Literature DB >> 34756706

Agreement Between A 2-Dimensional Digital Image-Based 3-Compartment Body Composition Model and Dual Energy X-Ray Absorptiometry for The Estimation of Relative Adiposity.

Katherine Sullivan1, Casey J Metoyer1, Bjoern Hornikel1, Clifton J Holmes2, Brett S Nickerson3, Michael R Esco1, Michael V Fedewa4.   

Abstract

The purpose of this study was to compare relative adiposity (%Fat) derived from a 2-dimensional image-based 3-component (3C) model (%Fat3C-IMAGE) and dual-energy X-ray absorptiometry (DXA) (%FatDXA) against a 5-component (5C) laboratory criterion (%Fat5C). 57 participants were included (63.2% male, 84.2% White/Caucasian, 22.5±4.7 yrs., 23.9±2.8 kg/m2). For each participant, body mass and standing height were measured to the nearest 0.1 kg and 0.1 cm, respectively. A digital image of each participant was taken using a 9.7 inch, 16g iPad Air 2 and analyzed using a commercially available application (version 1.1.2, made Health and Fitness, USA) for the estimation of body volume (BV) and inclusion in %Fat3C-IMAGE . %Fat3C-IMAGE and %Fat5C included measures of total body water derived from bioimpedance spectroscopy. The criterion %Fat5C included BV estimates derived from underwater weighing and bone mineral content measures via DXA. %FatDXA estimates were calculated from a whole-body DXA scan. A standardized mean effect size (ES) assessed the magnitude of differences between models with values of 0.2, 0.5, and 0.8 for small, moderate, and large differences, respectively. Data are presented as mean ± standard deviation. A strong correlation (r = 0.94, p <.001) and small mean difference (ES = 0.24, p <.001) was observed between %Fat3C-IMAGE (19.20±5.80) and %Fat5C (17.69±6.20) whereas a strong correlation (r = 0.87, p <.001) and moderate-large mean difference (ES = 0.70, p <.001) was observed between %FatDXA (22.01±6.81) and %Fat5C. Furthermore, %Fat3C-IMAGE (SEE = 2.20 %Fat, TE= 2.6) exhibited smaller SEE and TE than %FatDXA (SEE = 3.14 %Fat, TE = 5.5). The 3C image-based model performed slightly better in our sample of young adults than the DXA 3C model. Thus, the 2D image analysis program provides an accurate and non-invasive estimate of %Fat within a 3C model in young adults. Compared to DXA, the 3C image-based model allows for a more cost-effective and portable method of body composition assessment, potentially increasing accessibility to multi-component methods.
Copyright © 2021 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  2D image; Body composition; five-component, DXA; multi-compartment model; three-component

Mesh:

Year:  2021        PMID: 34756706      PMCID: PMC8942865          DOI: 10.1016/j.jocd.2021.08.004

Source DB:  PubMed          Journal:  J Clin Densitom        ISSN: 1094-6950            Impact factor:   2.963


  34 in total

1.  Percent body fat via DEXA: comparison with a four-compartment model.

Authors:  Grant E Van Der Ploeg; Robert T Withers; Joe Laforgia
Journal:  J Appl Physiol (1985)       Date:  2003-02

2.  The relative accuracy of skinfolds compared to four-compartment estimates of body composition.

Authors:  Brett S Nickerson; Michael V Fedewa; Zackary Cicone; Michael R Esco
Journal:  Clin Nutr       Date:  2019-04-19       Impact factor: 7.324

3.  Density of fat-free body mass: relationship with race, age, and level of body fatness.

Authors:  M Visser; D Gallagher; P Deurenberg; J Wang; R N Pierson; S B Heymsfield
Journal:  Am J Physiol       Date:  1997-05

4.  Five-component model validation of reference, laboratory and field methods of body composition assessment.

Authors:  Grant M Tinsley
Journal:  Br J Nutr       Date:  2020-09-14       Impact factor: 3.718

5.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

6.  Differences between young and old females in the five levels of body composition and their relevance to the two-compartment chemical model.

Authors:  M Mazariegos; Z M Wang; D Gallagher; R N Baumgartner; D B Allison; J Wang; R N Pierson; S B Heymsfield
Journal:  J Gerontol       Date:  1994-09

7.  Skinfolds and body density and their relation to body fatness: a review.

Authors:  T G Lohman
Journal:  Hum Biol       Date:  1981-05       Impact factor: 0.553

Review 8.  Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review.

Authors:  Rafdzah Zaki; Awang Bulgiba; Roshidi Ismail; Noor Azina Ismail
Journal:  PLoS One       Date:  2012-05-25       Impact factor: 3.240

9.  Total body water estimations in healthy men and women using bioimpedance spectroscopy: a deuterium oxide comparison.

Authors:  Jordan R Moon; Sarah E Tobkin; Michael D Roberts; Vincent J Dalbo; Chad M Kerksick; Michael G Bemben; Joel T Cramer; Jeffrey R Stout
Journal:  Nutr Metab (Lond)       Date:  2008-03-19       Impact factor: 4.169

Review 10.  Body composition techniques.

Authors:  Rebecca Kuriyan
Journal:  Indian J Med Res       Date:  2018-11       Impact factor: 2.375

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.