OBJECTIVE: Three-dimensional (3D) imaging systems are increasingly being used in health care settings for quantifying body size and shape. The potential exists to provide similar phenotyping capabilities outside of professional settings using smartphone applications (apps). The current study aim was to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20-camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites. METHODS: Fifty-nine adults were scanned with the app and SS20; the same software was used to generate circumference estimates from device-acquired object files that were then compared with reference tape measurements. RESULTS: The app and SS20 had similar coefficients of variation that were minimally larger than those by the tape (e.g., waist, 0.93%, 0.87%, and 0.06%). Correlations of the app and of SS20 with tape circumferences were all strong (p < 0.001) and similar in magnitude (R2 s: 0.72-0.93 and 0.78-0.95, respectively); minimally significant (p < 0.05 to p < 0.01) bias was present between both imaging approaches and some tape measurements. CONCLUSION: These proof-of-concept observations combined with ubiquitous smartphone availability create the possibility of phenotyping adult body size and shape, with important clinical and research implications, on a global scale.
OBJECTIVE: Three-dimensional (3D) imaging systems are increasingly being used in health care settings for quantifying body size and shape. The potential exists to provide similar phenotyping capabilities outside of professional settings using smartphone applications (apps). The current study aim was to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20-camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites. METHODS: Fifty-nine adults were scanned with the app and SS20; the same software was used to generate circumference estimates from device-acquired object files that were then compared with reference tape measurements. RESULTS: The app and SS20 had similar coefficients of variation that were minimally larger than those by the tape (e.g., waist, 0.93%, 0.87%, and 0.06%). Correlations of the app and of SS20 with tape circumferences were all strong (p < 0.001) and similar in magnitude (R2 s: 0.72-0.93 and 0.78-0.95, respectively); minimally significant (p < 0.05 to p < 0.01) bias was present between both imaging approaches and some tape measurements. CONCLUSION: These proof-of-concept observations combined with ubiquitous smartphone availability create the possibility of phenotyping adult body size and shape, with important clinical and research implications, on a global scale.
Authors: Sima Sobhiyeh; Alexander Dunkel; Marcelline Dechenaud; Ali Mehrnezhad; Samantha Kennedy; John Shepherd; Peter Wolenski; Steven B Heymsfield Journal: Med Phys Date: 2021-07-09 Impact factor: 4.071
Authors: Steven B Heymsfield; Brianna Bourgeois; Bennett K Ng; Markus J Sommer; Xin Li; John A Shepherd Journal: Eur J Clin Nutr Date: 2018-05-10 Impact factor: 4.016
Authors: Sima Sobhiyeh; Samantha Kennedy; Alexander Dunkel; Marcelline E Dechenaud; Jerome A Weston; John Shepherd; Peter Wolenski; Steven B Heymsfield Journal: Obes Sci Pract Date: 2020-11-06
Authors: Patrick S Harty; Breck Sieglinger; Steven B Heymsfield; John A Shepherd; David Bruner; Matthew T Stratton; Grant M Tinsley Journal: Eur J Clin Nutr Date: 2020-03-16 Impact factor: 4.016