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

The value for Mortality rate, under-5, female (per 1,000 live births) in Nepal was 25.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 326.20 in 1960 and a minimum value of 25.90 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 326.20
1961 322.40
1962 318.00
1963 312.30
1964 306.20
1965 299.80
1966 293.20
1967 286.40
1968 279.50
1969 273.20
1970 267.00
1971 261.20
1972 255.70
1973 250.30
1974 245.00
1975 239.50
1976 233.90
1977 227.90
1978 221.70
1979 215.20
1980 208.80
1981 202.20
1982 195.60
1983 188.80
1984 181.90
1985 174.90
1986 167.80
1987 160.40
1988 152.90
1989 145.40
1990 137.90
1991 130.60
1992 123.70
1993 117.00
1994 110.50
1995 104.20
1996 98.30
1997 92.50
1998 87.00
1999 81.80
2000 76.80
2001 72.20
2002 67.90
2003 63.90
2004 60.10
2005 56.70
2006 53.60
2007 50.70
2008 47.90
2009 45.50
2010 43.20
2011 40.90
2012 38.80
2013 36.80
2014 34.80
2015 33.00
2016 31.30
2017 29.70
2018 28.30
2019 27.00
2020 25.90

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