Objective To explore the potential causal relationship between occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") and five mental disorders (depression, bipolar disorder, schizophrenia, insomnia and anxiety) using the two-sample Mendelian randomization (MR) method. Methods Single nucleotide polymorphisms (SNPs) loci associated with pneumoconiosis and five mental disorders were screened from Genome-Wide Association Studies. Inverse variance weighting (IVW), weighted median (WM) and MR-Egger regression methods were used to evaluate the significance of the causal relationship between pneumoconiosis and five mental disorders. Sensitivity analysis was used to evaluate the accuracy and reliability of the research results. Results After matching data of pneumoconiosis and the five mental disorders, 16 SNPs were ultimately included as instrumental variables in this study. The result of MR analysis revealed a positive causal relationship between pneumoconiosis and both depression [IVW: odds ratio (OR) and 95% confidence interval (CI) was 1.017 (1.000-1.035), P<0.05] and bipolar disorder [IVW: OR(95%CI)was 1.046(1.009-1.083), P<0.05; WM: OR (95%CI) was 1.055(1.007-1.105), P<0.05]. Result of sensitivity analysis indicated there was no heterogeneity and horizontal pleiotropy in the above results. There was no causal association observed between pneumoconiosis and schizophrenia, insomnia, or anxiety disorders (all P>0.05). Conclusion This study provides genetic evidence supporting a positive causal relationship between pneumoconiosis and both depression and bipolar disorder.

Objective To analyze the current status of occupational health literacy (OHL) among front-line workers in the metal products industry and to explore its influencing factors. Methods A total of 5 193 front-line workers from the metal products industry in 14 prefecture-level cities in Guangdong Province were selected as the research subjects by the stratified cluster random sampling method. The Occupational Health Literacy Questionnaire of National Key Populations was used to assess their OHL levels. To analyze the influencing factors of OHL, binary logistic regression analysis was conducted. Results The overall OHL level among the participants was 40.0% (2 079/5 193). The result of binary logistic regression analysis showed that workers with lower educational level, lower average monthly personal income, and smaller enterprise size had lower OHL levels (all P<0.01). In addition, workers in foreign-funded enterprises had higher OHL levels than those in private enterprises (P<0.01). Conclusion There remains considerable room for improvement in OHL among front-line workers in the metal products industry. Priority focus is to improve OHL among workers with lower education and income levels, as well as those employed in private and micro- or small-sized enterprises.

Objective To analyze the effect of night-shift work, anxiety and their interaction on work-related musculoskeletal disorders (WMSDs) among electronics manufacturing employees. Methods A total of 2 676 employees from 58 electronic manufacturing enterprises in the Pearl River Delta region of Guangdong Province were selected as the research subjects using the judgment sampling method. The Basic Situation Survey Scale, Generalized Anxiety Disorder 7-item Scale and Questionnaire of Musculoskeletal Disorders were used to assess night-shift work, anxiety and the prevalence of WMSDs in employees. The multivariate logistic regression model was used to analyze the effects of night-shift work, anxiety and their combined effects on the risk of WMSDs. Results The proportion of night-shift work was 30.3%, and the detection rates of anxiety and WMSDs were 26.8% and 41.3%, respectively. The results of multivariate logistic regression analysis showed that night-shift work and anxiety were independent risk factors of WMSDs in the research subjects, after excluding the influence of confounding factors such as age, marital status, enterprise size and length of service [odds ratio (OR) and 95% confidence interval (CI) were 1.307 (1.092-1.564) and 3.282 (2.739-3.934), respectively, both P<0.01]. Compared with those without night-shift work or anxiety, the risk of WMSDs was higher in individuals with only night-shift work, only anxiety, or both night-shift work and anxiety [OR and 95%CI were 1.347 (1.091-1.663), 3.395 (2.727-4.227) and 4.117 (3.072-5.519), respectively, all P<0.01]. Conclusion Both night-shift work and anxiety can increase the risk of WMSDs among electronic manufacturing employees, and these two factors exhibit a synergistic effect in increasing the risk of WMSDs.