AUTHOR=Pan Liang , Xu Qianqian , Liu Jianmin , Gao Yang , Li Jun , Peng Hongye , Chen Linli , Wang Miyuan , Mai Gang , Yang Shuo 

TITLE=Dose–response relationship between Chinese visceral adiposity index and type 2 diabetes mellitus among middle-aged and elderly Chinese

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.959860

DOI=10.3389/fendo.2022.959860

ISSN=1664-2392

ABSTRACT=Abstract:
Introduction: China has the largest population of diabetic patients (about 116 million) in the world. As a novel model of 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 Chinese population, considering CVAI as continuous/categorical variable.
Method: Baseline and follow-up data were collected from wave 2011 and 2015 respectively of the China Health and Retirement Longitudinal Study (CHARLS). Multi-variate 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, SBP and DBP) on the outcome. The restricted cubic splines were used to examine possible nonlinear association 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 nonlinear (U-shaped) relationship between CVAI index and the risk of T2DM (p for nonlinear < 0.001) in restricted cubic spline regression model. CVAI was a risk factor of T2DM when exceeded 92.49, every IQR increment in CVAI index was associated with 57% higher risk of developing T2DM (OR = 1.57, 95% CI = 1.36-1.83) after adjusting for potential confounders. The AUC (95% confidence interval) for CVAI was 0.623, and the optimal cut-off point was 111.2. There was 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.