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

The value for Mortality rate, infant, female (per 1,000 live births) in Indonesia was 17.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 134.00 in 1960 and a minimum value of 17.30 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 134.00
1961 130.50
1962 127.20
1963 123.90
1964 120.60
1965 130.90
1966 113.70
1967 110.30
1968 106.90
1969 103.60
1970 100.30
1971 97.20
1972 94.30
1973 91.50
1974 88.80
1975 86.30
1976 83.90
1977 81.60
1978 79.50
1979 77.50
1980 75.50
1981 73.60
1982 71.60
1983 69.70
1984 67.80
1985 65.70
1986 63.70
1987 61.60
1988 59.60
1989 57.40
1990 55.30
1991 53.10
1992 51.00
1993 49.00
1994 47.00
1995 45.20
1996 43.40
1997 41.70
1998 40.10
1999 38.50
2000 36.90
2001 35.40
2002 34.00
2003 32.60
2004 33.50
2005 30.10
2006 29.00
2007 27.90
2008 26.90
2009 25.90
2010 24.90
2011 24.00
2012 23.10
2013 22.20
2014 21.40
2015 20.60
2016 19.80
2017 19.10
2018 18.50
2019 17.90
2020 17.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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