Seychelles - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Seychelles was 13.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 104.50 in 1960 and a minimum value of 13.70 in 2001.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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 104.50
1961 103.10
1962 101.60
1963 99.90
1964 97.90
1965 95.40
1966 92.40
1967 88.90
1968 84.90
1969 80.40
1970 75.50
1971 70.50
1972 65.50
1973 60.50
1974 55.60
1975 50.80
1976 46.10
1977 41.60
1978 37.50
1979 33.70
1980 30.40
1981 27.60
1982 25.20
1983 23.30
1984 21.70
1985 20.40
1986 19.30
1987 18.40
1988 17.60
1989 16.90
1990 16.30
1991 15.80
1992 15.30
1993 14.90
1994 14.60
1995 14.40
1996 14.10
1997 14.00
1998 13.90
1999 13.80
2000 13.80
2001 13.70
2002 13.70
2003 13.70
2004 13.70
2005 13.70
2006 13.80
2007 13.80
2008 13.90
2009 14.00
2010 14.10
2011 14.20
2012 14.40
2013 14.50
2014 14.70
2015 14.80
2016 14.80
2017 14.70
2018 14.50
2019 14.30
2020 13.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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