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

The value for Mortality rate, infant, male (per 1,000 live births) in Bolivia was 22.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 191.10 in 1960 and a minimum value of 22.90 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 191.10
1961 187.70
1962 184.30
1963 181.00
1964 177.70
1965 174.30
1966 170.90
1967 167.40
1968 164.00
1969 160.60
1970 157.10
1971 153.50
1972 149.70
1973 145.90
1974 142.10
1975 138.30
1976 134.40
1977 130.70
1978 127.20
1979 123.90
1980 120.80
1981 117.90
1982 114.90
1983 111.90
1984 109.00
1985 105.90
1986 103.00
1987 99.90
1988 96.90
1989 93.70
1990 90.60
1991 87.60
1992 84.50
1993 81.50
1994 78.50
1995 75.40
1996 72.50
1997 69.50
1998 66.50
1999 63.40
2000 60.40
2001 57.50
2002 54.70
2003 52.00
2004 49.40
2005 46.90
2006 44.50
2007 42.30
2008 40.10
2009 38.00
2010 36.10
2011 34.20
2012 32.50
2013 30.80
2014 29.30
2015 27.90
2016 26.70
2017 25.60
2018 24.60
2019 23.70
2020 22.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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