Abstract
BACKGROUND: Serum lipids are strongly associated with kidney stones. The atherogenic index of plasma (AIP) can be used to quantify lipid levels. However, the nonlinear relationship between AIP and kidney stones is unknown. Hence, our objective was to investigate the nonlinear association between AIP and kidney stones and to identify potential threshold effects and subgroup-specific associations. METHODS: We conducted a cross-sectional study involving individuals aged 18 and above from the National Health and Nutrition Examination Survey (NHANES) dataset between 2011 and 2018. Overall, 9,366 subjects were enrolled in this research. AIP was determined using log10 [triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C)]. The outcome variable was a self-reported history of kidney stones. Multifactorial logistic regression, subgroup analyses, interaction tests, restricted cubic spline (RCS) modeling, and threshold effect evaluations were used to investigate the connection between AIP and kidney stones. RESULTS: Data from 9,366 participants were analyzed, and 936 (9.99%) subjects with kidney stones were identified. After adjusting for all covariates, logistic regression analysis demonstrated a meaningful positive association between AIP and the renal calculi, with a 1.33-fold rise in the prevalence of renal calculi for every 1-unit raise in AIP in participants [odds ratio (OR) 1.33, 95% confidence interval (CI): 1.06, 1.68]. RCS analysis showed an inverted V-shaped nonlinear association between AIP and kidney stones. Among participants with AIP <0, a notable correlation was observed between elevated AIP levels and a heightened risk of renal calculi. CONCLUSIONS: AIP correlates with kidney stones in an inverted V-shape, suggesting the potential of AIP in predicting kidney stones. However, this relationship is limited, and further studies are needed to validate it.