The association of changes in the Chinese visceral adiposity index and cardiometabolic diseases: a cohort study

Abstract

Abstract Objective The relationship between changes in Chinese visceral adiposity index (CVAI) and cardiometabolic diseases (CMD) in middle-aged and elderly individuals remains unclear. This study aimed to explore whether changes in the CVAI were associated with CMD incidence. Methods This study included 3,243 individuals aged over 45 years from the China Health and Retirement Longitudinal Study. The exposures were changes in the CVAI and cumulative CVAI from 2012 to 2015. Changes in the CVAI were classified using K-means clustering analysis, and the cumulative CVAI was calculated as follows: (CVAI2012 + CVAI2015)/2 × time (2015–2012). Multivariable logistic regression models were used to assess the relationship between different CVAI change classes and CMD incidence. Restricted cubic splines regression was used to assess the dose–response relationship between cumulative CVAI and CMD incidence. To investigate the relationship between combined exposure to each component of CAVI and CMD incidence, a weighted quantile sum regression analysis was employed. Results During the 5 years of follow-up, 776 (24%) incident CMD cases were identified. Changes in CVAI and cumulative CVAI were independently and positively associated with CMD. After adjusting for potential confounders, compared with Class 1, the adjusted ORs (95% CIs) for incident CMD were 1.18 (0.90–1.57) for Class 2, 1.40 (1.03–1.92) for Class 3, and 1.56 (1.04–2.34) for Class 4. When cumulative CVAI was categorized into quartiles, compared with Q1, the adjusted ORs (95% CIs) for incident CMD were 1.30 (1.00–1.70) for Q2, 1.34 (1.01–1.79) for Q3, and 1.63 (1.15–2.31) for Q4. In addition, cumulative CVAI in the overall population exhibited a linear association with CMD (P overall = 0.012, P non-linearity = 0.287), diabetes (P overall = 0.022, P non-linearity = 0.188), and stroke (P overall = 0.002, P non-linearity = 0.978), but showed no significant association with heart disease (P overall = 0.619, P non-linearity = 0.442). Conclusion Participants with higher baseline CVAI level and a change of elevating CVAI level may suffer an increased incidence of CMD. Furthermore, our findings elucidate the underlying mechanisms of the CVAI by highlighting TG as the primary contributor to the observed associations. Long-term CVAI monitoring is of significant importance for early identification and prevention of CMD, with significant implications for clinical practice.

Keywords

• Chinese visceral adiposity index
• Cardiometabolic diseases
• Diabetes
• Heart disease
• Stroke