Body Roundness Index Predicts Incident Cardio-metabolic-depression Multimorbidity: A Dose-response Analysis of 19,802 Adults in CHARLS and ELSA Cohorts.

Abstract

Objective: To examine the association between body roundness index (BRI) and cardio-metabolic-depression multimorbidity.

Methods: This study used data of two prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS) and English Longitudinal Study of Ageing (ELSA). Firstly, the relationship between baseline BRI and the incidence of cardio-metabolic-depression multimorbidity was analyzed using Cox regression models. Subsequently, stratified Cox models with interaction terms were conducted among different groups. To investigate the potential nonlinear relationships, restricted cubic spline (RCS) regression of hazard ratio (HR) was employed. Furthermore, longitudinal associations between BRI and cardio-metabolic-depression multimorbidity over time were estimated by using generalized estimating equations (GEE) model.

Results: A total of 12,840 participants from CHARLS (female: 52.7%, mean age: 58.39 y), 6962 from ELSA (female: 55.0%, mean age: 65.94 y) were included according to inclusion and exclusion criteria. Cox models revealed consistent and significant association between BRI (continuous and quartiles) and cardio-metabolic-depression multimorbidity risk. Fully adjusted HRs showed a progressive increase compared to Q1, indicating a strong graded association (P for trend <0.001). Stratified analyses showed no significant interactions by demographic and lifestyle factors. In both cohorts, RCS analyses revealed particularly steep risk gradients beyond BRI values of 4. GEE analyses confirmed significant longitudinal associations with cardio-metabolic-depression multimorbidity risk. Sensitivity analyses including landmark, outlier exclusion, and multiple imputation approach consistently supported these findings.

Conclusions: Higher BRI consistently predicts cardio-metabolic-depression multimorbidity across populations in a dose-dependent patterns. These findings highlight BRI's potential for early risk stratification and integrated care approaches that target metabolic-mental health interactions.