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

The value for Mortality rate, under-5, male (per 1,000 live births) in India was 32.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 236.40 in 1960 and a minimum value of 32.20 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 236.40
1961 233.00
1962 229.90
1963 227.10
1964 224.40
1965 221.70
1966 219.20
1967 216.80
1968 214.20
1969 211.50
1970 208.60
1971 205.30
1972 201.80
1973 198.10
1974 194.20
1975 189.90
1976 185.20
1977 180.10
1978 174.60
1979 169.00
1980 163.60
1981 158.60
1982 154.10
1983 149.90
1984 145.70
1985 141.70
1986 137.70
1987 133.60
1988 129.80
1989 125.90
1990 122.30
1991 118.70
1992 115.10
1993 111.60
1994 108.00
1995 104.40
1996 100.90
1997 97.20
1998 93.70
1999 90.70
2000 87.00
2001 83.40
2002 79.90
2003 76.60
2004 73.90
2005 70.60
2006 67.60
2007 64.40
2008 61.30
2009 58.30
2010 55.30
2011 52.50
2012 49.70
2013 47.10
2014 44.50
2015 42.10
2016 39.80
2017 37.70
2018 35.60
2019 33.90
2020 32.20

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