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

The value for Mortality rate, under-5, female (per 1,000 live births) in Benin was 79.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 297.10 in 1960 and a minimum value of 79.90 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 297.10
1961 292.20
1962 287.30
1963 282.10
1964 276.80
1965 271.70
1966 266.70
1967 262.00
1968 257.40
1969 252.80
1970 248.40
1971 244.10
1972 239.70
1973 235.00
1974 230.10
1975 225.20
1976 220.30
1977 215.40
1978 210.60
1979 206.10
1980 201.90
1981 197.90
1982 194.20
1983 190.50
1984 187.00
1985 183.40
1986 179.90
1987 176.20
1988 172.70
1989 169.10
1990 165.30
1991 161.50
1992 157.80
1993 154.20
1994 150.60
1995 147.10
1996 143.70
1997 140.50
1998 137.30
1999 133.80
2000 130.40
2001 127.00
2002 123.90
2003 120.80
2004 117.90
2005 115.00
2006 112.20
2007 109.60
2008 107.10
2009 104.50
2010 102.20
2011 99.80
2012 97.60
2013 95.40
2014 93.20
2015 91.00
2016 88.90
2017 86.90
2018 84.60
2019 82.30
2020 79.90

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