São Tomé and Principe - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in São Tomé and Principe was 14.30 as of 2020. As the graph below shows, over the past 55 years this indicator reached a maximum value of 108.30 in 1986 and a minimum value of 14.30 in 2020.

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
1965 89.70
1966 86.80
1967 84.20
1968 82.30
1969 80.90
1970 80.30
1971 80.30
1972 80.60
1973 81.30
1974 82.00
1975 82.40
1976 82.80
1977 83.20
1978 83.70
1979 84.30
1980 85.00
1981 86.20
1982 87.70
1983 89.60
1984 91.80
1985 93.90
1986 108.30
1987 97.90
1988 99.60
1989 100.90
1990 102.00
1991 102.80
1992 103.00
1993 102.40
1994 101.00
1995 98.70
1996 95.50
1997 91.50
1998 86.90
1999 82.00
2000 76.80
2001 71.40
2002 66.10
2003 60.80
2004 55.70
2005 51.00
2006 46.60
2007 42.50
2008 38.90
2009 35.50
2010 32.50
2011 29.60
2012 27.00
2013 24.60
2014 22.50
2015 20.50
2016 18.80
2017 17.30
2018 16.10
2019 15.10
2020 14.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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