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

The value for Mortality rate, under-5, male (per 1,000 live births) in Syrian Arab Republic was 24.40 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 20.60 in 2009.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 161.70
1962 154.50
1963 147.70
1964 141.60
1965 135.60
1966 129.70
1967 123.70
1968 117.70
1969 111.60
1970 105.80
1971 100.30
1972 95.10
1973 90.40
1974 86.00
1975 81.70
1976 77.70
1977 73.70
1978 69.90
1979 66.20
1980 62.70
1981 65.60
1982 72.80
1983 53.20
1984 50.60
1985 48.20
1986 46.00
1987 44.20
1988 42.50
1989 40.90
1990 39.40
1991 38.00
1992 36.40
1993 34.80
1994 33.30
1995 31.80
1996 30.30
1997 28.90
1998 27.50
1999 26.30
2000 25.20
2001 24.30
2002 23.40
2003 22.70
2004 22.10
2005 21.60
2006 21.20
2007 20.90
2008 20.70
2009 20.60
2010 20.70
2011 21.90
2012 38.80
2013 47.10
2014 48.90
2015 43.40
2016 41.40
2017 25.50
2018 25.40
2019 24.20
2020 24.40

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