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

The value for Mortality rate, under-5, male (per 1,000 live births) in Brazil was 16.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 182.00 in 1960 and a minimum value of 16.40 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 182.00
1961 177.20
1962 172.70
1963 168.30
1964 164.50
1965 160.80
1966 157.50
1967 154.30
1968 151.10
1969 147.60
1970 144.10
1971 140.50
1972 136.90
1973 133.30
1974 129.60
1975 125.90
1976 122.10
1977 118.20
1978 113.90
1979 109.30
1980 104.50
1981 99.70
1982 95.20
1983 91.10
1984 87.30
1985 83.90
1986 80.60
1987 77.60
1988 74.60
1989 71.90
1990 69.10
1991 66.10
1992 63.00
1993 59.60
1994 56.20
1995 52.90
1996 49.70
1997 46.70
1998 43.80
1999 41.10
2000 38.60
2001 36.20
2002 33.80
2003 31.60
2004 29.60
2005 27.60
2006 25.90
2007 24.30
2008 23.00
2009 21.80
2010 20.80
2011 19.90
2012 19.20
2013 18.60
2014 18.20
2015 17.80
2016 18.50
2017 17.10
2018 16.90
2019 16.60
2020 16.40

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