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

The value for Mortality rate, infant, male (per 1,000 live births) in Kenya was 34.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 123.60 in 1960 and a minimum value of 34.30 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 123.60
1961 119.20
1962 115.30
1963 112.00
1964 109.30
1965 107.10
1966 105.20
1967 103.50
1968 101.70
1969 99.90
1970 97.90
1971 95.90
1972 93.90
1973 91.70
1974 89.50
1975 87.00
1976 84.70
1977 82.30
1978 79.80
1979 77.40
1980 75.30
1981 73.30
1982 71.40
1983 69.90
1984 68.70
1985 67.80
1986 67.30
1987 67.30
1988 67.80
1989 68.70
1990 69.90
1991 71.40
1992 72.60
1993 73.30
1994 73.50
1995 73.00
1996 72.10
1997 70.60
1998 69.00
1999 67.10
2000 65.00
2001 62.80
2002 60.40
2003 57.90
2004 55.40
2005 52.50
2006 49.90
2007 47.80
2008 45.30
2009 44.30
2010 43.10
2011 42.20
2012 41.90
2013 41.10
2014 40.00
2015 38.70
2016 37.80
2017 37.00
2018 36.00
2019 35.10
2020 34.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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