Guatemala - Mortality rate, under-5, female (per 1,000 live births)

The value for Mortality rate, under-5, female (per 1,000 live births) in Guatemala was 21.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 214.00 in 1960 and a minimum value of 21.10 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 214.00
1961 208.90
1962 204.00
1963 199.00
1964 194.20
1965 189.20
1966 184.40
1967 179.40
1968 174.50
1969 169.50
1970 164.40
1971 159.30
1972 154.20
1973 149.00
1974 143.90
1975 138.90
1976 154.90
1977 129.20
1978 124.50
1979 119.80
1980 115.50
1981 111.10
1982 128.40
1983 102.50
1984 98.20
1985 94.10
1986 89.90
1987 86.00
1988 82.00
1989 78.20
1990 74.60
1991 71.10
1992 67.80
1993 64.80
1994 61.90
1995 59.10
1996 56.50
1997 54.10
1998 51.80
1999 49.70
2000 47.70
2001 45.70
2002 43.80
2003 42.00
2004 40.30
2005 38.70
2006 37.10
2007 35.60
2008 34.10
2009 32.70
2010 31.30
2011 29.90
2012 28.70
2013 27.50
2014 26.30
2015 25.30
2016 24.40
2017 23.50
2018 22.60
2019 21.80
2020 21.10

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