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The adverse health effects of pyrethroids exposure have attracted wide concern. We aimed to assess the associations of bifenthrin, a widely used pyrethroid, with glucose homeostasis and risk of type 2 diabetes mellitus (T2DM) and to explore the underlying mechanism. Serum bifenthrin, fasting plasma glucose (FPG), fasting plasma insulin (FPI), and plasma protein carbonyl (PCO) were determined among 3822 participants from the Wuhan-Zhuhai cohort. Glucose homeostasis was evaluated by FPG, FPI, homeostasis model assessment of insulin resistance (HOMA-IR), impaired fasting glucose (IFG), and abnormal glucose regulation (AGR). The associations of serum bifenthrin with glucose homeostasis and risk of T2DM were assessed by generalized linear models and logistic regression models. The role of PCO in the above associations was evaluated by mediation analyses. After adjusting for covariates, each 2-fold increase in serum bifenthrin was associated with a 0.21 mmol/L increase in FPG and a 5.19%, 10.49%, and 12.18% increase in FPI, HOMA-IR, and PCO levels, respectively. Monotonically elevated ORs of IFG and AGR (all P and P for trend0.05), but not T2DM (P 0.05) were detected to be associated with increased bifenthrin. Compared with the participants with low bifenthrin and low PCO, participants with high bifenthrin exposure and high PCO showed a 0.40 mmol/L, 11.07%, and 22.50% increase in FPG, FPI, and HOMA-IR, as well as a 119.97% and 48.88% increase in risks of IFG and AGR, respectively (P for trend0.05). Moreover, PCO mediated 13.61%-24.98% of the serum bifenthrin-associated glucose dyshomeostasis. The study suggested that bifenthrin exposure was dose-dependently associated with glucose dyshomeostasis in the general Chinese urban adults, and these associations were exacerbated and partly mediated by PCO. Given that other pollutants were not included in this study, the effect of co-exposure of pyrethroids with multiple pollutants is necessary to be considered in future studies.

The adverse effects of polycyclic aromatic hydrocarbon (PAHs), a group of common environmental pollutants, on mental health are unclear. This study is developed to evaluate the potential association of urinary PAH metabolites with depression in US adults.Measurement of 8 urinary PAH metabolites and assessment of depression were available for 9625 adults in the National Health and Nutritional Examination Survey 2005-2016. Multiple logistic regression models and weighted quantile sum (WQS) regression models were applied to evaluate the association between urinary PAH metabolites and depression.Among 9625 individuals with a weighted geometric mean age of 42.63 years, 801 participants suffered from depression. Significant positive dose-response relationships were observed between specific urinary PAH metabolites and the risk of depression after adjusting for potential confounders. Urinary 1-hydroxynaphthalene was positively and dose-dependently associated with the risk of depression among total participants (odds ratio: 1.188; 95% confidence interval: 1.096-1.288). In addition, each 1-unit increase of ln-transformed urinary 1-hydroxynaphthalene, 2-hydroxynaphthalene, 3-hydroxyfluorene, 2-hydroxyfluorene, 1-hydroxyphenanthrene, 23-hydroxyphenanthrene, 1-hydroxypyrene, and total PAH metabolites was associated with a 23.3%, 32.6%, 23.3%, 29.4%, 30.8%, 22.8%, 29.4%, and 31.7% increment in the risk of depression in smokers, respectively (all P and PExposure to PAHs may elevate the risk of depression among US adults. More studies are warranted to investigate the underlying mechanism by which PAHs induce the development of depression.

Polychlorinated biphenyls (PCBs) exposure has been related to the abnormal glucose metabolism and the risk of diabetes. However, the joint effects of various PCBs are uncertain and the potential mechanisms remain unclear. Our objectives were to evaluate the associations of serum PCBs with fasting plasma glucose (FPG) and the risk of diabetes among a general Chinese population, and to estimate the mediating effects of oxidative stress in the above associations. Serum levels of seven indicator-PCBs (PCB-28, 52, 101, 118, 138, 153, and 180) and FPG values were determined among 4498 subjects from the Wuhan-Zhuhai cohort. Oxidative DNA damage biomarker (urinary 8-hydroxy-2'-deoxyguanosine, 8-OHdG) and lipid peroxidation biomarker (urinary 8-isoprostane, 8-iso-PGF

Coal workers’ pneumoconiosis (CWP) is one of the most serious occupational diseases caused by long-term inhalation of coal dust (including dust from coal mining or pure coal dust) in the workplace [1]. Although prevention efforts have been taken for many decades, CWP is still a public health issue around the world [2]. Especially in developing countries where coal is the main energy source, millions of workers are exposed to coal dust during their professional activities. Published literatures reported that more than 20 million workers are exposed to coal dust in the workplace in China and India alone [3, 4]. In addition, several international or national plans and programs were conducted to control industrial coal dust and prevent CWP since 1990. However, the global incidence and disease burden of CWP and their temporal trends over time are limited. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: Dr. Wang has nothing to disclose. Conflict of interest: Dr. Liang has nothing to disclose. Conflict of interest: Dr. Yang has nothing to disclose. Conflict of interest: Dr. Ma has nothing to disclose. Conflict of interest: Dr. Li has nothing to disclose. Conflict of interest: Dr. Mu has nothing to disclose. Conflict of interest: Dr. Xiao has nothing to disclose. Conflict of interest: Dr. Feng has nothing to disclose. Conflict of interest: Dr. Dong has nothing to disclose. Conflict of interest: Dr. Yu has nothing to disclose. Conflict of interest: Dr. Liu has nothing to disclose. Conflict of interest: Dr. Tan has nothing to disclose. Conflict of interest: Dr. Zhou has nothing to disclose. Conflict of interest: Dr. Wang has nothing to disclose. Conflict of interest: Dr. Shi has nothing to disclose. Conflict of interest: Dr. Yuan has nothing to disclose. Conflict of interest: Dr. Chen has nothing to disclose.