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

The value for Mortality rate, infant, male (per 1,000 live births) in St. Vincent and the Grenadines was 14.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 118.40 in 1960 and a minimum value of 14.00 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 118.40
1961 112.40
1962 104.40
1963 95.60
1964 86.70
1965 78.60
1966 71.70
1967 66.00
1968 61.70
1969 58.80
1970 57.40
1971 57.10
1972 57.70
1973 58.80
1974 59.70
1975 59.60
1976 58.20
1977 55.60
1978 51.90
1979 47.90
1980 43.90
1981 40.00
1982 36.40
1983 33.10
1984 30.20
1985 27.70
1986 25.70
1987 24.00
1988 22.70
1989 21.80
1990 21.10
1991 20.60
1992 20.30
1993 20.10
1994 20.10
1995 20.20
1996 20.30
1997 20.50
1998 20.60
1999 20.70
2000 20.70
2001 20.60
2002 20.60
2003 20.60
2004 20.50
2005 20.50
2006 20.40
2007 20.30
2008 20.00
2009 19.70
2010 19.30
2011 18.70
2012 18.20
2013 17.60
2014 17.10
2015 16.50
2016 16.00
2017 15.50
2018 15.00
2019 14.50
2020 14.00

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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