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

医学 四分位间距 四分位数 2型糖尿病 血压 人口学 内科学 婚姻状况 逻辑回归 纵向研究 糖尿病 人口 体质指数 贝叶斯多元线性回归 人口研究 线性回归 内分泌学 环境卫生 统计 数学 病理 社会学 置信区间
作者
Liang Pan,Qianqian Xu,Jianmin Liu,Yang Gao,Jun Li,Hongye Peng,Linli Chen,Miyuan Wang,Gang Mai,Shuo Yang
出处
期刊:Frontiers in Endocrinology [Frontiers Media SA]
卷期号:13: 959860-959860 被引量:30
标识
DOI:10.3389/fendo.2022.959860
摘要

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.
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