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

The value for Mortality rate, under-5, male (per 1,000 live births) in Sri Lanka was 7.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 97.10 in 1960 and a minimum value of 7.60 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 97.10
1961 92.60
1962 89.90
1963 88.10
1964 86.40
1965 84.30
1966 81.90
1967 79.30
1968 76.90
1969 75.20
1970 74.00
1971 73.10
1972 72.30
1973 71.30
1974 69.80
1975 67.60
1976 64.70
1977 61.10
1978 57.10
1979 53.10
1980 49.20
1981 45.80
1982 42.80
1983 39.30
1984 35.90
1985 32.50
1986 29.50
1987 27.10
1988 25.70
1989 28.90
1990 24.70
1991 24.50
1992 24.00
1993 23.20
1994 22.40
1995 21.60
1996 20.70
1997 19.90
1998 19.20
1999 18.40
2000 17.90
2001 17.30
2002 16.90
2003 16.40
2004 30.20
2005 15.40
2006 14.70
2007 14.00
2008 13.30
2009 22.40
2010 12.40
2011 12.00
2012 11.40
2013 10.80
2014 10.20
2015 9.60
2016 9.10
2017 8.60
2018 8.20
2019 7.90
2020 7.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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