Statistical methods for modeling socioeconomic indicators affecting all-cause mortality in Thailand

摘要

This study aims to model the socioeconomic indicators affecting all-cause mortality pattern with different 18 age groups. Based on the data from Thailand's 2000 Population and Housing Census and the Vital Registration database from 1999 to 2001, this study incorporates the factor analysis into the multivariate multiple regression analysis to determine five factors: four composite factors (farming, urban, comfort and goods) derived from twenty socioeconomic indicators and one unexplained mortality factor. The result shows that the mortality rates of three predictors: farming, goods and the unexplained, are higher in all age groups except for the group with less than one year of age. The mortality due to the unexplained factor of both genders is high in northern part of the country, particularly the super-districts in Chiang Mai, Chiang Rai and Phayao. The finding provides useful guidelines for the policy makers in healthcare authorities to set up health promotion and education programs, especially for 30 to 39 years old males in urban area and 25 to 29 years old females in farming group.