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

The value for Mortality rate, infant, female (per 1,000 live births) in Kiribati was 35.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 124.30 in 1960 and a minimum value of 35.10 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 124.30
1961 121.50
1962 118.30
1963 114.60
1964 111.00
1965 107.10
1966 103.40
1967 99.70
1968 96.30
1969 92.90
1970 89.80
1971 87.00
1972 84.60
1973 82.70
1974 81.40
1975 80.30
1976 79.60
1977 78.90
1978 78.30
1979 77.40
1980 76.60
1981 75.70
1982 74.60
1983 73.40
1984 72.10
1985 70.60
1986 68.90
1987 67.10
1988 65.00
1989 62.80
1990 60.70
1991 58.50
1992 56.60
1993 54.80
1994 53.30
1995 52.00
1996 50.80
1997 49.70
1998 48.60
1999 47.60
2000 46.50
2001 45.60
2002 45.00
2003 44.50
2004 44.40
2005 44.50
2006 44.70
2007 45.00
2008 45.00
2009 44.90
2010 44.40
2011 43.70
2012 43.00
2013 42.00
2014 41.20
2015 40.20
2016 39.10
2017 38.10
2018 37.10
2019 36.10
2020 35.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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