Seychelles - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Seychelles was 11.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 70.70 in 1960 and a minimum value of 11.10 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female live births in a given 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 70.70
1961 69.90
1962 69.00
1963 67.90
1964 66.70
1965 65.20
1966 63.40
1967 61.40
1968 58.90
1969 56.10
1970 53.20
1971 50.20
1972 47.10
1973 43.90
1974 40.70
1975 37.50
1976 34.30
1977 31.30
1978 28.40
1979 25.80
1980 23.40
1981 21.30
1982 19.60
1983 18.10
1984 16.90
1985 15.80
1986 15.00
1987 14.40
1988 13.80
1989 13.20
1990 12.80
1991 12.40
1992 12.20
1993 11.90
1994 11.70
1995 11.60
1996 11.50
1997 11.40
1998 11.40
1999 11.40
2000 11.30
2001 11.30
2002 11.30
2003 11.30
2004 11.30
2005 11.20
2006 11.20
2007 11.20
2008 11.20
2009 11.30
2010 11.40
2011 11.40
2012 11.50
2013 11.60
2014 11.70
2015 11.80
2016 11.90
2017 11.80
2018 11.60
2019 11.40
2020 11.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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