Wu Luli, Cui Fengtao, Ma Junxiang, Huang Zhengjie, Zhang Shixuan, Xiao Zhongxin, Li Jie, Ding Xinping, Niu Piye
School of Public Health and the Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China.
Occupational Disease Prevention and Control Hospital of Huaibei Mining Co., Ltd, Huaibei, Anhui Province, 235000, China.
Chemosphere. 2022 Jul;298:134202. doi: 10.1016/j.chemosphere.2022.134202. Epub 2022 Mar 4.
Exposure to heavy metals has been related to decreased lung function in workers. However, due to limitations in statistical methods for mixtures, previous studies mainly focused on single or several toxic metals, with few studies involving metal exposome and lung function.
The study aimed to evaluate the effects of co-exposure to the metal mixtures on multiple parameters of pulmonary function tests and to identify the elements that play an essential role in elastic-net regression (ENET), multivariate linear regression, bayesian kernel machine regression (BKMR), and quantile g-computation (QG-C) models.
We have recruited 186 welders from Anhui (China) in 2019. And their end-of-shift urine and lung function measure data were collected with informed consent. The urinary concentrations of 23 metals were measured by inductively coupled urinary mass spectrometry. The lung function measures including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) were also detected as outcome indicators. Four statistical methods, ENET, multivariate linear regression, BKMR, and QG-C models were used to evaluate the associations of element mixtures on lung function comprehensively.
Lead and cadmium were negatively associated with FVC and FEV1, nickel and chromium were inversely associated with PEF, and strontium showed significant positive effects in linear regression models, which were consistent with the results in BKMR and QG-C models. Both BKMR and QG-C models showed a significantly negative overall effect of metal mixtures on lung function parameters (FVC, FEV1, and PEF). Meanwhile, BKMR showed the non-linear relationships of cadmium with FVC.
Multi-pollutant mixtures of metals were negatively associated with lung function. Lead, cadmium, nickel, and strontium might be crucial elements. Our findings highlight a need to prioritize workers' environmental health, and guide future research into the toxic mechanisms of metal-mediated lung function injury.
接触重金属与工人肺功能下降有关。然而,由于混合物统计方法的局限性,以往研究主要集中在单一或几种有毒金属上,涉及金属暴露组与肺功能的研究较少。
本研究旨在评估金属混合物共同暴露对肺功能测试多个参数的影响,并确定在弹性网回归(ENET)、多元线性回归、贝叶斯核机器回归(BKMR)和分位数g计算(QG-C)模型中起关键作用的元素。
2019年,我们从中国安徽招募了186名焊工。在获得知情同意后,收集了他们的下班时尿液和肺功能测量数据。采用电感耦合尿质谱法测定23种金属的尿浓度。肺功能指标包括用力肺活量(FVC)、1秒用力呼气量(FEV1)和呼气峰值流速(PEF)。采用ENET、多元线性回归、BKMR和QG-C模型4种统计方法综合评估元素混合物与肺功能的关系。
铅和镉与FVC和FEV1呈负相关,镍和铬与PEF呈负相关,锶在线性回归模型中显示出显著的正效应,这与BKMR和QG-C模型的结果一致。BKMR和QG-C模型均显示金属混合物对肺功能参数(FVC、FEV1和PEF)有显著的负向总体影响。同时,BKMR显示镉与FVC之间存在非线性关系。
多种金属污染物混合物与肺功能呈负相关。铅、镉、镍和锶可能是关键元素。我们的研究结果强调需要优先考虑工人的环境卫生,并指导未来对金属介导的肺功能损伤毒性机制的研究。