The Gambia - Mortality rate, under-5, male (per 1,000 live births)

The value for Mortality rate, under-5, male (per 1,000 live births) in The Gambia was 54.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 372.50 in 1960 and a minimum value of 54.00 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 372.50
1961 365.40
1962 358.60
1963 352.00
1964 345.40
1965 338.80
1966 332.10
1967 325.60
1968 318.90
1969 312.50
1970 306.10
1971 299.70
1972 293.20
1973 286.40
1974 279.70
1975 272.90
1976 266.20
1977 259.50
1978 253.10
1979 246.70
1980 240.40
1981 233.80
1982 227.20
1983 220.70
1984 213.90
1985 207.20
1986 200.40
1987 193.80
1988 187.50
1989 181.40
1990 175.40
1991 169.70
1992 163.70
1993 157.70
1994 151.90
1995 146.30
1996 140.80
1997 135.50
1998 130.20
1999 125.20
2000 120.20
2001 115.40
2002 110.80
2003 106.30
2004 101.90
2005 97.70
2006 93.70
2007 89.80
2008 86.10
2009 82.50
2010 79.20
2011 76.10
2012 73.10
2013 70.30
2014 67.60
2015 64.90
2016 62.50
2017 60.10
2018 57.90
2019 55.90
2020 54.00

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