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

The value for Mortality rate, under-5, male (per 1,000 live births) in Bolivia was 27.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 303.20 in 1960 and a minimum value of 27.80 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 303.20
1961 296.90
1962 290.70
1963 284.50
1964 278.10
1965 271.90
1966 265.50
1967 259.20
1968 252.90
1969 246.70
1970 240.30
1971 233.80
1972 227.10
1973 220.40
1974 213.70
1975 206.90
1976 200.40
1977 194.10
1978 188.10
1979 182.50
1980 177.20
1981 172.40
1982 167.50
1983 162.70
1984 157.90
1985 152.90
1986 147.90
1987 143.00
1988 137.90
1989 132.80
1990 127.70
1991 122.70
1992 117.80
1993 112.90
1994 108.10
1995 103.40
1996 98.70
1997 93.90
1998 89.30
1999 84.60
2000 80.00
2001 75.70
2002 71.50
2003 67.50
2004 63.70
2005 60.10
2006 56.70
2007 53.50
2008 50.50
2009 47.60
2010 45.00
2011 42.50
2012 40.10
2013 38.00
2014 35.90
2015 34.20
2016 32.60
2017 31.20
2018 30.00
2019 28.90
2020 27.80

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