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

The value for Mortality rate, infant, female (per 1,000 live births) in Brazil was 11.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 115.00 in 1960 and a minimum value of 11.60 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female 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 115.00
1961 112.00
1962 109.00
1963 106.20
1964 103.60
1965 101.30
1966 99.10
1967 97.00
1968 95.00
1969 93.00
1970 90.90
1971 88.80
1972 86.60
1973 84.50
1974 82.40
1975 80.40
1976 78.30
1977 76.00
1978 73.60
1979 71.00
1980 68.40
1981 65.70
1982 63.10
1983 60.60
1984 58.30
1985 56.20
1986 54.30
1987 52.40
1988 50.70
1989 48.90
1990 47.00
1991 45.10
1992 43.00
1993 40.90
1994 38.70
1995 36.40
1996 34.30
1997 32.30
1998 30.30
1999 28.50
2000 26.80
2001 25.10
2002 23.60
2003 22.00
2004 20.60
2005 19.30
2006 18.10
2007 17.10
2008 16.10
2009 15.30
2010 14.60
2011 14.00
2012 13.50
2013 13.10
2014 12.80
2015 12.50
2016 13.30
2017 12.10
2018 11.90
2019 11.70
2020 11.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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