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

The value for Mortality rate, under-5, female (per 1,000 live births) in El Salvador was 11.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 175.50 in 1960 and a minimum value of 11.50 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 175.50
1961 171.70
1962 168.20
1963 164.70
1964 161.20
1965 157.80
1966 154.40
1967 151.20
1968 148.00
1969 144.80
1970 141.40
1971 138.20
1972 134.70
1973 131.20
1974 127.30
1975 123.30
1976 118.90
1977 114.30
1978 109.50
1979 104.50
1980 118.70
1981 94.20
1982 89.10
1983 84.10
1984 79.10
1985 74.40
1986 70.00
1987 65.80
1988 62.10
1989 58.60
1990 55.30
1991 52.20
1992 49.30
1993 46.50
1994 43.70
1995 41.00
1996 38.50
1997 36.10
1998 33.90
1999 31.80
2000 30.00
2001 28.20
2002 26.70
2003 25.20
2004 23.80
2005 22.50
2006 21.40
2007 20.20
2008 19.20
2009 18.30
2010 17.30
2011 16.50
2012 15.70
2013 15.00
2014 14.40
2015 13.90
2016 13.30
2017 12.80
2018 12.40
2019 11.90
2020 11.50

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