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

The value for Mortality rate, infant, male (per 1,000 live births) in Nepal was 25.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 226.30 in 1960 and a minimum value of 25.70 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 226.30
1961 223.40
1962 219.90
1963 215.90
1964 211.50
1965 206.80
1966 202.10
1967 197.50
1968 193.00
1969 188.70
1970 184.60
1971 180.70
1972 176.70
1973 172.90
1974 169.10
1975 165.50
1976 161.90
1977 158.00
1978 154.20
1979 150.00
1980 145.80
1981 141.60
1982 137.40
1983 133.30
1984 128.90
1985 124.60
1986 120.20
1987 115.90
1988 111.40
1989 106.80
1990 102.20
1991 97.50
1992 92.90
1993 88.50
1994 84.40
1995 80.40
1996 76.50
1997 72.90
1998 69.50
1999 66.00
2000 62.80
2001 59.80
2002 56.90
2003 54.20
2004 51.80
2005 49.40
2006 47.20
2007 45.20
2008 43.30
2009 41.40
2010 39.60
2011 37.90
2012 36.30
2013 34.70
2014 33.20
2015 31.70
2016 30.30
2017 28.90
2018 27.80
2019 26.70
2020 25.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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