Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players
Abstract Digital anthropometry by three-dimensional optical imaging systems and smartphones has recently been shown to provide non-invasive, precise, and accurate anthropometric and body composition measurements. To our knowledge, no previous study performed smartphone-based digital anthropometric a...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-48055-y |
| _version_ | 1797453319357071360 |
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| author | Marco A. Minetto Angelo Pietrobelli Andrea Ferraris Chiara Busso Massimo Magistrali Chiara Vignati Breck Sieglinger David Bruner John A. Shepherd Steven B. Heymsfield |
| author_facet | Marco A. Minetto Angelo Pietrobelli Andrea Ferraris Chiara Busso Massimo Magistrali Chiara Vignati Breck Sieglinger David Bruner John A. Shepherd Steven B. Heymsfield |
| author_sort | Marco A. Minetto |
| collection | DOAJ |
| description | Abstract Digital anthropometry by three-dimensional optical imaging systems and smartphones has recently been shown to provide non-invasive, precise, and accurate anthropometric and body composition measurements. To our knowledge, no previous study performed smartphone-based digital anthropometric assessments in young athletes. The aim of this study was to investigate the reproducibly and validity of smartphone-based estimation of anthropometric and body composition parameters in youth soccer players. A convenience sample of 124 male players and 69 female players (median ages of 16.2 and 15.5 years, respectively) was recruited. Measurements of body weight and height, one whole-body Dual-Energy X-ray Absorptiometry (DXA) scan, and acquisition of optical images (performed in duplicate by the Mobile Fit app to obtain two avatars for each player) were performed. The reproducibility analysis showed percent standard error of measurement values < 10% for all anthropometric and body composition measurements, thus indicating high agreement between the measurements obtained for the two avatars. Mobile Fit app overestimated the body fat percentage with respect to DXA (average overestimation of + 3.7% in males and + 4.6% in females), while it underestimated the total lean mass (− 2.6 kg in males and − 2.5 kg in females) and the appendicular lean mass (− 10.5 kg in males and − 5.5 kg in females). Using data of the soccer players, we reparameterized the equations previously proposed to estimate the body fat percentage and the appendicular lean mass and we obtained new equations that can be used in youth athletes for body composition assessment through conventional anthropometrics-based prediction models. |
| first_indexed | 2024-03-09T15:20:10Z |
| format | Article |
| id | doaj.art-11ed47c4cf7c40ca83efb70950aa24fd |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:20:10Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-11ed47c4cf7c40ca83efb70950aa24fd2023-11-26T12:48:56ZengNature PortfolioScientific Reports2045-23222023-11-0113111310.1038/s41598-023-48055-yEquations for smartphone prediction of adiposity and appendicular lean mass in youth soccer playersMarco A. Minetto0Angelo Pietrobelli1Andrea Ferraris2Chiara Busso3Massimo Magistrali4Chiara Vignati5Breck Sieglinger6David Bruner7John A. Shepherd8Steven B. Heymsfield9Division of Physical Medicine and Rehabilitation, Department of Surgical Sciences, University of TurinPennington Biomedical Research CentreDivision of Physical Medicine and Rehabilitation, Department of Surgical Sciences, University of TurinDivision of Physical Medicine and Rehabilitation, Department of Surgical Sciences, University of TurinJ|medicalJuventus Football ClubSize Stream LLCSize Stream LLCDepartment of Epidemiology, University of Hawaii Cancer CenterPennington Biomedical Research CentreAbstract Digital anthropometry by three-dimensional optical imaging systems and smartphones has recently been shown to provide non-invasive, precise, and accurate anthropometric and body composition measurements. To our knowledge, no previous study performed smartphone-based digital anthropometric assessments in young athletes. The aim of this study was to investigate the reproducibly and validity of smartphone-based estimation of anthropometric and body composition parameters in youth soccer players. A convenience sample of 124 male players and 69 female players (median ages of 16.2 and 15.5 years, respectively) was recruited. Measurements of body weight and height, one whole-body Dual-Energy X-ray Absorptiometry (DXA) scan, and acquisition of optical images (performed in duplicate by the Mobile Fit app to obtain two avatars for each player) were performed. The reproducibility analysis showed percent standard error of measurement values < 10% for all anthropometric and body composition measurements, thus indicating high agreement between the measurements obtained for the two avatars. Mobile Fit app overestimated the body fat percentage with respect to DXA (average overestimation of + 3.7% in males and + 4.6% in females), while it underestimated the total lean mass (− 2.6 kg in males and − 2.5 kg in females) and the appendicular lean mass (− 10.5 kg in males and − 5.5 kg in females). Using data of the soccer players, we reparameterized the equations previously proposed to estimate the body fat percentage and the appendicular lean mass and we obtained new equations that can be used in youth athletes for body composition assessment through conventional anthropometrics-based prediction models.https://doi.org/10.1038/s41598-023-48055-y |
| spellingShingle | Marco A. Minetto Angelo Pietrobelli Andrea Ferraris Chiara Busso Massimo Magistrali Chiara Vignati Breck Sieglinger David Bruner John A. Shepherd Steven B. Heymsfield Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players Scientific Reports |
| title | Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players |
| title_full | Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players |
| title_fullStr | Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players |
| title_full_unstemmed | Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players |
| title_short | Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players |
| title_sort | equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players |
| url | https://doi.org/10.1038/s41598-023-48055-y |
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