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

The value for Mortality rate, infant, female (per 1,000 live births) in El Salvador was 9.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 115.50 in 1960 and a minimum value of 9.90 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 115.50
1961 113.30
1962 111.10
1963 109.00
1964 106.90
1965 104.90
1966 102.90
1967 100.90
1968 99.10
1969 97.10
1970 95.00
1971 93.10
1972 91.10
1973 88.80
1974 86.50
1975 84.00
1976 81.20
1977 78.50
1978 75.50
1979 72.40
1980 77.00
1981 66.20
1982 63.00
1983 60.00
1984 56.90
1985 54.00
1986 51.30
1987 48.80
1988 46.40
1989 44.20
1990 42.10
1991 40.10
1992 38.10
1993 36.20
1994 34.40
1995 32.60
1996 30.80
1997 29.10
1998 27.50
1999 26.10
2000 24.70
2001 23.40
2002 22.20
2003 21.10
2004 20.00
2005 19.00
2006 18.10
2007 17.20
2008 16.40
2009 15.60
2010 14.80
2011 14.10
2012 13.50
2013 12.90
2014 12.40
2015 11.90
2016 11.50
2017 11.00
2018 10.60
2019 10.30
2020 9.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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