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

The value for Mortality rate, under-5, male (per 1,000 live births) in Nepal was 30.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 324.00 in 1960 and a minimum value of 30.30 in 2020.

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 324.00
1961 320.20
1962 315.50
1963 309.80
1964 303.70
1965 297.10
1966 290.60
1967 284.00
1968 277.50
1969 271.10
1970 265.10
1971 259.30
1972 253.50
1973 248.20
1974 242.60
1975 237.20
1976 231.70
1977 226.00
1978 220.00
1979 213.60
1980 207.10
1981 200.60
1982 194.10
1983 187.60
1984 181.20
1985 174.50
1986 167.80
1987 160.90
1988 153.90
1989 146.80
1990 139.80
1991 132.80
1992 125.90
1993 119.40
1994 113.20
1995 107.30
1996 101.60
1997 96.30
1998 91.20
1999 86.20
2000 81.40
2001 76.90
2002 72.80
2003 68.80
2004 65.30
2005 62.00
2006 58.90
2007 56.10
2008 53.50
2009 50.90
2010 48.50
2011 46.20
2012 44.00
2013 41.80
2014 39.90
2015 38.00
2016 36.10
2017 34.30
2018 32.90
2019 31.50
2020 30.30

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