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

The value for Mortality rate, infant, female (per 1,000 live births) in Lesotho was 62.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 132.30 in 1965 and a minimum value of 59.90 in 1992.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female live births in a given 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 130.90
1961 130.40
1962 130.60
1963 131.30
1964 132.00
1965 132.30
1966 132.20
1967 131.40
1968 130.00
1969 128.00
1970 125.70
1971 123.10
1972 120.30
1973 117.30
1974 114.10
1975 110.30
1976 106.20
1977 101.90
1978 97.50
1979 93.10
1980 88.70
1981 84.60
1982 80.50
1983 76.90
1984 73.70
1985 70.80
1986 68.10
1987 65.80
1988 63.80
1989 62.20
1990 60.90
1991 60.10
1992 59.90
1993 60.30
1994 61.20
1995 61.90
1996 62.20
1997 62.30
1998 62.30
1999 62.50
2000 62.90
2001 63.40
2002 64.00
2003 64.90
2004 65.60
2005 66.40
2006 66.80
2007 66.20
2008 69.30
2009 66.20
2010 63.70
2011 61.90
2012 63.00
2013 63.80
2014 64.80
2015 65.40
2016 65.60
2017 65.80
2018 64.90
2019 64.30
2020 62.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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