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

The value for Mortality rate, under-5, male (per 1,000 live births) in Lesotho was 96.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 197.50 in 1965 and a minimum value of 90.50 in 1991.

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 196.70
1961 195.70
1962 195.70
1963 196.50
1964 197.10
1965 197.50
1966 197.10
1967 195.90
1968 193.60
1969 190.40
1970 186.90
1971 182.90
1972 178.80
1973 174.30
1974 169.30
1975 163.80
1976 157.60
1977 151.20
1978 144.60
1979 138.00
1980 131.40
1981 125.00
1982 119.20
1983 113.80
1984 109.00
1985 104.60
1986 100.70
1987 97.50
1988 94.60
1989 92.40
1990 91.00
1991 90.50
1992 91.10
1993 93.10
1994 96.30
1995 100.30
1996 104.10
1997 107.30
1998 109.90
1999 112.10
2000 114.30
2001 116.40
2002 118.40
2003 120.60
2004 122.40
2005 124.10
2006 124.60
2007 122.30
2008 121.20
2009 111.90
2010 104.00
2011 101.10
2012 100.00
2013 99.90
2014 101.70
2015 102.10
2016 99.00
2017 98.50
2018 97.90
2019 98.30
2020 96.80

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