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

The value for Mortality rate, under-5, male (per 1,000 live births) in Thailand was 9.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 152.80 in 1960 and a minimum value of 9.50 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 152.80
1961 147.60
1962 142.50
1963 137.50
1964 132.70
1965 127.90
1966 123.10
1967 118.40
1968 113.70
1969 109.00
1970 104.40
1971 99.80
1972 95.30
1973 90.90
1974 86.80
1975 82.80
1976 79.00
1977 75.50
1978 72.10
1979 68.80
1980 65.80
1981 62.90
1982 60.10
1983 57.50
1984 54.90
1985 52.40
1986 50.00
1987 47.60
1988 45.30
1989 43.00
1990 40.80
1991 38.70
1992 36.70
1993 34.90
1994 33.10
1995 31.50
1996 29.90
1997 28.40
1998 27.00
1999 25.70
2000 24.40
2001 23.20
2002 22.10
2003 21.00
2004 20.00
2005 19.10
2006 18.20
2007 17.30
2008 16.50
2009 15.80
2010 15.00
2011 14.30
2012 13.70
2013 13.10
2014 12.50
2015 11.90
2016 11.40
2017 10.90
2018 10.40
2019 9.90
2020 9.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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