Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Su, Shu-Yuan, Li, Yu-Wen, Wen, Fur-Hsing, Yao, Chi-Yu, Wang, Jong-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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
_version_ 1784885722225836032
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
work_keys_str_mv AT sushuyuan associationsamonghealthstatusoccupationandoccupationalinjuriesordiseasesamultilevelanalysis
AT liyuwen associationsamonghealthstatusoccupationandoccupationalinjuriesordiseasesamultilevelanalysis
AT wenfurhsing associationsamonghealthstatusoccupationandoccupationalinjuriesordiseasesamultilevelanalysis
AT yaochiyu associationsamonghealthstatusoccupationandoccupationalinjuriesordiseasesamultilevelanalysis
AT wangjongyi associationsamonghealthstatusoccupationandoccupationalinjuriesordiseasesamultilevelanalysis