20 research outputs found

    Geographical gradient of mean age of dengue haemorrhagic fever patients in northern Thailand

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    Dengue haemorrhagic fever (DHF) is caused by dengue virus transmitted by Aedes mosquitoes; mean age of patients varies temporally and geographically. Variability in age of patients may be due to differences in transmission intensity or demographic structure. To compare these two hypotheses, the mean age of DHF patients from 90 districts in northern Thailand (1994–1996, 2002–2004) was regressed against (i) Aedes abundance or (ii) demographic variables (birthrate, average age) of the district. We also developed software to quantify direction and strength of geographical gradients of these variables. We found that, after adjusting for socioeconomics, climate, spatial autocorrelation, the mean age of patients was correlated only with Aedes abundance. The geographical gradient of mean age of patients originated from entomological, climate, and socioeconomic gradients. Vector abundance was a stronger determinant of mean age of patients than demographic variables, in northern Thailand

    Post universal health coverage trend and geographical inequalities of mortality in Thailand

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    BACKGROUND: Thailand has achieved remarkable improvement in health status since the achievement of universal health coverage in 2002. Health equity has improved significantly. However, challenges on health inequity still remain.This study aimed to determine the trends of geographical inequalities in disease specific mortality in Thailand after the country achieved universal health coverage. METHODS: National vital registration data from 2001 to 2014 were used to calculate age-adjusted mortality rate and standardized mortality ratio (SMR). To minimize large variations in mortality across administrative districts, the adjacent districts were systematically grouped into “super-districts” by taking into account the population size and proximity. Geographical mortality inequality among super-districts was measured by the coefficient of variation. Mixed effects modeling was used to test the difference in trends between super-districts. RESULTS: The overall SMR steadily declined from 1.2 in 2001 to 0.9 in 2014. The upper north and upper northeast regions had higher SMR whereas Greater Bangkok achieved the lowest SMR. Decreases in SMR were mostly seen in Greater Bangkok and the upper northern region. Coefficient of variation of SMR rapidly decreased from 20.0 in 2001 to 12.5 in 2007 and remained close to this value until 2014. The mixed effects modelling revealed significant differences in trends of SMR across super-districts. Inequality in mortality declined among adults (≥15 years old) but increased in children (0–14 years old). A declining trend in inequality of mortality was seen in almost all regions except Greater Bangkok where the inequality in SMR remained high throughout the study period. CONCLUSIONS: A decline in the adult mortality inequality across almost all regions of Thailand followed universal health coverage. Inequalities in child mortality rates and among residents of Greater Bangkok need further exploration

    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
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