Nonlinear association of a body shape index and hyperlipidemia: an American population-based cross-sectional study

This study aimed to evaluate the association between A Body Shape Index (ABSI) and hyperlipidemia, and assess nonlinear relationships via restricted cubic spline (RCS) analysis.

Data from 21,013 adults in the National Health and Nutrition Examination Survey (NHANES, 2005-2020) were analyzed. Hyperlipidemia was defined using National Cholesterol Education Program (NCEP) criteria. ABSI was calculated as waist circumference/(BMI^(2/3) × H^(1/2)) and stratified into quartiles (Q1-Q4). Multivariable logistic regression models, adjusted for demographic characteristics, health behaviors, and clinical features, assessed the association between ABSI and hyperlipidemia. RCS and subgroup analyses explored nonlinearity and interactions, with sensitivity analyses excluding lipid-lowering medication users and participants who died within two years.

Higher ABSI was significantly associated with increased hyperlipidemia risk across all models. In the fully adjusted model, each unit increase in ABSI corresponded to a 24% increased risk (OR = 1.24, 95% CI: 1.17-1.31). Quartile-based analysis revealed progressive risk increases, with the highest quartile demonstrating 68% higher odds compared to the lowest (OR = 1.68, 95% CI: 1.46-1.94 P for trend < 0.001). RCS analysis revealed a significant nonlinear inverse U-shaped relationship (P for nonlinearity < 0.001) with a threshold at 0.084. Participants with ABSI > 0.084 had 28% higher hyperlipidemia risk compared to those with ABSI ≤ 0.084 (OR = 1.28, 95% CI: 1.13-1.44). Subgroup analyses identified significant interactions with age (p < 0.001), marital status (p = 0.028), hypertension (p = 0.005), and diabetes (p = 0.001). Sensitivity analyses excluding participants using lipid-lowering medications and those who died within two years confirmed the robustness of these associations.Higher ABSI was significantly associated with increased hyperlipidemia risk across models. In the fully adjusted model, each ABSI unit increase correlated with a 24% higher risk (OR=1.24, 95% CI:1.17-1.31). Quartile analysis showed gradually elevated risk, with Q4 (highest) having 68% higher odds than Q1 (lowest; OR=1.68, 95% CI:1.46-1.94, P-trend<0.001). RCS revealed a significant nonlinear inverse U-shaped relationship (P for nonlinearity<0.001) with a threshold of 0.084; participants with ABSI>0.084 had a 28% higher risk (OR=1.28, 95% CI:1.13-1.44) versus ABSI≤0.084. Subgroup analyses identified significant interactions with age (P<0.001), marital status (P=0.028), hypertension (P=0.005), and diabetes (P=0.001). Sensitivity analyses confirmed result robustness.

This study provides the first comprehensive evidence of a significant association between ABSI and hyperlipidemia. The identified threshold effect suggests that ABSI may serve as a valuable anthropometric tool for hyperlipidemia risk stratification. Future studies should validate causality and explore mechanisms underlying the observed nonlinear dynamics.This study provides the first comprehensive evidence of a significant ABSI-hyperlipidemia association. The threshold effect suggests ABSI may serve as a valuable anthropometric tool for hyperlipidemia risk stratification. Future studies should validate causality and explore mechanisms underlying the observed nonlinear dynamics.