PURPOSE Body surface area (BSA) is an important measurement for many thermophysiological, pharmaceutical, toxicological, environmental, and military applications. Unfortunately, BSA is difficult to quantify, and existing prediction methods are not optimized for contemporary populations. METHODS The present study analyzed data body measurements from 5603 male and female participants of a US Army Anthropometric Survey to determine optimal methods for estimating BSA in modern US Army Soldiers. This data included 94 individual body measurements as well as three dimensional (3D) whole body scans for each participant. We used this data to assess and compared 15 existing equations to the measured data. We also derived best fitting nonlinear regression models for estimating BSA from different combinations of sex, height, and weight and iteratively included the remaining 91 measurements to determine which combinations resulted in the highest goodness-of-fit. RESULTS We found that inclusion of armspan measurements as a third body dimension maximized the model goodness-of-fit. CONCLUSION Some of the existing formulae provide reasonable estimates of 3D-scanner derived BSA; while our new formulae derived from this study allows for more accurate estimates of BSA using one or more common input variables.

中文翻译：

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现代美军士兵体表面积计算公式

目的 体表面积 (BSA) 是许多热生理学、制药、毒理学、环境和军事应用的重要测量值。不幸的是，BSA 难以量化，现有的预测方法并未针对当代人群进行优化。方法 本研究分析了美国陆军人体测量学调查的 5603 名男性和女性参与者的身体测量数据，以确定估计现代美国陆军士兵 BSA 的最佳方法。该数据包括每个参与者的 94 次个人身体测量以及三维 (3D) 全身扫描。我们使用这些数据来评估和比较 15 个现有方程与测量数据。我们还推导出了最佳拟合非线性回归模型，用于从性别、身高、和重量并迭代地包括剩余的 91 个测量值，以确定哪些组合导致最高的拟合优度。结果我们发现，将臂展测量作为第三个身体维度可以最大化模型的拟合优度。结论 一些现有公式提供了对 3D 扫描仪得出的 BSA 的合理估计；而我们从这项研究中得出的新公式允许使用一个或多个常见输入变量更准确地估计 BSA。