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

The value for Mortality rate, under-5, male (per 1,000 live births) in Sierra Leone was 114.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 404.00 in 1960 and a minimum value of 114.60 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 404.00
1961 398.30
1962 392.60
1963 386.60
1964 380.30
1965 374.50
1966 368.40
1967 362.50
1968 356.90
1969 351.10
1970 345.60
1971 340.30
1972 335.10
1973 330.10
1974 325.10
1975 320.10
1976 315.50
1977 311.20
1978 307.00
1979 302.80
1980 299.10
1981 295.70
1982 291.90
1983 288.80
1984 285.80
1985 282.90
1986 280.20
1987 277.60
1988 275.30
1989 273.10
1990 271.10
1991 269.30
1992 267.30
1993 265.00
1994 262.20
1995 258.70
1996 254.60
1997 250.30
1998 245.40
1999 240.00
2000 234.60
2001 228.80
2002 223.00
2003 216.90
2004 210.40
2005 203.90
2006 197.00
2007 190.00
2008 182.70
2009 175.30
2010 168.20
2011 161.30
2012 154.70
2013 148.50
2014 146.60
2015 147.60
2016 132.60
2017 127.70
2018 123.10
2019 118.70
2020 114.60

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