Metabolic Obesity Phenotypes and Their Transitions as Determinants of Multimorbidity Trajectories: Evidence from Global Aging Cohorts

Objective : The high prevalence of multimorbidity poses significant challenges to the health burden of the elderly population and healthcare systems, understanding its trajectories is critical for intervention strategies. Metabolic obesity phenotypes are considered key predictors of multimorbidity. This study aimed to analyze the associations between metabolic obesity phenotypes and their transitions with multimorbidity trajectories. Methods : Longitudinal data from three cohort studies (CHARLS, ELSA, and HRS) were used, and trajectories of multimorbidity were identified through trajectory analysis. Baseline metabolic obesity phenotypes were classified into Metabolically Healthy Normal Weight (MHNW), Metabolically Healthy Obesity/Overweight (MHOO), Metabolically Unhealthy Normal Weight (MUNW), and Metabolically Unhealthy Obesity/Overweight (MUOO). The Group-Based Trajectory Modeling method was used to construct multimorbidity trajectories, perform logistic regression analysis on trajectory groups. Findings : In baseline analysis, compared with the MH (both MHNW and MHOO) group, the likelihood of MU group individuals in the low-risk trajectory significantly decreased, and the risk in the high-risk trajectory significantly increased, especially in CHARLS (OR=4.03), ELSA (OR=4.73), HRS (OR=3.01). The analysis of changes in metabolic obesity phenotypes showed that individuals with stable metabolic unhealth had the lowest risk in the low-risk trajectory, and the risk of developing high-risk trajectories significantly increased for phenotypes that had been exposed to metabolic unhealth. In particular, in CHARLS, ELSA, and HRS, individuals continuously exposed to metabolic unhealth significantly increased the risk of developing high-risk trajectories. Interpretations : Metabolic obesity phenotypes and their changes have significant impacts on multimorbidity trajectories, especially the strong association between metabolic unhealthy status and high-risk multimorbidity trajectories. Fundings: This study was funded by GDPH Supporting Fund for Talent Program (KY0120220263), LiaoNing Revitalization Talents Program (XLYC2203192), and Guangzhou School (hospital) Enterprise Joint Funding Project (2025A03J3901).