Header

UZH-Logo

Maintenance Infos

Associations between relative body fat and areal body surface roughness characteristics in 3D photonic body scans-a proof of feasibility


Ritter, Severin; Staub, Kaspar; Eppenberger, Patrick (2021). Associations between relative body fat and areal body surface roughness characteristics in 3D photonic body scans-a proof of feasibility. International Journal of Obesity, 45(4):906-913.

Abstract

INTRODUCTION

A reliable and accurate estimate of the percentage and distribution of adipose tissue in the human body is essential for evaluating the risk of developing chronic and noncommunicable diseases. A precise and differentiated method, which at the same time is fast, noninvasive, and straightforward to perform, would, therefore, be desirable. We sought a new approach to this research area by linking a person's relative body fat with their body surface's areal roughness characteristics.

MATERIALS AND METHODS

For this feasibility study, we compared areal surface roughness characteristics, assessed from 3D photonic full-body scans of 76 Swiss young men, and compared the results with body impedance-based estimates of relative body fat. We developed an innovative method for characterizing the areal surface roughness distribution of a person's entire body, in a similar approach as it is currently used in geoscience or material science applications. We then performed a statistical analysis using different linear and stepwise regression models.

RESULTS

In a stepwise regression analysis of areal surface roughness frequency tables, a combination of standard deviation, interquartile range, and mode showed the best association with relative body fat (R$^{2}$ = 0.55, p < 0.0001). The best results were achieved by calculating the arithmetic mean height, capable of explaining up to three-quarters of the variance in relative body fat (R$^{2}$ = 0.74, p < 0.001).

DISCUSSION AND CONCLUSION

This study shows that areal surface roughness characteristics assessed from 3D photonic whole-body scans associate well with relative body fat, therefore representing a viable new approach to improve current 3D scanner-based methods for determining body composition and obesity-associated health risks. Further investigations may validate our method with other data or provide a more detailed understanding of the relation between the body's areal surface characteristics and adipose tissue distribution by including larger and more diverse populations or focusing on particular body segments.

Abstract

INTRODUCTION

A reliable and accurate estimate of the percentage and distribution of adipose tissue in the human body is essential for evaluating the risk of developing chronic and noncommunicable diseases. A precise and differentiated method, which at the same time is fast, noninvasive, and straightforward to perform, would, therefore, be desirable. We sought a new approach to this research area by linking a person's relative body fat with their body surface's areal roughness characteristics.

MATERIALS AND METHODS

For this feasibility study, we compared areal surface roughness characteristics, assessed from 3D photonic full-body scans of 76 Swiss young men, and compared the results with body impedance-based estimates of relative body fat. We developed an innovative method for characterizing the areal surface roughness distribution of a person's entire body, in a similar approach as it is currently used in geoscience or material science applications. We then performed a statistical analysis using different linear and stepwise regression models.

RESULTS

In a stepwise regression analysis of areal surface roughness frequency tables, a combination of standard deviation, interquartile range, and mode showed the best association with relative body fat (R$^{2}$ = 0.55, p < 0.0001). The best results were achieved by calculating the arithmetic mean height, capable of explaining up to three-quarters of the variance in relative body fat (R$^{2}$ = 0.74, p < 0.001).

DISCUSSION AND CONCLUSION

This study shows that areal surface roughness characteristics assessed from 3D photonic whole-body scans associate well with relative body fat, therefore representing a viable new approach to improve current 3D scanner-based methods for determining body composition and obesity-associated health risks. Further investigations may validate our method with other data or provide a more detailed understanding of the relation between the body's areal surface characteristics and adipose tissue distribution by including larger and more diverse populations or focusing on particular body segments.

Statistics

Citations

Altmetrics

Downloads

10 downloads since deposited on 19 Feb 2021
10 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Evolutionary Medicine
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:1 April 2021
Deposited On:19 Feb 2021 16:14
Last Modified:01 May 2021 21:07
Publisher:Nature Publishing Group
ISSN:0307-0565
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/s41366-021-00758-w
PubMed ID:33589772

Download

Hybrid Open Access

Download PDF  'Associations between relative body fat and areal body surface roughness characteristics in 3D photonic body scans-a proof of feasibility'.
Preview
Content: Published Version
Filetype: PDF
Size: 1MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)