Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

Abstract

Background: Environmental and occupational exposure to metals is ubiquitous worldwide, and understanding the hazardous metal components in this complex mixture is essential for environmental and occupational regulations.

Objective: To identify hazardous components from metal mixtures that are associated with alterations in cardiac autonomic responses.

Methods: Urinary concentrations of 16 types of metals were examined and 'acceleration capacity' (AC) and 'deceleration capacity' (DC), indicators of cardiac autonomic effects, were quantified from ECG recordings among 54 welders. We fitted linear mixed-effects models with least absolute shrinkage and selection operator (LASSO) to identify metal components that are associated with AC and DC. The Bayesian Information Criterion was used as the criterion for model selection procedures.

Results: Mercury and chromium were selected for DC analysis, whereas mercury, chromium and manganese were selected for AC analysis through the LASSO approach. When we fitted the linear mixed-effects models with 'selected' metal components only, the effect of mercury remained significant. Every 1 µg/L increase in urinary mercury was associated with -0.58 ms (-1.03, -0.13) changes in DC and 0.67 ms (0.25, 1.10) changes in AC.

Conclusion: Our study suggests that exposure to several metals is associated with impaired cardiac autonomic functions. Our findings should be replicated in future studies with larger sample sizes.

Keywords: cardiovascular; epidemiology; metals.

Figure 1

The relationship between λ, the penalisation factor, and model BIC, the criterion for model selection. AC, acceleration capacity; BIC, Bayesian Information Criterion; DC, deceleration capacity.