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

The value for Mortality rate, under-5, female (per 1,000 live births) in Maldives was 5.90 as of 2020. As the graph below shows, over the past 55 years this indicator reached a maximum value of 292.80 in 1965 and a minimum value of 5.90 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 292.80
1966 284.10
1967 275.00
1968 265.90
1969 257.10
1970 247.60
1971 237.20
1972 226.10
1973 214.80
1974 203.30
1975 191.90
1976 180.90
1977 170.30
1978 160.40
1979 151.10
1980 142.40
1981 134.20
1982 126.70
1983 119.60
1984 113.00
1985 106.70
1986 100.80
1987 95.10
1988 89.70
1989 84.60
1990 79.80
1991 75.20
1992 70.60
1993 66.20
1994 61.70
1995 57.20
1996 52.70
1997 48.20
1998 43.70
1999 39.40
2000 35.20
2001 31.10
2002 27.40
2003 24.10
2004 24.20
2005 19.10
2006 17.20
2007 15.60
2008 14.30
2009 13.30
2010 12.40
2011 11.60
2012 10.80
2013 10.10
2014 9.50
2015 8.80
2016 8.20
2017 7.50
2018 6.90
2019 6.40
2020 5.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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