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The COVID-19 pandemic changed the future of work sustainably and led to a general increase in mental stress. A study conducted during the second and third pandemic wave with a retrospective survey of the first wave among 1,545 non-healthcare workers confirmed an increase in anxiety and depression symptoms and showed a correlation with the occupational SARS-CoV-2 infection risk. This online follow-up survey aims to examine changes in mental distress as the pandemic progressed in Germany and to identify factors influencing potential changes. Longitudinal data from 260 subjects were available for this analysis. Mental distress related to anxiety and depression symptoms, assessed by the Patient Health Questionnaire-4 (PHQ-4), and occupational risk factors were solicited at the end of 2022 and retrospectively at the fifth wave. Categorized PHQ-4 scores were modelled with mixed ordinal regression models and presented with odds ratios (OR) and 95% confidence intervals (95% CI). A previous diagnosis of a depressive or anxiety disorder was a strong risk factor for severe symptoms (OR 3.49, 95% CI 1.71-7.11). The impact of occupational SARS-CoV-2 infection risk on mental distress was increased, albeit failing to reach the formal level of statistical significance (high risk OR 1.83, 95% CI 0.59-5.63; probable risk OR 1.72, 95% CI 0.93-3.15). Mental distress was more pronounced in those with a previous diagnosis of anxiety and depression. Confirmed occupational risk factors were protective measures against occupational SARS-CoV-2 infection perceived as inadequate, chronic work-related stress, overcommitment, reduced interactions with fellow-workers, and work-privacy conflicts. The pandemic had a negative impact on anxiety and depression symptoms among the studied non-healthcare workers, particularly early in the pandemic, although this effect does not appear to be permanent. There are modifiable risk factors that can protect workers' mental health, including strengthening social interactions among employees and reducing work-privacy conflicts.

Night and shift work are suspected to cause various adverse effects on health and sleep. Sleep deprivation through shift work is assumed to be compensated on free days. So far it is not clear how different shift systems and shift lengths affect sleep structure on work and free days. Especially working night shifts disrupts the circadian rhythm but also extended working hours (12h) might affect sleep characteristics. Hitherto, the magnitude of sleep debt, social jetlag, and Locomotor Inactivity During Sleep (LIDS) in different shift systems is unknown. Here, we investigated the impact of five different shift rosters on sleep in 129 industrial workers from Germany. Permanent night work with multiple shift systems with and without night shifts and with different shift lengths were compared. Wrist-activity was monitored over 28 days revealing sleep on- and offsets as well as LIDS as proxy for sleep quality. Overall, 3,865 sleep bouts comprising 22,310 hours of sleep were examined. The mean daily age-adjusted sleep duration (including naps) was 6:43h and did not differ between shift workers of different rosters. However, sleep duration on workdays was particularly low in rotational shift systems with 12h-shifts (5:00h), while overall sleep debt was highest. Shift workers showed a median absolute social jetlag of 3:03h, which differed considerably between shift types and rosters (p<0.0001). Permanent night workers had the highest social jetlag (5:08h) and latest mid-sleeps on workdays and free days. Sleep quality was reduced in permanent night shift workers compared with shift workers in other rosters and differed between daytime and nighttime sleep. Shift work leads to partial sleep deprivation, which particularly affects workers in 12h-shifts and permanent night shifts. Working these shifts resulted in higher sleep debts and larger absolute social jetlag whereas sleep quality was especially reduced in permanent night shift workers compared with shift workers of other rosters.

We compared psychomotor vigilance in female shift workers of the Bergmannsheil University Hospital in Bochum, Germany (N = 74, 94% nurses) after day and night shifts. Participants performed a 3-minute Psychomotor Vigilance Task (PVT) test bout at the end of two consecutive day and three consecutive night shifts, respectively. Psychomotor vigilance was analyzed with respect to mean reaction time, percentage of lapses and false starts, and throughput as an overall performance score, combining reaction time and error frequencies. We also determined the reaction time coefficient of variation (RTCV) to assess relative reaction time variability after day and night shifts. Further, we examined the influence of shift type (night vs. day) by mixed linear models with associated 95% confidence intervals (CI), adjusted for age, chronotype, study day, season, and the presence of obstructive sleep apnea (OSA). At the end of a night shift, reaction times were increased (β = 7.64; 95% CI 0.94; 14.35) and the number of lapses higher compared to day shifts (exp(β) = 1.55; 95% CI 1.16-2.08). By contrast, we did not observe differences in the number of false starts between day and night shifts. Throughput was reduced after night shifts (β = -15.52; 95% CI -27.49; -3.46). Reaction times improved across consecutive day and night shifts, whereas the frequency of lapses decreased after the third night. RTCV remained unaffected by both, night shifts and consecutive shift blocks. Our results add to the growing body of literature demonstrating that night-shift work is associated with decreased psychomotor vigilance. As the analysis of RTCV suggests, performance deficits may selectively be driven by few slow reactions at the lower end of the reaction time distribution function. Comparing intra-individual PVT-performances over three consecutive night and two consecutive day shifts, we observed performance improvements after the third night shift. Although a training effect cannot be ruled out, this finding may suggest better adaptation to the night schedule if avoiding fast-changing shift schedules.

The use of face masks became mandatory during SARS-CoV-2 pandemic. Wearing masks may lead to complaints about laboured breathing and stress. The influence of different masks on cardiopulmonary performance was investigated in a partially double-blinded randomized cross-over design. Forty subjects (19–65 years) underwent body plethysmography, ergometry, cardiopulmonary exercise test and a 4-h wearing period without a mask, with a surgical mask (SM), a community mask (CM), and an FFP2 respirator (FFP2). Cardiopulmonary, physical, capnometric, and blood gas related parameters were recorded. Breathing resistance and work of breathing were significantly increased while wearing a mask. During exercise the increase in minute ventilation tended to be lower and breathing time was significantly longer with mask than without mask. Wearing a mask caused significant minimal decreases in blood oxygen pressure, oxygen saturation, an initial increase in blood and inspiratory carbon dioxide pressure, and a higher perceived physical exertion and temperature and humidity behind the mask under very heavy exercise. All effects were stronger when wearing an FFP2. Wearing face masks at rest and under exercise, changed breathing patterns in the sense of physiological compensation without representing a health risk. Wearing a mask for 4-h during light work had no effect on blood gases.

Objectives: We investigated the association of shift and night work with the incidence of prostate cancer using data of the population-based prospective Heinz Nixdorf Recall Study from the highly industrialized Ruhr area in Germany. Methods: Participants of the baseline survey were recruited between 2000-2003. A follow-up survey including, a detailed interview on shift and night work, was conducted from 2011-2014. We included 1757 men who did not report a history of prostate cancer at baseline. We assessed shift- and night-work exposure up to time of the baseline interview. Incident prostate cancers were recorded from baseline through September 2014. We calculated hazard ratios (HR) of shift- and night-work exposure using Cox proportional hazards regression with age at event as timescale, adjusting for smoking status, family history of prostate cancer, education (≤13, 14-17, ≥18 years), and equivalent income (low, medium, high). Results: We observed a twofold increased HR for prostate cancer among shift and night workers. Ever employment in shift work was associated with HR 2.29, 95% confidence interval (CI) 1.43-3.67 and night work with HR 2.27, 95% CI 1.42-3.64. HR increased steadily with duration of employment in shift or night work. Stratifying analyses by preferred midpoint of sleep, yielded strongly elevated HR among subjects with early sleep preference, although these analyses were limited by small number of cases. Conclusions: We identified increased risks for prostate cancer among men with employment in shift or night work. HR were strongly elevated among long-term employed shift workers and men with early preferred midpoint of sleep.

An increased risk for an occupation-related SARS-CoV-2 infection has been linked to higher psychological distress. This online survey investigates the prevalence of depressive and anxiety symptoms in a large sample of 34,303 participants from the German cohort for digital health research (DigiHero) after the pandemic (late 2023, t1) and retrospectively from the Omicron wave (early 2022, t0), emphasizing variations across occupational groups and work-related risk factors. Participants reported their employment status (currently working; seeking employment; not working). Workers provided their primary occupation to assess occupational SARS-CoV-2 infection risk. Symptoms of depression and anxiety (assessed via PHQ-4) and additional occupational risk factors were solicited for each time point. Associations between occupational exposure and stressors with the four-level PHQ-4 outcome were analyzed separately for t1 and t0 using ordinal regression and expressed as odds ratios (OR) with 95% confidence intervals (CI). Over 60% of respondents were working at t1, and 1.4% classified themselves as seeking a job. Job seekers reported highest and non-working individuals lowest depressive and anxiety symptoms. Symptom severity varied by occupation with elevated odds in traffic/logistics professions exclusively at t1 (OR=1.24, 95% CI 1.04-1.48) and healthcare professions exclusively at t0 (OR=1.08, 95% CI 1.01-1.16). High occupational SARS-CoV-2 infection risk was linked to symptoms at t0. Overall, these associations were modest and partly attenuated after additional adjustment for individual work-related stressors (e.g., loneliness at work, chronic work-related stress, work-privacy conflicts). At both timepoints, individual stressors and sociodemographic factors showed stronger associations with severe symptoms than occupation (e.g., chronic work-related stress at t1 OR=2.87, 95% CI 2.70-3.04). Persistent post-pandemic depressive and anxiety symptoms among workers emphasize the importance of addressing individual psychosocial work-related stressors.

To quantify the subjective and cognitive impairment caused by wearing face masks at work, 20 men and 20 women (median age 47 years, range 19–65) were tested under different ergometer workloads while wearing surgical mask, community mask, FFP2 respirator or no mask in a randomized and partially double-blinded design. Masks were worn also at the workplace for four hours. Subjective impairment was recorded by questionnaires. Cognitive performance was tested before and after the workplace examination. Subjective feeling of heat, humidity, and difficult breathing increased with rising physical exertion and wearing time for all three mask types, most notably for FFP2. Even when blinded, participants with FFP2 reported difficult breathing already at rest. During physical exertion, individuals with low tolerance to discomfort reported significantly stronger impairment (OR 1.14, 95% CI 1.02–1.27). Regarding light work, older subjects (OR 0.95, 95% CI 0.92–0.98) and women (OR 0.84, 95% CI 0.72–0.99) showed significantly lower and atopic subjects stronger impairment (OR 1.16, 95% CI 1.06–1.27). No significant influence of mask wearing was detected on cognitive performance. Wearing a mask had no effect on cognitive performance, but led to discomfort which increased with physical exertion and wearing time. Individuals who tolerate discomfort poorly felt more impaired by wearing a mask during physical exertion.

Background For more than 80 years, cystoscopy has been the gold standard for identification of urothelial carcinoma (UCa). Because of many factors, such as pain of the patients during this procedure or the costs involved, non-invasive detection of UCa remains a challenge. Herein, we verify our previously identified urinary biomarkers C-X-C Motif Chemokine Ligand 16 (CXCL16) and transforming growth-factor beta induced protein (TGFBI) on the protein level as well as the CpG sites ALOX5, TRPS1 and an intergenic region on Chromosome 16 on DNA methylation level in an independent cross-sectional study. Methods We collected N = 1119 urines from individuals coming to urological and gynecological check-ups, follow-up care or patients suspicious for UCa or already diagnosed for different urologic or gynecologic cancer entities. We performed methylation analysis of various CpG sites with DNA isolated from urine sediment and quantified the concentration of the protein markers CXCL16 and TGFBI in the corresponding urine supernatant using ELISA. We tested for patient-group differences with two-sided Wilcoxon rank sum tests and examined the performance with receiver operating characteristic curves. For verification, we analyzed the marker performance with previously set cutoff-values and marker combinations with established and experimental algorithms (with logical OR-conjunction, iterative threshold-based biomarker and score combining algorithm “PanelomiX”). Results Evaluation confirmed that our previously identified protein and DNA methylation biomarkers can distinguish UCa from frequent urological and gynecological cancers. CXCL16 and TGFBI discriminated UCa cases with a sensitivity of 31% and 56% and a specificity of 94% and 85%, respectively. Combining methylation markers resulted in UCa detection in men with a sensitivity of 54% and a specificity of 94%. Extending analysis by combining all methylation and protein markers (up to five markers in total) yielded a convincingly high specificity of 97% at a sensitivity of 72% for the identification of UCa patients within a heterogeneous collective of cancer-free individuals and patients suffering from urological or gynecological cancers. Conclusion Combining various biomarkers at protein and DNA level demonstrates a new option of non-invasive UCa diagnosis in urine, and thus might help to reduce the number of unnecessary cystoscopies, especially in patients without a history of UCa.

ObjectivesTraditional epidemiological approaches usually assume a constant relationship between cumulative exposure and disease, which implies that exposure duration and intensity contribute equally to the studied outcome. But individuals with the same cumulative exposure but different temporal exposure patterns may show different risks. Trajectory classification is a good way to assess exposure–risk associations and leads to a better understanding of lifetime variability in exposure levels. Therefore, this study aimed to estimate lung cancer risk according to the exposure trajectory classes on welding fumes and cigarette smoking.DesignTwo population-based German case–control studies.Participants3498 male lung cancer cases and 3539 male control subjects.MethodsSeparate latent class mixed models (LCMM) were determined to identify profiles of exposure trajectories of cigarette smoking and occupational exposure to welding fumes. To investigate the risk of lung cancer by class membership, ORs with 95% CI were estimated via multiple logistic regression analyses.ResultsLCMM each identified four latent classes of smoking and welding-fume exposure. Classes of smokers showed much higher risk of lung cancer compared with never smokers or subjects exposed to welding fumes. Smokers in one class characterised with the highest exposure over the past 10 years had the highest adjusted lung cancer risk (OR=39; 95% CI 29 to 53). For welding, the highest lung cancer risks were found for the class in which exposure to welding fumes in the past 10 years prior to the diagnosis of lung cancer was highest and the duration of welding was also quite high (OR=1.71; 95% CI 0.92 to 3.15).ConclusionsIn summary, LCMM opens a new perspective on dose–effect relationships and could be employed to complement established epidemiological methods.

To examine the effect of night shift on salivary cortisol at awakening (C1), 30 min later (C2), and on the cortisol awakening response (CAR, the difference between C2 and C1). We compared shift and non-shift workers with a focus on the impact of worker chronotype. Our study included 66 shift-working females (mean age = 37.3 years, SD = 10.2) and 21 non-shift working females (mean age = 47.0 years, SD = 8.9). The shift workers collected their saliva samples at C1 and C2 on each two consecutive day shifts and night shifts. Non-shift workers collected their samples on two consecutive day shifts. We applied linear mixed-effects models (LMM) to determine the effect of night shift on CAR and log-transformed C1 and C2 levels. LMMs were stratified by chronotype group. Compared to non-shift workers, shift workers before day shifts (i.e. after night sleep) showed lower cortisol at C1 (exp ( β ^ ) =0.58, 95% CI 0.42, 0.81) but not at C2. In shift workers, the CARs after night shifts (i.e. after day sleep) were lower compared to CARs before day shifts ( β ^ = − 11.07, 95% CI − 15.64, − 6.50). This effect was most pronounced in early chronotypes (early: β ^ = − 16.61, 95% CI − 27.87, − 5.35; intermediate: β ^ = − 11.82, 95% CI − 18.35, − 5.29; late: β ^ = − 6.27, 95% CI − 14.28, 1.74). Chronotype did not modify the association between night shift and CAR. In our population of shift workers, there was a mismatch between time of waking up and their natural cortisol peak at waking up (CAR) both during day and night shift duties.