Measuring and decomposing inequity in self-reported morbidity and self-assessed health in Thailand.

Vasoontara Yiengprugsawan,Adrian C Sleigh,Lynette Ly Lim,Alexandra Sidorenko,Gordon A Carmichael

doi:10.1186/1475-9276-6-23

Vasoontara Yiengprugsawan, Adrian C Sleigh + Show 3 more

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https://doi.org/10.1186/1475-9276-6-23

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Abstract

BackgroundIn recent years, interest in the study of inequalities in health has not stopped at quantifying their magnitude; explaining the sources of inequalities has also become of great importance. This paper measures socioeconomic inequalities in self-reported morbidity and self-assessed health in Thailand, and the contributions of different population subgroups to those inequalities.MethodsThe Health and Welfare Survey 2003 conducted by the Thai National Statistical Office with 37,202 adult respondents is used for the analysis. The health outcomes of interest derive from three self-reported morbidity and two self-assessed health questions. Socioeconomic status is measured by adult-equivalent monthly income per household member. The concentration index (CI) of ill health is used as a measure of socioeconomic health inequalities, and is subsequently decomposed into contributing factors.ResultsThe CIs reveal inequality gradients disadvantageous to the poor for both self-reported morbidity and self-assessed health in Thailand. The magnitudes of these inequalities were higher for the self-assessed health outcomes than for the self-reported morbidity outcomes. Age and sex played significant roles in accounting for the inequality in reported chronic illness (33.7 percent of the total inequality observed), hospital admission (27.8 percent), and self-assessed deterioration of health compared to a year ago (31.9 percent). The effect of being female and aged 60 years or older was by far the strongest demographic determinant of inequality across all five types of health outcome. Having a low socioeconomic status as measured by income quintile, education and work status were the main contributors disadvantaging the poor in self-rated health compared to a year ago (47.1 percent) and self-assessed health compared to peers (47.4 percent). Residence in the rural Northeast and rural North were the main regional contributors to inequality in self-reported recent and chronic illness, while residence in the rural Northeast was the major contributor to the tendency of the poor to report lower levels of self-assessed health compared to peers.ConclusionThe findings confirm that substantial socioeconomic inequalities in health as measured by self-reported morbidity and self-assessed health exist in Thailand. Decomposition analysis shows that inequalities in health status are associated with particular demographic, socioeconomic and geographic population subgroups. Vulnerable subgroups which are prone to both ill health and relative poverty warrant targeted policy attention.

Highlights

In recent years, interest in the study of inequalities in health has not stopped at quantifying their magnitude; explaining the sources of inequalities has become of great importance
This section consists of four subsections that follow the steps of the decomposition analysis: i) to obtain the population-weighted proportion and concentration index for each health outcome and each determinant; ii) to obtain marginal effects of the set of determinants for each health outcome variable; iii) to interpret the decomposition results using the 'recently ill' outcome as an example; and iv) to compare the contributions of determinants across the five self-reported morbidity and self-assessed health outcomes
The self-reported morbidity variables show that percent of the sample of 37,202 reported having been recently ill (i.e., 'ill or not feeling well' in the last month), while percent reported having suffered from a chronic illness during the past month and 6 percent reported a non-maternity hospital admission during the past 12 months

Summary

Introduction

Interest in the study of inequalities in health has not stopped at quantifying their magnitude; explaining the sources of inequalities has become of great importance. Gaps in health-related outcomes between the rich and the poor can be large [10,11,12,13]. Research should identify which population subgroups are the most disadvantaged Once this is known it becomes possible to identify the determinants of inequalities, including those associated with age, gender, education, occupation and geographical location. These variables have previously been identified as powerful sources of health inequalities in low and middle income countries [14,16,17]

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