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

The value for Mortality rate, under-5, female (per 1,000 live births) in Tonga was 10.10 as of 2020. As the graph below shows, over the past 57 years this indicator reached a maximum value of 71.70 in 1963 and a minimum value of 10.10 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
1963 71.70
1964 66.90
1965 62.60
1966 58.40
1967 54.40
1968 50.70
1969 47.20
1970 44.00
1971 41.20
1972 38.60
1973 36.40
1974 34.30
1975 32.60
1976 30.90
1977 29.50
1978 28.20
1979 26.90
1980 25.90
1981 25.00
1982 24.20
1983 23.60
1984 23.00
1985 22.50
1986 21.90
1987 21.40
1988 20.70
1989 20.10
1990 19.40
1991 18.70
1992 18.00
1993 17.40
1994 16.90
1995 16.50
1996 16.10
1997 15.80
1998 15.50
1999 15.20
2000 14.80
2001 14.40
2002 14.00
2003 13.60
2004 13.20
2005 12.90
2006 12.60
2007 12.30
2008 12.00
2009 11.70
2010 11.50
2011 11.40
2012 11.20
2013 11.10
2014 11.00
2015 10.90
2016 10.80
2017 10.70
2018 10.50
2019 10.30
2020 10.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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