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

The value for Mortality rate, under-5, male (per 1,000 live births) in Liberia was 84.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 329.00 in 1961 and a minimum value of 84.10 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 328.80
1961 329.00
1962 328.80
1963 327.90
1964 326.30
1965 323.60
1966 320.50
1967 316.60
1968 312.10
1969 306.90
1970 301.70
1971 296.80
1972 291.80
1973 287.00
1974 282.20
1975 277.30
1976 272.70
1977 268.50
1978 264.70
1979 261.20
1980 257.90
1981 254.90
1982 252.40
1983 251.20
1984 251.10
1985 252.80
1986 256.60
1987 262.00
1988 268.00
1989 273.90
1990 278.60
1991 280.60
1992 279.60
1993 275.70
1994 269.20
1995 260.50
1996 250.10
1997 238.50
1998 226.00
1999 213.20
2000 200.10
2001 186.60
2002 173.20
2003 160.30
2004 148.40
2005 137.70
2006 128.70
2007 121.30
2008 115.30
2009 110.50
2010 106.50
2011 103.30
2012 100.70
2013 98.40
2014 98.40
2015 94.50
2016 92.20
2017 90.40
2018 88.40
2019 86.30
2020 84.10

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