Associations of multiple metals with lung function in welders by four statistical models

Area of Science:

• Occupational Health
• Environmental Toxicology
• Pulmonary Medicine

Background:

• Heavy metal exposure is linked to reduced lung function in occupational settings.
• Previous research on metal mixtures and lung function is limited due to statistical challenges.
• This study addresses the metal exposome's impact on lung function.

Purpose of the Study:

• To assess the effects of co-exposure to metal mixtures on pulmonary function tests.
• To identify critical elements influencing lung function using advanced statistical models.
• To evaluate the utility of elastic-net regression (ENET), multivariate linear regression, Bayesian Kernel Machine Regression (BKMR), and quantile g-computation (QG-C).

Main Methods:

• 186 welders in Anhui, China, provided end-of-shift urine and lung function data.
• Urinary concentrations of 23 metals were measured using inductively coupled plasma mass spectrometry.
• Lung function parameters including forced vital capacity (FVC), forced expiratory volume in 1s (FEV1), and peak expiratory flow (PEF) were assessed.

Main Results:

• Lead and cadmium showed negative associations with FVC and FEV1.
• Nickel and chromium were inversely associated with PEF; strontium had positive effects.
• BKMR and QG-C models confirmed negative overall effects of metal mixtures on lung function, with BKMR revealing non-linear cadmium-FVC relationships.

Conclusions:

• Multi-pollutant metal mixtures are detrimental to lung function.
• Lead, cadmium, nickel, and strontium are identified as potentially crucial elements.
• Findings underscore the importance of prioritizing worker environmental health and investigating metal toxicity mechanisms.