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

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. 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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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.
Publisher
The World Bank
Origin
Republic of Kenya
Records
63
Source
Kenya | Mortality rate, under-5, female (per 1,000 live births)
1960 188.9
1961 181
1962 174
1963 168.2
1964 163.2
1965 159.1
1966 155.7
1967 152.6
1968 149.7
1969 146.6
1970 143.4
1971 140
1972 136.5
1973 132.7
1974 128.8
1975 124.8
1976 120.6
1977 116.4
1978 112.2
1979 108.1
1980 104.4
1981 100.9
1982 97.8
1983 95.1
1984 92.9
1985 91.3
1986 90.6
1987 90.6
1988 91.6
1989 93.5
1990 96
1991 98.7
1992 101.3
1993 103.3
1994 104.4
1995 104.6
1996 103.7
1997 102.1
1998 99.8
1999 96.7
2000 92.9
2001 88.8
2002 84.4
2003 80
2004 75.6
2005 71
2006 66.8
2007 62.9
2008 58.3
2009 54.3
2010 51.7
2011 49.8
2012 48.1
2013 46
2014 44.1
2015 42
2016 40.1
2017 38.7
2018 37.2
2019 35.9
2020 35.1
2021 33.7
2022

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

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. 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.
Publisher
The World Bank
Origin
Republic of Kenya
Records
63
Source