Correlation of Fat Distribution in Whole Body MRI With Generally Used Anthropometric Data
Correlation of Fat Distribution in Whole Body MRI With Generally Used Anthropometric Data
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DOI：
10.1097/rli.0b013e3181afbb1e
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发表时间：
2009-11-01
影响因子：
6.7
通讯作者：
Schick, Fritz
中科院分区：
文献类型：
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作者：
Ludescher, Burkhard;Machann, Juergen;Schick, Fritz
目的：肥胖是代谢综合征和心血管疾病等许多疾病的众所周知的风险。尤其重要的是区分腹部内的脂肪组织和皮下脂肪组织。本研究的目的是将全身脂肪分布以及不同脂肪组织区室的体积分别与人体测量数据进行比较。 材料和方法：在 2 项全身磁共振成像 (MRI) 研究的背景下对 68 名志愿者（20 名男性，48 名女性，42.3 +/- 15.4 岁）进行了调查，这些研究将抑郁症和暴食症患者的身体脂肪分布与健康对照进行了比较。对这些研究中获得的未发表的数据进行了回顾性分析。样本包括 38 名健康志愿者、17 名抑郁症患者和 13 名患有神经性贪食症的女性。使用全身 MRI 确定个体的身体体积、总脂肪组织 (TAT) 体积、躯干皮下脂肪组织 (SCAT) 体积和内脏脂肪组织 (VAT) 体积。此外，对身体脂肪概况进行标准化并计算平均身体分布。获取身体脂肪含量的其他方式包括：皮褶卡尺、身体阻抗（3 种不同的设备）和简单的人体测量数据（腰臀比 [WHR]、体重指数 [BMI]、腹直肌腱膜到腹主动脉腹侧边缘的距离（在脐水平上的 MRI 图像中测量）（AD）和同一水平的皮下脂肪组织厚度）。不同模态与MRI数据相关。结果：皮皱数据与TAT（Spearman系数0.668，P≥0.0004）和SCAT（0.662，P≥0.0004）之间存在高度显着相关性。但与增值税没有相关性。阻抗数据显示 TAT 和 SCAT 显着相关（Spearman 0.7，P >= 0.0004）。腰围和臀围、WHR 和 BMI 等简单人体测量数据显示与脂肪室 TAT、VAT 和 SCAT 显着相关（Spearman 系数约为 0.7-0.4，P < 0.05）。标准化体脂切片和 VAT 切片与人体测量数据和阻抗数据，用于探索沿身体轴相关性较高或较弱的特定区域。皮褶数据、BMI 和身体阻抗数据与整个身体轴上的 TAT 以及几乎整个分析区域的 VAT 具有显着相关性。然而，不存在局部相关性较高的特殊身体区域。腰臀比与整体增值税和腹部区域 TAT（而不是与其他身体部位）高度相关，尤其是在女性中。因此，它似乎是本研究中腹部脂肪和增值税的最佳标记。结论：我们将不同的身体测量值和体脂设备与 MRI 获取的全身脂肪分布进行了比较。一般来说，所有模式都与体脂含量 (TAT) 显着相关，主要与 SCAT 相关。与增值税部分的相关性要弱得多，因此不可能对增值税进行充分估计。只有腰臀比与身体中心的脂肪显着相关，但仅限于女性。如果有必要特别研究增值税，因为增值税会导致较高的心血管风险、代谢综合征风险，并且与不同精神疾病的病程相关，那么 MRI 等横断面技术不能用更简单的方法替代
Objectives: Obesity is a commonly known risk for many diseases such as metabolic syndrome and cardiovascular disease. Especially important is the discrimination of the adipose tissue inside the abdomen and the subcutaneous adipose tissue. Aim of this study was to compare the whole body fat distribution, and the volume of different adipose tissue compartments respectively, with anthropometric data.Materials and Methods: Sixty-eight volunteers (20 males, 48 females, 42.3 +/- 15.4 years) were investigated in the context of 2 whole body magnetic resonance imaging (MRI) studies which compared the body fat distribution of depressive and bulimic patients with healthy controls. Unpublished data acquired in these studies were analyzed retrospectively.The sample consisted of 38 healthy volunteers, 17 patients with a depressive syndrome and 13 women suffering front bulimia nervosa. Individual body volume, total adipose tissue (TAT) volume, subcutaneous adipose tissue (SCAT) volume at the trunk, and visceral adipose tissue (VAT) volume were determined, using whole body MRI. Additionally, body fat profiles were standardized and a mean body distribution was calculated. Other modalities to acquire body fat content were: skin fold caliper, body impedance (3 different devices) and simple anthropometric data (Waist to Hip Ratio [WHR], Body Mass Index [BMI], distance of the aponeurosis of the rectus abdominis muscle to the ventral rim of the abdominal aorta (measured in MRI images on umbilical level) (AD) and subcutaneous adipose tissue thickness at the same level). The different modalities were correlated with the MRI data.Results: There were highly significant correlations between the skin fold data and TAT (Spearman coefficient 0.668, P >= 0.0004) and SCAT (0.662, P >= 0.0004). But there was no correlation with VAT. Impedance data revealed significant correlations of TAT and SCAT (Spearman 0.7, P >= 0.0004).Simple anthropometric data like waist and hip circumference, WHR, and BMI revealed significant correlations (Spearman coefficient around 0.7-0.4, P < 0.05) with the fat compartments TAT, VAT, and SCAT.The standardized body fat slices and the VAT slices were correlated with the anthropometric data and impedance data to explore specific areas along the body axis where the correlations were higher or weaker. Skinfold data, BMI, and body impedance data yielded significant correlations with TAT along the whole body axis, as well as with VAT in almost the whole analyzed area. However, there was no special body region with locally higher correlations. WHR depicted high correlations with whole VAT, and regional TAT at the abdomen (and not with the other body regions) especially in women. Therefore, it seems to be the best marker for abdominal fat and VAT in this study.Conclusions: We compared different body measures and body fat devices with the whole body fat distribution acquired by MRI. Generally, there were significant correlations of all modalities with body fat content (TAT) and mainly with SCAT. Correlations with VAT compartment were much weaker and an adequate estimation of VAT is, therefore, not possible. Only WHR revealed significant correlations with the fat in the body center, but only in women. If it is important to investigate especially the VAT which is responsible for a higher cardiovascular risk, risk for a metabolic syndrome and that is correlated with the course of different psychiatric diseases, cross sectional techniques such as MRI can not be substituted by simpler methods