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Body Composition Methods in Adults with Type 2 Diabetes or at Risk for T2D: a Clinical Review
Current Diabetes Reports ( IF 5.2 ) Pub Date : 2021-03-17 , DOI: 10.1007/s11892-021-01381-9
Nadia Markie Sneed , Shannon A. Morrison

Purpose of Review

The aim of this study is to summarize anthropometric and advanced methods used to assess body composition in adults diagnosed with type 2 diabetes (T2D) or at risk for T2D that provide clinically relevant information about T2D disease-related complications or risk factors.

Recent Findings

Anthropometry is commonly used in clinical settings; however, provides unreliable estimates of fat mass, fat-free mass, and body fat distribution for metabolic health assessments compared to advanced techniques such as bioelectrical impedance analysis (BIA), dual-energy x-ray absorptiometry (DXA), computerized tomography (CT), and magnetic resonance imaging (MRI). Few studies report the clinical use of anthropometric and advanced body composition methods that identify T2D disease-related complications or T2D risk factors.

Summary

Anthropometry, BIA, DXA, CT, and MRI were used to estimate body adiposity and distribution, visceral and subcutaneous adipose tissue depots, and skeletal muscle mass. Review findings indicate that these methods were capable of identifying clinically relevant T2D disease-related complications such as sarcopenia and T2D risk factors such as obesity or regional adiposity. However, estimates were often sex and race/ethnicity specific warranting cross-validation of these methods in broader populations with T2D or risk for T2D prior to clinical implementation.



中文翻译:

成人2型糖尿病或有T2D风险的成年人的身体成分分析方法:临床评价

审查目的

这项研究的目的是总结人体测量学和先进的方法,用于评估诊断为2型糖尿病(T2D)或有T2D风险的成年人的身体成分,这些方法可提供有关T2D疾病相关并发症或危险因素的临床相关信息。

最近的发现

人体测量法通常用于临床环境中。但是,与生物电阻抗分析(BIA),双能X射线吸收法(DXA),计算机断层扫描(CT)等先进技术相比,代谢质量评估无法提供可靠的脂肪量,无脂肪量和人体脂肪分布估算值)和磁共振成像(MRI)。很少有研究报告临床使用人体测量学和先进的人体成分分析方法来鉴定与T2D疾病相关的并发症或T2D危险因素。

概括

人体测量法,BIA,DXA,CT和MRI用于估计人体的肥胖和分布,内脏和皮下脂肪组织的储库以及骨骼肌的质量。审查结果表明,这些方法能够识别与临床相关的与T2D疾病相关的并发症,如肌肉减少症和T2D危险因素(如肥胖症或区域性肥胖症)。但是,估计值通常是针对性别和种族/种族的,因此可以在临床实施之前在更广泛的具有T2D或T2D风险的人群中对这些方法进行交叉验证。

更新日期:2021-03-17
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