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

The value for Mortality rate, infant, male (per 1,000 live births) in Brazil was 14.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 140.00 in 1960 and a minimum value of 14.60 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 140.00
1961 136.70
1962 133.50
1963 130.40
1964 127.60
1965 125.00
1966 122.60
1967 120.40
1968 118.10
1969 115.60
1970 113.10
1971 110.50
1972 107.80
1973 105.30
1974 102.60
1975 99.90
1976 97.20
1977 94.20
1978 91.20
1979 87.80
1980 84.40
1981 81.00
1982 77.60
1983 74.50
1984 71.80
1985 69.10
1986 66.70
1987 64.40
1988 62.20
1989 60.20
1990 58.00
1991 55.80
1992 53.40
1993 50.80
1994 48.10
1995 45.50
1996 42.90
1997 40.50
1998 38.10
1999 35.90
2000 33.80
2001 31.80
2002 29.80
2003 28.00
2004 26.30
2005 24.60
2006 23.10
2007 21.70
2008 20.60
2009 19.50
2010 18.60
2011 17.80
2012 17.20
2013 16.70
2014 16.30
2015 15.90
2016 16.60
2017 15.30
2018 15.10
2019 14.90
2020 14.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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