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

The value for Mortality rate, under-5, female (per 1,000 live births) in Lesotho was 81.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 179.00 in 1965 and a minimum value of 76.10 in 1991.

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 177.40
1961 176.60
1962 176.90
1963 177.70
1964 178.60
1965 179.00
1966 178.80
1967 177.60
1968 175.50
1969 172.70
1970 169.30
1971 165.60
1972 161.70
1973 157.40
1974 152.60
1975 147.20
1976 141.50
1977 135.20
1978 128.90
1979 122.50
1980 116.30
1981 110.20
1982 104.40
1983 99.10
1984 94.40
1985 90.20
1986 86.40
1987 83.10
1988 80.40
1989 78.20
1990 76.70
1991 76.10
1992 76.60
1993 78.60
1994 81.80
1995 85.70
1996 89.40
1997 92.40
1998 94.90
1999 97.00
2000 99.00
2001 100.90
2002 102.70
2003 104.50
2004 106.20
2005 107.60
2006 107.90
2007 105.90
2008 104.50
2009 96.00
2010 88.60
2011 86.10
2012 84.80
2013 84.80
2014 86.50
2015 86.70
2016 83.40
2017 82.90
2018 82.70
2019 83.20
2020 81.90

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