Anthropometric and lipid indices in relation to prediabetes and diabetes: A cross-sectional study in resource-limited areas of northwestern China

人体测量学和血脂指标与糖尿病前期和糖尿病的关系:一项在中国西北部资源匮乏地区开展的横断面研究

阅读:1

Abstract

AIMS: This cross-sectional study was conducted to assess the association of triglyceridemic-waist phenotype, waist-to-height ratio (WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), and triglyceride-glucose (TyG) index with prediabetes and diabetes (PAD) using data from the Ningxia Cardiovascular Disorders and Related Risk Factors Survey. MATERIALS AND METHODS: This study included 10,803 patients. Logistic regression analysis and restricted cubic splines were applied to identify the association between the PAD and each index. The receiver operating characteristic curve was analyzed to identify and compare the discriminative power of different indexes in identifying PAD. RESULTS: A total of 43.87% patients were diagnosed with prediabetes and 11.75% patients were diagnosed with diabetes. After adjusting for confounders, participants with elevated high triglyceride levels with increased waist circumference (HTGW) were associated with a 2.65-fold (odds ratio [OR] 2.65, 95% confidence interval [95% CI] 2.31-3.03) risk of PAD. Comparing with the lowest quartile, those in the highest quartile of WHtR, LAP, VAI, and TyG index had a significantly increased risk of developing PAD. TyG index (area under the curve [AUC] 0.71, 95% CI 0.70-0.72) was better than WHtR (AUC 0.66, 95% CI 0.65-0.67), LAP (AUC 0.68, 95% CI 0.67-0.69), and VAI (AUC 0.65, 95% CI 0.64-0.66) at predicting the risk of PAD. CONCLUSIONS: The HTGW and elevated WHtR, LAP, VAI, and TyG index are associated with a greater risk of PAD. The TyG index is a more favorable anthropometric measure for predicting PAD, but its clinical utility needs to be validated in prospective cohorts, especially in resource-limited areas.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。