Burkina Faso - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in Burkina Faso was 80.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 333.30 in 1960 and a minimum value of 80.10 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 333.30
1961 329.60
1962 326.20
1963 323.10
1964 319.90
1965 316.90
1966 314.10
1967 311.80
1968 309.20
1969 306.80
1970 304.30
1971 301.20
1972 297.00
1973 291.00
1974 283.20
1975 273.80
1976 263.60
1977 253.60
1978 244.50
1979 236.70
1980 230.20
1981 224.80
1982 220.20
1983 216.00
1984 211.80
1985 207.20
1986 202.60
1987 198.40
1988 194.90
1989 192.60
1990 191.40
1991 191.00
1992 191.00
1993 190.90
1994 190.30
1995 188.90
1996 186.30
1997 183.10
1998 179.70
1999 176.10
2000 172.40
2001 168.30
2002 163.80
2003 158.80
2004 153.20
2005 146.90
2006 140.30
2007 133.70
2008 127.40
2009 121.50
2010 116.30
2011 111.50
2012 107.20
2013 103.30
2014 99.50
2015 95.80
2016 92.40
2017 89.00
2018 85.90
2019 82.90
2020 80.10

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