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

The value for Mortality rate, under-5 (per 1,000 live births) in Sri Lanka was 6.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 93.90 in 1960 and a minimum value of 6.90 in 2020.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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 93.90
1961 89.70
1962 86.90
1963 84.80
1964 82.80
1965 80.80
1966 78.20
1967 75.40
1968 73.10
1969 71.40
1970 70.20
1971 69.40
1972 68.60
1973 67.60
1974 66.10
1975 64.00
1976 61.10
1977 57.60
1978 53.80
1979 49.90
1980 46.20
1981 43.00
1982 40.00
1983 36.80
1984 33.40
1985 30.20
1986 27.40
1987 25.20
1988 23.80
1989 27.00
1990 22.80
1991 22.40
1992 22.00
1993 21.40
1994 20.70
1995 19.90
1996 19.20
1997 18.50
1998 17.80
1999 17.10
2000 16.50
2001 16.00
2002 15.50
2003 15.10
2004 28.90
2005 14.20
2006 13.50
2007 12.80
2008 12.20
2009 21.30
2010 11.40
2011 10.90
2012 10.40
2013 9.80
2014 9.30
2015 8.70
2016 8.20
2017 7.80
2018 7.50
2019 7.20
2020 6.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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