Alumni

Nipa Rojroongwasinkul

Country: Thailand
Thesis Title: INCOME,INCOME INEQUALITYAND MORTALITY IN THAILAND.
Advisor: PIMONPAN ISARABHAKDI
Abstract:

The purpose of this study is to examine the effect of income and incomeinequality on the three aspects of mortality, namely, age-standardized death rates,life expectancy at birth, and adult mortality (15q45) in the 76 provinces of Thailand.This study used secondary data such as socio-economic characteristics and healthresources of provinces from many published sources in the year 2000. Pearson'sProduct Moment Correlation Coefficient and Multiple regression analysis wereused to test the relationships between per capita income, income inequality,socioeconomic and health resources with the three aspects of mortality in thestudy. The income inequality measures tested are the Gini coefficient, decileratio, Robin Hood Index, the proportion of total household income received bythe less well-off 50% (bottom 50%), 60% (bottom 60%), and 70% (bottom 70%).Although the correlations among these six measures were high (r = 0.65 to 0.99),the one most closely associated with the three indicators of mortality mentionedabove is the bottom 50%, which was selected to be used as the single measure ofincome inequality throughout the study. Results showed significant association between income inequality,absolute income and age-standardized death rates and life expectancy at birth butthere was no association with adult mortality rate. When stratification analysis bythe poverty group was used, the (not poor) and the poor provinces were found tobe significantly different based on the explanatory power of the regressionequations. The (not poor) provinces showed much better model specification forall aspects of mortality. For the poor category, only adult mortality for female wasimproved by stratification. The role of relative income among the (not poor) andpoor provinces was found to be less important when compared to absoluteincome. Absolute income had larger effect on aspects of mortality than relativeincome. Moreover, relative income had the reverse association with theaspects of mortality. This might be due to aggregation bias and unknown sourcesof confounding factors. Vulnerability analysis and mapping are also used to identify andcharacterize the vulnerable areas of poor health status in this study.

Alumni

Doctor of Philosophy in Demography (International Program)
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