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

The value for Mortality rate, infant (per 1,000 live births) in Thailand was 7.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 101.40 in 1960 and a minimum value of 7.40 in 2020.

Definition: Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 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 101.40
1961 98.30
1962 95.10
1963 92.00
1964 89.00
1965 86.00
1966 83.10
1967 80.10
1968 77.10
1969 74.20
1970 71.20
1971 68.30
1972 65.50
1973 62.70
1974 60.10
1975 57.60
1976 55.20
1977 53.00
1978 50.90
1979 48.90
1980 46.90
1981 45.00
1982 43.20
1983 41.50
1984 39.80
1985 38.10
1986 36.50
1987 34.90
1988 33.40
1989 31.80
1990 30.30
1991 28.90
1992 27.50
1993 26.20
1994 25.00
1995 23.80
1996 22.70
1997 21.60
1998 20.60
1999 19.60
2000 18.70
2001 17.80
2002 17.00
2003 16.20
2004 15.50
2005 14.80
2006 14.10
2007 13.40
2008 12.80
2009 12.20
2010 11.70
2011 11.20
2012 10.60
2013 10.20
2014 9.70
2015 9.30
2016 8.90
2017 8.50
2018 8.10
2019 7.70
2020 7.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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