Abstract
OBJECTIVE: Dyslipidemia has been found to promote platelet activation and aggregation, contributing to the formation of atherosclerotic plaques. This study aims to explore the relationship between lipid profiles and platelet indices (PI) among middle-aged and older people without cardiovascular disease (CVD) history. METHODS: The study employed a cross-sectional design, a total of 10,060 participants from Chongming District, Shanghai, were enrolled in the study. Serum lipids (total cholesterol[CHOL], low-density lipoprotein cholesterol[LDL-C], triglycerides[TG], and high-density lipoprotein cholesterol[HDL-C]) were measured on an automatic analyzer and platelets indices (platelet count[PLT], mean platelet volume[MPV], platelet distribution width[PDW], and plateletcrit[PCT]) were measured using an automatic blood cell analyzer. Lasso regression was used to select significant covariates. Multiple linear regression models were then constructed to evaluate the impact of lipids on platelet indices, adjusting for these selected covariates. Restricted cubic spline (RCS) models were utilized to explore potential nonlinear relationships and subgroup analyses stratified by gender were conducted to enhance the robustness of the findings. RESULTS: After applying exclusion criteria, 9,396 participants aged 40 to 70 were included, with a median age of 56 years, of whom 32.5% were male. Multivariate linear regression analysis revealed that LDL-C (β = 11.266, P < 0.001) and CHOL (β = 8.012, P < 0.001) were independently and positively associated with PLT. Conversely, LDL-C showed inverse associations with MPV (β=-0.081, P < 0.001) and PDW (β=-0.237, P < 0.001). RCS analyses demonstrated nonlinear dose-response patterns between TG and PLT/MPV/PDW. HDL exhibited a significant positive correlation with MPV, specifically observed in the female subgroup. CONCLUSION: Changes in lipids significantly affect platelet indices among middle-aged and older Chinese. Especially, elevated LDL-C levels lead to a marked increase in PLT count, potentially guiding clinical lipid management decisions.