St. Vincent and the Grenadines - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in St. Vincent and the Grenadines was 14.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 174.60 in 1960 and a minimum value of 14.10 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 174.60
1961 163.40
1962 149.80
1963 135.20
1964 121.00
1965 108.30
1966 97.50
1967 88.80
1968 82.20
1969 77.50
1970 74.80
1971 73.80
1972 74.00
1973 74.90
1974 75.50
1975 74.80
1976 72.40
1977 68.60
1978 63.60
1979 58.20
1980 52.80
1981 47.90
1982 43.20
1983 39.00
1984 35.30
1985 32.20
1986 29.60
1987 27.60
1988 25.90
1989 24.70
1990 23.80
1991 23.10
1992 22.60
1993 22.30
1994 22.20
1995 22.20
1996 22.20
1997 22.30
1998 22.30
1999 22.30
2000 22.20
2001 22.00
2002 21.90
2003 21.70
2004 21.60
2005 21.50
2006 21.30
2007 21.10
2008 20.80
2009 20.40
2010 19.80
2011 19.20
2012 18.60
2013 18.00
2014 17.40
2015 16.70
2016 16.20
2017 15.60
2018 15.10
2019 14.60
2020 14.10

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