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Research Progress

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Postdoctoral fellow Hang Yu et al. published a paper titled "Associations of multiple hydroxy-polycyclic aromatic hydrocarbons with serum levels of lipids in the workers from coking and non-ferrous smelting industries"in JHM

Release date:2024-05-27    Author:     Source:     Click:

《Associations of multiple hydroxy-polycyclic aromatic hydrocarbons with serum levels of lipids in the workers from coking and non-ferrous smelting industries 》

Website:https://doi.org/10.1016/j.jhazmat.2024.134664

Graphical Abstract

Abstract:

Epidemiological evidence indicates that exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with certain metabolic diseases. However, the relationship between PAHs and serum lipid profiles in exposed subjects remain unknown. Herein, the associations of multiple (8) urinary hydroxylated PAHs (OH-PAHs) in workers of coking (n = 655) and non-ferrous smelting (n = 614) industries with serum lipid levels (marking lipid metabolism) were examined. Multivariable linear regression, Bayesian kernel machine regression, and quantile g-computation were used. Most urinary OH-PAHs were significantly higher (p < 0.001) in coking workers than in non-ferrous smelting workers. In workers of both industries, OH-PAH exposure was associated with elevated levels of serum total cholesterol, total triglyceride, and low-density lipoprotein, as well as reduced high-density lipoprotein levels. Specifically, urinary 4-hydroxyphenanthrene was significantly positively associated with serum total cholesterol, total triglyceride, and low-density lipoprotein levels in non-ferrous smelting workers; however, the completely opposite association of 4-hydroxyphenanthrene with these lipid levels was observed in coking workers. The results of this pioneering examination suggest that exposure to OH-PAHs may contribute to dyslipidemia in coking and non-ferrous smelting workers, and distinct patterns of change were observed. Further prospective studies involving larger sample sizes are needed to further validate the findings.