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Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis
Purpose: The present study used a hierarchical generalized linear model to explore the effects of physical and mental health and occupational categories on occupational injuries and diseases. Methods: The data were obtained from the Registry for Beneficiaries of the 2002–2013 National Health Insuran...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914676/ https://www.ncbi.nlm.nih.gov/pubmed/36766485 http://dx.doi.org/10.3390/diagnostics13030381 |
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author | Su, Shu-Yuan Li, Yu-Wen Wen, Fur-Hsing Yao, Chi-Yu Wang, Jong-Yi |
author_facet | Su, Shu-Yuan Li, Yu-Wen Wen, Fur-Hsing Yao, Chi-Yu Wang, Jong-Yi |
author_sort | Su, Shu-Yuan |
collection | PubMed |
description | Purpose: The present study used a hierarchical generalized linear model to explore the effects of physical and mental health and occupational categories on occupational injuries and diseases. Methods: The data were obtained from the Registry for Beneficiaries of the 2002–2013 National Health Insurance Research Database. The benefit categories involved adults with occupational injuries and diseases. Six major occupational categories and 28 subcategories were used. The main analysis methods were binary logistic regression (BLR) and hierarchical generalized linear model (HGLM). Results: After adjustment for relevant factors, the three major occupation subcategories most likely to develop occupational injuries and diseases were Subcategory 12 “employees with fixed employers” of Category 1 “civil servants, employees in public or private schools, laborers, and self-employed workers”; Subcategory 2 “employees in private organizations” of Category 1; and “sangha and religionists” of Category 6 “other citizens.” Conditions such as mental disorders and obesity increased the risk of occupational injuries and diseases. Conclusion: A portion of the occupational categories had a higher risk of occupational injuries and diseases. Physical and mental health issues were significantly correlated with occupational injuries and diseases. To the authors’ knowledge, this is the first study to use HGLM to analyze differences in occupational categories in Taiwan. |
format | Online Article Text |
id | pubmed-9914676 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99146762023-02-11 Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis Su, Shu-Yuan Li, Yu-Wen Wen, Fur-Hsing Yao, Chi-Yu Wang, Jong-Yi Diagnostics (Basel) Viewpoint Purpose: The present study used a hierarchical generalized linear model to explore the effects of physical and mental health and occupational categories on occupational injuries and diseases. Methods: The data were obtained from the Registry for Beneficiaries of the 2002–2013 National Health Insurance Research Database. The benefit categories involved adults with occupational injuries and diseases. Six major occupational categories and 28 subcategories were used. The main analysis methods were binary logistic regression (BLR) and hierarchical generalized linear model (HGLM). Results: After adjustment for relevant factors, the three major occupation subcategories most likely to develop occupational injuries and diseases were Subcategory 12 “employees with fixed employers” of Category 1 “civil servants, employees in public or private schools, laborers, and self-employed workers”; Subcategory 2 “employees in private organizations” of Category 1; and “sangha and religionists” of Category 6 “other citizens.” Conditions such as mental disorders and obesity increased the risk of occupational injuries and diseases. Conclusion: A portion of the occupational categories had a higher risk of occupational injuries and diseases. Physical and mental health issues were significantly correlated with occupational injuries and diseases. To the authors’ knowledge, this is the first study to use HGLM to analyze differences in occupational categories in Taiwan. MDPI 2023-01-19 /pmc/articles/PMC9914676/ /pubmed/36766485 http://dx.doi.org/10.3390/diagnostics13030381 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Viewpoint Su, Shu-Yuan Li, Yu-Wen Wen, Fur-Hsing Yao, Chi-Yu Wang, Jong-Yi Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis |
title | Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis |
title_full | Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis |
title_fullStr | Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis |
title_full_unstemmed | Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis |
title_short | Associations among Health Status, Occupation, and Occupational Injuries or Diseases: A Multi-Level Analysis |
title_sort | associations among health status, occupation, and occupational injuries or diseases: a multi-level analysis |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914676/ https://www.ncbi.nlm.nih.gov/pubmed/36766485 http://dx.doi.org/10.3390/diagnostics13030381 |
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