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

The value for Mortality rate, under-5, male (per 1,000 live births) in Indonesia was 25.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 242.10 in 1965 and a minimum value of 25.40 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 237.80
1961 231.30
1962 225.10
1963 219.20
1964 213.30
1965 242.10
1966 201.50
1967 195.70
1968 189.80
1969 184.00
1970 178.30
1971 172.70
1972 167.20
1973 161.90
1974 156.70
1975 151.70
1976 147.00
1977 142.60
1978 138.20
1979 134.00
1980 129.90
1981 125.80
1982 121.70
1983 117.80
1984 113.80
1985 109.90
1986 106.00
1987 102.10
1988 98.20
1989 94.30
1990 90.30
1991 86.30
1992 82.40
1993 78.60
1994 75.00
1995 71.40
1996 68.10
1997 64.90
1998 61.90
1999 59.00
2000 56.40
2001 53.90
2002 51.60
2003 49.40
2004 53.40
2005 45.40
2006 43.50
2007 41.80
2008 40.10
2009 38.60
2010 37.00
2011 35.60
2012 34.30
2013 33.00
2014 31.70
2015 30.50
2016 29.40
2017 28.30
2018 27.20
2019 26.30
2020 25.40

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