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

The value for Mortality rate, infant, female (per 1,000 live births) in Guatemala was 17.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 138.00 in 1960 and a minimum value of 17.70 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 138.00
1961 134.80
1962 131.90
1963 129.00
1964 125.90
1965 123.00
1966 120.00
1967 117.00
1968 114.00
1969 111.00
1970 107.90
1971 104.80
1972 101.80
1973 98.60
1974 95.50
1975 92.40
1976 96.50
1977 86.40
1978 83.50
1979 80.60
1980 78.00
1981 75.30
1982 81.20
1983 70.10
1984 67.50
1985 65.00
1986 62.40
1987 60.00
1988 57.60
1989 55.30
1990 53.10
1991 51.00
1992 49.10
1993 47.30
1994 45.50
1995 43.80
1996 42.20
1997 40.70
1998 39.30
1999 37.90
2000 36.60
2001 35.30
2002 34.00
2003 32.80
2004 31.70
2005 30.50
2006 29.50
2007 28.40
2008 27.40
2009 26.40
2010 25.40
2011 24.40
2012 23.50
2013 22.60
2014 21.80
2015 21.00
2016 20.30
2017 19.60
2018 19.00
2019 18.30
2020 17.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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