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Predictors of working days lost due to sickness absence and disability pension
OBJECTIVE: To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. METHODS: The data from the Finnish Helsinki Health Study included participants aged 55 years at the basel...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238732/ https://www.ncbi.nlm.nih.gov/pubmed/33433695 http://dx.doi.org/10.1007/s00420-020-01630-6 |
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author | Shiri, Rahman Hiilamo, Aapo Rahkonen, Ossi Robroek, Suzan J. W. Pietiläinen, Olli Lallukka, Tea |
author_facet | Shiri, Rahman Hiilamo, Aapo Rahkonen, Ossi Robroek, Suzan J. W. Pietiläinen, Olli Lallukka, Tea |
author_sort | Shiri, Rahman |
collection | PubMed |
description | OBJECTIVE: To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. METHODS: The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. RESULTS: The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. CONCLUSIONS: Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00420-020-01630-6. |
format | Online Article Text |
id | pubmed-8238732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-82387322021-07-13 Predictors of working days lost due to sickness absence and disability pension Shiri, Rahman Hiilamo, Aapo Rahkonen, Ossi Robroek, Suzan J. W. Pietiläinen, Olli Lallukka, Tea Int Arch Occup Environ Health Original Article OBJECTIVE: To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. METHODS: The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. RESULTS: The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. CONCLUSIONS: Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00420-020-01630-6. Springer Berlin Heidelberg 2021-01-12 2021 /pmc/articles/PMC8238732/ /pubmed/33433695 http://dx.doi.org/10.1007/s00420-020-01630-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Shiri, Rahman Hiilamo, Aapo Rahkonen, Ossi Robroek, Suzan J. W. Pietiläinen, Olli Lallukka, Tea Predictors of working days lost due to sickness absence and disability pension |
title | Predictors of working days lost due to sickness absence and disability pension |
title_full | Predictors of working days lost due to sickness absence and disability pension |
title_fullStr | Predictors of working days lost due to sickness absence and disability pension |
title_full_unstemmed | Predictors of working days lost due to sickness absence and disability pension |
title_short | Predictors of working days lost due to sickness absence and disability pension |
title_sort | predictors of working days lost due to sickness absence and disability pension |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238732/ https://www.ncbi.nlm.nih.gov/pubmed/33433695 http://dx.doi.org/10.1007/s00420-020-01630-6 |
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