Objectives The aim of this study was to assess the effects of coexposure to job strain and shift work on mental health in railway workers. Design Cross-sectional study. Setting One Railway Bureau Group in China. Participants A total of 1270 front-line railway workers. Outcome measures The Symptom Checklist-90-Revised questionnaire was used to measure general mental health. Job strain variables were derived from the Job Content Questionnaire. Based on the records of the work schedule 3 months prior to the survey, the following three shift types were identified: fixed day, fixed night and rotating night shifts. Risks associated with mental health were assessed by carrying out logistic regression analysis which was adjusted for age, job tenure, smoking and exercise. Additionally, a crossover analysis was employed for the combined effects. Results High levels of job strain were linked to a higher risk of poor mental health (OR=1.53, 95% CI: 1.10 to 2.11). After adjusting for confounding factors, night shifts and rotating night shifts were significant risk factors for mental health (OR=2.21, 95% CI: 1.60 to 3.07; OR=2.36, 95% CI: 1.73 to 3.22). Compared with participants who experienced a low level of job strain and day shifts, those with a high level of job strain and who worked rotating shifts were at the highest risk of poor mental health (OR=4.68, 95% CI: 2.91 to 8.04), whereas the influence of a low level of job strain and rotating night shifts was not statistically significant. Conclusion Job strain and night shifts among workers were associated, both independently and in combination, with an increased risk of poor mental health. Our data suggest that job strain contributes to the risk of poor mental health by means of a combined effect with shift work.

The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32–16.72) and 3.84% (95% CI: 0.28–7.54) per 10 μg/m³ increase of PM_2.5 and PM₁₀, respectively, compared to non-heat waves. Compared with low-level PM_2.5 concentration on non-heat waves layer, the high level of PM_2.5 concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37–106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.

Background: Previous studies have suggested that there is an association between air pollutants and circulatory and respiratory diseases; however, relatively few have analyzed the association between air pollutants and outpatient visits based on the mortality, hospitalization rates, etc., especially in areas with relatively good air quality. Therefore, we conducted this study to research the association between air pollutants and outpatient visits in Fuzhou, China. Methods: We used a generalized linear Poisson model to study the association between air pollution and outpatient visits for respiratory and circulatory diseases from 2016 to 2018 in Fuzhou, China. Results: In the single pollutant model, nitrogen dioxide (NO₂) had a significant effect. For lag day 0 to lag day 5, the effect decreased with every 10 μg/L increase in NO₂. The daily maximum 8-h mean ozone (O₃-8h) and upper respiratory outpatient visits were positively associated during the cold period [lag2, excess risk (ER) (95% confidence interval (CI)): 1.68% (0.44–2.94%)], while O₃-8h and respiratory disease were positively associated during the warm period [lag5, ER (95% CI): 1.10% (0.11–2.10%) and lag4, ER (95% CI): 1.02% (0.032–2.02%)]. Similarly, particulate matter (PM) with an average aerodynamic diameter of less than 10 μm (PM₁₀) and lower respiratory diseases were positively associated during the warm period [lag0, ER (95% CI): 1.68% (0.44–2.94%)]. When the concentration of O₃-8h was higher than 100 μg/L, there was a positive effect on circulatory [lag5, ER (95% CI): 2.83% (0.65–5.06%)], respiratory [lag5, ER (95% CI): 2.47% (0.85–4.11%)] and upper respiratory [lag5, ER (95% CI): 3.06% (1.38–4.77%)] outpatient visits. The variation in O₃-8h changed slightly when we adjusted for other air pollutants, and after adjusting for O₃-8h, the ERs of the other air pollutants changed slightly. After adjusting for PM with an average aerodynamic diameter of less than 2.5 μm (PM_2.5), the ERs of the other air pollutants increased, and after adjusting for NO₂, the ER of PM decreased. Conclusion: Exposure to ambient NO₂, O₃, PM_2.5 and PM₁₀ was associated with an increase in respiratory and circulatory system-related outpatient visits in Fuzhou, China.

Gastric cancer (GC) typically carries a poor prognosis as it is often diagnosed at a late stage. Altered metabolism has been found to impact cancer outcomes and affect patients’ quality of life, and the role of metabolites in gastric cancer prognosis has not been sufficiently understood. We aimed to establish a prognostic prediction model for GC patients based on a metabolism-associated signature and identify the unique role of metabolites in the prognosis of GC. Thus, we conducted untargeted metabolomics to detect the plasma metabolites of 218 patients with gastric adenocarcinoma and explored the metabolites related to the survival of patients with gastric cancer. Firstly, we divided patients into two groups based on the cutoff value of the abundance of each of the 60 metabolites and compared the differences using Kaplan–Meier (K-M) survival analysis. As a result, 23 metabolites associated with gastric cancer survival were identified. To establish a risk score model, we performed LASSO regression and Cox regression analysis on the 60 metabolites and identified 8 metabolites as an independent prognostic factor. Furthermore, a nomogram incorporating clinical parameters and the metabolic signature was constructed to help individualize outcome predictions. The results of the ROC curve and nomogram plot showed good predictive performance of metabolic risk features. Finally, we performed pathway analysis on the 24 metabolites identified in the two parts, and the results indicated that purine metabolism and arachidonic acid metabolism play important roles in gastric cancer prognosis. Our study highlights the important role of metabolites in the progression of gastric cancer and newly identified metabolites could be potential biomarkers or therapeutic targets for gastric cancer patients.

Recent studies have shown that incessant job stress could eventually result in sleep dysfunction (SD), and most importantly, the essential role dopamine receptor D2 (DRD2) gene polymorphisms play in the psychopathological mechanism of SD. The Effort-Reward Imbalance scale and the Pittsburgh Sleep Quality Index were both used to access SD and job stress (JS). A significant negative correlation was observed between the sDA levels and SD subscale scores (sleep efficiency, daytime dysfunction). The findings revealed that high levels of JS were linked to a higher SD score (OR = 2.13, 95% CI: 1.46–3.12). Likewise, the homozygous A1A1 genotype of DRD2 rs1800497 was more likely to be associated with SD (OR = 2.90, 95% CI: 1.75–4.82). Compared to participants with low JS and heterozygous A1A2/A2A2 genotype, those with both high JS and homozygous A1A1 genotype had a higher SD score (OR = 5.40, 95% CI: 2.89–10.11). The A1 allele of the DRD2 rs1800497 polymorphism also enhances the likelihood of SD when undergoing JS. Besides, subjects with low JS and the homozygous A1A1 genotype also showed an increased possibility for sleep dysfunction (OR = 2.05, 95% CI: 1.03–4.11). Our results suggest that the DA system may interrelate with JS to affect sleep.