Association between urinary multiple metals and platelet-related parameters: A cross-sectional study in a metal-contaminated area of China

Previous works have shown that hematological system can be affected by exposure to lead; however, the effects of multiple metals on platelets remain elusive within the population from metal-contaminated areas. Hence, the study enrolled 609 participants, with 396 from a metal-exposed area and 213 from a control area. Platelet count (PLT), mean platelet volume (MPV), thrombocytocrit (PCT), platelet to large cell ratio (P-LCR), and platelet distribution width (PDW) were selected to evaluate platelet function. Stepwise regression and Lasso regression were utilized to identify the most influential metals. Moreover, the generalized linear model (GLM), Bayesian kernel machine regression (BKMR) models, and quantile g-computation were employed to estimate the individual or combined effects associations between 12 urinary metals and platelet indices. The results revealed all metals except vanadium, copper, strontium, and molybdenum were significantly higher in the exposed group. The GLM models indicated that urinary metals, including lead, antimony, and arsenic, exhibited associations with PLT, MPV, P-LCR, and PDW. Quantile g-computation and BKMR demonstrated negative correlations between metal mixtures and MPV as well as PDW. In conclusion, the study highlights the associations between multiple metal exposures and platelet indices, suggesting that elevated levels of the metal mixture may impede platelet activation in the population in metal-contaminated areas.