Formulae for calculating body surface area in modern U.S. Army Soldiers. (August 2020)

• Record Type: Journal Article
• Authors: Looney, David P.; Sanford, Diana P.; Li, Peng; Santee, William R.; Doughty, Elizabeth M.; Potter, Adam W
• Is Part Of: Journal of thermal biology. Volume 92(2020)
• Publication Date: 2020-08
• Subjects: BSA -- Anthropometrics -- Predictive modeling -- Surface scan; Thermobiology -- Periodicals; Temperature -- Periodicals; Biology -- Periodicals; Thermobiologie -- Périodiques; Thermobiology; Periodicals; 571.46
• DOI: 10.1016/j.jtherbio.2020.102650
• Languages: English
• ISSNs: 0306-4565

Abstract

Abstract: 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. Highlights: Uses an extensive anthropometic database that includes 94 direct measures along with 3D body scans. Compares accuracy of existing methods for estimating body surface area to a dataset of 5, 603 male and females. Provides an improved method for body surface area calculation. Includes a supplemental Excel file with new formulae embedded for easy use. Provides evidence to support the inclusion of an additional measure of armspan in body composition assessments.