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

The value for Mortality rate, infant, female (per 1,000 live births) in St. Vincent and the Grenadines was 11.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 111.50 in 1960 and a minimum value of 11.80 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 111.50
1961 105.00
1962 96.80
1963 87.70
1964 78.80
1965 71.00
1966 64.20
1967 58.80
1968 54.80
1969 52.00
1970 50.60
1971 50.20
1972 50.70
1973 51.80
1974 52.60
1975 52.60
1976 51.30
1977 48.80
1978 45.60
1979 41.90
1980 38.20
1981 34.80
1982 31.60
1983 28.70
1984 26.10
1985 23.90
1986 22.10
1987 20.60
1988 19.50
1989 18.70
1990 18.10
1991 17.60
1992 17.30
1993 17.20
1994 17.20
1995 17.20
1996 17.30
1997 17.50
1998 17.50
1999 17.60
2000 17.50
2001 17.50
2002 17.40
2003 17.40
2004 17.30
2005 17.30
2006 17.20
2007 17.00
2008 16.80
2009 16.50
2010 16.20
2011 15.70
2012 15.20
2013 14.80
2014 14.30
2015 13.80
2016 13.40
2017 13.00
2018 12.50
2019 12.20
2020 11.80

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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