India - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in India was 33.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 249.30 in 1960 and a minimum value of 33.00 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 249.30
1961 245.60
1962 242.20
1963 238.80
1964 235.80
1965 233.00
1966 230.10
1967 227.30
1968 224.50
1969 221.70
1970 218.80
1971 215.70
1972 212.30
1973 208.60
1974 204.30
1975 199.60
1976 194.40
1977 189.10
1978 183.80
1979 178.30
1980 172.80
1981 167.50
1982 162.60
1983 157.90
1984 153.80
1985 149.80
1986 146.00
1987 142.20
1988 138.10
1989 134.10
1990 130.30
1991 126.90
1992 123.60
1993 120.60
1994 117.60
1995 114.60
1996 111.20
1997 107.90
1998 104.30
1999 100.10
2000 96.60
2001 92.90
2002 89.40
2003 85.80
2004 81.80
2005 78.40
2006 74.80
2007 71.50
2008 68.00
2009 64.60
2010 61.20
2011 57.70
2012 54.40
2013 51.10
2014 48.00
2015 45.00
2016 42.20
2017 39.50
2018 37.10
2019 34.90
2020 33.00

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