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

The value for Mortality rate, infant, female (per 1,000 live births) in The Gambia was 30.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 140.30 in 1960 and a minimum value of 30.40 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 140.30
1961 137.80
1962 135.40
1963 133.00
1964 130.70
1965 128.30
1966 126.10
1967 123.90
1968 121.80
1969 119.50
1970 117.30
1971 114.90
1972 112.60
1973 110.30
1974 108.00
1975 105.70
1976 103.30
1977 101.10
1978 98.90
1979 96.70
1980 94.50
1981 92.30
1982 90.10
1983 87.80
1984 85.60
1985 83.30
1986 81.10
1987 78.90
1988 76.70
1989 74.70
1990 72.70
1991 70.80
1992 69.00
1993 67.20
1994 65.40
1995 63.50
1996 61.70
1997 59.90
1998 58.10
1999 56.40
2000 54.80
2001 53.10
2002 51.50
2003 49.90
2004 48.40
2005 46.90
2006 45.40
2007 44.00
2008 42.70
2009 41.50
2010 40.20
2011 39.00
2012 37.90
2013 36.80
2014 35.80
2015 34.80
2016 33.80
2017 32.90
2018 32.00
2019 31.20
2020 30.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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