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

The value for Mortality rate, infant, female (per 1,000 live births) in Bangladesh was 22.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 199.50 in 1971 and a minimum value of 22.70 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 162.00
1961 158.00
1962 154.50
1963 151.20
1964 148.30
1965 145.90
1966 144.00
1967 142.60
1968 141.60
1969 141.00
1970 158.00
1971 199.50
1972 140.70
1973 140.40
1974 139.70
1975 138.70
1976 137.60
1977 136.00
1978 134.10
1979 131.80
1980 129.00
1981 126.10
1982 122.90
1983 119.50
1984 115.70
1985 111.80
1986 107.90
1987 104.20
1988 100.70
1989 97.00
1990 93.40
1991 89.70
1992 86.10
1993 82.50
1994 78.90
1995 75.10
1996 71.40
1997 68.10
1998 64.70
1999 61.50
2000 58.50
2001 55.70
2002 53.00
2003 50.50
2004 48.10
2005 45.80
2006 43.60
2007 41.60
2008 39.70
2009 37.90
2010 36.30
2011 34.80
2012 33.40
2013 32.00
2014 30.60
2015 29.20
2016 27.90
2017 26.50
2018 25.20
2019 23.90
2020 22.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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