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

The value for Mortality rate, under-5 (per 1,000 live births) in Colombia was 13.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 134.60 in 1960 and a minimum value of 13.20 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 134.60
1961 130.20
1962 126.10
1963 122.20
1964 118.50
1965 114.90
1966 111.40
1967 108.10
1968 104.60
1969 101.10
1970 97.50
1971 93.90
1972 90.10
1973 86.30
1974 82.40
1975 78.20
1976 74.10
1977 69.90
1978 65.90
1979 62.00
1980 58.30
1981 54.80
1982 51.50
1983 48.60
1984 45.90
1985 43.60
1986 41.50
1987 39.70
1988 38.20
1989 36.80
1990 35.60
1991 34.40
1992 33.20
1993 32.10
1994 31.00
1995 29.90
1996 28.80
1997 27.80
1998 26.80
1999 25.90
2000 25.10
2001 24.30
2002 23.50
2003 22.80
2004 22.10
2005 21.50
2006 20.80
2007 20.20
2008 19.50
2009 18.90
2010 18.30
2011 17.70
2012 17.10
2013 16.60
2014 16.00
2015 15.50
2016 15.00
2017 14.60
2018 14.10
2019 13.60
2020 13.20

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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