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

The value for Mortality rate, infant, male (per 1,000 live births) in Liberia was 63.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 226.10 in 1961 and a minimum value of 63.60 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male live births in a given 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 225.80
1961 226.10
1962 225.70
1963 225.30
1964 224.20
1965 222.40
1966 220.30
1967 217.40
1968 214.10
1969 210.50
1970 206.90
1971 203.40
1972 199.80
1973 196.50
1974 193.00
1975 189.60
1976 186.40
1977 183.50
1978 181.00
1979 178.70
1980 176.40
1981 174.20
1982 172.60
1983 171.60
1984 171.50
1985 172.60
1986 175.00
1987 178.60
1988 182.70
1989 186.70
1990 189.90
1991 191.30
1992 190.60
1993 187.80
1994 183.30
1995 177.40
1996 170.40
1997 162.60
1998 154.40
1999 146.20
2000 137.80
2001 129.20
2002 120.90
2003 112.90
2004 105.40
2005 98.50
2006 92.70
2007 87.80
2008 83.90
2009 80.80
2010 78.10
2011 76.10
2012 74.40
2013 72.90
2014 71.90
2015 70.20
2016 68.90
2017 67.60
2018 66.30
2019 65.00
2020 63.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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