Occupational Asthma Reference

Wu L, Cui F, Ma J, Huang Z, Zhang S, Xiao Z, Li J, Ding X, Niu P, Associations of multiple metals with lung function in welders by four statistical models, Chemosphere, 2022;298:13402,https://doi.org/10.1016/j.chemosphere.2022.134202

Keywords: China, metal, welder, pft, cadmium, nickel, chrome, strontium,

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Abstract

Background
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.

Objectives
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.

Methods
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.

Results
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.

Conclusion
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.
Keywords: Multiple metals; Welders; Lung function; Bayesian kernel machine regression; Quantile g-computation

Plain text: Background 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. Objectives 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. Methods 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. Results 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. Conclusion 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. Keywords: Multiple metals; Welders; Lung function; Bayesian kernel machine regression; Quantile g-computation

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7/4/2022

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