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

The value for Mortality rate, infant, female (per 1,000 live births) in Thailand was 6.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 94.10 in 1960 and a minimum value of 6.60 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 94.10
1961 91.00
1962 88.00
1963 85.10
1964 82.20
1965 79.30
1966 76.40
1967 73.60
1968 70.70
1969 67.90
1970 65.00
1971 62.20
1972 59.50
1973 56.80
1974 54.20
1975 51.90
1976 49.60
1977 47.60
1978 45.60
1979 43.80
1980 42.00
1981 40.20
1982 38.60
1983 37.00
1984 35.40
1985 33.90
1986 32.40
1987 31.00
1988 29.60
1989 28.20
1990 26.90
1991 25.60
1992 24.30
1993 23.10
1994 22.00
1995 20.90
1996 19.90
1997 19.00
1998 18.10
1999 17.20
2000 16.40
2001 15.70
2002 14.90
2003 14.20
2004 13.60
2005 13.00
2006 12.40
2007 11.80
2008 11.30
2009 10.80
2010 10.30
2011 9.90
2012 9.40
2013 9.00
2014 8.60
2015 8.30
2016 7.90
2017 7.60
2018 7.20
2019 6.90
2020 6.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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