Evaluation of Body Roundness Index as a Novel Anthropometric Biomarker for Cognitive Impairment: Evidence From the CHARLS Cohort

Background Obesity is a major clinical and public health concern and a recognized contributor to cognitive impairment. Conventional anthropometric measures such as body mass index (BMI) provide limited information on fat distribution, which constrains their utility in risk stratification. The body roundness index (BRI), a novel anthropometric indicator, captures central adiposity more effectively and may serve as a clinically actionable biomarker. However, its utility as a biomarker in analytical models of cognitive impairment remains insufficiently explored. Methods We conducted a cross‐sectional analysis of 33,286 adults aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS), using only participants with contemporaneous BRI and cognitive assessment data. Cognitive function was assessed using a standardized cognitive test battery. Multivariable logistic regression quantified the BRI–cognitive impairment association, with subgroup analyses for robustness. Model discrimination was examined by the area under the receiver operating characteristic (ROC) curve (AUC). Reclassification ability was measured through integrated discrimination improvement (IDI) and net reclassification improvement (NRI). The decision curve analysis (DCA) was applied to determine the clinical decision utility. Results BRI showed significant associations with demographic factors, metabolic comorbidities, and cognitive impairment. After comprehensive adjustment, higher BRI remained independently associated with increased odds of cognitive impairment within the same survey wave (OR = 1.10, 95% CI: 1.06–1.15, p < 0.001). This relationship was stable across multiple subgroups. Incorporation of BRI into multivariable logistic regression models resulted in superior discrimination (AUC = 0.807, 95% CI: 0.801–0.813, p < 0.001), with improved sensitivity (79.70%) and specificity (69.14%) compared with models without BRI. Reclassification metrics showed mixed results, with improved specificity but reduced sensitivity for cognitive impairment. DCA highlighted the need for careful threshold selection when incorporating BRI into risk assessment models. Conclusions Within an analytical modeling framework, BRI emerges as an independent and clinically interpretable anthropometric biomarker that is significantly associated with cognitive impairment and exhibits enhanced discriminatory ability in this cross‐sectional setting. These findings support the use of simple, routinely available measures to serve as a cost‐effective screening filter for low‐risk populations in community‐based assessments, though clinical utility requires further validation.