Associations of personal PM2.5-bound heavy metals and heavy metal mixture with lung function: Results from a panel study in Chinese urban residents

被引：0

作者：

Zhang, Jiake ^{[1
]}

Hu, Yuxiang ^{[1
]}

Wang, Xing ^{[1
]}

Ding, Xuejie ^{[1
]}

Wang, Bin ^{[1
]}

Yang, Shijie ^{[1
]}

Ye, Zi ^{[1
]}

Qiu, Weihong ^{[1
]}

Chen, Weihong ^{[1
]}

Zhou, Min ^{[1
]}

Zhang, Jiake ^{[2
]}

Hu, Yuxiang ^{[2
]}

Wang, Xing ^{[2
]}

Ding, Xuejie ^{[2
]}

Wang, Bin ^{[2
]}

Yang, Shijie ^{[2
]}

Ye, Zi ^{[2
]}

Qiu, Weihong ^{[2
]}

Chen, Weihong ^{[2
]}

Zhou, Min ^{[2
]}

Cen, Xingzu ^{[3
]}

机构：

[1] Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hubei, Wuhan,430030, China

[2] Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Techn

[3] The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, Hangzhou,310003, China

来源：

Chemosphere | 2024年 / 364卷

基金：

中国国家自然科学基金;

关键词：

Bioremediation - Brain - Cash registers - Gas bearings - Health risks - Lung cancer - Manganese - Public risks - Respirators - Risk perception - Selective catalytic reduction - Statistical process control;

D O I：

10.1016/j.chemosphere.2024.143084

中图分类号：

学科分类号：

摘要：

Background: There are a few reports on the associations between fine particulate matter (PM2.5)-bound heavy metals and lung function. Objectives: To evaluate the associations of single and mixed PM2.5-bound heavy metals with lung function. Methods: This study included 316 observations of 224 Chinese adults from the Wuhan-Zhuhai cohort over two study periods, and measured participants' personal PM2.5-bound heavy metals and lung function. Three linear mixed models, including the single constituent model, the PM2.5-adjusted constituent model, and the constituent residual model were used to evaluate the association between single metal and lung function. Mixed exposure models including Bayesian kernel machine regression (BKMR) model, weighted quantile sum (WQS) model, and Explainable Machine Learning model were used to assess the relationship between PM2.5-bound heavy metal mixtures and lung function. Results: In the single exposure analyses, significant negative associations of PM2.5-bound lead, antimony, and cadmium with peak expiratory flow (PEF) were observed. In the mixed exposure analyses, significant decreases in forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC), maximal mid-expiratory flow (MMF), and forced expiratory flow at 75% of the pulmonary volume (FEF75) were associated with the increased PM2.5-bound heavy metal mixture. The BKMR models suggested negative associations of PM2.5-bound lead and antimony with lung function. In addition, PM2.5-bound copper was positively associated with FEV1/FVC, MMF, and FEF75. The Explainable Machine Learning models suggested that FEV1/FVC, MMF, and FEF75 decreased with the elevated PM2.5-bound lead, manganese, and vanadium, and increased with the elevated PM2.5-bound copper. Conclusions: The negative relationships were detected between PM2.5-bound heavy metal mixture and FEV1/FVC, MMF, as well as FEF75. Among the PM2.5-bound heavy metal mixture, PM2.5-bound lead, antimony, manganese, and vanadium were negatively associated with FEV1/FVC, MMF, and FEF75, while PM2.5-bound copper was positively associated with FEV1/FVC, MMF, and FEF75. © 2024 Elsevier Ltd

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