Uganda - Mortality rate, under-5, male (per 1,000 live births)

The value for Mortality rate, under-5, male (per 1,000 live births) in Uganda was 47.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 236.00 in 1960 and a minimum value of 47.80 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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
1960 236.00
1961 232.30
1962 228.60
1963 224.70
1964 221.10
1965 217.80
1966 214.40
1967 211.00
1968 208.10
1969 205.60
1970 204.30
1971 203.90
1972 204.80
1973 206.80
1974 210.10
1975 214.20
1976 218.80
1977 223.50
1978 227.80
1979 230.50
1980 232.60
1981 230.90
1982 226.20
1983 220.00
1984 213.90
1985 209.20
1986 205.90
1987 203.50
1988 201.40
1989 198.70
1990 194.90
1991 190.60
1992 186.10
1993 182.10
1994 178.90
1995 176.80
1996 174.80
1997 172.00
1998 168.10
1999 163.20
2000 157.00
2001 149.60
2002 141.50
2003 132.90
2004 124.00
2005 115.50
2006 107.60
2007 100.40
2008 93.90
2009 88.30
2010 82.80
2011 77.80
2012 72.60
2013 68.00
2014 64.30
2015 61.00
2016 57.60
2017 54.80
2018 52.20
2019 49.90
2020 47.80

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