Abstract

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. 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. We found that inclusion of armspan measurements as a third body dimension maximized the model goodness-of-fit. 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.

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