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Tracking and Decomposing Health and Disease Inequality in Thailand

PURPOSE: In middle-income countries, interest in the study of inequalities in health has focused on aggregate types of health outcomes, like rates of mortality. This work moves beyond such measures to focus on disease-specific health outcomes with the use of national health survey data. METHODS: Cro...

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Autores principales: Yiengprugsawan, Vasoontara, Lim, Lynette L.-Y., Carmichael, Gordon A., Seubsman, Sam-Ang, Sleigh, Adrian C.
Formato: Texto
Lenguaje:English
Publicado: Elsevier 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2766637/
https://www.ncbi.nlm.nih.gov/pubmed/19560371
http://dx.doi.org/10.1016/j.annepidem.2009.04.009
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author Yiengprugsawan, Vasoontara
Lim, Lynette L.-Y.
Carmichael, Gordon A.
Seubsman, Sam-Ang
Sleigh, Adrian C.
author_facet Yiengprugsawan, Vasoontara
Lim, Lynette L.-Y.
Carmichael, Gordon A.
Seubsman, Sam-Ang
Sleigh, Adrian C.
author_sort Yiengprugsawan, Vasoontara
collection PubMed
description PURPOSE: In middle-income countries, interest in the study of inequalities in health has focused on aggregate types of health outcomes, like rates of mortality. This work moves beyond such measures to focus on disease-specific health outcomes with the use of national health survey data. METHODS: Cross-sectional data from the national Health and Welfare Survey 2003, covering 52,030 adult aged 15 or older, were analyzed. The health outcomes were the 20 most commonly reported diseases. The age-sex adjusted concentration index (C∗) of ill health was used as a measure of socioeconomic health inequality (values ranging from −1 to +1). A negative (or positive) concentration index shows that a disease was more concentrated among the less well off (or better off). Crude concentration indices (C) for four of the most common diseases were also decomposed to quantify determinants of inequalities. RESULTS: Several diseases, such as malaria (C∗ = −0.462), goiter (C∗ = −0.352), kidney stone (C∗ = −0.261), and tuberculosis (C∗ = −0.233), were strongly concentrated among those with lower incomes, whereas allergic conditions (C∗ = 0.174) and migraine (C∗ = 0.085) were disproportionately reported by the better off. Inequalities were found to be associated with older age, low education, and residence in the rural Northeast and rural North of Thailand. CONCLUSIONS: Pro-equity health policy in Thailand and other middle-income countries with health surveys can now be informed by national data combining epidemiological, socioeconomic and health statistics in ways not previously possible.
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spelling pubmed-27666372009-10-26 Tracking and Decomposing Health and Disease Inequality in Thailand Yiengprugsawan, Vasoontara Lim, Lynette L.-Y. Carmichael, Gordon A. Seubsman, Sam-Ang Sleigh, Adrian C. Ann Epidemiol Article PURPOSE: In middle-income countries, interest in the study of inequalities in health has focused on aggregate types of health outcomes, like rates of mortality. This work moves beyond such measures to focus on disease-specific health outcomes with the use of national health survey data. METHODS: Cross-sectional data from the national Health and Welfare Survey 2003, covering 52,030 adult aged 15 or older, were analyzed. The health outcomes were the 20 most commonly reported diseases. The age-sex adjusted concentration index (C∗) of ill health was used as a measure of socioeconomic health inequality (values ranging from −1 to +1). A negative (or positive) concentration index shows that a disease was more concentrated among the less well off (or better off). Crude concentration indices (C) for four of the most common diseases were also decomposed to quantify determinants of inequalities. RESULTS: Several diseases, such as malaria (C∗ = −0.462), goiter (C∗ = −0.352), kidney stone (C∗ = −0.261), and tuberculosis (C∗ = −0.233), were strongly concentrated among those with lower incomes, whereas allergic conditions (C∗ = 0.174) and migraine (C∗ = 0.085) were disproportionately reported by the better off. Inequalities were found to be associated with older age, low education, and residence in the rural Northeast and rural North of Thailand. CONCLUSIONS: Pro-equity health policy in Thailand and other middle-income countries with health surveys can now be informed by national data combining epidemiological, socioeconomic and health statistics in ways not previously possible. Elsevier 2009-11 /pmc/articles/PMC2766637/ /pubmed/19560371 http://dx.doi.org/10.1016/j.annepidem.2009.04.009 Text en © 2009 Elsevier Inc. https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
spellingShingle Article
Yiengprugsawan, Vasoontara
Lim, Lynette L.-Y.
Carmichael, Gordon A.
Seubsman, Sam-Ang
Sleigh, Adrian C.
Tracking and Decomposing Health and Disease Inequality in Thailand
title Tracking and Decomposing Health and Disease Inequality in Thailand
title_full Tracking and Decomposing Health and Disease Inequality in Thailand
title_fullStr Tracking and Decomposing Health and Disease Inequality in Thailand
title_full_unstemmed Tracking and Decomposing Health and Disease Inequality in Thailand
title_short Tracking and Decomposing Health and Disease Inequality in Thailand
title_sort tracking and decomposing health and disease inequality in thailand
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2766637/
https://www.ncbi.nlm.nih.gov/pubmed/19560371
http://dx.doi.org/10.1016/j.annepidem.2009.04.009
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