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

The value for Mortality rate, under-5, female (per 1,000 live births) in Sierra Leone was 100.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 374.90 in 1960 and a minimum value of 100.90 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 374.90
1961 369.10
1962 363.60
1963 358.10
1964 352.30
1965 346.60
1966 340.70
1967 334.90
1968 329.40
1969 323.90
1970 318.70
1971 313.70
1972 308.80
1973 304.10
1974 299.60
1975 294.80
1976 290.50
1977 286.10
1978 282.10
1979 278.30
1980 274.80
1981 271.40
1982 268.00
1983 264.90
1984 262.00
1985 259.20
1986 256.60
1987 254.10
1988 251.60
1989 249.40
1990 247.40
1991 245.40
1992 243.10
1993 240.90
1994 238.50
1995 235.60
1996 232.40
1997 228.50
1998 224.10
1999 219.60
2000 214.50
2001 209.70
2002 204.30
2003 198.80
2004 193.00
2005 186.80
2006 180.50
2007 173.70
2008 166.70
2009 159.80
2010 152.60
2011 145.80
2012 139.40
2013 133.40
2014 131.60
2015 132.60
2016 117.80
2017 113.30
2018 109.00
2019 104.80
2020 100.90

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