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

The value for Mortality rate, infant, male (per 1,000 live births) in Thailand was 8.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 108.40 in 1960 and a minimum value of 8.10 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 108.40
1961 105.10
1962 101.80
1963 98.60
1964 95.50
1965 92.40
1966 89.30
1967 86.30
1968 83.30
1969 80.20
1970 77.20
1971 74.20
1972 71.30
1973 68.40
1974 65.70
1975 63.00
1976 60.50
1977 58.20
1978 55.90
1979 53.70
1980 51.60
1981 49.60
1982 47.60
1983 45.70
1984 43.90
1985 42.10
1986 40.30
1987 38.60
1988 36.90
1989 35.20
1990 33.60
1991 32.00
1992 30.50
1993 29.10
1994 27.70
1995 26.50
1996 25.20
1997 24.10
1998 23.00
1999 21.90
2000 20.90
2001 19.90
2002 18.90
2003 18.10
2004 17.20
2005 16.40
2006 15.70
2007 14.90
2008 14.30
2009 13.60
2010 13.00
2011 12.40
2012 11.80
2013 11.30
2014 10.80
2015 10.30
2016 9.80
2017 9.30
2018 8.90
2019 8.50
2020 8.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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