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

The value for Mortality rate, under-5 (per 1,000 live births) in Cameroon was 72.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 278.40 in 1960 and a minimum value of 72.20 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 278.40
1961 272.20
1962 267.20
1963 262.70
1964 258.00
1965 252.60
1966 245.80
1967 237.80
1968 229.30
1969 220.40
1970 212.00
1971 204.70
1972 198.90
1973 194.80
1974 192.30
1975 191.00
1976 189.90
1977 188.50
1978 186.50
1979 183.50
1980 179.10
1981 173.90
1982 167.70
1983 161.30
1984 154.80
1985 148.80
1986 143.60
1987 139.70
1988 137.10
1989 135.90
1990 136.30
1991 137.80
1992 140.00
1993 142.50
1994 144.80
1995 146.40
1996 147.60
1997 148.10
1998 147.80
1999 146.30
2000 143.90
2001 140.90
2002 137.50
2003 134.00
2004 130.60
2005 127.50
2006 124.20
2007 121.00
2008 117.60
2009 114.30
2010 110.10
2011 105.80
2012 101.30
2013 96.70
2014 92.40
2015 88.00
2016 84.20
2017 80.60
2018 77.30
2019 74.70
2020 72.20

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