Literature DB >> 29288245

Validation of a three-dimensional body scanner for body composition measures.

Michelle M Harbin1, Alexander Kasak2, Joseph D Ostrem3, Donald R Dengel2.   

Abstract

The accuracy of an infrared three-dimensional (3D) body scanner in determining body composition was compared against hydrostatic weighing (HW), bioelectrical impedance analysis (BIA), and anthropometry. A total of 265 adults (119 males; age = 22.1 ± 2.5 years; body mass index = 24.5 ± 3.9 kg/m2) had their body fat percent (BF%) estimated from 3D scanning, HW, BIA, skinfolds, and girths. A repeated measures analysis of variance (ANOVA) indicated significant differences among methods (p < 0.001). Multivariate ANOVA indicated a significant main effect of sex and method (p < 0.001), with a non-significant interaction (p = 0.101). Bonferroni post-hoc comparisons identified that BF% from 3D scanning (18.1 ± 7.8%) was significantly less than HW (22.8 ± 8.5%, p < 0.001), BIA (20.1 ± 9.1%, p < 0.001), skinfolds (19.7 ± 9.7%, p < 0.001), and girths (21.2 ± 10.4%, p < 0.001). The 3D scanner decreased in precision with increasing adiposity, potentially resulting from inconsistences in the 3D scanner's analysis algorithm. A correction factor within the algorithm is required before infrared 3D scanning can be considered valid in measuring BF%.

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Year:  2017        PMID: 29288245     DOI: 10.1038/s41430-017-0046-1

Source DB:  PubMed          Journal:  Eur J Clin Nutr        ISSN: 0954-3007            Impact factor:   4.016


  6 in total

1.  Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner.

Authors:  Jonathan P Bennett; Yong En Liu; Brandon K Quon; Nisa N Kelly; Michael C Wong; Samantha F Kennedy; Dominic C Chow; Andrea K Garber; Ethan J Weiss; Steven B Heymsfield; John A Shepherd
Journal:  Clin Nutr       Date:  2021-12-07       Impact factor: 7.643

2.  Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men.

Authors:  Roman Sager; Sabine Güsewell; Frank Rühli; Nicole Bender; Kaspar Staub
Journal:  PLoS One       Date:  2020-06-11       Impact factor: 3.240

Review 3.  Comparison of Body Scanner and Manual Anthropometric Measurements of Body Shape: A Systematic Review.

Authors:  Lorena Rumbo-Rodríguez; Miriam Sánchez-SanSegundo; Rosario Ferrer-Cascales; Nahuel García-D'Urso; Jose A Hurtado-Sánchez; Ana Zaragoza-Martí
Journal:  Int J Environ Res Public Health       Date:  2021-06-08       Impact factor: 3.390

Review 4.  Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review.

Authors:  Paola Piqueras; Alfredo Ballester; Juan V Durá-Gil; Sergio Martinez-Hervas; Josep Redón; José T Real
Journal:  Front Psychol       Date:  2021-07-09

5.  Novel body fat estimation using machine learning and 3-dimensional optical imaging.

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

Review 6.  Come Back Skinfolds, All Is Forgiven: A Narrative Review of the Efficacy of Common Body Composition Methods in Applied Sports Practice.

Authors:  Andreas M Kasper; Carl Langan-Evans; James F Hudson; Thomas E Brownlee; Liam D Harper; Robert J Naughton; James P Morton; Graeme L Close
Journal:  Nutrients       Date:  2021-03-25       Impact factor: 5.717

  6 in total

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