Choi Hyuk-Jae, Ko Chang-Yong, Chang Yunhee, Kim Gyoo-Suk, Choi Kyungsik, Kim Chul-Hyun
Department of Medical Convergence Research & Development, Rehabilitation Engineering Research Institute, Incheon, Republic of Korea.
Department of Research & Development, Refind Inc, Wonju, Gangwon-do, Republic of Korea.
PeerJ. 2021 Mar 8;9:e10970. doi: 10.7717/peerj.10970. eCollection 2021.
Metabolic disease due to increased fat mass is observed in amputees (APTs), thereby restricting their activity. Systemic health management with periodic body composition (BC) testing is essential for healthy living. Bioelectrical impedance analysis (BIA) is a non-invasive and low-cost method to test BC; however, the APTs are classified as being exempted in the BIA.
To develop segmental estimated regression equations (sEREs) for determining the fat-free mass (FFM, kg) suitable for APTs and improve the accuracy and validity of the sERE.
Seventy-five male APTs participated in this cross-sectional study. Multiple regression analysis was performed to develop highly accurate sEREs of BIA based on independent variables derived from anthropometric measurements, dual-energy X-ray absorptiometry (DXA), and BIA parameters. The difference in validity between the predicted DXA and sum of the segmentally-predicted FFM values by sEREs (Sum_sEREs) values was evaluated using bivariate linear regression analysis and the Bland-Altman plot.
The coefficient of determination ( ) and total error () between DXA and Sum_sEREs were 71% and 5.4 (kg) in the cross-validation analysis.
We confirmed the possibility of evaluating the FFM of APTs through the sEREs developed in this study. We also identified several independent variables that should be considered while developing such sEREs. Further studies are required to determine the validity of our sEREs and the most appropriate BIA frequencies for measuring FFM in APTs.
截肢者(APTs)中观察到因脂肪量增加导致的代谢性疾病,这限制了他们的活动。通过定期进行身体成分(BC)检测进行全身健康管理对健康生活至关重要。生物电阻抗分析(BIA)是一种检测BC的非侵入性低成本方法;然而,APTs被归类为BIA检测的豁免对象。
开发适用于APTs的用于确定去脂体重(FFM,kg)的分段估计回归方程(sEREs),并提高sERE的准确性和有效性。
75名男性APTs参与了这项横断面研究。基于人体测量、双能X线吸收法(DXA)和BIA参数得出的自变量,进行多元回归分析以开发高度准确的BIA的sEREs。使用双变量线性回归分析和Bland-Altman图评估预测的DXA与sEREs(Sum_sEREs)值分段预测的FFM值总和之间的有效性差异。
在交叉验证分析中,DXA与Sum_sEREs之间的决定系数( )和总误差()分别为71%和5.4(kg)。
我们证实了通过本研究开发的sEREs评估APTs的FFM的可能性。我们还确定了在开发此类sEREs时应考虑的几个自变量。需要进一步研究以确定我们的sEREs的有效性以及测量APTs的FFM的最合适的BIA频率。