St. Lucia - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in St. Lucia was 24.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 164.00 in 1960 and a minimum value of 18.20 in 2002.

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 164.00
1961 156.00
1962 146.90
1963 137.30
1964 127.40
1965 117.40
1966 107.70
1967 98.40
1968 89.70
1969 81.50
1970 74.10
1971 67.40
1972 61.30
1973 56.00
1974 51.20
1975 47.00
1976 43.30
1977 40.10
1978 37.30
1979 34.90
1980 32.80
1981 30.90
1982 29.40
1983 28.00
1984 26.80
1985 25.70
1986 24.70
1987 23.90
1988 23.10
1989 22.40
1990 21.80
1991 21.30
1992 20.70
1993 20.30
1994 19.90
1995 19.50
1996 19.20
1997 18.90
1998 18.70
1999 18.50
2000 18.40
2001 18.30
2002 18.20
2003 18.30
2004 18.30
2005 18.40
2006 18.60
2007 18.80
2008 19.00
2009 19.30
2010 19.70
2011 20.00
2012 20.40
2013 20.90
2014 21.40
2015 21.90
2016 22.40
2017 23.00
2018 23.50
2019 24.00
2020 24.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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