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

The value for Mortality rate, infant, male (per 1,000 live births) in India was 27.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 166.20 in 1960 and a minimum value of 27.20 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 166.20
1961 163.90
1962 161.70
1963 159.60
1964 157.70
1965 155.90
1966 154.20
1967 152.40
1968 150.70
1969 148.80
1970 146.90
1971 144.70
1972 142.40
1973 139.90
1974 137.50
1975 134.80
1976 131.90
1977 128.60
1978 124.90
1979 121.40
1980 118.00
1981 114.80
1982 111.90
1983 109.30
1984 106.60
1985 104.00
1986 101.10
1987 98.30
1988 95.70
1989 93.20
1990 90.80
1991 88.40
1992 85.90
1993 83.50
1994 81.10
1995 78.70
1996 76.30
1997 73.70
1998 71.20
1999 69.20
2000 66.40
2001 63.90
2002 61.30
2003 58.90
2004 57.20
2005 54.80
2006 52.90
2007 50.70
2008 48.60
2009 46.50
2010 44.30
2011 42.30
2012 40.30
2013 38.30
2014 36.50
2015 34.70
2016 33.00
2017 31.30
2018 29.80
2019 28.40
2020 27.20

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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