Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Clin Nutr ESPEN. 2024 Oct;63:214-225. doi: 10.1016/j.clnesp.2024.06.040. Epub 2024 Jun 29.
Bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) serves as common modalities for body composition assessment. This study was aimed to evaluate the agreement between BIA and DXA measures in UK Biobank.
UK Biobank participants with body fat mass (FM) and fat-free mass (FFM) estimates obtained through BIA (Tanita BC418MA) and DXA concurrently were included. Correlation between BIA and DXA-derived estimates were assessed with Lin's concordance correlation coefficients. Bland-Altman and Passing-Boblok analyses were performed to quantify the difference and agreement between BIA and DXA. Multivariable linear regression was used to identify predictors influencing the differences. Finally, prediction models were developed to calibrate BIA measures against DXA.
The analysis included 34437 participants (female 51.4%, mean age 64.1 years at imaging assessment). BIA and DXA measurements were highly correlated (Lin's concordance correlation coefficient 0.94 for FM and 0.94 for FFM). BIA (Tanita BC418MA) underestimates FM overall by 1.84 kg (23.77 vs. 25.61, p < 0.01), and overestimated FFM overall by 2.56 kg (52.49 vs. 49.93, p < 0.01). The BIA-DXA differences were associated with FM, FFM, BMI and waist circumference. The developed prediction models showed overall good performance in calibrating BIA data.
Our analysis exhibited strong correlation between BIA (Tanita BC418MA)- and DXA-derived body composition measures at a population level in UK Biobank. However, the BIA-DXA differences were observed at individual level and associated with individual anthropometric measures. Future studies may explore the use of prediction models to enhance the calibration of BIA measures for more accurate assessments in UK Biobank.
生物电阻抗分析（BIA）和双能 X 射线吸收法（DXA）是评估身体成分的常用方法。本研究旨在评估英国生物库中 BIA 和 DXA 测量值之间的一致性。
纳入同时接受 BIA（Tanita BC418MA）和 DXA 测量体脂肪量（FM）和去脂体重（FFM）的英国生物库参与者。采用 Lin 一致性相关系数评估 BIA 和 DXA 衍生估计值之间的相关性。采用 Bland-Altman 和 Passing-Boblok 分析评估 BIA 和 DXA 之间的差异和一致性。采用多元线性回归确定影响差异的预测因子。最后，建立预测模型以校准 BIA 测量值与 DXA。
该分析纳入 34437 名参与者（女性占 51.4%，成像评估时的平均年龄为 64.1 岁）。BIA 和 DXA 测量值高度相关（FM 的 Lin 一致性相关系数为 0.94，FFM 为 0.94）。BIA（Tanita BC418MA）总体低估 FM 1.84kg（25.61 比 23.77，p<0.01），总体高估 FFM 2.56kg（49.93 比 49.93，p<0.01）。BIA-DXA 差异与 FM、FFM、BMI 和腰围相关。所开发的预测模型在校准 BIA 数据方面总体表现良好。
我们的分析表明，在英国生物库中，BIA（Tanita BC418MA）和 DXA 衍生的身体成分测量值在人群水平上具有很强的相关性。然而，在个体水平上观察到 BIA-DXA 差异，且与个体人体测量指标相关。未来的研究可能会探索使用预测模型来增强 BIA 测量值的校准，以在英国生物库中进行更准确的评估。
