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阻抗指数或标准人体测量指标,哪一个是预测患病儿童去脂体重的更好变量?

Impedance index or standard anthropometric measurements, which is the better variable for predicting fat-free mass in sick children?

作者信息

Nguyen Quang Dung, Fusch Gerhard, Armbrust Sven, Jochum Frank, Fusch Christoph

机构信息

Department of Neonatology and Pediatric Intensive Care, University Children's Hospital, Greifswald, Germany.

出版信息

Acta Paediatr. 2007 Jun;96(6):869-73. doi: 10.1111/j.1651-2227.2007.00272.x.

Abstract

AIM

To compare the predictive value of impedance index (ZI, height2/impedance) with anthropometric measurements for estimating fat-free mass (FFM).

METHODS

FFM of 120 white paediatric children (46 males, 74 females), aged 2.5-18 years was measured by using dual energy X-ray absorptiometry. Weight, height, mid-upper arm circumference (MUAC), skinfold thickness (biceps, triceps, subscapular and suprailiac) and bioelectrical impedance were also obtained. Stepwise multiple regression analysis and residual plots were performed to determine the most significant variables to predict FFM.

RESULTS

The single best predictor of FFM was ZI, which explained 96.2% of the variance in FFM (r = 0.981, SEE = 2.15 kg). Addition of weight to the model containing ZI increased the explained variance of FFM to 96.6% (r = 0.983, SEE = 2.03 kg). BMI and MUAC were the poorest predictors of FFM: r = 0.422, SEE = 10.2 kg and r = 0.621, SEE = 8.93 kg, respectively.

CONCLUSION

Impedance index is a more significant single predictor of FFM than other anthropometric measurements. The predictive accuracy of bioelectrical impedance analysis-based prediction equations for FFM was improved by addition of weight.

摘要

目的

比较阻抗指数(ZI,身高²/阻抗)与人体测量指标对估计去脂体重(FFM)的预测价值。

方法

采用双能X线吸收法测量120名2.5至18岁白人儿童(46名男性,74名女性)的FFM。同时获取体重、身高、上臂中部周长(MUAC)、皮褶厚度(肱二头肌、肱三头肌、肩胛下和髂嵴上)以及生物电阻抗数据。进行逐步多元回归分析和残差图分析,以确定预测FFM的最显著变量。

结果

FFM的最佳单一预测指标是ZI,其解释了FFM方差的96.2%(r = 0.981,标准误 = 2.15 kg)。在包含ZI的模型中加入体重后,FFM的解释方差增加到96.6%(r = 0.983,标准误 = 2.03 kg)。BMI和MUAC是FFM最差的预测指标:r分别为0.422,标准误为10.2 kg和r为0.621,标准误为8.93 kg。

结论

阻抗指数是比其他人体测量指标更显著的FFM单一预测指标。通过加入体重,基于生物电阻抗分析的FFM预测方程的预测准确性得到提高。

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