An Evaluation of the Ventilatory Function in Shipyard Welders Using the Lifetime Cumulative Exposure to Welding Fumes

Author(s):  
Chun Hwa Jung ◽  
Hyeon Woo Yim ◽  
Jung Wan Koo ◽  
Chung Yill Park
2020 ◽  
pp. oemed-2020-106738
Author(s):  
Angelo d’Errico ◽  
Jana Zajacova ◽  
Anna Cacciatore ◽  
Santo Alfonzo ◽  
Fabio Beatrice ◽  
...  

ObjectivesThere is sufficient evidence for a causal association of sinonasal epithelial cancers (SNEC) only for exposure to wood and leather dusts, nickel compounds and employment in isopropyl alcohol production. The aim of this study was to assess whether other occupational hazards are associated with the risk of SNEC for the main histologic types, namely adenocarcinoma (AD) and squamous cell carcinoma (SCC).MethodsThe study population included 375 incident SNEC cases collected from 1996 to 2014 (79% of all diagnosed SNEC) throughout the Piedmont region by the regional Sinonasal Cancer Registry, and 408 hospital controls. Exposure to 17 occupational agents was assigned through expert assessment based on interviews to the subjects on jobs held throughout their working life. The relationship of SNEC with ever and cumulative exposure to the hazards was assessed through unconditional logistic regression models adjusted for age, sex, area of residence, smoking habit, year of enrolment and coexposures.ResultsAD was associated with both ever and cumulative exposure to wood dust, leather dust and organic solvents, and with cumulative exposure to textiles dusts. SCC risk was significantly increased by ever exposure to nickel, chromium and welding fumes, as well as by cumulative exposure to welding fumes, arsenic and organic solvents. A mixed group of other histological types was associated with both ever and cumulative exposure to wood dust and textile dusts.ConclusionsThe associations of SNEC with wood dust, leather dust and nickel were confirmed, while some new associations were observed for other hazards, which merit further investigation.


2019 ◽  
Vol 188 (11) ◽  
pp. 1984-1993 ◽  
Author(s):  
Beate Pesch ◽  
Benjamin Kendzia ◽  
Hermann Pohlabeln ◽  
Wolfgang Ahrens ◽  
Heinz-Erich Wichmann ◽  
...  

Abstract To investigate the risk of lung cancer after exposure to welding fumes, hexavalent chromium (Cr(VI)), and nickel, we analyzed 3,418 lung cancer cases and 3,488 controls among men from 2 German case-control studies (1988–1996). We developed a welding-process exposure matrix from measurements of these agents, and this was linked with welding histories from a job-specific questionnaire to calculate cumulative exposure variables. Logistic regression models were fitted to estimate odds ratios with confidence intervals conditional on study, and they adjusted for age, smoking, and working in other at-risk occupations. Additionally, we mutually adjusted for the other exposure variables under study. Overall, 800 cases and 645 controls ever worked as regular or occasional welders. Odds ratios for lung cancer with high exposure were 1.55 (95% confidence interval (CI): 1.17, 2.05; median, 1.8 mg/m3 × years) for welding fumes, 1.85 (95% CI: 1.35, 2.54; median, 1.4 μg/m3 × years) for Cr(VI), and 1.60 (95% CI: 1.21, 2.12; median, 9 μg/m3 × years) for nickel. Risk estimates increased with increasing cumulative exposure to welding fumes and with increasing exposure duration for Cr(VI) and nickel. Our results showed that welding fumes, Cr(VI), and nickel might contribute independently to the excess lung cancer risk associated with welding. However, quantitative exposure assessment remains challenging.


JAMA ◽  
1966 ◽  
Vol 197 (13) ◽  
pp. 1095-1095
Author(s):  
G. L. Snider
Keyword(s):  

2004 ◽  
Author(s):  
D. Vinson ◽  
L. Conroy ◽  
T. Schoonover ◽  
S. Dorevitch ◽  
S. Erdal ◽  
...  

2004 ◽  
Author(s):  
J. Schnackenbeck ◽  
S. Erdal ◽  
T. Schoonover ◽  
L. Conroy

2020 ◽  
Author(s):  
Brian M. Hicks ◽  
D. Angus Clark ◽  
Joseph D. Deak ◽  
Mengzhen Liu ◽  
C. Emily Durbin ◽  
...  

Importance: Large consortia of genome wide association studies have yielded more accurate polygenic risk scores (PRS) that aggregate the small effects of many genetic variants to characterize the genetic architecture of disorders and provide a personalized measure of genetic risk. Objective: We examined whether a PRS for smoking measured genetic risk for general behavioral disinhibition by estimating its associations with externalizing and internalizing psychopathology and related personality traits. We examined these associations at multiple time points in adolescence using more refined phenotypes defined by stable characteristics across time and at young ages, which reduced potential confounds associated with cumulative exposure to substances and reverse causality. Methods: Random intercept panel models were fit to symptoms of conduct disorder, oppositional defiant disorder, major depressive disorder (MDD), and teacher ratings of externalizing and internalizing problems and personality traits at ages 11, 14, and 17 years-old in the Minnesota Twin Family Study (N = 3225). Results: The smoking PRS had strong associations with the random intercept factors for all the externalizing measures (mean standardized ꞵ = .27), agreeableness (ꞵ=-.22, 95% CI: -.28, -.16), and conscientiousness (ꞵ=-.19, 95% CI: -.24, -.13), but was not significantly associated with the internalizing measures (mean ꞵ = .06) or extraversion (ꞵ=.01, 95% CI: -.05, .07). After controlling for smoking at age 17, the associations with the externalizing measures (mean ꞵ = .13) and personality traits related to behavioral control (mean ꞵ = -.10) remained statistically significant. Conclusions and Relevance: The smoking PRS measures genetic influences that contribute to a spectrum of phenotypes related to behavioral disinhibition including externalizing psychopathology and normal-range personality traits related to behavioral control, but not internalizing psychopathology. Continuing to identify the correlates and delineate the mechanisms of the genetic influences associated with disinhibition could have substantial impact in mitigating a variety of public health problems (e.g., mental health, academic achievement, criminality).


Sign in / Sign up

Export Citation Format

Share Document