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

The value for Mortality rate, under-5, male (per 1,000 live births) in Ghana was 49.20 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 218.40 in 1960 and a minimum value of 49.20 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 218.40
1961 216.30
1962 214.70
1963 213.50
1964 212.60
1965 212.40
1966 212.40
1967 212.70
1968 212.80
1969 212.70
1970 212.30
1971 211.00
1972 208.80
1973 205.20
1974 200.80
1975 195.50
1976 190.20
1977 185.20
1978 181.00
1979 177.80
1980 175.50
1981 174.00
1982 172.40
1983 170.30
1984 167.40
1985 163.30
1986 158.20
1987 152.50
1988 146.40
1989 140.50
1990 135.30
1991 131.10
1992 127.80
1993 125.40
1994 123.60
1995 121.90
1996 120.00
1997 117.70
1998 114.80
1999 111.20
2000 107.10
2001 102.90
2002 99.00
2003 95.60
2004 92.70
2005 89.90
2006 87.40
2007 84.70
2008 81.80
2009 78.60
2010 75.20
2011 71.70
2012 68.40
2013 65.20
2014 62.30
2015 59.70
2016 57.20
2017 55.00
2018 52.90
2019 51.00
2020 49.20

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