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

The value for Mortality rate, infant, male (per 1,000 live births) in Benin was 61.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 197.20 in 1960 and a minimum value of 61.90 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 197.20
1961 194.00
1962 190.80
1963 187.60
1964 184.20
1965 180.90
1966 177.50
1967 174.40
1968 171.40
1969 168.60
1970 165.90
1971 162.80
1972 159.80
1973 156.80
1974 153.70
1975 150.60
1976 147.40
1977 144.20
1978 141.20
1979 138.50
1980 135.80
1981 133.30
1982 130.70
1983 128.40
1984 126.00
1985 123.50
1986 121.10
1987 118.70
1988 116.20
1989 113.80
1990 111.50
1991 109.20
1992 106.90
1993 104.60
1994 102.30
1995 100.20
1996 98.30
1997 96.40
1998 94.50
1999 92.90
2000 91.20
2001 89.50
2002 87.60
2003 85.80
2004 84.00
2005 82.40
2006 80.90
2007 79.30
2008 78.00
2009 76.80
2010 75.50
2011 74.30
2012 73.00
2013 71.70
2014 70.40
2015 69.10
2016 67.70
2017 66.30
2018 64.90
2019 63.40
2020 61.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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