Indonesia - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in Indonesia was 20.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 216.20 in 1965 and a minimum value of 20.40 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female age-specific mortality rates of the specified year.

Source: Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.

See also:

Year Value
1960 209.40
1961 203.70
1962 198.00
1963 192.50
1964 187.10
1965 216.20
1966 176.00
1967 170.40
1968 164.70
1969 159.20
1970 153.70
1971 148.50
1972 143.50
1973 138.70
1974 134.20
1975 129.90
1976 125.80
1977 121.90
1978 118.30
1979 114.80
1980 111.40
1981 108.10
1982 104.80
1983 101.50
1984 98.20
1985 94.80
1986 91.40
1987 88.00
1988 84.60
1989 81.00
1990 77.50
1991 73.90
1992 70.50
1993 67.10
1994 63.80
1995 60.80
1996 57.90
1997 55.20
1998 52.60
1999 50.20
2000 47.80
2001 45.50
2002 43.40
2003 41.40
2004 45.70
2005 37.80
2006 36.20
2007 34.60
2008 33.20
2009 31.80
2010 30.40
2011 29.20
2012 27.90
2013 26.80
2014 25.70
2015 24.70
2016 23.70
2017 22.80
2018 21.90
2019 21.20
2020 20.40

Development Relevance: Mortality rates for different age groups (infants, children, and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

Limitations and Exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.

Statistical Concept and Methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A "complete" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development ac

Classification

Topic: Health Indicators

Sub-Topic: Mortality