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

The value for Mortality rate, infant, male (per 1,000 live births) in Kiribati was 43.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 143.00 in 1960 and a minimum value of 43.10 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 143.00
1961 139.80
1962 136.20
1963 132.30
1964 128.20
1965 124.00
1966 119.90
1967 115.90
1968 112.00
1969 108.30
1970 104.90
1971 101.90
1972 99.30
1973 97.20
1974 95.70
1975 94.60
1976 93.80
1977 93.10
1978 92.30
1979 91.50
1980 90.50
1981 89.50
1982 88.30
1983 87.00
1984 85.50
1985 83.80
1986 81.90
1987 79.80
1988 77.50
1989 75.00
1990 72.50
1991 70.10
1992 67.90
1993 66.00
1994 64.30
1995 62.80
1996 61.50
1997 60.20
1998 59.00
1999 57.70
2000 56.60
2001 55.50
2002 54.70
2003 54.20
2004 54.00
2005 54.20
2006 54.40
2007 54.60
2008 54.70
2009 54.50
2010 53.90
2011 53.10
2012 52.20
2013 51.20
2014 50.20
2015 49.00
2016 47.90
2017 46.70
2018 45.50
2019 44.30
2020 43.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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