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Association between the Chinese Visceral Adiposity Index and Multimorbidity in Middle-Aged and Older Chinese Adults: A Prospective Cohort Study

Year: 2026

Type: article

Abstract: Background: The association between visceral adiposity and multimorbidity in Chinese middle-aged and older adults remains underexplored. This study used data from the China Health and Retirement Longitudinal Study (CHARLS) to examine the relationship between visceral adiposity, measured by the Chinese visceral adiposity index (CVAI), and multimorbidity. Methods: This prospective cohort study analyzed data from 6,410 participants who were multimorbidity-free in the 2015 CHARLS wave, with follow-up assessments in 2018 and 2020. CVAI was calculated using age, body mass index, waist circumference, triglycerides, and high-density lipoprotein cholesterol. Latent class analysis (LCA) identified multimorbidity patterns, defined as the presence of ≥2 chronic conditions based on self-reported physician diagnoses. Cox regression and restricted cubic spline (RCS) analyses assessed the impact of CVAI on multimorbidity risk. Results: Over a median 5.0-year follow-up (interquartile range [IQR], 3.0 to 5.0), 2,809 participants (43.8%) developed multimorbidity. Each IQR increase in CVAI significantly elevated the risk of multimorbidity (hazard ratio [HR], 1.20; 95% confidence interval [CI], 1.16 to 1.24). Higher risks were observed in the second (HR, 1.16; 95% CI, 1.04 to 1.30), third (HR, 1.28; 95% CI, 1.14 to 1.43), and fourth (HR, 1.76; 95% CI, 1.58 to 1.96) quartiles compared with the first. The RCS analysis demonstrated a dose-response relationship (Pnonlinearity=0.109). LCA identified four multimorbidity clusters. CVAI increments were significantly associated with the cardio- metabolic cluster (HR, 1.51; 95% CI, 1.42 to 1.62) and the arthritis-renal cluster (HR, 1.29; 95% CI, 1.21 to 1.39). Conclusion: Elevated CVAI is a strong risk factor for incident multimorbidity among middle-aged and older Chinese adults, emphasizing its importance in the development of distinct disease clusters.

Source: Endocrinology and Metabolism

DOI: 10.3803/enm.2025.2525