Hill Alison M, LaForgia Joe, Coates Alison M, Buckley Jonathan D, Howe Peter R C
ATN Centre for Metabolic Fitness, Nutritional Physiology Research Centre, University of South Australia, Adelaide, South Australia 5005, Australia.
Obesity (Silver Spring). 2007 Feb;15(2):504-10. doi: 10.1038/oby.2007.629.
To identify an anatomically defined region of interest (ROI) from DXA assessment of body composition that when combined with anthropometry can be used to accurately predict intra-abdominal adipose tissue (IAAT) in overweight/obese individuals.
Forty-one postmenopausal women (age, 49 to 66 years; BMI, 26 to 37 kg/m(2)) underwent anthropometric and body composition assessments. ROI were defined as quadrilateral boxes extending 5 or 10 cm above the iliac crest and laterally to the edges of the abdominal soft tissue. A single-slice computed tomography (CT) scan was measured at the L3 to L4 intervertebral space, and abdominal skinfolds were taken.
Forward step-wise regression revealed the best predictor model of IAAT area measured by CT (r(2) = 0.68, standard error of estimate = 17%) to be: IAAT area (centimeters squared) = 51.844 + DXA 10-cm ROI (grams) (0.031) + abdominal skinfold (millimeters) (1.342). Interobserver reliability for fat mass (r = 0.994; coefficient of variation, 2.60%) and lean mass (r = 0.986, coefficient of variation, 2.67%) in the DXA 10-cm ROI was excellent.
This study has identified a DXA ROI that can be reliably measured using prominent anatomical landmarks, in this case, the iliac crest. Using this ROI, combined with an abdominal skinfold measurement, we have derived an equation to predict IAAT in overweight/obese postmenopausal women. This approach offers a simpler, safer, and more cost-effective method than CT for assessing the efficacy of lifestyle interventions aimed at reducing IAAT. However, this warrants further investigation and validation with an independent cohort.
从双能X线吸收法（DXA）对身体成分的评估中确定一个解剖学定义的感兴趣区域（ROI），该区域与人体测量学相结合时，可用于准确预测超重/肥胖个体的腹内脂肪组织（IAAT）。
41名绝经后女性（年龄49至66岁；体重指数26至37kg/m²）接受了人体测量和身体成分评估。ROI定义为在髂嵴上方5或10厘米处并横向延伸至腹部软组织边缘的四边形框。在L3至L4椎间隙进行单层计算机断层扫描（CT）测量，并测量腹部皮褶厚度。
向前逐步回归显示，通过CT测量的IAAT面积的最佳预测模型（r² = 0.68，估计标准误差 = 17%）为：IAAT面积（平方厘米）= 51.844 + DXA 10厘米ROI（克）（0.031）+腹部皮褶厚度（毫米）（1.342）。DXA 10厘米ROI中脂肪量（r = 0.994；变异系数，2.60%）和瘦体量（r = 0.986，变异系数，2.67%）的观察者间可靠性极佳。
本研究确定了一个可以使用突出的解剖学标志（在本案例中为髂嵴）可靠测量的DXA ROI。使用该ROI，结合腹部皮褶测量，我们得出了一个预测超重/肥胖绝经后女性IAAT的方程。与CT相比，这种方法为评估旨在减少IAAT的生活方式干预效果提供了一种更简单、更安全且更具成本效益的方法。然而，这需要在独立队列中进行进一步的研究和验证。
