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

The value for Mortality rate, infant, male (per 1,000 live births) in El Salvador was 12.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 133.60 in 1960 and a minimum value of 12.20 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 133.60
1961 131.20
1962 128.80
1963 126.40
1964 124.20
1965 122.00
1966 119.90
1967 117.80
1968 115.80
1969 113.60
1970 111.50
1971 109.20
1972 106.80
1973 104.40
1974 101.60
1975 98.80
1976 95.60
1977 92.30
1978 88.80
1979 85.30
1980 89.30
1981 78.00
1982 74.40
1983 70.90
1984 67.40
1985 64.10
1986 61.00
1987 58.00
1988 55.30
1989 52.80
1990 50.40
1991 48.00
1992 45.70
1993 43.50
1994 41.30
1995 39.20
1996 37.10
1997 35.20
1998 33.30
1999 31.60
2000 30.00
2001 28.50
2002 27.10
2003 25.70
2004 24.50
2005 23.30
2006 22.20
2007 21.10
2008 20.10
2009 19.10
2010 18.20
2011 17.40
2012 16.60
2013 15.90
2014 15.20
2015 14.60
2016 14.10
2017 13.60
2018 13.10
2019 12.60
2020 12.20

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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