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

The value for Mortality rate, infant, male (per 1,000 live births) in Bangladesh was 25.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 221.70 in 1971 and a minimum value of 25.90 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 187.60
1961 183.10
1962 178.80
1963 175.10
1964 171.80
1965 169.10
1966 166.80
1967 165.20
1968 164.20
1969 163.60
1970 180.40
1971 221.70
1972 162.60
1973 162.10
1974 161.10
1975 159.90
1976 158.00
1977 155.60
1978 152.90
1979 149.90
1980 146.70
1981 143.20
1982 139.70
1983 136.10
1984 132.40
1985 128.70
1986 124.90
1987 120.90
1988 116.70
1989 112.60
1990 108.50
1991 104.30
1992 99.90
1993 95.60
1994 91.30
1995 87.20
1996 83.10
1997 78.90
1998 74.90
1999 71.10
2000 67.40
2001 64.00
2002 60.90
2003 58.00
2004 55.30
2005 52.70
2006 50.20
2007 47.90
2008 45.60
2009 43.40
2010 41.40
2011 39.40
2012 37.60
2013 35.90
2014 34.30
2015 32.80
2016 31.20
2017 29.80
2018 28.40
2019 27.10
2020 25.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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