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

The value for Mortality rate, infant, female (per 1,000 live births) in Bolivia was 18.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 158.90 in 1960 and a minimum value of 18.40 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 158.90
1961 155.80
1962 152.90
1963 150.00
1964 146.90
1965 143.90
1966 141.00
1967 137.90
1968 134.80
1969 131.80
1970 128.70
1971 125.80
1972 122.80
1973 119.90
1974 116.90
1975 113.80
1976 110.90
1977 108.10
1978 105.40
1979 102.90
1980 100.50
1981 98.30
1982 96.30
1983 94.40
1984 92.30
1985 90.10
1986 87.60
1987 85.00
1988 82.30
1989 79.70
1990 77.10
1991 74.50
1992 72.00
1993 69.60
1994 67.00
1995 64.50
1996 61.80
1997 59.10
1998 56.40
1999 53.70
2000 51.10
2001 48.40
2002 45.90
2003 43.50
2004 41.20
2005 39.00
2006 36.90
2007 34.90
2008 33.10
2009 31.30
2010 29.60
2011 28.10
2012 26.60
2013 25.20
2014 23.90
2015 22.70
2016 21.70
2017 20.70
2018 19.90
2019 19.10
2020 18.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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