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Estimation of fat-free mass in Asian neonates using bioelectrical impedance analysis

机译:使用生物电阻抗分析估算亚洲新生儿的无脂肪体重

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摘要

The aims of this study were to develop and validate a prediction equation of fat-free mass (FFM) based on bioelectrical impedance analysis (BIA) and anthropometry using air displacement plethysmography (ADP) as a reference in Asian neonates and to test the applicability of the prediction equations in independent Western cohort. A total of 173 neonates at birth and 140 at week-2 of age were included. Multiple linear regression analysis was performed to develop the prediction equations in a two-third randomly selected subset and validated on the remaining one-third subset at each time point and in an independent Queensland cohort. FFM measured by ADP was the dependent variable and anthropometric measures, sex and impedance quotient (L2/R50) were independent variables in the model. Accuracy of prediction equations were assessed using intra-class correlation and Bland-Altman analyses. L2/R50 was the significant predictor of FFM at week-2 but not at birth. Compared to the model using weight, sex and length, including L2/R50 slightly improved the prediction with a bias of 0.01kg with 2SD limits of agreement (LOA) (0.18, −0.20). Prediction explained 88.9% of variation but not beyond that of anthropometry. Applying these equations to Queensland cohort provided similar performance at the appropriate age. However, when the Queensland equations were applied to our cohort, the bias increased slightly but with similar LOA. BIA appears to have limited use in predicting FFM in the first few weeks of life compared to simple anthropometry in Asian populations. There is a need for population and age appropriate FFM prediction equations.
机译:这项研究的目的是基于生物电阻抗分析(BIA)和人体测量法,以空气体积体积描记法(ADP)为参考,开发和验证无脂肪质量(FFM)的预测方程式,并测试该方法的适用性。西方独立队列中的预测方程。总共包括173例新生儿和140例2周龄的新生儿。进行了多元线性回归分析,以在三分之二的随机选择子集中建立预测方程,并在每个时间点和独立的昆士兰队列中对其余的三分之一子集进行验证。 ADP测量的FFM是因变量,人体测量指标,性别和阻抗商(L 2 / R50)是模型中的自变量。使用类内相关性和Bland-Altman分析评估了预测方程的准确性。 L 2 / R50是第2周而非出生时FFM的重要预测因子。与使用体重,性别和长度(包括L 2 / R50)的模型相比,偏差为0.01kg且具有2SD协议限制(LOA)的模型稍有改善(0.18,-0.20)。预测可以解释88.9%的变化,但不能超出人体测量学的变化。将这些方程式应用于昆士兰队列在适当的年龄提供了类似的表现。但是,当将昆士兰方程式应用于我们的队列时,偏差略有增加,但LOA相似。与简单的人体测量法相比,在亚洲人群中,BIA在预测生命的最初几周时似乎使用有限。需要适合人群和年龄的FFM预测方程。

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