65.3 25.1 19.4 14.3 10.4 8.9 4.9 6.2 19.2 23.8 0.5 3.4 245 40-44 63.9 25.9 15.4 15.3 11.1 6.0 4.5 8.0 18.7 20.0 1.5 3.8 245 45-49 66.7 19.9 18.8 12.1 9.8 5.7 4.6 6.5 19.4 22.6 1.8 1.9 344 50-54 58.0 17.3 18.2 14.7 10.5 10.3 4.7 8.7 20.1 22.1 2.7 3.9 290 55-59 59.5 19.3 15.0 11.8 11.0 9.1 3.4 8.5 17.9 22.7 0.0 4.4 220 Residence Urban 67.3 28.8 14.1 20.0 14.9 9.1 6.1 10.3 21.0 22.4 1.7 3.3 1,051 Rural 61.9 16.1 18.8 11.4 8.0 7.2 3.0 5.2 16.4 20.3 1.2 4.3 1,415 Region North 63.2 21.4 18.1 15.1 8.5 7.1 3.0 6.4 15.1 22.4 2.3 4.3 738 Center 70.1 16.3 16.8 11.7 10.1 9.4 5.0 7.7 19.6 23.1 1.0 3.7 691 South 54.1 19.2 18.4 11.4 9.8 4.5 4.0 5.9 14.9 16.5 0.3 4.3 483 Chisinau 67.0 30.1 13.6 22.4 16.2 10.5 5.6 9.5 24.2 21.4 1.7 3.2 553 Education No education/primary * * * * * * * * * * * * 13 Secondary 62.1 18.1 15.8 11.5 9.0 6.8 3.1 6.0 15.8 19.0 1.0 4.2 1,750 Secondary special 68.6 23.1 20.9 21.5 11.5 11.8 4.9 11.4 22.7 25.3 0.7 1.7 301 Higher 70.2 35.6 18.4 25.8 19.3 10.9 9.5 10.4 26.7 28.5 4.0 4.3 402 Wealth quintile Lowest 62.7 10.9 17.2 7.0 5.4 4.7 1.5 3.3 13.2 19.6 0.4 2.0 424 Second 55.8 17.9 18.4 10.1 5.7 7.2 3.4 4.8 12.3 19.7 0.7 4.6 459 Middle 67.0 18.9 16.6 13.6 11.7 5.9 5.1 7.0 18.7 20.3 2.4 3.5 462 Fourth 64.1 25.8 18.6 16.7 12.7 10.3 4.4 8.1 21.7 24.5 1.3 4.5 558 Highest 70.0 30.4 13.5 24.8 17.0 10.6 6.5 12.1 23.7 21.1 2.0 4.4 563 Total 64.2 21.5 16.8 15.1 10.9 8.0 4.3 7.4 18.4 21.2 1.4 3.9 2,466 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Treatment of Tuberculosis and the Stigma Attached to the Disease Those respondents who have heard of tuberculosis were also asked whether they thought that tuberculosis was treatable. In addition, in order to evaluate the degree to which a person infected with tuberculosis might experience social stigma, respondents were also asked whether they would prefer to keep it a secret that a member of the family is infected with tuberculosis. Table 12.7 shows that women (74 percent) and men (75 percent) are equally aware that tuberculosis can be treated. The level of awareness is lower for the youngest age group (15-19). Awareness is also higher in urban areas, in particular in Chisinau, and it increases with level of education and wealth quintile. Adult Health | 171 Table 12.7 Knowledge of treatment of tuberculosis and attitude towards those with TB Percentage of women and men who know that tuberculosis (TB) can be completely cured, and the percentage willing to provide home care for a family member with TB, by background characteristics, Moldova 2005 Women Men Background characteristic Knows that TB can be completely cured Prefers that it be kept a secret that a family member has TB Number of women Knows that TB can be completely cured Prefers that it be kept a secret that a family member has TB Number of men Age 15-19 69.8 34.4 1,380 71.0 31.7 397 20-24 75.2 31.1 1,107 77.3 29.4 270 25-29 73.3 30.4 944 78.3 30.1 231 30-34 75.8 31.3 910 71.2 22.1 223 35-39 78.7 28.9 848 76.8 24.5 245 40-44 75.8 32.3 991 77.6 24.7 245 45-49 73.0 29.8 1,131 76.0 22.3 344 50-54 na na na 77.7 18.2 290 55-59 na na na 73.0 22.9 220 Residence Urban 76.8 34.3 3,168 80.4 33.2 1,051 Rural 72.1 29.1 4,142 71.5 19.5 1,415 Region North 74.6 32.2 2,176 73.5 23.0 738 Center 71.7 26.2 1,969 73.7 21.5 691 South 71.0 31.6 1,381 74.3 20.3 483 Chisinau 78.8 35.9 1,784 80.6 37.6 553 Education No education/primary (59.4) (12.6) 40 * * 13 Secondary 69.6 30.4 4,423 71.0 22.7 1,750 Secondary special 78.9 33.5 1,322 83.7 26.7 301 Higher 83.7 32.9 1,524 88.5 35.0 402 Wealth quintile Lowest 66.7 25.6 1,190 65.5 17.6 424 Second 72.8 29.4 1,199 74.0 23.7 459 Middle 74.3 30.0 1,495 75.3 17.3 462 Fourth 74.3 32.4 1,655 75.3 26.1 558 Highest 79.8 36.8 1,772 83.6 38.2 563 Total 74.2 31.4 7,311 75.3 25.3 2,466 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. na = Not applicable Results bring to light the stigmatized perception of tuberculosis by the population: 31 percent of females and 25 percent of males would prefer to keep it a secret that a member of their family is infected with tuberculosis. The stigma is more acute among the urban population, people with a higher level of education, and those in the wealthiest quintiles. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 173 HIV-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR 13 In the countries of Eastern Europe and Central Asia, the early stages of the HIV epidemic in the 1990s were mainly fuelled by intravenous drug users (IDUs) who transmitted the virus through the sharing of contaminated needles. In the new millennium, however, there is evidence of a changing pattern of infection, suggesting that the epidemic is gaining a foothold in the wider population. More countries in the region have started reporting a higher proportion of sexually transmitted HIV cases and a dispro- portionate number of young people infected (Hamers and Downs, 2003; Kelly and Amirkhanian, 2003). These changes have resulted in a faster growing epidemic. UNAIDS estimates that the number of adults and children living with HIV in Eastern Europe and Central Asia rose from 1.2 million at the end of 2003 to 1.6 million by the end of 2005. And, although the overall HIV prevalence among adults in the region is estimated to be only around 1 percent, the disease has spread most rapidly among young people whose sexually active years span before them. This results in a potentially longer stretch of time for uninfected persons to be exposed to risk through sexual contact with those who have the virus. Around 75 percent of the reported infections between 2000 and 2004 were among people younger than 30 years, where, in Western Europe, the corresponding figure was 33 percent (EuroHIV, 2005; UNAIDS/WHO, 2005). The HIV situation in Moldova reflects that of the larger region. Aside from isolated cases of HIV identified in the late 1980s, the onset of the epidemic is recognized to be 1996 (Government of Moldova, 2005). Initially in the postsocialist transition period, the disease was primarily spread by injecting drug users and, to a lesser extent, among the prison population (U.S. Census Bureau, 2005). After the late 1990s, however, the proportion of cases transmitted by injecting drug users began declining while the proportion of sexually transmitted cases began increasing. In 2003, for the first time, more new cases were reportedly due to infections transmitted by sexual contact than by IDUs—a signal that the disease has begun to spread among the general population (EuroHIV, 2005; UNAIDS/WHO, 2005). Concomitant with this crossover in infection modes, another shift was occurring in infection rates by sex. That is, until 2000, females represented only about one-quarter of all persons infected with HIV; by 2004, they represented 45 percent (UNICEF, 2005). With the overall adult HIV prevalence rate in Moldova estimated to be about 0.2 percent at the end of 2003 (about 5,500 people living with HIV), the epidemic is still in an early stage (UNAIDS, 2004). This means that, with effective interventions, there is reason for optimism that the country might reach its stated goal of reversing and even halting the epidemic by 2015.1 However, the future direction of the HIV epidemic depends on the level of knowledge of how the virus is spread and vigilance in practicing safe sexual behavior. This chapter presents findings on current levels of knowledge, attitudes, and behaviors related to the spread of HIV for the general adult population of Moldova and for youth, as the latter are the main target of many HIV prevention efforts.2 Based on the findings presented here, HIV control programs can target particular groups of people most in need of information and services and most vulnerable to the risk of HIV infection. 1 Millennium Development Goal No. 6, Target 7: “Combat HIV/AIDS, TB and Malaria” by 1) Preventing and decreasing the spread of HIV/AIDS by 2015; 2) Reducing HIV/AIDS cases from 4.66 (per 100,000 people) in 2002 to 4 in 2006, to 3.5 in 2010, and to 3.2 in 2015; and 3) Reducing HIV cases among young people age 15-24 from 6 in 2002 to 4.9 in 2006, to 4.2 in 2010, and to 4 in 2015 (Government of Moldova, 2005). 2 MDHS results on HIV knowledge are presented for women age 15-49, and for men age 15-49 and age 15-59 (men age 15-59 were interviewed). However, for reasons of comparability between the sexes, comparisons between men and women are made for one standard age group, age 15-49. 174 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior 13.1 KNOWLEDGE OF HIV TRANSMISSION AND PREVENTION METHODS Awareness of AIDS Table 13.1 shows that the knowledge of AIDS is widespread in Moldova—97 percent of women and men have heard of AIDS. At least 92 percent of all respondents, regardless of background characteristics, have heard of the epidemic. Note that the number of respondents with no education or only primary education is too low to interpret these differentials with confidence. This is generally the case for all tables in this chapter where education levels are presented. Table 13.1 Knowledge of AIDS Percentage of women and men who have heard of AIDS, by background characteristics, Moldova 2005 Women Men Background characteristic Has heard of AIDS Number of women Has heard of AIDS Number of men Age 15-19 96.8 1,417 97.1 411 20-24 98.8 1,124 98.6 275 25-29 97.5 964 97.0 234 30-39 97.9 1,778 99.0 472 40-49 96.7 2,156 95.9 596 15-24 97.7 2,541 97.7 686 Marital status Never married 97.2 1,862 97.8 720 Ever had sex 99.1 447 99.1 459 Never had sex 96.6 1,415 95.4 260 Married/living together 97.5 4,937 97.1 1,189 Divorced/separated/ widowed 97.5 641 98.1 80 Residence Urban 99.2 3,194 98.9 857 Rural 96.1 4,246 96.3 1,132 Region North 97.7 2,207 97.5 582 Center 95.3 2,033 97.2 553 South 97.7 1,402 94.6 388 Chisinau 99.2 1,798 99.8 466 Education No education/primary (72.5) 49 * 14 Secondary 96.2 4,534 96.8 1,433 Secondary special 99.8 1,327 100.0 214 Higher 99.9 1,530 99.6 328 Wealth quintile Lowest 91.9 1,243 94.1 349 Second 95.6 1,234 94.9 352 Middle 98.7 1,511 98.6 366 Fourth 99.1 1,672 98.7 452 Highest 99.9 1,780 99.5 470 Total 15-49 97.4 7,440 97.4 1,989 Total men 15-59 na na 96.8 2,508 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. na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 175 Knowledge of Ways to Reduce AIDS Transmission The most common routes of HIV transmission are through the exchange of body fluids during sexual intercourse and through the sharing of needles by injecting drug users. Commercial sex workers and injecting drug users are, therefore, considered to be higher-risk groups for both infection and transmission of sexually transmitted diseases, including HIV. For the general population, many HIV prevention programs aim to reduce transmission by focusing their messages and efforts on three important aspects of behavior summed up in the ABC approach: absti- nence (outside of marriage), be faithful (to one partner), and use condoms (in higher-risk sexual relationships) (Shelton et al., 2004). To ascertain whether programs are effectively communicating these messages, respondents were prompted with specific questions about whether it is possible to reduce the chance of getting the AIDS virus by having just one faithful sexual partner, using a condom at every sexual encounter, and abstaining from sex. The MDHS asked respondents whether there is anything one can do to avoid becoming infected with HIV. Table 13.2 shows that when asked to spontaneously mention ways to avoid contracting the AIDS virus, 15 percent of women and 40 percent of men say that it is unavoidable. Among women, condom use is the most commonly mentioned ways of avoiding HIV (15 percent), followed closely by faithfulness to one partner and limiting sex to one partner (14 percent), and abstinence (11 percent). Avoiding sex with prostitutes and drug users was also high on the list of way to avoid HIV, with 9 percent each. Similarly, among men, the use of condoms is the most commonly mentioned method to avoid HIV infection (13 percent), followed by being faithful and limiting sex to one partner (8 percent), and abstinence, limiting number of sexual partners, avoiding sex with prostitutes and avoiding injections (7-8 percent each). Comparing the 2005 MDHS results with those from the 1997 MRHS, the same general pattern is seen.3 The use of condoms was the most common spontaneously mentioned way to avoid AIDS (60 percent), followed by monogamy and the use of clean needles (almost 50 percent each), with avoiding sex with prostitutes and homosexuals mentioned by one in five respondents (each method). Note that for questions that elicit spontaneous responses, caution should be taken in interpreting reported differences in response rates over time. For example, a respondent may not report spontaneously because of lack of recall at the time of the interview. 3 Several indicators reported in this chapter are similar to ones estimated in the 1997 Moldova Reproductive Health Survey (MRHS). However, there are important differences between the two surveys that preclude exact comparability between the 1997 MRHS and the MDHS. First, the 1997 MRHS includes Transnistria region in its sample whereas the MDHS does not. Second, although key indicators may be the same, the wording of certain questions to collect information to calculate the indicators may differ between the surveys. Third, the denominators may not be exactly the same. One example of different denominators is that the 1997 MRHS reports values based on women age 15-44 while MDHS indicators reports values based on women age 15-49. Table 13.2 Knowledge of ways to avoid HIV/AIDS Percentage of women and men who have heard of AIDS and who spontaneously mentioned ways to avoid HIV/AIDS, Moldova 2005 Ways to avoid HIV/AIDS Women Men Believes no way to avoid AIDS 15.0 39.7 Abstain from sex 10.8 7.1 Use condoms 15.3 13.1 Limit sex to one partner/stay faithful to one partner 13.6 8.3 Limit number of sexual partners 10.3 7.0 Avoid sex with prostitutes 8.8 7.5 Avoid sex with persons who have many partners 5.6 3.5 Avoid sex with homosexuals 4.9 2.4 Avoid sex with drug users 8.8 4.3 Avoid blood transfusions 7.4 3.8 Avoid injections 7.3 6.7 Avoid sharing razors/ blades 5.0 3.3 Avoid kissing 1.1 0.5 Avoid mosquito bites 0.6 0.3 Seek protection from traditional healer 0.2 0.1 Other ways 2.6 1.9 Total 15-49 7,440 1,989 Total men 15-59 na 2,508 na = Not applicable 176 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.3 shows results on levels of knowledge of HIV prevention methods, obtained by asking questions on specific methods. Approximately 8 in 10 women and 9 in 10 men say that chances of getting the AIDS virus can be reduced by using condoms every time they have sexual intercourse. About the same proportion say that limiting sex to one uninfected partner who has no other partners can reduce chances of infection. Approximately 4 of 5 respondents know that condoms can reduce the risk of contracting the HIV virus during sexual intercourse. Notably, while only 3 in 5 women cite abstaining from sex as an HIV prevention method, 4 in 5 men cite this method. The HIV prevention method most widely known by both women and men is limiting sex to one uninfected partner. Table 13.3 Knowledge of HIV prevention methods Percentage of women and men who, in response to prompted questions, say that people can reduce the risk of contracting the AIDS virus by using condoms, by having sex with just one partner who is not infected and who has no other partners, and by abstaining from sex, by background characteristics, Moldova 2005 Women Men Background characteristic Using condoms1 Limiting sex to one uninfected partner2 Using condoms and limiting sex to one uninfected partner Abstaining from sex Number of women Using condoms1 Limiting sex to one uninfected partner2 Using condoms and limiting sex to one uninfected partner Abstaining from sex Number of men Age 15-19 77.0 79.4 69.7 64.3 1,417 87.5 87.5 82.4 81.6 411 20-24 82.4 83.3 75.9 65.2 1,124 92.4 91.0 87.4 87.8 275 25-29 79.8 83.0 74.8 61.8 964 86.4 89.7 82.6 83.9 234 30-39 81.3 83.6 75.7 64.1 1,778 90.1 91.5 85.8 88.1 472 40-49 73.6 78.8 68.3 61.4 2,156 81.5 85.7 77.4 83.6 596 15-24 79.4 81.1 72.4 64.7 2,541 89.5 88.9 84.4 84.1 686 Marital status Never married 79.4 82.1 72.9 64.6 1,862 88.9 88.6 84.0 84.5 720 Ever had sex 84.0 85.0 77.6 63.6 447 90.8 91.4 86.1 87.9 459 Never had sex 77.9 81.2 71.3 64.9 1,415 85.7 83.5 80.3 78.5 260 Married/living together 78.2 81.6 72.7 63.3 4,937 85.8 88.5 81.6 85.5 1,189 Divorced/separated/ widowed 74.8 76.5 68.2 58.5 641 84.5 90.7 79.8 78.2 80 Residence Urban 84.9 87.3 79.3 65.1 3,194 92.6 92.1 88.3 90.2 857 Rural 73.2 76.8 67.1 61.8 4,246 82.5 86.0 77.9 80.8 1,132 Region North 77.3 80.4 71.4 62.9 2,207 86.2 89.5 82.9 86.7 582 Center 74.5 77.3 68.2 62.3 2,033 87.8 88.5 82.8 84.8 553 South 75.3 80.5 70.5 60.5 1,402 80.8 85.8 77.4 79.5 388 Chisinau 85.8 87.6 79.7 66.7 1,798 91.7 90.1 85.4 87.2 466 Education No education/primary (47.4) (58.4) (44.5) (40.9) 49 * * * * 14 Secondary 71.2 74.8 64.1 58.6 4,534 84.3 86.5 79.2 81.7 1,433 Secondary special 87.9 90.1 83.7 70.6 1,327 94.6 97.7 93.8 95.2 214 Higher 91.6 93.7 87.8 71.2 1,530 94.8 95.0 91.5 94.5 328 Wealth quintile Lowest 58.5 64.1 52.4 48.6 1,243 71.6 75.8 64.0 72.3 349 Second 71.8 76.7 65.5 62.7 1,234 84.4 85.5 79.5 81.5 352 Middle 79.5 81.5 72.9 66.0 1,511 90.1 92.5 86.5 87.3 366 Fourth 84.4 87.2 79.0 68.1 1,672 89.6 93.5 87.7 89.7 452 Highest 89.5 90.8 84.2 66.9 1,780 95.0 92.8 90.1 90.2 470 Total 15-49 78.2 81.3 72.3 63.2 7,440 86.9 88.6 82.4 84.9 1,989 Total men 15-59 na na na na na 84.8 86.9 80.1 84.1 2,508 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. na =Not applicable 1 Every time they have sexual intercourse 2 Who has no other partner HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 177 Table 13.3 also shows that, across respondents, there are notable differences in knowledge of HIV prevention. While age differentials in prevention methods are not significant, there is about a 10 percentage point difference in the level of knowledge of all prevention methods between urban and rural residents, with rural residents less likely to know HIV prevention methods. As expected, women and men with higher levels of schooling are significantly more likely than those with lower levels of schooling to be aware of various preventive methods. Notably, the level of knowledge of HIV prevention methods does not vary significantly by marital status. Misconceptions Associated with HIV/AIDS The MDHS asked about common misconceptions about AIDS and HIV transmission. Respondents were asked whether they think it is possible for a healthy-looking person to have the AIDS virus and whether a person can get AIDS through sharing food with a person who has AIDS. Results for women and men are presented in Tables 13.4.1 and 13.4.2. The vast majority of people in Moldova know that persons infected with HIV do not necessarily show signs of infection. Overall, 76 percent of women and 81 percent of men know that a healthy-looking person can have the virus that causes AIDS. Notably, for women the level of knowledge did not change compared with the 1997 RHS survey in which 79 percent of women said that HIV infection could be asymptomatic. Currently, there are no substantial age variations by level of knowledge either for women or men, except in the oldest age group where men and women age 40-49 are less likely to know about AIDS than younger men and women. Women and men with higher levels of schooling, those from the wealthier quintiles, and those in urban areas are more likely than other respondents to know that a healthy-looking person can have the AIDS virus. Regionally, the level of knowledge is highest in Chisinau (84 percent for women and 90 percent for men), with the lowest being in the Center region for women (74 percent) and the South region for men (78 percent). Fewer respondents know that HIV infection is not transmitted by sharing food with a person who has HIV (57 percent of women and 60 percent of men). There is no significant difference in knowledge by sex. The pattern of variations in the level of knowledge about the asymptomatic nature of the AIDS virus is similar to, but stronger than, the patterns of variations in knowledge about the misconception that HIV can be transmitted through sharing food: women and men with higher levels of schooling, those from the wealthier quintiles, and those in urban areas are more likely than other respondents to know that AIDS cannot be transmitted through sharing food. While only about half of women and men with secondary education know that HIV/AIDS is not transmitted through food, around four of five respondents with higher education know of it. In the same way, only half of women and men in rural areas reject the misconception, compared with about 70 percent in urban areas. General knowledge of HIV/AIDS (column 3 in Tables 13.4.1 and 13.4.2) is defined as: 1) know- ing that both condom use and limiting sex partners to one uninfected partner are HIV prevention methods; 2) being aware that a healthy-looking person can have HIV; and 3) rejecting the misconception that HIV/AIDS can be transmitted through sharing food. Approximately half of the respondents have general knowledge of HIV/AIDS transmission and prevention methods: 42 percent of women and 51 percent of men. General knowledge is related to age, education, wealth, and residence. Those in the youngest age group (15-19) and in the oldest age group (40-49) are least likely to have general knowledge of HIV/ AIDS transmission and prevention methods. As expected, women and men with higher levels of schooling, those in the wealthier quintiles, and those in urban areas are more likely than other respondents to have general knowledge of HIV/AIDS. 178 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.4.1 Misconceptions and general knowledge about AIDS: women Percentage of women age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to a prompted question, correctly reject a common misconception about AIDS transmission, and the percentage with general knowledge about AIDS, by background characteristics, Moldova 2005 Percentage of women who know that: Background characteristic A healthy- looking person can have the AIDS virus A person cannot become infected by sharing food with someone with AIDS1 Percentage with general knowledge about AIDS2 Number of women Age 15-19 74.0 55.3 37.9 1,417 20-24 79.7 62.1 46.3 1,124 25-29 76.7 56.3 43.3 964 30-39 78.3 60.8 46.6 1,778 40-49 71.7 51.5 36.3 2,156 15-24 76.5 58.3 41.6 2,541 Marital status Never married 76.7 61.8 44.1 1,862 Ever had sex 79.9 69.5 51.5 447 Never had sex 75.7 59.4 41.7 1,415 Married/living together 75.5 54.9 40.9 4,937 Divorced/separated/ widowed 73.1 55.4 38.1 641 Residence Urban 82.6 67.7 51.6 3,194 Rural 70.3 48.4 33.9 4,246 Region North 76.0 54.5 39.8 2,207 Center 69.3 51.3 36.2 2,033 South 72.7 53.4 38.9 1,402 Chisinau 84.4 67.9 51.6 1,798 Education No education/primary (45.1) (35.2) (24.4) 49 Secondary 68.3 46.1 29.7 4,534 Secondary special 84.6 67.8 54.1 1,327 Higher 90.2 79.1 65.9 1,530 Wealth quintile Lowest 57.8 32.6 18.9 1,243 Second 67.0 46.0 29.8 1,234 Middle 76.6 56.2 41.0 1,511 Fourth 81.4 67.0 50.9 1,672 Highest 87.7 71.5 56.9 1,780 Total 15-49 75.6 56.7 41.5 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 A common misconception is the belief that the AIDS virus can be contracted by sharing food. 2 Respondents with general knowledge of AIDS are those who say that using a condom for every sexual intercourse and having just one uninfected and faithful partner can reduce the chance of getting the AIDS virus, and say that a healthy-looking person can have the AIDS virus, and who reject the common misconception that HIV can be spread by sharing food with someone with AIDS. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 179 Table 13.4.2 Misconceptions and general knowledge about AIDS: men Percentage of men age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to a prompted question, correctly reject a common misconception about AIDS transmission, and the percentage with general knowledge about AIDS, by background characteristics, Moldova 2005 Percentage of men who know that: Background characteristic A healthy- looking person can have the AIDS virus A person cannot become infected by sharing food with someone with AIDS1 Percentage with general knowledge about AIDS2 Number of men Age 15-19 76.9 62.6 50.4 411 20-24 84.1 68.6 60.3 275 25-29 83.7 62.6 50.5 234 30-39 84.0 62.9 54.4 472 40-49 78.2 52.2 43.7 596 15-24 79.8 65.0 54.3 686 Marital status Never married 80.5 66.1 54.8 720 Ever had sex 85.9 71.4 61.3 459 Never had sex 70.8 56.7 43.2 260 Married/living together 81.2 57.6 48.8 1,189 Divorced/separated/ widowed 78.4 50.4 42.3 80 Residence Urban 88.5 73.4 63.2 857 Rural 74.9 50.5 41.2 1,132 Region North 80.5 57.7 50.5 582 Center 78.0 58.3 48.3 553 South 74.4 49.0 39.0 388 Chisinau 89.7 75.6 63.6 466 Education No education/primary * * * 14 Secondary 75.6 52.9 42.3 1,433 Secondary special 94.9 74.4 68.2 214 Higher 96.8 85.9 77.6 328 Wealth quintile Lowest 58.3 35.7 24.4 349 Second 79.0 47.2 38.0 352 Middle 82.8 60.1 52.0 366 Fourth 86.5 69.1 60.3 452 Highest 91.7 80.4 69.6 470 Total 15-49 80.8 60.4 50.7 1,989 Total men 15-59 78.3 58.4 48.4 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 A common misconception involves the belief that the AIDS virus can be contracted by sharing food. 2 Respondents with general knowledge of AIDS are those who say that using a condom for every sexual intercourse and having just one uninfected and faithful partner can reduce the chance of getting the AIDS virus, and say that a healthy- looking person can have the AIDS virus, and who reject the common misconception that HIV can be spread by sharing food with someone with AIDS. 180 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Knowledge about Mother-to-Child Transmission Increasing the level of general knowledge of transmission of HIV from mother to child is critical to reducing mother-to-child transmission (MTCT) during pregnancy, delivery, and through breastfeeding. Respondents in the 2005 MDHS were asked if the virus that causes AIDS can be transmitted from a mother to a child during pregnancy, delivery, and breastfeeding (Table 13.5). Table 13.5 Knowledge of prevention of mother-to-child transmission of HIV Percentage of women and men who know that HIV can be transmitted from mother to child during pregnancy, during delivery, and by breastfeeding, by background characteristics, Moldova 2005 Women Men Background characteristic During pregnancy During delivery During breastfeeding Number of women During pregnancy During delivery During breastfeeding Number of men Age 15-19 80.6 73.4 63.9 1,417 71.4 63.6 45.9 411 20-24 87.8 83.3 67.9 1,124 83.6 80.8 52.7 275 25-29 88.7 84.0 68.9 964 79.7 77.5 51.7 234 30-39 89.6 86.9 70.4 1,778 83.4 81.2 54.8 472 40-49 85.0 82.1 67.2 2,156 78.3 77.8 56.3 596 Marital status Never married 82.7 76.6 64.4 1,862 75.3 69.9 47.2 720 Ever had sex 87.6 80.8 70.2 447 81.1 76.0 49.1 459 Never had sex 81.2 75.3 62.6 1,415 65.0 59.1 43.8 260 Married/living together 87.4 83.9 69.0 4,937 81.0 79.3 55.9 1,189 Divorced/separated/ widowed 86.8 83.5 66.8 641 82.4 83.2 56.5 80 Residence Urban 90.8 86.6 67.1 3,194 82.8 80.9 49.7 857 Rural 82.7 78.6 68.1 4,246 76.1 72.3 55.1 1,132 Region North 85.4 81.7 68.7 2,207 80.3 78.9 57.2 582 Center 82.7 78.2 66.6 2,033 76.3 73.6 54.0 553 South 84.6 80.4 67.2 1,402 75.5 70.6 55.0 388 Chisinau 92.3 88.1 68.0 1,798 83.4 79.9 43.9 466 Education No education/[primary (62.1) (52.6) (49.6) 41 * * * 14 Secondary 81.8 76.6 65.5 4,534 75.8 71.4 53.3 1,433 Secondary special 92.4 90.5 73.3 1,327 90.7 92.6 51.4 214 Higher 94.4 91.6 69.7 1,530 88.1 88.2 53.0 328 Wealth quintile Lowest 73.8 69.2 60.7 1,243 68.1 62.4 54.0 349 Second 81.0 77.6 67.3 1,234 75.2 71.4 57.6 352 Middle 88.0 83.2 70.6 1,511 82.3 80.5 55.3 366 Fourth 89.7 86.3 70.6 1,672 82.5 81.5 52.9 452 Highest 93.4 89.0 67.6 1,780 83.9 81.0 46.0 470 Total 15-49 86.2 82.0 67.7 7,440 79.0 76.0 52.7 1,989 Total men 15-59 na na na na 78.2 75.9 54.0 2,508 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. na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 181 The majority of respondents know about different transmission modes of MTCT, with a larger proportion of women compared to men: more than 4 in 5 women know that HIV can be transmitted during pregnancy and delivery, while slightly less than 4 in 5 men know. A smaller proportion of respondents are aware of MTCT during breastfeeding: 68 percent of women and only 53 percent of men. There is not a consistent pattern of knowledge of MTCT among women and men by level of educational attainment and wealth. For instance, there is a gap of almost 15 percentage points in knowledge of MTCT during pregnancy and delivery among women and men with secondary education compared with those with higher education; however, level of education does not appear to be a factor in knowledge of MTCT through breastfeeding. Urban women and men have higher levels of knowledge of MTCT during pregnancy and delivery than rural women and men, but there is little difference in the knowledge of MTCT knowledge during breastfeeding. 13.2 STIGMA AND ATTITUDES RELATED TO HIV/AIDS Knowledge and beliefs about AIDS affect how people treat those who they know to be living with HIV. In the 2005 MDHS, women and men who have heard of AIDS were asked questions to assess the level of stigma associated with HIV/AIDS. Results shown in Tables 13.6.1 and 13.6.2 indicate that most women would be willing to care for a relative with AIDS (76 percent) at home. A smaller proportion (61 percent) would not keep the HIV- positive status of a family member a secret, but only 28 percent believe that an HIV-positive female teacher should be allowed to continue teaching. Men are generally less accepting than women: about half of men would take care of a family member with AIDS at home (55 percent), and one-fifth believe that an HIV-positive female teacher should be allowed to continue teaching (23 percent). Men are also less likely than women to not want the HIV status of a family member to be kept a secret (51 percent). Only about 1 in 10 women and men would buy fresh food from a shopkeeper with AIDS. The reported acceptance on all four indicators is low for both sexes: only 5 percent of women and 3 percent of men said they would care for an HIV-positive family member in their own home, buy fresh food from a shopkeeper with AIDS, allow an HIV-positive teacher to continue teaching, and would not keep the HIV-positive status of a family member a secret. Accepting attitudes toward those who are HIV positive are related to education, wealth, and residence. Among women and men, the higher the educational attainment and the wealthier the household, the more likely respondents are to show acceptance on each of the four independent indicators. Respondents in urban areas are about twice as likely as those in rural areas to show acceptance on all four indicators. 182 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.6.1 Accepting attitudes toward those living with HIV: women Among women who have heard of HIV/AIDS, percentage expressing specific accepting attitudes toward people with HIV, by background characteristics, Moldova 2005 Percentage of women who: Background characteristic Are willing to care for family member with HIV at home Would buy fresh vegetables from shopkeeper with AIDS Believe HIV- positive female teacher should be allowed to teach Would not want HIV+ status of family member to remain secret Percentage expressing acceptance on all 4 measures Number of women who have heard of HIV/AIDS Age 15-19 76.6 14.1 34.0 59.5 6.0 1,371 20-24 71.8 12.2 32.4 61.2 5.3 1,110 25-29 74.0 13.1 28.4 61.4 6.7 940 30-39 76.5 10.5 27.6 64.5 5.3 1,741 40-49 77.7 8.0 22.7 59.2 3.4 2,085 15-24 74.4 13.2 33.3 60.3 5.7 2,482 Marital status Never married 78.2 15.3 37.2 62.5 6.6 1,811 Ever had sex 81.6 16.4 40.5 64.1 9.0 443 Never had sex 77.1 14.9 36.2 62.0 5.9 1,368 Married/living together 75.2 9.6 25.7 60.5 4.6 4,812 Divorced/separated/ widowed 73.5 9.5 21.6 61.9 4.4 625 Residence Urban 78.1 14.4 36.4 68.4 7.7 3,169 Rural 74.0 8.4 21.9 55.4 3.0 4,079 Region North 74.0 9.9 24.7 60.7 3.9 2,156 Center 75.6 9.9 25.7 52.9 4.1 1,938 South 78.2 9.6 25.0 65.1 4.2 1,371 Chisinau 76.4 14.7 37.8 67.5 8.3 1,784 Education No education/primary (71.9) (7.3) (21.1) (35.4) (7.3) 35 Secondary 73.7 8.4 21.1 56.0 3.1 4,359 Secondary special 76.6 10.1 31.3 65.4 5.0 1,324 Higher 81.3 19.4 46.1 72.5 10.8 1,529 Wealth quintile Lowest 70.0 5.7 15.3 50.9 1.2 1,143 Second 73.1 7.1 19.8 52.7 2.4 1,180 Middle 75.0 10.2 24.9 57.7 3.9 1,491 Fourth 79.4 13.1 33.7 67.1 6.8 1,657 Highest 78.7 15.9 39.8 70.7 8.7 1,777 Total 15-49 75.8 11.0 28.2 61.1 5.1 7,248 Note: Figures in parentheses are based on 25-49 unweighted cases. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 183 Table 13.6.2 Accepting attitudes toward those living with HIV: men Among men who have heard of HIV/AIDS, percentage expressing specific accepting attitudes toward people with HIV, by background characteristics, Moldova 2005 Percentage of men who: Background characteristic Are willing to care for family member with HIV at home Would buy fresh vegetables from shopkeeper with AIDS Believe HIV- positive female teacher should be allowed to teach Would not want HIV+ status of family member to remain secret Percentage expressing acceptance on all 4 measures Number of men who have heard of HIV/AIDS Age 15-19 51.2 11.3 27.2 56.4 3.8 399 20-24 55.3 12.1 25.7 51.2 4.0 271 25-29 54.7 13.6 26.6 55.3 3.6 227 30-39 57.5 11.0 24.4 50.7 3.2 468 40-49 56.2 8.2 17.3 50.1 2.7 571 15-24 52.9 11.6 26.6 54.3 3.9 671 Marital status Never married 52.7 12.4 27.4 55.2 4.0 703 Ever had sex 57.8 13.7 28.7 57.3 4.9 455 Never had sex 43.3 10.0 25.0 51.4 2.4 248 Married/living together 56.8 9.7 20.7 50.5 2.9 1,155 Divorced/separated/ widowed 54.5 10.2 26.0 52.6 3.3 79 Residence Urban 59.2 16.3 30.9 66.0 5.8 848 Rural 52.1 6.4 17.5 41.7 1.4 1,089 Region North 52.4 9.9 22.3 49.9 2.6 567 Center 54.4 6.8 19.7 48.5 2.9 538 South 57.9 9.0 17.7 43.2 1.5 367 Chisinau 57.5 17.5 33.3 66.9 6.1 465 Education No education/primary * * * * * 9 Secondary 52.1 7.9 18.5 48.8 2.4 1,388 Secondary special 59.5 9.4 29.8 56.1 2.2 214 Higher 65.9 23.6 40.2 64.8 8.2 326 Wealth quintile Lowest 44.2 4.2 13.8 33.3 1.1 329 Second 50.1 8.8 17.4 46.9 1.4 334 Middle 56.3 5.3 19.1 44.2 1.1 361 Fourth 58.8 13.9 25.2 60.5 4.1 446 Highest 62.3 17.7 35.7 68.0 7.3 467 Total 15-49 55.2 10.7 23.3 52.3 3.3 1,937 Total men 15-59 55.6 9.7 21.6 50.6 3.0 2,429 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Attitudes toward Negotiating and Teaching Safer Sex Knowledge about HIV transmission and ways to prevent HIV/AIDS are of little use if people feel powerless to negotiate safer sex practices with their partners. In an effort to assess the ability of women to negotiate safer sex with a spouse who has a sexually transmitted disease (STI), respondents were asked two attitudinal questions: 1) whether a wife is justified in refusing to have sex with her husband when she knows he has a disease that can be transmitted through sexual contact; and 2) whether a wife in the same circumstances is justified in asking her husband to use a condom. 184 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Ninety-five percent of women and 97 percent of men believe that a woman may either refuse to have sex with her husband or ask him to wear a condom if she knows he has an STI (Table 13.7). Approximately 9 in 10 women and men say that a woman is justified in refusing to have sex, and 91 percent of women and 94 percent of men say that she is justified in proposing to use a condom. Young women and men, age 15-19, are less likely than others to express accepting attitudes toward negotiating safer sex. The higher a respondent’s educational attainment, the more likely he or she is to say that a woman can refuse sex or propose using a condom. Women and men living in wealthier households are also more likely than those in poorer households to support women’s negotiating rights. The gender differences are not pronounced, and the overall sociodemographic variations are not significant. Never- married women and men who have had sex are slightly more likely to support women’s negotiating rights than those who have never had sex. Table 13.7 Attitudes toward negotiating safer sex with husband Percentage of women and men who believe that if a husband has a sexually transmitted disease his wife is justified in either refusing to have sex with him or asking that they use a condom, by background characteristics, Moldova 2005 Women Men Background characteristic Refuse sex Propose condom use Refuse sex or propose condom use Number of women Refuse sex Propose condom use Refuse sex or propose condom use Number of men Age 15-19 85.3 85.9 90.6 1,417 85.6 91.3 94.6 411 20-24 93.0 93.5 97.0 1,124 94.0 98.3 98.7 275 25-29 93.6 93.9 97.1 964 93.3 95.8 98.9 234 30-39 93.5 93.6 96.8 1,778 93.0 95.4 98.3 472 40-49 89.9 87.9 94.5 2,156 91.4 93.5 97.0 596 15-24 88.7 89.3 93.4 2,541 89.0 94.1 96.3 686 Marital status Never married 87.2 88.0 92.2 1,862 88.0 93.7 96.1 720 Ever had sex 90.4 92.2 95.1 447 91.1 97.3 98.5 459 Never had sex 86.2 86.6 91.3 1,415 82.5 87.3 91.8 260 Married/living together 92.5 91.6 96.3 4,937 93.2 95.1 98.1 1,189 Divorced/separated/ widowed 89.1 89.6 93.8 641 90.1 91.2 95.8 80 Residence Urban 93.0 94.1 97.5 3,194 93.0 96.7 99.1 857 Rural 89.2 87.8 93.2 4,246 89.8 92.7 95.9 1,132 Region North 92.3 91.8 95.6 2,207 92.4 93.5 96.2 582 Center 88.3 87.6 92.8 2,033 92.4 95.3 97.5 553 South 91.0 88.7 94.7 1,402 88.4 91.6 96.2 388 Chisinau 91.9 93.6 97.2 1,798 90.6 96.8 99.2 466 Education No education/primary (73.1) (68.3) (78.6) 49 * * * 14 Secondary 88.4 87.2 93.1 4,534 89.6 93.2 96.6 1,433 Secondary special 94.8 95.9 98.2 1,327 97.3 96.4 99.4 214 Higher 95.3 96.2 98.6 1,530 95.4 100.0 100.0 328 Wealth quintile Lowest 86.4 81.6 90.7 1,243 84.9 87.8 93.3 349 Second 87.9 87.0 91.9 1,234 88.5 94.3 96.1 352 Middle 91.6 91.8 95.3 1,511 94.3 93.7 97.2 366 Fourth 92.2 92.8 96.6 1,672 94.0 96.4 98.9 452 Highest 94.2 95.8 98.6 1,780 92.8 98.2 99.6 470 Total 15-49 90.8 90.5 95.0 7,440 91.2 94.4 97.3 1,989 Total men 15-59 na na na na 91.1 93.6 96.9 2,508 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. na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 185 The MDHS asked respondents over age 18 whether they supported teaching chil- dren age 12-14 about using condoms to avoid HIV/AIDS. Table 13.8 shows that 73 percent of women and 85 percent of men agree that children age 12-14 should be taught about condom use to avoid AIDS. Patterns by some background char- acteristics are similar for women and men, but for women variations are larger. The proportion of younger male and female re- spondents supporting education about con- dom use to prevent HIV/AIDS is higher than the proportion of women and men in the oldest age cohort. Women with secondary schooling are less likely to favor teaching about condom use (66 percent), than those with at least some university education (86 percent). Among men, also, but with a smaller differential than women, those with secondary schooling are less likely to ap- prove of teaching about condom use (83 percent) than men with higher education (90 percent). Differences by wealth quintile are more pronounced, ranging from 50 percent of women in the lowest quintile to 86 per- cent of women in the highest quintile and from 68 to 93 percent for men, respectively. 13.3 HIGHER-RISK SEX Given that HIV infections are be- coming more frequently contracted through heterosexual contact (see introduction to this chapter), information on sexual behavior is important in designing and monitoring inter- vention programs to control the spread of the epidemic. In the context of HIV/AIDS/STI prevention, limiting the number of sexual partners and having protected sex are crucial to the fight against the epidemic. Tables 13.9.1 and 13.9.2 show, among women and men who had sexual intercourse in the 12 months preceding the survey, the percentage who had sex with someone other than a spouse or live-in partner, and the extent of multiple sexual partners. Those who had engaged in sex with a nonmarital, noncohabiting partner (the definition of “higher-risk sex”) were then asked whether they used a condom the last time they engaged in sex with such a partner. The mean number of lifetime sexual partners was also determined. Table 13.8 Adult support of education about condom use to prevent AIDS Percentage of women and men age 18-49 who agree that children age 12-14 years should be taught about using a condom to avoid AIDS, by background characteristics, Moldova 2005 Women Men Background characteristic Percentage of women Number of women Percentage of men Number of men Age 18-19 75.2 570 87.9 291 20-24 77.7 1,124 86.1 550 25-29 76.2 964 90.2 468 30-39 74.8 1,778 88.3 944 40-49 66.0 2,156 78.6 1,192 Marital status Never married 77.9 1,049 88.4 454 Ever had sex 84.5 394 89.6 387 Never had sex 74.0 655 81.5 67 Married/living together 71.7 4,906 83.6 1,189 Divorced/separated/ widowed 71.4 638 83.2 80 Residence Urban 81.7 2,888 90.5 750 Rural 65.6 3,705 80.5 973 Region North 70.7 1,970 79.6 515 Center 67.4 1,751 86.5 458 South 67.4 1,233 82.6 342 Chisinau 84.5 1,639 91.4 408 Education No education/primary (43.1) 46 * 10 Secondary 65.5 3,723 82.6 1,183 Secondary special 78.6 1,297 90.6 202 Higher 85.9 1,527 90.4 328 Wealth quintile Lowest 50.4 1,056 68.2 294 Second 62.9 1,074 81.9 306 Middle 73.3 1,338 88.3 319 Fourth 79.7 1,495 88.1 386 Highest 86.4 1,630 92.9 418 Total 18-49 72.7 6,593 84.8 1,723 Total men 18-59 na na 82.9 2,242 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. na = Not applicable 186 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.9.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: women Among women age 15-49 who had sexual intercourse in the past 12 months, the percentage who had intercourse with more than one partner and the percentage who had higher-risk sexual intercourse in the past 12 months, and among those having higher-risk intercourse in the past 12 months, the percentage reporting that a condom was used at last higher-risk intercourse, and the mean number of sexual partners during her lifetime for women who ever had sexual intercourse, by background characteristics, Moldova 2005 Women who had sexual intercourse in past 12 months Women who had higher-risk intercourse in the past 12 months Women who ever had sexual intercourse Background characteristic Percentage who had 2+ partners in last 12 months Percentage who had higher-risk intercourse1 in past 12 months Number of women Percentage who reported using a condom at last higher-risk intercourse1 Number of women Mean number of sexual partners in lifetime Number of women Age 15-19 7.5 56.2 279 48.7 157 1.6 308 20-24 4.0 28.5 822 40.7 234 1.8 867 25-29 2.2 11.8 858 28.3 101 1.8 918 30-39 1.0 7.2 1,614 24.0 116 1.7 1,746 40-49 0.6 5.7 1,804 12.0 104 1.5 2,142 15-24 4.9 35.5 1,100 43.9 391 1.7 1,175 Marital status Never married 11.5 99.2 356 42.5 353 2.2 441 Ever had sex 11.5 99.2 356 42.5 353 2.2 441 Married/living together 0.8 3.3 4,751 32.8 157 1.5 4,907 Divorced/separated/ widowed 7.7 74.8 269 19.2 201 2.6 633 Residence Urban 3.0 19.9 2,344 35.6 468 2.0 2,604 Rural 0.9 8.0 3,032 30.3 244 1.4 3,377 Region North 1.5 8.7 1,597 35.6 139 1.6 1,790 Center 1.0 9.8 1,423 21.7 140 1.4 1,584 South 1.1 10.8 1,033 34.1 112 1.4 1,137 Chisinau 3.8 24.3 1,324 38.2 321 2.3 1,471 Education No education/primary (0.0) (10.8) 40 (18.5) 4 (2.3) 45 Secondary 1.5 9.9 3,066 28.2 304 1.6 3,431 Secondary special 1.3 10.0 1,103 31.1 111 1.6 1,233 Higher 3.3 24.9 1,167 40.7 291 1.9 1,272 Wealth quintile Lowest 0.7 6.7 877 32.7 58 1.4 988 Second 0.8 8.6 880 20.6 76 1.4 1,003 Middle 1.1 8.5 1,080 37.3 92 1.4 1,190 Fourth 2.3 15.1 1,190 33.8 180 1.7 1,320 Highest 3.5 22.6 1,350 36.2 305 2.2 1,481 Total 1.8 13.2 5,376 33.8 711 1.7 5,982 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Sexual intercourse with a nonmarital, noncohabiting partner HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 187 Table 13.9.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: men Among men age 15-49 who had sexual intercourse in the past 12 months, the percentage who had intercourse with more than one partner and the percentage who had higher-risk sexual intercourse in the past 12 months1, and among those having higher-risk intercourse in the past 12 months, the percentage reporting that a condom was used at last higher-risk intercourse, and the mean number of sexual partners during his lifetime for men who ever had sexual intercourse, by background characteristics, Moldova 2005 Men who had sexual intercourse in past 12 months Men who had higher-risk intercourse in past 12 months Men who ever had sexual intercourse Background characteristic Percentage who had 2+ partners in past 12 months Percentage who had higher-risk intercourse1 in past 12 months Number of men Percentage who reported using a condom at last higher-risk intercourse1 Number of men Mean number of sexual partners in lifetime Number of men Age 15-19 33.7 96.2 165 68.7 159 4.4 167 20-24 25.4 74.3 239 57.8 178 6.6 233 25-29 16.6 31.2 219 44.9 68 8.0 211 30-39 10.4 17.1 439 46.2 75 7.1 425 40-49 5.3 12.0 509 21.9 61 6.3 529 15-24 28.8 83.2 404 62.9 336 5.7 401 Marital status Never married 33.8 96.9 406 61.2 393 6.2 424 Ever had sex 33.8 96.9 406 61.2 393 6.2 424 Married/living together 6.1 8.0 1,105 40.4 89 6.5 1,072 Divorced/separated/ widowed 34.5 96.6 61 23.8 59 10.2 70 Residence Urban 18.0 38.4 695 54.2 267 8.0 673 Rural 11.4 31.2 876 53.2 273 5.5 893 Region North 11.3 30.8 478 54.0 147 5.6 481 Center 12.3 32.4 402 53.0 130 5.6 416 South 12.8 32.3 306 50.9 99 6.0 309 Chisinau 21.4 42.8 386 55.6 165 9.6 360 Education No education/primary * * 7 * 1 * 8 Secondary 13.0 33.6 1,080 52.8 363 5.6 1,086 Secondary special 15.4 25.9 187 48.5 48 8.8 189 Higher 18.7 43.1 297 57.7 128 9.1 283 Wealth quintile Lowest 7.2 26.2 258 53.1 68 4.6 257 Second 10.2 34.1 273 43.2 93 5.2 290 Middle 14.0 30.2 295 59.4 89 5.8 296 Fourth 16.6 35.4 357 51.7 126 6.8 358 Highest 20.0 42.4 388 58.4 164 9.7 365 Total 15-49 14.3 34.4 1,571 53.7 541 6.6 1,566 Total men 15-59 12.0 29.2 1,961 57.7 572 6.0 2,024 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Sexual intercourse with a nonmarital, noncohabiting partner Among those who reported having sex in the 12 months preceding the survey, a substantially larger proportion of men than women reported having had more than one sexual partner (14 percent for men and only 2 percent for women) and higher-risk sex (34 and 13 percent, respectively) at some time in the past 12 months. Eight percent of men who are currently married or cohabiting report having had sex with a nonmarital, noncohabiting partner in the past 12 months, compared with 3 percent of women. 188 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Sexual behaviors differ by residence, with women in urban areas more than twice as likely as those in rural areas to have had sex with a nonmarital, noncohabiting partner during the 12 months before the interview (20 and 8 percent, respectively). There is a 7 percentage point difference by urban-rural resi- dence in the likelihood of men having had sex with a nonmarital, noncohabiting partner during the 12 months before the interview (38 versus 31 percent) and in the likelihood to have had two or more partners (18 versus 11 percent). More educated and wealthier women and men are more likely than other respondents to engage in higher-risk sexual behaviors, while the education and wealth status variations in condom use in those sexual encounters are not as profound. There are substantial regional variations, with Chisinau residents reporting higher rates of higher-risk sex, but only a slightly higher rate of condom use. While only about one-third of women reported using a condom the last time they had sex with a nonmarital, noncohabiting partner (34 percent), over half of men did (58 percent). Married women and married men are less likely to use a condom at last higher-risk intercourse than those who were never married. Divorced, separated, or widowed women and men are the least likely to use a condom at last higher-risk sexual intercourse. On average, men have had 6.6 sexual partners over their lifetime. The mean number of sexual partners varies by education, with a higher mean number of partners among men with higher education compared to those with secondary education (9.1 and 5.6 percent, respectively). As one would expect, the mean number of sexual partners is nearly two times higher among divorced, separated, or widowed men (10.2) than among never-married men (6.2). The mean number of lifetime partners is much lower for women (1.7) and socio- demographic variations are not significant. Paid sex is considered a special category of higher-risk sex. Male respondents in the MDHS were asked whether they had paid money in exchange for sex in the past 12 months or if any of their last three partners in the past 12 months was a commercial sex worker. They were also asked about condom use during these sexual encounters. Only about 1 percent of men had commercial sex in the year before the survey (Table 13.10). Although the number of men who pay for sex is too small to draw conclusions about exact differentials, the data do show that men who are divorced, separated, or widowed are the most likely to pay for sex, that younger men age 15-29 are more likely than older men to pay for sex, and men from Chisinau and those in higher wealth quintiles are more likely to pay for sex. Table 13.10 Payment for sexual intercourse Percentage of men age 15-49 reporting payment for sexual intercourse in the past 12 months, by background characteristics, Moldova 2005 Background characteristic Percentage reporting sex with prostitute in past 12 months Number of men Age 15-19 1.2 411 20-24 1.2 275 25-29 1.3 234 30-39 0.6 472 40-49 0.6 596 15-24 1.2 686 Marital status Never married 1.0 720 Married or living together 0.6 1,189 Divorced/separated/ widowed 3.4 80 Residence Urban 1.7 857 Rural 0.2 1,132 Region North 0.2 582 Center 0.8 553 South 0.2 388 Chisinau 2.4 466 Education No education/primary * 14 Secondary 0.5 1,433 Secondary special 1.5 214 Higher 2.0 328 Wealth quintile Lowest 0.0 349 Second 0.0 352 Middle 0.5 366 Fourth 1.6 452 Highest 1.8 470 Total 15-49 0.9 1,989 Total men 15-59 0.7 2,508 Note: Includes men who reported having a prostitute as at least one of two sexual partners in the past 12 months. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 189 13.4 TESTING FOR HIV For those people who have HIV, knowledge of their status permits them to take appropriate actions to protect their sexual partners, to access treatment, and to plan for the future. For people who know that they do not have HIV, they can take actions to avoid the risk of contracting the disease and remain disease free. The MDHS asked respondents whether they had ever been tested for HIV, and if so, whether they received the results of their last test. Tables 13.11.1 and 13.11.2 show that in Moldova, 36 percent of the women have been tested at some time for HIV, compared with 30 percent for men. Thirty-four percent of women and 27 percent of men have been tested at some time and also received the results of their HIV test; approximately one in ten women and men were tested and received their results during the year preceding the survey. Women age 30-39 are more likely than respondents of other ages to have been tested. Men age 25-39 are more likely to have been tested than men in other age groups. Women and men age 15-19 years are the least likely to have ever had an HIV test. Table 13.11.1 Coverage of prior HIV testing: women Percent distribution of women by whether tested for HIV and by whether received the results of the test, and the percentage of women who received their test results the last time they were tested for HIV in the past 12 months, according to background characteristics, Moldova 2005 Ever tested for HIV Background characteristic Received results No results Don’t know whether received results/ missing Never tested/ don’t know if tested/ missing Total Percentage who received results from HIV test taken in past 12 months Number of women Age 15-19 9.2 0.9 0.0 89.9 100.0 5.5 1,417 20-24 41.3 2.5 0.3 55.9 100.0 18.5 1,124 25-29 51.3 2.4 0.5 45.7 100.0 20.5 964 30-39 45.4 2.1 0.4 52.1 100.0 15.0 1,778 40-49 30.1 1.3 0.6 68.0 100.0 8.9 2,156 15-24 23.4 1.6 0.2 74.9 100.0 11.3 2,541 Marital status Never married 10.1 0.4 0.1 89.5 100.0 4.2 1,862 Ever had sex 20.9 0.9 0.2 78.0 100.0 8.3 447 Never had sex 6.7 0.2 0.0 93.1 100.0 2.8 1,415 Married/living together 42.9 2.2 0.5 54.4 100.0 15.6 4,937 Divorced/separated/widowed 37.8 1.9 0.5 59.8 100.0 14.8 641 Residence Urban 42.5 1.9 0.4 55.2 100.0 15.2 3,194 Rural 28.0 1.6 0.4 70.0 100.0 10.8 4,246 Region North 34.2 1.6 0.5 63.7 100.0 12.1 2,207 Center 27.2 1.9 0.3 70.7 100.0 9.6 2,033 South 31.6 1.2 0.4 66.8 100.0 13.2 1,402 Chisinau 44.3 2.1 0.3 53.3 100.0 16.5 1,798 Education No education/primary (25.4) (0.0) (0.0) (74.6) 100.0 (15.7) 49 Secondary 27.2 1.9 0.3 70.6 100.0 10.8 4,534 Secondary special 43.4 1.8 0.4 54.4 100.0 14.5 1,327 Higher 47.4 1.4 0.4 50.7 100.0 16.6 1,530 Wealth quintile Lowest 21.3 1.6 0.2 76.8 100.0 8.4 1,243 Second 28.8 1.2 0.3 69.7 100.0 10.9 1,234 Middle 30.1 2.3 0.4 67.2 100.0 12.1 1,511 Fourth 38.3 1.7 0.6 59.4 100.0 14.6 1,672 Highest 46.7 1.7 0.3 51.3 100.0 15.6 1,780 Total 34.2 1.7 0.4 63.7 100.0 12.7 7,440 Note: Figures in parentheses are based on 25-49 unweighted cases. 190 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.11.2 Coverage of prior HIV testing: men Percent distribution of men by whether tested for HIV and by whether received the results of the test, and the percentage of men who received their test results the last time they were tested for HIV in the past 12 months, according to background characteristics, Moldova 2005 Ever tested for HIV Background characteristic Received results No results Don’t know whether received results/ missing Never tested/ don’t know if tested/ missing Total Percentage who received results from HIV test taken in past 12 months Number of men Age 15-19 12.0 2.4 0.6 84.9 100.0 5.7 411 20-24 33.3 1.0 1.1 64.6 100.0 11.7 275 25-29 39.5 1.2 2.5 56.9 100.0 12.4 234 30-39 38.4 2.1 1.3 58.2 100.0 12.8 472 40-49 27.3 1.6 0.7 70.4 100.0 9.2 596 15-24 20.6 1.8 0.8 76.8 100.0 8.1 686 Marital status Never married 18.7 1.8 0.7 78.8 100.0 7.8 720 Ever had sex 26.2 1.5 0.3 71.9 100.0 11.0 459 Never had sex 5.3 2.3 1.2 91.1 100.0 2.1 260 Married/living together 34.6 1.7 1.4 62.3 100.0 11.5 1,189 Divorced/separated/ widowed 39.3 1.7 0.0 59.0 100.0 9.0 80 Residence Urban 40.2 0.9 1.1 57.8 100.0 13.2 857 Rural 20.6 2.4 1.1 76.0 100.0 7.6 1,132 Region North 26.4 0.2 1.0 72.4 100.0 10.2 582 Center 21.5 3.0 0.9 74.6 100.0 7.3 553 South 26.2 3.3 1.9 68.6 100.0 8.6 388 Chisinau 43.6 1.0 0.6 54.7 100.0 14.4 466 Education No education/primary * * * 100.0 100.0 * 14 Secondary 22.3 1.9 0.9 75.0 100.0 7.3 1,433 Secondary special 39.4 2.2 1.7 56.7 100.0 16.0 214 Higher 52.3 0.9 1.6 45.2 100.0 18.3 328 Wealth quintile Lowest 12.2 1.1 0.8 85.8 100.0 3.2 349 Second 20.2 3.3 1.3 75.3 100.0 8.5 352 Middle 28.7 2.9 1.9 66.4 100.0 12.1 366 Fourth 35.0 0.9 0.6 63.5 100.0 11.6 452 Highest 42.6 1.0 0.9 55.4 100.0 13.2 470 Total 15-49 29.0 1.8 1.1 68.1 100.0 10.1 1,989 Total men 15-59 27.4 1.8 0.9 69.9 100.0 9.1 2,508 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. HIV testing varies substantially by background characteristics, but not by sex. The most highly educated and wealthiest respondents are more likely to be tested than those with less education and a lower standard of living. By wealth quintile, for example, less than 15 percent of men in the lowest wealth quintile have been tested, while in the wealthiest households more than 40 percent have been tested. Likewise, there is a large difference by residence: about 30 percent of rural women and 24 percent of rural men have ever been tested, while in urban areas 45 percent of women and 42 percent of men have been tested. Women and men who have never been married and who have never had sex are substantially less likely than others to have been tested. Patterns are similar for women and men who have been tested and received their results in the last 12 months. Regional variations are substantial in that the proportion of respondents who had an HIV test HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 191 and received results in the past 12 months is significantly higher in Chisinau (13 percent for women and 14 percent for men) than other regions (6-9 percent for women and 7-10 percent for men). Information on HIV counseling and HIV testing among pregnant women who gave birth in the two years preceding the survey is presented in Table 13.12. The previous table illustrated that there were no substantial variations in HIV-testing rates among women and men—somewhat surprising since women who become pregnant have the added opportunity to be tested and receive counseling when they attend antenatal clinics. Table 13.12 shows that half of women who delivered a baby in the past two years were counseled about HIV, and 7 in 10 were tested and received the results. The findings do not vary substantially by most background characteristics. Table 13.12 Pregnant women who received information and counseling about HIV/AIDS Among women who gave birth in the 2 years preceding the survey, percentage who received HIV counseling during antenatal care for their most recent birth, and percentage who accepted an offer for HIV testing by whether they received their test results and background characteristics, Moldova 2005 Voluntarily tested for HIV during antenatal care visits Background characteristic Counseled during antenatal visit1 Received results2 No results Counseled, tested for HIV, and received results Number of women who gave birth in the past 2 years3 Age 15-19 47.0 65.8 7.5 38.3 60 20-24 51.5 71.6 6.1 43.8 247 25-29 49.8 68.4 4.6 42.2 196 30-39 48.5 67.0 5.1 43.2 143 40-49 * * * * 12 15-24 50.6 70.5 6.4 42.7 307 Marital status Never married, has had sex * * * * 8 Married/living together 51.3 69.5 5.7 43.9 628 Divorced/separated/widowed * * * * 21 Residence Urban 50.6 76.9 3.3 45.3 268 Rural 50.0 64.2 7.2 41.7 389 Region North 53.1 71.7 5.4 45.5 198 Center 46.7 60.1 8.5 38.8 188 South 52.3 70.3 4.2 44.9 128 Chisinau 49.1 77.5 3.3 44.0 143 Education No education/primary * * * * 9 Secondary 49.7 68.5 6.2 42.6 439 Secondary special 61.5 66.5 4.9 54.8 75 Higher 48.0 74.9 4.2 40.9 134 Wealth quintile Lowest 45.8 63.6 9.4 37.2 132 Second 52.8 75.9 2.8 48.8 126 Middle 55.4 58.4 9.7 44.0 130 Fourth 51.1 71.9 3.5 44.8 138 Highest 46.4 77.1 2.5 41.2 132 Total 50.3 69.4 5.6 43.1 657 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 In this context, "counseled" means that someone talked with the respondent about all three of the following topics: 1) babies getting the AIDS virus from their mother, 2) preventing the virus, and 3) getting tested for the virus. 2 Only women who were offered the test are included here; women who were either required to have the test, or who asked themselves for the test, are excluded from the numerator of this measure. 3 Denominator for percentages includes women who did not receive antenatal care for their last birth in the past two years. 192 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Among those tested for HIV, 12 percent of women and 19 percent of men asked for the test, while 15 percent of women and 5 percent of men were offered the test and accepted (Figure 13.1). About three-quarters of women and men tested indicated that the test was required. 13.5 REPORTS OF RECENT SEXUALLY TRANSMITTED INFECTIONS Information about the incidence of sexually transmitted infections (STIs) is not only useful as an indicator of unprotected sexual intercourse, but also as a determinant of HIV transmission. The MDHS asked respondents who have ever had sex whether they had an STI in the past 12 months. They were also asked whether, in the past year, they had experienced a genital sore or ulcer and if they had any genital discharge. These symptoms have been shown useful in identifying STIs in men. These symptoms are less easily interpreted for women because women are likely to experience STI-like symptoms, like genital discharge, which are not actually related to an infection. Table 13.13 shows that less than 1 percent of women and men in Moldova reported having an STI in the past 12 months. Six percent of women and 1 percent of men reported having had an abnormal genital discharge, and about the same percentages reported having had a genital sore or ulcer in the 12 months before the survey (7 percent of women and 1 percent of men). Eleven percent of women and 2 percent of men reported having an STI, or an abnormal discharge, or a genital sore. It should be noted that these STI-related estimates are likely to be underestimates because respondents may be reticent or ashamed to admit having an STI or STI symptoms. Women and men in younger age groups were more likely to report having an STI, or abnormal discharge, or a genital sore. Patterns by other background characteristics are not clear because the overall reported prevalence of the disease or its symptoms is low, especially in men. Figure 13.1 Reasons for Having an HIV Test among Women and Men Age 15-49 Who Have Ever Been Tested 12 15 74 19 5 76 Asked for test Offered test Test required 0 20 40 60 80 100 Percent Women Men MDHS 2005 HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 193 Table 13.13 Self-reporting of sexually transmitted infections (STI) and STI symptoms Among women and men who ever had sex, percentage self-reporting an STI and/or symptoms of an STI in the past 12 months, by background characteristics, Moldova 2005 Women Men Background characteristic Percentage with STI Percentage with abnormal genital discharge Percentage with genital sore/ulcer Percentage with STI/ discharge/ genital sore/ulcer Number of women who ever had sex Percentage with STI Percentage with abnormal genital discharge Percentage with genital sore/ulcer Percentage with STI/ discharge/ genital sore/ulcer Number of men who ever had sex Age 15-19 1.4 11.7 5.3 14.8 310 0.8 2.3 2.0 3.3 179 20-24 1.2 11.2 9.7 16.8 874 1.2 2.9 0.9 3.3 256 25-29 0.7 7.4 9.3 13.1 929 1.6 0.8 0.5 1.6 230 30-39 0.9 5.5 7.1 10.2 1,761 0.6 1.4 0.5 1.4 470 40-49 0.5 3.6 4.4 7.0 2,150 0.3 0.4 0.4 0.8 594 Marital status Never married 1.4 8.5 6.0 12.4 447 1.3 2.9 0.9 3.3 459 Married or living together 0.7 6.1 7.0 10.7 4,937 0.6 0.7 0.4 1.0 1,189 Divorced/separated/ widowed 0.7 6.1 5.3 9.2 641 0.0 0.8 2.6 2.6 80 Residence Urban 1.3 7.1 8.1 12.5 2,637 0.6 1.8 0.5 2.0 764 Rural 0.4 5.6 5.7 9.3 3,387 0.8 0.9 0.8 1.4 965 Region North 0.4 5.4 5.7 9.1 1,797 0.8 1.0 0.7 1.5 514 Center 0.7 6.1 5.3 10.0 1,591 1.0 1.5 0.9 2.1 448 South 0.4 4.4 6.3 8.3 1,141 0.3 0.4 0.8 0.8 346 Chisinau 1.7 9.0 9.9 15.3 1,495 0.7 2.2 0.2 2.4 421 Education No education/primary (3.5) (8.7) (6.6) (10.1) 45 * * * * 9 Secondary 0.6 6.4 6.4 10.5 3,450 0.7 1.2 0.7 1.5 1,197 Secondary special 0.6 4.9 5.6 8.9 1,242 0.8 1.3 1.0 1.8 203 Higher 1.4 7.2 8.7 13.0 1,287 0.7 1.8 0.5 2.3 320 Wealth quintile Lowest 0.2 6.2 6.3 10.1 991 1.3 1.3 0.9 1.8 286 Second 0.5 6.2 5.2 9.5 1,004 1.4 1.0 1.1 1.9 305 Middle 0.7 5.1 5.8 8.8 1,196 0.0 0.3 0.0 0.3 320 Fourth 0.9 5.5 6.7 10.3 1,333 0.6 2.1 1.3 2.7 395 Highest 1.3 7.9 8.9 13.7 1,500 0.5 1.4 0.2 1.6 423 Total 15-49 0.8 6.3 6.7 10.7 6,024 0.7 1.3 0.7 1.7 1,729 Total men 15-59 na na na na na 0.6 1.1 0.6 1.5 2,247 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. na = Not applicable 13.6 INJECTIONS The overuse of injections in a health care setting can contribute to the transmission of blood- borne pathogens because it amplifies the effect of unsafe practices, such as the reusing of syringes. As a consequence, the prevalence of injections given with reused syringes is an important indicator in tracking prevention efforts against HIV/AIDS. Table 13.14 presents data on the prevalence of injections among respondents. Respondents were asked if they had any injections given by a health worker in the past 12 months, and if so, whether their last injection was given with a syringe from a new, unopened package. It should be noted that medical injections can be self-administered (e.g., insulin for diabetes). These injections were not included in the analysis. 194 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Almost a third of women and men reported receiving injections in the past 12 months (33 and 28 percent, respectively). Women and men in the youngest age cohort (15-19) were more likely to have received an injection than older women and men. The higher percentage of injections among women is probably due to their receiving injections in antenatal care or family planning settings. There are no other significant variations by sociodemographic characteristics and residence. Table 13.14 Prevalence of injections Percentage of women and men age 15-49 who received at least one injection from a health worker1 in the past 12 months, the average number of medical injections1 per person, and among those who received an injection, the percentage whose health worker took the syringe and needle from a new, unopened package for the last injection, by background characteristics, Moldova 2005 Women Men Background characteristic Percent received an injection in past 12 months Average number of injections per person in past 12 months Number of women Last injection, syringe, and needle taken from newly opened package Number receiving injections from a health worker in the past 12 months Percent received an injection in past 12 months Average number of injections per person in past 12 months Number of men Last injection, syringe, and needle taken from newly opened package Number receiving injections from a health worker in the past 12 months Age 15-19 41.4 3.5 1,417 97.1 587 39.5 1.7 411 98.6 162 20-24 30.3 4.3 1,124 97.9 340 26.0 2.3 275 95.9 72 25-29 30.7 4.5 964 99.5 296 25.1 3.2 234 99.1 59 30-39 30.6 6.2 1,778 99.1 543 27.7 3.6 472 100.0 131 40-49 33.4 8.9 2,156 99.2 721 23.5 4.4 596 99.6 140 Residence Urban 31.3 5.7 3,194 98.7 1,001 28.0 3.4 857 98.5 240 Rural 35.0 6.2 4,246 98.4 1,485 28.6 3.1 1,132 99.2 323 Region North 35.0 7.3 2,207 98.5 773 28.4 3.3 582 99.4 165 Center 31.6 4.9 2,033 98.1 642 29.0 3.1 553 97.7 160 South 36.1 6.1 1,402 98.8 506 27.2 3.2 388 100.0 105 Chisinau 31.5 5.5 1,798 98.8 566 28.4 3.3 466 98.9 132 Education No education/primary (27.5) (4.8) 49 * 13 * * 14 * 2 Secondary 33.8 5.6 4,534 98.5 1,532 28.9 2.9 1,433 99.0 414 Secondary special 35.0 8.0 1,327 99.0 465 26.7 5.2 214 99.1 57 Higher 31.1 5.3 1,530 98.2 476 27.7 3.2 328 98.3 91 Wealth quintile Lowest 32.6 5.5 1,243 98.4 405 23.7 3.4 349 98.3 83 Second 35.0 6.0 1,234 98.9 432 33.4 2.5 352 100.0 118 Middle 34.7 6.4 1,511 98.5 524 24.9 3.3 366 99.4 91 Fourth 33.8 5.9 1,672 98.2 565 30.1 3.5 452 96.9 136 Highest 31.4 6.0 1,780 98.8 560 28.9 3.3 470 100.0 136 Total 15-49 33.4 6.0 7,440 98.5 2,487 28.3 3.2 1,989 98.9 563 Total men 15-59 na na na na na 28.3 4.0 2,508 98.8 710 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. na = Not applicable 1 Includes injections given by a doctor, nurse, pharmacist, dentist, or other health worker HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 195 The average number of injections is twice as high among women as men (6 and 3, respectively). Virtually all recent injections were given with a syringe taken from a newly opened package. 13.7 HIV/AIDS-RELATED KNOWLEDGE AND BEHAVIOR AMONG YOUTH Youth are a main target of HIV prevention programs. This section addresses knowledge of HIV/AIDS issues and related sexual behavior among youth age 15-24. This period, between the initiation of sexual activity and marriage, is often a time of sexual experimentation and may involve risky behaviors. General knowledge of HIV/AIDS transmission and prevention as well as knowledge of where to obtain condoms is analyzed below. Issues such as abstinence, age at sexual debut, age differences between partners, and condom use are also covered in this section. Knowledge about HIV/AIDS and Source for Condoms Knowledge of how HIV is transmitted is crucial to enabling people to avoid infection, especially for young people who are often at greater risk because they may have shorter relationships with more partners and engage in other risky behaviors. Young respondents in the MDHS were asked the same set of questions as older respondents about whether condom use and limiting partners to one uninfected partner can help protect against HIV, and whether a healthy-looking person can have HIV (see Tables 13.4.1 and 13.4.2). Table 13.15 shows the level of general knowledge among young people, namely, the proportion who, in response to prompted questions: 1) agree that people can reduce their chances of getting the AIDS virus by having sex with only one uninfected, faithful partner, and by using condoms consistently; 2) know that a healthy-looking person can have the AIDS virus; and 3) know that HIV cannot be transmitted by sharing food with a person who has AIDS. Forty-two percent of young women and 54 percent of young men age 15-24 know all of these facts about HIV/AIDS. Among both women and men, those age 20-24 are about as likely as those age 15-19 to have general knowledge of HIV/AIDS. As one would expect, level of knowledge increases with household wealth status: the higher the wealth quintile, the more likely youth are to have general knowledge of HIV/AIDS. Youth in urban areas are more likely than those in rural areas to have general HIV/AIDS knowledge (a 15 percentage point difference). Given that condoms play an important role in combating the transmission of HIV, respondents were asked if they knew where condoms could be obtained. Only responses about “formal” sources were counted, so obtaining condoms from friends, family members, or other informal sources, was not in- cluded. As shown in Table 13.15, knowledge of where to obtain a condom is almost universal (90 percent of women and 97 percent of men, respectively). Consistent with trends for other indicators, respondents who are more educated and live in wealthier households are more likely than other respondents to know a source of condoms, but the differentials are smaller in men than women. While almost all young women in Chisinau know of a condom source (97 percent), young women in other regions are less likely to cite a source where a condom can be obtained. This regional variation does not appear for men. 196 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.15 General knowledge about AIDS and knowledge of a source for condoms among youth Percentage of women and men age 15-24 with general knowledge about AIDS and the percentage with knowledge for a source of condoms, by background characteristics, Moldova 2005 Women Men Background characteristic Percent with general knowledge of AIDS 1 Percent who know of a condom source2 Number of women Percent with general knowledge of AIDS 1 Percent who know of a condom source2 Number of men Age 15-17 37.9 87.6 1,417 50.4 95.5 411 18-19 34.7 84.4 847 46.5 94.3 266 15-19 42.7 92.3 570 57.4 97.6 145 20-22 46.3 93.8 1,124 60.3 98.1 275 23-24 48.1 93.4 707 61.4 98.4 176 20-24 43.3 94.3 417 58.4 97.6 100 Marital status Never married 43.5 90.2 1,707 54.8 96.5 614 Ever had sex 50.8 95.9 349 62.5 99.8 363 Never had sex 41.6 88.7 1,358 43.8 91.7 251 Married/living together 37.6 90.3 765 48.7 96.6 69 Divorced/separated/ widowed 39.1 94.3 69 * * 4 Residence Urban 50.7 97.3 1,098 62.5 98.5 309 Rural 34.7 85.0 1,443 47.6 94.9 378 Region North 38.2 88.6 718 57.0 98.1 187 Center 38.0 86.3 722 53.0 95.0 210 South 40.1 89.8 472 39.2 95.0 118 Chisinau 50.9 97.1 629 63.5 97.7 171 Education No education/primary * * 9 * * 7 Secondary 33.8 87.0 1,787 48.8 96.5 526 Secondary special 53.3 95.2 182 (68.0) (100.0) 38 Higher 63.3 99.6 563 78.6 98.7 115 Wealth quintile Lowest 21.1 77.6 415 24.0 88.0 119 Second 31.4 84.7 425 49.4 97.8 119 Middle 42.7 90.0 517 63.9 98.9 107 Fourth 48.0 95.0 589 61.2 98.3 163 Highest 56.0 98.8 596 65.7 98.3 178 Total 15-24 41.6 90.3 2,541 54.3 96.5 686 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Respondents with general knowledge of AIDS are those who say that using a condom for every sexual intercourse and that having just one uninfected and faithful partner can reduce the chance of getting the AIDS virus, and furthermore say that a healthy-looking person can have the AIDS virus, and who reject the common misconception that HIV can be spread by sharing food with someone with AIDS. 2 Friends, family members, and home are not considered sources for condoms. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 197 Age at First Sex The discussion below deals with age at first sex, premarital and other higher-risk sexual encounters, and condom use among young women and men. Table 13.16 shows the proportion of women and men age 15-24 that had sex before age 15 and before age 18. One percent of young women and 9 percent of young men had sex by age 15; this proportion rises quickly by age 18, however, when 19 percent of young women and 44 percent of young men had sex. Young women with secondary education are almost twice as likely as those with at least some university education to have had sex by age 18 (22 and 12 percent, respectively). For men, the trend is the opposite; young men with secondary education are less likely than those with higher education to have had sex by age 18 (42 and 54 percent, respectively). Young men from households in the highest wealth quintiles are most likely to have had sex by age 15 or 18. This pattern does not hold among women, however. Furthermore, there are no substantial regional variations in early sexual debut among women, but men in Chisinau are more likely than men in other regions to have an early sexual debut. Table 13.16 Age at first sex among youth Percentage of women and men age 15-24 who have had sexual intercourse by exact age 15 and 18, by background characteristics, Moldova 2005 Women Men Background characteristic 15 18 Number of women 15-24 15 18 Number of men 15-24 Age 15-17 1.3 na 1,417 9.0 na 411 18-19 1.0 na 847 8.3 na 266 15-19 1.7 25.9 570 10.1 63.2 145 20-22 0.8 22.7 1,124 8.3 51.4 275 23-24 0.5 22.5 707 7.1 50.6 176 20-24 1.2 23.0 417 10.4 52.9 100 Marital status Never married 0.5 8.1 1,707 7.3 42.2 614 Married or living together 2.2 39.7 765 17.8 62.4 69 Divorced/separated/ widowed 2.9 54.1 69 * * 4 Residence Urban 0.9 19.9 1,098 11.6 50.5 309 Rural 1.2 18.1 1,443 6.4 39.5 378 Region North 1.5 21.3 718 5.3 48.9 187 Center 0.8 15.4 722 5.8 31.8 210 South 1.1 20.9 472 9.9 46.2 118 Chisinau 0.8 18.6 629 15.1 53.8 171 Education No education * * 9 * * 7 Secondary 1.4 21.5 1,787 8.5 42.2 526 Secondary special 0.3 15.1 182 12.7 49.8 38 Higher 0.1 11.5 563 9.0 54.4 115 Knows a condom source1 Yes 0.9 18.7 2,295 8.9 45.8 662 No 2.1 20.2 246 * * 24 Wealth quintile Lowest 1.2 20.5 415 7.1 35.4 119 Second 2.2 23.3 425 8.0 40.2 119 Middle 0.7 16.8 517 4.1 38.0 107 Fourth 0.6 14.1 589 10.1 45.0 163 Highest 0.9 21.2 596 11.7 56.6 178 Total 15-24 1.1 18.9 2,541 8.7 44.4 686 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Friends, family members, and home are not considered sources for condoms. 198 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior To assess the extent of condom use from the beginning of sexual exposure, respondents age 15-24 were asked whether they had used a condom the first time they had sex. Table 13.17 shows that almost one-third of young women (29 percent) and over half of young men (56 percent) used condoms during their first sexual encounter. Never-married women are more than twice as likely, and married men almost twice as likely, as married or cohabiting respondents to have used a condom. Those with higher levels of education and from wealthier households are also more likely than others to have used condoms in their first sexual encounters. Table 13.17 Condom use at first sexual intercourse among youth Percentage of women and men age 15-24 who used a condom the first time they had sexual intercourse, by background characteristics, Moldova 2005 Women Men Background characteristic Used a condom at first sex Number of women 15-24 who have ever had sex Used a condom at first sex Number of men 15-24 who have ever had sex Age 15-17 34.3 310 64.4 179 18-19 37.2 87 65.5 72 15-19 33.1 223 63.7 107 20-22 26.6 874 49.6 256 23-24 27.5 497 53.3 161 20-24 25.4 376 43.4 95 Marital status Never married 45.0 349 59.2 363 Married or living together 20.7 765 36.0 69 Divorced/separated/ widowed 33.3 69 * 4 Residence Urban 35.8 571 59.2 217 Rural 21.9 613 52.2 219 Region North 23.7 325 49.8 125 Center 21.2 294 57.1 108 South 27.4 223 50.6 76 Chisinau 40.5 341 63.4 126 Education No education/primary * 9 * 1 Secondary 21.6 732 51.0 299 Secondary special 34.2 105 (69.9) 28 Higher 42.7 338 64.5 107 Knows a condom source1 Yes 30.1 1,091 55.9 432 No 10.6 93 * 3 Wealth quintile Lowest 14.8 170 40.9 60 Second 18.3 202 43.7 72 Middle 23.0 219 53.8 64 Fourth 35.7 266 58.0 107 Highest 40.2 326 68.0 132 Total 15-24 28.6 1,184 55.7 435 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Friends, family members, and home are not considered sources for condoms. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 199 13.8 RECENT SEXUAL ACTIVITY AMONG YOUNG WOMEN AND MEN The period between age at first sex and age at marriage is often a time of sexual experimentation, which can be a risky time. Table 13.18 presents data on the percentage of never-married young women and men age 15-24 that have not yet engaged in sex, the percentage that had sex in the 12 months preceding the survey, and the percentage that used condoms during most recent sex. As many as 4 in 5 never-married young women reported that they had never had sex, compared with 2 in 5 of men. Although the percentage of unmarried youth who have never had sex declines rapidly from age 15-19 to 20-24, 60 percent of women and 10 percent of men age 23-24 reported that they had not yet had sex. The proportion of young respondents who have never had sex was smaller in wealthy households compared to poorer households. Table 13.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth Among never-married women and men age 15-24, percentage who have never had sex, percentage who have had sex in the past 12 months and, among those who had premarital sex in the past 12 months, percentage who used a condom at last sex, by background characteristics, Moldova 2005 Women Men Background characteristic Percent- age who never had sexual intercourse Percentage who have had sexual intercourse in the past 12 months Number of never- married women 15-24 Percentage who used a condom at last sexual intercourse Number of women Percentage who never had sexual intercourse Percentage who have had sexual intercourse in the past 12 months Number of never- married men 15-24 Percentage who used a condom at last sexual intercourse Number of men Age 15-17 87.3 10.8 1,268 51.3 137 57.3 39.1 405 69.2 158 18-19 93.5 5.2 813 (52.9) 42 72.8 24.9 266 72.3 66 15-19 76.3 20.8 455 50.5 95 27.8 66.4 139 66.9 92 20-22 57.0 36.3 439 38.6 159 9.2 82.9 210 57.7 174 23-24 59.8 33.9 350 37.0 118 9.8 82.3 149 62.2 123 20-24 46.0 45.6 89 (43.3) 41 7.9 84.4 60 46.8 51 Residence Urban 74.1 22.4 711 43.9 159 34.5 58.4 267 62.7 156 Rural 83.4 13.8 996 45.1 137 45.9 50.7 347 63.6 176 Region North 85.6 11.6 459 59.3 53 37.6 60.2 166 58.7 100 Center 83.5 14.8 513 30.8 76 51.5 42.3 197 68.4 83 South 76.2 20.6 327 45.8 67 39.5 56.5 106 62.3 60 Chisinau 70.5 24.4 409 45.9 100 31.3 61.3 144 63.8 89 Education No education * * 3 * 1 * * 7 * 1 Secondary 86.5 10.8 1,219 41.9 132 47.6 47.9 478 62.4 229 Secondary special 69.6 28.9 110 (47.7) 32 (34.0) (59.5) 30 * 18 Higher 59.9 35.0 375 46.6 131 8.0 84.6 99 62.6 84 Knows a condom source1 Yes 78.2 18.7 1,539 45.6 287 38.9 56.0 593 63.2 332 No 91.5 5.3 168 * 9 (96.5) (0.0) 22 * 0 Wealth quintile Lowest 85.2 11.5 287 (49.1) 33 55.5 41.3 106 (66.5) 44 Second 84.6 14.2 264 (36.0) 38 42.3 53.5 111 (53.5) 60 Middle 81.4 15.2 366 48.7 56 43.3 53.3 100 66.6 53 Fourth 80.5 17.3 401 46.7 69 38.7 56.5 145 64.9 82 Highest 69.2 25.9 389 42.2 101 30.3 61.5 152 64.3 93 Total 15-24 79.5 17.4 1,707 44.5 296 40.9 54.1 614 63.2 332 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Friends, family members, and home are not considered sources for condoms. 200 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 13.18 also presents data on never-married youth who used a condom the last time they had sex. Only 17 percent of never-married women and 54 percent of never-married men had sex in the past 12 months. Almost half of the women (45 percent) and more than half of the men (63 percent) reported using a condom during their last sexual intercourse. Differentials by background characteristics do not vary in any expected directions. Higher-Risk Sex To prevent HIV/AIDS transmission through sexual intercourse, it is important that young people practice safe sex through the highly advocated ABC methods (abstinence, being faithful to one uninfected partner, and condom use) mentioned in the beginning of this chapter. Table 13.19 presents data on the percentage of young people who engaged in higher-risk sex (sex with a nonmarital, noncohabiting partner) in the 12-month period preceding the survey, and the prevalence of condom use in these higher- risk sexual encounters. Sexually active young men age 15-24 are more than twice as likely to have engaged in the higher-risk sex as women: 36 percent of women and 84 percent of men reported higher- risk sexual activity in the past 12 months. Approximately 2 in 5 of these women and 3 in 5 of these men reported condom use in their last high-risk sexual encounter. Among women there are significant differences in the prevalence of higher-risk sex and condom use by background characteristics. Women with secondary education and lower wealth status are about half as likely as those with higher education and from wealthy households to have engaged in higher-risk sex. Women in urban areas are more likely than those in rural areas to have engaged in risky sexual behavior (44 and 28 percent, respectively). These relationships do not generally hold for men, in part because a large proportion of men have engaged in higher-risk behaviors. Consistent with findings in Table 13.18, almost 2 in 5 women who know a condom source used a condom in their last sexual encounter, compared with more than one in ten of those unaware of a condom source. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 201 Table 13.19 Higher-risk sex and condom use at last higher-risk sex in the past year among youth Among sexually active women and men age 15-24, percentage who had sexual intercourse with higher-risk (nonmarital, noncohabiting) partners in the past 12 months, and among women and men age 15-24 who had higher-risk sex in the past 12 months, percentage who report using a condom the last time they had higher-risk sex, by background characteristics, Moldova 2005 Women Men Background characteristic Percentage engaging in higher-risk sex in past 12 months Number of women sexually active in past 12 months Percentage who used condom at last higher- risk sex1 Number of women 15-24 who had higher- risk sex in past 12 months Percentage engaging in higher-risk sex in past 12 months Number of men sexually active in past 12 months Percentage who used condom at last higher- risk sex1 Number of men 15-24 who had higher- risk sex in past 12 months Age 15-17 56.2 279 48.7 157 96.2 165 68.7 159 18-19 62.2 75 (52.6) 46 100.0 66 73.8 66 15-19 54.0 204 47.0 110 93.7 99 65.1 93 20-22 28.5 822 40.7 234 74.7 239 57.5 179 23-24 35.4 468 38.8 166 83.2 149 61.6 124 20-24 19.3 354 45.4 68 60.5 90 48.2 55 Marital status Never married 99.3 296 44.6 294 96.9 332 63.8 322 Married or living together 8.3 749 47.7 63 18.8 69 * 13 Divorced/separated/ widowed 62.2 55 (30.7) 34 * 4 * 3 Residence Urban 43.6 535 45.4 233 82.2 197 61.7 162 Rural 27.9 565 41.7 157 84.6 207 63.7 175 Region North 24.0 303 49.7 73 79.8 121 57.6 97 Center 33.0 274 27.3 90 85.7 96 71.0 82 South 36.0 211 45.2 76 86.3 72 61.5 62 Chisinau 48.5 312 50.4 151 83.6 115 61.8 96 Education No education/primary * 8 * 2 * 1 * 1 Secondary 26.2 677 39.5 177 83.2 277 62.7 231 Secondary special 38.2 100 (43.7) 38 (79.7) 26 * 20 Higher 54.8 314 48.7 172 84.9 100 61.4 85 Knows a condom source2 Yes 37.3 1,018 44.8 379 83.9 402 62.8 337 No 13.8 82 * 11 * 2 * 0 Wealth quintile Lowest 24.1 154 (43.7) 37 (77.7) 56 (66.5) 44 Second 26.3 191 (31.0) 50 88.7 67 (53.3) 59 Middle 30.2 203 46.6 61 85.0 61 (68.5) 52 Fourth 38.2 252 48.2 96 83.0 100 62.6 83 Highest 48.7 300 44.4 146 82.8 120 64.0 99 Total 15-24 35.5 1,100 43.9 391 83.5 404 62.8 337 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Corresponds to UNAIDS Young People's Sexual Behavior Indicator 5 "Young people using a condom at last higher-risk sex." 2 Friends, family members, and home are not considered sources for condoms. 202 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior Age-Mixing in Sexual Relationships In many societies, young women have sexual relationships with men who are considerably older than they are. This practice can contribute to the wider spread of HIV and other STIs because if a younger, uninfected partner has sex with an older, infected partner, this can introduce the virus into a younger, less infected cohort. To investigate this practice, in the MDHS women age 15-24 who had sex with a non- marital, noncohabiting partner in the 12 months pre- ceding the survey were asked whether the man was younger, about the same age, or older than they were. If older, they were asked if he was less than 10 years older, or 10 or more years older. The results in Table 13.20 show that in the past year, 5 percent of women age 15-24 had higher-risk sex with a man 10 or more years older than themselves. Women in urban areas are more likely to have sexual relationships with a man 10 years their senior than women in rural areas (8 percent and 2 percent, respectively). Alcohol use at the time of Sex Sexual intercourse when one or both partners are under the influence of alcohol is more likely to be unplanned, and couples are therefore less likely to use condoms. Respondents who had had sex during the preceding 12 months were asked if they or their part- ners drank alcohol the last time they had sex, and if so, whether they or their partners were drunk. Table 13.21 shows the prevalence of sexual intercourse while drunk. The overall prevalence of sex when the re- spondent is drunk is extremely low, especially for young women (less than 1 percent for women and 2 percent for men). It is higher when tabulated, by sex, when either the respondent or her/his partner is drunk (5 percent for women and 7 percent for men). Except in a few instances, differences across groups are minimal. Table 13.20 Age-mixing in sexual relationships Among women age 15-24 who had nonmarital sex in the past 12 months, percentage who had nonmarital sex with a man 10 years or more older than themselves in the past 12 months, by background characteristics, Moldova 2005 Background characteristic Percentage who had non- marital sex with a man 10+ years older1 Number of women 15-24 who had non- marital sex in past 12 months Age 15-19 4.4 157 15-17 (5.8) 46 18-19 3.8 110 20-24 6.0 234 20-22 6.2 166 23-24 5.4 68 Marital status Never married 4.1 294 Ever married 9.0 97 Residence Urban 7.6 233 Rural 2.0 157 Region North 2.7 73 Center 6.5 90 South 2.8 76 Chisinau 7.2 151 Education Primary/secondary * 179 Secondary special (0.0) 38 Higher 5.9 172 Knows a condom source2 Yes 5.5 379 No * 11 Wealth quintile Lowest (0.0) 37 Second (2.4) 50 Middle 8.3 61 Fourth 4.6 96 Highest 6.9 146 15-24 5.3 391 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Sexual intercourse with a nonmarital, noncohabiting partner 2 Friends, family members, and home are not considered sources for condoms. HIV/AIDS-Related Knowledge, Attitudes, and Behavior | 203 Table 13.21 Drunkenness during sexual intercourse among youth Among women and men age 15-24 who had sexual intercourse in the past 12 months, percentage who were drunk during the last sexual encounter, by background characteristics, Moldova 2005 Women Men Background characteristic Respondent drunk Respondent and/or partner drunk Number of women Respondent drunk Respondent and/or partner drunk Number of men Age 15-17 0.3 7.7 279 2.0 8.4 165 18-19 0.0 13.3 75 2.0 12.7 66 15-19 0.4 5.7 204 2.0 5.5 99 20-22 0.0 4.2 822 1.9 5.7 239 23-24 0.0 6.1 468 2.7 7.6 149 20-24 0.0 1.8 354 0.7 2.5 90 Marital status Never married 0.0 6.9 296 2.4 7.8 332 Married or living together 0.1 3.7 749 0.0 1.0 69 Divorced/separated/ widowed 0.0 15.3 55 * * 4 Residence Urban 0.2 4.3 535 1.6 6.9 197 Rural 0.0 5.9 565 2.3 6.6 207 Region North 0.3 6.2 303 3.0 7.0 121 Center 0.0 5.1 274 1.4 6.8 96 South 0.0 4.4 211 1.6 4.5 72 Chisinau 0.0 4.5 312 1.5 7.9 115 Education No education/primary * * 8 * * 1 Secondary 0.1 6.3 677 2.0 7.9 277 Secondary special 0.0 4.1 100 3.2 5.3 26 Higher 0.0 2.7 314 1.5 4.0 100 Knows a condom source1 Yes 0.1 5.1 1,018 2.0 6.8 402 No 0.0 5.1 82 * * 2 Wealth quintile Lowest 0.0 9.3 154 5.0 (16.5) 56 Second 0.0 4.5 191 0.0 0.0 67 Middle 0.0 3.7 203 3.2 7.5 61 Fourth 0.3 5.4 252 2.5 6.8 100 Highest 0.0 4.1 300 0.5 5.5 120 Total 15-24 0.1 5.1 1,100 2.0 6.8 404 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Friends, family members, and home are not considered sources for condoms. 204 | HIV/AIDS-Related Knowledge, Attitudes, and Behavior HIV Testing Young people may believe there are barriers to accessing health services and facilities, particularly for sensitive concerns related to family planning, sexual health in general, and specifically to sexually transmitted infections like HIV/AIDS. Table 13.22 presents data on the percentage of sexually active youth being tested and receiving the results within the past year. Young men were more likely than women to have been tested for HIV and to have received the results (12 and 9 percent, respectively). Given that HIV testing is uncommon among youth age 15-24, there is little variation across groups. However, female and male respondents in urban areas are more likely than those in rural areas to have been tested and to have received the results in the past year, and young, sexually active women who know of a condom source are more likely than those who do not know where to obtain a condom to have had an HIV test and received the results. Table 13.22 Recent HIV tests among youth Among women and men age 15-24 who had sexual intercourse in the past 12 months, the percentage who had an HIV test in the past 12 months and received the results of the test, by background characteristics, Moldova 2005 Women Men Background characteristic Percent who were tested and received results in past 12 months Number of women Percent who were tested and received results in past 12 months Number of men Age 15-17 6.5 279 11.2 165 18-19 5.7 75 9.6 66 15-19 6.8 204 12.4 99 20-22 10.4 822 12.7 239 23-24 9.3 468 14.0 149 20-24 11.7 354 10.5 90 Residence Urban 10.7 535 17.2 197 Rural 8.2 565 7.3 207 Region North 8.6 303 13.2 121 Center 7.2 274 10.9 96 South 10.6 211 7.2 72 Chisinau 11.3 312 15.1 115 Education No education/primary * 8 * 1 Secondary 7.9 677 9.2 277 Secondary special 11.1 100 15.3 26 Higher 12.1 314 18.0 100 Knows a condom source1 Yes 9.9 1,018 12.0 402 No 3.3 82 * 2 Wealth quintile Lowest 6.4 154 (9.0) 56 Second 8.9 191 6.6 67 Middle 8.0 203 13.0 61 Fourth 9.9 252 17.0 100 Highest 11.7 300 12.1 120 Total 9.4 1,100 12.1 404 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Friends, family members, and home are not considered sources for condoms. Domestic Violence | 205 DOMESTIC VIOLENCE 14 14.1 INTRODUCTION In recent years, there has been increasing concern about violence against women in general, and domestic violence in particular, in both developing and more developed countries. Not only has domestic violence against women been acknowledged worldwide as a violation of the basic human rights of women, but an increasing amount of research highlights the health burdens, intergenerational effects, and demographic consequences of such violence (Heise et al., 1994, 1998; Jejeebhoy, 1998; United Nations General Assembly, 1991). Gender-based violence occurs across all socioeconomic and cultural back- grounds, and in many societies women are socialized to accept, tolerate, and even rationalize domestic violence and to remain silent about such experiences (Zimmerman, 1994). Violence of any kind has a serious impact on the economy of a country; because women bear the brunt of domestic violence, they bear the health and psychological burdens as well. Victims of domestic violence are abused in a place that should be their most secure environment—their own homes. To stop this violence, which sometimes causes great physical harm, death, psychological abuse, separation, divorce, and a host of other social ills, the Moldovan government has enacted national legislation. For example, several articles in the 1994 Constitution provide for: equality for every person regardless of race, nationality, ethnic origin, language, religion, sex, opinions and political affiliation, and social status (Article 16); free access to the justice system in the case where rights have been violated (Article 20); and the right to physical and mental integrity, including freedom from torture or other inhumane and cruel punishment (Article 24). In 2003, the government passed the National Plan to Promote Human Equality (2003-2005) and, also in 1993, the National Plan of Action for Human Rights (2004-2008). NGOs have collaborated with government entities to implement programs to provide assistance to abused women (and children), as well as to launch informational campaigns advocating protection against violence. For example, Gender Centru, supported by the Soros Foundation, has collaborated with several ministries since 2000. Despite ongoing efforts to protect women and vulnerable populations against violence, there is still much to be done to enforce legislation, to protect potential victims, and to further inform and educate the population about the problem. Moreover, in addition to baseline indicators presented in this chapter, a mechanism is needed to keep a database with locally updated statistics (UNIFEM, 2005). 14.2 DATA COLLECTION Although gender-based violence is usually defined to include any physical, sexual, or psychologi- cal violence occurring not only in the family, but also within the general community (such as sexual har- assment at the workplace and trafficking in women for prostitution), this survey primarily covers domestic violence occurring within the household.1 There is a culture of silence surrounding gender-based violence, which makes collection of data on this sensitive topic particularly challenging. Even women who want to speak about their experiences of domestic violence may find it difficult because of feelings of shame or fear. The need to establish a 1 Outside of the MDHS, there have been no other large-scale data collection activities relevant to domestic violence conducted in Moldova. However, smaller scale surveys have been carried out; for example, UNIFEM conducted a survey in 2001-2001 entitled, “Atitudinea femeilor úi bărbaĠilor vis-a vis de violenĠa domestică úi hărĠuirea sexuală la locul de muncă” (UNIFEM, 2005). 206 | Domestic Violence rapport with the respondent and to ensure confidentiality and privacy during the interview is important for the entire survey, but is critical in ensuring the validity of the data on domestic violence. Complete privacy is also essential for ensuring the security of the respondent and the interviewer. Asking about or reporting violence, especially in households where the perpetrator may be present at the time of interview, carries the risk of further violence. Given these concerns related to the collection of data on violence, organizers of the 2005 MDHS took the following steps to ensure the validity of the data and the security of respondents and interview- ers: • The questionnaire was specially designed to allow the interviewer to continue with the domestic violence module only if privacy was ensured. If privacy could not be obtained, the interviewer was instructed to skip the module, thank the respondent, and end the interview. In Moldova, a total of 6,012 women were selected for interview with the module; about 5 percent of those selected did not respond to the module, of which about 1 percent could not be interviewed due to lack of privacy. In total, 5,737 women were successfully interviewed with the module. • Only one eligible woman in each selected household was administered the questionnaire module on domestic violence. In households with more than one eligible woman, the woman to whom the module was administered was randomly selected through a specially designed simple selection procedure. By interviewing only one woman in each household with the module, any security breach due to other persons in the household knowing about the information on domestic violence was minimized. • Informed consent of the respondent was obtained for the survey at the start of the individual interview. In addition, at the start of the domestic violence section, each respondent was read a statement informing her that she was now going to be asked questions that could be personal in nature because they explored different aspects of the relationship between couples. The statement assured her that her answers were completely confidential and would not be told to anyone else and that no one else in the household would be asked these questions. Research on violence suggests that the most common form of domestic violence for adults is spousal violence. Thus, spousal violence was measured using a modified and greatly shortened Conflict Tactics Scale (CTS) (Strauss, 1990). The CTS scale has been found to be effective in measuring domestic violence and can be easily adapted for use in different cultural situations. In the 2005 MDHS, spousal vio- lence was measured using the following set of questions: Does/Did your (last) husband/partner ever— a) Push you, shake you, or throw something at you? b) Slap you? c) Twist your arm or pull your hair? d) Punch you with his fist or with something that could hurt you? e) Kick you, drag you, or beat you up? f) Try to choke you or burn you on purpose? g) Threaten or attack you with a knife, gun, or any other weapon? h) Physically force you to have sexual intercourse even when you did not want to? i) Force you to perform any sexual acts you did not want to? The questions were asked with reference to the current husband for women currently married and the last husband for women formerly but not currently married. Women could answer with “yes” or “no” Domestic Violence | 207 to each item, and in cases when the answer was “yes,” women (excluding widows) were asked about the frequency of the act in the 12 months preceding the survey. A “yes” answer to one or more of items a to g constitutes evidence of physical violence, while a “yes” answer to items h or i constitutes evidence of sexual violence. A similar approach was used to measure the prevalence of emotional violence. Respondents were asked the question— Does/Did your (last) husband ever: a) Say or do something to humiliate you in front of others? b) Threaten to hurt or harm you or someone close to you? c) Insult you or make you feel bad about yourself? Women could answer “yes” or “no” to each item, and for items they answered “yes” to, they (excluding widows) were asked about frequency of occurrence in the 12 months preceding the survey. This approach of asking separately about specific acts has the advantage of not being affected by different understandings of what constitutes violence. A woman has to say whether she has, for example, ever been slapped, not whether she has ever experienced any violence. All women would probably agree on what constitutes a slap, but what constitutes a violent act or is understood as violence may vary across women as it does across cultures. In fact, summary terms such as “abuse” or “violence” were avoided in training and not used at all in the title, design, or implementation of the module. This approach has the advantage of giving the respondent multiple opportunities to disclose any experience of violence. In addition to spousal violence, women were asked whether they had experienced violence at the hands of anyone other than their current or last husband: “From the time you were 15 years old, has any- one other than your (current/last) husband hit, slapped, kicked, or done anything else to hurt you physi- cally?” Women who responded “yes” to this question were asked who had done this and the frequency of such violence during the 12 months preceding the survey. Although this approach to questioning is widely considered to be optimal, the possibility of some underreporting of violence cannot be entirely ruled out in any survey. Caution should always be exercised in interpreting not only the overall prevalence of violence data, but also differentials in prevalence be- tween subgroups of the population. Although a large part of any substantial difference in prevalence of violence between subgroups undoubtedly reflects actual differences in prevalence, differential underre- porting by women in the different subgroups can also contribute to exaggerating or narrowing differences in prevalence to an unknown extent. In the 2005 MDHS, men were not asked about their experience of violence because of security reasons. However, women were asked whether they had ever hit, slapped, kicked, or done anything else to physically hurt their husband or partner at any time when he was not already beating or physically hurt- ing them. They were further asked whether their husband/partner drinks alcohol and gets drunk, which is often associated with violence. 14.3 VIOLENCE SINCE AGE 15 Table 14.1 shows the distribution of women who have experienced violence since age 15, ever, and in the past 12 months, by background characteristics. The data show that one-quarter of all women (27 percent) have experienced violence since they were 15 and 13 percent experienced violence in the 12 months preceding the survey. 208 | Domestic Violence The social and economic background of a woman has a bearing on her chances of experiencing domestic violence. About one-third of all women in their thirties have experienced violence since age 15, with one in seven experiencing violence in the 12 months preceding the survey. Those age 15-19 have the lowest proportion of women who ever experienced violence (14 percent); this is likely due to the fact that the reference period of exposure to violence is short for many of the women in this group. Data from the 2005 MDHS imply that domestic violence may contribute to separation and divorce. Sixty percent of divorced or separated women report having experienced violence since age 15, compared with 28 percent of married women. Widowed women report somewhat higher levels of violence than women who are currently in union (34 percent versus 28 percent). Thirteen percent of women who have never been married report having experienced physical violence since age 15. Rural women are only somewhat more likely to report having ever experienced violence than urban women (29 percent as compared with 24 percent); dif- ferentials are similar for experience of violence in the past year, with 14 percent of rural women reporting violence, and 10 percent of urban women reporting the same. Women in Center region are most likely to have experienced violence since age 15 (30 percent), while women in North region are least likely to have experi- enced violence (23 percent). Table 14.1 Experience of physical mistreatment Percentage of women who have experienced violence since age 15, and percentage who experienced violence during the 12 months prior to the survey, by background characteristics, Moldova 2005 Percentage who have experienced violence Background characteristic Ever since age 15 In the past 12 months Number of women Age 15-19 14.0 7.3 1,075 20-24 22.5 11.1 872 25-29 27.0 14.4 736 30-34 31.9 15.7 723 35-39 33.2 15.1 651 40-44 28.3 12.7 786 45-49 30.9 14.3 895 Marital status Never married 12.7 4.9 1,415 Married or living together 27.9 14.7 3,805 Divorced/separated 60.3 22.1 404 Widowed 34.2 2.5 113 Residence Urban 23.7 10.0 2,301 Rural 28.5 14.3 3,436 Region North 23.4 9.3 1,726 Center 29.5 15.4 1,614 South 26.9 14.6 1,106 Chisinau 26.9 11.6 1,291 Education No education/primary (34.9) (24.6) 36 Secondary 28.9 14.6 3,516 Secondary special 27.9 12.3 1,014 Higher 18.4 6.2 1,170 Employment Not employed 22.8 10.6 2,784 Employed for cash 30.2 14.2 2,642 Employed not for cash 29.8 15.3 292 Missing * * 18 Wealth quintile Lowest 34.4 19.9 1,003 Second 32.3 14.6 985 Middle 22.6 10.3 1,200 Fourth 24.0 11.0 1,268 Highest 22.4 8.8 1,281 Total 26.6 12.6 5,737 Note: Figures in parentheses are based on 25-49 un- weighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been sup- pressed. Domestic Violence | 209 Experience of violence decreases with increasing educa- tion for both ever-experience of violence as well as experience of violence in the past year; however, only women who have higher than secondary education are much less likely to report violence. For example, 18 percent of women with higher than secondary education reported ever experiencing violence since the age of 15, while about 28 percent of women with secondary or secondary special education report having ever experienced violence. Women who are not employed are less likely to have experienced violence than those who are employed (23 percent compared with 30 per- cent). More violence is reported among women living in house- holds in the two poorest quintiles than among women living in the middle and higher quintiles (about 33 percent compared with about 22 percent). Table 14.2 shows that the main perpetrators of violence against women are husbands (69 percent) and, to a lesser extent, fathers/stepfathers (14 percent) and mothers/stepmothers (7 percent). 14.4 MARITAL VIOLENCE Marital violence refers to violence perpetrated by partners in a marital union. Table 14.3 shows the percentage of married, divorced, separated, or widowed women who have ever experi- enced emotional, physical, or sexual violence by their current or last husband or partner, according to selected background characteristics. Note that the different types of violence are not mutually exclusive; therefore, women may report experiencing multiple forms of violence. Twenty-three percent of ever-married women report having experienced emotional violence by husbands, 24 percent report physical violence, and 4 percent report sexual violence. Almost one-third (32 percent) of ever-married women report suffering emotional, physical, or sexual violence, while 3 percent have experienced all three forms of violence by their current or most recent husband. The experience of all forms of spousal violence generally rises with exposure: as women increase in age, there is an increasing tendency to report having ever experienced various types of violence. The table further shows that divorced or separated women are more than twice as likely to have been abused emotionally, physically, and sexually than other women, suggesting that the violence might have been a factor in the termination of their marriages. Again, widowed women showed somewhat higher levels of all types of violence than women who are currently in union; it may be that since these women’s husbands are no longer living, widows feel at greater liberty to report episodes of violent behavior. Women who have no living children report less emotional, physical, and sexual violence, perhaps because they are more likely to be newly married and therefore have spent less time exposed to the possibility of experiencing marital violence. The relationship between education and spousal violence is consistently negative across all types of violence: the more education a woman has, the less likely she is to report having experienced spousal abuse. Women who are employed, whether they are paid in cash or not, are marginally more likely to have experienced spousal violence as compared to unemployed women. Table 14.2 Perpetrators of violence Among women who have experienced physical violence since age 15, percentage reporting specific perpetrators, Moldova 2005 Perpetrator Percentage Husband 68.7 Former husband or partner 4.7 Mother-in-law 0.4 Father-in-law 0.1 Other in-law 0.2 Current boyfriend 0.8 Former boyfriend 4.3 Mother or step-mother 7.3 Father or step-father 13.7 Sister or brother 3.5 Daughter or son 0.2 Other blood relative 2.6 Teacher 0.3 Employer or someone at work 1.6 Police or soldier 0.1 Other 6.8 Number of women 1,491 210 | Domestic Violence The general trend in the relationship between household wealth status and experience of the three types of violence is that as wealth increases, reporting of violence decreases; an exception here is emotional violence, which has a nonlinear relationship to household wealth. The greatest differences between women in the poorest and wealthiest quintiles are apparent for physical violence: 35 percent of women in the poorest households report ever experiencing physical spousal violence, while 17 percent of women in the wealthiest households report the same. Table 14.3 Marital violence Percentage of married, divorced or separated, and widowed women who have ever suffered emotional, physical, or sexual violence by their current or most recent husband, according to background characteristics, Moldova 2005 Type of violence Background characteristic Emotional Physical Sexual Physical or sexual Emotional, physical, or sexual Emotional, physical, and sexual Number of women Age 15-19 18.6 20.1 1.7 20.1 27.9 1.0 113 20-24 12.3 16.8 1.7 17.5 20.9 0.8 531 25-29 20.9 19.6 3.1 19.6 27.9 2.6 679 30-34 22.6 24.3 4.8 24.8 32.1 3.6 701 35-39 26.7 28.3 5.6 28.7 35.9 5.0 634 40-44 25.0 25.6 4.2 26.6 34.1 3.3 778 45-49 27.3 28.1 5.1 28.3 36.1 4.0 884 Marital status Married or living together 19.8 20.6 3.0 21.0 28.1 2.2 3,805 Divorced/separated 52.2 55.3 14.0 55.6 64.8 12.8 404 Widowed 24.7 33.1 8.1 33.1 34.2 5.8 113 Number of living children 0 14.2 15.4 2.1 15.5 19.4 1.8 473 1-2 22.5 23.1 4.2 23.5 31.0 3.4 2,975 3-4 28.7 31.5 4.8 32.5 40.2 3.5 792 5+ 33.9 39.8 7.2 39.8 44.0 7.2 81 Education No education/primary (30.7) (29.1) (1.4) (29.1) (44.9) (0.0) 32 Secondary 25.3 28.6 5.0 29.1 36.0 4.2 2,549 Secondary special 21.4 22.3 4.3 23.0 29.1 3.0 904 Higher 17.2 12.3 1.6 12.4 20.9 1.0 836 Employment Not employed 20.1 23.1 3.7 23.4 29.6 2.9 1,698 Employed for cash 25.1 24.7 4.5 25.2 33.0 3.6 2,356 Employed not for cash 22.4 26.1 4.5 26.1 33.1 3.3 254 Wealth quintile Lowest 30.8 35.4 5.4 35.5 44.1 4.6 764 Second 24.7 29.4 5.0 30.1 35.5 4.1 749 Middle 17.9 20.5 3.9 21.4 26.8 2.6 897 Fourth 22.4 21.8 3.9 22.1 29.7 2.7 946 Highest 20.6 16.8 3.0 16.9 25.3 2.7 966 Total 23.0 24.1 4.1 24.6 31.7 3.3 4,322 Note: Figures in parentheses are based on 25-49 unweighted cases. Domestic Violence | 211 The proportions of ever-married women who have experienced different forms of violence by their current or last husbands, ever and during the 12 months preceding the survey, are presented in Figure 14.1. The most common forms of spousal violence are ever having been pushed, shaken or thrown, or having been slapped, each of which have been experienced by 20 percent of women. Eleven percent have ever been punched; 9 percent have ever had their arm twisted or hair pulled; and 6 percent have been kicked or dragged. Four percent of women have suffered marital rape. The least commonly reported forms of marital violence against women are being strangled or burned (3 percent), threatened or attacked with a weapon (3 percent), and being forced to perform sexual acts other than intercourse (2 percent). 14.5 ONSET OF SPOUSAL VIOLENCE AGAINST WOMEN To study the timing of the onset of marital violence, the 2005 MDHS asked ever-married women who reported physical or sexual violence by their spouse how long after they got married the violence first occurred. Table 14.4 shows the percent distribution of married women, divorced or separated women, and widowed women by the number of years between marriage and the first time they experienced physical or sexual violence by their current or most recent husband, according to duration since marriage. The percentages of women who have not experienced spousal violence are shown as well. Table 14.4 shows that in the majority of cases, initiation of violence takes place early in the mar- riage (or sometimes prior to marriage). Fourteen percent of women experience spousal violence in the first two years of marriage, and 20 percent experience violence in the first five years of marriage. Women who are currently married but married more than once and women who are currently di- vorced or separated are more likely to have experienced violence early in their marriages than women who married only once. 20 20 9 11 6 3 3 4 2 11 12 5 6 3 2 2 2 1 Slapped Pushed/shaken/thrown Twisted arm/pulled hair Punched Kicked/dragged/beaten up Strangled/burned Threatened/attacked with weapon Forced to have intercourse Forced to perform other sexual acts 0 5 10 15 20 25 Ever In the past 12 months Figure 14.1 Percentage of Women Who Have Experienced Specific Forms of Spousal Violence Ever and in the 12 Months Preceding the Survey MDHS 2005 212 | Domestic Violence Table 14.4 Onset of spousal violence Percent distribution of married, divorced or separated, and widowed women who have experienced physical or sexual violence by current or most recent husband, by the number of years between marriage and the first episode of violence, according to marital status and duration of first marriage or union, Moldova 2005 Years between union and first experience of violence Marital status/ duration of first marriage/union No violence experienced Violence before marriage Less than 1 year 1-2 years 3-5 years 6-9 years 10 or more years Don’t know/ missing Total Number of women Currently married 79.0 0.6 2.7 8.2 5.1 1.4 2.8 0.2 100.0 3,805 Married only once 79.3 0.6 2.5 7.9 5.1 1.5 2.9 0.2 100.0 3,403 <1 year 93.1 3.9 0.9 na na na na na 100.0 114 1-5 years 86.3 1.1 4.8 6.5 1.3 0.0 0.0 0.1 100.0 650 6-9 years 84.1 0.8 2.8 7.4 4.3 0.3 0.0 0.4 100.0 419 10 or more years 75.7 0.2 1.8 8.9 6.6 2.2 4.4 0.2 100.0 2,219 Married more than once 75.9 1.2 4.1 10.4 5.1 0.9 2.3 0.0 100.0 402 Formerly married Divorced/separated 44.4 3.7 14.2 21.8 7.5 3.0 4.6 0.7 100.0 404 Widowed 66.9 0.0 3.2 15.3 6.4 3.8 4.3 0.0 100.0 113 Total 75.4 0.9 3.8 9.7 5.3 1.6 3.0 0.3 100.0 4,322 na = Not applicable 14.6 PHYSICAL CONSEQUENCES OF SPOUSAL VIOLENCE Table 14.5 shows the percentage of married, divorced, or separated women reporting different types of physical consequences resulting from something their current or last husband or partner did to them, by type of violence. Among all married, divorced or separated, or widowed women, 15 percent reported having had bruises or aches. Eye injuries, sprains or dislocations (6 percent) and broken bones or other injuries (3 percent) are less common consequences of spousal violence. Looking at consequences of violence in the past year, which excludes widowed women from the denominator, it was found that 9 percent of women had bruises or aches, 4 percent of women had eye injuries, sprains or dislocations, and 2 percent had broken bones or other injuries as a result of something that their husband did to them. Among women who reported ever experiencing physical violence, 60 percent reported having had bruises or aches, 24 percent had an eye injury, sprain, or dislocation, and 11 percent had a broken bone or other injury because of something their husband or partner did. Women who reported ever experiencing sexual violence from their husband or partner were considerably more likely to report having experienced physical consequences as a result of something that their husband or partner did: 76 percent reported having bruises or aches, 41 percent reported having an eye injury, sprain, or dislocation, and 27 percent reported having a broken bone or other injury. Domestic Violence | 213 Table 14.5 Physical consequences of spousal violence Percentage of married, divorced or separated, and widowed women who reported specific physical consequences resulting from something their current or most recent husband or partner did to them, according to type of violence reported, Moldova 2005 Physical consequence Type of violence Had bruises or aches Had eye injuries, sprains or dislocations Had injury or broken bones Number Physical violence Ever experienced 60.2 23.9 10.6 1,043 At least once in last year 63.4 27.3 11.6 593 Sexual violence Ever experienced 75.5 40.9 26.9 179 At least once in last year 71.8 37.6 23.6 104 Physical or sexual violence Ever experienced 59.1 23.4 10.4 1,062 At least once in last year 61.9 26.5 11.6 614 No violence experienced na na na 3,260 Total who ever experienced violence 14.5 5.8 2.6 4,322 Total who experienced violence at least once in past year (excluding widows) 9.0 3.9 1.7 4,209 na = Not applicable 14.7 VIOLENCE BY SPOUSAL CHARACTERISTICS AND WOMEN’S STATUS INDICATORS Since the perpetrators of spousal violence are usually husbands, it is important to understand the characteristics of husbands. It is also useful to examine whether spousal violence varies with indicators of women’s status. Table 14.6 shows the percentage of married, divorced, or separated women who have experienced different forms of spousal violence by the current or last husband ever and in the year pre- ceding the survey, as well as the percentage of women who have initiated violence against their husbands, by spousal characteristics and selected women’s status variables. Twenty-three percent of married, separated, or divorced women have ever experienced emotional violence, 24 percent have ever experienced physical violence, and 4 percent have ever experienced sexual violence. Women’s experience of all three forms of violence varies negatively with spousal education; the more education the husband or partner has, the less likely the respondent is to report experience of violence. Interestingly, the proportion of women who report ever being violent to their husbands when the husband was not hitting her does not vary by husband’s education, and it varies inconsistently by husband’s education among women who report initiating violence against their husbands in the past year. Women who are older than their husband are consistently more likely to report experiencing all types of violence than women who are younger than their husbands. For women who are younger than their husbands, the age gap between spouses seems to matter little except in the case of emotional violence: women who are 10 or more years younger than their husbands are less likely to report emotional violence than other women. 214 | Domestic Violence Table 14.6 Spousal violence by spousal characteristics and women’s status indicators Percentage of married women and divorced or separated women who ever experienced violence or who experienced violence in the past year, by type of spousal violence from current or most recent husband, and percentage of women who have been violent to their husbands ever or in the past year, by spousal characteristics and women's status indicators, Moldova 2005 Emotional violence Physical violence Sexual violence Physical or sexual violence Violence against husband Spousal characteristics and women’s status indicators Ever Last year Ever Last year Ever Last year Ever Last year Never experi- enced violence Ever Last year Number of women Education of spouse No education/primary (32.3) (32.3) (26.7) (17.3) (1.5) (1.5) (26.7) (17.3) (73.3) (9.7) (6.5) 30 Secondary 25.4 19.0 28.0 16.8 4.8 3.0 28.4 17.3 71.6 7.0 3.4 2,846 Secondary special 21.4 15.4 22.4 12.0 3.8 2.3 23.3 13.1 76.7 7.1 2.3 623 Higher 13.0 9.4 7.8 4.4 1.0 0.3 7.9 4.5 92.1 7.1 4.5 680 Missing (36.1) (28.4) (27.7) (16.7) (4.3) (4.3) (27.7) (16.7) (72.3) (15.2) (2.0) 30 Age difference between wife and spouse Wife older than husband 24.4 19.5 26.6 18.0 3.8 3.0 26.6 18.1 73.4 8.0 4.1 475 Husband older by: < 2 years 18.1 15.2 19.2 12.4 2.0 1.5 19.6 12.6 80.4 7.0 4.3 815 2-4 years 21.2 18.3 20.5 13.6 3.5 2.6 21.2 14.3 78.8 5.3 2.6 1,419 5-9 years 17.8 15.3 18.8 12.4 2.5 1.7 19.2 12.9 80.8 5.2 2.5 898 10+ years 14.6 11.0 18.4 10.7 3.2 2.4 19.3 11.6 80.7 7.2 3.7 188 DK/Missing * * * * * * * * * * * 10 Differences in education Husband has more education 21.0 15.8 23.3 14.3 3.8 2.6 23.6 14.7 76.4 6.8 3.8 1,231 Wife has more education 23.4 16.6 24.3 13.0 3.9 2.3 24.7 13.5 75.3 8.4 3.9 1,344 Both have equal education 23.6 18.0 23.8 14.6 4.2 2.4 24.4 15.2 75.6 5.8 2.8 1,582 Neither educated * * * * * * * * * * * 3 Don’t know/missing (33.4) (27.3) (30.5) (19.6) (5.1) (5.1) (30.5) (19.6) (69.5) (19.5) (1.3) 48 Woman can refuse sex to husband1 Yes for all reasons 22.4 16.6 23.1 13.8 4.0 2.6 23.6 14.2 76.4 6.8 3.4 3,063 No for one or more reasons 24.4 18.2 26.0 15.0 4.1 2.1 26.4 15.5 73.6 8.0 3.6 1,146 Number of decisions in which woman has final say2 0 50.6 20.3 53.6 19.9 13.5 4.8 53.9 20.5 46.1 16.4 5.6 431 1-2 34.9 34.9 35.1 28.4 4.3 4.3 36.1 29.4 63.9 11.5 7.7 68 3-4 19.5 16.3 20.2 13.2 2.9 2.2 20.7 13.6 79.3 6.0 3.1 3,710 Family structure Nuclear 23.1 17.2 24.4 14.5 4.3 2.6 24.8 14.9 75.2 6.8 3.4 3,438 Non-nuclear 21.9 16.3 21.5 12.4 2.9 1.8 22.1 13.0 77.9 8.3 3.5 771 Total 22.9 17.1 23.9 14.1 4.0 2.5 24.3 14.6 75.7 7.1 3.4 4,209 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For specific reasons see Table 3.11.1. 2 For specific decisions see Table 3.9. Domestic Violence | 215 Experience of any of the three types of violence varies little by differences in level of education between women and their husbands. While the difference in experience of violence between women who think it is justifiable for a woman to refuse to have sex with her husband on any grounds, and those who do not is small, it is nevertheless consistent: women who think it is justifiable for a woman to refuse sex with her husband for all given reasons are slightly less likely to report ever experiencing any of the three types of violence. Differences in household decisionmaking ability have more obvious associations with experience of violence. Across all types of violence, for nearly all referenced time periods, women who have more decisionmaking authority are less likely to report having experienced violence from their husbands. They are also less likely to report that they have ever hit their husband when their husband was not hitting them. Women’s experience of violence varies minimally, yet consistently, across the three types of violence according to family structure: women who have non-nuclear living arrangements are slightly less likely to report violence. Emigration | 217 EMIGRATION 15 Emigration is an event that occurs when people leave their country to establish a new, “usual” place of residence across an international boundary, and the people who move abroad are called emigrants (Hinde, 1998). Net migration, or the difference between in-migration and out-migration, is one of the three components of population change. The other two components are fertility and mortality. Population change is the result of the difference between the birth rate and the death rate (natural increase) plus the net migration rate. In countries where birth rates are much higher than death rates, such as in lesser developed countries in the middle of their demographic transition, population change is primarily due to natural increase. However, in more industrialized countries where the difference between birth rates and death rates is low, net migration often becomes a more important factor in population change than natural increase. In Moldova, and in post-Soviet countries in general, large-scale labor emigration is an important demographic phenomenon that has a substantial negative impact on the population growth as well as on the social and economic structure of society (Cuc et al., 2005; Jandl, 2003; Korobkov and Palei, 2005). Accurate estimates on emigration are rarely available simply because few countries gather comprehensive migration statistics on a continuous basis. Likewise, collecting data on emigration in a cross-sectional survey presents challenges mainly because the people of interest, by definition, no longer live in the target population. Nevertheless, a nationally representative survey such as the 2005 MDHS presents a unique opportunity to assess the magnitude of this event and to describe attributes of the emigrant population. The MDHS collected information from households about former members who used to live in the household and who now live abroad. The survey incorporated the same kinds of questions that were asked in the Moldova Population Census 2004 (form 2P, approved by the Council of the Department for Statistics and Sociology of the Republic of Moldova). These questions gather information about the relationship of the former household member to the current head of household, the country where the former member currently resides, the reason that the former member moved abroad, and the year the former member emigrated. In addition to these questions, further information was gathered to flesh out the sociodemographic profile of emigrants. The purpose of this chapter is to describe the flow of emigration and to provide a demographic and socioeconomic profile of emigrants. It also identifies key areas where further research would serve to better explain trends. 15.1 HOUSEHOLDS HAVING AT LEAST ONE FORMER MEMBER LIVING ABROAD Table 15.1 shows the percentage of households in which at least one former member emigrated. Seventeen percent of households reported having had at least one member who emigrated. This percentage is about the same in urban and rural households (16 and 17 percent, respectively).1 While these estimates represent a substantial portion of households in Moldova, they still underestimate the true level of emigration to the degree that they do not include entire households that moved abroad. (The 1 A potential measurement imprecision of this indicator is that more than one household in the sample could theoretically report on the same former member having emigrated, in which case the household indicator would slightly overestimate the per capita emigration rate. For example, if a student from the North region lived in Chisinau while attending university, and the student’s former household in the North and the former household in Chisinau were both selected for the MDHS sample, then both households would report on the same emigrant. Anytime an event can be reported by more than one household, there is the potential to overestimate. 218 | Emigration MDHS sample is designed to collect information about former household members as reported by a member of the current household; the sample excludes those households in which all members have moved abroad.) By comparison, a study in 2004 estimated that almost 22 percent of households had somebody working abroad at the time of interview (CBX AXA, 2004). Some of this difference could be due to a difference in sample design. The percentage of households where at least one former member has emigrated is an important indicator in the value of remittances sent back to households in Moldova. In 2004, the total official estimate of gross inflows of worker’s remittances was about 27 percent of the gross domestic product (Cuc, 2005). Table 15.1 Households from which former members have emigrated Proportion of households with former members who have emigrated, by residence and region, Moldova 2005 Residence Region Emigration status Urban Rural North Center South Chisinau Total Households in which at least one former member emigrated 16.1 17.4 15.2 19.4 21.0 12.9 16.9 Households in which no one emigrated 83.9 82.6 84.8 80.6 79.0 87.1 83.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households 4,444 6,651 3,614 2,985 2,026 2,469 11,095 The highest percentage of households with at least one emigrant is in the South region (21 percent) and the lowest in Chisinau (13 percent). Further research could serve to explain the differential: Is the indicator the lowest in Chisinau because people have higher standards of living in the capital relative to other places in Moldova and are thus less motivated to move abroad? Is it a data artifact reflecting a systematic lack of entire households in Chisinau that moved away and are therefore not accounted for in the MDHS sample? Figure 15.1 shows the percentage of households with emigrants by wealth quintile. Overall, households with emigrants tend to come from the middle (23 percent) and fourth (21 percent) wealth quintiles, and fewer come from the richest and poorest quintiles. This pattern is not unexpected because poor households are least likely to have the capital to initiate or support a move abroad, and rich households may not be motivated by the potential remittances to move abroad. Emigration | 219 15.2 HOUSEHOLD CHARACTERISTICS OF EMIGRANTS’ FORMER HOUSEHOLDS A further examination of household emigration trends reveals the interdependent, clustering nature of emigrants in the population versus an even distribution among households. In the 17 percent of households where emigration has occurred, it is not unusual that more than one former resident has emigrated. Table 15.2 shows that in households where former members have emigrated, about a fifth of households had two members who emigrated (19 percent) and 6 percent had three or more. This clustered distribution is evident in urban and rural areas and across regions: in 24 percent of households in urban areas with at least one emigrant, more than one member has emigrated; in 27 percent of households in rural areas with at least one emigrant, more than one member has emigrated. The clustering effect is highest in the North region (29 percent), and lowest in Chisinau (22 percent). Table 15.2 Characteristics of households from which former members have emigrated Percent distribution of households with former members who have emigrated by number of emigrants and wealth quintile, according to residence and region, Moldova 2005 Residence RegionNumber of emigrants/ wealth quintile Urban Rural North Center South Chisinau Total Number of emigrants 1 75.6 73.5 71.0 75.3 74.3 78.2 74.3 2 18.4 20.0 22.4 17.6 19.8 17.1 19.4 3+ 6.0 6.4 6.6 7.1 5.9 4.6 6.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Wealth quintile Lowest 1.0 20.5 16.7 16.7 13.1 0.0 13.0 Second 4.1 31.7 28.4 24.2 22.5 1.3 21.2 Middle 14.4 30.6 26.7 25.5 35.5 3.5 24.4 Fourth 38.3 16.0 19.1 26.3 23.5 31.9 24.5 Highest 42.2 1.2 9.0 7.3 5.4 63.2 16.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households 715 1,158 549 580 426 319 1,874 Figure 15.1 Percentage of Households With at Least One Emigrant by Wealth Quintile 11 17 23 21 15 Lowest Second Middle Fourth Highest Wealth quintile 0 5 10 15 20 25 Percentage MDHS 2005 220 | Emigration The native language of an emigrant is a useful indicator of his or her ethnicity. The MDHS did not ask information specifically about the native language or ethnicity of the emigrant, but a revealing background characteristic pertaining to emigrant households is that in 81 percent of households with at least one emigrant, the head of household was interviewed in Romanian language, versus 19 percent interviewed in Russian language (data not shown). One would expect a significant association between the native language of the emigrant and the preferred language of the current head of household. 15.3 BACKGROUND CHARACTERISTICS OF EMIGRANTS Table 15.3 presents the percent distribution of emigrants by background characteristics. In addition to standard information collected on household assets, specific information on emigrants’ sex, age, and relation to current household head was reported by the respondent of the household questionnaire. Table 15.3 Background characteristics of emigrants at time of emigration Percent distribution of emigrants by age at time of emigration, residence, region, relationship to household head, and wealth quintile, according to sex, Moldova 2005 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age at time of emigration <15 3.3 40 43 2.6 34 42 15-19 10.4 125 133 12.0 157 168 20-24 22.0 265 258 26.6 350 349 25-29 17.9 215 217 19.0 250 242 30-34 12.4 149 150 11.4 150 151 35-39 10.7 128 135 9.7 128 127 40-44 9.9 118 131 7.2 95 100 45-49 9.0 107 112 7.6 100 105 50+ 4.0 47 54 3.5 46 50 Residence at time of emigration Urban 39.0 468 688 36.3 477 714 Rural 61.0 732 551 63.7 837 626 Region at time of emigration North 28.0 336 319 32.2 423 413 Center 29.8 358 329 32.2 423 391 South 24.2 290 313 21.2 279 298 Chisinau 18.0 216 278 14.5 190 238 Relation to current head of former household Spouse/partner 26.6 319 326 25.5 336 345 Father/mother 6.9 83 97 3.3 44 48 Son/daughter 46.5 559 567 53.9 708 720 Son-in-law/daughter-in-law 8.6 104 103 9.8 129 120 Other non-relative 7.6 91 96 5.0 66 73 Other relative/DK/missing 3.6 44 50 2.4 3.1 34 Wealth quintile of former household Lowest 10.2 122 97 14.9 196 148 Second 21.9 262 212 22.2 291 234 Middle 26.2 314 295 23.3 306 296 Fourth 24.9 299 363 24.4 320 391 Highest 16.8 202 272 15.3 201 271 Total1 100.0 1,200 1,239 100.0 1,314 1,340 1 Includes cases where information is missing Emigration | 221 The distribution of emigrants by age of emigration is similar for males and females. The most common age group for people to emigrate is age 20-24 for both sexes. This age group accounts for roughly one-quarter of all emigrants (22 percent of females and 27 percent of males). Approximately three-quarters of all emigrants emigrate between age 15 and 39 years (73 percent of females and 79 percent of males). As mentioned above, the percentage of households where former members emigrated was about 17 percent, with little difference between urban and rural households. However, examining the origin of individual emigrants in Table 15.3, it appears that more emigrants actually originate from rural households (61 female and 64 percent male). The difference between the distributions, that is, between the distribution of households with emigrants versus the distribution of individual emigrants, further suggests that the “clustering” effect is greater in rural households (i.e., rural households are more likely to have more than one member that emigrated). Overall, a slightly higher proportion of emigrants are males than females (52 and 48 percent, respectively). However, in Chisinau and the South region, a slightly higher proportion of emigrants are females than males. Emigration has considerable impact on family structure. More than one-quarter of both males and females living abroad have left behind a wife or husband in their household of origin. Over half of emigrants are the son or daughter, or son-in-law or daughter-in-law, of the head of the household (55 percent of female emigrants are the daughter or daughter-in-law, 64 percent of male emigrants are the son or son-in-law). The distribution of emigrant households by wealth quintile shows an inverted u-shaped pattern. A small proportion of emigrants originated in households in the poorest quintile (10 percent of women and 15 of men) and in the wealthiest quintile (17 percent of women and 15 percent of men) but the largest proportion of emigrants, 70 percent or more, came from households in the middle three quintiles. 15.4 MAIN REASON FOR EMIGRATING Labor is overwhelmingly the main reason that people in Moldova emigrate. Household respondents report that for 83 percent of female emigrants and 91 percent of male emigrants, work was the main reason for moving abroad. An additional 7 percent of women and 3 percent of men emigrated to accompany their spouse or family abroad; 3 percent of women and 1 percent of men emigrated in order to marry a foreigner. Five percent or less of emigrants left Moldova with their main purpose being to study. Table 15.4 Main reason for emigrating Percent distribution of emigrants by main reason for emigrating as reported by household interview respondent, according to sex, Moldova 2005 Women Men Total Main reason for emigration Weighted percent Number Weighted percent Number Weighted percent Number Work 83.3 999 90.8 1,194 87.2 2,193 Study 4.7 57 3.7 49 4.2 106 Accompany spouse/family 6.7 80 2.7 36 4.6 116 Marry foreigner 2.9 35 1.1 14 1.9 49 Other/don’t know 2.3 28 1.5 20 2.0 48 Total 100.0 1,200 100.0 1,314 100.0 2,514 222 | Emigration Specific information on the type of work that motivated people to move abroad was not collected. The reasons for this are mainly related to quality of data that would have been obtained from a secondary source. First, although work is clearly the main motivation for emigrants moving abroad, the household respondent who was reporting on behalf of the emigrant may not have been able to describe the type of work the emigrant expected to have abroad at the time of emigration (the emigrant may also not have had clear knowledge of the work he or she would find abroad). Second, the type of work that was the initial motivation for moving abroad is likely not to be the current occupation of the emigrant. Third, the more interesting information to have would be the work that the emigrant is currently doing. Information on current occupation was not collected from the household respondent because the respondent may not know exactly what kind of work the emigrant does, or they may not report honestly on the type of work (for trafficked emigrants, for example). Current occupation and remittances of emigrants are important but difficult fields to research, and other research methodologies better designed than a national survey to collect detailed information are being developed (IMF, 2005a; IMF, 2005b). 15.5 TRENDS IN EMIGRATION: CURRENT AGE AND SEX OF EMIGRANTS This section examines emigration trends over time and the age and sex profile of Moldovans living abroad. Figure 15.2 shows that emigration was negligible prior to the dissolution of the Soviet Union in 1991, and even throughout most of the first decade of Moldova’s independence after August 1991. In the first half of the decade, emigration may have been more ethnically or politically motivated when, for example, ethnic Russians moved to Russia and ethnic Ukrainians moved to Ukraine (Korobkov and Palei, 2005). By 2000, in the wake of the regional economic crisis in 1998 that hit Moldova particularly hard, it was the lure of better economic opportunities abroad that pushed emigration rates up sharply; over half (57 percent) of all emigrants recorded in the survey left between the beginning of 2001 and the time of data collection for this survey (mid-2005). With these observations in mind, however, two data quality issues should be noted. First, an inherent bias is that the survey asks about emigrants from current households. The longer ago the emigration, the more likely the household is to be reconstituted or dissolved and thus not able to report on emigrants. Second, there is potential recall bias. � � � � � � � � � � � � � � � � <1 99 1 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 (tr un ca ted mi d- ye ar) 20 05 0 5 10 15 20 25 30 35 Women Men� Figure 15.2 Percent Distribution of Emigrants by Year of Emigration and Sex Year Percent Emigration | 223 Figures 15.3.1 and 15.3.2 and Table 15.5 show the distribution of emigrants by current age and original household residence. In Figures 15.2.1 and 15.2.2, the distribution of emigrants from urban areas is a flatter distribution than that of emigrants from rural areas. Emigrants from rural areas are significantly younger than those from urban origins. Forty-three percent of emigrants from rural areas are age 20 to 29, compared with only 32 percent from urban areas (Table 15.5). For both areas of residence, but especially for rural areas, this level of emigration represents a significant loss of labor and reproductive potential. Figure 15.3.1 Current Age of Emigrants from Urban Areas 3 4 12 17 15 13 13 12 11 3 5 17 18 17 11 10 11 8 <15 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50+ 0 5 10 15 20 25 Women Men MDHS 2005 Age group Percent Figure 15.3.2 Current Age of Emigrants from Rural Areas 2 5 20 20 15 14 9 11 4 1 6 22 23 16 8 10 8 6 <15 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50+ 0 5 10 15 20 25 Women Men MDHS 2005 Age group Percent 224 | Emigration That emigrants are disproportionately younger from rural areas than from urban areas is potentially a combination of two phenomena. First, emigration trends may have started earlier in urban areas than in rural areas, so emigrants from urban areas have been subject to a longer period of aging abroad (much like populations age when fertility declines); second, emigrants from urban areas tend to emigrate at older ages than those in rural areas. Further research could explain these complex patterns. Table 15.5 Current age and sex of emigrants Percent distribution of emigrants by current age, in five-year age groups, according to sex and original residence, Moldova 2005 Residence Urban Rural Total Current age Women Men Total Women Men Total Women Men Total <15 2.7 3.1 2.9 1.9 0.7 1.3 2.2 1.5 1.9 15-19 3.9 4.7 4.3 4.6 5.8 5.2 4.3 5.4 4.9 20-24 12.2 17.2 14.7 20.4 22.4 21.4 17.2 20.5 18.9 25-29 16.7 18.0 17.3 19.5 23.4 21.6 18.4 21.4 20.0 30-34 14.8 16.9 15.8 15.1 15.8 15.5 15.0 16.2 15.6 35-39 13.4 11.3 12.4 14.4 8.1 11.0 14.0 9.3 11.5 40-44 13.4 9.8 11.6 9.4 9.8 9.6 11.0 9.8 10.4 45-49 11.7 11.1 11.4 10.6 8.4 9.4 11.0 9.4 10.2 50+ 10.5 7.7 9.1 3.9 5.7 4.9 6.5 6.4 6.5 Missing 0.8 0.2 0.5 0.2 0.0 0.1 0.4 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of emigrants 468 477 946 732 837 1,569 1,200 1,314 2,514 15.6 DESTINATION COUNTRIES Figure 15.4 shows emigrants’ destination countries. Given that many Moldovans are ethnic Russians, half of emigrants have moved to Russia; it increases to 54 percent when Ukraine and other Commonwealth of Independent States (countries of the former Soviet Union) are included. One-third of all emigrants moved to Western Europe, with Italy as the primary destination (20 percent) followed by Portugal, Greece, and Spain. The remainder of emigrant destinations include Turkey, North America, Israel, Romania, and other countries. Emigration | 225 Table 15.6 further breaks down emigrants by destination, according to sex and age. One reason for breaking down destinations by age of emigrant (at time of emigration) and sex is to try and detect evidence of human trafficking. Trafficking in persons, as defined in the United Nations Protocol to Prevent, Suppress, and Punish Trafficking in Persons (Dec. 2002) means “the recruitment, transportation, transfer, harboring, or receipt of persons, by means of the threat or use of force or other forms of coercion, of abduction, of fraud, of deception, of the abuse of power or of a position of vulnerability, or of the giving or receiving of payments or benefits to achieve the consent of a person having control over another person, for the purpose of exploitation.” Moldova is reported to be one of the leading exporters of human beings to Western Europe, a trend that started in 1994-1995 with the wave of illegal emigration (Costachi, 2003). (The reader is reminded that the MDHS sample does not include the Transnistria, a region that may be involved with trafficking.) Although the literature on this problem has continued to grow in the past 10 years, due to its sensitive nature there is still very limited statistical data relevant to its actual magnitude (Laczko, 2002). The MDHS tries to make up for some of this lack of data by providing a profile of emigrants in general, which may serve to at least validate or challenge previous estimates. Table 15.6 shows that about 50 percent of females from Moldova who ever emigrated to any country were age 15 to 29 years at the time of emigration. For males, this proportion is 58 percent indicating that overall, men have emigrated at younger ages than women. For economic reasons, most trafficking of women is to richer countries in Western Europe and to Turkey (Costachi, 2003). Table 15.6 shows that over half of the female emigrants to Turkey were between age 15 and 29 years, and similarly for some countries in Western Europe. While the MDHS data do not provide specific information on the trafficking of women, it is a valuable source of data that should be utilized along with other data available. Figure 15.4 Destination Countries of Emigrants MDHS 2005 Russia 50% Other FSU 4% Italy 20% Other Western Europe 15% Turkey 4% North America/Israel/ Romania 5% Other 2% 226 | Emigration Table 15.6 Destination countries of emigrants Percent distribution of emigrants by age and sex, according to destination countries, Moldova 2005 Women/girls Men/boys Total Destination Age 15-29 Age <15 and •30 Total Number Age 15-29 Age <15 and •30 Total Number Age 15-29 Age <15 and •30 Total Number Former Soviet Union 49.8 50.2 100.0 515 58.8 41.2 100.0 841 55.4 44.6 100.0 1,356 Russia 49.0 51.0 100.0 467 58.3 41.7 100.0 781 54.8 45.2 100.0 1,249 Ukraine (58.3) (41.7) 100.0 48 67.2 32.8 100.0 54 63.0 37.0 100.0 102 Other FSU * * 100.0 0 * * 100.0 5 * * 100.0 5 Western Europe 47.4 52.6 100.0 497 53.9 46.1 100.0 375 50.2 49.8 100.0 872 Greece (41.0) (59.0) 100.0 34 (53.3) (46.7) 100.0 30 46.8 53.2 100.0 64 Portugal * * 100.0 17 53.1 46.9 100.0 69 51.3 48.7 100.0 86 Italy 42.7 57.3 100.0 355 50.7 49.3 100.0 151 45.1 54.9 100.0 507 Spain * * 100.0 21 (49.0) (51.0) 100.0 35 48.9 51.1 100.0 55 Other Western Europe 75.2 24.8 100.0 70 62.0 38.0 100.0 90 67.8 32.2 100.0 160 Other 60.1 39.9 100.0 174 61.3 38.7 100.0 86 60.5 39.5 100.0 260 North America * * 100.0 13 * * 100.0 15 (57.7) (42.3) 100.0 28 Romania (74.7) (25.3) 100.0 33 (65.0) (35.0) 100.0 27 70.3 29.7 100.0 60 Turkey 58.9 41.1 100.0 85 * * 100.0 8 59.9 40.1 100.0 92 Israel * * 100.0 23 * * 100.0 12 (35.4) (64.6) 100.0 35 Other * * 100.0 20 * * 100.0 23 (70.4) (29.6) 100.0 44 Don’t know/missing * * 100.0 13 * * 100.0 13 (56.5) (43.5) 100.0 27 Total 50.3 49.7 100.0 1,200 57.6 42.4 100.0 1,314 54.1 45.9 100.0 2,514 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. FSU = Former Soviet Union 15.7 CHILDREN OF EMIGRANTS Children who do not live with their natural parents are more likely to be disadvantaged compared with those who do (UNICEF, 2004). Table 15.7 shows that almost half of households having a former member who now lives abroad are caring for at least one child left behind (44 percent), with households in rural areas more likely than those in urban areas to care for these children (47 and 40 percent, respectively). Households in Chisinau are the least likely to leave children behind (34 percent) (data not shown). Table 15.8 shows that 42 percent of emigrants left children behind, whether these children live in households interviewed or elsewhere in Moldova. Thirty-seven percent of emigrants from urban areas and 45 percent from rural areas left at least one child behind. Among the emigrants who left children behind, about 4 in 10 left behind two or more children. Table 15.7 Characteristics of households caring for the children of emigrants Percent distribution of households with children of emigrants, by number of children and wealth quintile, according to residence, Moldova 2005 Residence Households caring for emigrants' children Urban Rural Total Households with: 0 children 60.5 53.4 56.1 1 child 25.3 27.7 26.8 2 children 11.7 15.0 13.7 3+ children 2.5 3.9 3.4 Total 100.0 100.0 100.0 Wealth quintile Lowest 1.0 20.5 13.0 Second 4.1 31.7 21.2 Middle 14.4 30.6 24.4 Fourth 38.3 16.0 24.5 Highest 42.2 1.2 16.9 Total 100.0 100.0 100.0 Number of households 715 1,158 1,874 Emigration | 227 Table 15.8 Children of emigrants left behind Percent distribution of emigrants by number of children left behind, according to residence, Moldova 2005 Residence Emigrant children left behind Urban Rural Total No children 62.7 55.1 58.0 At least one child 37.3 44.9 42.1 1 child 23.8 25.5 24.9 2 children 11.3 15.7 14.0 3+ children 2.2 3.7 3.2 Total 100.0 100.0 100.0 Number 946 1,569 2,514 Figure 15.5 shows the distribution of emigrants’ children left behind by current age. About one- fifth of children are under 5 years (17 percent in urban areas and 20 percent in rural areas), and one- quarter or more are age 15 and above (31 percent in urban areas and 25 percent in rural areas). Below age 9, there are proportionally more children in rural households that were left behind than children in urban households; this trend is reversed for children age 10 and above. Overall, the median age of children left behind is age 11 years (data not shown). Figure 15.5 Current Age of Emigrants’ Children 17 21 31 31 20 25 30 25 0-04 5-9 10-14 15+ 0 5 10 15 20 25 30 35 Urban Rural MDHS 2005 Age group Percent 0-4 References | 229 REFERENCES Analytical and Information Center, Ministry of Health [Uzbekistan], State Department of Statistics [Uzbekistan], and ORC Macro. 2004. Uzbekistan Health Examination Survey 2002. Calverton, Maryland, USA. Bacalu, E. 2004. Supporting children from disintegrated families through the Service of Child Rights Protection. Paper presented at the national conference, Psychological Development of the Children in Disintegrated Families in the Republic of Moldova, September 30, 2004. Chisinau, Moldova. Brozek, J. and B. Schurch. 1984. Malnutrition and behavior: Critical assessment of key issues. Nestle Foundation Publication Series Vol. 4. Lausanne, Switzerland: Nestle Foundation. CBS AXA. 2004. Moldova Remittances Study. International Organization for Migration (IOM), International Monetary Fund (IMF), and European Commission Food Security Program. Chisinau, Moldova. Centers for Disease Control and Prevention (CDC). 1998. Recommendations to prevent and control iron deficiency in the United States. Morbidity and Mortality Weekly Report 47 (RR-3): 1-29. Centers for Disease Control and Prevention (CDC) and ORC Macro. 2003 (2005 revision). Reproductive, maternal and child health in Eastern Europe and Eurasia: A comparative report. Atlanta, Georgia, USA: CDC and ORC Macro. Center for Reproductive Rights. 2000. East Central Europe abortion laws and policies in brief. August 2000, Item: F032. http://www.crlp.org/pub_fac_ceeaborlaws.html. Cohen R.J., K.H. Brown, J. Canahuait, L.L. Rivera, and K.G. Dewey. 1994. Effect of age of introduction of complementary foods on infant breast milk intake, total energy intake, and growth: A randomized intervention study in Honduras. Lancet 334(8918): 288-293. Colin, Newell. 1988. Methods and models in demography. New York, USA: The Guilford Press. Costachi, J. 2003. Preventing victimization in Moldova. Center for Prevention of Trafficking in Women, Chisinau. Vol. 8, Number 2, June 2003. Electronic Journal of the U.S. Department of State. http://usinfo.state.gov/journals/itgic/0603/ijge/gj07.htm. Cuc, Milan, E. Lunback, and E. Ruggiero. 2005. Migration and remittances in Moldova. Washington DC, USA: International Monetary Fund. Crudu, V., Gh. ğîmbalari, V. Burinschi, O. Goliscev, G. Blagodetelev, and S. Ghinda. 2003. Clinical and epidemiological consequences of multi-resistant tuberculosis. Materials of the 5th Congress of hygienists, epidemiologists and microbiologists in the Republic of Moldova, Vol. 2B. De Colombani, P., N. Banatvala, R. Zaleskis, and D. Maher. 2003. European framework to decrease the burden of TB/HIV. EUR/03/5037600. Copenhagen, Denmark: World Health Organization (WHO) Regional Office for Europe. References | 230 DeMaeyer E. et al. 1989. Preventing and controlling iron deficiency anemia through primary care: A guide for health administrators and programme managers. Geneva, Switzerland: World Health Organization. Department of Statistics and Sociology [Moldova]. 2000. Situatia copiilor in Moldova. Chisinau, Moldova. Dubrovschi, A. 2004. Psychosocial development of the children in disintegrated families in Republic of Moldova: Official view. Presentation at the national conference, Psychological Development of the Children in Disintegrated Families in the Republic of Moldova, September 30, 2004. Chisinau, Moldova. EuroHIV. 2005. HIV/AIDS surveillance in Europe. End-year report 2004. Saint-Maurice: Institut de veille sanitaire, 2005. No. 71. European Centre for the Epidemiological Monitoring of AIDS. WHO and UNAIDS Collaborating Centre on AIDS. http://www.eurohiv.org/reports/report71/pdf/reporteurohiv71.pdf. Ghencea, B., and I. Gudumac. 2004. Labor migration and remittances in the Republic of Moldova. Sponsored by AMM and Moldova-Soros Foundation, March 14, 2004. Gonta, V. 2004. Psychological aspects of self-belief and personality of teenagers educated in temporarily disintegrated families. Presentation at the national conference, Psychological Development of the Children in Disintegrated Families in the Republic of Moldova, September 30, 2004. Chisinau, Moldova. Government of Moldova (GOM) and UNDP. 2004. Millennium development goals: Targets and indicators for the Republic of Moldova. http://www.un.md/mdg/mdg_in_moldova/2003_MDG_targets_and_indicators_draft_january_2004.doc. Government of Moldova (GOM). 2005. First national report on millennium development goals in the Republic of Moldova. Chisinau, Moldova. Gribincea, M. 1995. Basarabia in primii ani de ocupatie sovietica, 1944-1950. Cluj, Romania. Gwatkin, D.R., S. Rutstein, K. Johnson, R.P. Pande, and A. Wagstaff. 2000. Socio-economic differences in health, nutrition and poverty. HNP/Poverty Thematic Group of the World Bank. Washington D.C.: The World Bank. Hamers, F., and A.M. Downs. 2003. HIV in Central and Eastern Europe. Lancet 361(9362): 1035-1044. Heise L., M. Ellsberg, and M. Gottemoeller. 1998. Ending violence among women. Population Reports, Series L, No. 11. Baltimore, Maryland, USA: Population Information Program, Johns Hopkins University School of Public Health. Heise, L., J. Pitanguy, and A. Germain. 1994. Violence against women: The hidden health burden. Washington DC, USA: The World Bank. Hinde, A. 1998. Demographic methods. New York, USA: Oxford University Press Inc. Huffman, S.L., and C. Combest. 1990. Role of breast feeding in the prevention and treatment of diarrhea. Journal of Diarrhoeal Disease Research 8(3): 68-81. International Monetary Fund (IMF). 2005a. Republic of Moldova: 2004 Article IV Consultation—Staff Report Public Information Notice on the Executive Board Discussion; and Statement by the Executive Director for the Republic of Moldova. IMF Country Report No. 05/48. http://www.imf.org. References | 231 International Monetary Fund (IMF). 2005b. Republic of Moldova: Selected issues. IMF Country Report No. 05/54. http://www.imf.org. International Nutritional Anemia Consultative Group (INACG). 1989. Iron deficiency in women. INACG. Geneva, Switzerland: World Health Organization. Jandl, M. 2003. Moldova seeks stability amid mass emigration. Dec. 2003. Published on-line in the Migration Information Source, Migration Policy Institute: Washington, DC. http://www.migrationinformation.org. Jejeebhoy, S.J. 1998. Associations between wife-beating and fetal and infant death: Impressions from a survey in rural India. Studies in Family Planning 29(3): 300-308. Korobkov, A., and L. Palei. 2005. The socio-economic impact of migrant remittances in the CIS. In International migration trends. Scientific Series: International Migration of Population: Russia and the Contemporary World. Paper submitted to Session 143 of the XXV IUSSP Population Conference, Tours, France, 18-23 July 2005. Moscow State University, Department of Population. Vol.15 pp: 130-147. Moscow, Russia: MAX Press. Kelly, J.A., Y.A. Amirkhanian. 2003. The newest epidemic: A Review of HIV/AIDS in Central and Eastern Europe. International Journal of STD and AIDS 14(6): 361-371. Laczko, F. 2002. Data insight. Human trafficking: The need for better data. International Organization for Migration. November 2002. Published on-line in the Migration Information Source, Migration Policy Institute: Washington DC. http://www.migrationinformation.org. Lozoff et al. 1991. Long-term development outcome of infants with iron-deficiency. New England Journal of Medicine 325(10): 687-694. Moldova State Department of Statistics and UNDP. 2005. Women and men in the Republic of Moldova. Statistical collection. Chisinau, Moldova: Editura Statistica. http://www.statistica.md/publications/131/en/Femei_barbati_RM_md_en.pdf. Ministry of Economics and Commerce [Moldova]. 2005. Report on povery and its impact on policy, 2004 [Raport privind saracia si impactul politicilor, 2004]. Chisinau, Moldova. National Institutes of Health (NIH). 2006. Dietary supplement fact sheet: Iron. Washington, D.C., USA: Office of Dietary Supplements. NIG Clinical Center. National Institutes of Health. http://dietary-supplements.info.nih.gov/factsheets/iron.asp (April 2006). National Scientific and Applied Center for Preventive Medicine (NSACPM) [Centrul NaĠional Stiintifico- Practic de Medicina Preventiva (CNSPMP)] [Moldova]. 2004-2006. Starea sanitaro-igienica si epidemiologica in Republica Moldova conform rapoartelor statistice a organelor si institutiilor SSES, 2003, 2004, 2005, Chisinau, Moldova. National Statistical Service (NSS), Ministry of Health (MOH) [Armenia], and ORC Macro. 2006. Armenia Demographic and Health Survey 2005: Preliminary report. Calverton, Maryland, USA: ORC Macro. Notzo, F.C., Y.M. Komarov, A.V. Korotkova, S.P. Ermanov, A.I. Savinykh, E. Sharapova, D.I. Zelinskaya, T.L. Armstrong, and M. Kiely. 1999. Maternal and child health statistics: Russian Federation and United States, Selected years, 1985-1995. Vital Health Statistics 5(10):1-4. References | 232 ORC Macro. 2005. MEASURE DHS STAT compiler. http://www.measuredhs.com. September 12, 2005. Pelletier, D.L., E.A. Frongillo, Jr., and J.-P. Habicht. 1993. Epidemiologic evidence for a potentiating effect of malnutrition on child mortality. American Journal of Public Health 83(8): 1130-1133. Population Reference Bureau (PRB). 2005. World Population Data Sheet. http://www.prb.org/pdf05/05WorldDataSheet_Eng.pdf. Rutstein, S. 1999. Wealth versus expenditure: Comparison between the DHS wealth index and household expenditures in four departments of Guatemala. Calverton, Maryland, USA: ORC Macro. Rutstein, S.O., and G. Rojas. 2003. Guide to DHS statistics. Calverton, Maryland, USA: ORC Macro. Rutstein, S.O., K. Johnson, and D. Gwatkin. 2000. Poverty, health inequality, and its health and demographic effects. Paper presented at the 2000 Annual Meeting of the Population Association of America, Los Angeles, California, USA. Salaru, V. 2004. Children with parents, children with no parents. Presentation at the national conference, Psychological Development of the Children in Disintegrated Families in the Republic of Moldova, September 30, 2004. Chisinau, Moldova. Scientific and Practical Center for Public Health and Health Management (SPCPHHM) [Centrul Stiintifico-Practic de Sanatate Publica si Management Sanitar (CSPSPMS)] [Moldova]. 2005. Sanatatea publica in Moldova, 2005. Chisinau, Moldova. Scrimshaw, N.S. 1984. Functional consequences of iron deficiency in human populations. Journal of Nutritional Science and Vitaminology 30(1): 47-63. Serbanescu, F., L. Morris, M. Stratila, and O. Bivol. 1998. Moldova Reproductive Health Survey 1997. Atlanta, Georgia, USA: Ministry of Health [Moldova], Centers for Disease Control and Prevention, and United Nations Population Fund. Shelton, J.D., D.T. Halperin, N. Ninand, M. Potts, H.D. Gayle, and K.K. Holmes. 2004. Partner reduction is crucial for balanced “ABC” approach to HIV prevention. British Medical Journal 324: 891-893. Stratulat, P., V. Baltag, A. Cureanu. and T. Caraush. 2005. Assessment of maternity practice in the Republic of Moldova. Entre Nous No. 60-2005. Copenhagen, Denmark: WHO Regional Office for Europe and UNFPA. http://www.euro.who.int/document/ENS/EN60.pdf. Strauss, M.A. 1990. Measuring intrafamily conflict and violence: The conflict tactics (CT) scales. In Physical violence in American families: Risk factors and adaptations to violence in 8,145 families, ed. M.A. Strauss and R.J. Gelles, 39-47. New Brunswick, New Jersey, USA: Transaction Publishers. Sullivan, J.M., S.O. Rutstein, and G.T. Bicego. 1994. Infant and child mortality. DHS Comparative Studies No. 15. Calverton, Maryland, USA: Macro International Inc. Taran, A.M., et al. 1993. Golod v Moldove, 1946-1947: Sbornik documentov. ùtiinĠa, Chisinau, Moldova. UNAIDS. 2004. Report on the global AIDS epidemic. Geneva, Switzerland: UNAIDS. UNAIDS. 2005. Uniting the world against AIDS. http://www.unaids.org/en/Regions_Countries/default.asp. References | 233 UNAIDS/WHO. 2005. AIDS epidemic update: December 2005, Eastern Europe and Central Asia. Geneva, Switzerland: UNAIDS/WHO. http://www.unaids.org/epi/2005/doc/EPIupdate2005_pdf_en/Epi05_07_en.pdf. UNICEF. 1990. Strategy for improved nutrition of children and women in developing countries. New York, New York, USA: UNICEF. UNICEF. 2005. HIV/SIDA, situatia epidemiologica in Republica Moldova. Presentation by Silviu Domente to MDHS iterviewers during the main training program, 8 April 2005. Chisinau, Moldova: UNICEF. UNICEF and Government of Moldova (GOM). 2000. Multiple Indicator Cluster Survey (MICS). Chisinau, Moldova: UNICEF. UNICEF and Ministry of Health (MOH) [Moldova]. 2002. Starea de nutritie in Republica Moldova: Analiza situatiei si strategiile de interventie, Raport 1996-2000. Stiinta, Chisinau, Moldova: UNICEF. UNIFEM. 2005. Prevenirea violenĠei domestice. Presentation by Valentina Bodrug-Lungu to MDHS interviewers during the main training program, 8 April 2005. Chisinau, Moldova. United Nations. 1973. The determinants and consequences of population trends. Vol. 1. New York, New York, USA: United Nations. United Nations Development Programme (UNDP), Republic of Moldova. 2003. Millennium goals: Desk study. Chisinau, Moldova: UNDP. United Nations Development Programme (UNDP). 2006. Human development report 2005. http://hdr.undp.org/reports/global/2005. United Nations General Assembly. 1991. Advancement of women: Convention on the elimination of all forms of discrimination against women, Report of the Secretary-General. New York, New York, USA: United Nations. United Nations Population Fund (UNFPA). 2003. Millennium development goals. Comparative Analysis in the Republic of Moldova. Chisinau, Moldova: UNFPA. United Nations Population Fund (UNFPA). 2006. Country in focus: Moldova. UNFPA Assistance Highlight. http://www.unfpa.org/countryfocus/moldova/countryassistance.htm. U.S. Census Bureau, International Program Center. 2002. HIV/AIDS Surveillance Data Base. June 2002 Release. Washington, D.C., USA. U.S. Census Bureau. 2005. International Data Base. http://www.census.gov/ipc/www/ (April 26, 2005). United States Library of Congress. 1995. Country studies: CIA World Factbook. http://countrystudies.us/moldova/16.htm (June 1995). References | 234 Ursu-Moraru, N. 2006. Economic aspects of tobacco control in the Republic of Moldova. Presentation of results of a study carried out for the regional project, Development of capacities in the sphere of public health for augmentation of tobacco control in South-Eastern Europe. National Meeting for the WHO Framework Convention for Tobacco Control, January 30, 2006. Chisinau, Moldova. Westoff, C.F. 2005. Recent trends in abortion and contraception in 12 countries. DHS Analytical Studies No. 8. Calverton, Maryland, USA: ORC Macro. World Bank. 2005. Moldova: Oportunitati pentru o crestere economica accelerata. Memorandum economic de tara pentru Republica Moldova. September 9, 2005. Poverty Reduction and Economic Management Division, European Region and Central Asia, Report no. 32876-MD. World Health Organization (WHO). 1992. International statistical classification of diseases and related health problems, 10th Revision (ICD-1), Vol. 1 (definition 3.1). Geneva, Switzerland: WHO. World Health Organization (WHO). 1993. International statistical classification of diseases and related health problems, tenth revision. Geneva, Switzerland: WHO. World Health Organization (WHO). 1995. World Health Organization Expert Committee. Physical status: The use and interpretation of anthropometry. WHO Technical Report Series No. 854. Geneva, Switzerland: WHO. World Health Organization (WHO). 1998. Tuberculosis fact sheet No. 104. World Health Organization Press Office. Geneva, Switzerland: WHO. World Health Organization (WHO). 2001. Alcohol in the European region – consumption, harm and policies. Copenhagen, Denmark: WHO Regional Office for Europe. World Health Organization (WHO). 2002a. Core information for the development of immunization policy, 2002 update. Department of Vaccines and Biologicals, Geneva, Switzerland: WHO. 129-131. World Health Organization (WHO). 2002b. DOTS expansion plan to stop TB in the WHO European region 2002–2006. Copenhagen, Denmark: WHO Regional Office for Europe. World Health Organization (WHO). 2003. Vitamin A supplementation. Vaccines and other Biologicals Department of the Health Technology and Pharmaceuticals cluster. Geneva, Switzerland: WHO. http://www.who.int/vaccines/en/vitamina.shtml#strategies (May 2003). World Health Organization (WHO) 2005. World health statistics 2005. http://www.who.int/healthinfo/statistics/mortality_en.pdf. World Health Organization (WHO). 2006. European health for all database (HFA-DB). Copenhagen, Denmark: WHO Regional Office for Europe. http://data.euro.who.int/hfadb/ (January 2006). Zimmerman, C. 1994. Plates in a basket will rattle: Domestic violence in Cambodia. Phnom Penh, Cambodia: The Asia Foundation, USAID. Appendix A | 235 SAMPLE DESIGN Appendix A A.1 INTRODUCTION The 2005 Moldova Demographic and Health Survey (2005 MDHS) is based on a representative probability sample of women age 15-49 and men age 15-59. Transnistria, the semiautonomous region in the eastern part of the country accounting for approximately 15 percent of Moldova’s population, is not included in the sample. In this appendix, therefore, the national sample area is referred to as Moldova (West). In every selected household, all women were eligible for interview. In one out of three selected households, all men were eligible for interview. The sample was designed to provide estimates with an acceptable level of precision for popula- tion, health and nutrition indicators such as fertility, contraceptive prevalence, selected maternal and child indicators including anthropometric measures and anemia prevalence, and mortality rates for children un- der five. The major sample domains for which these estimates are computed are: • Moldova (West) at a national level; • Total urban areas and total rural areas of Moldova (West); and • Subregions of Moldova (West), including North, Center, South regions and Chisinau. A.2 SAMPLE FRAME Administratively, Moldova (West) is divided into three major geographical regions including North, Center, South regions and Chisinau municipality. For the purposes of conducting the 2004 Popu- lation and Housing Census, each geographical region was further subdivided into administrative areas called census sectors (CS). Each CS is classified as urban or rural. The population size of each CS, made available from the 2004 census, coupled with detailed cartographic information for each CS, comprise the master sample frame for the 2005 MDHS survey. A.3 CHARACTERISTICS OF THE SAMPLE The primary sampling unit (PSU), referred to as a “cluster” in the 2005 MDHS, is defined based on the list of CSs as demarcated in the 2004 census. The CS was a unit originally constructed to ensure a convenient census workload, and it also serves as a practical primary sampling unit for the 2005 MDHS. The 2005 MDHS utilized a two-stage sample design. The primary sampling stage involved se- lecting a sample of 400 clusters from an updated master sampling frame from the 2004 census. The pre- classified urban and rural CSs were used to define the explicit strata for the purpose of cluster selection i.e., for Moldova (West) as a whole, a specified number of urban and rural CSs was selected independ- ently. The second stage of sampling involved the systematic selection of households from an updated list- ing of all households in each of the selected clusters. A sample take of 30 households in each cluster was selected prior to data collection. 236 | Appendix A A.4 SAMPLE ALLOCATION AND SAMPLE SIZE The target household sample size needed for the 2005 MDHS survey was estimated to be 12,000 selected households in the whole of Moldova (West). This number of households was expected to yield an adequate number of women of eligible age (approximately 8,100) to compute survey indicators, and an adequate number of children under five years (approximately 1,800) whose information would be col- lected from the women (or, in some cases, the child’s caretaker). The estimated sample sizes are based on the levels of response resulting from the 2000 Moldova MICS, where both urban and rural households provided, on average, 0.7 women of eligible age (Table A.1). The average number of children under age five was approximately 0.1-0.2 per household. Table A.1 Number of selected households and completed women and children interviews, by residence 2000 MICS Survey Completed Domain Estimated total house- holds Distribution of house- holds Selected number of households Sample household distribution Eligible women Women per selected household Eligible children Urban Moldova (West) 57,1660 0.40 3,744 0.40 2,586 0.69 449 Rural Moldova (West) 86,0775 0.60 5,509 0.60 3,787 0.69 974 Total 1,432,435 9,253 6,373 1,423 Table A.2 uses information in Table A.1 to calculate the expected number of completed women interviews, and the number of children under five, under proportional and non-proportional distributions for the 2005 MDHS. Under a proportional distribution the urban area is 40 percent, while under the non- proportional allocation the sample in the urban area is 45 percent. The latter ultimately permits a better urban analysis. Table A.2 Proportional and non-proportional sample allocation Proportional and Square Root Sample Allocation, 2005 MDHS Completed Domain Proportional allocation Square root of total households Distribution square root of house- holds Square root allocation Adjusted sample Expected women Expected children Urban Moldova (West) 4,789 756.1 0.45 5,388 5,400 3,730 648 Rural Moldova (West) 7,211 927.8 0.55 6,612 6,600 4,537 1,167 Total 12,000 1,683.9 12,000 12,000 8,267 1,814 The final recommended sample is one adjusted to collect information on an approximately equal number of children in each domain (Table A.3). A total of 400 clusters in Moldova (West) were selected from the sampling frame, including 233 urban and 167 rural clusters selected using systematic sampling with probabilities proportional to their size. Table A.3 shows the final distribution of selected households for the 2005 MDHS. Appendix A | 237 Table A.3 Final recommended sample size Domain Expected completed children Household sample selection Expected completed women Number of clusters to select Urban Moldova (West) 839 7,000 4,835 233 Rural Moldova (West) 884 5,000 3,437 167 Total 1,723 12,000 8,272 400 Table A.4 Sample implementation: women 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 region, Moldova 2005 Residence Region Result Urban Rural North Center South Chisinau Total Selected households Completed (C) 87.7 95.4 92.5 94.7 95.0 83.9 90.9 Household present but no compe- tent respondent at home (HP) 4.0 1.0 1.4 1.1 1.5 6.1 2.8 Postponed (P) 0.1 0.1 0.1 0.0 0.0 0.2 0.1 Refused (R) 2.5 0.3 0.5 0.6 0.5 4.0 1.6 Dwelling not found (DNF) 0.1 0.0 0.1 0.1 0.0 0.2 0.1 Household absent (HA) 3.0 1.4 2.9 2.2 1.0 2.9 2.4 Dwelling vacant/address not a dwelling (DV) 2.5 1.6 2.6 1.2 1.8 2.6 2.1 Dwelling destroyed (DD) 0.1 0.1 0.0 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of sampled households 7,104 5,102 3,576 2,786 2,201 3,643 12,206 Household response rate (HRR)1 92.8 98.5 97.9 98.1 97.8 88.8 95.2 Eligible women Completed (EWC) 93.5 97.4 97.7 97.1 97.1 89.8 95.1 Not at home (EWNH) 3.9 1.6 1.1 1.6 1.7 6.5 3.0 Postponed (EWP) 0.0 0.0 0.0 0.0 0.1 0.1 0.0 Refused (EWR) 1.9 0.2 0.6 0.5 0.4 2.9 1.2 Partly completed (EWPC) 0.2 0.1 0.0 0.1 0.1 0.4 0.2 Incapacitated (EWI) 0.4 0.7 0.5 0.6 0.5 0.4 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 4,602 3,224 2,113 1,858 1,486 2,369 7,826 Eligible women response rate (EWRR)2 93.5 97.4 97.7 97.1 97.1 89.8 95.1 Overall response rate (ORR) 3 86.8 95.9 95.7 95.3 95.0 79.7 90.5 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: 100 * C _______________________________ C + HP + P + R + DNF 2 Using the number of eligible women falling into specific response categories, the eligible woman response rate (EWRR) is calculated as: 100 * EWC ________________________________________________ EWC + EWNH + EWP + EWR + EWPC + EWI + EWO 3 The overall response rate (ORR) is calculated as: ORR = HRR * EWRR/100 238 | Appendix A Table A.5 Sample implementation: men Percent distribution of households and eligible men by results of the household and individual interviews, and household, eligible men and overall response rates, according to urban-rural residence and region, Moldova 2005 Residence Region Result Urban Rural North Center South Chisinau Total Selected households Completed (C) 87.2 95.2 92.6 94.3 95.5 82.7 90.6 Household present but no compe- tent respondent at home (HP) 3.8 1.2 1.2 1.2 1.6 6.2 2.8 Postponed (P) 0.1 0.1 0.2 0.0 0.0 0.1 0.1 Refused (R) 2.8 0.5 0.5 0.9 0.5 4.8 1.9 Dwelling not found (DNF) 0.2 0.0 0.0 0.2 0.0 0.2 0.1 Household absent (HA) 3.3 1.4 3.0 2.3 1.0 3.0 2.5 Dwelling vacant/address not a dwelling (DV) 2.5 1.6 2.5 1.2 1.4 2.8 2.1 Dwelling destroy (DD) 0.1 0.0 0.0 0.0 0.0 0.2 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of sampled households 2,365 1,696 1,190 931 730 1,210 4,061 Household response rate (HRR)1 92.6 98.1 98.0 97.7 97.8 88.0 94.9 Eligible men Completed (EMC) 83.5 91.0 90.0 90.2 89.8 78.2 86.6 Not at home (EMNH) 9.8 5.8 5.1 5.4 7.1 13.8 8.1 Postponed (EMP) 0.0 0.1 0.1 0.0 0.0 0.0 0.0 Refused (EMR) 4.8 1.3 2.6 2.6 1.2 6.2 3.3 Partly completed (EMPC) 1.0 0.0 0.6 0.4 0.0 1.1 0.6 Incapacitated (EMI) 0.9 1.9 1.5 1.4 1.9 0.7 1.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 1,698 1,199 778 702 577 840 2,897 Eligible men response rate (EMRR)2 83.5 91.0 90.0 90.2 89.8 78.2 86.6 Overall response rate (ORR)3 77.3 89.3 88.2 88.1 87.8 68.8 82.2 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: 100 * C _______________________________ C + HP + P + R + DNF 2 Using the number of eligible women falling into specific response categories, the eligible woman response rate (EWRR) is calculated as: 100 * EMC ________________________________________________ EMC + EMNH + EMP + EMR + EMPC + EMI + EMO 3 The overall response rate (ORR) is calculated as: ORR = HRR * EMRR/100 Appendix B | 239 ESTIMATES OF 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 col- lection and data processing, such as failure to locate and interview the correct household, misunderstand- ing 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 MDHS to minimize this type of error, non- sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents se- lected in the MDHS 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 calcu- late 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 MDHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex for- mulae. The computer software used to calculate sampling errors for the MDHS is the ISSA Sampling Er- ror Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jacknife 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: ¦ ¦ = =− » » ¼ º « « ¬ ª ¸¸¹ · ¨¨© § − − == H h h h m i hi h h m z z m m x frvarrSE h 1 2 1 2 1 2 2 1)()( in which hihihi rxyz −= , and hhh rxyz −= where h represents the stratum which varies from 1 to H, mh is the total number of enumeration areas selected in the hth stratum, 240 | Appendix B yhi is the sum of the values of variable y in EA i in the hth stratum, xhi is the sum of the number of cases in EA i in the hth stratum, and f is the overall sampling fraction, which is so small that it is ignored. The Jacknife 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 rep- lications are thus created. In the MDHS, there were 400 non-empty clusters (PSUs). Hence, 400 replica- tions were created. The variance of a rate r is calculated as follows: SE r var r k k r r i k i 2 1 21 1 ( ) ( ) ( ) ( )= = − − = ¦ in which )()1( ii rkkrr −−= where r is the estimate computed from the full sample of 400 clusters, r(i) is the estimate computed from the reduced sample of 399 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 in- crease in the sampling error due to the use of a more complex and less statistically efficient design. IS- SAS also computes the relative error and confidence limits for the estimates. Sampling errors for the MDHS 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 urban and rural areas, for the three regions (North, Center, and South) and for Chisanau. 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.7 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 considering sim- ple 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, ex- cept for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of subpopulations. 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 1.1 percent, 1.5 percent, and 1.5 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 .678 and its standard error is 0.007. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e. .678±2(0.007). 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 .663 and .692. Appendix B | 241 Table B.1 List of selected variables for sampling errors, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Variable Estimate Base population –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence Proportion All women Literate Proportion All women No education Proportion All women Secondary education or higher Proportion All women Net attendance ratio for primary school Ratio Children with primary school Never married Proportion All women Currently married/in union Proportion All women Married before age 20 Proportion All women Currently pregnant Proportion All women Children ever born Mean All women Abortions, women age 40-49 Mean All women 40-49 Induced abortions (%) Proportion All women Children surviving Proportion All women Children ever born to women age 40-49 Proportion All women 40-49 Knows any contraceptive method Proportion Currently married women Ever using contraceptive method Proportion Currently married women Currently using any contraceptive method Proportion Currently married women Currently using a modern method Proportion Currently married women Currently using pill Proportion Currently married women Currently using IUD 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 Obtained method from public sector source Proportion Currently users Want no more children Proportion Currently married women Want to delay birth at least 2 years Proportion Currently married women Mothers received tetanus injection for last birth Proportion Last birth in 5 years Mothers received medical assistance at delivery Proportion Births in 5 years Had diarrhoea in two weeks before survey Proportion Births in 5 years Vaccination card seen Proportion Children 15-26 Received BCG Proportion Children 15-26 Received DPT (3 doses) Proportion Children 15-26 Received polio (3 doses) Proportion Children 15-26 Received measles Proportion Children 15-26 Fully immunized Proportion Children 15-26 Height-for-age (below -2SD) Proportion Children 0-59 months measured Weight-for-height (below -2SD) Proportion Children 0-59 months measured Weight-for-age (below -2SD) Proportion Children 0-59 months measured BMI <18.5 Proportion All women Has heard of HIV/AIDS Proportion All women Knows about condoms Proportion All women Knows about limiting partners Proportion All women Any anemia (children) Proportion All children under five Any anemia (women) Proportion All women Total abortion rate Rate All currently married last 3 years Total fertility rate (last 3 years) Rate All births last 3 years Neonatal mortality Rate All children in last 5(10) years Postneonatal mortality Rate All children in last 5(10) years Infant mortality Rate All children in last 5(10) years Child mortality Proportion All children in last 5(10) years Under 5 mortality Proportion All children in last 5(10) years –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence Proportion All men Literate Proportion All men No education Proportion All men Secondary education or higher Proportion All men Never married Proportion All men Currently married/in union Proportion All men Married before age 20 Proportion All men Want no more children Proportion Currently married men Want to delay birth at least 2 years Proportion Currently married men Has heard of HIV/AIDS Proportion All men Knows about condoms Proportion All men Knows about limiting partners Proportion All men –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Five years for national sample and 10 years for regional sample 2 Maternal mortality ratio is reported only for national sample 242 | Appendix B Table B.2 Sampling errors for National sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.429 0.008 7440 7440 1.348 0.018 0.414 0.445 Literate 0.997 0.001 7440 7440 1.147 0.001 0.996 0.999 No education 0.002 0.001 7440 7440 1.260 0.308 0.001 0.004 Secondary education or higher 0.993 0.002 7440 7440 1.598 0.002 0.990 0.996 Net attendance ratio for primary school 0.782 0.010 2066 2110 1.084 0.013 0.762 0.801 Never married 0.250 0.006 7440 7440 1.101 0.022 0.239 0.261 Currently married/in union 0.664 0.006 7440 7440 1.104 0.009 0.651 0.676 Married before age 20 0.428 0.008 6037 6023 1.189 0.018 0.413 0.443 Currently pregnant 0.024 0.002 7440 7440 1.134 0.084 0.020 0.028 Children ever born 1.380 0.016 7440 7440 1.040 0.011 1.349 1.412 Abortions, women age 40-49 1.486 0.053 2151 2156 1.373 0.035 1.381 1.591 Induced abortions (%) 0.342 0.013 1839 1845 1.122 0.038 0.316 0.368 Children surviving 1.326 0.015 7440 7440 1.037 0.011 1.296 1.355 Children ever born to women age 40-49 2.348 0.032 2151 2156 1.252 0.014 2.284 2.412 Knows any contraceptive method 0.995 0.001 4892 4937 1.079 0.001 0.993 0.997 Ever using contraceptive method 0.911 0.005 4892 4937 1.204 0.005 0.902 0.921 Currently using any contraceptive method 0.678 0.007 4892 4937 1.102 0.011 0.663 0.692 Currently using a modern method 0.438 0.008 4892 4937 1.094 0.018 0.423 0.454 Currently using pill 0.036 0.003 4892 4937 1.112 0.082 0.030 0.042 Currently using IUD 0.252 0.007 4892 4937 1.094 0.027 0.239 0.266 Currently using condom 0.074 0.004 4892 4937 1.159 0.059 0.065 0.082 Currently using female sterilization 0.047 0.003 4892 4937 1.060 0.069 0.040 0.053 Currently using periodic abstinence 0.035 0.003 4892 4937 1.015 0.077 0.029 0.040 Obtained method from public sector source 0.686 0.010 2431 2377 1.108 0.015 0.665 0.707 Want no more children 0.641 0.008 4892 4937 1.144 0.012 0.626 0.657 Want to delay birth at least 2 years 0.136 0.005 4892 4937 1.049 0.038 0.126 0.146 Mothers received tetanus injection for last birth 0.900 0.011 1369 1387 1.340 0.012 0.878 0.921 Mothers received medical assistance at delivery 0.995 0.002 1552 1591 0.989 0.002 0.992 0.999 Had diarrhoea in two weeks before survey 0.074 0.006 1533 1571 0.918 0.083 0.062 0.087 Vaccination card seen 0.897 0.019 321 329 1.110 0.021 0.859 0.934 Received BCG 0.997 0.003 321 329 0.925 0.003 0.992 1.003 Received DPT (3 doses) 0.935 0.014 321 329 1.003 0.015 0.908 0.962 Received polio (3 doses) 0.948 0.013 321 329 1.030 0.013 0.923 0.973 Received measles 0.906 0.019 321 329 1.181 0.021 0.867 0.944 Fully immunized 0.853 0.021 321 329 1.098 0.025 0.811 0.896 Height-for-age (below -2SD) 0.084 0.008 1456 1498 1.054 0.094 0.068 0.099 Weight-for-height (below -2SD) 0.039 0.006 1456 1498 1.230 0.158 0.026 0.051 Weight-for-age (below -2SD) 0.043 0.005 1456 1498 0.900 0.110 0.033 0.052 BMI <18.5 0.059 0.003 7039 7062 1.109 0.053 0.053 0.066 Has heard of HIV/AIDS 0.974 0.002 7440 7440 1.316 0.002 0.969 0.979 Knows about condoms 0.782 0.007 7440 7440 1.422 0.009 0.768 0.796 Knows about limiting partners 0.813 0.006 7440 7440 1.359 0.008 0.801 0.825 Any anemia (children) 0.322 0.015 1315 1364 1.195 0.048 0.291 0.352 Any anemia (women) 0.279 0.007 7099 7138 1.317 0.025 0.265 0.293 Total abortion rate 1.304 0.072 na 23455 1.695 0.055 1.161 1.448 Total fertility rate (last 3 years) 1.687 0.055 na 21045 1.113 0.033 1.576 1.797 Neonatal mortality (last 5 years) 4.603 1.961 1569 1606 1.163 0.426 0.681 8.526 Postneonatal mortality (last 5 years) 8.233 2.354 1569 1606 1.042 0.286 3.525 12.941 Infant mortality (last 5 years) 12.836 3.025 1569 1606 1.081 0.236 6.787 18.885 Child mortality (last 5 years) 0.740 0.462 1570 1607 0.703 0.624 0.184 1.665 Under 5 mortality (last 5 years) 13.567 3.052 1570 1607 1.073 0.225 7.464 19.670 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.420 0.010 2508 2508 0.983 0.023 0.401 0.440 Literate 0.997 0.001 2508 2508 1.148 0.001 0.995 1.000 No education 0.001 0.001 2508 2508 1.082 0.603 0.000 0.003 Secondary education or higher 0.994 0.002 2508 2508 1.266 0.002 0.989 0.998 Never married 0.291 0.010 2508 2508 1.058 0.033 0.272 0.310 Currently married/in union 0.661 0.010 2508 2508 1.058 0.015 0.641 0.681 Married before age 20 0.086 0.006 2097 2097 1.014 0.072 0.073 0.098 Want no more children 0.641 0.013 1644 1657 1.104 0.020 0.615 0.668 Want to delay birth at least 2 years 0.083 0.008 1644 1657 1.132 0.093 0.068 0.099 Has heard of HIV/AIDS 0.968 0.005 2508 2508 1.356 0.005 0.959 0.978 Knows about condoms 0.848 0.010 2508 2508 1.378 0.012 0.828 0.868 Knows about limiting partners 0.869 0.009 2508 2508 1.296 0.010 0.852 0.887 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable Appendix B | 243 Table B.3 Sampling errors for Urban sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 1.000 0.000 4301 3194 na 0.000 1.000 1.000 Literate 0.997 0.001 4301 3194 1.427 0.001 0.994 0.999 No education 0.003 0.001 4301 3194 1.506 0.415 0.001 0.006 Secondary education or higher 0.993 0.003 4301 3194 2.098 0.003 0.987 0.998 Net attendance ratio for primary school 0.788 0.014 979 690 1.061 0.018 0.759 0.816 Never married 0.253 0.007 4301 3194 1.030 0.027 0.240 0.267 Currently married/in union 0.640 0.007 4301 3194 1.016 0.012 0.625 0.655 Married before age 20 0.374 0.009 3552 2647 1.068 0.023 0.356 0.391 Currently pregnant 0.023 0.003 4301 3194 1.143 0.114 0.017 0.028 Children ever born 1.110 0.015 4301 3194 0.945 0.014 1.079 1.141 Abortions, women age 40-49 1.630 0.060 1223 892 1.116 0.037 1.511 1.750 Induced abortions (%) 0.390 0.016 1067 801 1.036 0.041 0.358 0.422 Children surviving 1.073 0.015 4301 3194 0.961 0.014 1.043 1.103 Children ever born to women age 40-49 1.944 0.034 1223 892 1.160 0.017 1.876 2.012 Knows any contraceptive method 0.996 0.001 2751 2045 0.721 0.001 0.994 0.998 Ever using contraceptive method 0.918 0.005 2751 2045 1.023 0.006 0.907 0.929 Currently using any contraceptive method 0.672 0.010 2751 2045 1.142 0.015 0.651 0.692 Currently using a modern method 0.478 0.010 2751 2045 1.066 0.021 0.458 0.499 Currently using pill 0.050 0.005 2751 2045 1.187 0.099 0.040 0.060 Currently using IUD 0.216 0.008 2751 2045 1.059 0.038 0.200 0.233 Currently using condom 0.129 0.008 2751 2045 1.220 0.061 0.113 0.144 Currently using female sterilization 0.046 0.004 2751 2045 1.036 0.090 0.038 0.054 Currently using periodic abstinence 0.049 0.004 2751 2045 0.981 0.082 0.041 0.057 Obtained method from public sector source 0.534 0.014 1512 1130 1.114 0.027 0.506 0.563 Want no more children 0.568 0.009 2751 2045 0.955 0.016 0.550 0.586 Want to delay birth at least 2 years 0.174 0.008 2751 2045 1.082 0.045 0.158 0.190 Mothers received tetanus injection for last birth 0.879 0.012 759 566 1.036 0.014 0.855 0.904 Mothers received medical assistance at delivery 0.996 0.002 824 611 1.030 0.002 0.992 1.001 Had diarrhoea in two weeks before survey 0.116 0.011 815 604 0.932 0.090 0.095 0.137 Vaccination card seen 0.904 0.025 174 128 1.124 0.028 0.854 0.955 Received BCG 1.000 0.000 174 128 na 0.000 1.000 1.000 Received DPT (3 doses) 0.907 0.022 174 128 0.976 0.024 0.863 0.950 Received polio (3 doses) 0.933 0.018 174 128 0.953 0.019 0.897 0.970 Received measles 0.881 0.029 174 128 1.185 0.033 0.823 0.940 Fully immunized 0.797 0.034 174 128 1.101 0.042 0.729 0.865 Height-for-age (below -2SD) 0.067 0.009 711 497 0.986 0.140 0.048 0.086 Weight-for-height (below -2SD) 0.040 0.007 711 497 0.903 0.168 0.027 0.053 Weight-for-age (below -2SD) 0.026 0.006 711 497 0.969 0.222 0.015 0.038 BMI <18.5 0.066 0.004 4024 2980 1.070 0.064 0.057 0.074 Has heard of HIV/AIDS 0.992 0.002 4301 3194 1.120 0.002 0.989 0.995 Knows about condoms 0.849 0.006 4301 3194 1.168 0.008 0.837 0.862 Knows about limiting partners 0.873 0.006 4301 3194 1.191 0.007 0.861 0.885 Any anemia (children) 0.268 0.018 627 432 0.984 0.066 0.232 0.303 Any anemia (women) 0.246 0.008 4014 2962 1.234 0.034 0.229 0.263 Total abortion rate 1.459 0.089 na 10128 1.561 0.061 1.281 1.637 Total fertility rate (last 3 years) 1.504 0.060 na 9132 1.048 0.040 1.385 1.623 Neonatal mortality (last 10 years) 10.646 2.895 1552 1153 1.054 0.272 4.855 16.436 Postneonatal mortality (last 10 years) 6.545 2.043 1552 1153 1.002 0.312 2.458 10.631 Infant mortality (last 10 years) 17.190 3.407 1552 1153 1.006 0.198 10.377 24.004 Child mortality (last 10 years) 3.066 1.335 1555 1155 0.941 0.435 0.397 5.735 Under five years mortality (last 10 years) 20.204 3.631 1555 1155 0.996 0.180 12.942 27.465 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 1.000 0.000 1417 1055 na 0.000 1.000 1.000 Literate 0.999 0.001 1417 1055 0.997 0.001 0.997 1.000 No education 0.001 0.001 1417 1055 0.927 1.002 0.000 0.002 Secondary education or higher 0.997 0.001 1417 1055 0.970 0.001 0.994 1.000 Never married 0.316 0.013 1417 1055 1.029 0.040 0.290 0.341 Currently married/in union 0.634 0.014 1417 1055 1.071 0.022 0.607 0.661 Married before age 20 0.083 0.009 1184 881 1.094 0.105 0.066 0.101 Want no more children 0.569 0.017 900 669 1.029 0.030 0.535 0.603 Want to delay birth at least 2 years 0.100 0.011 900 669 1.059 0.106 0.078 0.121 Has heard of HIV/AIDS 0.985 0.003 1417 1055 0.854 0.003 0.980 0.991 Knows about condoms 0.914 0.008 1417 1055 1.045 0.009 0.899 0.930 Knows about limiting partners 0.915 0.008 1417 1055 1.140 0.009 0.898 0.931 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable 244 | Appendix B Table B.4 Sampling errors for Rural sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.000 0.000 3139 4246 na na 0.000 0.000 Literate 0.997 0.001 3139 4246 0.910 0.001 0.996 0.999 No education 0.002 0.001 3139 4246 1.036 0.455 0.000 0.003 Secondary education or higher 0.994 0.002 3139 4246 1.189 0.002 0.991 0.997 Net attendance ratio for primary school 0.779 0.013 1087 1420 0.999 0.016 0.753 0.805 Never married 0.248 0.008 3139 4246 1.066 0.033 0.232 0.264 Currently married/in union 0.681 0.009 3139 4246 1.088 0.013 0.663 0.699 Married before age 20 0.470 0.011 2485 3375 1.148 0.024 0.447 0.493 Currently pregnant 0.025 0.003 3139 4246 1.053 0.117 0.019 0.031 Children ever born 1.584 0.025 3139 4246 0.995 0.016 1.535 1.634 Abortions, women age 40-49 1.384 0.080 928 1264 1.436 0.058 1.224 1.544 Induced abortions (%) 0.305 0.019 772 1044 1.112 0.064 0.266 0.344 Children surviving 1.516 0.023 3139 4246 0.992 0.015 1.470 1.563 Children ever born to women age 40-49 2.633 0.049 928 1264 1.231 0.019 2.535 2.731 Knows any contraceptive method 0.995 0.002 2141 2892 1.085 0.002 0.991 0.998 Ever using contraceptive method 0.907 0.007 2141 2892 1.188 0.008 0.892 0.922 Currently using any contraceptive method 0.682 0.010 2141 2892 1.023 0.015 0.661 0.702 Currently using a modern method 0.410 0.011 2141 2892 1.048 0.027 0.388 0.433 Currently using pill 0.026 0.004 2141 2892 1.077 0.142 0.019 0.033 Currently using IUD 0.278 0.010 2141 2892 1.027 0.036 0.258 0.298 Currently using condom 0.035 0.005 2141 2892 1.226 0.140 0.025 0.044 Currently using female sterilization 0.047 0.005 2141 2892 1.005 0.098 0.038 0.056 Currently using periodic abstinence 0.024 0.003 2141 2892 1.048 0.144 0.017 0.031 Obtained method from public sector source 0.824 0.013 919 1247 1.049 0.016 0.798 0.850 Want no more children 0.693 0.012 2141 2892 1.166 0.017 0.670 0.716 Want to delay birth at least 2 years 0.109 0.007 2141 2892 0.998 0.062 0.096 0.123 Mothers received tetanus injection for last birth 0.914 0.016 610 821 1.420 0.018 0.882 0.946 Mothers received medical assistance at delivery 0.995 0.002 728 980 0.886 0.002 0.990 0.999 Had diarrhoea in two weeks before survey 0.048 0.008 718 966 0.935 0.159 0.033 0.064 Vaccination card seen 0.892 0.026 147 201 1.016 0.029 0.840 0.944 Received BCG 0.996 0.004 147 201 0.794 0.004 0.987 1.004 Received DPT (3 doses) 0.953 0.018 147 201 1.023 0.019 0.918 0.989 Received polio (3 doses) 0.958 0.017 147 201 1.040 0.018 0.924 0.992 Received measles 0.921 0.025 147 201 1.145 0.028 0.870 0.972 Fully immunized 0.889 0.028 147 201 1.079 0.031 0.834 0.945 Height-for-age (below -2SD) 0.092 0.011 745 1001 0.956 0.117 0.070 0.113 Weight-for-height (below -2SD) 0.038 0.009 745 1001 1.209 0.224 0.021 0.055 Weight-for-age (below -2SD) 0.051 0.006 745 1001 0.787 0.126 0.038 0.064 BMI <18.5 0.055 0.004 3015 4082 1.073 0.081 0.046 0.064 Has heard of HIV/AIDS 0.961 0.004 3139 4246 1.184 0.004 0.953 0.969 Knows about condoms 0.732 0.011 3139 4246 1.401 0.015 0.709 0.754 Knows about limiting partners 0.768 0.010 3139 4246 1.310 0.013 0.748 0.787 Any anemia (children) 0.347 0.021 688 932 1.122 0.060 0.305 0.388 Any anemia (women) 0.301 0.010 3085 4176 1.237 0.034 0.281 0.322 Total abortion rate 1.207 0.107 na 13329 1.658 0.089 0.993 1.422 Total fertility rate last 3 years) 1.847 0.087 na 11912 1.050 0.047 1.673 2.022 Neonatal mortality (last 10 years) 15.836 3.576 1555 2062 1.039 0.226 8.683 22.989 Postneonatal mortality (last 10 years) 7.459 2.031 1556 2063 0.934 0.272 3.398 11.520 Infant mortality (last 10 years) 23.295 4.110 1556 2063 1.026 0.176 15.075 31.514 Child mortality (last 10 years) 6.416 1.740 1561 2069 0.920 0.271 2.935 9.897 Under five years mortality (last 10 years) 29.562 4.384 1562 2071 1.006 0.148 20.793 38.330 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.000 0.000 1091 1453 na na 0.000 0.000 Literate 0.996 0.002 1091 1453 1.048 0.002 0.992 1.000 No education 0.002 0.001 1091 1453 0.988 0.709 0.000 0.004 Secondary education or higher 0.991 0.003 1091 1453 1.175 0.003 0.985 0.998 Never married 0.273 0.014 1091 1453 1.025 0.051 0.246 0.301 Currently married/in union 0.680 0.014 1091 1453 1.001 0.021 0.652 0.709 Married before age 20 0.087 0.009 913 1216 0.918 0.098 0.070 0.104 Want no more children 0.690 0.019 744 989 1.091 0.027 0.653 0.727 Want to delay birth at least 2 years 0.072 0.011 744 989 1.148 0.151 0.050 0.094 Has heard of HIV/AIDS 0.956 0.008 1091 1453 1.270 0.008 0.940 0.972 Knows about condoms 0.800 0.016 1091 1453 1.311 0.020 0.768 0.831 Knows about limiting partners 0.836 0.014 1091 1453 1.210 0.016 0.809 0.864 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable Appendix B | 245 Table B.5 Sampling errors for North sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.316 0.011 2065 2207 1.112 0.036 0.294 0.339 Literate 0.995 0.002 2065 2207 1.310 0.002 0.992 0.999 No education 0.005 0.002 2065 2207 1.352 0.441 0.001 0.009 Secondary education or higher 0.991 0.004 2065 2207 1.898 0.004 0.984 0.999 Net attendance ratio for primary school 0.767 0.020 549 605 1.114 0.026 0.728 0.807 Never married 0.224 0.011 2065 2207 1.147 0.047 0.203 0.245 Currently married/in union 0.687 0.012 2065 2207 1.177 0.017 0.663 0.711 Married before age 20 0.497 0.014 1695 1809 1.128 0.028 0.469 0.524 Currently pregnant 0.026 0.004 2065 2207 1.033 0.140 0.018 0.033 Children ever born 1.407 0.030 2065 2207 1.152 0.021 1.347 1.467 Abortions, women age 40-49 1.483 0.101 634 680 1.504 0.068 1.280 1.686 Induced abortions (%) 0.334 0.028 499 531 1.247 0.084 0.277 0.390 Children surviving 1.355 0.029 2065 2207 1.180 0.022 1.296 1.413 Children ever born to women age 40-49 2.191 0.050 634 680 1.251 0.023 2.091 2.291 Knows any contraceptive method 0.995 0.002 1405 1515 1.148 0.002 0.991 1.000 Ever using contraceptive method 0.915 0.009 1405 1515 1.158 0.009 0.898 0.933 Currently using any contraceptive method 0.690 0.012 1405 1515 0.955 0.017 0.666 0.714 Currently using a modern method 0.415 0.014 1405 1515 1.075 0.034 0.386 0.443 Currently using pill 0.034 0.006 1405 1515 1.188 0.168 0.023 0.046 Currently using IUD 0.260 0.013 1405 1515 1.108 0.050 0.234 0.286 Currently using condom 0.052 0.007 1405 1515 1.158 0.133 0.038 0.065 Currently using female sterilization 0.048 0.007 1405 1515 1.142 0.135 0.035 0.061 Currently using periodic abstinence 0.034 0.006 1405 1515 1.137 0.161 0.023 0.045 Obtained method from public sector source 0.778 0.018 659 678 1.085 0.023 0.743 0.813 Want no more children 0.702 0.014 1405 1515 1.169 0.020 0.673 0.730 Want to delay birth at least 2 years 0.108 0.009 1405 1515 1.117 0.086 0.089 0.126 Mothers received tetanus injection for last birth 0.930 0.016 396 424 1.234 0.017 0.898 0.961 Mothers received medical assistance at delivery 1.000 0.000 440 473 na 0.000 1.000 1.000 Had diarrhoea in two weeks before survey 0.081 0.012 435 468 0.920 0.149 0.057 0.106 Vaccination card seen 0.853 0.042 91 102 1.169 0.050 0.769 0.938 Received BCG 1.000 0.000 91 102 na 0.000 1.000 1.000 Received DPT (3 doses) 0.931 0.027 91 102 1.026 0.029 0.878 0.984 Received polio (3 doses) 0.940 0.026 91 102 1.092 0.028 0.888 0.993 Received measles 0.915 0.039 91 102 1.365 0.043 0.837 0.993 Fully immunized 0.864 0.043 91 102 1.220 0.050 0.778 0.949 Height-for-age (below -2SD) 0.063 0.011 426 460 0.920 0.172 0.041 0.084 Weight-for-height (below -2SD) 0.039 0.011 426 460 1.164 0.282 0.017 0.062 Weight-for-age (below -2SD) 0.024 0.008 426 460 1.030 0.322 0.008 0.039 BMI <18.5 0.060 0.007 1968 2111 1.260 0.112 0.047 0.074 Has heard of HIV/AIDS 0.977 0.005 2065 2207 1.411 0.005 0.968 0.986 Knows about condoms 0.773 0.014 2065 2207 1.536 0.018 0.745 0.801 Knows about limiting partners 0.804 0.010 2065 2207 1.173 0.013 0.783 0.824 Any anemia (children) 0.353 0.029 411 443 1.187 0.082 0.295 0.411 Any anemia (women) 0.316 0.013 2014 2164 1.294 0.042 0.289 0.343 Total abortion rate 1.250 0.144 na 6817 1.988 0.115 0.962 1.537 Total fertility rate (last 3 years) 1.678 0.109 na 6264 1.117 0.065 1.460 1.895 Neonatal mortality (last 10 years) 14.732 4.982 874 961 1.137 0.338 4.767 24.696 Postneonatal mortality (last 10 years) 3.430 1.766 874 961 0.917 0.515 -0.103 6.962 Infant mortality (last 10 years) 18.161 5.215 874 961 1.093 0.287 7.731 28.591 Child mortality (last 10 years) 3.511 1.933 877 965 1.013 0.551 -0.355 7.377 Under five years mortality (last 10 years) 21.608 5.680 877 965 1.114 0.263 10.248 32.969 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.311 0.014 700 756 0.815 0.046 0.282 0.339 Literate 0.997 0.002 700 756 1.129 0.002 0.992 1.000 No education 0.001 0.001 700 756 0.770 1.003 0.000 0.003 Secondary education or higher 0.994 0.003 700 756 1.059 0.003 0.988 1.000 Never married 0.252 0.017 700 756 1.041 0.068 0.218 0.286 Currently married/in union 0.703 0.017 700 756 1.011 0.025 0.668 0.738 Married before age 20 0.104 0.013 606 656 1.039 0.124 0.078 0.129 Want no more children 0.689 0.026 488 532 1.252 0.038 0.637 0.742 Want to delay birth at least 2 years 0.074 0.017 488 532 1.393 0.222 0.041 0.108 Has heard of HIV/AIDS 0.966 0.008 700 756 1.225 0.009 0.949 0.983 Knows about condoms 0.835 0.020 700 756 1.447 0.024 0.794 0.875 Knows about limiting partners 0.860 0.019 700 756 1.480 0.023 0.822 0.899 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable 246 | Appendix B Table B.6 Sampling errors for Center sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.196 0.011 1805 2033 1.182 0.056 0.174 0.218 Literate 0.997 0.001 1805 2033 1.057 0.001 0.994 1.000 No education 0.002 0.001 1805 2033 1.028 0.521 0.000 0.004 Secondary education or higher 0.992 0.003 1805 2033 1.491 0.003 0.986 0.999 Net attendance ratio for primary school 0.772 0.018 578 655 1.033 0.024 0.735 0.809 Never married 0.268 0.013 1805 2033 1.231 0.048 0.243 0.294 Currently married/in union 0.657 0.014 1805 2033 1.249 0.021 0.629 0.685 Married before age 20 0.425 0.015 1401 1577 1.140 0.035 0.395 0.455 Currently pregnant 0.021 0.004 1805 2033 1.243 0.200 0.013 0.029 Children ever born 1.556 0.032 1805 2033 0.936 0.021 1.492 1.620 Abortions, women age 40-49 1.414 0.115 541 606 1.463 0.081 1.184 1.644 Induced abortions (%) 0.283 0.024 434 486 1.039 0.087 0.234 0.331 Children surviving 1.492 0.029 1805 2033 0.904 0.020 1.433 1.550 Children ever born to women age 40-49 2.732 0.075 541 606 1.342 0.028 2.582 2.883 Knows any contraceptive method 0.994 0.002 1181 1336 1.091 0.002 0.989 0.999 Ever using contraceptive method 0.909 0.010 1181 1336 1.222 0.011 0.888 0.929 Currently using any contraceptive method 0.667 0.016 1181 1336 1.147 0.024 0.635 0.698 Currently using a modern method 0.411 0.016 1181 1336 1.138 0.040 0.378 0.443 Currently using pill 0.022 0.004 1181 1336 0.858 0.165 0.015 0.030 Currently using IUD 0.279 0.015 1181 1336 1.173 0.055 0.249 0.310 Currently using condom 0.035 0.007 1181 1336 1.381 0.211 0.020 0.050 Currently using female sterilization 0.048 0.006 1181 1336 0.947 0.123 0.036 0.060 Currently using periodic abstinence 0.030 0.005 1181 1336 0.932 0.155 0.020 0.039 Obtained method from public sector source 0.823 0.019 521 581 1.156 0.023 0.785 0.862 Want no more children 0.668 0.016 1181 1336 1.176 0.024 0.635 0.700 Want to delay birth at least 2 years 0.121 0.009 1181 1336 0.999 0.079 0.102 0.140 Mothers received tetanus injection for last birth 0.881 0.025 338 386 1.449 0.029 0.830 0.932 Mothers received medical assistance at delivery 0.991 0.004 402 464 0.956 0.004 0.983 1.000 Had diarrhoea in two weeks before survey 0.049 0.010 398 458 0.902 0.208 0.029 0.069 Vaccination card seen 0.931 0.027 94 104 1.006 0.029 0.878 0.984 Received BCG 0.992 0.008 94 104 0.867 0.008 0.975 1.000 Received DPT (3 doses) 0.945 0.022 94 104 0.948 0.024 0.900 0.990 Received polio (3 doses) 0.954 0.021 94 104 0.953 0.022 0.912 0.996 Received measles 0.909 0.028 94 104 0.939 0.031 0.852 0.965 Fully immunized 0.870 0.030 94 104 0.863 0.035 0.810 0.931 Height-for-age (below -2SD) 0.102 0.016 397 462 1.042 0.159 0.069 0.134 Weight-for-height (below -2SD) 0.049 0.014 397 462 1.349 0.294 0.020 0.077 Weight-for-age (below -2SD) 0.065 0.009 397 462 0.755 0.143 0.047 0.084 BMI <18.5 0.053 0.006 1731 1954 1.030 0.105 0.042 0.064 Has heard of HIV/AIDS 0.953 0.006 1805 2033 1.227 0.006 0.941 0.966 Knows about condoms 0.745 0.015 1805 2033 1.497 0.021 0.714 0.776 Knows about limiting partners 0.773 0.016 1805 2033 1.609 0.021 0.741 0.805 Any anemia (children) 0.311 0.028 369 432 1.165 0.091 0.255 0.368 Any anemia (women) 0.258 0.013 1761 1992 1.216 0.049 0.233 0.284 Total abortion rate 1.125 0.143 na 6496 1.420 0.128 0.838 1.412 Total fertility rate (last 3 years) 1.961 0.130 na 5677 1.160 0.066 1.700 2.222 Neonatal mortality (last 10 years) 11.154 4.152 814 934 1.159 0.372 2.850 19.457 Postneonatal mortality (last 10 years) 7.949 3.258 814 934 1.070 0.410 1.433 14.465 Infant mortality (last 10 years) 19.103 5.428 814 934 1.176 0.284 8.247 29.959 Child mortality (last 10 years) 8.376 2.893 817 938 0.982 0.345 2.591 14.161 Under five years mortality (last 10 years) 27.319 5.802 817 938 1.076 0.212 15.715 38.922 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.211 0.014 633 702 0.887 0.068 0.182 0.239 Literate 0.994 0.003 633 702 1.114 0.003 0.987 1.000 No education 0.002 0.002 633 702 1.125 1.000 0.000 0.006 Secondary education or higher 0.988 0.006 633 702 1.354 0.006 0.976 0.999 Never married 0.317 0.021 633 702 1.112 0.065 0.276 0.359 Currently married/in union 0.646 0.021 633 702 1.100 0.032 0.604 0.688 Married before age 20 0.085 0.010 501 556 0.833 0.122 0.064 0.106 Want no more children 0.673 0.024 410 453 1.020 0.035 0.625 0.720 Want to delay birth at least 2 years 0.068 0.013 410 453 1.028 0.189 0.042 0.093 Has heard of HIV/AIDS 0.968 0.009 633 702 1.319 0.010 0.949 0.986 Knows about condoms 0.856 0.022 633 702 1.553 0.025 0.813 0.899 Knows about limiting partners 0.874 0.017 633 702 1.275 0.019 0.841 0.908 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable Appendix B | 247 Table B.7 Sampling errors for South sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.302 0.013 1443 1402 1.056 0.042 0.276 0.327 Literate 0.998 0.001 1443 1402 0.437 0.001 0.997 0.999 No education 0.001 0.001 1443 1402 0.896 0.995 0.000 0.002 Secondary education or higher 0.995 0.001 1443 1402 0.810 0.001 0.993 0.998 Net attendance ratio for primary school 0.795 0.018 468 466 1.041 0.023 0.758 0.832 Never married 0.252 0.010 1443 1402 0.846 0.038 0.233 0.271 Currently married/in union 0.683 0.010 1443 1402 0.808 0.015 0.663 0.703 Married before age 20 0.435 0.019 1165 1135 1.319 0.044 0.397 0.473 Currently pregnant 0.025 0.005 1443 1402 1.110 0.181 0.016 0.034 Children ever born 1.565 0.040 1443 1402 1.087 0.025 1.486 1.645 Abortions, women age 40-49 1.404 0.094 431 418 1.107 0.067 1.216 1.593 Induced abortions (%) 0.290 0.030 352 354 1.222 0.103 0.231 0.350 Children surviving 1.492 0.038 1443 1402 1.103 0.025 1.417 1.568 Children ever born to women age 40-49 2.642 0.074 431 418 1.279 0.028 2.493 2.790 Knows any contraceptive method 0.995 0.002 975 958 1.097 0.002 0.991 1.000 Ever using contraceptive method 0.901 0.013 975 958 1.349 0.014 0.875 0.927 Currently using any contraceptive method 0.673 0.019 975 958 1.233 0.028 0.636 0.710 Currently using a modern method 0.431 0.017 975 958 1.088 0.040 0.396 0.465 Currently using pill 0.030 0.006 975 958 1.156 0.211 0.017 0.043 Currently using IUD 0.285 0.014 975 958 0.968 0.049 0.257 0.313 Currently using condom 0.038 0.007 975 958 1.075 0.173 0.025 0.051 Currently using female sterilization 0.049 0.008 975 958 1.115 0.157 0.034 0.065 Currently using periodic abstinence 0.020 0.004 975 958 0.885 0.197 0.012 0.028 Obtained method from public sector source 0.772 0.022 456 439 1.114 0.028 0.728 0.815 Want no more children 0.657 0.018 975 958 1.191 0.028 0.621 0.693 Want to delay birth at least 2 years 0.125 0.009 975 958 0.890 0.075 0.106 0.144 Mothers received tetanus injection for last birth 0.941 0.017 265 264 1.191 0.018 0.906 0.975 Mothers received medical assistance at delivery 0.994 0.004 314 317 1.015 0.004 0.985 1.003 Had diarrhoea in two weeks before survey 0.059 0.014 309 311 1.030 0.230 0.032 0.086 Vaccination card seen 0.915 0.027 56 54 0.726 0.030 0.860 0.969 Received BCG 1.000 0.000 56 54 na 0.000 1.000 1.000 Received DPT (3 doses) 0.966 0.026 56 54 1.055 0.027 0.915 1.017 Received polio (3 doses) 0.952 0.029 56 54 1.005 0.030 0.895 1.010 Received measles 0.947 0.038 56 54 1.252 0.040 0.872 1.022 Fully immunized 0.899 0.047 56 54 1.154 0.052 0.806 0.992 Height-for-age (below -2SD) 0.110 0.021 313 314 1.114 0.190 0.068 0.152 Weight-for-height (below -2SD) 0.032 0.010 313 314 0.991 0.305 0.012 0.051 Weight-for-age (below -2SD) 0.056 0.012 313 314 0.986 0.222 0.031 0.081 BMI <18.5 0.047 0.006 1386 1345 0.979 0.118 0.036 0.059 Has heard of HIV/AIDS 0.977 0.005 1443 1402 1.209 0.005 0.968 0.987 Knows about condoms 0.753 0.014 1443 1402 1.249 0.019 0.724 0.781 Knows about limiting partners 0.805 0.013 1443 1402 1.219 0.016 0.779 0.830 Any anemia (children) 0.357 0.033 280 281 1.229 0.094 0.290 0.424 Any anemia (women) 0.314 0.018 1409 1367 1.442 0.057 0.278 0.350 Total abortion rate 1.215 0.159 na 4357 1.389 0.131 0.897 1.533 Total fertility rate (last 3 years) 1.823 0.105 na 3958 0.973 0.058 1.613 2.033 Neonatal mortality (last 10 years) 19.639 6.895 672 678 1.138 0.351 5.849 33.429 Postneonatal mortality (last 10 years) 11.184 3.959 673 679 1.013 0.354 3.266 19.102 Infant mortality (last 10 years) 30.823 7.695 673 679 1.096 0.250 15.433 46.213 Child mortality (last 10 years) 7.438 3.058 674 679 1.031 0.411 1.323 13.553 Under five years mortality (last 10 years) 38.031 8.130 675 681 1.091 0.214 21.771 54.292 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.321 0.017 518 496 0.814 0.052 0.287 0.354 Literate 1.000 0.000 518 496 na 0.000 1.000 1.000 No education 0.002 0.002 518 496 1.108 0.997 0.000 0.007 Secondary education or higher 0.995 0.003 518 496 0.962 0.003 0.989 1.000 Never married 0.261 0.017 518 496 0.894 0.066 0.226 0.295 Currently married/in union 0.682 0.021 518 496 1.029 0.031 0.640 0.724 Married before age 20 0.076 0.013 440 420 1.027 0.171 0.050 0.102 Want no more children 0.672 0.029 354 338 1.150 0.043 0.614 0.729 Want to delay birth at least 2 years 0.074 0.015 354 338 1.095 0.206 0.044 0.105 Has heard of HIV/AIDS 0.940 0.015 518 496 1.468 0.016 0.910 0.971 Knows about condoms 0.792 0.020 518 496 1.096 0.025 0.753 0.831 Knows about limiting partners 0.845 0.016 518 496 0.983 0.019 0.813 0.876 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable 248 | Appendix B Table B.8 Sampling errors for Chisinau sample, Moldova 2005 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of cases Stand- –––––––––––––––– Rela- ard Un- Weight- Design tive Confidence limits Value error weighted ed effect error –––––––––––––––– Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– WOMEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.932 0.004 2127 1798 0.761 0.004 0.923 0.940 Literate 0.999 0.001 2127 1798 1.011 0.001 0.997 1.000 No education 0.001 0.001 2127 1798 0.970 0.706 0.000 0.002 Secondary education or higher 0.995 0.002 2127 1798 1.200 0.002 0.992 0.999 Net attendance ratio for primary school 0.804 0.020 471 384 1.072 0.025 0.764 0.844 Never married 0.260 0.009 2127 1798 0.959 0.035 0.242 0.279 Currently married/in union 0.627 0.010 2127 1798 0.963 0.016 0.607 0.647 Married before age 20 0.342 0.012 1776 1503 1.095 0.036 0.317 0.367 Currently pregnant 0.024 0.004 2127 1798 1.131 0.155 0.017 0.032 Children ever born 1.005 0.023 2127 1798 1.063 0.023 0.958 1.052 Abortions, women age 40-49 1.662 0.096 545 452 1.233 0.058 1.470 1.855 Induced abortions (%) 0.451 0.022 554 474 1.017 0.048 0.408 0.494 Children surviving 0.973 0.022 2127 1798 1.021 0.022 0.930 1.016 Children ever born to women age 40-49 1.797 0.049 545 452 1.174 0.027 1.699 1.895 Knows any contraceptive method 0.997 0.001 1331 1127 0.618 0.001 0.995 0.999 Ever using contraceptive method 0.919 0.008 1331 1127 1.007 0.008 0.904 0.934 Currently using any contraceptive method 0.679 0.014 1331 1127 1.075 0.020 0.651 0.706 Currently using a modern method 0.510 0.014 1331 1127 1.053 0.028 0.481 0.539 Currently using pill 0.059 0.008 1331 1127 1.200 0.131 0.043 0.074 Currently using IUD 0.183 0.010 1331 1127 0.948 0.055 0.163 0.203 Currently using condom 0.179 0.013 1331 1127 1.193 0.070 0.154 0.204 Currently using female sterilization 0.040 0.005 1331 1127 0.961 0.129 0.030 0.050 Currently using periodic abstinence 0.053 0.006 1331 1127 1.000 0.116 0.041 0.065 Obtained method from public sector source 0.422 0.019 795 678 1.062 0.044 0.385 0.459 Want no more children 0.515 0.014 1331 1127 1.058 0.028 0.486 0.544 Want to delay birth at least 2 years 0.202 0.012 1331 1127 1.109 0.060 0.178 0.226 Mothers received tetanus injection for last birth 0.849 0.025 370 313 1.333 0.029 0.799 0.898 Mothers received medical assistance at delivery 0.995 0.003 396 337 0.974 0.003 0.989 1.002 Had diarrhoea in two weeks before survey 0.114 0.014 391 333 0.892 0.125 0.085 0.143 Vaccination card seen 0.895 0.043 80 69 1.249 0.048 0.809 0.980 Received BCG 1.000 0.000 80 69 na 0.000 1.000 1.000 Received DPT (3 doses) 0.901 0.035 80 69 1.047 0.038 0.832 0.971 Received polio (3 doses) 0.948 0.024 80 69 0.993 0.026 0.900 0.997 Received measles 0.854 0.049 80 69 1.239 0.057 0.757 0.951 Fully immunized 0.776 0.056 80 69 1.198 0.072 0.665 0.887 Height-for-age (below -2SD) 0.058 0.013 320 262 0.996 0.229 0.031 0.085 Weight-for-height (below -2SD) 0.029 0.009 320 262 0.983 0.318 0.010 0.047 Weight-for-age (below -2SD) 0.022 0.008 320 262 0.995 0.372 0.006 0.038 BMI <18.5 0.076 0.006 1954 1652 1.065 0.084 0.063 0.089 Has heard of HIV/AIDS 0.992 0.003 2127 1798 1.325 0.003 0.987 0.997 Knows about condoms 0.858 0.009 2127 1798 1.159 0.010 0.841 0.876 Knows about limiting partners 0.876 0.009 2127 1798 1.223 0.010 0.858 0.893 Any anemia (children) 0.227 0.023 255 208 0.868 0.102 0.181 0.274 Any anemia (women) 0.223 0.012 1915 1616 1.234 0.053 0.199 0.246 Total abortion rate 1.641 0.123 na 5677 1.476 0.075 1.395 1.888 Total fertility rate (last 3 years) 1.381 0.085 na 5145 1.078 0.061 1.211 1.550 Neonatal mortality (last 10 years) 10.960 3.970 747 642 1.062 0.362 3.021 18.899 Postneonatal mortality (last 10 years) 7.277 2.963 747 642 0.962 0.407 1.350 13.203 Infant mortality (last 10 years) 18.237 4.692 747 642 0.980 0.257 8.853 27.621 Child mortality (last 10 years) 0.778 0.780 748 643 0.758 1.002 0.000 2.338 Under five years mortality (last 10 years) 19.001 4.829 748 643 0.991 0.254 9.342 28.660 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– MEN ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban residence 0.925 0.010 657 554 1.004 0.011 0.904 0.946 Literate 0.999 0.001 657 554 0.983 0.001 0.996 1.000 No education 0.000 0.000 657 554 na na 0.000 0.000 Secondary education or higher 0.999 0.001 657 554 0.983 0.001 0.996 1.000 Never married 0.338 0.020 657 554 1.073 0.059 0.298 0.378 Currently married/in union 0.603 0.020 657 554 1.048 0.033 0.563 0.643 Married before age 20 0.069 0.013 550 466 1.167 0.183 0.044 0.094 Want no more children 0.493 0.023 392 334 0.902 0.046 0.447 0.538 Want to delay birth at least 2 years 0.127 0.016 392 334 0.947 0.125 0.095 0.159 Has heard of HIV/AIDS 0.998 0.002 657 554 0.888 0.002 0.994 1.000 Knows about condoms 0.905 0.012 657 554 1.068 0.014 0.880 0.929 Knows about limiting partners 0.897 0.014 657 554 1.214 0.016 0.868 0.926 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable Appendix C | 249 QUALITY TABLES Appendix C Table C.1 Household age distribution Single-year age distribution of the de facto household population by sex (weighted), Moldova 2005 Female Male Female Male Age Number Percentage Number Percentage Age Number Percentage Number Percentage 0 167 1.2 168 1.0 36 148 1.0 186 1.1 1 191 1.3 169 1.0 37 161 1.1 157 1.0 2 183 1.3 190 1.2 38 172 1.2 183 1.1 3 183 1.3 153 0.9 39 168 1.2 176 1.1 4 176 1.2 163 1.0 40 185 1.3 186 1.1 5 159 1.1 157 1.0 41 156 1.1 177 1.1 6 197 1.4 173 1.1 42 187 1.3 195 1.2 7 181 1.3 201 1.2 43 210 1.5 213 1.3 8 188 1.3 175 1.1 44 182 1.3 256 1.6 9 194 1.4 201 1.2 45 268 1.9 255 1.6 10 238 1.7 232 1.4 46 211 1.5 239 1.5 11 255 1.8 248 1.5 47 208 1.5 227 1.4 12 242 1.7 263 1.6 48 204 1.4 243 1.5 13 271 1.9 248 1.5 49 193 1.4 222 1.4 14 296 2.1 310 1.9 50 222 1.6 296 1.8 15 305 2.1 278 1.7 51 181 1.3 262 1.6 16 294 2.1 295 1.8 52 241 1.7 236 1.5 17 285 2.0 288 1.8 53 230 1.6 275 1.7 18 258 1.8 309 1.9 54 220 1.5 270 1.7 19 228 1.6 265 1.6 55 257 1.8 308 1.9 20 263 1.8 268 1.7 56 265 1.9 299 1.8 21 217 1.5 230 1.4 57 153 1.1 186 1.1 22 194 1.4 225 1.4 58 113 0.8 157 1.0 23 212 1.5 240 1.5 59 61 0.4 117 0.7 24 204 1.4 203 1.2 60 95 0.7 110 0.7 25 204 1.4 200 1.2 61 104 0.7 129 0.8 26 206 1.4 183 1.1 62 141 1.0 166 1.0 27 189 1.3 192 1.2 63 138 1.0 165 1.0 28 179 1.3 177 1.1 64 132 0.9 186 1.1 29 198 1.4 217 1.3 65 142 1.0 182 1.1 30 207 1.5 190 1.2 66 84 0.6 133 0.8 31 148 1.0 187 1.2 67 110 0.8 188 1.2 32 168 1.2 183 1.1 68 115 0.8 160 1.0 33 158 1.1 194 1.2 69 112 0.8 164 1.0 34 161 1.1 172 1.1 70+ 923 6.5 1,583 9.8 35 186 1.3 176 1.1 Don’t know/ missing 1 0.0 2 0.0 Total 14,278 100.0 16,210 100.0 250 | Appendix C Table C.2.1 Age distribution of eligible and interviewed women De facto household population of women age 10-54, interviewed women age 15-49, and percentage of eligible women who were inter- viewed (weighted), by five-year age groups, Moldova 2005 Interviewed women age 15-49 Age group Household population of women age 10-54 Number Percent Percentage of eligible women interviewed 10-14 1,302 na na na 15-19 1,434 1,388 19.2 96.8 20-24 1,166 1,095 15.1 93.9 25-29 968 935 12.9 96.5 30-34 926 896 12.4 96.8 25-39 878 833 11.5 94.9 40-44 1,027 982 13.5 95.6 45-49 1,186 1,119 15.4 94.3 50-54 1,339 na na na 15-49 7,585 7,248 100.0 95.6 Note: The de facto population includes all residents and nonresidents who stayed in the household the night before the interview. Weights for both household population of women and interviewed women are household weights. Age is based on the household schedule. na = Not applicable Table C.2.2 Age distribution of eligible and interviewed men De facto household population of men age 10-64, interviewed men aged 15-59 and percentage of eligible men who were interviewed (weighted), by five-year age groups, Moldova 2005 Interviewed men age 15-59 Age group Household population of men age 10-64 Number Percent Percentage of eligible men interviewed 10-14 416 na na na 15-19 451 404 16.4 89.6 20-24 310 272 11.0 87.7 25-29 272 227 9.2 83.4 30-34 252 222 9.0 88.1 25-39 273 244 9.9 89.5 40-44 283 241 9.7 85.2 45-49 390 345 14.0 88.5 50-54 342 298 12.0 87.1 55-59 250 218 8.8 87.1 60-64 207 na na na 15-59 2,824 2,472 100.0 87.5 Note: The de facto population includes all residents and nonresidents who stayed in the household the night before the interview. Weights for both household population of men and interviewed men are household weights. Age is based on the household schedule. na = Not applicable Appendix C | 251 Table C.3 Completeness of reporting Percentage of observations missing information for selected demographic and health questions (weighted), Moldova 2005 Subject Reference group Percentage with missing information Number of cases Birth date Births in the past 15 years Month only 0.05 5,317 Month and year 0.02 5,317 Age at death Deceased children born in the past 15 years 1.85 140 Age/date at first union1 Ever-married women age 15-49 0.54 5,578 Respondent's education All women age 15-49 0.00 7,440 Diarrhea in past 2 weeks Living children age 0-59 months 0.69 1,571 Anthropometry2 Child’s height Living children age 0-59 months (from household questionnaire) 8.28 1,730 Child’s weight 7.83 1,730 Height or weight 8.51 1,730 Anemia test Anemia in children Children age 6-59 months (from household questionnaire) 11.88 1,573 Anemia in women Women age 15-49 (from household questionnaire) 7.88 7,585 1 Both year and age missing 2 Child not measured Table C.4 Births by calendar years since birth Number of births, percentage with complete birth date, sex ratio at birth, and calendar year ratio by calendar year, according to living, dead, and total children (weighted), Moldova 2005 Number of births Percentage with complete birth date1 Sex ratio at birth2 Calendar year ratio3Calendar year Living Dead Total Living Dead Total Living Dead Total Living Dead Total 2005 189 0 189 100.0 na 100.0 100.6 na 100.6 na na na 2004 349 6 355 100.0 100.0 100.0 108.5 58.0 107.4 na na na 2003 337 3 340 100.0 100.0 100.0 96.6 261.8 97.4 104.3 47.8 103.2 2002 297 7 304 100.0 100.0 100.0 102.7 73.5 101.9 95.3 244.9 96.7 2001 286 3 288 100.0 100.0 100.0 121.2 0.0 118.8 97.5 38.6 96.2 2000 289 7 296 100.0 100.0 100.0 99.3 182.3 100.7 99.2 146.5 99.9 1999 298 7 304 100.0 100.0 100.0 115.6 105.8 115.4 96.0 61.2 94.9 1998 331 15 345 99.5 100.0 99.5 105.4 470.0 111.2 116.7 181.9 118.6 1997 269 10 278 99.6 100.0 99.6 94.6 310.5 98.2 80.2 81.7 80.2 1996 340 9 349 100.0 100.0 100.0 96.8 135.3 97.7 105.6 64.8 104.0 2001-2005 1,458 18 1,476 100.0 100.0 100.0 105.7 65.1 105.0 na na na 1996-2000 1,526 47 1,573 99.8 100.0 99.8 102.2 226.0 104.5 na na na 1991-1995 2,017 72 2,089 99.9 100.0 99.9 107.5 163.7 109.0 na na na 1986-1990 2,220 84 2,305 99.9 98.4 99.8 105.1 135.6 106.0 na na na <1986 2,643 185 2,828 99.9 100.0 99.9 105.0 162.5 108.0 na na na All 9,864 407 10,271 99.9 99.7 99.9 105.2 155.5 106.8 na na na 1 Both 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 na = Not applicable 252 | 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 (weighted), Moldova 2005 Number of years preceding the survey Age at death (days) 0-4 5-9 10-14 15-19 Total 0-19 <1 3 4 4 8 18 1 2 12 5 12 30 2 1 3 4 3 10 3 2 6 3 3 14 4 0 1 1 2 4 5 0 3 3 3 8 6 0 1 0 0 1 7 0 4 3 1 7 8 0 0 0 1 1 9 0 1 0 1 2 10 0 0 1 2 3 14 0 1 0 0 2 16 0 0 0 1 1 20 0 0 0 2 2 28 0 0 0 1 1 Total 0-30 7 36 23 38 105 Percent early neonatal1 100.0 81.9 84.9 77.2 82.1 1 (0-6 days / 0-30 days)*100 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 age under one month, for five-year periods of birth preceding the survey, Moldova 2005 Number of years preceding the survey Age at death (months) 0-4 5-9 10-14 15-19 Total 0-19 <1a 7 36 23 38 105 1 3 2 3 6 15 2 3 0 3 8 14 3 2 2 1 6 11 4 1 1 0 1 3 5 1 0 5 3 8 6 2 1 3 4 10 7 0 2 1 3 5 8 0 0 0 1 1 9 1 0 0 0 1 11 0 0 1 1 2 13 0 0 1 0 1 14 0 0 2 0 2 15 0 1 0 1 3 16 0 0 1 0 1 17 0 0 3 0 3 18 0 0 1 0 1 23 0 1 0 0 1 1 year 0 0 1 2 3 Total 0-11 20 44 41 71 176 Percent neonatal1 36.1 83.1 57.5 53.3 59.7 1 (Under one month / under one year)*100 a Includes deaths under one month reported in days Appendix D | 253 PERSONS INVOLVED IN THE 2005 MOLDOVA DEMOGRAPHIC AND HEALTH SURVEY Appendix D ADMINISTRATION National Director Constantin Spînu, Vice director, National Scientific and Applied Center for Preventive Medicine, Ministry of Health and Social Protection (MOHSP) Technical Directors Oleg Beneú, Chief of Epidemiological Section for Conventional Diseases and Extremely Dangerous Diseases, National Scientific and Applied Center for Preventive Medicine, MOHSP Anatolie Melnic, Chief of General Epidemiology Section, National Scientific and Applied Center for Preventive Medicine, MOHSP Scientific Consultant Ion Bahnarel, Director, National Scientific and Applied Center for Preventive Medicine, MOHSP Project Accountants and Financial Advisors Liuba Calmîc Ecaterina Zazuc Ghenadie OĠel Senior Field Staff Victoria Bucov, Field Coordinator Angela Vrinceanu-Benes, Field Coordinator National Advisory Committee and Report Contributors Viorica Berdaga, Coordinator of Early Childhood Development Program, UNICEF Valentina Bodrug, Project Manager and National Gender Expert, UNIFEM Diana Cazacu, Project Manager, USAID Mihai Ciocan, Director, Scientific Center for Applied Public Health and Health Management Boris Gîlca, Program Coordinator, UNFPA Olga Poalelungi, Director General, Department of Migration Maria Strajescu, Vice Director General, Department of Statistics and Sociology Mihai Stratila, Vice Director, National Scientific Center for Human Reproduction, Medical Genetics and Family Planning Petru Stratulat, First Vice Director, Institute for Scientific Research in Mother and Child Protection Maria ğăruú, Chief of Department of Mother and Child Protection, MOHSP Mihai Paiu, Consultant for European Integration, Ministry of Education, Youth and Sports Valentin Friptu, Head of Faculty of Obstetrics and Gynecology, State University of Medicine and Pharmacology Ion Jarcutchi, Historian, National Scientific Academcy of Moldova Nina Munteanu, Chief of the Department of Medical Technology and Medical Assurance, Ministry of Health and Social Protection Ecaterina Stasi, Head of Faculty of Pediatrics State University of Medicine and Pharmacology Tudor Vasilev, Chief Physician in Narcology 254 | Appendix D ORC Macro Staff Fern Greewell, Project Manager Alfredo Aliaga, Sampling Statistician Alexander Izmukhambetov, Data Processing Specialist Anne Cross, Demographer Kiersten Johnson, Demographer Svetlana Negroustoueva, Pretest Trainer Sidney Moore, Editor Kaye Mitchell, Report Production Specialist FIELD STAFF Sample Selection Preparations Vitalie Valcov, Director General, Department of Statistics and Sociology Maria Străjescu, Vice Director General, Department of Statistics and Sociology Vasile DeaĠunic, Archivist Ion GrigoreĠ, Archivist Snigalitea Popa, Archivist Svetlana Dunaeva, Archivist Svetlana Terzi, Archivist Elena Oprea, Archivist LuminiĠa Arnaut, Archivist Dumitru Enache, Archivist Mihail Enache, Archivist Listers and Mappers Mihail Adamache, Supervisor Ion Cebotari, Supervisor Ovidiu Tafuni, Supervisor Mariana Chiúaca Mariana ùepilov Constantin Cebotari Valentin Goraú Zinaida Cheptea Vasile Novac Victor Buruncic Angela Leahu Ion Ghiúiu Tamara Sandu Ion Cheptene Mihail Peútereanu Nicolae Cotiujanu Ludmila Prociuc Veaceslav Chislari Iurie Bobu Vera Lefter Elena Saculteanu Elena Gusev Petru Robu Elizaveta Iordan Valentina ùciusi Ion Eni Vladimir Rîbalco Veaceslav Carp Ion CoiĠan Mihai Buhai ùtefan Surdu Svetlana Lupu Ecaterina Pascal Andrei Brinza Ecaterina Brinza Tamara Levinte Lidia Pogor Tatiana Pavilenco Nina Tinta Tamara Mînăscurtă Eugenia Rîbca Ludmila Rîbac Maxim Stasiuc Nina Popa Cornel ğaruú Serghei Gavrilita Maria Grecu Appendix D | 255 Data Collection Teams Leonid Savca, Supervisor Zinaida Ceban, Editor Svetlana Chirău, Interviewer Evelina Păslaru, Interviewerr Liuba Reileanu, Interviewer Veaceslav Carp, Interviewer Nicolae Furtună, Supervisor Lucia Chetraru, Editor Elena SaculĠanu, Interviewer Eugenia Tomceac, Interviewer Elena Usatîi, Interviewer Nicolae Pirojanschi, Interviewer Eugen Capcelea, Supervisor Zinaida Coroi, Editor Stela Balan, Interviewer Angela Capcelea, Interviewer Inga Mitrigan, Interviewer Sergiu Coroi, Interviewer Vasile Guútiuc, Supervisor Nina PanĠa, Editor Angela Guútiuc, Interviewer Ina Gilca, Interviewer Adela Horodiúteanu-Banu, Interviewer Oleg Horodisteanu, Interviewer Ion Cheptene, Supervisor Tamara Culicovschi, Editor Diana Coadă, Interviewer Violeta Negară, Interviewer Raisa Staver, Interviewer Mihai Culicovschi, Interviewer Alexandru Cărăruú, Supervisor Angela Ciobanu, Editor Alina Ferdohleb, Interviewer Oxana Indricean, Interviewer Daniela Prescur, Interviewer Radu Burghis, Interviewer Vasile Bejenaru, Supervisor Victoria Burlacu, Editor Maria Chiúcă, Interviewer Valentina Sciusi, Interviewer Laura ğurcan, Interviewer Eugen Beschieru, Interviewer Nicolae David, Supervisor Valentina Chiúlari, Editor Nina Carazanu, Interviewer Doina Lazurca, Interviewer Ala Munteanu, Interviewer Nicolae Bajurea, Interviewer Gheorghe GeĠoi, Supervisor Tamara Sandu, Editor Eudochia Doroftei, Interviewer Diana Gîscă, Interviewer Maria Revenco, Interviewer Ghenadii Apostol, Interviewer Nelea Ceban, Supervisor Viorica Prisacari, Editor Aurelia Brinza, Interviewer Natalia Silitrari, Interviewer Vera Stângu, Interviewer Dumitru Tabuncic, Interviewer Raisa ChisiliĠa, Supervisor Valentina Livandovschi, Editor Vladislava Breahnă, Interviewer Maria Capcelea, Interviewer Valentina Moscvitina, Interviewer Eduard Tcaci, Interviewer Maria Gusev, Supervisor Andriana Cucuruzac, Editor Marina Arama, Interviewer Elena Gusev, Interviewer Liudmila Sirbu, Interviewer Victor OĠel, Interviewer Ecaterina Pascal, Supervisor Olga Slastina, Editor Diana Bobeica, Interviewer Lucia Sînică, Interviewer Nadejda Sînică, Interviewer Nicolae Cotiujanu, Interviewer Cornel ğăruú, Supervisor Lidia Luchianov, Editor Ecaterina Capcelea, Interviewer Natalia Lavric, Interviewer Olga Romanova, Interviewer Andrei ğăruú, Interviewer Gheorghe ùtefeneĠ, Supervisor Mariana Lupu, Editor Viorica Liurca, Interviewer Efrosinia Bragarenco, Interviewer Eugenia Foleútean, Interviewer Victor Vovcenco, Interviewer 256 | Appendix D Data Processing Andrei Cazacu, Computer Programmer Dinu GuriĠa, Supervisor Constantin Jucovschi, Supervisor Alexandra Cecan, Office editor Adela Cucereanu, Office editor Olesea Babencu, Data keyer (operator) Natalia Caterinciuc, Data keyer (operator) Victor Ciugurean, Data keyer (operator) Corneliu Cordeleanu, Data keyer (operator) Iulian Cordeleanu, Data keyer (operator) Nina Dragomir, Data keyer (operator) Natalia Eni, Data keyer (operator) Mihai Marandici, Data keyer (operator) Pascal Denis, Data keyer (operator) Maria Perepelicinaea, Data keyer (operator) Tatiana Revenco, Data keyer (operator) Valeria Schirliu, Data keyer (operator) Drivers Igor Antoci Victor Bumbu Constantin Cebotari Rodica Cebotari Andrei Cherchez Ion Chifa Eduard Chiúca Ion Cîrlan Andrei CoiĠan Iurie Coliban Anatolie Dicusar Mihail Gavrilita Serghei Grosu Constantin Grozav Valeriu Hudoba Ilie Leahu Valeriu Lesnicenco Constantin Marandel Francisco Novac Vasile Pascar Alexandru Pavlenco Gheorghe Popa Vasile Popa Constantin Rîbca Violeta Stasiuc Victor Badea Vitalie Balta Iurie Botusneanu Iurie Budeanu Alexandru Calbura ùtefan Hariton Samil Magametov Victor Mahnovschi Nicolae Mîndru Ion Munteanu Valentin Paladi Petru Pîntea Mihail Popa Ivan Rotari Iurie Socolov Dumitru Spînu Serghei Stoicescu Veaceslav Svediuc Vladic Toma Igor Vacari QUESTIONNAIRES Appendix E 257Appendix E | MOLDOVA DEMOGRAPHIC AND HEALTH SURVEY HOUSEHOLD QUESTIONNAIRE MINISTRY OF HEALTH REPUBLIC OF MOLDOVA CENTER FOR PREVENTIVE MEDICINE IDENTIFICATION LOCALITY NAME NAME OF HOUSEHOLD HEAD CLUSTER NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MUNICIPIUL/RAIONUL RESIDENCE (URB=1, RUR=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD SELECTED FOR MALE SURVEY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .(YES=1, NO=2) INTERVIEWER VISITS FINAL VISIT DATE DAY MONTH YEAR INTERVIEWER'S NAME INT. CODE RESULT* RESULT NEXT VISIT: DATE TOTAL NUMBER TIME OF VISITS *RESULT CODES: 1 COMPLETED TOTAL PERSONS 2 NO HOUSEHOLD MEMBER AT HOME OR NO COMPETENT RESPONDENT AT IN HOUSEHOLD HOME AT TIME OF VISIT 3 ENTIRE HOUSEHOLD ABSENT FOR EXTENDED PERIOD OF TIME TOTAL ELIGIBLE 4 POSTPONED WOMEN 5 REFUSED 6 DWELLING VACANT OR ADDRESS NOT A DWELLING TOTAL ELIGIBLE 7 DWELLING DESTROYED MEN 8 DWELLING NOT FOUND 9 OTHER LINE NO. OF (SPECIFY) RESPONDENT TO HOUSEHOLD QUESTIONNAIRE SUPERVISOR FIELD EDITOR NAME NAME DATE DATE EDITOR OFFICE KEYED BY 2 0 0 5 1 2 3 June 1, 2005 259Appendix E | 1A RECORD THE TIME. HOUR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MINUTES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Now we would like some information about the people who usually live in your household or who are staying with you now. LINE USUAL RESIDENTS AND LINE NO. VISITORS NO. Please give me the names of What is the Is Does Did How old is CIRCLE CIRCLE CHECK IF the persons who usually live relationship of (NAME) (NAME) (NAME) (NAME)? LINE LINE HH IS in your household and guests (NAME) to the male or usually stay here NUMBER NUMBER SELECTED Is Does of the household who stayed head of the female? live last OF ALL OF ALL FOR MALE (NAME)'s (NAME)'s here last night, starting with household?* here? night? WOMEN CHILDREN SURVEY natural natural the head of the household. AGE UNDER mother mother 15-49 AGE 6 CIRCLE alive? live in this LINE house- NUMBER hold? OF ALL IF YES: MEN What is AGE her name? 15-59 RECORD MOTHER'S LINE NUMBER** (1) (2) (8) (9) (9A) M F YES NO YES NO Y N DK 01 1 2 1 2 1 2 01 01 01 01 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 02 1 2 1 2 1 2 02 02 02 02 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 03 1 2 1 2 1 2 03 03 03 03 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 04 1 2 1 2 1 2 04 04 04 04 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 05 1 2 1 2 1 2 05 05 05 05 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 06 1 2 1 2 1 2 06 06 06 06 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 07 1 2 1 2 1 2 07 07 07 07 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 08 1 2 1 2 1 2 08 08 08 08 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 * CODES FOR Q. 3 RELATIONSHIP TO HEAD OF HOUSEHOLD: 01 = HEAD 06 = PARENT 11 = OTHER RELATIVE 02 = WIFE OR HUSBAND 07 = PARENT-IN-LAW 12 = ADOPTED/FOSTER/STEPCHILD 03 = SON OR DAUGHTER 08 = BROTHER OR SISTER 13 = NOT RELATED 04 = SON-IN-LAW OR 09 = NIECE/NEPHEW BY BLOOD 98 = DON'T KNOW DAUGHTER-IN-LAW 10 = NIECE/NEPHEW BY MARRIAGE 05 = GRANDCHILD HOUSEHOLD SCHEDULE RELATIONSHIP TO HEAD OF HOUSEHOLD SEX (3) (4) (5) (6) AGE (11) RESIDENCE ELIGIBILITY IN YEARS (7) (10) SURVIVO OF B 260 | Appendix E260 LINE USUAL RESIDENTS AND LINE NO. VISITORS NO. Please give me the names of What is the Is Does Did How old is CIRCLE CIRCLE CHECK IF the persons who usually live relationship of (NAME) (NAME) (NAME) (NAME)? LINE LINE HH IS in your household and guests (NAME) to the male or usually stay here NUMBER NUMBER SELECTED Is Does of the household who stayed head of the female? live last OF ALL OF ALL FOR MALE (NAME)'s (NAME)'s here last night, starting with household?* here? night? WOMEN CHILDREN SURVEY natural natural the head of the household. AGE UNDER mother mother 15-49 AGE 6 CIRCLE alive? live in this LINE house- NUMBER hold? OF ALL IF YES: MEN What is AGE her name? 15-59 RECORD MOTHER'S LINE NUMBER** RELATIONSHIP TO HEAD OF HOUSEHOLD SEX AGERESIDENCE ELIGIBILITY SURVIVO OF B (1) (2) (8) (9) (9A) M F YES NO YES NO Y N DK 09 1 2 1 2 1 2 09 11 09 09 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 10 1 2 1 2 1 2 10 12 10 10 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 11 1 2 1 2 1 2 11 13 11 11 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 12 1 2 1 2 1 2 12 14 12 12 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 13 1 2 1 2 1 2 13 15 13 13 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 14 1 2 1 2 1 2 14 16 14 14 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 15 1 2 1 2 1 2 15 17 15 15 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 16 1 2 1 2 1 2 16 18 16 16 1 2 8 GO TO 12 GO TO 12 NO . . . .'00 *CODES FOR Q. 3 RELATIONSHIP TO HEAD OF HOUSEHOLD: 01 = HEAD 09 = NIECE/NEPHEW 02 = WIFE OR HUSBAND BY BLOOD 03 = SON OR DAUGHTER 10 = NIECE/NEPHEW 04 = SON-IN-LAW OR BY MARRIAGE DAUGHTER-IN-LAW 11 = OTHER RELATIVE 05 = GRANDCHILD 12 = ADOPTED/FOSTER/ 06 = PARENT STEPCHILD 07 = PARENT-IN-LAW 13 = NOT RELATED 08 = BROTHER OR SISTER 98 = DON'T KNOW IN YEARS (7) (10)(3) (4) (5) (6) (11) 261Appendix E | LINE NO. Where does Is Does Where does Has What is the Did During this/that Did During that Does (NAME)'s (NAME)'s (NAME)'s (NAME)'s (NAME) highest level of (NAME) school year, (NAME) school year, (NAME) natural natural natural natural ever school (NAME) attend what level and attend what have a birth mother live?** father father live father live?** attended has attended?*** school grade [is/was] school level and grade certificate? alive? in this school? What is the at any (NAME) at any did (NAME) IF NO, house- highest grade time attending?** time attend?*** PROBE: hold? (NAME) during during the Has IF YES: completed at that the previous (NAME)'s What is level?*** (2004 - school birth ever his name? 2005) year, been regis- RECORD school that is, tered with FATHER'S year? (2003 - the civil LINE 2004) ? authority? NUMBER** **** A O I DK Y N DK A O I DK YES NO LEVEL GRADE YES NO LEVEL GRADE YES NO LEVEL GRADE C R N DK 1 2 3 8 1 2 8 1 2 3 8 01 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 NO . . . .'00 GO TO 20 GO TO 18 GO TO 20 1 2 3 8 1 2 8 1 2 3 8 02 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 03 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 04 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 05 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 06 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 07 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 08 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 ** CODES FOR Qs 11A AND 13A *** CODES FOR Qs. 15, 17 AND 19 **** CODES FOR Q.20 A = ABROAD EDUCATION LEVEL: C = CERTIFICATE (REGISTERED WITH CIVIL AUTHORITY) O = OTHER HH 0 = PRESCHOOL, NURSERY SCHOOL R = REGISTRATION (EX. CONSTATATOR DE NASTERE) I = INSTITUTION 1 = PRIMARY (GR 1-4) N = NEITHER DK = DON'T KNOW 2ND INCOMPLETE 2 = GYMNASIUM (GR 5-9) DK = DON'T KNOW 2ND COMPLETE 3 = LYCEUM/MIDDLE SCHOOL (GR 10-12) 2ND COMPLETE 4 = POLIVALENT/SPT/MESERII EDUCATION GRADE: 2ND + 5 = COLLEGE/TECHNICAL SCHOOL 00 = LESS THAN 1 YEAR COMPLETED, OR PRE-SCHOOL 2ND + 6 = UNIVERSITY/POST-GRAD (FOR Q. 15 ONLY. THIS CODE IS 8 = DON'T KNOW NOT ALLOWED FOR Qs. 17 AND 19) 98 = DON'T KNOW BIRTH REGIS- TRATION IF AGE 0-4 (14) IF AGE 3 YEARS OR OLDER (15)(12) (13) IF AGE 0-17 YEARS (13A) (20)(18)(16) (19) EDUCATIONVORSHIP AND RESIDENCE BIOLOGICAL PARENTS (17)(11A) IF AGE 3-24 YEARS 262 | Appendix E262 LINE NO. Where does Is Does Where does Has What is the Did During this/that Did During that Does (NAME)'s (NAME)'s (NAME)'s (NAME)'s (NAME) highest level of (NAME) school year, (NAME) school year, (NAME) natural natural natural natural ever school (NAME) attend what level and attend what have a birth mother live?** father father live father live?** attended has attended?*** school grade [is/was] school level and grade certificate? alive? in this school? What is the at any (NAME) at any did (NAME) IF NO, house- highest grade time attending?** time attend?*** PROBE: hold? (NAME) during during the Has IF YES: completed at that the previous (NAME)'s What is level?*** (2004 - school birth ever his name? 2005) year, been regis- RECORD school that is, tered with FATHER'S year? (2003 - the civil LINE 2004) ? authority? NUMBER** **** BIRTH REGIS- TRATION IF AGE 0-4IF AGE 3 YEARS OR OLDERIF AGE 0-17 YEARS EDUCATIONVORSHIP AND RESIDENCE BIOLOGICAL PARENTS IF AGE 3-24 YEARS A O I DK Y N DK A O I DK YES NO LEVEL GRADE YES NO LEVEL GRADE YES NO LEVEL GRADE C R N DK 1 2 3 8 1 2 8 1 2 3 8 09 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 NO . . . .'00 GO TO 20 GO TO 18 GO TO 20 1 2 3 8 1 2 8 1 2 3 8 10 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 11 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 12 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 13 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 14 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 15 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 1 2 3 8 1 2 8 1 2 3 8 16 1 2 1 2 1 2 1 2 3 8 GO TO 14 GO TO 14 GO TO 20 GO TO 18 GO TO 20 NO . . . .'00 *** CODES FOR Qs 11A AND 13A A = ABROAD O = OTHER HH I = INSTITUTION Just to make sure that I have a complete household listing: DK = DON'T KNOW 1) Are there any other persons such as small children or infants that we have ENTER EACH not listed? YES IN TABLE NO 2) Are there any other people who may not be members of your family, ENTER EACH such as domestic servants, lodgers or friends who usually live here? YES IN TABLE NO 3) Are there any guests or temporary visitors staying here, or anyone else who ENTER EACH slept here last night, who have not been listed? YES IN TABLE NO (16) (17) (20)(13) (14) (15) (18) (19)(12)(11A) (13A) 263Appendix E | 20 A N ow p le as e te ll m e if th er e is a ny on e w ho u se d to b e a m em be r o f t hi s ho us eh ol d an d no w re si de s ou ts id e of M ol do va ? Y E S N O N S K IP T O 2 0K If ye s, h ow m an y ? R E LA TI O N S H IP S E X C U R R E N T C O U N TR Y A G E Y E A R F IR S T LE FT R E A S O N F O R C H IL D R E N O F E M IG R A N T C H IL D R E N O F E M IG R A N T TO H H H E A D O F R E S ID E N C E LE A V IN G M O LD O V A IN H H E LS E W H E R E IN M O LD O V A P le as e lis t t he fi rs t W ha t i s th e Is [N A M E ] In w ha t c ou nt ry d oe s H ow o ld is In w ha t y ea r d id N A M E W ha t w as h is /h er D oe s [N A M E ] h av e an y na tu ra l D oe s [N A M E ] h av e an y (o th er ) na m es o f t he p er so ns re la tio ns hi p of m al e or [N A M E ] l iv e no w ? [N A M E ] fir st le av e M ol do va m ai n m ot iv e fo r f irs t ch ild re n ag e 0- 17 w ho li ve in na tu ra l c hi ld re n ag e 0- 17 w ho w ho u se d to re si de in [N A M E ] t o he ad fe m al e? no w ? to re si de in a no th er le av in g th e co un try ? th is h ou se ho ld ? liv e in M ol do va , b ut n ot in th is th is h ou se ho ld w h o of H H ? * co un try ? ho us eh ol d? ar e no w li vi ng in IF Y E S , an ot he r c ou nt ry . LI S T LI N E N O s O F C H IL D R E N IF Y E S , A S K : A G E 0 -1 7. H ow m an y of h is /h er c hi ld re n liv e in M ol do va ? 01 M F IN Y E A R S Y E A R W O R K . . . . . . . . . . . . . . . 1 Y E S . . . . . . . . . . . . . . . . . . . . 1 N O C H IL D R E N E LS E W H E R E S TU D Y . . . . . . . . . . . . . . . 2 LI N E N O s. IN M O LD O V A 1 1 2 A C C O M .S P O U S E /F A M IL Y 3 M A R R Y F O R E IG N . . . . . . 4 C H IL D R E N E LS E W H E R E 2 O TH E R IN M O LD O V A 6 N R . (S P E C IF Y ) D O N 'T K N O W . . . . . . . . . . 8 N O C H IL D R E N IN H H . . . . . . 2 D O N 'T K N O W. . . . . . . . . . . . 8 IN Y E A R S Y E A R W O R K . . . . . . . . . . . . . . . 1 Y E S . . . . . . . . . . . . . . . . . . . . 1 N O C H IL D R E N E LS E W H E R E 02 M F S TU D Y . . . . . . . . . . . . . . . 2 LI N E N O s. IN M O LD O V A 1 A C C O M .S P O U S E /F A M IL Y 3 1 2 M A R R Y F O R E IG N . . . . . . 4 C H IL D R E N E LS E W H E R E 2 O TH E R IN M O LD O V A 6 N R . (S P E C IF Y ) D O N 'T K N O W . . . . . . . . . . 8 N O C H IL D R E N IN H H . . . . . . 2 D O N 'T K N O W. . . . . . . . . . . . 8 IN Y E A R S Y E A R W O R K . . . . . . . . . . . . . . . 1 Y E S . . . . . . . . . . . . . . . . . . . . 1 N O C H IL D R E N E LS E W H E R E 03 M F S TU D Y . . . . . . . . . . . . . . . 2 LI N E N O s. IN M O LD O V A 1 A C C O M .S P O U S E /F A M IL Y 3 1 2 M A R R Y F O R E IG N . . . . . . 4 C H IL D R E N E LS E W H E R E 2 O TH E R IN M O LD O V A 6 N R . (S P E C IF Y ) D O N 'T K N O W . . . . . . . . . . 8 N O C H IL D R E N IN H H . . . . . . 2 D O N 'T K N O W. . . . . . . . . . . . 8 * S E E C O D E S F O R Q . 3 (2 0I ) (2 0J ) (2 0F ) (2 0G ) (2 0H ) (2 0B ) (2 0C ) (2 0D ) (2 0E ) 264 | Appendix E264 R E LA TI O N S H IP S E X C U R R E N T C O U N TR Y A G E Y E A R F IR S T LE FT R E A S O N F O R C H IL D R E N O F E M IG R A N T C H IL D R E N O F E M IG R A N T TO H H H E A D O F R E S ID E N C E LE A V IN G M O LD O V A IN H H E LS E W H E R E IN M O LD O V A P le as e lis t t he fi rs t W ha t i s th e Is [N A M E ] In w ha t c ou nt ry d oe s H ow o ld is In w ha t y ea r d id N A M E W ha t w as h is /h er D oe s [N A M E ] h av e an y na tu ra l D oe s [N A M E ] h av e an y (o th er ) na m es o f t he p er so ns re la tio ns hi p of m al e or [N A M E ] l iv e no w ? [N A M E ] fir st le av e M ol do va m ai n m ot iv e fo r f irs t ch ild re n ag e 0- 17 w ho li ve in na tu ra l c hi ld re n ag e 0- 17 w ho w ho u se d to re si de in [N A M E ] t o he ad fe m al e? no w ? to re si de in a no th er le av in g th e co un try ? th is h ou se ho ld ? liv e in M ol do va , b ut n ot in th is th is h ou se ho ld w h o of H H ? * co un try ? ho us eh ol d? ar e no w li vi ng in IF Y E S , an ot he r c ou nt ry . LI S T LI N E N O s O F C H IL D R E N IF Y E S , A S K : A G E 0 -1 7. H ow m an y of h is /h er c hi ld re n liv e in M ol do va ? 04 M F IN Y E A R S Y E A R W O R K . . . . . . . . . . . . . . . 1 Y E S . . . . . . . . . . . . . . . . . . . . 1 N O C H IL D R E N E LS E W H E R E S TU D Y . . . . . . . . . . . . . . . 2 LI N E N O s. IN M O LD O V A 1 1 2 A C C O M .S P O U S E /F A M IL Y 3 M A R R Y F O R E IG N . . . . . . 4 C H IL D R E N E LS E W H E R E 2 O TH E R IN M O LD O V A 6 N R . (S P E C IF Y ) D O N 'T K N O W . . . . . . . . . . 8 N O C H IL D R E N IN H H . . . . . . 2 D O N 'T K N O W. . . . . . . . . . . . 8 IN Y E A R S Y E A R W O R K . . . . . . . . . . . . . . . 1 Y E S . . . . . . . . . . . . . . . . . . . . 1 N O C H IL D R E N E LS E W H E R E 05 M F S TU D Y . . . . . . . . . . . . . . . 2 LI N E N O s. IN M O LD O V A 1 A C C O M .S P O U S E /F A M IL Y 3 1 2 M A R R Y F O R E IG N . . . . . . 4 C H IL D R E N E LS E W H E R E 2 O TH E R IN M O LD O V A 6 N R . (S P E C IF Y ) D O N 'T K N O W . . . . . . . . . . 8 N O C H IL D R E N IN H H . . . . . . 2 D O N 'T K N O W. . . . . . . . . . . . 8 IN Y E A R S Y E A R W O R K . . . . . . . . . . . . . . . 1 Y E S . . . . . . . . . . . . . . . . . . . . 1 N O C H IL D R E N E LS E W H E R E 06 M F S TU D Y . . . . . . . . . . . . . . . 2 LI N E N O s. IN M O LD O V A 1 A C C O M .S P O U S E /F A M IL Y 3 1 2 M A R R Y F O R E IG N . . . . . . 4 C H IL D R E N E LS E W H E R E 2 O TH E R IN M O LD O V A 6 N R . (S P E C IF Y ) D O N 'T K N O W . . . . . . . . . . 8 N O C H IL D R E N IN H H . . . . . . 2 D O N 'T K N O W. . . . . . . . . . . . 8 * S E E C O D E S F O R Q . 3 TI C K H E R E IF C O N TI N U A TI O N S H E E T U S E D (2 0J ) (2 0F ) (2 0G ) (2 0H ) (2 0I ) (2 0B ) (2 0C ) (2 0D ) (2 0E ) 265Appendix E | NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 20K Now I would like to talk to you about the water you drink. YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 21 In the last year, have you been able to obtain sufficient quantities of NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 potable water? 20L For what reasons have you not been able to obtain sufficient WATER SOURCE TOO FAR . . . . . . . . 1 potable water? COSTS TOO MUCH . . . . . . . . . . . . 2 LIMITED QUANTITY AVAILABLE/ WATER RATIONED . . . . . . . . . . . . 3 DROUGHT . . . . . . . . . . . . . . . . . . . 4 OTHER . . . . . . . . . . . . . . . . . . . 6 21 What is the main source of drinking water for members of your PIPED WATER household? PIPED INTO DWELLING . . . . . . . . 11 PIPED TO YARD/PLOT . . . . . . . . 12 26 PUBLIC TAP/STANDPIPE . . . . . . 13 ARTESIAN/TUBE WELL OR BOREHOLE 21 DUG WELL PROTECTED WELL . . . . . . . . . . 31 23 UNPROTECTED WELL . . . . . . . . 32 WATER FROM SPRING PROTECTED SPRING . . . . . . . . 41 UNPROTECTED SPRING . . . . . . 42 RAINWATER . . . . . . . . . . . . . . . . . . . 51 TANKER TRUCK . . . . . . . . . . . . . . . . . 61 CISTERN 62 CART WITH SMALL TANK . . . . . . . . 71 26 SURFACE WATER (RIVER/DAM/ LAKE/POND/STREAM/CANAL/ IRRIGATION CHANNEL) . . . . . . 81 BOTTLED WATER . . . . . . . . . . . . . . 91 OTHER _______________________ 96 23 (SPECIFY) 22 What is the main source of water used by your household for PIPED WATER other purposes such as cooking and handwashing? PIPED INTO DWELLING . . . . . . . . 11 PIPED TO YARD/PLOT . . . . . . . . 12 26 PUBLIC TAP/STANDPIPE . . . . . . 13 TUBE WELL OR BOREHOLE . . . . . . 21 DUG WELL PROTECTED WELL . . . . . . . . . . 31 UNPROTECTED WELL . . . . . . . . 32 WATER FROM SPRING PROTECTED SPRING . . . . . . . . 41 UNPROTECTED SPRING . . . . . . 42 RAINWATER . . . . . . . . . . . . . . . . . . . 51 26 TANKER TRUCK . . . . . . . . . . . . . . . . . 61 CISTERN 62 CART WITH SMALL TANK . . . . . . . . 71 SURFACE WATER (RIVER/DAM/ LAKE/POND/STREAM/CANAL/ IRRIGATION CHANNEL) . . . . . . 81 OTHER _______________________ 96 (SPECIFY) 23 Where is that water source located? IN OWN DWELLING . . . . . . . . . . . . . . 1 IN OWN YARD/PLOT . . . . . . . . . . . . . . 2 ELSEWHERE . . . . . . . . . . . . . . . . . . . . . 3 26 Do you treat your water in any way to make it safer to drink? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . . . . . . . . . . . . . . . . . 8 28 266 | Appendix E266 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 27 What do you usually do to the water to make it safer to drink? BOIL . . . . . . . . . . . . . . . . . . . . . . . . . . . A ADD BLEACH/CHLORINE . . . . . . . . . . B Anything else? STRAIN THROUGH A CLOTH . . . . . . . . C USE WATER FILTER (CERAMIC/ RECORD ALL MENTIONED. SAND/COMPOSITE/ETC.) . . . . . . . . D SOLAR DISINFECTION . . . . . . . . . . . . E LET IT STAND AND SETTLE . . . . . . . . F OTHER _______________________ X (SPECIFY) DON'T KNOW . . . . . . . . . . . . . . . . . . . . . Z 28 What kind of toilet facility do members of your household usually FLUSH OR POUR FLUSH TOILET use? FLUSH TO PIPED SEWER SYSTEM . . . . . . . . . . . . . . . . . . . 11 FLUSH TO SEPTIC TANK . . . . . . 12 FLUSH TO PIT LATRINE . . . . . . . . 13 FLUSH TO SOMEWHERE ELSE . 14 FLUSH, DON'T KNOW WHERE . 15 PIT LATRINE VENTILATED IMPROVED PIT LATRINE (VIP) . . . . . . . . . . 21 PIT LATRINE WITH SLAB 22 PIT LATRINE WITHOUT SLAB/ OPEN PIT 23 COMPOSTING TOILET . . . . . . . . . . 31 BUCKET TOILET . . . . . . . . . . . . . . . . . 41 31 OTHER _______________________ 96 (SPECIFY) 29 Do you share this toilet facility with other households? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 31 30 How many households use this toilet facility? NO. OF HOUSEHOLDS IF LESS THAN 10 . . . . . . . . 10 OR MORE HOUSEHOLDS . . . 95 DON'T KNOW . . . . . . . . . . . . . . . . . . . 98 31 Does your household have: YES NO Electricity? ELECTRICITY . . . . . . . . . . . . . . 1 2 A radio? RADIO . . . . . . . . . . . . . . . . . . . . . 1 2 A black-white television? BLACK-WHITE TV . . . . . . . . . . . 1 2 A color TV? COLOR TV . . . . . . . . . . . . . . 1 2 A VCR/DVD? VCR/DVD. . . . . . . . . . . . . . . . . . . 1 2 A mobile telephone? MOBILE TELEPHON. . . . . . . . . . 1 2 A non-mobile telephone? NON-MOBILE TELEPH. . . . . . . . 1 2 A refrigerator? REFRIGERATO. . . . . . . . . . . . . . 1 2 A sofa? SOFA . . . . . . . . . . . . . . . . . . . . . 1 2 An armoire? ARMOIRE. . . . . . . . . . . . . . . . . . . 1 2 A washing machine? WASHING MACH . . . . . . . . . . . . 1 2 A water heater? WATER HEATE. . . . . . . . . . . . . . 1 2 A bathtub or shower? BATHTUB/SHOW. . . . . . . . . . . . 1 2 A vacuum cleaner? VACUUM CLEAN . . . . . . . . . . . . 1 2 A microwave? MICROWAV. . . . . . . . . . . . . . . . . 1 2 A computer? COMPUTER. . . . . . . . . . . . . . . . . 1 2 32 What type of fuel does your household mainly use for cooking? ELECTRICITY . . . . . . . . . . . . . . . . . . . 01 PROPANE GAS TAN. . . . . . . . . . . . . . 02 NATURAL GAS . . . . . . . . . . . . . . . . . 03 BIOGAS . . . . . . . . . . . . . . . . . . . . . . . 04 34 KEROSENE . . . . . . . . . . . . . . . . . . . . . 05 COAL, LIGNITE . . . . . . . . . . . . . . . . . 06 CHARCOAL . . . . . . . . . . . . . . . . . . . . . 07 WOOD . . . . . . . . . . . . . . . . . . . . . . . 08 STRAW/SHRUBS/GRASS/COAGE D. 09 AGRICULTURAL CROP . . . . . . . . . . 10 ANIMAL DUNG . . . . . . . . . . . . . . . . . 11 OTHER _______________________ 96 34 (SPECIFY) . . . . . . . . . . . . . . . . . 0 267Appendix E | NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 33 In this household, is food cooked on a stove or an open fire? STOVE 1 OPEN FIRE . . . . . . 2 PROBE FOR TYPE. OTHER _________________________ 6 34 (SPECIFY) 33A Does the stove have a chimney or hood? YES . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 34 Is the cooking usually done in the house, in a separate building, IN THE HOUSE . . . . . . . . . . . . . . . . . . . 1 or outdoors? IN A SEPARATE BUILDING . . . . . . . . 2 OUTDOORS . . . . . . . . . . . . . . . . . . . . . 3 36 OTHER _________________________ 6 (SPECIFY) 35 Do you have a separate room which is used as a kitchen? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 36 MAIN MATERIAL ON THE FLOOR. NATURAL FLOOR EARTH/SAND . . . . . . . . . . . . . . . . . 11 RECORD OBSERVATION. RUDIMENTARY FLOOR WOOD PLANKS . . . . . . . . . . . . . . 21 FINISHED FLOOR PARQUET OR POLISHED WOOD . . . . . . . . . . . . . . . . . . . 31 VINYL OR ASPHALT STRIPS . . . 32 CERAMIC TILES . . . . . . . . . . . . . . 33 CEMENT . . . . . . . . . . . . . . . . . . . . . 34 CARPET . . . . . . . . . . . . . . . . . . . . . 35 OTHER _______________________ 96 (SPECIFY) 37 MAIN MATERIAL ON THE ROOF. METAL . . . . . . . . . . . . . . . . . . . . . 31 RECORD OBSERVATION. WOOD . . . . . . . . . . . . . . . . . . . . . 32 CALAMINE/CEMENT FIBER . . . 33 CERAMIC TILES . . . . . . . . . . . . . . 34 CEMENT . . . . . . . . . . . . . . . . . . . . . 35 ROOFING SHINGLES . . . . . . . . . . 36 THATCHED ROO . . . . . . . . . . . . . . 37 OTHER_______________________ 96 (SPECIFY) 38 MAIN MATERIAL OF THE WALLS. CEMENT/CEMENT BLOCKS 31 RECORD OBSERVATION. STONE WITH LIME/CEME. . . . . . 32 BRICKS . . . . . . . . . . . . . . . . . . . . . 33 LUT PRELUCRAT (CA IN SU. . . . . . 34 WOOD PLANKS/SHING. . . . . . . . . . 35 ADOBE WITH SOD 36 OTHER_______________________ 96 (SPECIFY) 40 How many rooms in this household are used for sleeping? ROOMS . . . . . . . . . . . . . . . . . . . 268 | Appendix E268 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 41 Does any member of this household own: YES NO A watch? WATCH . . . . . . . . . . . . . . . . . . . 1 2 A bicycle? BICYCLE . . . . . . . . . . . . . . . . . . . 1 2 A motorcycle or motor scooter? MOTORCYCLE/SCOOTER . . . 1 2 An animal-drawn cart? ANIMAL-DRAWN CART . . . . . . 1 2 A car or truck? CAR/TRUCK . . . . . . . . . . . . . . 1 2 A tractor? TRACTOR. . . . . . . . . . . . . . . . . . . 1 2 42 Does any member of this household own any land YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 that can be used for agriculture? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 44 43 How many hectarces of agricultural land do members of this household own? HECTARES . . . . . . . . . . . . 1 IF MORE OR EQUAL TO 1 HA, RECORD HECTARES ARI . . . . . . . . . . . . . . . . . 2 IF MORE THAN 95 HECTARES, ENTER '95'. IF LESS THAN 1 HA, RECORD ARI DK . . . . . . . . . . . . . . . . . . . . . . . . . . . 998 44 Does this household own any livestock, herds, or farm animals? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 46 45 How many of the following animals does this household own? Cattle/milk cows/bulls? CATTLE, ETC. Horses, donkeys, or mules? HORSES/DONKEYS/MULES Goats/ sheep? GOATS/SHEEP Fowl (ex. Chickens, geese, ducks)? FOWL . . . . . . . . . . . . . . . . . Pigs? PIGS. . . . . . . . . . . . . . . . . . . . . . . Other (ex. Rabbits, guinea pigs) OTHER. . . . . . . . . . . . . . . . . . . . . IF NONE, ENTER '00'. IF MORE THAN 95, ENTER '95'. IF UNKNOWN, ENTER '98'. 46 Does any member of this household have a bank account? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 49 ASK RESPONDENT FOR A TEASPOONFUL OF COOKING SALT. 0 PPM (NO IODINE) . . . . . . . . . . . . . . . . . 1 TEST SALT FOR IODINE. 7 PPM . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 15 PPM . . . . . . . . . . . . . . . . . . . . . . . . . 3 30 PPM . . . . . . . . . . . . . . . . . . . . . . . . . 4 RECORD PPM (PARTS PER MILLION) NO SALT IN HH . . . . . . . . . . . . . . . . . . . 5 SALT NOT TESTED 6 (SPECIFY REASON) 49A What kind of salt do you usually use for daily preparation of food? IODIZED 1 NOT IODIZED 2 DON’T KNOW 8 49B What kind of salt do you usually use for pickling? IODIZED 1 NON-IODIZED 2 DON'T KNOW 8 49C CHECK 49Ⱥ AND 49ȼ: CODE '1' NOT CIRCLED CODE '1' CIRCLED NOR IN 49A NOR IN 49B 49E IN EITHER 49A AND/OR 49B 49D The last time you bought salt, what kind of package was it in, I KG PACKAGE . . . . . . . . . . . . . . . . . . . 1 a box, a bag or by the kilo (no package)? INDUSTRIAL BAG 1-2KG . . . . . . . . . . 2 PRE-PACKAGED SACS BY SELLER . 3 IF BAG, ASK: BY KILOGRAMS . . . . . . . . . . . . . . . . . . . 4 Was it in an industrial bag with a label, or re-packaged in a bag with OTHER . . . . . . . . . . . . . . . . . . . . . . . . . 6 no label? 49E The last time you bought salt, in what quantity did you buy it in? < 1 kg . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 4 - 5 kg . . . . . . . . . . . . . . . . . . . . . . . . . 3 10 - 25 kg . . . . . . . . . . . . . . . . . . . . . . . 4 > 25 kg . . . . . . . . . . . . . . . . . . . . . . . . . 5 49F The last time you bought salt, from where did you buy it? STORE . . . . . . . . . . . . . . . . . . . . . . . . . 1 MARKET . . . . . . . . . . . . . . . . . . . . . . . . . 2 OTHER . . . . . . . . . . . . . . . . . . . . . . . . . 6 269Appendix E | Q. 49G INSTRUCTIONS FOR THE RANDOM SELECTION OF A WOMAN TO WHOM QUESTIONS ON "RELATIONS IN THE HOUSEHOLD" WILL BE ASKED (SECTION 10 OF WOMAN'S Q.). IF THERE IS ONLY ONE ELEGIBLE WOMAN IN THE HOUSEHOLD: In the first line (row) of the table below, write the name, age and line number of the elegible woman (see Column (8) of the Household Schedule) : this woman is selected to be interviewed with questions on Relations in the Household. IF THERE ARE SEVERAL ELEGIBLE WOMEN IN THE HOUSEHOLD: 1. In the table below, write the name, the age and the line number of all elegible women (see Column (8) of the Household Questionnaire), beginning with the oldest and ending with the youngest. 2. Note the last digit of the household structure number recorded on the cover page of the questionnaire and circle that number on the first line of the table below. Descend down this column of this number until you reach the line of the last woman recorded. Circle the number that is at the intersection between the column descended and the line of the last woman recorded. The number you circled (1,2,3 etc.) at this intersection tells you the order of the woman selected for Section 10 of the Women’s Questionnaire (the 1st, 2nd, 3rd, etc…). In the table below, circle the LINE NUMBER of the woman selected. Name of woman Line number from household schedule 1 2 3 4 5 6 7 8 9 0 I I I I I I I I I I I II II I II I II I II I II I III I II III I II III I II III I IV I II III IV I II III IV I II V IV V I II III IV V I II III VI IV V VI I II III IV V VI I VII III IV V VI VII I II III IV V VIII III IV V VI VII VIII I II III IV IX II III IV V VI VII VIII IX I II III IVX IX X Order of woman listed Age of woman V VI VII VIII I II 270 | Appendix E270 WEIGHT, HEIGHT AND HEMOGLOBIN MEASUREMENT CHECK COLUMNS (8) AND (9): RECORD THE LINE NUMBER, NAME AND AGE OF ALL WOMEN AGE 15-49 AND ALL CHILDREN UNDER AGE 6 RESULT 1 MEASURED 2 NOT PRESENT 3 REFUSED 4 TECHN PROB 6 OTHER YEARS . . . . . . . . . . RESULT 1 MEASURED 2 NOT PRESENT 3 REFUSED 4 TECHN PROB 6 OTHER DAY MONTH YEAR LYING STAND. . . 1 2 . . 1 2 . . 1 2 . . 1 2 . . 1 2 . . 1 2 TICK HERE IF CONTINUATION SHEET USED * COPY MONTH AND YEAR FROM 215 IN THE MOTHER'S PREGNANCY HISTORY AND ASK DAY OF BIRTH. FOR CHILDREN NOT INCLUDED IN ANY PREGNANCY HISTORY, ASK DAY, MONTH, AND YEAR. 0 0 0 0 0 COL. (9) UP 0 FROM FROM OR FROM COL. (2) COL. (7) STANDING NO. (KILOGRAMS) (CENTIMETERS) LYING DOWN WEIGHT HEIGHT MEASUREDLINE NAME AGE What is (NAME'S) date of birth?* CHILDREN BORN IN 2000 OR LATER WEIGHT AND HEIGHT MEASUREMENT OF CHILDREN BORN IN 2000 OR LATER (57) COL. (8) UP (50) (51) (52) (53) (54) (55) (56) FROM COL. (2) COL. (7) STANDING FROM FROM OR NO. (KILOGRAMS) (CENTIMETERS) LYING DOWN WOMEN 15-49 WEIGHT AND HEIGHT MEASUREMENT OF WOMEN 15-49 LINE NAME AGE What is (NAME'S) date of birth? WEIGHT HEIGHT MEASURED 271Appendix E | RESULT 1 MEASURED 2 NOT PRESENT 3 REFUSED 4 TECHN PROB 6 OTHER AGE 15-17 AGE 18-49 GRANTED REFUSED YES NO/DK 1 2 1 2 GO TO 60 SIGN NEXT LINE . 1 2 1 2 1 2 GO TO 60 SIGN NEXT LINE . 1 2 1 2 1 2 GO TO 60 SIGN NEXT LINE . 1 2 1 2 1 2 GO TO 60 SIGN NEXT LINE . 1 2 1 2 1 2 GO TO 60 SIGN NEXT LINE . 1 2 RESULT BORN IN MONTH 1 MEASURED OF INTERVIEW 2 NOT PRESENT OR PREVIOUS 3 REFUSED 5 MONTHS 4 TECHN PROB 6 OTHER 1 2 GRANTED REFUSED NEXT 1 2 CHILD SIGN NEXT LINE . 1 2 1 2 NEXT CHILD SIGN NEXT LINE . 1 2 1 2 NEXT CHILD SIGN NEXT LINE . 1 2 1 2 NEXT CHILD SIGN NEXT LINE . 1 2 1 2 NEXT CHILD SIGN NEXT LINE . 1 2 1 2 NEXT CHILD SIGN NEXT LINE . * CONSENT STATEMENT As part of this survey, we are studying anemia among women and children. Anemia is a serious health problem that usually results from poor nutrition, infection, or chronic disease. This survey will assist the government to develop programs to prevent and treat anemia. We request that you (and all children born in 2000 or later) participate in the anemia testing part of this survey and give a few drops of blood from a finger. The test uses disposable sterile instruments that are clean and completely safe. The blood will be analyzed with modern, new equipment and the results of the test will be given to you right after the blood is taken. The results will be kept confidential. Do you have any questions? Now may I ask that you (and NAME OF CHILD[REN]) participate in the anemia test. Now please tell me if you agree to have the test(s) done. SCHEDULE LISTED IN HOUSEHOLD CIRCLE CODE (AND SIGN) RECORD '00' IF NOT LINE NO. OF PARENT/ READ CONSENT STATEMENT TO HEMOGLOBIN RESPONSIBLE ADULT. PARENT/RESPONSIBLE ADULT* LEVEL (G/DL) CHECK COLUMN (53): (61) (62) (63) HEMOGLOBIN MEASUREMENT OF CHILDREN BORN IN 2000 OR LATER (58) (59) (60) SCHEDULE (G/DL) LISTED IN HOUSEHOLD CIRCLE CODE (AND SIGN)** RECORD '00' IF NOT CURRENTLY RESPONSIBLE ADULT. WOMAN/PARENT/RESPONSIBLE ADULT* LEVEL PREGNANT CHECK COLUMN (52): LINE NO. OF PARENT/ READ CONSENT STATEMENT TO HEMOGLOBIN HEMOGLOBIN MEASUREMENT OF WOMEN 15-49 272 | Appendix E272 64 CHECK 61 AND 62: NUMBER OF PERSONS WITH HEMOGLOBIN LEVEL BELOW THE CUTOFF POINT* ONE OR MORE NONE GIVE EACH WOMAN/PARENT/RESPONSIBLE ADULT GIVE EACH WOMAN/PARENT/RESPONSIBLE ADULT RESULT OF HEMOGLOBIN MEASUREMENT AND RESULT OF HEMOGLOBIN MEASUREMENT AND CONTINUE WITH 65.** END INTERVIEW. 65 We detected a low level of hemoglobin in (your blood/the blood of NAME OF CHILD(REN)). This indicates that (you/NAME OF CHILD(REN)) have developed severe anemia, which is a serious health problem. We recommend that you visit a health facility as soon as possible to be examined and obtain proper treatment. GIVE THE ADULT THE REFERENCE FORM FOR ANEMIA AND CONTINUE TO Q. 60. 65A RECORD THE TIME. HOUR . . . . . . . . . . . . . . . . . . . . . MINUTES * The cutoff point is 9 g/dl for pregnant women and 7 g/dl for children and for women who are not pregnant (or who don't know if they are pregnant). ** If more than one woman or child is below the cutoff point, read the statement in Q.65 to each woman who is below the cutoff point and to each parent/responsible adult of a child who is below the cutoff point. . . . . . . . . . . . . . . . . . . . 273Appendix E | MOLDOVA DEMOGRAPHIC AND HEALTH SURVEY 2005 June 1, 2005 WOMAN'S QUESTIONNAIRE MINISTRY OF HEALTH REPUBLIC OF MOLDOVA CENTER FOR PREVENTIVE MEDECINE IDENTIFICATION LOCALITY NAME NAME OF HOUSEHOLD HEAD CLUSTER NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MUNICIPIUL / RAIONUL RESIDENCE (URBAN = 1, RURAL = 2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME AND LINE NUMBER OF WOMAN CHECK TABLE 49G IN HOUSEHOLD QUESTIONNAIRE. IS THIS WOMAN SELECTED FOR QUESTIONS ON "RELATIONS IN THE HOUSEHOLD" (SECTION 10 WOMAN'S Q.)? . . . . . . . . . . . . (YES = 1, NO=2) INTERVIEWER VISITS FINAL VISIT DATE DAY MONTH YEAR INTERVIEWER'S NAME INT. CODE RESULT* RESULT NEXT VISIT: DATE TOTAL NUMBER TIME OF VISITS *RESULT CODES: 1 COMPLETED 4 REFUSED 2 NOT AT HOME 5 PARTLY COMPLETED 7 OTHER 3 POSTPONED 6 INCAPACITATED (SPECIFY) LANGUAGE OF QUESTIONNAIRE: LANGUAGE OF INTERVIEW: LANGUAGE OF RESPONDENT: LANGUAGE CODES: ROMANIAN = 1, RUSSIAN = 2, OTHER (SPECIFY________________________)= 3 TRANSLATOR USED: 1-YES, 2-NO SUPERVISOR FIELD EDITOR NAME NAME DATE DATE EDITOR OFFICE KEYED BY 1 2 3 2 0 0 5 275Appendix E | SECTION 1. RESPONDENT'S BACKGROUND INTRODUCTION AND CONSENT INFORMED CONSENT Hello. My name is _______________________________________ and I am working with the Ministry of Health. 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 if you have any. This information will help the government to plan health services. The survey usually takes about 45 minutes to complete. Whatever information you provide will be kept strictly confidential and will not be shown to other persons. Participation in this survey is voluntary and you can choose not to answer any individual question or all of the questions. However, we hope that you will participate in this survey since your views are important. At this time, do you want to ask me anything about the survey? May I begin the interview now? Signature of interviewer: Date: RESPONDENT AGREES TO BE INTERVIEWED . . . . . . 1 RESPONDENT DOES NOT AGREE TO BE INTERVIEWED . . . 2 END NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 101 RECORD THE TIME. HOUR . . . . . . . . . . . . . . . . . . . . . MINUTES . . . . . . . . . . . . . . . . . . . 102 How long have you been living continuously in (NAME OF CURRENT PLACE OF RESIDENCE)? YEARS . . . . . . . . . . . . . . . . . . . IF LESS THAN ONE YEAR, RECORD '00' YEARS. ALWAYS . . . . . . . . . . . . . . . . . . . . . . . 95 VISITOR . . . . . . . . . . . . . . . . . . . . . . . 96 106 103 Just before you moved here, did you live in a CITY 1 city, a town or the countryside? MINICIPAL 2 COUNTRYSIDE . . . . . . . . . . . . . . . . . . . 3 106 In what month and year were you born? MONTH . . . . . . . . . . . . . . . . . . . DON'T KNOW MONTH . . . . . . . . . . . . 98 YEAR . . . . . . . . . . . . . DON'T KNOW YEAR . . . . . . . . . . . . 9998 107 How old were you at your last birthday? AGE IN COMPLETED YEARS COMPARE AND CORRECT 104 AND/OR 105 IF INCONSISTENT. 108 Have you ever attended school? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 112 109 What is the highest level of school you attended? PRIMARY (GR 1-4) . . . . . . . . . . . . . . . . . 1 GYMNASIUM (GR 5-9) . . . . . . . . . . . . . . 2 LYCEUM/MEDIUM (GR 10-12) . . . . . . . . 3 POLYVALENT/SPT/MESERII . 4 COLLEGE/TECHNICAL . . . . . . . . . . . . 5 INSTIT/UNIV/POST GRAD 6 110 What is the highest grade you completed at that level? GRADE/YEAR . . . . . . . . . . . . . 276 | Appendix E276 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 111 CHECK 109: PRIMARY GRADE 5 OR HIGHER 115 112 Now I would like you to read this sentence to me. CANNOT READ AT ALL . . . . . . . . . . . . 1 ABLE TO READ ONLY PARTS OF SHOW CARD TO RESPONDENT. SENTENCE . . . . . . . . . . . . . . . . . . . . . 2 ABLE TO READ WHOLE SENTENCE 3 IF RESPONDENT CANNOT READ WHOLE SENTENCE, PROBE: NO CARD WITH REQUIRED Can you read any part of the sentence to me? LANGUAGE 4 (SPECIFY LANGUAGE) BLIND/VISUALLY IMPAIRED . . . . . . . 5 114 CHECK 112: CODE '2', '3' CODE '1' OR '5' OR '4' CIRCLED 116 CIRCLED 115 Do you read a newspaper or magazine almost every day, at least ALMOST EVERY DAY . . . . . . . . . . . . . . 1 once a week, less than once a week or not at all? AT LEAST ONCE A WEEK . . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . . 4 116 115A Which language(s) do you read most easily? ROMANIAN / LATIN CHARAC. . . . . . . . . 1 ROMANIAN / CYRILLIC CHARAC. . . . 2 RUSSIAN . . . . . . . . . . . . . . . . . . . . . . . . . . 3 READ BOTH ROMANIAN . . . . . . . . . . . . AND RUSSIAN EQUALLY WELL . . . 4 OTHER 6 (SPECIFY) 116 Do you listen to the radio almost every day, at least once a week, ALMOST EVERY DAY . . . . . . . . . . . . . . 1 less than once a week or not at all? AT LEAST ONCE A WEEK . . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . . 4 117 Do you watch television almost every day, at least once a week, ALMOST EVERY DAY . . . . . . . . . . . . . . 1 less than once a week or not at all? AT LEAST ONCE A WEEK . . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . . 4 118 What is your religion? ORTHODOX . . . . . . . . . . . . . . . . . . . . . 1 CATHOLIC/GREEK CATH. 2 PROTESTANT (EX. EVANGELICAL, BAPTIST, JEHOVAH WITNESS) 3 JEWISH 4 NO RELIGION . . . . . . . . . . . . . . . . . . . . . 5 OTHER 6 (SPECIFY) REFUSED TO ANSWER/DK . . . . . . . . . 8 119 What is your ethnic background? MOLDOVAN . . . . . . . . . . . . . . . . . . . . . . . 01 ROMANIAN . . . . . . . . . . . . . . . . . . . . . . . 02 UKRAINIAN . . . . . . . . . . . . . . . . . . . . . . . 03 RECORD MAJOR ETHNIC GROUP RUSSIAN . . . . . . . . . . . . . . . . . . . . . . . . . . 04 GAGAUZAN . . . . . . . . . . . . . . . . . . . . . . . 05 ROMA (GYPSY) . . . . . . . . . . . . . . . . . . . 06 BULGARIAN . . . . . . . . . . . . . . . . . . . . . . . 07 JEWISH . . . . . . . . . . . . . . . . . . . . . . . . . . 08 OTHER 96 (SPECIFY) REFUSED/NOT STATED . . . . . . . . . . 98 277Appendix E | 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 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 your life. Have you ever given birth? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 206 202 Do you have any sons or daughters to whom you have given YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 birth who are now living with you? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 204 203 How many sons live with you? SONS AT HOME . . . . . . . . . . . . And how many daughters live with you? DAUGHTERS AT HOME . . . . . IF NONE, RECORD '00'. 204 Do you have any sons or daughters to whom you have given YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 birth who are alive but do not live with you? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 206 205 How many sons are alive but do not live with you? SONS ELSEWHERE . . . . . . . . And how many daughters are alive but do not live with you? DAUGHTERS ELSEWHERE . IF NONE, RECORD '00'. 206 Have you ever given birth to a boy or girl who was born alive but later died? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 IF NO, PROBE: Any baby who cried or showed signs of life but NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 208 did not survive? 207 How many boys have died? BOYS DEAD . . . . . . . . . . . . . . And how many girls have died? GIRLS DEAD . . . . . . . . . . . . . . IF NONE, RECORD '00'. 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. 209A Women sometimes have pregnancies which do not end in a live born child. That is, a pregnancy can be ended early by an abortion, a miscarriage, or a stillbirth. I will now ask you about each of them separately. How many abortions have you had? IF NONE, RECORD '00' 209B How many miscarriages? IF NONE, RECORD '00' 209C How many stillbirths? IF NONE, RECORD '00' 209D SUM ANSWERS TO 208, 209A, 209B, 209C, AND ENTER TOTAL. IF NO PREGNANCIES, RECORD '00'. TOTAL . . . . . . . . . . . . . . . . . . . . 210 CHECK 209D: ONE OR MORE NO PREGNANCIES PREGNANCIES 226 TOTAL ABORTIONS TOTAL STILLBIRTHS TOTAL MISCARRIAGES 278 | Appendix E278 21 1 P R E G N A N C Y H IS T O R Y . N ow I w an tt o ta lk a bo ut e ac h of y ou r pr eg na nc ie s, in cl ud in g th os e w hi ch e nd ed in a li ve bi rt h, a n in du ce d ab or tio n, a m is ca rr ia ge , a nd a s til lb irt h S ta rt in g w ith y ou r la st p re gn an cy , p le as e te ll m e th e fo llo w in g in fo rm at io n IF A LI V E : IF A LI V E : IF A LI V E : IF D IE D : D id th is p re gn an cy In w ha t m on th a nd W as th er e C H E C K 2 12 : W as th is W ha t n am e w as Is ( N A M E ) Is ( N A M E ) H ow o ld Is ( N A M E ) R E C O R D H ow o ld w as ( N A M E ) en d in a li ve b irt h, a n ye ar ( w as th is c hi ld an y ot he r a si ng le o r gi ve n to th is a bo y or st ill a liv e? w as liv in g w ith H O U S E H O LD w he n he /s he d ie d? in du ce d ab or tio n, a bo rn / di d th is pr eg na nc y R E C O R D S A M E a m ul tip le ch ild ? gi rl? (N A M E ) yo u? LI N E N 0. se lf- in du ce d ab or tio n, pr eg na nc y en d? ) be tw ee n R E S P O N S E bi rt h? on h is /h er O F C H IL D . IF '1 Y R ', P R O B E : a m is ca rr ia ge , th is o ne a nd la st H ow m an y m on th s ol d or a s til lb irt h? th e pr eg na nc y bi rt hd ay ? w as ( N A M E )? yo u ju st R E C O R D D A Y S IF m en tio ne d? R E C O R D LE S S T H A N 1 A G E IN R E C O R D '0 0' M O N T H ; M O N T H S IF IF Y E S , A D D C O M P LT IF C H IL D N O T LE S S T H A N T W O IT T O T A B LE Y E A R S LI S T E D IN Y E A R S ; O R Y E A R S . H O U S E H O LD 01 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 02 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 03 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 04 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 05 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 22 2A 22 0 21 8 22 2 21 9 21 5 21 6 21 7 22 1 21 2 21 4 21 3 279Appendix E | IF A LI V E : IF A LI V E : IF A LI V E : IF D IE D : D id th is p re gn an cy In w ha t m on th a nd W as th er e C H E C K 2 12 : W as th is W ha t n am e w as Is ( N A M E ) Is ( N A M E ) H ow o ld Is ( N A M E ) R E C O R D H ow o ld w as ( N A M E ) en d in a li ve b irt h, a n ye ar ( w as th is c hi ld an y ot he r a si ng le o r gi ve n to th is a bo y or st ill a liv e? w as liv in g w ith H O U S E H O LD w he n he /s he d ie d? in du ce d ab or tio n, a bo rn / di d th is pr eg na nc y R E C O R D S A M E a m ul tip le ch ild ? gi rl? (N A M E ) yo u? LI N E N 0. se lf- in du ce d ab or tio n, pr eg na nc y en d? ) be tw ee n R E S P O N S E bi rt h? on h is /h er O F C H IL D . IF '1 Y R ', P R O B E : a m is ca rr ia ge , th is o ne a nd la st H ow m an y m on th s ol d or a s til lb irt h? th e pr eg na nc y bi rt hd ay ? w as ( N A M E )? yo u ju st R E C O R D D A Y S IF m en tio ne d? LE S S T H A N 1 06 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 07 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 08 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 09 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 10 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 11 Y E S . . . . 1 LI V E B IR T H . . . 1 S IN G 1 N A M E : B O Y 1 Y E S . 1 A G E IN Y E S . . 1 LI N E N O .: D A Y S . . . 1 LI V E B IR T H . . . . 1 M O N T H A B O R T IO N . . . . . 2 Y E A R S : A B O R T IO N . . . . 2 N O . . . . 2 M IS C A R R IA G . . . 3 M U LT 2 G IR L 2 N O . . 2 N O . . . 2 M O N T H S . 2 M IS C A R R IA G. . . . 3 Y E A R S T IL L B IR T . . . . . 4 S T IL L B IR T H . . . . 4 22 2A N E X T Y E A R S . . 3 N E X T P R E G N A C Y P R E G N A N C Y 21 2 21 3 21 4 21 5 21 6 21 7 21 8 21 9 22 0 22 2 22 2A 22 1 280 | Appendix E280 222B Have you had any pregnancies since the the last birth/abortion/miscarriage/still birth? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 IF YES, RECORD PREGNANCIES IN TABLE ABOVE. NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 223 COMPARE 209D WITH TOTAL NUMBER OF LlVE BIRTHS AND TERMINATED PREGNANCIES IN HISTORY ABOVE AND MARK: NUMBERS NUMBERS ARE ARE SAME DIFFERENT (PROBE AND RECONCILE) CHECK: FOR EACH PREGNANCY: YEAR WHEN PREGNANCY ENDED (Q.213) FOR EACH LIVING CHILD: CURRENT AGE IS RECORDED (Qs. 213, 220) FOR EACH CHILD THAT DIED: AGE AT DEATH IS RECORDED (Qs. 219, 222A). FOR AGE AT DEATH 12 MONTHS OR 1 YEAR: PROBE TO DETERMINE EXACT NUMBER OF MONTHS (Q. 222A). 224 CHECK 212 AND 213: ENTER THE NUMBER OF LIVE BIRTHS BORN IN 2000 OR LATER. IF NONE, RECORD '00'. 281Appendix E | 225 FOR EACH BIRTH SINCE JANUARY 2000, ENTER 'B' IN THE MONTH OF BIRTH IN COLUMN 1 OF THE CALENDAR. FOR EACH BIRTH, ASK THE NUMBER OF MONTHS THE PREGNANCY LASTED AND RECORD 'P' IN EACH OF THE PRECEDING MONTHS ACCORDING TO THE DURATION OF PREGNANCY. (NOTE: THE NUMBER OF 'P's MUST BE ONE LESS THAN THE NUMBER OF MONTHS THAT THE PREGNANCY LASTED.) WRITE THE NAME OF THE CHILD TO THE LEFT OF THE 'B' CODE. FOR EACH PREGNANCY TERMINATION (ABORTION, MISCARRIAGE OR STILLBIRTH), ENTER 'T' IN COLUMN 1 OF THE CALENDAR IN THE MONTH THAT THE PREGNANCY TERMINATED, AND 'P' IN EACH OF THE PRECEDING MONTHS ACCORDING TO THE DURATION OF THE PREGNANCY. AS ABOVE, THE NUMBER OF P's MUST BE ONE LESS THAN THE NUMBER OF MONTHS THAT THE PREGNANCY LASTED. 226 Are you pregnant now? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 UNSURE . . . . . . . . . . . . . . . . . . . . . . . . 8 237 227 How many months pregnant are you? MONTHS . . . . . . . . . . . . . . . . . . RECORD NUMBER OF COMPLETED MONTHS. ENTER 'P's IN COLUMN 1 OF CALENDAR, BEGINNING WITH THE MONTH OF INTERVIEW AND FOR THE TOTAL NUMBER OF COMPLETED MONTHS. 228 At the time you became pregnant did you want to become THEN . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 pregnant then, did you want to wait until later, or did you not want LATER . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 to have any (more) children at all? NOT AT ALL . . . . . . . . . . . . . . . . . . . . . . 3 237 When did your last menstrual period start? DAYS AGO . . . . . . . . . . . . 1 WEEKS AGO . . . . . . . . . . 2 MONTHS AGO . . . . . . . . 3 (DATE, IF GIVEN) 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 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 when a woman is more likely to become pregnant if she has NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 sexual relations? DON'T KNOW . . . . . . . . . . . . . . . . . . . . 8 301 239 Is this time just before her period begins, during her period, right JUST BEFORE HER PERIOD after her period has ended, or halfway between two periods? BEGINS . . . . . . . . . . . . . . . . . . . . . . 1 DURING HER PERIOD . . . . . . . . . . . . 2 RIGHT AFTER HER PERIOD HAS ENDED . . . . . . . . . . . . 3 HALFWAY BETWEEN TWO PERIODS . . . . . . . . . . . . . . . . 4 OTHER _______________________ 6 (SPECIFY) DON'T KNOW . . . . . . . . . . . . . . . . . . . . 8 282 | Appendix E282 SECTION 3. CONTRACEPTION 301 Now I would like to talk about family planning - the various ways or methods that a couple 302 Have you ever used can use to delay or avoid a pregnancy. (METHOD)? 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. Which ways or methods have you heard about? FOR METHODS NOT MENTIONED SPONTANEOUSLY, ASK: Have you ever heard of (METHOD)? 01 FEMALE STERILIZATION Women can have an operation to avoid YES . . . . . . . . . . . . . 1 Have you ever had an operation to having any more children. NO . . . . . . . . . . . . . 2 avoid having any more children? YES . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . 2 02 MALE STERILIZATION Men can have an operation to avoid having YES . . . . . . . . . . . . . 1 Have you ever had a partner who had any more children. NO . . . . . . . . . . . . . 2 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 YES . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 04 IUD Women can have a loop or coil placed inside them by a doctor YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 or a nurse. NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 05 INJECTABLES Women can have an injection by a health provide YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 that stops them from becoming pregnant for one or more months. NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 06 IMPLANTS Women can have several small rods placed in their YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 upper arm by a doctor or nurse which can prevent pregnancy fo NO . . . . . . . . . . . . . 2 one or more years. NO . . . . . . . . . . . . . . . . . . 2 07 CONDOM Men can put a rubber sheath on their penis before YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 sexual intercourse. NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 08A DIAPHRAGM Women can place a thin flexible disk in their vagina YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 before intercourse. NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 08B FOAM / JELLY / SPERMICIDE Women can place a suppository, jelly or YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 cream, in their vagina before intercourse. NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 09 LACTATIONAL AMENORRHEA METH Up to 6 months after YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 childbirth, a woman can use a method that requires that she NO . . . . . . . . . . . . . 2 breastfeeds frequently, day and night, and that her menstrual period NO . . . . . . . . . . . . . . . . . . 2 has not returned. 10 RHYTHM METHOD Every month that a woman is sexually active YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 she can avoid pregnancy by not having sexual intercourse on the NO . . . . . . . . . . . . . 2 days of the month she is most likely to get pregnant NO . . . . . . . . . . . . . . . . . . 2 11 WITHDRAWAL Men can be careful and pull out before climax YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 12 EMERGENCY CONTRACEPTION Women can take pills up to five YES . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 days after sexual intercourse to avoid becoming pregnant NO . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 13 Have you heard of any other ways or methods that women or men YES . . . . . . . . . . . . . 1 can use to avoid pregnancy? YES . . . . . . . . . . . . . . . . . . 1 (SPECIFY) NO . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . 1 (SPECIFY) NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . 2 303 CHECK 302: NOT A SINGLE AT LEAST ONE "YES" "YES" 307 (NEVER USED) (EVER USED) 283Appendix E | NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 304 Have you ever used anything or tried in any way to delay or avoid YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 306 getting pregnant? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 305 ENTER '0' IN COLUMN 1 OF CALENDAR IN EACH BLANK MONTH. 331 306 What have you used or done? CORRECT 302 AND 303 (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. NUMBER OF CHILDREN . . . . . How many living children did you have at that time, if any? IF NONE, RECORD '00'. 308 CHECK 302 (01): WOMAN NOT WOMAN STERILIZED STERILIZED 311A 309 CHECK 226: NOT PREGNANT PREGNANT OR UNSURE 322 310 Are you currently doing something or using any method to delay YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 or avoid getting pregnant? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 322 311 Which method are you using? FEMALE STERILIZATION . . . . . . . . . . A MALE STERILIZATION . . . . . . . . . . . . B 316 CIRCLE ALL MENTIONED. PILL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C IUD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D IF MORE THAN ONE METHOD MENTIONED, FOLLOW SKIP INJECTABLES . . . . . . . . . . . . . . . . . . E INSTRUCTION FOR HIGHEST METHOD ON LIST. IMPLANTS . . . . . . . . . . . . . . . . . . . . . . F 315 CONDOM . . . . . . . . . . . . . . . . . . . . . . G 311A CIRCLE 'A' FOR FEMALE STERILIZATION. DIAPHRAGM . . . . . . . . . . . . . . . . . . . . H FOAM/JELLY/S . . . . . . . . . . . . . . . . . . . . I LACTATIONAL AMEN. METHOD . . . . . J RHYTHM METHOD . . . . . . . . . . . . . . . . K WITHDRAWAL . . . . . . . . . . . . . . . . . . L 319A OTHER _______________________ X (SPECIFY) 315 The last time you obtained (CURRENT METHOD IN 311), how COST . . . . . . . . . . LEI much did you pay in total, including the cost of the method and any consultation you may have had? 319A FREE . . . . . . . . . . . . . . . . . . . . . . 995 DON'T KNOW . . . . . . . . . . . . . . . . 998 284 | Appendix E284 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 316 In what facility did the sterilization take place? PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . 11 IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, FAMILY DOCTOR . . . . . 12 WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY FAMILY PLANNING OFFICE . . . . . 13 THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE OTHER PUBLIC 16 CODE. (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . 21 (NAME OF PLACE) PRIVATE DOCTOR'S OFFICE . . . 23 OTHER PRIVATE MEDICAL 26 (SPECIFY) OTHER _______________________ 96 (SPECIFY) DON'T KNOW . . . . . . . . . . . . . . . . . . 98 317 CHECK 311/311A: CODE 'A' CODE 'B' CIRCLED CIRCLED YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Before your sterilization Before the sterilization operation, NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 operation, were you told was your husband/partner told DON'T KNOW . . . . . . . . . . . . . . . . . . . . 8 that you would not be able that he would not be able to to have any (more) children have any (more) children because of the operation? because of the operation? 318 How much did you pay in total for the sterilization, including COST LEI any consultation you may have had? FREE . . . . . . . . . . . . . . . . . . . . . . 9995 DON'T KNOW . . . . . . . . . . . . . . . . 9998 319 In what month and year was the sterilization performed? MONTH . . . . . . . . . . . . . . . . 320 YEAR . . . . . . . . . . 319A In what month and year did you start using (CURRENT MONTH . . . . . . . . . . . . . . . . METHOD) continuously? YEAR . . . . . . . . . . PROBE: Since when have you been using (CURRENT METHOD) now without stopping? 320 CHECK 319/319A AND 213: ANY BIRTH OR PREGNANCY TERMINATION AFTER MONTH AND YES NO YEAR OF START OF USE OF CONTRACEPTION IN 319/319A ? IF YES, GO BACK TO 319/319A, PROBE AND RECORD MONTH AND YEAR AT START OF CONTINUOUS USE OF CURRENT METHOD (MUST BE AFTER LAST BIRTH OR PREGNANCY TERMINATION). 321 CHECK 319/319A: YEAR IS 2000 OR LATER YEAR IS 1999 OR EARLIER ENTER CODE FOR METHOD USED IN MONTH OF ENTER CODE FOR METHOD USED IN MONTH OF INTERVIEW IN COLUMN 1 OF THE CALENDAR AND IN INTERVIEW IN COLUMN 1 OF THE CALENDAR AND EACH MONTH BACK TO THE DATE STARTED USING. EACH MONTH BACK TO JANUARY 2000. ENTER METHOD SOURCE CODE IN COLUMN 2 OF THEN SKIP TO CALENDAR IN MONTH STARTED USING. THEN CONTINUE WITH 322 329 285Appendix E | NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 322 I would like to ask you some questions about the times you or your partner may have used a method to avoid getting pregnant during the last few years. USE CALENDAR TO PROBE FOR EARLIER PERIODS OF USE AND NONUSE, STARTING WITH MOST RECENT USE, BACK TO JANUARY 2000. USE NAMES OF CHILDREN, DATES OF BIRTH, AND PERIODS OF PREGNANCY AS REFERENCE POINTS. IN COLUMN 1, ENTER METHOD USE CODE OR '0' FOR NONUSE IN EACH BLANK MONTH. ILLUSTRATIVE QUESTIONS: COLUMN 1: * When was the last time you used a method? Which method was that? * When did you start using that method? How long after the birth of (NAME)? * How long did you use the method then? IN COLUMN 2, ENTER METHOD SOURCE CODE IN FIRST MONTH OF EACH USE. ILLUSTRATIVE QUESTIONS: COLUMN 2: * Where did you obtain the method when you started using it? * Where did you get advice on how to use the method [for LAM or rhythm]? IN COLUMN 3, ENTER THE CODES FOR THE REASON FOR DISCONTINUATION NEXT TO LAST MONTH OF USE. THE NUMBER OF CODES IN COLUMN 3 MUST BE THE SAME AS THE NUMBER OF INTERRUPTIONS OF METHOD USE IN COLUMN 1. ASK WHY SHE STOPPED USING THE METHOD. IF A PREGNANCY FOLLOWED, ASK WHETHER SHE BECAME PREGNANT UNINTENTIONALLY WHILE USING THE METHOD OR DELIBERATELY STOPPED IN ORDER TO GET PREGNANT. ILLUSTRATIVE QUESTIONS: COLUMN 3: * Why did you stop using the (METHOD)? * Did you become pregnant while using (METHOD), or did you stop using to get pregnant, or did you stop for some other reason? IF DELIBERATELY STOPPED TO BECOME PREGNANT, ASK: * How many months did it take you to get pregnant after you stopped using (METHOD)? AND ENTER '0' IN EACH SUCH MONTH IN COLUMN 1. 323 CHECK 311/311A: NO CODE CIRCLED . . . . . . . . . . . . 00 331 FEMALE STERILIZATION . . . . . . . . 01 CIRCLE METHOD CODE: MALE STERILIZATION . . . . . . . . . . 02 334 PILL . . . . . . . . . . . . . . . . . . . . . . . . . . . 03 IF MORE THAN ONE METHOD CODE CIRCLED IN 311/311A, IUD . . . . . . . . . . . . . . . . . . . . . . . . . . . 04 CIRCLE CODE FOR HIGHEST METHOD IN LIST. INJECTABLES . . . . . . . . . . . . . . . . . . 05 IMPLANTS . . . . . . . . . . . . . . . . . . . . 06 CONDOM . . . . . . . . . . . . . . . . . . . . 07 330 DIAPHRAGM . . . . . . . . . . . . . . . . . . 09 FOAM/JELLY . . . . . . . . . . . . . . . . . . 10 327 LACTATIONAL AMEN. METHOD . . . 11 RHYTHM METHOD . . . . . . . . . . . . . . 12 WITHDRAWAL . . . . . . . . . . . . . . . . 13 334 OTHER METHOD . . . . . . . . . . . . . . 96 324 You obtained (CURRENT METHOD) from (SOURCE OF METHOD YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 326 FROM CALENDAR) in (DATE). At that time, were you told about NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 side effects or problems you might have with the method? 325 Were you ever told by a health or family planning worker about YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 side effects or problems you might have with the method? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 327 326 Were you told what to do if you experienced side effects or YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 problems? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 286 | Appendix E286 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 327 CHECK 324: CODE '1' CODE '1' CIRCLED NOT CIRCLED At that time, were you told When you obtained (CURRENT about other methods of family METHOD) from (SOURCE OF planning that you could use? METHOD FROM CALENDAR) in (DATE), were you told about YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 329 other methods of family NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 planning that you could use? 328 Were you ever told by a health or family planning worker about YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 other methods of family planning that you could use? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 329 CHECK 311/311A: FEMALE STERILIZATION . . . . . . . . 01 MALE STERILIZATION . . . . . . . . . . 02 334 CIRCLE METHOD CODE: PILL . . . . . . . . . . . . . . . . . . . . . . . . . . . 03 IUD . . . . . . . . . . . . . . . . . . . . . . . . . . . 04 INJECTABLES . . . . . . . . . . . . . . . . . . 05 IMPLANTS . . . . . . . . . . . . . . . . . . . . 06 CONDOM . . . . . . . . . . . . . . . . . . . . 07 DIAPHRAGM . . . . . . . . . . . . . . . . . . 09 FOAM/JELLY . . . . . . . . . . . . . . . . . . 10 LACTATIONAL AMEN. METHOD . . . 11 RHYTHM METHOD . . . . . . . . . . . . . . 12 WITHDRAWAL . . . . . . . . . . . . . . . . 13 334 OTHER METHOD . . . . . . . . . . . . . . 96 330 Where did you obtain (CURRENT METHOD) the last time? PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . 11 FAMILY DOCTOR . . . . . 12 IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, FAMILY PLANNING OFFICE . . . . . 13 WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE OTHER PUBLIC ________________ 16 TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . 21 (NAME OF PLACE) PHARMACY . . . . . . . . . . . . . . . . . . 22 PRIVATE DOCTOR . . . . . . . . . . . . 23 OTHER PRIVATE 334 MEDICAL 26 (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . . 31 CHURCH . . . . . . . . . . . . . . . . . . . . 32 FRIEND/RELATIVE . . . . . . . . . . . . 33 NGO . . . . . . . . . . . . . . . . . . . . 34 OTHER _______________________ 96 (SPECIFY) 331 Do you know of a place where you can obtain a method of family YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 planning? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 334 287Appendix E | NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 332 Where is that? PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . . . A FAMILY DOCTOR . . . . . . . . B IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, FAMILY PLANNING OFFICE . . . . . . . . C WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE OTHER PUBLIC ________________ D TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . . E (NAME OF PLACE) PHARMACY . . . . . . . . . . . . . . . . . . F PRIVATE DOCTOR . . . . . . . . . . . . . . G OTHER PRIVATE Any other place? MEDICAL H (SPECIFY) RECORD ALL PLACES MENTIONED. OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . . . . I CHURCH . . . . . . . . . . . . . . . . . . . . . . J FRIEND/RELATIVE . . . . . . . . . . . . . . K BAR L NGO M OTHER _________________________ X (SPECIFY) 334 In the last 12 months, have you visited a health facility for care YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 for yourself (or your children)? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 401 335 Did any staff member at the health facility speak to you about YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 family planning methods? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 288 | Appendix E288 SECTION 4. PREGNANCY, POSTNATAL CARE AND NUTRITION 401 CHECK 224: ONE OR MORE NO 550 BIRTHS BIRTHS IN 2000 IN 2000 OR LATER OR LATER 402 ENTER IN THE TABLE THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH BIRTH IN 2000 OR LATER. ASK THE QUESTIONS ABOUT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH. (IF THERE ARE MORE THAN 3 BIRTHS, USE LAST 2 COLUMNS 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 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH LINE NUMBER FROM 212 LINE LINE LINE NUMBER . . . NUMBER . . . NUMBER . . . 404 NAME _________________ NAME ________________ NAME _________________ FROM 217 AND 219 LIVING DEAD LIVING DEAD LIVING DEAD 405 At the time you became pregnant THEN . . . . . . . . . . . . 1 THEN . . . . . . . . . . . . 1 THEN . . . . . . . . . . . . 1 with (NAME), did you want to (SKIP TO 407) (SKIP TO 429) (SKIP TO 429) become pregnant then, did you LATER . . . . . . . . . . . . 2 LATER . . . . . . . . . . . . 2 LATER . . . . . . . . . . . . 2 want to wait until later, or did you not want to have any (more) NOT AT ALL . . . . . . 3 NOT AT ALL . . . . . . 3 NOT AT ALL . . . . . . 3 children at all? (SKIP TO 407) (SKIP TO 429) (SKIP TO 429) 406 How much longer would you have liked to have waited? MONTHS MONTHS MONTHS YEARS YEARS YEARS DON'T KNOW . . . 998 DON'T KNOW . . . 998 DON'T KNOW . . . 998 407 Did you see anyone for antenatal HEALTH PROFESSIONAL care for this pregnancy? OB/GYN DOCTOR A FAMILY DOCTOR B OTHER DOCTOR C IF YES: Whom did you see? DOCTOR SPEC Anyone else? UNKNOWN D NURSE/MEDICAL PROBE FOR THE TYPE OF ASSISTANT E PERSON AND RECORD ALL PERSONS SEEN. OTHER X (SPECIFY) NO ONE . . . . . . . . . . Y (SKIP TO 413E) 1 2 1 2 1 2 289Appendix E | LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 408 Where did you receive antenatal HOME care for this pregnancy? YOUR HOME . . . A OTHER HOME . . . B CIRCLE ALL MENTIONED. PUBLIC SECTOR IF SOURCE IS HOSPITAL, GOVT. HOSPITAL C HEALTH CENTER, OR CLINIC, FAMILY DOC WRITE THE NAME OF THE OFFICE . . . . . . D PLACE. PROBE TO IDENTIFY HEALTH THE TYPE OF SOURCE AND POST . . . . . . . . E CIRCLE THE APPROPRIATE OTHER PUBLIC CODE. F (SPECIFY) (NAME OF PLACE) PRIVATE MED. SECTOR PVT. HOSPITAL/ CLINIC . . . . . . . . G OTHER PRIVATE MED. H (SPECIFY) OTHER X (SPECIFY) 408A How did you get to your last ante- ON FOOT . . . . . . . . 1 natal care visit? DONKEY/HORSE CAR. 2 PUBLIC TRANSPORT 3 PRIVATE VEHICLE . 4 HOME VISIT . . . . . . 5 (SKIP TO 409) 408B How long did it take you to get to your last ante-natal care visit? MINUTES HOURS 409 How many months pregnant were you when you first received MONTHS . . . antenatal care for this pregnancy? DON'T KNOW . . . . . . 98 409A Would you say that seeking RESPONDENT . . . 1 ante-natal care for this pregnancy: HUSBAND/PARTN . 2 was mainly your decision, mainly RESPONDENT AND your husband/partner's decision, HUSB/PART JOINT 3 or did you both decide together? SOMEONE ELSE . 4 JOINTLY . . . . . . . . . . 5 409B During your first prenatal care YES, COMPLT . . . . . . 1 visit, were you provided with YES, NOT a perinatal card? NOT COMPLT . . . 2 NO . . . . . . . . . . . . . . . 3 IF YES, ASK: DK . . . . . . . . . . . . . . . 8 Was the perinatal card filled in? 410 How many times did you receive NUMBER antenatal care during this OF TIMES . pregnancy? DON'T KNOW . . . . . . 98 411 As part of your antenatal care during this pregnancy, were any of the following done at least once? YES NO Were you weighed? WEIGHT . . . 1 2 Was your blood pressure measured? BP . . . . . . . . 1 2 Did you give a urine sample? URINE . . . . . . 1 2 Did you give a blood sample? BLOOD . . . 1 2 Did you have an ultrasound exam? ULTRASOUND 1 2 Were you given iron tablets? IRON TABLT 1 2 Were you given folic acid tablets? FOLIC ACID 1 2 290 | Appendix E290 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 411A During those visits did you receive any information about: YES NO Nutrition NUTRITION 1 2 Smoking during pregnancy SMOKING 1 2 Drinking alcohol during pregnancy ALCOLHOL 1 2 Breastfeeding BREASTFD 1 2 Birth plan in case of emergency EMERG PLAN 1 2 Child spacing/contraception CONTRAC 1 2 Warning signs of preg comlications COMPLICAT 1 2 Postnatal care POSTNATAL 1 2 411B During those visits were you ever YES . . . . . . . . . . . . . . . 1 encouraged to bring a companion NO . . . . . . . . . . . . . . . 2 of your choice to the delivery, for example, your husband/partner, family member, or close friend? 411C Were the costs of your pre- COSTS FULLY natal care covered by some COVERED . . . . . . 1 government or insurance plan? COSTS PARTIAL COVERED . 2 IF YES, did it cover all costs for COSTS NOT prenatal services, or only some COVERED 3 costs? 412 During (any of) your antenatal YES . . . . . . . . . . . . . . . 1 care visit(s), were you told about NO . . . . . . . . . . . . . . . 2 the signs of pregnancy (SKIP TO 413A) complications? DON'T KNOW . . . . . . 8 413 Were you told where to go if you YES . . . . . . . . . . . . . . . 1 had any of these complications? NO . . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . . 8 413A Did you have any of the following complications during your pregnancy? YES NO Risk of miscarriage? MISCARR 1 2 First trimester bleeding? FIRST TRI 1 2 Second trimester bleeding? SECOND TRI 1 2 High blood pressure? HBP 1 2 Diabetes? DIABET 1 2 Heart disease? HEART DIS 1 2 Liver disease? LIVER DIS 1 2 Urinary tract infection? UTI 1 2 Risk of preterm labor? PRETERM 1 2 Rh Izoimmunization? RH IZO 1 2 Anemia ANEMIA 1 2 Other? OTHER 1 2 (SPECIFY) 413B CHECK 413A: HAD PREGNANCY COMPLICATIONS ATLEAST NOT ONE YES ONE YES (SKIP TO 413E) 413C Did you seek care or treatment for YES . . . . . . . . . . . . . . . 1 (this/these) complication(s)? NO . . . . . . . . . . . . . . . 2 (SKIP TO 413E) 413D Were costs of this/these complic- COSTS FULLY ations covered by some govern- COVERED . . . . . . 1 ment or insurance plan? COSTS PARTIAL COVERED . . . . . . 2 IF YES, did it cover all COSTS NOT costs for complications, or COVERED . . . . . . 3 only some costs? 291Appendix E | LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 413E When did you last receive a NEVER 00 tetanus injection? (SKIP TO 421) MONTH . . . DK MONTH . . . . . . . . 98 YEAR DK YEAR . . . . . . . . 9998 413F In total, how many times have you had a tetanus TIMES . . . . . . . . . . injection? IF 7 OR MORE TIMES, DON'T KNOW . . . . 8 RECORD '7'. 413G Have you ever heard of iron YES . . . . . . . . . . . . . . . 1 tablets, or sirop, that women NO . . . . . . . . . . . . . . . 2 are recommended to take? (SKIP TO 422C) 421 During this pregnancy, were you YES,WAS GIVEN . . 1 given or did you buy any iron YES, BOUGHT . . . . 2 tablets or sirop? NO . . . . . . . . . . . . . . . 3 (SKIP TO 422B) SHOW TABLETS. DON'T KNOW . . . . . . 8 422 During the whole pregnancy, for how many days did you take the NUMBER OF iron tablets? DAYS IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE DON'T KNOW . . . 998 NUMBER OF DAYS. 422A Who recommended that you DOCTOR/ take the iron tablets/sirop? MEDICAL ASST . 1 PHARMACIST . . . . . . 2 OTHER . . . . . . . . . . 6 (SPECIFY) 422B Do you think that iron supple- ments: YES NO DK Strengthen bones? 1 2 8 Prevent congential malformations? 1 2 8 Prevent hyper tension? 1 2 8 Prevent anemia? 1 2 8 422C Have you ever heard of folic YES . . . . . . . . . . . . . . . 1 acid? NO . . . . . . . . . . . . . . . 2 (SKIP TO 423) 422D During this pregnancy, were you YES,WAS GIVEN . . 1 given or did you buy any folic YES, BOUGHT . . . . 2 acid tablets? NO . . . . . . . . . . . . . . . 3 (SKIP TO 422H) DON'T KNOW . . . . . . 8 422E Did you take folic acid at any YES . . . . . . . . . . . . . . . 1 time during the first three NO . . . . . . . . . . . . . . . 2 months of your pregnancy? (SKIP TO 422G) 422F Did you take folic acid for YES . . . . . . . . . . . . . . . 1 at least 45 days within the first NO . . . . . . . . . . . . . . . 2 trimester of your pregnacy? DK . . . . . . . . . . . . . . . 8 292 | Appendix E292 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 422G Who recommended that you DOCTOR/ take the folic acid during MEDICAL ASST . 1 pregnancy? PHARMACIST . . . . . . 2 OTHER . . . . . . . . . . 6 (SPECIFY) 422H Do you think that folic acid: YES NO DK Strengthen bones? 1 2 8 Prevent congential malformations? 1 2 8 Prevent hyper tension? 1 2 8 Prevent anemia? 1 2 8 423 During this pregnancy, did you YES . . . . . . . . . . . . . . . 1 have difficulty with your vision NO . . . . . . . . . . . . . . . 2 during daylight? DON'T KNOW . . . . . . 8 424 During this pregnancy, did you YES . . . . . . . . . . . . . . . 1 have a difficulty with vision in the NO . . . . . . . . . . . . . . . 2 evenings? DON'T KNOW . . . . . . 8 429 When (NAME) was born, was VERY LARGE . . . . . . 1 VERY LARGE . . . . . . 1 VERY LARGE . . . . . . 1 he/she very large, larger than LARGER THAN LARGER THAN LARGER THAN average, average, smaller than AVERAGE . . . . . . 2 AVERAGE . . . . . . 2 AVERAGE . . . . . . 2 average, or very small? AVERAGE . . . . . . . . 3 AVERAGE . . . . . . . . 3 AVERAGE . . . . . . . . 3 SMALLER THAN SMALLER THAN SMALLER THAN AVERAGE . . . . . . 4 AVERAGE . . . . . . 4 AVERAGE . . . . . . 4 VERY SMALL . . . . . . 5 VERY SMALL . . . . . . 5 VERY SMALL . . . . . . 5 DON'T KNOW . . . . . . 8 DON'T KNOW . . . . . . 8 DON'T KNOW . . . . . . 8 293Appendix E | LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 430 Was (NAME) weighed at birth? YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 (SKIP TO 432) (SKIP TO 432) (SKIP TO 432) DON'T KNOW . . . . . . 8 DON'T KNOW . . . . . . 8 DON'T KNOW . . . . . . 8 431 How much did (NAME) weigh? KG FROM CARD KG FROM CARD KG FROM CARD RECORD WEIGHT IN . . . KILOGRAMS FROM HEALTH CARD, IF AVAILABLE. KG FROM RECALL KG FROM RECALL KG FROM RECALL . . . DON'T KNOW . 99998 DON'T KNOW . 99998 DON'T KNOW . 99998 432 Who assisted with the delivery DOCTOR . . . . . . . . A DOCTOR . . . . . . . . A DOCTOR . . . . . . . . A of (NAME)? NURSE/MIDWIFE . . . B NURSE/MIDWIFE . . . B NURSE/MIDWIFE . . . B AUXILIARY MIDWIFE C AUXILIARY MIDWIFE C AUXILIARY MIDWIFE C Anyone else? RELATIVE/FRIEND . . D RELATIVE/FRIEND . . D RELATIVE/FRIEND . . D OTHER OTHER OTHER PROBE FOR THE TYPE OF X X X PERSON AND RECORD ALL (SPECIFY) (SPECIFY) (SPECIFY) PERSONS ASSISTING. NO ONE . . . . . . . . . . Y NO ONE . . . . . . . . . . Y NO ONE . . . . . . . . . . Y IF RESPONDENT SAYS NO ONE ASSISTED, PROBE TO DETERMINE WHETHER ANY ADULTS WERE PRESENT AT THE DELIVERY. 432A Did you have a companion such as HUSBAND / the husband/partner a close friend, or relat PARTNER A present during the birth of [NAME]? RELATIVE B CLOSE FRIEND C IF YES: OTHER X Who was present with you? NO COMPANION Y 2 1 2 1 2 1 294 | Appendix E294 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 433 Where did you give birth to HOME HOME HOME (NAME)? YOUR HOME . . . 11 YOUR HOME . . . 11 YOUR HOME . . . 11 (SKIP TO 440) (SKIP TO 441) (SKIP TO 441) IF SOURCE IS HOSPITAL, OTHER HOME . . . 12 OTHER HOME . . . 12 OTHER HOME . . . 12 HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PUBLIC SECTOR PUBLIC SECTOR PUBLIC SECTOR PLACE. PROBE TO IDENTIFY GOVT. HOSPITAL 21 GOVT. HOSPITAL 21 GOVT. HOSPITAL 21 THE TYPE OF SOURCE AND GOVT. HEALTH GOVT. HEALTH GOVT. HEALTH CIRCLE THE APPROPRIATE CENTER . . . . . . 22 CENTER . . . . . . 22 CENTER . . . . . . 22 CODE. GOVT. HEALTH GOVT. HEALTH GOVT. HEALTH POST . . . . . . . . 23 POST . . . . . . . . 23 POST . . . . . . . . 23 OTHER PUBLIC OTHER PUBLIC OTHER PUBLIC (NAME OF PLACE) 26 26 26 (SPECIFY) (SPECIFY) (SPECIFY) PRIVATE MED. SECTOR PRIVATE MED. SECTOR PRIVATE MED. SECTOR PVT. HOSPITAL/ PVT. HOSPITAL/ PVT. HOSPITAL/ CLINIC . . . . . . . . 31 CLINIC . . . . . . . . 31 CLINIC . . . . . . . . 31 OTHER PRIVATE OTHER PRIVATE OTHER PRIVATE MED. 36 MED. 36 MED. 36 (SPECIFY) (SPECIFY) (SPECIFY) OTHER 96 OTHER 96 OTHER 96 (SPECIFY) (SPECIFY) (SPECIFY) (SKIP TO 440) (SKIP TO 441) (SKIP TO 441) 434 How long after (NAME) was delivered did you stay there? HOURS 1 HOURS 1 HOURS 1 DAYS 2 DAYS 2 DAYS 2 IF LESS THAN ONE DAY, RECORD HOURS. WEEKS 3 WEEKS 3 WEEKS 3 IF LESS THAN ONE WEEK, RECORD DAYS. DON'T KNOW . . . 998 DON'T KNOW . . . 998 DON'T KNOW . . . 998 434A Before you were discharged after (NAME) was born did you receive any information about: YES NO a. Self-care such as hygiene, or nutrition? SELF-CARE 1 2 b. When to seek care in the case of danger signs for you or (NAME)? SEEK CARE 1 2 c. Post partum contraception/FP? FP 1 2 d. Breastfeeding? BREASTFD 1 2 e. Immunizations? IMMUNIZ 1 2 435 Was (NAME) delivered by YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 caesarean section? NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 436 Before you were discharged after YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 (NAME) was born, did a health NO . . . . . . . . . . . . . . . 2 (SKIP TO 451) (SKIP TO 451) professional check on your health? (SKIP TO 439) NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 437 How many hours, days or weeks after delivery did the first check HOURS 1 take place? DAYS 2 IF LESS THAN ONE DAY, RECORD HOURS. WEEKS 3 IF LESS THAN ONE WEEK, RECORD DAYS. DON'T KNOW . . . 998 295Appendix E | LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 438 Who checked on your health DOCTOR . . . . . . . . . . 11 at that time? NURSE/MIDWIFE . . . 12 AUXILIARY PROBE FOR MOST QUALIFIED MIDWIFE . . . . . . . . 13 PERSON. OTHER 96 (SPECIFY) (SKIP TO 450) 439 After you were discharged, did a YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 health professional (SKIP TO 442) (SKIP TO 451) (SKIP TO 451) check on your NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 health? (SKIP TO 450) 440 Why didn't you deliver in a health COST TO MUCH . . . A facility? FACILITY NOT OPEN B TOO FAR/ NO PROBE: Any other reason? TRANSPORT . . . C DON'T TRUST RECORD ALL MENTIONED. FACILITY/POOR QUALITY SERV. . D NO FEMALE PROV. AT FACILITY . . . E HUSBAND/FACILITY DID NOT ALLOW . F NOT NECESSARY . G NOT CUSTOMARY . H OTHER (SPECIFY) . X 441 After (NAME) was born, did a YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 health professional check on your NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 health? (SKIP TO 445) 442 How many hours, days or weeks after delivery did the first check HOURS 1 take place? DAYS 2 IF LESS THAN ONE DAY, RECORD HOURS. WEEKS 3 IF LESS THAN ONE WEEK, RECORD DAYS. DON'T KNOW . . . 998 443 Who checked on your health DOCTOR . . . . . . . . . . 11 at that time? NURSE/MIDWIFE . . . 12 AUXILIARY PROBE FOR MOST QUALIFIED MIDWIFE . . . . . . . . 13 PERSON. OTHER 96 (SPECIFY) 444 Where did this first check HOME take place? YOUR HOME . . . 11 OTHER HOME . . . 12 IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, PUBLIC SECTOR WRITE THE NAME OF THE GOVT. HOSPITAL 21 PLACE. PROBE TO IDENTIFY FAMILY THE TYPE OF SOURCE AND DOCTOR . . . . . . 22 CIRCLE THE APPROPRIATE GOVT. HEALTH CODE. POST . . . . . . . . 23 OTHER PUBLIC 26 (NAME OF PLACE) (SPECIFY) PRIVATE MED. SECTOR PVT. HOSPITAL/ CLINIC . . . . . . . . 31 OTHER PRIVATE MED. 36 (SPECIFY) OTHER 96 (SPECIFY) 296 | Appendix E296 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 445 In the two months after (NAME) YES . . . . . . . . . . . . . . . 1 was born, did a health professional NO . . . . . . . . . . . . . . . 2 on the baby's health? (SKIP TO 450) DON'T KNOW . . . . . . 8 446 How many hours, days or weeks after the birth of (NAME) did the HOURS 1 first check take place? DAYS 2 IF LESS THAN ONE DAY, RECORD HOURS. WEEKS 3 IF LESS THAN ONE WEEK, RECORD DAYS. DON'T KNOW . . . 998 447 Who checked on (NAME)'s health DOCTOR . . . . . . . . . . 1 at that time? NURSE/MIDWIFE . . . 2 AUXILIARY PROBE FOR MOST QUALIFIED MIDWIFE . . . . . . . . 3 PERSON. OTHER 6 (SPECIFY) 448 Where did this first check of HOME (NAME) take place? YOUR HOME . . . 11 OTHER HOME . . . 12 IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, PUBLIC SECTOR WRITE THE NAME OF THE GOVT. HOSPITAL 21 PLACE. PROBE TO IDENTIFY FAMILY THE TYPE OF SOURCE AND DOCTOR . . . . . . 22 CIRCLE THE APPROPRIATE GOVT. HEALTH CODE. POST . . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) (NAME OF PLACE) PRIVATE MED. SECTOR PVT. HOSPITAL/ CLINIC . . . . . . . . 31 OTHER PRIVATE MED. 36 (SPECIFY) OTHER 96 (SPECIFY) 450 Has your menstrual period returned YES . . . . . . . . . . . . . . . 1 since the birth of (NAME)? (SKIP TO 452) NO . . . . . . . . . . . . . . . 2 (SKIP TO 452) 451 Did your period return between YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 the birth of (NAME) and your NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 next pregnancy? (SKIP TO 455) (SKIP TO 455) 452 For how many months after the birth of (NAME) did you not have MONTHS . . . MONTHS . . . MONTHS . . . a period? DON'T KNOW . . . . . . 98 DON'T KNOW . . . . . . 98 DON'T KNOW . . . . . . 98 453 CHECK 226: NOT PREGNANT PREG- OR IS RESPONDENT PREGNANT? NANT UNSURE (SKIP TO 455) 454 Have you resumed sexual YES . . . . . . . . . . . . . . . 1 relations since the birth of NO . . . . . . . . . . . . . . . 2 (NAME)? (SKIP TO 456) 455 For how many months after the birth of (NAME) did you not have MONTHS . . . MONTHS . . . MONTHS . . . sexual relations? DON'T KNOW . . . . . . 98 DON'T KNOW . . . . . . 98 DON'T KNOW . . . . . . 98 297Appendix E | LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 456 Did you ever breastfeed (NAME)? YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 (SKIP TO 463) (SKIP TO 463) (SKIP TO 463) 457 How long after birth did you first put (NAME) to the breast? < 1 HOUR . . . . . . 000 < 1 HOUR . . . . . . 000 < 1 HOUR . . . . . . 000 IF LESS THAN 1 HOUR, RECORD ‘00' HOURS. IF LESS THAN 24 HOURS, HOURS 1 HOURS 1 HOURS 1 RECORD HOURS. OTHERWISE, RECORD DAYS. DAYS 2 DAYS 2 DAYS 2 458 In the first three days after YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 delivery, was (NAME) given NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 anything to drink other than (SKIP TO 460) (SKIP TO 460) (SKIP TO 460) breast milk? 459 What was (NAME) given to drink? MILK (OTHER THAN MILK (OTHER THAN MILK (OTHER THAN BREAST MILK ) . A BREAST MILK ) . A BREAST MILK ) . A PLAIN WATER . . . B PLAIN WATER . . . B PLAIN WATER . . . B SUGAR OR GLU- SUGAR OR GLU- SUGAR OR GLU- Anything else? COSE WATER . . . C COSE WATER . . . C COSE WATER . . . C SUGAR-SALT-WATER SUGAR-SALT-WATER SUGAR-SALT-WATER RECORD ALL LIQUIDS SOLUTION . . . . . . D SOLUTION . . . . . . D SOLUTION . . . . . . D MENTIONED. FRUIT JUICE . . . . . . E FRUIT JUICE . . . . . . E FRUIT JUICE . . . . . . E INFANT FORMULA . F INFANT FORMULA . F INFANT FORMULA . F TEA/INFUSIONS . . . G TEA/INFUSIONS . . . G TEA/INFUSIONS . . . G HONEY . . . . . . . . . . H HONEY . . . . . . . . . . H HONEY . . . . . . . . . . H OTHER X OTHER X OTHER X (SPECIFY) (SPECIFY) (SPECIFY) 460 CHECK 404: LIVING DEAD LIVING DEAD LIVING DEAD IS CHILD LIVING? (SKIP TO 462) (SKIP TO 462) (SKIP TO 462) 461 Are you still breastfeeding YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 (NAME)? (SKIP TO 464) (SKIP TO 464) (SKIP TO 464) NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 462 For how many months did you breastfeed (NAME)? MONTHS . . . MONTHS . . . MONTHS . . . DON'T KNOW . . . 98 DON'T KNOW . . . 98 DON'T KNOW . . . 98 463 CHECK 404: LIVING DEAD LIVING DEAD LIVING DEAD IS CHILD LIVING? (GO BACK TO (GO BACK TO (GO BACK TO 405 405 IN NEXT 405 IN NEXT IN NEXT-TO-LAST COLUMN; OR, COLUMN; OR, COLUMN OF NEW IF NO MORE IF NO MORE QUESTIONNAIRE; OR, BIRTHS, GO BIRTHS, GO IF NO MORE (SKIP TO 466) TO 501) (SKIP TO 466) TO 501) (SKIP TO 466) BIRTHS, GO TO 501) 298 | Appendix E298 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH 464 How many times did you breastfeed last night between NUMBER OF sunset and sunrise? NIGHTTIME FEEDINGS . IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. 465 How many times did you breastfeed yesterday during NUMBER OF the daylight hours? DAYLIGHT FEEDINGS . IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. 466 Did (NAME) drink anything from YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . 1 a bottle with a nipple yesterday NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . 2 or last night? DON'T KNOW . . . . . . 8 DON'T KNOW . . . . . . 8 DON'T KNOW . . . . . . 8 467 GO BACK TO 405 IN GO BACK TO 405 IN GO BACK TO 405 IN NEXT COLUMN; OR, IF NEXT COLUMN; OR, IF NEXT-TO-LAST NO MORE BIRTHS, GO NO MORE BIRTHS, GO COLUMN OF NEW TO 501. TO 501. QUESTIONNAIRE; OR, IF NO MORE BIRTHS, GO TO 501. 299Appendix E | SECTION 5. IMMUNIZATION AND HEALTH 501 ENTER IN THE TABLE THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH LIVE BIRTH IN 2000 OR LATER. ASK THE QUESTIONS ABOUT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH. (IF THERE ARE MORE THAN 3 BIRTHS, USE LAST 2 COLUMNS OF ADDITIONAL QUESTIONNAIRES). 502 LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH LINE NUMBER FROM 212 LINE LINE LINE NUMBER . . . . . . . . NUMBER . . . . . . . . NUMBER . . . . . . 503 CHECK 217 NAME NAME NAME AND 219 LIVING DEAD LIVING DEAD LIVING DEAD (GO TO 503 (GO TO 503 (GO TO 503 IN NEXT- IN NEXT COLUMN IN NEXT COLUMN TO-LAST COLUMN OF OR, IF NO MORE OR, IF NO MORE NEW QUESTIONNAIRE, BIRTHS, GO TO 547) BIRTHS, GO TO 547) OR IF NO MORE BIRTHS, GO TO 547) 506 Is (NAME) currently taking iron pills, YES . . . . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . 1 sprinkles with iron, or NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . 2 iron syrup (like this/ DON'T KNOW . . . . . . . . . . 8 DON'T KNOW . . . . . . . . . . 8 DON'T KNOW . . . . . . . . . 8 any of these)? 506A Has (NAME) taken YES . . . . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . 1 any drug for intestinal NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . 2 parasites in the past DON'T KNOW . . . . . . . . . . 8 DON'T KNOW . . . . . . . . . . 8 DON'T KNOW . . . . . . . . . 8 6 months? 507 Do you have a card where (NAME'S) YES, SEEN . . . . . . . . . . . . 1 YES, SEEN . . . . . . . . . . . . 1 YES, SEEN . . . . . . . . . . . . 1 vaccinations are (SKIP TO 509) (SKIP TO 509) (SKIP TO 509) written down? YES, NOT SEEN . . . . . . . . 2 YES, NOT SEEN . . . . . . . . 2 YES, NOT SEEN . . . . . . . . 2 IF YES: (SKIP TO 512) (SKIP TO 512) (SKIP TO 512) May I see it please? NO CARD . . . . . . . . . . . . . 3 NO CARD . . . . . . . . . . . . . 3 NO CARD . . . . . . . . . . . . . 3 508 Did you ever have YES . . . . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . 1 a vaccination (SKIP TO 512) (SKIP TO 512) (SKIP TO 512) card for (NAME)? NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . 2 300 | Appendix E300 509 (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. LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST BIRTH DAY MONTH YEAR DAY MONTH YEAR DAY MONTH YEAR BCG BCG BCG POLIO 1 POLIO 1 POLIO 1 POLIO 2 POLIO 2 POLIO 2 POLIO 3 POLIO 3 POLIO 3 POLIO 4 POLIO 4 POLIO 4 DPT 1 DPT 1 DPT 1 DPT 2 DPT 2 DPT 2 DPT 3 DPT 3 DPT 3 DPT 4 DPT 4 DPT 4 HepB 1 HepB 1 HepB 1 HepB 2 HepB 2 HepB 2 HepB 3 HepB 3 HepB 3 MEASLES MEASLES MEASLES MUMPS MUMPS MUMPS RUBELLA RUBELLA RUBELLA NOTE: Since 2002 in Moldova, vaccines against measles, mumps and rubella are administered in a single combined vaccine. 301Appendix E | NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 512 Please tell me if (NAME) received any of the following vaccinations: 512A A BCG vaccination against YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 tuberculosis, that is, an injection NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 in the arm or shoulder that usually DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 causes a scar? 512B Polio vaccine, that is, drops in the YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 mouth? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 (SKIP TO 512E) (SKIP TO 512E) (SKIP TO 512E) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 512D How many times was the polio NUMBER NUMBER NUMBER vaccine received? OF TIMES . . . . . OF TIMES . . . . . OF TIMES . . . . . 512E A DPT vaccination, that is, an YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 injection given in the thigh or NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 buttocks to protect him/her (SKIP TO 512G) (SKIP TO 512G) (SKIP TO 512G) against tetanus, whooping cough, DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 \ and diptheria? This is sometimes given at the same time as polio drops. 512F How many times was a DPT NUMBER NUMBER NUMBER vaccination received? OF TIMES . . . . . OF TIMES . . . . . OF TIMES . . . . . 512G An HepB vaccination, that is, an YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 injection in the thigh or buttock, NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 to protect against Hepatitis B? (SKIP TO 512I) (SKIP TO 512I) (SKIP TO 512I) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 512H How many times was a HepB NUMBER NUMBER NUMBER vaccination received? OF TIMES . . . . . OF TIMES . . . . . OF TIMES . . . . . 512 I An injection in the arm to prevent MEASLES ONLY . 1 MEASLES ONLY . 1 MEASLES ONLY . 1 measles? YES, MMR COMB . 2 YES, MMR COMB . 2 YES, MMR COMB . 2 (SKIP TO 512L) (SKIP TO 512L) (SKIP TO 512L) NO . . . . . . . . . . . . . . 3 NO . . . . . . . . . . . . . . 3 NO . . . . . . . . . . . . . . 3 IF YES, ASK DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 Was this a single injection to prevent measles, mumps and rubella? 512J An injection to prevent mumps? YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 512 K An injection to prevent rubella? YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 302 | Appendix E302 NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 512L LAST BIRTH RECORD THE NAME AND ADDRESS OF THE HEALTH CENTER OR MEDICAL FACILITY WHERE THE CHILD IMMUNIZATION RECORD IS KEPT. FULL NAME OF CHILD: BIRTHDATE DAY MONTH YEAR NAME AND ADDRESS OF MEDICAL FACILITY: NEXT-TO-LAST BIRTH RECORD THE NAME AND ADDRESS OF THE HEALTH CENTER OR MEDICAL FACILITY WHERE THE CHILD IMMUNIZATION RECORD IS KEPT. FULL NAME OF CHILD: BIRTHDATE DAY MONTH YEAR NAME AND ADDRESS OF MEDICAL FACILITY: SECOND-FROM-LAST BIRTH RECORD THE NAME AND ADDRESS OF THE HEALTH CENTER OR MEDICAL FACILITY WHERE THE CHILD IMMUNIZATION RECORD IS KEPT. FULL NAME OF CHILD: BIRTHDATE DAY MONTH YEAR NAME AND ADDRESS OF MEDICAL FACILITY: AFTER COMPLETION OF THE INTERVIEWS IN THIS HOUSEHOLD GO THE HEALTH CENTER AND COMPLETE THE VACCINATION DATES IN SECTION 11. 303Appendix E | NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 515 Has (NAME) had diarrhea in the YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 last 2 weeks? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 (SKIP TO 530) (SKIP TO 530) (SKIP TO 530) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 516 Was there any blood in the stools? YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 517 Now I would like to know how much MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 (NAME) was given to drink during SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 the diarrhea. Was he/she given ABOUT THE SAME . 3 ABOUT THE SAME . 3 ABOUT THE SAME . 3 less than usual to drink, about MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 the same amount, or more than NOTHING TO DRINK 5 NOTHING TO DRINK 5 NOTHING TO DRINK 5 usual to drink? DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 IF LESS, PROBE: Was he/she given much less than usual to drink or somewhat less? 518 When (NAME) had diarrhea, was MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 he/she given less than usual to SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 eat, about the same amount, more ABOUT THE SAME . 3 ABOUT THE SAME . 3 ABOUT THE SAME . 3 than usual, or nothing to eat? MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 STOPPED FOOD . 5 STOPPED FOOD . 5 STOPPED FOOD . 5 IF LESS, PROBE: Was he/she NEVER GAVE FOOD 6 NEVER GAVE FOOD 6 NEVER GAVE FOOD 6 given much less than usual to DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 eat or somewhat less? 519 Did you seek advice or treatment YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 for the diarrhea from any source? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 (SKIP TO 524) (SKIP TO 524) (SKIP TO 524) 304 | Appendix E304 NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 520 Where did you seek advice or PUBLIC SECTOR PUBLIC SECTOR PUBLIC SECTOR treatment? GOVT HOSPITAL A GOVT HOSPITAL A GOVT HOSPITAL A FAMILY HEALTH FAMILY HEALTH FAMILY HEALTH IF SOURCE IS A HOSPITAL, CENTER . . . . . B CENTER . . . . . B CENTER . . . . . B HEALTH CENTER, OR CLINIC, MEDICAL MEDICAL MEDICAL WRITE THE NAME OF THE CABINET . . . . . C CABINET . . . . . C CABINET . . . . . C PLACE. PROBE TO IDENTIFY OTHER PUBLIC OTHER PUBLIC OTHER PUBLIC THE TYPE OF SOURCE AND D D D CIRCLE THE APPROPRIATE (SPECIFY) (SPECIFY) (SPECIFY) CODE. PRIVATE MEDICAL PRIVATE MEDICAL PRIVATE MEDICAL SECTOR SECTOR SECTOR (NAME OF PLACE) PVT. HOSPITAL/ PVT. HOSPITAL/ PVT. HOSPITAL/ CLINIC . . . . . . . . E CLINIC . . . . . . . . E CLINIC . . . . . . . . E Anywhere else? PHARMACY . . . F PHARMACY . . . F PHARMACY . . . F PVT DOCTOR . . . G PVT DOCTOR . . . G PVT DOCTOR . . . G RECORD ALL PLACES OTHER PRIVATE OTHER PRIVATE OTHER PRIVATE MENTIONED. MED. H MED. H MED. H (SPECIFY) (SPECIFY) (SPECIFY) OTHER SOURCE OTHER SOURCE OTHER SOURCE SHOP . . . . . . . . . . I SHOP . . . . . . . . . . I SHOP . . . . . . . . . . I TRADITIONAL TRADITIONAL TRADITIONAL PRACTITIONER J PRACTITIONER J PRACTITIONER J OTHER X OTHER X OTHER X (SPECIFY) (SPECIFY) (SPECIFY) 521 CHECK 520: TWO OR ONLY TWO OR ONLY TWO OR ONLY MORE ONE MORE ONE MORE ONE CODES CODE CODES CODE CODES CODE CIRCLED CIRCLED CIRCLED CIRCLED CIRCLED CIRCLED (SKIP TO 523) (SKIP TO 523) (SKIP TO 523) 522 Where did you first seek advice or treatment? FIRST PLACE . . . FIRST PLACE . . . FIRST PLACE . . . USE LETTER CODE FROM 520. 523 How many days after the diarrhea began did you first seek advice or treatment for (NAME)? DAYS . . . . . DAYS . . . . . DAYS . . . . . IF THE SAME DAY, RECORD '00'. 524 Does (NAME) still have diarrhea? YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 525 Was he/she given any of the following to drink at any time since he/she started having the diarrhea: YES NO DK YES NO DK YES NO DK a. A fluid made from a special FLUID FROM FLUID FROM FLUID FROM packet called Regidron or Rehidol? ORS PKT 1 2 8 ORS PKT 1 2 8 ORS PKT 1 2 8 b. A pre-packaged ORS liquid? ORS LIQUID 1 2 8 ORS LIQUID 1 2 8 ORS LIQUID 1 2 8 305Appendix E | NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 526 Was anything (else) given to YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 treat the diarrhea? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 (SKIP TO 530) (SKIP TO 530) (SKIP TO 530) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 527 What (else) was given to treat PILL OR SYRUP PILL OR SYRUP PILL OR SYRUP the diarrhea? ANTIBIOTIC . . . . . A ANTIBIOTIC . . . . . A ANTIBIOTIC . . . . . A ANTIMOTILITY . . . B ANTIMOTILITY . . . B ANTIMOTILITY . . . B Anything else? ZINC . . . . . . . . . . C ZINC . . . . . . . . . . C ZINC . . . . . . . . . . C OTHER (NOT ANTI- OTHER (NOT ANTI- OTHER (NOT ANTI- RECORD ALL TREATMENTS BIOTIC, ANTI- BIOTIC, ANTI- BIOTIC, ANTI- GIVEN. MOTILITY, OR MOTILITY, OR MOTILITY, OR ZINC) . . . . . . . . D ZINC) . . . . . . . . D ZINC) . . . . . . . . D UNKNOWN PILL UNKNOWN PILL UNKNOWN PILL OR SYRUP . . . E OR SYRUP . . . E OR SYRUP . . . E INJECTION INJECTION INJECTION ANTIBIOTIC . . . . . F ANTIBIOTIC . . . . . F ANTIBIOTIC . . . . . F NON-ANTIBIOTIC . G NON-ANTIBIOTIC . G NON-ANTIBIOTIC . G UNKNOWN UNKNOWN UNKNOWN INJECTION . . . H INJECTION . . . H INJECTION . . . H (IV) INTRAVENOUS . I (IV) INTRAVENOUS . I (IV) INTRAVENOUS . I HOME REMEDY/ HOME REMEDY/ HOME REMEDY/ HERBAL MED- HERBAL MED- HERBAL MED- ICINE . . . . . . . . . . J ICINE . . . . . . . . . . J ICINE . . . . . . . . . . J OTHER X OTHER X OTHER X (SPECIFY) (SPECIFY) (SPECIFY) 530 Has (NAME) been ill with a fever YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 at any time in the last 2 weeks? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 531 Has (NAME) had an illness with YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 a cough at any time in the NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 last 2 weeks? (SKIP TO 534) (SKIP TO 534) (SKIP TO 534) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 532 When (NAME) had an illness with YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 a cough, did he/she breathe faster NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 than usual with short, rapid breaths (SKIP TO 535) (SKIP TO 535) (SKIP TO 535) or have difficulty breathing? DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 533 When (NAME) had this illness, did CHEST ONLY . . . 1 CHEST ONLY . . . 1 CHEST ONLY . . . 1 he/she have a problem in the chest NOSE ONLY . . . . . 2 NOSE ONLY . . . . . 2 NOSE ONLY . . . . . 2 or a blocked or runny nose? BOTH . . . . . . . . . . . . 3 BOTH . . . . . . . . . . . . 3 BOTH . . . . . . . . . . . . 3 OTHER 6 OTHER 6 OTHER 6 (SPECIFY) (SPECIFY) (SPECIFY) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 (SKIP TO 535) (SKIP TO 535) (SKIP TO 535) 534 CHECK 530: YES NO OR DK YES NO OR DK YES NO OR DK HAD FEVER? (SKIP TO 546) (SKIP TO 546) (SKIP TO 546) 306 | Appendix E306 NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 535 Now I would like to know how much MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 (NAME) was given to drink during SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 the illness with a (fever/cough). ABOUT THE SAME . 3 ABOUT THE SAME . 3 ABOUT THE SAME . 3 Was he/she given less than MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 usual to drink, about the same NOTHING TO DRINK 5 NOTHING TO DRINK 5 NOTHING TO DRINK 5 amount, or more than usual to DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 drink? IF LESS, PROBE: Was he/she given much less than usual to drink or somewhat less? 536 When (NAME) had a (fever/cough), MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 MUCH LESS . . . . . 1 was he/she given less than usual SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 SOMEWHAT LESS . 2 to eat, about the same amount, ABOUT THE SAME . 3 ABOUT THE SAME . 3 ABOUT THE SAME . 3 more than usual, or nothing to eat? MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 MORE . . . . . . . . . . . . 4 STOPPED FOOD . 5 STOPPED FOOD . 5 STOPPED FOOD . 5 IF LESS, PROBE: Was he/she NEVER GAVE FOOD 6 NEVER GAVE FOOD 6 NEVER GAVE FOOD 6 given much less than usual to DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 eat or somewhat less? 537 Did you seek advice or treatment YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 for the illness from any source? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 (SKIP TO 542) (SKIP TO 542) (SKIP TO 542) 538 Where did you seek advice or PUBLIC SECTOR PUBLIC SECTOR PUBLIC SECTOR treatment? GOVT HOSPITAL A GOVT HOSPITAL . A GOVT HOSPITAL . A GOVT HEALTH GOVT HEALTH GOVT HEALTH Anywhere else? CENTER . . . . . B CENTER . . . . . B CENTER . . . . . B GOVT HEALTH GOVT HEALTH GOVT HEALTH RECORD ALL SOURCES POST . . . . . . . . C POST . . . . . . . . C POST . . . . . . . . C MENTIONED. OTHER PUBLIC OTHER PUBLIC OTHER PUBLIC D D D (SPECIFY (SPECIFY (SPECIFY PRIVATE MEDICAL PRIVATE MEDICAL PRIVATE MEDICAL SECTOR SECTOR SECTOR PVT HOSPITAL/ PVT HOSPITAL/ PVT HOSPITAL/ CLINIC . . . . . . . . E CLINIC . . . . . . . . E CLINIC . . . . . . . . E PHARMACY . . . F PHARMACY . . . F PHARMACY . . . F PVT DOCTOR . . . G PVT DOCTOR . . . G PVT DOCTOR . . . G OTHER PRIVATE OTHER PRIVATE OTHER PRIVATE MED. H MED. H MED. H (SPECIFY) (SPECIFY) (SPECIFY) OTHER SOURCE OTHER SOURCE OTHER SOURCE SHOP . . . . . . . . . . I SHOP . . . . . . . . . . I SHOP . . . . . . . . . . I TRADITIONAL TRADITIONAL TRADITIONAL PRACTITIONER J PRACTITIONER J PRACTITIONER J OTHER X OTHER X OTHER X (SPECIFY) (SPECIFY) (SPECIFY) 539 CHECK 538: TWO OR ONLY TWO OR ONLY TWO OR ONLY MORE ONE MORE ONE MORE ONE CODES CODE CODES CODE CODES CODE CIRCLED CIRCLED CIRCLED CIRCLED CIRCLED CIRCLED (SKIP TO 541) (SKIP TO 541) (SKIP TO 541) 307Appendix E | NAME ________________ NAME ________________ NAME __________________ LAST BIRTH NEXT-TO-LAST BIRTH SECOND-FROM-LAST-BIRTH 540 Where did you first seek advice or treatment? FIRST PLACE . . . FIRST PLACE . . . FIRST PLACE . . . USE LETTER CODE FROM 538. 541 How many days after the illness began did you first seek advice or treatment for (NAME)? DAYS . . . . . DAYS . . . . . DAYS . . . . . IF THE SAME DAY, RECORD '00'. 542 Is (NAME) still sick with a (fever/ YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 cough)? NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 543 At any time during the illness, did YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 (NAME) take any drugs for the NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 illness? (SKIP TO 546) (SKIP TO 546) (SKIP TO 546) DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 DON'T KNOW . . . . . 8 544 What drugs did (NAME) take? ANTIBIOTIC ANTIBIOTIC ANTIBIOTIC AMOXICILLINUM / AMOXICILLINUM / AMOXICILLINUM / COTRIMOXAZOL A COTRIMOXAZOL A COTRIMOXAZOL A OTHER ANTI- OTHER ANTI- OTHER ANTI- Any other drugs? BIOTICS . . . . . B BIOTICS . . . . . B BIOTICS . . . . . B RECORD ALL MENTIONED. OTHER DRUGS OTHER DRUGS OTHER DRUGS ASPIRIN . . . . . . . . C ASPIRIN . . . . . . . . C ASPIRIN . . . . . . . . C ACETA- ACETA- ACETA- MINOPHEN . . . D MINOPHEN . . . D MINOPHEN . . . D IBUPROFEN . . . E IBUPROFEN . . . E IBUPROFEN . . . E PARACETAMOL F PARACETAMOL F PARACETAMOL F OTHER X OTHER X OTHER X (SPECIFY) (SPECIFY) (SPECIFY) DON'T KNOW . . . . . Z DON'T KNOW . . . . . Z DON'T KNOW . . . . . Z 544A CHECK 544: YES NO YES NO YES NO ANY ANTIBIOTICS CIRCLED (CODES A-B)? (SKIP TO 546) (SKIP TO 546) (SKIP TO 546) 545 Did you already have (NAME OF ANTIBIOTIC ANTIBIOTIC ANTIBIOTIC DRUG FROM 544) at home when AMOXICILLINUM / AMOXICILLINUM / AMOXICILLINUM / the child became ill? COTRIMOXAZOL A COTRIMOXAZOL A COTRIMOXAZOL A OTHER ANTI- OTHER ANTI- OTHER ANTI- IF YES, CIRCLE CODE FOR BIOTICS . . . . . B BIOTICS . . . . . B BIOTICS . . . . . B THAT DRUG. OTHER DRUGS OTHER DRUGS OTHER DRUGS ASK SEPARATELY FOR EACH ASPIRIN . . . . . . . . C ASPIRIN . . . . . . . . C ASPIRIN . . . . . . . . C ANTIBIOTIC GIVEN IN 544. ACETA- ACETA- ACETA- MINOPHEN . . . D MINOPHEN . . . D MINOPHEN . . . D IBUPROFEN . . . E IBUPROFEN . . . E IBUPROFEN . . . E PARACETAMOL F PARACETAMOL F PARACETAMOL F OTHER X OTHER X OTHER X (SPECIFY) (SPECIFY) (SPECIFY) DON'T KNOW . . . . . Z DON'T KNOW . . . . . Z DON'T KNOW . . . . . Z 546 GO BACK TO 503 IN GO BACK TO 503 IN GO TO 503 IN NEXT COLUMN; OR, IF NEXT COLUMN; OR, IF NEXT-TO-LAST NO MORE BIRTHS, GO NO MORE BIRTHS, GO COLUMN OF NEW TO 547. TO 547. QUESTIONNAIRE; OR, IF NO MORE BIRTHS, GO TO 547. 308 | Appendix E308 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 547 CHECK 213 AND 221, ALL ROWS: NUMBER OF CHILDREN BORN IN 2000 OR LATER AND LIVING WITH THE RESPONDENT ONE OR MORE NONE 550 549 CHECK 525(a) AND 525(b), ALL COLUMNS: NO CHILD ANY CHILD RECEIVED FLUID RECEIVED FLUID 551 FROM ORS PACKET OR FROM ORS PACKET OR PRE-PACKAGED ORS LIQUID (11) PRE-PACKAGED ORS LIQUID (11) 550 Have you ever heard of a special product called Regidrom YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Rehidol, or a pre-packaged ORS liquid you can NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 get for the treatment of diarrhea? 551 Now I would like to ask you some questions about medical care for you yourself. Many different factors can prevent women from getting medical advice or treatment for themselves. When you are sick and BIG NOT A BIG want to get medical advice or treatment, is each of the following PROB- PROB- a big problem or not? LEM LEM Getting permission to go. PERMISSION TO GO . . . 1 2 Getting money needed for treatment. GETTING MONEY . . . . . 1 2 The distance to the health facility. DISTANCE . . . . . . . . . . . . 1 2 Having to take transport. TAKING TRANSPORT . . . 1 2 Not wanting to go alone. GO ALONE . . . . . . . . . . . . 1 2 Concern that there may not be a female health provider. NO FEMALE PROV. . . . 1 2 552 Do you have health insurance? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 554 553 What type of health insurance do you have? HEALTH INSURANCE THROUGH EMPLOYER/EDUCAT INST. . . . . . . A RECORD ALL MENTIONED. SOCIAL SECURITY . . . . . . . . . . . . . . . . B OTHER PRIVATELY PURCHASED COMMERCIAL HEALTH INSURANCE. C OTHER X (SPECIFY) 554 Now I would like to ask you some questions about any injections you have had in the last twelve months. Have you had an injection for any reason in the last twelve months? NUMBER OF INJECTIONS . . . IF YES: How many injections have you had? IF NUMBER OF INJECTIONS IS GREATER THAN 90, NONE 00 558 OR DAILY FOR 3 MONTHS OR MORE, RECORD '90'. IF NON-NUMERIC ANSWER, PROBE TO GET AN ESTIMATE. 555 Among these injections, how many were administered by a doctor, a nurse, a pharmacist, a dentist, or any other NUMBER OF INJECTIONS . . . health worker? IF NUMBER OF INJECTIONS IS GREATER THAN 90, OR DAILY FOR 3 MONTHS OR MORE, RECORD '90'. NONE 00 558 IF NON-NUMERIC ANSWER, PROBE TO GET AN ESTIMATE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309Appendix E | NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 556 The last time you had an injection given to you by a health PUBLIC SECTOR worker, where did you go to get the injection? GOVERNMENT HOSPITAL . . . . . 11 FAMILY HEALTH CENTER . . . . . . . . 12 OTHER PUBLIC 16 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC/ PRIVATE DOCTOR . . . . . . . . . . 21 DENTAL CLINIC/OFFICE . . . .