Associations between serum trace elements and biological age acceleration in the Chinese elderly: A community-based study investigating the mediating role of inflammatory markers and the moderating effect of physical activity

Growing evidence suggests that environmental factors play a significant role in the aging process. We established the Klemera and Doubal Method biological age acceleration (KDM-BAA) by using the KDM as a biological age predictor to assess the trace elements (ELEs) role. Generalized Linear Model (GLM) was used to assess the associations between single ELE (trace element) and KDM-BAA. Restricted cubic splines (RCS) were used to assess the nonlinear relationship between elemental levels and KDM-BAA. Quantile G-Computation (QGC) regression was employed to explore the direction and weight. Weighted Quantile Sum (WQS) Regression was used to study the weights of different groups of ELEs. Bayesian Kernel Machine Regression (BKMR) was utilized to analyze the overall effect of mixed elemental exposure. Mediation analysis was conducted to investigate the role of intermediate biomarkers and the moderating effects of physical activity (PA) was used on the pathway. The results showed serum Copper (Cu) levels positively correlated with KDM-BAA, while Zinc (Zn) and Iron (Fe) negatively correlated with it, respectively. The mixture of Zn, Cobalt (Co), Selenium (Se), and Fe exhibited a significant overall negative effect. Additionally, PA could ease the association between Cu and KDM-BAA through impacting the inflammation level. This study provides novel insights into how inflammation mediates the association between ELEs exposure and KDM-BAA, while PA acts as a potential protective factor.