使用DXA和人体测量技术预测青少年和年轻人的内脏脂肪组织。

Deepika R Laddu, Vinson R Lee, Robert M Blew, Tetsuya Sato, Timothy G Lohman, Scott B Going
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引用次数: 0

摘要

目的:腹腔内(内脏)脂肪组织的积累与总脂肪无关,与儿童和成人胰岛素抵抗和2型糖尿病等代谢异常的发生有关。本研究的目的是利用人体测量变量和青少年和年轻人DXA腹部脂肪量的测量,建立预测公式,用于估计磁共振成像(MRI)测量的内脏脂肪(VAT)。方法:收集来自多民族人群的横断面数据,共70名男性和女性,年龄12-25岁,BMI范围为14.5-38.1 kg/m2。Android (AFM);使用DXA (GE Lunar Prodigy;GE Lunar Corp, Madison, WI, USA)。使用单层MRI(通用电气信号模型5x 1.5T)获得腹内内脏脂肪的标准测量,并在L4-L5水平分析VAT面积。使用ZedView 3.1进行图像分析。结果:AFM的DXA测量值(r=0.76)和L1-L4 (r=0.71)显著(P2)。DXA L1-L4脂肪量与性别解释了54%的VAT差异(SEE=11.08 cm2)。加入显著交互作用,性别× DXA脂肪质量,改进了AFM对VAT的预测(Radj2=0.61, SEE=10.10cm2)和L1-L4 (Radj2=0.59, SEE=10.39cm2)。结论:这些结果表明,从DXA测量的青少年和年轻人的区域脂肪量中可以准确地估计出VAT。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting visceral adipose tissue by MRI using DXA and anthropometry in adolescents and young adults.

Objective: Accumulation of intra-abdominal (visceral) adipose tissue, independent of total adiposity, is associated with development of metabolic abnormalities such as insulin resistance and type-2 diabetes in children and adults. The objective of this study was to develop prediction equations for estimating visceral adiposity (VAT) measured by magnetic resonance imaging (MRI) using anthropometric variables and measures of abdominal fat mass from DXA in adolescents and young adults.

Methods: Cross-sectional data was collected from a multiethnic population of seventy males and females, aged 12-25 years, with BMI ranging from 14.5-38.1 kg/m2. Android (AFM; android region as defined by manufacturers instruction) and lumbar L1-L4 regional fat masses were assessed using DXA (GE Lunar Prodigy; GE Lunar Corp, Madison, WI, USA). Criterion measures of intra-abdominal visceral fat were obtained using single-slice MRI (General Electric Signa Model 5x 1.5T) and VAT area was analyzed at the level OF L4-L5. Image analysis was carried out using ZedView 3.1.

Results: DXA measures of AFM (r=0.76) and L1-L4 (r=0.71) were significantly (P<0.0001) correlated with MRI-measured VAT. DXA AFM, together with gender and weight, explained 62% of the variance in VAT (SEE=10.06 cm2). DXA L1-L4 fat mass with gender explained 54% of the variance in VAT (SEE=11.08 cm2). Addition of the significant interaction, gender × DXA fat mass, improved prediction of VAT from AFM (Radj2=0.61, SEE=10.10cm2) and L1-L4 (Radj2=0.59, SEE=10.39cm2).

Conclusion: These results demonstrate that VAT is accurately estimated from regional fat masses measured by DXA in adolescents and young adults.

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