Predicting Post-Stroke Depression in Middle-Aged and Older Adults in China Using Obesity-Related Index: A Cohort Study.

OBJECTIVE: The purpose of this study was to investigate the efficacy of 13 obesity and dyslipidemia-related indicators in predicting post-stroke depression (PSD) and to determine the optimal cutoff values for these indicators in middle-aged and elderly Chinese populations. METHOD: This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011 to 2020, which included 3,912 participants aged 45 years and older. Body Mass Index (BMI), Waist Circumference (WC), Waist-to-Height Ratio (WHtR), Visceral Adiposity Index (VAI), Adiposity Body Shape Index (ABSI), Body Roundness Index (BRI), Lipid Accumulation Score (LAP), Cone Index (CI), Chinese Visceral Adiposity Index (CVAI), Triglyceride-Glucose (TyG) Index, and its related indices (TyG-BMI, TyG-WC, TyG-WHtR). Logistic regression analysis assessed the unadjusted and adjusted associations between these indicators and PSD. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated for each indicator as a predictor of PSD capability to compare predictive performance and determine optimal cutoff values. RESULTS: After adjusting for confounding factors, 12 obesity and dyslipidemia-related indices were independently associated with PSD risk in women (p < 0.05), with 11 indicators demonstrating predictive value for PSD (all AUC > 0.6). Among these, the CVAI index exhibited the highest predictive efficacy (AUC = 0.693, 95% CI: 0.602-0.757, optimal cutoff = 128.031). Among men, 12 obesity and lipid-related indices were independently associated with PSD risk (p < 0.05), but all indices demonstrated poor predictive value for PSD (AUC < 0.6). PSD risk significantly increased with higher obesity and lipid indices. CONCLUSION: Among the 12 obesity-related lipid parameters excluding ABSI, all were effective predictors of PSD risk in middle-aged and elderly Chinese women, with CVAI being the optimal predictor. These indices can serve as simple screening tools to identify PSD risk and facilitate early intervention. Effective predictors for male PSD require further exploration.