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

The value for Mortality rate, under-5, female (per 1,000 live births) in St. Vincent and the Grenadines was 12.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 173.30 in 1960 and a minimum value of 12.90 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 173.30
1961 161.80
1962 147.70
1963 132.60
1964 118.20
1965 105.40
1966 94.50
1967 85.70
1968 79.00
1969 74.30
1970 71.50
1971 70.40
1972 70.50
1973 71.30
1974 71.90
1975 71.20
1976 68.90
1977 65.10
1978 60.20
1979 54.90
1980 49.70
1981 44.90
1982 40.40
1983 36.40
1984 32.80
1985 29.80
1986 27.40
1987 25.40
1988 23.90
1989 22.80
1990 21.90
1991 21.20
1992 20.80
1993 20.50
1994 20.40
1995 20.40
1996 20.40
1997 20.50
1998 20.50
1999 20.40
2000 20.30
2001 20.20
2002 20.00
2003 19.90
2004 19.70
2005 19.60
2006 19.40
2007 19.20
2008 18.90
2009 18.50
2010 18.10
2011 17.50
2012 16.90
2013 16.40
2014 15.80
2015 15.20
2016 14.70
2017 14.20
2018 13.70
2019 13.30
2020 12.90

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