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

The value for Mortality rate, under-5, male (per 1,000 live births) in Hungary was 4.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 59.50 in 1960 and a minimum value of 4.40 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 59.50
1961 56.40
1962 53.90
1963 52.30
1964 50.80
1965 49.20
1966 47.50
1967 46.20
1968 45.10
1969 43.80
1970 42.70
1971 42.00
1972 42.40
1973 42.90
1974 41.90
1975 39.20
1976 35.70
1977 32.60
1978 30.10
1979 28.00
1980 26.30
1981 25.20
1982 24.60
1983 24.50
1984 24.40
1985 24.00
1986 23.30
1987 22.00
1988 20.50
1989 19.50
1990 19.10
1991 18.50
1992 17.40
1993 16.00
1994 14.70
1995 13.70
1996 13.10
1997 12.60
1998 12.20
1999 11.70
2000 11.10
2001 10.40
2002 9.80
2003 9.10
2004 8.60
2005 8.20
2006 7.80
2007 7.40
2008 7.00
2009 6.70
2010 6.50
2011 6.30
2012 6.20
2013 6.10
2014 5.80
2015 5.50
2016 5.10
2017 4.80
2018 4.60
2019 4.50
2020 4.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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