Grenada - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Grenada was 16.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 101.60 in 1960 and a minimum value of 14.60 in 2005.

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 101.60
1961 93.50
1962 85.70
1963 78.50
1964 72.60
1965 67.80
1966 64.20
1967 61.60
1968 59.50
1969 57.70
1970 56.10
1971 54.50
1972 52.90
1973 51.20
1974 49.50
1975 47.70
1976 45.90
1977 44.00
1978 42.00
1979 40.00
1980 38.00
1981 36.00
1982 34.10
1983 32.30
1984 30.60
1985 29.00
1986 27.50
1987 26.10
1988 24.80
1989 23.60
1990 22.40
1991 21.20
1992 20.20
1993 19.20
1994 18.40
1995 17.60
1996 17.00
1997 16.50
1998 16.10
1999 15.80
2000 15.50
2001 15.20
2002 15.00
2003 14.80
2004 14.70
2005 14.60
2006 14.60
2007 14.60
2008 14.70
2009 14.90
2010 15.10
2011 15.30
2012 15.50
2013 15.80
2014 16.00
2015 16.20
2016 16.40
2017 16.60
2018 16.60
2019 16.50
2020 16.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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