Neamat-Allah Jasmine, Wald Diana, Hüsing Anika, Teucher Birgit, Wendt Andrea, Delorme Stefan, Dinkel Julien, Vigl Matthaeus, Bergmann Manuela M, Feller Silke, Hierholzer Johannes, Boeing Heiner, Kaaks Rudolf
Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Division of Medical and Biological Informatics, German Cancer Research Center, Heidelberg, Germany.
PLoS One. 2014 Mar 13;9(3):e91586. doi: 10.1371/journal.pone.0091586. eCollection 2014.
In epidemiological studies, measures of body fat generally are obtained through anthropometric indices such as the body mass index (BMI), waist (WC), and hip circumferences (HC). Such indices, however, can only provide estimates of a person's true body fat content, overall or by adipose compartment, and may have limited accuracy, especially for the visceral adipose compartment (VAT).
To determine the extent to which different body adipose tissue compartments are adequately predicted by anthropometry, and to identify anthropometric measures alone, or in combination to predict overall adiposity and specific adipose tissue compartments, independently of age and body size (height).
In a sub-study of 1,192 participants of the German EPIC (European Prospective Investigation into Cancer and Nutrition) cohorts, whole-body MRI was performed to determine adipose and muscle tissue compartments. Additional anthropometric measurements of BMI, WC and HC were taken.
After adjusting for age and height, BMI, WC and HC were better predictors of total body volume (TBV), total adipose tissue (TAT) and subcutaneous adipose tissue (SAT) than for VAT, coronary adipose tissue (CAT) and skeletal muscle tissue (SMT). In both sexes, BMI was the best predictor for TBV (men: r = 0.72 [0.68-0.76], women: r = 0.80 [0.77-0.83]) and SMT (men: r = 0.52 [0.45-0.57], women: r = 0.48 [0.41-0.54]). WC was the best predictor variable for TAT (r = 0.48 [0.41-0.54]), VAT (r = 0.44 [0.37-0.50]) and CAT (r = 0.34 [0.26-0.41]) (men), and for VAT (r = 0.42 [0.35-0.49]) and CAT (r = 0.29 [0.22-0.37]) (women). BMI was the best predictor for TAT (r = 0.49 [0.43-0.55]) (women). HC was the best predictor for SAT (men (r = 0.39 [0.32-0.45]) and women (r = 0.52 [0.46-0.58])).
Especially the volumes of internal body fat compartments are poorly predicted by anthropometry. A possible implication may be that associations of chronic disease risks with the sizes of internal body fat as measured by BMI, WC and HC may be strongly underestimated.
在流行病学研究中，身体脂肪的测量通常通过人体测量指标来获得，如体重指数（BMI）、腰围（WC）和臀围（HC）。然而，这些指标只能提供一个人真实身体脂肪含量的估计值，无论是总体还是按脂肪组织分区，并且准确性可能有限，尤其是对于内脏脂肪组织（VAT）。
确定人体测量法能在多大程度上充分预测不同的身体脂肪组织分区，并确定单独的人体测量指标或其组合，以独立于年龄和体型（身高）来预测总体肥胖及特定的脂肪组织分区。
在德国EPIC（欧洲癌症与营养前瞻性调查）队列研究的1192名参与者的子研究中，进行了全身MRI以确定脂肪和肌肉组织分区。另外还测量了BMI、WC和HC等人体测量指标。
在调整年龄和身高后，BMI、WC和HC对总体积（TBV）、总脂肪组织（TAT）和皮下脂肪组织（SAT）的预测能力优于对VAT、冠状动脉脂肪组织（CAT）和骨骼肌组织（SMT）的预测能力。在男女两性中，BMI是TBV（男性：r = 0.72 [0.68 - 0.76]，女性：r = 0.80 [0.77 - 0.83]）和SMT（男性：r = 0.52 [0.45 - 0.57]，女性：r = 0.48 [0.41 - 0.54]）的最佳预测指标。WC是男性TAT（r = 0.48 [0.41 - 0.54]）、VAT（r = 0.44 [0.37 - 0.50]）和CAT（r = 0.34 [0.26 - 0.41]）以及女性VAT（r = 0.42 [0.35 - 0.49]）和CAT（r = 0.29 [0.2,2 - 0.37]）的最佳预测变量。BMI是女性TAT（r = 0.49 [0.43 - 0.55]）的最佳预测指标。HC是SAT的最佳预测指标（男性（r = 0.39 [0.32 - 0.45]）和女性（r = 0.52 [0.46 - 0.58]））。
尤其是人体测量法对体内脂肪组织分区体积的预测效果较差。一个可能的影响是，通过BMI、WC和HC测量的慢性病风险与体内脂肪大小之间的关联可能被严重低估。
