Central African Republic - Mortality rate, under-5, male (per 1,000 live births)

The value for Mortality rate, under-5, male (per 1,000 live births) in Central African Republic was 109.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 287.20 in 1960 and a minimum value of 109.00 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 287.20
1961 281.90
1962 276.40
1963 270.70
1964 264.80
1965 258.90
1966 252.70
1967 246.60
1968 240.50
1969 234.80
1970 229.20
1971 224.20
1972 219.50
1973 215.30
1974 211.30
1975 207.40
1976 204.00
1977 200.70
1978 197.50
1979 194.70
1980 192.30
1981 190.20
1982 188.50
1983 187.00
1984 185.90
1985 184.80
1986 183.90
1987 183.20
1988 183.00
1989 183.50
1990 184.20
1991 184.60
1992 184.30
1993 183.70
1994 182.80
1995 181.90
1996 180.90
1997 179.70
1998 178.40
1999 176.90
2000 175.60
2001 174.00
2002 172.40
2003 170.80
2004 169.10
2005 167.40
2006 165.00
2007 162.50
2008 159.50
2009 155.50
2010 151.70
2011 147.10
2012 142.60
2013 138.90
2014 134.50
2015 129.60
2016 124.40
2017 120.60
2018 117.20
2019 112.50
2020 109.00

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