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

The value for Mortality rate, infant (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 115.00 in 1960 and a minimum value of 12.90 in 2020.

Definition: Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given 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 115.00
1961 108.80
1962 100.70
1963 91.80
1964 82.90
1965 74.90
1966 68.10
1967 62.50
1968 58.40
1969 55.50
1970 54.00
1971 53.70
1972 54.30
1973 55.40
1974 56.30
1975 56.20
1976 54.80
1977 52.30
1978 48.80
1979 44.90
1980 41.10
1981 37.50
1982 34.10
1983 31.00
1984 28.20
1985 25.90
1986 23.90
1987 22.40
1988 21.20
1989 20.30
1990 19.60
1991 19.10
1992 18.80
1993 18.70
1994 18.70
1995 18.80
1996 18.90
1997 19.00
1998 19.10
1999 19.20
2000 19.20
2001 19.10
2002 19.10
2003 19.00
2004 19.00
2005 18.90
2006 18.80
2007 18.70
2008 18.50
2009 18.20
2010 17.80
2011 17.30
2012 16.80
2013 16.20
2014 15.70
2015 15.20
2016 14.70
2017 14.30
2018 13.80
2019 13.40
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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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