Impact of sitting at work on musculoskeletal complaints of German workers - results from the study on mental health at work (S-MGA).

INTRODUCTION: Sedentary behavior (including prolonged sitting) is a form of physical inactivity that has a negative impact on health, possibly including musculoskeletal complaints (MSCs). The purpose of this study was to determine the extent to which time spent sitting at work is associated with the one-year prevalence of MSCs in the neck, shoulder, upper back/thoracic spine, and lower back among workers from the Study of Mental Health in the Workplace (S-MGA). In addition, the study also examined whether leisure time, physical activity, and sex modify the relationship between occupational sitting and MSCs. METHODS: For this analysis, we used the S-MGA, a 5-year prospective study in Germany. The S-MGA is a nationwide representative employee cohort study with a baseline survey in 2012 and a follow-up survey in 2017. Sitting at work was measured using a question asked at baseline. The Nordic Musculoskeletal Questionnaire was used to determine the one-year prevalence of MSCs in the neck, shoulder, upper back, and lower back pain (yes/no). The assessment of MSCs was only conducted at the 2017 follow-up. Adjusted Poisson regression models were used to determine the association of baseline level of weekly hours spent sitting at work with MSCs during follow-up. In addition to unadjusted models, models were adjusted for demographic (age, sex, body mass index and occupational skill level), occupational (heavy lifting at work), psychological disorders and lifestyle factors (smoking status and leisure time physical activity), as well as preexisting musculoskeletal conditions reported at baseline. To examine whether the relationship between sitting time and pain was modified by sex and leisure time physical activity, the models were stratified for both these variables. RESULTS: Among the participants analyzed (n = 2,082), 49.8% were male, while 50.2% were female, and more than 60% of the study population spent over half of their working hours in a sitting position. Exposure to increased sitting at work reported at baseline was not consistently associated with 12-month prevalence of MSCs in the upper body at follow-up. However, differences in the association between occupational sitting and MSCs were dependent on the intensity of leisure time physical activity. Prevalence ratios (PRs) indicated an increased prevalence of MSC in the neck (PR = 1.46; 95% CI = 1.18-1.80) and shoulder (PR = 1.30; 95% CI = 1.03-1.64) in workers without leisure time physical activity who spent 25 to < 35 weekly working hours sitting. DISCUSSION: These findings suggest that leisure time physical activity interacts with the relationship between sitting at work and MSCs. The relationship between sitting at work and musculoskeletal pain needs further investigation, but we found indications that leisure time physical activity may counter the effects of sitting at work.

Psychosocial work stress and parent-child bonding during the COVID-19 pandemic: clarifying the role of parental symptoms of depression and aggressiveness.

BACKGROUND: Parental work stress and impaired mental health seem to have intensified during the current COVID-19 pandemic. Both can have a negative impact on parent-child bonding: psychosocial work stress in the course of a spillover effect from work to family and symptoms of impaired mental health as part of a crossover effect from parent to child. This potentially affects the child's development in the long term. METHOD: This cross-sectional study examined the relationship between psychosocial work stress and parent-child bonding during the early COVID-19 pandemic (May-June 2020). Symptoms of depression and aggressiveness were considered as mediators of this relationship. The sample consisted of employees in Eastern Germany (n = 380; 42.9% mothers, 57.1% fathers), aged 24-55 years, with children aged 0-36 months. RESULTS: In the total sample, an association was only found after adjusting for potential confounders, indicating that higher psychosocial work stress is associated with weaker bonding between the parent and child (ß = 0.148, p = .017, 95% CI [0.566, 5.614]). The separate analyses for mothers and fathers did not reveal a statistically significant relationship between psychosocial work stress and parent-child bonding. In the total sample, the higher the psychosocial work stress was, the higher were the parental symptoms of depression (ß = 0.372, p < .001, 95% CI [3.417, 5.696]) and aggressiveness ß = 0.254, p < .001, 95% CI [1.008, 3.208]). The mental health symptoms in turn were related to weaker parent-child bonding (symptoms of depression ß = 0.320, p < .001, 95% CI [0.345, 0.749]; symptoms of aggressiveness ß = 0.394, p < .001, 95% CI [0.697, 1.287]). The results furthermore suggested that parental mental health symptoms mediate the association between psychosocial work stress and parent-child bonding (symptoms of depression, ab = 2.491, 95% CI [1.472, 3.577] and of aggressiveness, ab = 2.091, 95% CI [1.147, 3.279]). The mediation effect was also found in the separate analyses for the mothers and fathers. DISCUSSION: The results of this study during the early COVID-19 pandemic in Germany highlight the importance of prevention as well as intervention measures in relation to psychosocial work stress that may play a debilitating role in the context of family relationships. In addition, the results suggest that both employers and employees should be made aware of the importance of psychosocial work stress, as it can have a negative impact on mental health, which in turn may have a major influence on family relationships.

Psychosocial Occupational Exposures and Mental Illness.

BACKGROUND: The purpose of this study is to investigate the exposure-risk relationship between psychosocial occupational stress and mental illness. METHODS: We conducted a systematic review with meta-analyses as an update of a systematic review published in 2014. The study protocol was registered in PROSPERO (CRD42020170032). Literature searches were carried out in the MEDLINE, PsycINFO, and Embase databases. All procedural steps were performed independently by two reviewers; discordances were solved by consensus. All of the included full texts were subject to a methodological appraisal. Certainty of evidence was determined with the GRADE procedure. RESULTS: The pooled risk of depression was found to be approximately doubled in workers exposed to high job strain, which is defined as high work demands combined with low job control (effect estimate [EE] = 1.99, 95% CI [1.68; 2.35], heterogeneity [I2] = 24.7%, n = 8). In particular, high work demands are associated with incident depression (ES = 13.8 [1.19; 1.61], I2 = 69.0%, n = 9) and with incident anxiety disorder (ES = 1.79 [1.44; 2.23], I2 = 48.1%, n = 5). There were only a small number of methodologically adequate studies available on burnout, somatoform disorders, suicidal ideation, and suicide. Thus, no pooled risk estimates were calculated, although some individual studies showed a considerably increased risk. CONCLUSION: Psychosocial occupational stress is clearly associated with depression and anxiety disorders.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias.

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany.

OBJECTIVE: The aim of this study was to identify the occupational risk for a SARS-CoV-2 infection in a nationwide sample of German workers during the first wave of the COVID-19 pandemic (1 February-31 August 2020). METHODS: We used the data of 108 960 workers who participated in a COVID follow-up survey of the German National Cohort (NAKO). Occupational characteristics were derived from the German Classification of Occupations 2010 (Klassifikation der Berufe 2010). PCR-confirmed SARS-CoV-2 infections were assessed from self-reports. Incidence rates (IR) and incidence rate ratios (IRR) were estimated using robust Poisson regression, adjusted for person-time at risk, age, sex, migration background, study center, working hours, and employment relationship. RESULTS: The IR was 3.7 infections per 1000 workers [95% confidence interval (CI) 3.3-4.1]. IR differed by occupational sector, with the highest rates observed in personal (IR 4.8, 95% CI 4.0-5.6) and business administration (IR 3.4, 95% CI 2.8-3.9) services and the lowest rates in occupations related to the production of goods (IR 2.0, 95% CI 1.5-2.6). Infections were more frequent among essential workers compared with workers in non-essential occupations (IRR 1.95, 95% CI 1.59-2.40) and among highly skilled compared with skilled professions (IRR 1.36, 95% CI 1.07-1.72). CONCLUSIONS: The results emphasize higher infection risks in essential occupations and personal-related services, especially in the healthcare sector. Additionally, we found evidence that infections were more common in higher occupational status positions at the beginning of the pandemic.

The Gutenberg health study: a five-year prospective analysis of psychosocial working conditions using COPSOQ (Copenhagen psychosocial Questoinnaire) and ERI (effort-reward imbalance).

BACKGROUND: Psychosocial working conditions were previously analyzed using the first recruitment wave of the Gutenberg Health Study (GHS) cohort (n = 5000). We aimed to confirm the initial analysis using the entire GHS population at baseline (N = 15,010) and at the five-year follow-up. We also aimed to determine the effects of psychosocial working conditions at baseline on self-rated outcomes measured at follow-up. METHODS: At baseline, working GHS participants were assessed with either the Effort-Reward-Imbalance questionnaire (ERI) (n = 4358) or with the Copenhagen Psychosocial Questionnaire (COPSOQ) (n = 4322); participants still working after five years received the same questionnaire again (ERI n = 3142; COPSOQ n = 3091). We analyzed the association between working conditions and the outcomes job satisfaction, general health, burnout, and satisfaction with life at baseline, at follow-up and also prospectively from baseline to follow-up using linear regression models. We examined the outcome variance explained by the models (R2) to estimate the predictive performance of the questionnaires. RESULTS: The models' R2 was comparable to the original baseline analyses at both t0 and t1 (R2 range: ERI 0.10-0.43; COPSOQ 0.10-0.56). However, selected scales of the regression models sometimes changed between assessment times. The prospective analysis showed weaker associations between baseline working conditions and outcomes after five years (R2 range: ERI 0.07-0.19; COPSOQ 0.07-0.24). This was particularly true for job satisfaction. After adjusting for the baseline levels of the outcomes, fewer scales still explained some of the variance in the distribution of the outcome variables at follow-up. The models using only data from t0 or t1 confirmed the previous baseline analysis. We observed a loss of explained variance in the prospective analysis models. This loss was greatest for job satisfaction, suggesting that this outcome is most influenced by short-term working conditions. CONCLUSIONS: Both the COPSOQ and ERI instruments show good criterion validity and adequately predict contemporaneously measured self-reported measurements of health and (occupational) well-being. However, the COPSOQ provides a more detailed picture of working conditions and might be preferable for improvment strategies in workplaces. Additional prospective research with shorter follow-up times would be beneficial for estimating dose-response relationships.

Correction: Work-life conflict and cardiovascular health: 5-year follow-up of the Gutenberg Health Study.

[This corrects the article DOI: 10.1371/journal.pone.0251260.].

Vaccine-Preventable Infections in Childcare Workers.

BACKGROUND: Adequate immunity to so-called childhood diseases can lower the occupational risk of vaccine-preventable infectious diseases in persons who work in day-care centers for children. METHODS: A systematic literature survey was carried out in PubMed and Embase for the period January 2000 to February 2019. Studies on immune status and vaccination status were included. In addition, data from the first wave of the German Health Interview and Examination Survey for Adults (Studie zur Gesundheit Erwachsener in Deutschland, DEGS1) and surveillance data on notifiable infections in Germany were evaluated. RESULTS: Six studies and the DEGS1 analysis of vaccination or immune status for varicella zoster, rubella, hepatitis A (HAV), pertussis, measles, and mumps in persons caring for children in day-care centers, most of whom are women, were included in this review. According to DEGS1, childcare workers are more commonly vaccinated against HAV and pertussis than the general female population (prevalence ratios [PR]: 1.46 [1.12; 1.90] and 1.57 [1.05; 2.36]), yet 57% had not been vaccinated against HAV and 77% had not been vaccinated against pertussis. Childcare workers were found to be less commonly vaccinated against rubella than the general female population, although the difference was not statistically significant (PR: 0.87 [0.71; 1.07]). In a Canadian study, positive HAV serology was found to be correlated with the duration of activity as a childcare worker. In the DEGS1 study, large proportions of the younger childcare workers in particular were seronegative against measles (16%), mumps (19%), and HAV (37%). Notifiable disease statistics show that those working in community facilities had a markedly higher risk of mumps, pertussis, and varicella (relative risk [RR]: 1.8-2.6) and a somewhat higher risk of rubella and HAV (RR: 1.47 and 1.21, respectively). CONCLUSION: Childcare workers have a higher occupational risk of infection but do not always receive the appropriate vaccinations. In particular, women of child-bearing age working in day-care centers should be made more aware of the need for vaccination.

Behavioral and Emotional Disorders and Transportation Noise among Children and Adolescents: A Systematic Review and Meta-Analysis.

Children and adolescents may be particularly vulnerable to environmental influences such as noise which can affect mental well-being. The aim of this systematic review was to evaluate the effect of transportation noise on behavioral and emotional disorders in children and adolescents using a meta-analytic approach. Therefore, we searched four databases (Pubmed, Embase, PsychINFO, and PSYNDEX) and grey literature until February of 2019. We identified 14 articles from 10 studies examining the effect of transportation noise exposure on the mental health of children. These studies predominately used the Strength and Difficulties Questionnaire (SDQ) and mainly focused on schoolchildren and adolescents aged 9-10 years and 15-17 years in Europe. Three studies could be included in the meta-analysis. In sum, the odds for hyperactivity/inattention and total difficulties was significantly increased by 11% (Odds Ratio, OR = 1.11 (95% Confidence Interval, CI 1.04-1.19), respectively 9% (95% CI 1.02-1.16) per 10 dB road traffic noise. Thus, we obtained evidence for an effect of road traffic noise on hyperactivity/inattention and total difficulties, although we could consider few studies. Future studies are needed that use similar techniques to assess outcomes and exposures at schools and in homes. This would make it possible to conduct an individual participant data pooled analysis of the data.