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

The value for Mortality rate, under-5 (per 1,000 live births) in Central African Republic was 103.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 280.30 in 1960 and a minimum value of 103.00 in 2020.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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 280.30
1961 275.00
1962 269.50
1963 264.00
1964 258.30
1965 252.10
1966 246.20
1967 240.20
1968 234.30
1969 228.60
1970 223.20
1971 218.20
1972 213.50
1973 209.20
1974 205.10
1975 201.30
1976 197.80
1977 194.40
1978 191.10
1979 188.30
1980 185.70
1981 183.50
1982 181.70
1983 180.20
1984 179.00
1985 177.90
1986 176.80
1987 176.00
1988 175.70
1989 176.10
1990 176.70
1991 176.90
1992 176.70
1993 176.10
1994 175.40
1995 174.60
1996 173.70
1997 172.80
1998 171.50
1999 170.20
2000 168.90
2001 167.40
2002 165.80
2003 164.20
2004 162.50
2005 160.80
2006 158.30
2007 155.60
2008 152.80
2009 148.90
2010 145.00
2011 140.50
2012 136.20
2013 132.50
2014 128.20
2015 123.30
2016 118.20
2017 114.50
2018 111.10
2019 106.60
2020 103.00

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