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

The value for Mortality rate, infant, male (per 1,000 live births) in Indonesia was 21.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 164.20 in 1960 and a minimum value of 21.70 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male live births in a given 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 164.20
1961 159.90
1962 155.90
1963 152.00
1964 148.30
1965 158.20
1966 140.70
1967 136.90
1968 133.20
1969 129.60
1970 126.10
1971 122.60
1972 119.10
1973 115.70
1974 112.30
1975 109.10
1976 105.90
1977 102.90
1978 100.10
1979 97.20
1980 94.50
1981 91.70
1982 89.00
1983 86.30
1984 83.60
1985 81.00
1986 78.40
1987 75.90
1988 73.30
1989 70.70
1990 68.10
1991 65.50
1992 62.80
1993 60.30
1994 57.90
1995 55.50
1996 53.20
1997 51.00
1998 48.80
1999 46.80
2000 44.90
2001 43.20
2002 41.50
2003 39.90
2004 40.50
2005 36.90
2006 35.60
2007 34.30
2008 33.00
2009 31.90
2010 30.80
2011 29.70
2012 28.60
2013 27.60
2014 26.70
2015 25.70
2016 24.80
2017 23.90
2018 23.10
2019 22.40
2020 21.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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