Dose–response relationship between Chinese visceral adiposity index and type 2 diabetes mellitus among middle-aged and elderly Chinese - Pan, Liang; Xu, Qianqian; Liu, Jianmin; Gao, Yang; Li, Jun; Peng, Hongye; Chen, Linli; Wang, Miyuan; Mai, Gang; Yang, Shuo (Frontiers in Endocrinology, 2022)
Introduction China has the largest population of diabetic patients (about 116 million) in the world. As a novel model of the fat index for Chinese people, the Chinese visceral adiposity index (CVAI) was considered a reliable indicator to assess the dysfunction of visceral fat. This study aimed to explore the dose–response relationship between CVAI and type 2 diabetes mellitus (T2DM) in the Chinese population, considering CVAI as a continuous/categorical variable. Method Baseline and follow-up data were collected from waves 2011 and 2015, respectively, of the China Health and Retirement Longitudinal Study (CHARLS). Multivariate logistic regression models were used to explore the relationship between CVAI and T2DM. We built three models to adjust the possible effect of 10 factors (age, gender, education level, location, marital status, smoking status, drinking status, sleep time, systolic blood pressure (SBP), and diastolic blood pressure (DBP)) on the outcome. The restricted cubic splines were used to examine possible non-linear associations and visualize the dose–response relationship between CVAI and T2DM. Results A total of 5,014 participants were included, with 602 (12.00%) T2DM patients. The last CVAI quartile group (Q4) presented the highest risk of T2DM (OR, 2.17, 95% CI, 1.67–2.83), after adjusting for all covariates. There was a non-linear (U-shaped) relationship between the CVAI and the risk of T2DM (p for non-linear <0.001) in the restricted cubic spline regression model. CVAI was a risk factor of T2DM when it exceeded 92.49; every interquartile range (IQR) increment in the CVAI was associated with a 57% higher risk of developing T2DM (OR = 1.57, 95% CI = 1.36–1.83) after adjusting for potential confounders. The area under the receiver operating characteristic curve (AUC) (95% confidence interval) for CVAI was 0.623, and the optimal cutoff point was 111.2. There was a significant interaction between CVAI and gender by stratified analysis. Conclusion CVAI was closely associated with the risk of T2DM and might possibly be a potential marker in predicting T2DM development. The outcome suggested that it might be better to maintain CVAI within an appropriate range.