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      Associations between depressive symptoms and 5-year subsequent work nonparticipation due to long-term sickness absence, unemployment and early retirement in a cohort of 2,413 employees in Germany

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          Abstract

          Background

          We examined the association of depressive symptoms with subsequent events – and duration thereof – of work nonparticipation (long-term sickness absence, unemployment and early retirement).

          Methods

          We employed a 5-year cohort from the Study on Mental Health at Work (S-MGA), based on a random sample of employees subject to social contributions aged 31–60 years in 2012 (N = 2413). Depressive symptoms were assessed at baseline through questionnaires, while work nonparticipation was recorded in follow-up interviews. Associations of depressive symptoms with subsequent events of work nonparticipation were examined in two-part models, with events analysed by logistic regressions and their duration by generalized linear models.

          Results

          Medium to severe depressive symptoms were associated with events of work nonparticipation (males Odds Ratio [OR] = 3.22; 95% CI = 1.90–5.45; females OR = 1.92; 95% CI = 1.29–2.87), especially with events of long-term sickness absence in both genders and events of unemployment in males. Mild depressive symptoms were also associated with events of work nonparticipation (males OR = 1.59; 95% CI = 1.19–2.11; females OR = 1.42; 95% CI = 1.10–1.84). Among those experiencing one or more events, the duration of total work nonparticipation was twice as high among males [Exp(β) = 2.06; 95% CI = 1.53–2.78] and about one third higher [Exp(β) = 1.38; 95% CI = 1.05–1.83] among females with medium to severe depressive symptoms.

          Conclusions

          The present study focuses on both events and duration of work nonparticipation, which are both critical for examining societal consequences of depressive symptoms. It is key to regard also mild depressive symptoms as a possible risk factor and to include different types of work nonparticipation.

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          Most cited references27

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          An inventory for measuring depression.

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            The size and burden of mental disorders and other disorders of the brain in Europe 2010.

            To provide 12-month prevalence and disability burden estimates of a broad range of mental and neurological disorders in the European Union (EU) and to compare these findings to previous estimates. Referring to our previous 2005 review, improved up-to-date data for the enlarged EU on a broader range of disorders than previously covered are needed for basic, clinical and public health research and policy decisions and to inform about the estimated number of persons affected in the EU. Stepwise multi-method approach, consisting of systematic literature reviews, reanalyses of existing data sets, national surveys and expert consultations. Studies and data from all member states of the European Union (EU-27) plus Switzerland, Iceland and Norway were included. Supplementary information about neurological disorders is provided, although methodological constraints prohibited the derivation of overall prevalence estimates for mental and neurological disorders. Disease burden was measured by disability adjusted life years (DALY). Prevalence: It is estimated that each year 38.2% of the EU population suffers from a mental disorder. Adjusted for age and comorbidity, this corresponds to 164.8million persons affected. Compared to 2005 (27.4%) this higher estimate is entirely due to the inclusion of 14 new disorders also covering childhood/adolescence as well as the elderly. The estimated higher number of persons affected (2011: 165m vs. 2005: 82m) is due to coverage of childhood and old age populations, new disorders and of new EU membership states. The most frequent disorders are anxiety disorders (14.0%), insomnia (7.0%), major depression (6.9%), somatoform (6.3%), alcohol and drug dependence (>4%), ADHD (5%) in the young, and dementia (1-30%, depending on age). Except for substance use disorders and mental retardation, there were no substantial cultural or country variations. Although many sources, including national health insurance programs, reveal increases in sick leave, early retirement and treatment rates due to mental disorders, rates in the community have not increased with a few exceptions (i.e. dementia). There were also no consistent indications of improvements with regard to low treatment rates, delayed treatment provision and grossly inadequate treatment. Disability: Disorders of the brain and mental disorders in particular, contribute 26.6% of the total all cause burden, thus a greater proportion as compared to other regions of the world. The rank order of the most disabling diseases differs markedly by gender and age group; overall, the four most disabling single conditions were: depression, dementias, alcohol use disorders and stroke. In every year over a third of the total EU population suffers from mental disorders. The true size of "disorders of the brain" including neurological disorders is even considerably larger. Disorders of the brain are the largest contributor to the all cause morbidity burden as measured by DALY in the EU. No indications for increasing overall rates of mental disorders were found nor of improved care and treatment since 2005; less than one third of all cases receive any treatment, suggesting a considerable level of unmet needs. We conclude that the true size and burden of disorders of the brain in the EU was significantly underestimated in the past. Concerted priority action is needed at all levels, including substantially increased funding for basic, clinical and public health research in order to identify better strategies for improved prevention and treatment for disorders of the brain as the core health challenge of the 21st century. Copyright © 2011. Published by Elsevier B.V.
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              Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches.

              A central problem in public health studies is how to make inferences about the causal effects of treatments or agents. In this article we review an approach to making such inferences via potential outcomes. In this approach, the causal effect is defined as a comparison of results from two or more alternative treatments, with only one of the results actually observed. We discuss the application of this approach to a number of data collection designs and associated problems commonly encountered in clinical research and epidemiology. Topics considered include the fundamental role of the assignment mechanism, in particular the importance of randomization as an unconfounded method of assignment; randomization-based and model-based methods of statistical inference for causal effects; methods for handling noncompliance and missing data; and methods for limiting bias in the analysis of observational data, including propensity score matching and sensitivity analysis.
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                Author and article information

                Contributors
                rose.uwe@baua.bund.de
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                3 November 2023
                3 November 2023
                2023
                : 23
                : 2159
                Affiliations
                [1 ]Federal Institute for Occupational Safety and Health (BAuA), ( https://ror.org/01aa1sn70) Nöldnerstr. 40/42, D-10317 Berlin, Germany
                [2 ]Department of Psychology, University of Copenhagen, ( https://ror.org/035b05819) Øster Farimagsgade 2A, København, 1353 Denmark
                Author information
                http://orcid.org/0000-0002-0170-6297
                Article
                17090
                10.1186/s12889-023-17090-9
                10625302
                baac4342-abc5-4a95-a4fe-208965da6271
                © The Author(s) 2023

                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 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.

                History
                : 14 February 2023
                : 28 October 2023
                Funding
                Funded by: Bundesanstalt für Arbeitsschutz und Arbeitsmedizin (BAuA) (4229)
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Public health
                longitudinal study,depression,sickness absence,employment,disability pension,work participation

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