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

The value for Mortality rate, under-5, male (per 1,000 live births) in Cameroon was 77.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 289.30 in 1960 and a minimum value of 77.80 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 289.30
1961 282.90
1962 277.50
1963 272.90
1964 268.00
1965 262.20
1966 255.30
1967 247.10
1968 238.40
1969 229.40
1970 220.70
1971 213.10
1972 207.60
1973 203.60
1974 201.10
1975 200.00
1976 199.00
1977 197.80
1978 195.80
1979 192.60
1980 188.30
1981 182.70
1982 176.50
1983 169.80
1984 163.20
1985 157.10
1986 151.80
1987 147.70
1988 145.00
1989 143.90
1990 144.20
1991 145.80
1992 148.10
1993 150.90
1994 153.30
1995 155.10
1996 156.40
1997 156.90
1998 156.40
1999 154.80
2000 152.40
2001 149.40
2002 145.80
2003 142.20
2004 138.70
2005 135.50
2006 132.20
2007 128.90
2008 125.40
2009 122.00
2010 117.60
2011 113.10
2012 108.40
2013 103.50
2014 98.90
2015 94.40
2016 90.30
2017 86.60
2018 83.30
2019 80.40
2020 77.80

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