biostudies-literatureUnknown13(8)Zhou ZOxidative stress plays a central role in the development of peripheral artery disease (PAD), yet composite indices quantifying its impact remain underutilized. The oxidative balance score (OBS), integrating dietary and lifestyle exposures, may offer a comprehensive approach to vascular risk stratification. We analyzed data from 7249 U.S. adults in NHANES 1999-2004 to examine the association between OBS and PAD, defined by an ankle-brachial index ≤ 0.9. Multivariable logistic regression and restricted cubic spline models were used to assess both linear and nonlinear associations. Twelve machine learning models were constructed to predict PAD status; the top-performing model (GLMNet) was interpreted using SHapley Additive exPlanations (SHAP) to identify key predictors. Higher OBS levels wereFood science & nutritione70798https://www.ebi.ac.uk/biostudies/studies/S-EPMC12358680biostudies-literatureEvaluating the Oxidative Balance Score for Peripheral Artery Disease Risk: Integrating Epidemiologic Modeling and SHAP-Interpretable Machine Learning in NHANES.PMC12358680Jiang YQian JLee HZhu XLi KZhou ZfalseEvaluating the Oxidative Balance Score for Peripheral Artery Disease Risk: Integrating Epidemiologic Modeling and SHAP-Interpretable Machine Learning in NHANES.Oxidative stress plays a central role in the development of peripheral artery disease (PAD), yet composite indices quantifying its impact remain underutilized. The oxidative balance score (OBS), integrating dietary and lifestyle exposures, may offer a comprehensive approach to vascular risk stratification. We analyzed data from 7249 U.S. adults in NHANES 1999-2004 to examine the association between OBS and PAD, defined by an ankle-brachial index ≤ 0.9. Multivariable logistic regression and restricted cubic spline models were used to assess both linear and nonlinear associations. Twelve machine learning models were constructed to predict PAD status; the top-performing model (GLMNet) was interpreted using SHapley Additive exPlanations (SHAP) to identify key predictors. Higher OBS levels were2025-01-01T00:00:00Z2025 Aug2026-05-02T03:50:14.961Z2026-04-07T17:36:18.075ZS-EPMC123586804083194210.1002/fsn3.70798