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

The value for Mortality rate, infant, male (per 1,000 live births) in The Gambia was 38.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 163.90 in 1960 and a minimum value of 38.90 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 163.90
1961 161.10
1962 158.50
1963 155.80
1964 153.20
1965 150.70
1966 148.20
1967 145.60
1968 143.20
1969 140.70
1970 138.20
1971 135.70
1972 133.10
1973 130.60
1974 128.10
1975 125.60
1976 123.20
1977 120.70
1978 118.30
1979 115.90
1980 113.60
1981 111.10
1982 108.70
1983 106.20
1984 103.70
1985 101.10
1986 98.50
1987 96.10
1988 93.70
1989 91.40
1990 89.20
1991 87.00
1992 84.80
1993 82.60
1994 80.30
1995 78.20
1996 76.10
1997 74.00
1998 72.10
1999 70.10
2000 68.10
2001 66.20
2002 64.40
2003 62.60
2004 60.70
2005 59.00
2006 57.30
2007 55.70
2008 54.10
2009 52.50
2010 51.00
2011 49.60
2012 48.20
2013 46.90
2014 45.60
2015 44.40
2016 43.20
2017 42.00
2018 40.90
2019 39.80
2020 38.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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