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The study also compares eGDR with other insulin resistance (IR) indices, including the triglyceride\u2010glucose index (TyG), triglyceride\u2010to\u2010high\u2010density lipoprotein cholesterol ratio (TG\/HDL\u2010C), and metabolic score for insulin resistance (METS\u2010IR).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data were obtained from the National Health and Nutrition Examination Survey (NHANES) for participants aged \u2265\u200960\u2009years. Cognitive function was assessed using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). Participants were stratified by eGDR quartiles, and multivariable regression models were applied to evaluate the relationship between eGDR and cognitive impairment. Further analyses included interaction tests, restricted cubic splines (RCS), and machine learning models (LASSO, XGBoost, Random Forest), with performance assessed through ROC curves, decision curve analysis (DCA), and SHAP values.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Higher eGDR levels were significantly associated with improved cognitive scores and a reduced risk of cognitive impairment. For each 1\u2010unit increase in eGDR, cognitive scores improved by 0.095 points, and the odds of cognitive impairment decreased by 7.5%. Quartile analysis revealed the highest eGDR quartile to be associated with better cognitive function when compared with the lowest quartile. Additionally, the eGDR is potentially more predictive of cognitive dysfunction than other infrared indices. The machine learning model confirms the potential clinical utility of the eGDR in predicting cognitive dysfunction.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>eGDR may be a reliable and effective predictor of cognitive function and cognitive impairment risk in older adults. The study suggests that higher eGDR levels may serve as a protective factor against cognitive decline, highlighting the potential\u00a0importance of managing eGDR for cognitive health, particularly in at\u2010risk populations. Further research, including longitudinal studies and interventions targeting eGDR components, is needed to confirm these findings and explore potential therapeutic strategies.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cns.70524","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T06:49:58Z","timestamp":1752562198000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Assessing the Impact of Estimated Glucose Disposal Rate (<scp>eGDR<\/scp>) on Cognitive Function in Older Adults: A <scp>NHANES<\/scp>\u2010Based Machine Learning Study"],"prefix":"10.1111","volume":"31","author":[{"given":"Tianyi","family":"Wang","sequence":"first","affiliation":[{"name":"Heilongjiang University of Chinese Medicine  Harbin Heilongjiang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haochen","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Traditional 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