Central African Republic - Mortality rate, infant, male (per 1,000 live births)

The value for Mortality rate, infant, male (per 1,000 live births) in Central African Republic was 83.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 173.30 in 1960 and a minimum value of 83.70 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 173.30
1961 170.70
1962 168.00
1963 165.30
1964 162.60
1965 159.70
1966 156.80
1967 153.80
1968 150.80
1969 147.90
1970 145.10
1971 142.60
1972 140.50
1973 138.40
1974 136.60
1975 134.70
1976 133.10
1977 131.50
1978 130.00
1979 128.80
1980 127.60
1981 126.80
1982 125.80
1983 125.10
1984 124.60
1985 124.10
1986 123.70
1987 123.50
1988 123.60
1989 124.00
1990 124.20
1991 124.10
1992 123.60
1993 123.00
1994 122.40
1995 121.80
1996 121.10
1997 120.30
1998 119.50
1999 118.60
2000 117.80
2001 117.10
2002 116.30
2003 115.50
2004 114.70
2005 113.90
2006 112.50
2007 111.50
2008 110.10
2009 108.10
2010 106.40
2011 104.00
2012 101.70
2013 100.10
2014 97.40
2015 94.90
2016 92.30
2017 90.40
2018 88.10
2019 85.50
2020 83.70

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