Abstract
BACKGROUND: Body fat distribution and metabolic health may be associated with the occurrence of kidney stones (KS), although the exact nature of this relationship remains uncertain. Our study aimed to investigate the connection between six anthropometric indexes and KS in adults. METHODS: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) cycles 2007-2018. Anthropometric and health data were collected from a large representative sample of U.S. adults. The anthropometric indexes examined included a body shape index (ABSI), lipid accumulation products (LAPs), triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C), triglyceride and glucose index (TyG), visceral adiposity index (VAI), and waist triglyceride index (WTI). The association between these indexes and the prevalence of KS was investigated by using multivariate adjusted logistic regression and restricted cubic spline (RCS) regression for dose-response curves. Additionally, algorithm for metrics to identify individuals with KS was established by XGBoost models, and evaluated through receiver operating characteristic (ROC) curves. RESULTS: A total of 14,132 adults were included in our study, among whom 1,353 (9.6%) were diagnosed with KS. After adjusting for multiple variables, the fourth quartile of ABSI [odds ratio (OR) =1.460; 95% confidence interval (CI): 1.106-1.925], LAP (OR =1.880; 95% CI: 1.487-2.377), TG/HDL-C (OR =1.334; 95% CI: 1.058-1.682), TyG (OR =1.303; 95% CI: 1.018-1.688), VAI (OR =1.516; 95% CI: 1.206-1.906), and WTI (OR =1.559; 95% CI: 1.236-1.967) were positively linked with the prevalence of KS. LAP and VAI were positively and non-linearly related to the prevalence of KS, with inflection points of 50.45 and 1.62, respectively. The XGBoost model identified LAP as the strongest predictor of KS among adults. Stratified analyses indicated no significant interactions between LAP and the prevalence of KS. CONCLUSIONS: This study demonstrated that the positive association between body fat distribution, metabolic health, and the prevalence of KS among U.S. adults. Moreover, LAP acts as a reliable predictor for identifying individuals with KS.