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

The value for Mortality rate, infant, female (per 1,000 live births) in Micronesia was 17.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 78.90 in 1960 and a minimum value of 17.90 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 78.90
1961 75.90
1962 72.90
1963 70.10
1964 67.50
1965 64.90
1966 62.50
1967 60.10
1968 57.80
1969 55.80
1970 53.80
1971 51.90
1972 50.30
1973 48.70
1974 47.20
1975 45.90
1976 44.80
1977 43.60
1978 42.70
1979 41.80
1980 41.10
1981 40.60
1982 40.10
1983 39.60
1984 39.00
1985 38.30
1986 37.40
1987 36.50
1988 35.50
1989 34.50
1990 33.60
1991 32.80
1992 32.10
1993 31.50
1994 30.90
1995 30.20
1996 29.50
1997 28.70
1998 27.80
1999 27.00
2000 26.30
2001 25.60
2002 25.00
2003 24.60
2004 24.40
2005 24.30
2006 24.20
2007 24.10
2008 24.00
2009 23.70
2010 23.40
2011 22.90
2012 22.30
2013 21.80
2014 21.30
2015 20.70
2016 20.00
2017 19.50
2018 18.90
2019 18.40
2020 17.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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