MONGOLIA - PREVALENCE OF UNDERWEIGHT CHILDREN (UNDER FIVE YEARS OF AGE)

MONGOLIA 4. Prevalence of underweight children (under five years of age) Kachondham Y. Report of a consultancy on the Mongolian Child Nutrition Survey. Institute of Nutrition. Nakompathom, Thailand; 1992 Kachondham Y. Report on the 2nd national child and nutrition survey. Mongolia 1999. Institute of Nutrition and Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Thailand, 2000 Multiple Indicator Cluster Survey 2000 Acronym CNS92 CNS99 MICS00 20 MONGOLIA - PREVALENCE OF UNDERWEIGHT CHILDREN (UNDER FIVE YEARS OF AGE) % of children under 5 15 10 5 0 1985 1990 1995 2000 CNS92 CNS99 MICS00 Observed Line MDG Line CNS92: Children 0-3 years old. CNS99, MICS00: Children 0-4 years old. Percentage of children under five years who are classified as undernourished according to the anthropometric index of nutritional status: weight-for-age. The index is expressed in terms of the number of standard deviation (SD) units from the median of the NCHS/CDC/WHO international reference 1

population. Children are classified as malnourished if their z-scores are below minus two standard deviations (-2 SD) from the median of the reference population. To achieve MDGs (to halve the prevalence of underweight children), 2.8% of annual reduction is needed between 1990-2015, shown as MDG line in the graph. Mongolia s progress, shown as observed line, is slower than MDG line, and it is about 0.3 % of annual increase. Additional indicators: Stunting, Breastfeeding, Vitamin A Prevalence of stunting (height for age <2 Z-scores) in children under 5 (%) % of infants under 6 months who are exclusively breastfed 0-3 months 4-6 months % of children 12-59 months who consumed vitamin A supplements 1992 26.4 1999 24.6 87.0 2000 24.6 64.0 Note: Breastfeeding status refers to 24 hours preceding the survey. Stunting data refers children the same age as underweight. Source: For vitamin A, UNICEF/Nutrition Section survey 2000 For stunting and breastfeeding, the same as underweight 2

13. Under-five mortality rate Acronym 1994 Mongolian Demographic Survey (indirect) MDS94i 1998 Reproductive Health Survey (indirect) RHS98i 1998 Reproductive Health Survey (direct) RHS98d 2000 Multiple Indicator Cluster Survey MICS00i 200 MONGOLIA - UNDER-FIVE MORTALITY Under-five mortality rate (per 1000 births) 180 160 140 120 100 80 60 40 20 0 1960 1970 1980 1990 2000 MDS94i RHS98d RHS98i MICS00i KH line WDI04 MDG Line Direct estimates: Infant and under-five mortality rates are calculated from the data from a sample survey that collects birth histories, with a mother being asked for information on the date of birth and, if relevant, the age at death of every live-born child she has had. However, the collection of such information by surveys is complex and requires high levels of interviewer quality and training. The surveys are therefore quite expensive and can only cover small samples. Indirect estimates: Indirectly, under-five mortality and infant mortality can be calculated by asking each woman surveyed for very simple information: her age, the total number of children she has borne, and the number of those children that have died. Indirect estimates adjust the proportions dead by age group of mother for an estimated exposure distribution in order to arrive at pure measures of under-five mortality and of reference dates for these measures. The information from the younger women gives under-five mortality of more recent years whereas the information from the older women gives under-five mortality of 3

more distant years. The adjustment process assumes certain patterns of fertility and under-five mortality by age (East, North, South, West model life tables), and results can be quite sensitive to the choices made. KH line: The line was estimated by fitting a regression line to the relationship between infant or under 5 mortality rates and their reference dates using weighted least squares. The method of estimation is adopted from the papers: 1) K. Hill, R. Pande and G. Jones, Trends in child mortality in the developing world: 1990 to 1995, UNICEF staff working papers, Evaluation, Policy and Planning Series, UNICEF, New York, 1997. 2) K. Hill et al, Trends in child mortality in the developing world: 1990 to 1996, unpublished report, UNICEF, New York, January 1998. The weights are listed in the table in the last section of this document. WDI04: Estimates used for World Development Indicators 2004. To achieve MDGs (to reduce under five mortality by 2/3), 4.4% of annual reduction is needed between 1990-2025. Mongolia s progress, shown as WDI04 line, is slower than MDG line, and it is about 3.4% of annual reduction between 1990-2002. Additional indicators: Child (aged 1-4) mortality rate by gender Child (aged 1-4) mortality rate (per 1000 births) Survey year Male Female Note: Mortality rates are for the ten-year period preceding the survey Source: 4

14. Infant mortality rate Acronym 1994 Mongolian Demographic Survey (indirect) MDS94i 1994 Mongolian Demographic Survey (direct) MDS94d 1998 Reproductive Health Survey (indirect) RHS98i 1998 Reproductive Health Survey (direct) RHS98d 2000 Multiple Indicator Cluster Survey MICS00i 140 MONGOLIA - INFANT MORTALITY Infant mortality rate (per 1000 births) 120 100 80 60 40 20 0 1960 1970 1980 1990 2000 MDS94i MDS94d RHS98d RHS98i MICS00i KH line WDI04 MDG Line Direct estimates: Infant and under-five mortality rates are calculated from the data from a sample survey that collects birth histories, with a mother being asked for information on the date of birth and, if relevant, the age at death of every live-born child she has had. However, the collection of such information by surveys is complex and requires high levels of interviewer quality and training. The surveys are therefore quite expensive and can only cover small samples. Indirect estimates: Indirectly, under-five mortality and infant mortality can be calculated by asking each woman surveyed for very simple information: her age, the total number of children she has borne, and the number of those children that have died. Indirect estimates adjust the proportions dead by age group of mother for an estimated exposure distribution in order to arrive at pure measures of under-five mortality and of reference dates for these measures. The information from the younger women gives under-five 5

mortality of more recent years whereas the information from the older women gives under-five mortality of more distant years. The adjustment process assumes certain patterns of fertility and under-five mortality by age (East, North, South, West model life tables), and results can be quite sensitive to the choices made. KH line: The line was estimated by fitting a regression line to the relationship between infant or under 5 mortality rates and their reference dates using weighted least squares. The method of estimation is adopted from the papers: 1) K. Hill, R. Pande and G. Jones, Trends in child mortality in the developing world: 1990 to 1995, UNICEF staff working papers, Evaluation, Policy and Planning Series, UNICEF, New York, 1997. 2) K. Hill et al, Trends in child mortality in the developing world: 1990 to 1996, unpublished report, UNICEF, New York, January 1998. The weights are listed in the table in the last section of this document. WDI04: Estimates used for World Development Indicators 2004. To achieve MDGs (to reduce under five mortality by 2/3), 4.4% of annual reduction is needed between 1990-2025. Mongolia s progress, shown as WDI04 line, is slower than MDG line, and it is about 2.4% of annual reduction between 1990-2002. Additional indicators: Infant mortality rate by gender Infant mortality rate (per 1000 births) Survey year Male Female Note: Mortality rates are for the ten-year period preceding the survey Source: 6

15. Proportion of 1-year-old children immunized against measles Reported to WHO by country Reported to UNICEF by country Mongolia, Child and Development survey-2000 (MICS-2), 2001 1999 The graph is taken from WHO web site. http://www.who.int/vaccines-surveillance/whounicef_coverage_review/wucoveragecountrylist.htm Draft WHO/UNICEF estimate: WHO/UNICEF estimates of the most likely coverage for each year and antigen were made based on data from the WHO and UNICEF data bases and information from other sources. WHO and UNICEF consulted with Regional Offices and, where possible, national experts, to seek more in-depth knowledge regarding the functioning of the immunization system. 7

Additional indicators: WHO/UNICEF estimate of immunization coverage, BCG, DPT3, Pol3 Immunization coverage (%) WHO/UNICEF estimate BCG DPT3 Pol3 1985 52 80 86 1986 54 81 86 1987 60 80 86 1988 78 82 87 1989 92 84 87 1990 81 84 87 1991 85 81 78 1992 87 81 79 1993 84 80 79 1994 90 78 77 1995 94 88 86 1996 92 90 90 1997 96 92 93 1998 95 94 94 1999 97 94 94 2000 97 95 94 2001 98 95 95 2002 98 98 98 Source: WHO/UNICEF Review of National Immunization Coverage 1980-2002 http://www.who.int/vaccines-surveillance/whounicef_coverage_review/wucoveragecountrylist.htm 8

16. Maternal mortality ratio Estimate by WHO, UNICEF Estimate by WHO, UNICEF, UNFPA Estimate by WHO, UNICEF, UNFPA Acronym WHO90 WHO95 WHO00 200 MONGOLIA - MATERNAL MORTALITY Maternal Mortality Ratio (per 100,000 live births) 150 100 50 0 1985 1990 1995 2000 WHO90 WHO95 WHO00 WHO90: The WHO-UNICEF estimate. For countries with good death registration but poor or non-existent attribution of cause of death. The model is used to predict the proportion of deaths of women of reproductive age that are maternal. This proportion is then applied to the deaths of women of reproductive age actually registered to obtain the number of maternal deaths and the maternal mortality ratio. Source: Revised 1990 estimates of maternal mortality: a new approach by WHO and UNICEF. WHO95:The estimate is developed using the model. The regression model was used to predict the proportion maternal among deaths of women of reproductive age (PMDF), and the prediction was then applied to an envelope of deaths of females of reproductive age in 1995 to estimate maternal deaths. The maternal mortality ratio was then obtained by dividing the number of maternal deaths by an estimate of the number of births in 1995. In almost all cases, the deaths envelope was obtained from the UN population projections (1998 Revision). Source: Maternal mortality in 1995: Estimates developed by WHO, UNICEF, UNFPA WHO00: The WHO, UNICEF and UNFPA estimate. The method is used for countries with complete vital registration (as classified by the United Nations Statistics Division and WHO. Complete means 90% or more of adult deaths are reported. WHO estimates of the quality of cause of death attribution were used) with good attribution of cause of death. Maternal mortality estimates are based on the observed value adjusted by a nationally reported adjustment factor if available or by 1.5 if not. In order to reduce the problem of stochastic fluctuation due to small numbers, the average value for the most recent three-year period was used as the basis for the adjustment. Source: Maternal mortality in 2000: Estimates developed by WHO, UNICEF and UNFPA 9

17. Proportion of births attended by skilled health personnel Reproductive Health Survey 1998 Multiple Indicator Cluster Survey 2000 Acronym RHS98 MICS00 100 MONGOLIA - % of Births Attended by Skilled Health Personnel % of Births Attended by Skilled Health Personnel 80 60 40 20 0 1985 1990 1995 2000 RHS98 MICS00 The year in the graph indicates the year of the survey. MICS00: Proportion of births in the one year before the survey attended by skilled health personnel. Doctor, nurse/midwife, auxiliary midwife is considered to be skilled health personnel. Additional reproductive health indicators: Fertility rate Adolescent fertility Total fertility rate (per woman) rate (per 1000 women aged 15-19) 1990 4.1 2000 2.5 2000-2005 53 Note: Total fertility rate is average lifetime total of live births per woman at the fertility rates of the year. Adolescent fertility rate is an annual number of live births to girls aged 15-19 per 1,000 girls aged 15-19. Source: UNICEF End-decade Databases 10

18. HIV prevalence among 15-to-24-year-old pregnant women HIV prevalence among 15-to-24-year-old pregnant women (No data) 11

HIV prevalence among pregnant women UNAIDS/WHO Epidemiological Fact Sheet 2002 Update (No data) The graphs are taken from WHO web site. Trends in HIV prevalence among antenatal clinic attendees. The data reported are mainly based on the HIV database maintained by the United States Bureau of the Census where data from different sources, including national reports, scientific publications and international conferences are compiled. Studies conducted in the same year are aggregated and the median prevalence rates are given for each of the categories. The maximum and minimum prevalence rates observed are also provided. The differentiation between the two geographical areas Urban and Rural is not based on strict criteria, such as the number of inhabitants. For most countries, urban areas were considered to be the capital city and where applicable other metropolitan areas with similar socio-economic patterns. The term rural considers that most sentinel sites are not located in strictly rural areas, even if they are located in somewhat rural districts. 12

HIV prevalence among young people 15 to 24 years UNAIDS Report on the global HIV/AIDS epidemic June 2000 1999 UNAIDS Report on the global HIV/AIDS epidemic July 2002 2001 (No data) Regarding the UNAIDS data, the estimated number of young people (15-24) living with HIV/AIDS at the end of the year divided by the population of young people (15-24) of the year. The estimates are expressed as a range generated by regional modeling. 13

19. Contraceptive prevalence rate Any method and modern method Multiple Indicator Cluster Survey 2000 Acronym MICS00 100 MONGOLIA - CONTRACEPTIVE PREVALENCE 80 Contraceptive prevalence (%) 60 40 20 0 1985 1990 1995 2000 MICS00(any) MICS00 (modern) Percentage of women in union aged 15-49 who are using any contraception and modern contraception 14

Condom use rate of the contraceptive prevalence rate Multiple Indicator Cluster Survey 2000 Acronym MICS00 MONGOLIA - CONDOM USE RATE OF THE CONTRACEPTIVE PREVALENCE RATE 20 Condom use rate (%) 15 10 5 0 1985 1990 1995 2000 MICS00 Percentage of women in union aged 15-49 who or whose partner are using male or female condoms for contraception among women in union aged 15-49 who or whose partner are using any method. Simply calculated by: condom use divided by all methods. 15

20. Number of children orphaned by HIV/AIDS Number of orphans (No data) Number of children (aged 0-14) currently living whose mother, father or both parents have died due to AIDS (including those children who lost both parents and those who lost one parent to AIDS and the other parent due to another cause) 16

Ratio of proportion of orphans to non-orphans aged 10 to 14 years who are attending school (No data) The ratio of children (aged 10-14) who lost both parents and are attending school to non-orphaned children the same age who are attending school 17

21. Prevalence and death rates associated with malaria (No data) 18

22. Proportion of population in malaria risk areas using effective malaria prevention and treatment measures Bednet usage Acronym (No data) 19

Bednet treatment Acronym (No data) 20

Malaria treatment Acronym (No data) Percentage of children who received antimalarial medicine, among children who had fever in the last 2 weeks before the survey. 21

23. Prevalence and death rates associated with tuberculosis Prevalence rates WHO TB data submitted to the UN in May 2002 Acronym WHO 500 MONGOLIA - TUBERCULOSIS PREVALENCE Prevalence rate per 100,000 400 300 200 100 0 1985 1990 1995 2000 WHO Rates for tuberculosis prevalence excluding cases attributable to HIV/AIDS. Prevalence of smear-positive disease. 22

Death rates WHO TB data submitted to the UN in May 2002 Acronym WHO MONGOLIA - TUBERCULOSIS MORTALITY 100 Death rate per 100,000 80 60 40 20 0 1985 1990 1995 2000 WHO Rates for tuberculosis mortality excluding cases attributable to HIV/AIDS. 23

24. Proportion of tuberculosis cases detected and cured under directly observed treatment short course (DOTS) Proportion of tuberculosis cases detected WHO Report 2004 Global Tuberculosis Control 100 MONGOLIA - PROPORTION OF ESTIMATED NEW SMEAR-POSITIVE TB CASES DETECTED UNDER DOTS DOTS detection rate (%) 80 60 40 20 0 1985 1990 1995 2000 Proportion of estimated new smear-positive tuberculosis cases detected under DOTS (Directly Observed Treatment Short Course) 24

Proportion of tuberculosis cases cured WHO Report 2004 Global Tuberculosis Control MONGOLIA - PROPORTION OF REGISTERED NEW SMEAR-POSITIVE TB CASES SUCCESSFULLY TREATED UNDER DOTS 100 DOTS treatment success (%) 80 60 40 20 0 1985 1990 1995 2000 Proportion of registered new smear positive tuberculosis cases successfully treated under DOTS (Directly Observed Treatment Short Course) 25

Data: Maternal mortality Proportion of Prevalence of ratio (per births attended underweight 100,000 live by skilled health children (%) Proportaion of 1-year-old children immunized against measles (%) births) personnel (%) HIV prevalence among 15-to-24-year-old pregnant women HIV prevalence among pregnant women (%) Reported by Reported by WHO/UNICE country to country to F estimate WHO UNICEF Government official estimate Reported doses administered Survey 12-23 months Survey <12 months Major urban areas, age 15-19 Major urban areas, age 20-24 Outside major urban areas, age 15-19 Outside major urban areas, age 20-24 Urban Rural Minimum Median Maximum Minimum Median Maximum 1985 18 18 17 1986 11 11 10 1987 61 61 10 1988 70 70 97 1989 86 86 86 1990 92 92 86 65 1991 82 82 1992 84 88 84 12.3 1993 84 84 84 1994 80 80 80 1995 85 85 85 65 1996 88 88 88 1997 91 91 91 1998 93 93 93 93.6 1999 93 93 93 12.5 93 93 86 2000 12.7 94 94 94 94 94 110 96.6 2001 95 95 95 95 2002 98 98 98 98 Ratio of proportion of Condom use Number of orphans to non- Proportion of Proportion of rate of the children orphans aged 10 Prevalence and tuberculosis tuberculosis contraceptive orphaned by to 14 years who death rates Treatment Tuberculosis Tuberculosis cases detected cases cured Contraceptive prevalence rate HIV/AIDS are attending associated w ith Bednet usage bednet usage Malaria prevalence rate death rate (per under DOTS under DOTS HIV prevalence among young people aged 15-24 (% ) prevalence rate (% ) (% ) currently living school (% ) malaria (% ) (% ) treatm ent (% ) (per 100,000) 100,000) (% ) (% ) Fem ale low Female high Male low Male high Modern estim ate estim ate estimate estimate All mdthods methods 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 59 1995 8 78 1996 32 78 1997 31 86 1998 53 84 1999 66 86 2000 67.4 54.3 7.3 152 24 59 87 2001 69 87 2002 69 26

Estimates of Under-five mortality and IMR, data and weights used for estimation: KH line MDS94 Indirect RHS98 direct Under-five mortality rate (per 1000 births) Data used RHS98 Indirect MICS2000 Indirect Rate Reference year Rate Weight Reference year Rate Weight Reference year Rate Weight Reference year Rate Weight 1960 169 1992.71 160 0.1 1996.5 81 1 1998 228 0 1999.6 31 0 1965 158 1991.02 168 0.6 1991.5 102 0.9 1996.7 90 0.1 1998.3 61 0.2 1970 148 1988.96 125 0.6 1986.5 125 0.6 1994.8 91 0.6 1996.1 87 1.2 1975 139 1986.65 173 0.6 1992.4 109 0.6 1993.5 87 1.2 1980 130 1984.06 154 0.4 1989.7 111 0.6 1990.6 91 1.2 1985 121 1981.07 106 0.2 1986.8 104 0.4 1987.6 111 0.8 1990 114 1983.8 109 0.2 1984.6 95 0.4 1995 86 2000 63 2001 59 2002 56 Infant mortality rate (per 1000 births) Data used KH line MDS94 Indirect MDS94 Direct RHS98 direct RHS98 Indirect MICS2000 Indirect Rate Reference year Rate Weight Reference year Rate Weight Reference year Rate Weight Reference year Rate Weight Reference year Rate Weight 1960 116 1992.71 110 0.1 1992.25 102 1 1996.5 63 1 1998 152 0 1999.6 26 0 1965 109 1991.02 115 0.6 1987.25 88 0.9 1991.5 73 0.9 1996.7 66 0.1 1998.3 47 0.2 1970 103 1988.96 88 0.6 1982.25 96 0.6 1986.5 84 0.6 1994.8 67 0.6 1996.1 64 1.2 1975 97 1986.65 118 0.6 1992.4 78 0.6 1993.5 64 1.2 1980 91 1984.06 106 0.4 1989.7 79 0.6 1990.6 66 1.2 1985 86 1981.07 76 0.2 1986.8 75 0.4 1987.6 79 0.8 1990 81 1983.8 78 0.2 1984.6 69 0.4 1995 63 2000 48 2001 46 2002 44 27