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

The value for Mortality rate, under-5, female (per 1,000 live births) in Micronesia was 21.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 116.00 in 1960 and a minimum value of 21.20 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
1960 116.00
1961 111.00
1962 106.20
1963 101.70
1964 97.30
1965 93.20
1966 89.30
1967 85.40
1968 81.70
1969 78.20
1970 75.00
1971 72.00
1972 69.30
1973 66.70
1974 64.40
1975 62.20
1976 60.20
1977 58.50
1978 56.90
1979 55.60
1980 54.60
1981 53.70
1982 52.90
1983 52.20
1984 51.30
1985 50.20
1986 49.00
1987 47.60
1988 46.10
1989 44.50
1990 43.20
1991 42.00
1992 41.00
1993 40.10
1994 39.20
1995 38.30
1996 37.30
1997 36.10
1998 34.90
1999 33.70
2000 32.60
2001 31.70
2002 30.90
2003 30.30
2004 30.00
2005 29.80
2006 29.70
2007 29.70
2008 29.50
2009 29.00
2010 28.50
2011 27.90
2012 27.20
2013 26.40
2014 25.70
2015 24.90
2016 24.10
2017 23.30
2018 22.60
2019 21.90
2020 21.20

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