基于DXA的估计体积在4个隔间模型:验证和修改史密斯-瑞安方程
Lee Doernte1, April Spears2, Michael Lane2
1West Texas A&M University, College of Nursing and Health Science, Canyon, Texas, USA.
Clinical physiology and functional imaging
|July 24, 2025
概括
双能X射线吸收计 (DXA) 身体体积方程可以准确估计身体成分. 修改后的史密斯 - 瑞安方程为四模型提供相当于空气位移囊学的体积估计.
科学领域:
- 人体生理学 人体生理学
- 生物医学工程 生物医学工程
- 身体组成分析 身体成分分析
背景情况:
- 准确的身体成分评估对于健康评估和干预至关重要.
- 四个隔间 (4C) 模型提供高精度,但通常需要多个设备.
- 双能X射线吸收度 (DXA) 是一种常见的工具,但其对4C模型的体积 (BV) 估计需要验证.
研究的目的:
- 为了验证DXA衍生的BV方程 (威尔逊和史密斯-瑞安) 与空气位移囊学 (ADP) 相比.
- 在4C模型中修改史密斯-瑞安方程以改进BV估计.
- 评估DXA衍生的BV对4C模型对体脂百分比 (%BF) 和脂肪质量 (FM) 的准确性的影响.
主要方法:
- 90名健康成年人 (50名女性,40名男性) 接受了DXA,ADP (Bod Pod) 和生物电阻谱.
- 使用原始的威尔逊和史密斯-瑞安方程以及回归修改的史密斯-瑞安方程计算DXA衍生的BV.
- BV估计被整合到一个4C模型中,以计算%BF和FM.
主要成果:
- 所有基于DXA的BV估计都显示出与ADP的高相关性 (r ≥0.99).
- 原始方程与ADP相比,在%BF和FM中产生了小而显著的差异.
- 修改后的史密斯-瑞安方程产生了BV估计,统计学上相当于ADP (p = 0.998).
结论:
- 校准的DXA衍生BV方程可以在4C模型中可靠地取代ADP.
- 这提高了身体成分分析的可访问性和成本效益.
- 建议在多种不同人群中进一步验证.
关键词:
德克萨 (DEXA) 是一个史密斯 - 瑞安方程空气位移复合体图 (plethysmography) 是一种空气位移复合体图.身体构成 身体组成身体体积体积体积的体积.双能X射线吸收度计是双能X射线吸收度计.四个隔间模型的模型.百分比的身体脂肪百分比的身体脂肪更多相关视频
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