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

The value for Mortality rate, under-5, female (per 1,000 live births) in Ethiopia was 42.90 as of 2020. As the graph below shows, over the past 54 years this indicator reached a maximum value of 234.40 in 1966 and a minimum value of 42.90 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
1966 234.40
1967 233.80
1968 233.50
1969 232.90
1970 232.40
1971 231.90
1972 231.70
1973 231.20
1974 231.00
1975 230.70
1976 230.10
1977 229.50
1978 228.60
1979 227.10
1980 225.10
1981 222.40
1982 219.10
1983 215.50
1984 211.60
1985 207.70
1986 204.10
1987 200.40
1988 196.50
1989 192.50
1990 188.20
1991 183.50
1992 178.20
1993 172.20
1994 166.00
1995 159.50
1996 153.10
1997 146.90
1998 141.10
1999 135.40
2000 129.60
2001 123.80
2002 117.70
2003 111.60
2004 105.40
2005 99.20
2006 93.40
2007 88.00
2008 82.90
2009 78.30
2010 73.90
2011 69.80
2012 65.90
2013 62.20
2014 58.80
2015 55.50
2016 52.40
2017 49.60
2018 47.00
2019 44.80
2020 42.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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