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

The value for Mortality rate, under-5, male (per 1,000 live births) in Portugal was 3.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 121.20 in 1960 and a minimum value of 3.60 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 121.20
1961 117.10
1962 111.10
1963 103.70
1964 96.70
1965 91.00
1966 86.60
1967 83.50
1968 81.10
1969 78.00
1970 73.80
1971 68.80
1972 63.30
1973 57.70
1974 52.80
1975 48.20
1976 43.90
1977 39.90
1978 36.10
1979 33.10
1980 30.70
1981 28.70
1982 27.00
1983 25.40
1984 24.00
1985 22.70
1986 21.50
1987 20.20
1988 18.90
1989 17.60
1990 16.40
1991 15.10
1992 13.80
1993 12.60
1994 11.60
1995 10.70
1996 10.10
1997 9.50
1998 9.00
1999 8.40
2000 7.90
2001 7.30
2002 6.60
2003 6.00
2004 5.50
2005 5.10
2006 4.80
2007 4.50
2008 4.40
2009 4.30
2010 4.20
2011 4.10
2012 4.00
2013 4.00
2014 4.00
2015 4.00
2016 4.00
2017 4.00
2018 3.90
2019 3.80
2020 3.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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