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

The value for Mortality rate, under-5, female (per 1,000 live births) in Sri Lanka was 6.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 90.60 in 1960 and a minimum value of 6.30 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 90.60
1961 86.70
1962 83.70
1963 81.20
1964 79.10
1965 77.10
1966 74.30
1967 71.40
1968 69.10
1969 67.40
1970 66.20
1971 65.40
1972 64.60
1973 63.60
1974 62.20
1975 60.20
1976 57.40
1977 54.10
1978 50.30
1979 46.50
1980 43.00
1981 40.00
1982 37.00
1983 34.20
1984 30.90
1985 27.90
1986 25.30
1987 23.20
1988 21.90
1989 25.10
1990 20.70
1991 20.30
1992 19.90
1993 19.50
1994 18.90
1995 18.20
1996 17.60
1997 17.00
1998 16.30
1999 15.70
2000 15.10
2001 14.50
2002 14.10
2003 13.80
2004 27.60
2005 12.90
2006 12.30
2007 11.60
2008 11.10
2009 20.10
2010 10.30
2011 9.80
2012 9.30
2013 8.80
2014 8.30
2015 7.80
2016 7.40
2017 7.00
2018 6.80
2019 6.50
2020 6.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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