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人体成分分析在肥胖表型中的相关性。

Relevance of body composition in phenotyping the obesities.

机构信息

Metabolic Research Laboratory, Clínica Universidad de Navarra, Irunlarrea 1, Pamplona, 31008, Spain.

CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain.

出版信息

Rev Endocr Metab Disord. 2023 Oct;24(5):809-823. doi: 10.1007/s11154-023-09796-3. Epub 2023 Mar 17.

Abstract

Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.

摘要

肥胖是全球范围内最为广泛的代谢异常,增加了发生心血管代谢异常的风险,如 2 型糖尿病、高血压和血脂异常。体重指数(BMI)仍然是最常用于分类肥胖患者的工具,但它并不能准确反映身体脂肪量。在本文件中,我们回顾了用于表型肥胖的经典和新分类系统。随着对心血管代谢危险因素的认识和应用的增加,以及对身体成分技术的更高精度和更易获得性,肥胖患者的表型分析更加精细。现在是将这些进展纳入常规临床实践的时候了,以便更好地诊断超重和肥胖,并优化肥胖患者的治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95d8/10492885/f7a45cbd7ab4/11154_2023_9796_Fig5_HTML.jpg

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