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

The value for Mortality rate, infant, male (per 1,000 live births) in Cameroon was 53.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 175.50 in 1960 and a minimum value of 53.20 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 175.50
1961 171.30
1962 167.90
1963 165.00
1964 161.90
1965 158.30
1966 154.10
1967 149.30
1968 144.00
1969 138.70
1970 133.80
1971 129.80
1972 126.80
1973 124.80
1974 123.50
1975 122.90
1976 122.40
1977 121.80
1978 120.80
1979 119.10
1980 116.80
1981 113.80
1982 110.50
1983 107.00
1984 103.40
1985 100.00
1986 97.00
1987 94.60
1988 93.00
1989 92.30
1990 92.30
1991 93.20
1992 94.60
1993 96.10
1994 97.40
1995 98.30
1996 98.80
1997 98.90
1998 98.40
1999 97.20
2000 95.50
2001 93.50
2002 91.30
2003 89.10
2004 87.00
2005 85.30
2006 83.30
2007 81.60
2008 79.60
2009 77.90
2010 75.20
2011 73.00
2012 70.40
2013 67.60
2014 65.30
2015 62.60
2016 60.70
2017 58.50
2018 56.50
2019 55.00
2020 53.20

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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