Syrian Arab Republic - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in Syrian Arab Republic was 20.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 169.90 in 1960 and a minimum value of 17.00 in 2008.

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 169.90
1961 161.30
1962 153.60
1963 146.70
1964 140.30
1965 134.00
1966 127.90
1967 121.60
1968 115.40
1969 109.20
1970 103.20
1971 97.40
1972 92.20
1973 87.20
1974 82.50
1975 78.00
1976 73.70
1977 69.30
1978 65.10
1979 61.20
1980 57.50
1981 60.40
1982 67.50
1983 47.90
1984 45.20
1985 42.70
1986 40.60
1987 38.70
1988 36.90
1989 35.30
1990 33.80
1991 32.40
1992 30.90
1993 29.50
1994 28.00
1995 26.60
1996 25.20
1997 23.90
1998 22.70
1999 21.60
2000 20.70
2001 19.90
2002 19.20
2003 18.60
2004 18.10
2005 17.70
2006 17.40
2007 17.10
2008 17.00
2009 17.00
2010 17.00
2011 18.20
2012 35.10
2013 43.30
2014 45.10
2015 39.50
2016 37.40
2017 21.40
2018 21.30
2019 20.00
2020 20.30

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