High-Resolution Three-Dimensional Photonic Scan-Derived Equations Improve Body Surface Area Prediction in Diverse Populations

Maxine Ashby-Thompson, Ying Ji, Jack Wang, Wen Yu, John C. Thornton, Carla Wolper, Richard Weil, Earle C. Chambers, Blandine Laferrère, F. Xavier Pi-Sunyer, Dympna Gallagher

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Objective: Equations for predicting body surface area (BSA) produce flawed estimates, especially for individuals with obesity. This study aimed to compare BSA measured by a three-dimensional photonic scanner (3DPS) with BSA predicted by six commonly cited prediction equations and to develop new prediction equations if warranted. Methods: The 3DPS was validated against manual measurements by breadth caliper for body thicknesses measured at three anatomical sites on a mannequin. BSA was derived from 3DPS whole-body scans of 67 males and 201 females, aged 18 to 83 years, with BMI between 17.8 and 77.8 kg/m2 and varied races/ethnicities. Results: Width and depth measurements by 3DPS and caliper were within 1%, except for hip, with an error of 1.8%. BSA3DPS differed from BSA predicted by each equation (P < 0.05), except for males by DuBois and DuBois (P = 0.60), Tikuisis (P = 0.27), and Yu (P = 0.45) and for females by Tikuisis (P = 0.70). The combined and sex-specific equations obtained by regressing ln(BSA) on ln(weight in kilograms [W]) and ln(height in meters [H]) are as follows (R2 and SEE correspond to ln[BSA]): combined, BSA3DPS = 0.03216 × W0.4904 × H0.3769, R2 = 0.982, SEE = 0.021; males, BSA3DPS = 0.01624 × W0.4725 × H0.5231; and females, BSA3DPS = 0.01522 × W0.4921 × H0.5231, R2= 0.986, SEE = 0.019. Conclusions: New height and weight BSA equations improve BSA estimation in individuals with BMI ≥ 40 and in African Americans, Hispanic Americans, and Asian Americans.

Original languageEnglish (US)
Pages (from-to)706-717
Number of pages12
JournalObesity
Volume28
Issue number4
DOIs
StatePublished - Apr 1 2020

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Nutrition and Dietetics

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