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

The value for Mortality rate, under-5, female (per 1,000 live births) in The Gambia was 44.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 347.00 in 1960 and a minimum value of 44.50 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 347.00
1961 340.30
1962 333.60
1963 327.30
1964 320.90
1965 314.50
1966 308.30
1967 301.90
1968 295.60
1969 289.30
1970 283.20
1971 276.70
1972 270.20
1973 263.70
1974 257.20
1975 250.40
1976 243.80
1977 237.50
1978 231.30
1979 225.20
1980 219.00
1981 212.70
1982 206.30
1983 199.90
1984 193.40
1985 186.80
1986 180.40
1987 174.10
1988 168.00
1989 162.30
1990 156.70
1991 151.20
1992 146.00
1993 140.70
1994 135.60
1995 130.40
1996 125.30
1997 120.30
1998 115.40
1999 110.60
2000 106.10
2001 101.60
2002 97.20
2003 93.00
2004 88.90
2005 85.00
2006 81.20
2007 77.50
2008 74.10
2009 70.80
2010 67.70
2011 64.80
2012 62.00
2013 59.40
2014 56.80
2015 54.40
2016 52.10
2017 50.00
2018 48.00
2019 46.20
2020 44.50

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