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SMRT:一种智能质量比率技术,其表现优于身体质量指数 (BMI),用于预测腰与身高的比率
1Department of Anesthesiology, Regio Klinikum, Pinneberg, Germany.
German medical science : GMS e-journal
|February 20, 2026
概括
一个新的SMRT模型仅使用身高和体重来估计腰与身高的比率 (WHtR),为评估中心肥胖和心脏代谢风险提供了比BMI更好的替代方案. 这种简单的工具可以改善风险评估,当腰围测量不可用时.
科学领域:
- 人类测量学 人类测量学.
- 公共卫生 公共卫生
- 评估心血管风险评估
背景情况:
- 腰与身高的比率 (WHtR) 是比BMI更好的中心肥胖和心脏代谢风险的指标.
- 由于腰围测量不一致,WHtR的临床使用受到限制.
研究的目的:
- 开发和验证SMRT,一个简单的人类测量模型,仅使用身高和体重来估计WHtR.
- 为评估中心脂肪和心脏代谢风险提供临床实用的工具.
主要方法:
- 从四个NHANES周期 (2015-2023) 收集代表性成年人样本 (n=22,109) 的数据.
- 开发了一种线性回归模型 (SMRT) 来从身高和体重来估计WHtR.
- 使用相关性,预测误差 (RMSE,MAE) 和风险类别分类准确度评估模型性能,与BMI进行比较.
主要成果:
- SMRT模型 (WHtR_est = 1.271 + 0.00470 ×重量 (公斤) - 0.634 ×高度 (米)) 与测量的WHtR (r=0.925) 显示出强烈的相关性.
- 在相关性 (r=0.913) 和分类准确性方面,SMRT的表现优于BMI (78.2%对64.4%).
- 与BMI (78.1%) 相比,SMRT在检测高WHtR (≥0.50) 时显示出较低的预测误差和更高的灵敏度 (90.3%).
结论:
- SMRT是一种简单,强大的,临床上实用的模型,用于从身高和体重来估计WHtR.
- 该模型是中央脂肪和心脏代谢风险的宝贵查工具,特别是在缺少腰围数据的情况下.
- SMRT提高了与肥胖相关的健康风险的评估.
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