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

The value for Mortality rate, under-5, female (per 1,000 live births) in Korea was 2.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 107.20 in 1960 and a minimum value of 2.70 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 107.20
1961 101.80
1962 96.90
1963 92.30
1964 87.50
1965 82.60
1966 77.50
1967 72.20
1968 66.90
1969 61.90
1970 57.30
1971 53.30
1972 49.90
1973 47.10
1974 44.70
1975 42.70
1976 40.80
1977 39.00
1978 37.20
1979 35.30
1980 33.30
1981 31.10
1982 28.90
1983 26.70
1984 24.50
1985 22.40
1986 20.40
1987 18.60
1988 17.00
1989 15.50
1990 14.30
1991 13.10
1992 12.10
1993 11.20
1994 10.40
1995 9.70
1996 9.00
1997 8.40
1998 7.90
1999 7.40
2000 7.00
2001 6.70
2002 6.30
2003 5.90
2004 5.60
2005 5.20
2006 4.80
2007 4.50
2008 4.20
2009 4.00
2010 3.80
2011 3.70
2012 3.50
2013 3.40
2014 3.30
2015 3.20
2016 3.10
2017 3.00
2018 2.90
2019 2.80
2020 2.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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