Relationship between cumulative exposure to metal mixtures and heart rate among Chinese preschoolers. (August 2022) - Fu, Ye; Liu, Yun; Liu, Yanli; Wang, Yan; Zhu, Meiqin; Lin, Wei; Li, Mingzhu; Liu, Yang; He, Minghui; Yu, Lili; Wang, Jing
Abstract: The cumulative exposure to metals affects cardiac conduction, and the effect of polymetallic exposure on heart rate in children is unknown. To evaluate the relationship between cumulative exposure to metal mixtures and heart rate among Chinese preschoolers, the determination of urinary 24 metals was processed by high-resolution inductively coupled plasma-mass spectrometry. Heart rate was recorded when measuring blood pressure after resting 5 min or longer. As a method to compute the Environmental risk score (ERS) according to heart rate under heavy metal mixtures, adaptive elastic net (AENET) with 299 predictors which were formed by the combination of main eﬀects, squared terms, and pairwise interactions of heavy metals with a total number of 23, 23, 253 respectively. To further assess the associations between ERS and heart rate, regression analyses were performed with complex survey designs. The construction of ERS under heart rate-related metal mixtures was returned by AENET in according to 11 main eﬀects (tin, arsenic, zinc, iron, titanium, vanadium, nickel, manganese, cobalt, copper and chromium) and 2 squared terms (tungsten and rubidium). A high correlation was monitored between the alteration of ERS in the study population and heart rate ( β = 1.030, 95% CI : 0.730 - 1.330 in 1239; β = 1.085, 95% CI : 0.777 - 1.393 in 1061). Significant associations of ERS with higher heart rates were also pointed out ( P s < 0.05). Our study elucidates the association of the cumulative exposure of heavy metals as mixtures and heart rate among Chinese preschoolers. Further research is obliged to corroborate these findings in longitudinal studies. Graphical abstract: Image 1 Highlights: Urinary markers of 24 metals had been examined among 1239 preschoolers in China. AENET is a method proposed to analyse high dimensional data when dealing with collinearity problems. ERS was used to appraise cumulative exposure to metal mixtures, higher ERS related to increased risk of higher heart rate.