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一种新型内脏脂肪指数预测中国成年人 2 型糖尿病和糖尿病前期:一项为期 5 年的前瞻性研究。

A Novel Visceral Adiposity Index for Prediction of Type 2 Diabetes and Pre-diabetes in Chinese adults: A 5-year prospective study.

机构信息

The First Affiliated Hospital of Chongqing Medical University, Department of Endocrinology, Chongqing, 400016, China.

出版信息

Sci Rep. 2017 Oct 23;7(1):13784. doi: 10.1038/s41598-017-14251-w.

Abstract

The Chinese visceral adiposity index (CVAI) is a recently developed indicator of visceral adiposity. We investigated the predictive value of the CVAI for the development of dysglycemia (pre-diabetes and type 2 diabetes) and compared its predictive power with that of the Visceral adiposity index (VAI) and various anthropometric indices. This community-based study included 2,383 participants. We assessed the predictive power of adiposity indices by performing univariate and multivariate binary logistic regression analysis and calculating the area under the receiver-operating characteristic (ROC) curve according to their quartiles. Logistic regression analysis showed that individuals in higher CVAI quartiles at baseline were more likely to develop dysglycemia than those in lower CVAI quartiles. The area under the ROC curve for CVAI was significantly higher than that of other adiposity indices. In addition, among the various adiposity indices tested, the CVAI had the greatest Youden index for identifying dysglycemia in both genders. Our data demonstrate that the CVAI is a better predictor of type 2 diabetes and pre-diabetes than the VAI, BMI, waist circumference, waist-to-hip ratio and waist-to-height ratio in Chinese adults.

摘要

中国内脏脂肪指数 (CVAI) 是一种新近开发的内脏脂肪指标。我们研究了 CVAI 对糖代谢异常(糖尿病前期和 2 型糖尿病)发展的预测价值,并将其预测能力与内脏脂肪指数 (VAI) 和各种人体测量指数进行了比较。这项基于社区的研究纳入了 2383 名参与者。我们通过单变量和多变量二元逻辑回归分析评估了肥胖指数的预测能力,并根据四分位数计算了受试者工作特征 (ROC) 曲线下的面积。逻辑回归分析显示,基线时 CVAI 四分位较高的个体发生糖代谢异常的可能性高于 CVAI 四分位较低的个体。ROC 曲线下的 CVAI 面积明显高于其他肥胖指数。此外,在测试的各种肥胖指数中,CVAI 在两性中识别糖代谢异常的约登指数最大。我们的数据表明,CVAI 是中国成年人 2 型糖尿病和糖尿病前期的更好预测指标,优于 VAI、BMI、腰围、腰臀比和腰高比。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8746/5653832/372927174c3c/41598_2017_14251_Fig1_HTML.jpg

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