Cognitive function and dietary index for gut microbiota in the aging population: association and machine learning screening models

BACKGROUND: Accelerated global population aging has heightened cognitive impairment as a critical public health challenge. Emerging evidence implicates gut microbiota in cognitive regulation via the gut-brain axis, with diet being a key modifiable factor. The Dietary Index for Gut Microbiota (DI-GM) quantifies diet-microbiota interactions, but its link to cognition remains unexplored. This study investigated the DI-GM-cognition relationship in older adults and evaluated its predictive value for cognitive impairment. METHODS: Data from 2168 older participants in the 2011-2014 NHANES were analyzed. The association between DI-GM and cognitive function was assessed using linear regression with smoothed curve fitting. The robustness and heterogeneity of the results were evaluated through sensitivity and subgroup analyses. A cognitive impairment screening model was developed using three machine learning algorithms (XGBoost, AdaBoost, Random Forest), and key associated features in the optimal model were identified via SHAP analysis. RESULTS: After full covariate adjustment, higher DI-GM scores significantly correlated with better cognitive function (β = 1.25, 95 % CI: 0.62-1.88, p = 0.0001) and reduced cognitive impairment probability (OR = 0.91, 95 % CI: 0.84-0.99, p = 0.023). Subgroup analyses confirmed consistency across populations, with marital status moderating effects. XGBoost achieved optimal prediction (AUC = 0.87); SHAP analysis identified age, diabetes, and DI-GM as key associated features. CONCLUSION: DI-GM positively associates with cognitive function and negatively with impairment probability, suggesting diet targeting gut microbiota may support cognitive protection. Key associated features (age, diabetes, DI-GM) highlight the importance of dietary optimization and chronic disease management for cognitive health in aging populations.