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Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers

BACKGROUND: Identify and compare health risk indicators for common chronic diseases between different occupational groups. METHODS: A total of 72,855 participants (41% women) participating in an occupational health service screening in 2014–2019 were included. Occupation was defined by the Swedish S...

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Autores principales: Väisänen, Daniel, Kallings, Lena V., Andersson, Gunnar, Wallin, Peter, Hemmingsson, Erik, Ekblom-Bak, Elin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641800/
https://www.ncbi.nlm.nih.gov/pubmed/33148214
http://dx.doi.org/10.1186/s12889-020-09755-6
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author Väisänen, Daniel
Kallings, Lena V.
Andersson, Gunnar
Wallin, Peter
Hemmingsson, Erik
Ekblom-Bak, Elin
author_facet Väisänen, Daniel
Kallings, Lena V.
Andersson, Gunnar
Wallin, Peter
Hemmingsson, Erik
Ekblom-Bak, Elin
author_sort Väisänen, Daniel
collection PubMed
description BACKGROUND: Identify and compare health risk indicators for common chronic diseases between different occupational groups. METHODS: A total of 72,855 participants (41% women) participating in an occupational health service screening in 2014–2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3). RESULTS: The greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR = 0.68 to OR = 5.12), physically demanding work (OR = 0.55 to OR = 45.74) and high sitting at work (OR = 0.04 to OR = 1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71–1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88–2.13) as high-skilled blue-collar workers (1.98; 1.86–2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17–2.48). CONCLUSION: There were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention.
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spelling pubmed-76418002020-11-05 Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers Väisänen, Daniel Kallings, Lena V. Andersson, Gunnar Wallin, Peter Hemmingsson, Erik Ekblom-Bak, Elin BMC Public Health Research Article BACKGROUND: Identify and compare health risk indicators for common chronic diseases between different occupational groups. METHODS: A total of 72,855 participants (41% women) participating in an occupational health service screening in 2014–2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3). RESULTS: The greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR = 0.68 to OR = 5.12), physically demanding work (OR = 0.55 to OR = 45.74) and high sitting at work (OR = 0.04 to OR = 1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71–1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88–2.13) as high-skilled blue-collar workers (1.98; 1.86–2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17–2.48). CONCLUSION: There were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention. BioMed Central 2020-11-04 /pmc/articles/PMC7641800/ /pubmed/33148214 http://dx.doi.org/10.1186/s12889-020-09755-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Väisänen, Daniel
Kallings, Lena V.
Andersson, Gunnar
Wallin, Peter
Hemmingsson, Erik
Ekblom-Bak, Elin
Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
title Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
title_full Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
title_fullStr Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
title_full_unstemmed Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
title_short Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
title_sort lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72,855 workers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641800/
https://www.ncbi.nlm.nih.gov/pubmed/33148214
http://dx.doi.org/10.1186/s12889-020-09755-6
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