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

The value for Mortality rate, under-5, male (per 1,000 live births) in Bangladesh was 31.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 375.20 in 1971 and a minimum value of 31.00 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 268.20
1961 261.80
1962 255.60
1963 250.20
1964 245.50
1965 241.40
1966 238.10
1967 235.60
1968 234.10
1969 233.00
1970 277.90
1971 375.20
1972 231.40
1973 230.50
1974 229.20
1975 227.30
1976 224.40
1977 221.00
1978 216.80
1979 212.30
1980 207.50
1981 202.40
1982 197.20
1983 191.70
1984 186.00
1985 180.30
1986 174.40
1987 168.30
1988 162.00
1989 155.90
1990 149.60
1991 143.40
1992 137.10
1993 130.70
1994 124.50
1995 118.40
1996 112.30
1997 106.30
1998 100.40
1999 94.90
2000 89.60
2001 84.60
2002 79.90
2003 75.60
2004 71.60
2005 67.80
2006 64.20
2007 60.80
2008 57.60
2009 54.60
2010 51.80
2011 49.10
2012 46.70
2013 44.40
2014 42.20
2015 40.20
2016 38.10
2017 36.30
2018 34.40
2019 32.60
2020 31.00

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