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      Occupational exposures and genetic susceptibility to occupational exposures are related to sickness absence in the Lifelines cohort study

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          Abstract

          In this cross-sectional study, we investigated the association between occupational exposures and sickness absence (SA), the mediating role of respiratory symptoms, and whether genetic susceptibility to SA upon occupational exposures exists. Logistic regression was used to examine associations and structural equation modelling was used for mediation analyses. Genetic susceptibility was investigated by including interactions between occupational exposures and 11 candidate single nucleotide polymorphisms (SNPs). Biological dust, mineral dust, and pesticides exposure were associated with a lower prevalence of any SA (OR (95% CI) = 0.72 (0.58–0.89), 0.88 (0.78–0.99), and 0.70 (0.55–0.89), respectively) while gases/fumes exposure was associated with a higher prevalence of long-term SA (1.46 (1.11–1.91)). Subjects exposed to solvents and metals had a higher prevalence of any (1.14 (1.03–1.26) and 1.68 (1.26–2.24)) and long-term SA (1.26 (1.08–1.46) and 1.75 (1.15–2.67)). Chronic cough and chronic phlegm mediated the association between high gases/fumes exposure and long-term SA. Two of 11 SNPs investigated had a positive interaction with exposure on SA and one SNP negatively interacted with exposure on SA. Exposure to metals and gases/fumes showed a clear dose–response relationship with a higher prevalence of long-term SA; contrary, exposure to pesticides and biological/mineral dust showed a protective effect on any SA. Respiratory symptoms mediated the association between occupational exposures and SA. Moreover, gene-by-exposure interactions exist.

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          Most cited references37

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          Pesticides: an update of human exposure and toxicity.

          Pesticides are a family of compounds which have brought many benefits to mankind in the agricultural, industrial, and health areas, but their toxicities in both humans and animals have always been a concern. Regardless of acute poisonings which are common for some classes of pesticides like organophosphoruses, the association of chronic and sub-lethal exposure to pesticides with a prevalence of some persistent diseases is going to be a phenomenon to which global attention has been attracted. In this review, incidence of various malignant, neurodegenerative, respiratory, reproductive, developmental, and metabolic diseases in relation to different routes of human exposure to pesticides such as occupational, environmental, residential, parental, maternal, and paternal has been systematically criticized in different categories of pesticide toxicities like carcinogenicity, neurotoxicity, pulmonotoxicity, reproductive toxicity, developmental toxicity, and metabolic toxicity. A huge body of evidence exists on the possible role of pesticide exposures in the elevated incidence of human diseases such as cancers, Alzheimer, Parkinson, amyotrophic lateral sclerosis, asthma, bronchitis, infertility, birth defects, attention deficit hyperactivity disorder, autism, diabetes, and obesity. Most of the disorders are induced by insecticides and herbicides most notably organophosphorus, organochlorines, phenoxyacetic acids, and triazine compounds.
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            A meta-analysis of observational studies identifies predictors of sickness absence.

            About one in every three employees seen by their occupational physician is absent from work because of psychosocial health complaints. To implement preventive measures, it is necessary to identify predictors for this type of sickness absence. A meta-analysis was carried out to quantify the association between predictive factors and psychosocial sickness absence and to assess clinical outcomes and heterogeneity. Eligible for inclusion were prospective studies that examined this association and provided sufficient information to estimate summary odds ratios (SORs). Twenty prospective studies were included. Significant SORs for sick leave >3 days were found for being unmarried, 1.37 (95% confidence interval [CI]=1.15-1.64), experiencing psychosomatic complaints, 1.79 (95% CI=1.54-2.07), using medication, 3.13 (95% CI=1.71-5.72), having a burnout, 2.34 (95% CI=1.59-3.45), suffering from psychological problems, 1.97 (95% CI=1.37-2.85), having low job control, 1.28 (95% CI=1.23-1.33), having low decision latitude, 1.33 (95% CI=1.16-1.56), and experiencing no fairness at work, 1.30 (95% CI=1.18-1.45). This study shows that predictors of sickness absence can be identified in a homogeneous manner. The results provide leads to public health interventions to successfully improve psychosocial health and to reduce sickness absence.
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              Healthy worker effect phenomenon

              The Healthy Worker Effect (HWE) phenomenon has been under debate since some years. Some epidemiologists regard HWE as an ordinary method problem while others consider it a field of science by itself. This article gives definitions of HWE explained with historical background; discusses factors affecting it and suggests methods to minimize problems associated with it.
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                Author and article information

                Contributors
                h.m.boezen@umcg.nl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 July 2020
                31 July 2020
                2020
                : 10
                : 12963
                Affiliations
                [1 ]University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
                [2 ]ISNI 0000 0000 9558 4598, GRID grid.4494.d, University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), ; Groningen, The Netherlands
                [3 ]ISNI 0000000120346234, GRID grid.5477.1, University of Utrecht, Institute for Risk Assessment Sciences (IRAS), Division of Environmental Epidemiology, ; Utrecht, The Netherlands
                [4 ]ISNI 0000 0000 9558 4598, GRID grid.4494.d, University of Groningen, University Medical Center Groningen, Department of Health Sciences, Community and Occupational Medicine, ; Groningen, The Netherlands
                Article
                69372
                10.1038/s41598-020-69372-6
                7395760
                32737337
                14f0d39f-58c5-4fb1-9f47-456f9567f444
                © The Author(s) 2020

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 April 2020
                : 17 June 2020
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                © The Author(s) 2020

                Uncategorized
                health occupations,risk factors
                Uncategorized
                health occupations, risk factors

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