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

The value for Mortality rate, under-5 (per 1,000 live births) in Burkina Faso was 85.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 345.50 in 1960 and a minimum value of 85.00 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 345.50
1961 341.60
1962 338.20
1963 335.10
1964 331.90
1965 328.90
1966 326.20
1967 323.80
1968 321.50
1969 319.20
1970 316.50
1971 313.30
1972 308.90
1973 302.70
1974 294.70
1975 285.20
1976 274.70
1977 264.40
1978 255.00
1979 246.80
1980 239.90
1981 234.20
1982 229.10
1983 224.40
1984 219.90
1985 215.30
1986 210.60
1987 206.40
1988 202.90
1989 200.50
1990 199.10
1991 198.40
1992 198.20
1993 197.70
1994 196.80
1995 195.10
1996 192.50
1997 189.40
1998 186.10
1999 182.60
2000 178.90
2001 174.90
2002 170.40
2003 165.30
2004 159.50
2005 153.10
2006 146.30
2007 139.50
2008 132.90
2009 126.90
2010 121.50
2011 116.90
2012 112.50
2013 108.30
2014 104.50
2015 100.90
2016 97.50
2017 94.10
2018 90.80
2019 87.80
2020 85.00

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