Piers L S, Soares M J, Frandsen S L, O'Dea K
Centre for Population Health and Nutrition, Monash Institute of Public Health, Monash Medical Centre, Clayton, Vic, Australia.
Int J Obes Relat Metab Disord. 2000 Sep;24(9):1145-52. doi: 10.1038/sj.ijo.0801387.
To assess the usefulness of the body mass index (BMI) in identifying individuals classified as overweight or obese based on estimates of body fat percentage (BF%) obtained by the deuterium dilution (BF%DD) method. In addition, to assess the accuracy of bioelectrical impedance analysis (BIA) and skinfold thickness (SFT) measurements in the estimation of body composition of Australians at the individual and group level.
Cross-sectional study.
One hundred and seventeen healthy Australian volunteers of European descent, comprising of 51 males and 66 females, ranging in age from 19 to 77 y.
BMI was calculated from body weight and height. Fat-free mass (FFM) was estimated from measures of total body water (TBW) using deuterium dilution (FFM(DD)), SFT using the equations of Durnin and Womersley (Br J Nutr 1974; 32: 77-97) (FFM(SFT)), and BIA using the equations of Lukaski et al (J Appl Physiol 1986; 60: 1327-1332) (FFM(Lu)), Segal et al (Am J Clin Nutr 1988; 47: 7-14) (FFM(Se)) and Heitmann (Eur J Clin Nutr 1990; 44: 831-837) (FFM(He)). Estimates of fat mass (FM) were calculated as the difference between body weight and FFM, while BF% was calculated by expressing FM as a percentage of body weight.
BMI had poor sensitivity and positive predictive value in identifying individuals as being overweight/obese as classified by BF%DD. Furthermore, estimates of FFM (and hence FM) from BIA or SFT could not be used interchangeably with DD, without the risk of considerable error at the individual level. At the group level errors were relatively smaller, though statistically significant. While FFM(SFT) could be corrected by the addition of the bias (1.2 kg in males and 0.8 kg in females), no simple correction was possible with BIA estimates of FFM for any of the equations used. However, an accurate prediction of FFM(DD) was possible from the combination of FFM(He), biceps SFT and mid-arm circumference in both males and females. The bias of this prediction was small (<0.15 kg), statistically non-significant in both sexes, and unrelated to the mean FFM obtained by the two methods. The revision of Heitmann's estimate of FFM using anthropometric variables described in this study had the best sensitivity (79%), specificity (96%) and positive predictive value (92%) in identifying overweight/obese individuals in comparison to the other equations tested.
BMI was a poor surrogate for body fatness in both males and females. The currently recommended equations for the prediction of body composition from SFT and BIA provided inaccurate estimates of FFM both at the individual and group level as compared to estimates from DD. However, Heitmann's equations, when combined with measures of the biceps SFT and mid-arm circumference, provided better estimates of FFM both at the individual and group level.
基于通过氘稀释法（BF%DD）获得的体脂百分比（BF%）估计值，评估体重指数（BMI）在识别超重或肥胖个体方面的有用性。此外，评估生物电阻抗分析（BIA）和皮褶厚度（SFT）测量在个体和群体水平上对澳大利亚人体成分估计的准确性。
横断面研究。
117名健康的欧洲裔澳大利亚志愿者，包括51名男性和66名女性，年龄在19至77岁之间。
BMI根据体重和身高计算得出。无脂肪量（FFM）通过氘稀释法（FFM(DD)）从总体水（TBW）测量值估算，通过杜宁和沃姆斯利方程（Br J Nutr 1974; 32: 77 - 97）（FFM(SFT)）从SFT估算，通过卢卡斯凯等人的方程（J Appl Physiol 1986; 60: 1327 - 1332）（FFM(Lu)）、西格尔等人的方程（Am J Clin Nutr 1988; 47: 7 - 14）（FFM(Se)）和海特曼的方程（Eur J Clin Nutr 1990; 44: 831 - 837）（FFM(He)）从BIA估算。脂肪量（FM）的估计值通过体重与FFM的差值计算得出，而BF%通过将FM表示为体重的百分比来计算。
在识别BF%DD分类为超重/肥胖的个体时，BMI的敏感性和阳性预测值较差。此外，来自BIA或SFT的FFM（以及因此的FM）估计值不能与DD互换使用，否则在个体水平存在相当大误差的风险。在群体水平，误差相对较小，尽管具有统计学意义。虽然FFM(SFT)可以通过加上偏差（男性为1.2 kg，女性为0.8 kg）进行校正，但对于所使用的任何方程，BIA估算的FFM都无法进行简单校正。然而，通过结合FFM(He)、肱二头肌SFT和上臂中部周长，可以在男性和女性中准确预测FFM(DD)。该预测的偏差较小（<0.15 kg），在两性中均无统计学意义，且与两种方法获得的平均FFM无关。与其他测试方程相比，使用本研究中描述的人体测量变量对海特曼的FFM估计值进行修订，在识别超重/肥胖个体方面具有最佳的敏感性（79%）、特异性（96%）和阳性预测值（92%）。
BMI在男性和女性中都不是体脂的良好替代指标。与DD估计值相比，目前推荐的从SFT和BIA预测身体成分的方程在个体和群体水平上对FFM的估计都不准确。然而，海特曼的方程与肱二头肌SFT和上臂中部周长测量值相结合，在个体和群体水平上对FFM的估计都更好。
