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

The value for Mortality rate, under-5, male (per 1,000 live births) in Seychelles was 15.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 108.60 in 1960 and a minimum value of 14.50 in 1999.

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 108.60
1961 107.30
1962 105.80
1963 104.00
1964 102.00
1965 99.40
1966 96.40
1967 92.80
1968 88.70
1969 84.00
1970 79.00
1971 73.90
1972 68.80
1973 63.80
1974 58.70
1975 53.80
1976 49.00
1977 44.40
1978 40.00
1979 36.10
1980 32.70
1981 29.70
1982 27.30
1983 25.20
1984 23.60
1985 22.20
1986 21.00
1987 20.00
1988 19.10
1989 18.40
1990 17.70
1991 17.10
1992 16.50
1993 16.00
1994 15.60
1995 15.30
1996 15.00
1997 14.80
1998 14.60
1999 14.50
2000 14.50
2001 14.50
2002 14.50
2003 14.50
2004 14.50
2005 14.60
2006 14.60
2007 14.80
2008 14.90
2009 15.00
2010 15.10
2011 15.30
2012 15.40
2013 15.60
2014 15.80
2015 15.90
2016 15.90
2017 15.80
2018 15.60
2019 15.30
2020 15.00

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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