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

The value for Mortality rate, under-5 (per 1,000 live births) in Thailand was 8.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 146.60 in 1960 and a minimum value of 8.70 in 2020.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to 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 146.60
1961 141.60
1962 136.50
1963 131.60
1964 126.80
1965 122.10
1966 117.50
1967 112.80
1968 108.10
1969 103.50
1970 98.90
1971 94.30
1972 89.80
1973 85.50
1974 81.30
1975 77.40
1976 73.70
1977 70.20
1978 66.90
1979 63.80
1980 60.80
1981 58.00
1982 55.40
1983 52.80
1984 50.40
1985 48.00
1986 45.70
1987 43.50
1988 41.30
1989 39.20
1990 37.10
1991 35.10
1992 33.30
1993 31.50
1994 29.90
1995 28.40
1996 27.00
1997 25.60
1998 24.30
1999 23.10
2000 22.00
2001 20.90
2002 19.90
2003 18.90
2004 18.00
2005 17.20
2006 16.40
2007 15.60
2008 14.90
2009 14.20
2010 13.60
2011 13.00
2012 12.40
2013 11.80
2014 11.30
2015 10.80
2016 10.30
2017 9.90
2018 9.40
2019 9.00
2020 8.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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