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

The value for Mortality rate, under-5 (per 1,000 live births) in Lesotho was 89.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 188.60 in 1965 and a minimum value of 83.50 in 1991.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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 187.30
1961 186.30
1962 186.60
1963 187.30
1964 188.10
1965 188.60
1966 188.30
1967 186.90
1968 184.80
1969 181.90
1970 178.30
1971 174.40
1972 170.40
1973 166.00
1974 161.20
1975 155.70
1976 149.70
1977 143.40
1978 137.10
1979 130.60
1980 124.00
1981 117.80
1982 112.00
1983 106.60
1984 101.90
1985 97.60
1986 93.80
1987 90.50
1988 87.70
1989 85.50
1990 84.00
1991 83.50
1992 84.00
1993 86.10
1994 89.30
1995 93.10
1996 96.90
1997 100.00
1998 102.60
1999 104.70
2000 106.90
2001 108.80
2002 110.70
2003 112.70
2004 114.50
2005 116.10
2006 116.50
2007 114.30
2008 113.00
2009 104.20
2010 96.40
2011 93.90
2012 92.70
2013 92.60
2014 94.20
2015 94.60
2016 91.50
2017 91.00
2018 90.60
2019 90.90
2020 89.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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