28 research outputs found

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

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    <p>Abstract</p> <p>Background</p> <p>In 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.</p> <p>Methods</p> <p>The 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.</p> <p>Results</p> <p>The 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.</p> <p>Conclusion</p> <p>The 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.</p

    Amyloid Plaques Beyond Aβ: A Survey of the Diverse Modulators of Amyloid Aggregation

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    Aggregation of the amyloid-β (Aβ) peptide is strongly correlated with Alzheimer’s disease (AD). Recent research has improved our understanding of the kinetics of amyloid fibril assembly and revealed new details regarding different stages in plaque formation. Presently, interest is turning toward studying this process in a holistic context, focusing on cellular components which interact with the Aβ peptide at various junctures during aggregation, from monomer to cross-β amyloid fibrils. However, even in isolation, a multitude of factors including protein purity, pH, salt content, and agitation affect Aβ fibril formation and deposition, often producing complicated and conflicting results. The failure of numerous inhibitors in clinical trials for AD suggests that a detailed examination of the complex interactions that occur during plaque formation, including binding of carbohydrates, lipids, nucleic acids, and metal ions, is important for understanding the diversity of manifestations of the disease. Unraveling how a variety of key macromolecular modulators interact with the Aβ peptide and change its aggregation properties may provide opportunities for developing therapies. Since no protein acts in isolation, the interplay of these diverse molecules may differentiate disease onset, progression, and severity, and thus are worth careful consideration

    COVID

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    Lipoma of the infundibulum

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