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

The value for Mortality rate, under-5, female (per 1,000 live births) in Kiribati was 45.00 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 190.00 in 1960 and a minimum value of 45.00 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 190.00
1961 185.30
1962 180.10
1963 174.30
1964 168.10
1965 161.60
1966 155.40
1967 149.20
1968 143.30
1969 137.90
1970 132.90
1971 128.40
1972 124.50
1973 121.40
1974 119.20
1975 117.50
1976 116.20
1977 115.30
1978 114.30
1979 113.00
1980 111.50
1981 109.90
1982 108.30
1983 106.30
1984 104.20
1985 101.80
1986 99.10
1987 96.10
1988 92.70
1989 89.20
1990 85.60
1991 82.20
1992 79.00
1993 76.20
1994 73.70
1995 71.50
1996 69.50
1997 67.70
1998 66.10
1999 64.30
2000 62.60
2001 61.20
2002 60.00
2003 59.30
2004 59.10
2005 59.30
2006 59.70
2007 60.10
2008 60.20
2009 59.80
2010 59.10
2011 58.00
2012 56.90
2013 55.50
2014 54.10
2015 52.70
2016 51.10
2017 49.50
2018 47.90
2019 46.50
2020 45.00

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