Zinc and copper status, biological aging, and mild cognitive impairment: cross-sectional mediation analysis in a high-risk occupational population

Occupational exposures and long-term work-related stressors may accelerate biological aging and contribute to cognitive impairment among high-risk working populations. Zinc (Zn) and copper (Cu) are essential trace elements involved in neurophysiological regulation and may affect cognitive function during aging. However, it remains unclear whether biological age (BA) serves as a potential intermediary factor in the association between Zn and Cu status and mild cognitive impairment (MCI) among occupational populations. This study measured whole blood Zn and Cu levels among coal miners from a large-scale mining facility in northern Shanxi Province, China. Multivariable logistic regression was employed to examine the relationship of Zn and Cu concentrations with MCI. Potential dose-response patterns and non-linear trends were further evaluated using restricted cubic spline (RCS) functions. Constructed the BA to reflect the physiological status of coal miners by integrating multiple biochemical and functional indicators. In addition, mediation analyses were performed to quantify the indirect association of BA within these relationships. Participants with moderate whole blood Zn levels exhibited a reduced likelihood of MCI (OR = 0.51, 95% CI: 0.31–0.86), whereas the association attenuated at higher concentrations. RCS analysis suggested a U-shaped pattern, with the lowest MCI risk observed at intermediate Zn levels. BA statistically explained 28.53% of the association between Zn and MCI in cross-sectional mediation analysis. Whole blood Cu levels did not show a significant relationship with the risk of MCI. These findings suggest a non-linear association between Zn status and cognitive health in occupational populations, with potential involvement of aging-related processes reflected by BA. Incorporating aging-related indicators into occupational health assessment may help identify workers at elevated risk of cognitive impairment.