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

The value for Mortality rate, infant, female (per 1,000 live births) in Cameroon was 43.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 153.90 in 1960 and a minimum value of 43.10 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 153.90
1961 150.50
1962 147.80
1963 145.40
1964 142.90
1965 139.90
1966 136.10
1967 131.50
1968 126.60
1969 121.70
1970 117.10
1971 113.00
1972 109.80
1973 107.40
1974 106.00
1975 105.00
1976 104.40
1977 103.50
1978 102.40
1979 100.60
1980 98.40
1981 95.60
1982 92.60
1983 89.40
1984 86.00
1985 82.80
1986 80.20
1987 78.20
1988 76.90
1989 76.40
1990 76.70
1991 77.30
1992 78.40
1993 79.50
1994 80.40
1995 81.10
1996 81.60
1997 81.70
1998 81.50
1999 80.60
2000 79.30
2001 77.60
2002 75.80
2003 73.90
2004 72.00
2005 70.50
2006 68.80
2007 67.30
2008 65.50
2009 64.00
2010 61.70
2011 59.80
2012 57.60
2013 55.20
2014 53.30
2015 51.10
2016 49.40
2017 47.50
2018 45.90
2019 44.60
2020 43.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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