International Archives of Occupational and Environmental Health最新文献

Objective: This study aimed to shed light on the potential relationships between blood volatile organic compounds (VOCs) and sleep health as well as mortality.

Methods: We employed generalized linear (GL), restricted cubic spline (RCS), weighted quantile sum (WQS), quantile-based g-calculation (QGC), and Bayesian kernel machine regression (BKMR) models to assess the relationship between blood VOCs-including bromoform (NHANES code: LBXVBF), bromodichloromethane (LBXVBM), chloroform (LBXVCF), dibromochloromethane (LBXVCM), and methyl tert-butyl ether (LBXVME)-and sleep health indicators (trouble sleeping, sleep disorders, and insufficient (< 6 h/day) or excessive (> 9 h/day) sleep) in participants from the NHANES 2007-2012. The Cox proportional hazards regression model was also used for survival analysis.

Results: The baseline profile categorized by sex showed that women had a higher prevalence of trouble sleeping, whereas men were more prone to insufficient sleep. We did not observe significant linear-correlations between VOCs and both increased sleep duration and poor sleep patterns, as shown by the weighted linear/logistic regression models. The RCS regression model indicated significant non-linear relationships (P for non-linear < 0.05) between certain VOC and sleep health. Adjusted QGC analysis highlighted LBXVBF as a crucial factor related to poor sleep quality (weighted 0.733). The BKMR analysis showed a positive trend between VOC levels (55th to 75th percentiles) and poor sleep pattern. Furthermore, the adjusted COX-RCS analysis identified LBXVME (P for non-linear = 0.0359) as a risk factor for all-cause mortality.

Conclusions: This study investigated the non-linear association between VOC exposure and sleep function, suggesting that VOC exposure may be linked to poor sleep patterns among U.S. adults.

Background: Limited research has explored the relationship between occupational noise exposure and liver enzymes, particularly at the individual exposure level. This study examines the association between occupational noise exposure and liver enzyme levels and the mediating role of metabolic dysfunction-associated fatty liver disease (MAFLD).

Methods: We recruited 3,427 workers from two factories in Guangzhou, China. Cumulative noise exposure (CNE) was estimated based on noise levels and years of exposure. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), and γ-glutamyl transferase (GGT) levels were obtained from medical examinations. Linear and logistic regression models, along with subgroup and mediation analyses, were employed to assess the associations between CNE and liver enzyme levels.

Results: Cumulative noise exposure (CNE) demonstrated a dose-response relationship with liver health indicators, with significant associations observed across different statistical models. Specifically, each 10 dB(A)-year increase in CNE was associated with a 2.10 U/L increase in ALT levels and a 26% higher risk of elevated ALT. Concurrently, categorical models revealed that workers in the highest CNE group had significantly increased risks of elevated ALT, AST, and GGT, with the most pronounced effect observed for AST. These associations were significantly strengthened by insufficient physical activity (P_{for interaction}<0.05). Notably, MAFLD mediated approximately 15-20% of the observed associations between CNE and liver enzymes (such as ALT and GGT).

Conclusion: Occupational noise exposure is positively associated with liver enzymes, with MAFLD as a partial mediator. Noise control measures and liver function monitoring may help mitigate liver dysfunction.

Purpose: Globally, coal production exposes millions of workers to coal mine dust. This study aimed to measure overall and site specific cancer incidence among coal mine workers (CMW) who performed different types of work.

Methods: A retrospective cohort of CMW in Queensland, Australia, was assembled using health assessment records from 1992. CMW were grouped by job type and then into Work Categories and linked to the Australian Cancer Database up to 2016. Standardized cancer incidence ratios (SIR) and relative cancer incidence ratios (aRIR) within the cohort, adjusted for age, era, and smoking status, were calculated for men and women with Poisson regression.

Results: There were 5,568 cancers diagnosed among 146,553 men and 396 in 19,927 women. The overall cancer risk was comparable to that of the general population for most Work Categories. The risk of lung cancer was higher for male Production (SIR 123, 95% Confidence Interval [CI] 107-142; adjusted Relative incidence Ratio (aRIR) (adjusted for era, age and smoking status) 1.23, 95%CI 0.99-1.52) and Construction workers (SIR 189, 95%CI 31-272; aRIR 1.78, 95%CI 1.20-2.62) when compared with the Australian population and within the cohort after adjusting for smoking. Laryngeal cancer was increased in Production workers (SIR 145, 95%CI 100-212).

Conclusions: Increased rates of lung and laryngeal cancers were identified for male Production workers and lung cancer for Construction workers. These could be related to mine workplace exposures such as silica and diesel engine exhaust.