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

The value for Mortality rate, under-5, male (per 1,000 live births) in Burkina Faso was 89.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 356.50 in 1960 and a minimum value of 89.60 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 356.50
1961 353.00
1962 349.60
1963 346.20
1964 343.30
1965 340.20
1966 337.70
1967 335.20
1968 333.00
1969 330.70
1970 328.00
1971 324.80
1972 320.40
1973 313.90
1974 305.80
1975 295.90
1976 285.20
1977 274.50
1978 264.90
1979 256.30
1980 249.10
1981 243.10
1982 237.60
1983 232.60
1984 227.60
1985 222.90
1986 218.20
1987 214.00
1988 210.50
1989 207.90
1990 206.30
1991 205.40
1992 204.80
1993 204.10
1994 203.10
1995 201.10
1996 198.40
1997 195.30
1998 192.20
1999 188.80
2000 185.10
2001 181.20
2002 176.70
2003 171.50
2004 165.50
2005 159.00
2006 152.00
2007 144.90
2008 138.10
2009 132.00
2010 126.50
2011 121.90
2012 117.40
2013 113.40
2014 109.50
2015 105.70
2016 102.30
2017 98.80
2018 95.50
2019 92.50
2020 89.60

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