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A laryngeal disorders prediction model based on cluster analysis and regression analysis

This study provided the baseline for establishing policies for community health promotion programs to propose the clusters of multiple health risk factors and identify the risks of laryngeal disorders according to the clusters by using the national level survey representing the South Korean populati...

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Autor principal: Byeon, Haewon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709150/
https://www.ncbi.nlm.nih.gov/pubmed/31374053
http://dx.doi.org/10.1097/MD.0000000000016686
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author Byeon, Haewon
author_facet Byeon, Haewon
author_sort Byeon, Haewon
collection PubMed
description This study provided the baseline for establishing policies for community health promotion programs to propose the clusters of multiple health risk factors and identify the risks of laryngeal disorders according to the clusters by using the national level survey representing the South Korean population. This study targeted 5941 people who completed the 5th Korean National Health and Nutrition Examination Survey. The independent variables were age, sex, smoking, high-risk drinking, education level, occupation, household income, and self-reported voice problems. The identify cluster relationship with laryngeal disorders by conducting 2-way cluster analysis and multinomial logit analysis. The prevalence of laryngeal disorder was 6.7%. The results of analysis, 3 clusters were automatically extracted. Multinomial logistic regression analysis showed that sociodemographic factors, health risk behaviors, and health status clusters were significantly related to the risk of laryngeal disorders. The males who were smoking, high-risk drinking, college graduate and above, high income, and non-manual workers had a higher risk of laryngeal disorders than females who were non-smokers, non-drinkers, 60 years old and older, economically inactive, and high school graduate. The results of this study suggested that it may be effective to classify population according to sociodemographic and health behaviors and develop health education materials and health promotion program accordingly in order to prevent laryngeal disorders.
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spelling pubmed-67091502019-10-01 A laryngeal disorders prediction model based on cluster analysis and regression analysis Byeon, Haewon Medicine (Baltimore) Research Article This study provided the baseline for establishing policies for community health promotion programs to propose the clusters of multiple health risk factors and identify the risks of laryngeal disorders according to the clusters by using the national level survey representing the South Korean population. This study targeted 5941 people who completed the 5th Korean National Health and Nutrition Examination Survey. The independent variables were age, sex, smoking, high-risk drinking, education level, occupation, household income, and self-reported voice problems. The identify cluster relationship with laryngeal disorders by conducting 2-way cluster analysis and multinomial logit analysis. The prevalence of laryngeal disorder was 6.7%. The results of analysis, 3 clusters were automatically extracted. Multinomial logistic regression analysis showed that sociodemographic factors, health risk behaviors, and health status clusters were significantly related to the risk of laryngeal disorders. The males who were smoking, high-risk drinking, college graduate and above, high income, and non-manual workers had a higher risk of laryngeal disorders than females who were non-smokers, non-drinkers, 60 years old and older, economically inactive, and high school graduate. The results of this study suggested that it may be effective to classify population according to sociodemographic and health behaviors and develop health education materials and health promotion program accordingly in order to prevent laryngeal disorders. Wolters Kluwer Health 2019-08-02 /pmc/articles/PMC6709150/ /pubmed/31374053 http://dx.doi.org/10.1097/MD.0000000000016686 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0
spellingShingle Research Article
Byeon, Haewon
A laryngeal disorders prediction model based on cluster analysis and regression analysis
title A laryngeal disorders prediction model based on cluster analysis and regression analysis
title_full A laryngeal disorders prediction model based on cluster analysis and regression analysis
title_fullStr A laryngeal disorders prediction model based on cluster analysis and regression analysis
title_full_unstemmed A laryngeal disorders prediction model based on cluster analysis and regression analysis
title_short A laryngeal disorders prediction model based on cluster analysis and regression analysis
title_sort laryngeal disorders prediction model based on cluster analysis and regression analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709150/
https://www.ncbi.nlm.nih.gov/pubmed/31374053
http://dx.doi.org/10.1097/MD.0000000000016686
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