<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Study aim: The measurement of body composition is important from a population perspective as it is a variable associated with a person’s health, and also from a sporting perspective as it can be used to evaluate training. This study aimed to examine the reliability of a mobile application that estimates body composition by digitising a two-dimensional image. Materials and methods: Thirty participants (15 men and 15 women) volunteered to have their percentage body fat (%BF) estimated via three different methods (skinfold measurements, SFM; bio-electrical impedance, BIA; LeanScreenTM mobile application, LSA). Intra-method reproducibility was assessed using intra-class correlation coefficients (ICC), coefficient of variance (CV) and typical error of measurement (TEM). The average measurement for each method were also compared. Results: There were no significant differences between the methods for estimated %BF (p = 0.818) and the reliability of each method as assessed via ICC was good (≥0.974). However the absolute reproducibility, as measured by CV and TEM, was much higher in SFM and BIA (≤1.07 and ≤0.37 respectively) compared with LSA (CV 6.47, TEM 1.6). Conclusion: LSA may offer an alternative to other field-based measures for practitioners, however individual variance should be considered to develop an understanding of minimal worthwhile change, as it may not be suitable for a one-off measurement.</p></abstract>

Study aim: The measurement of body composition is important from a population perspective as it is a variable associated with a person’s health, and also from a sporting perspective as it can be used to evaluate training. This study aimed to examine the reliability of a mobile application that estimates body composition by digitising a two-dimensional image. Materials and methods: Thirty participants (15 men and 15 women) volunteered to have their percentage body fat (%BF) estimated via three different methods (skinfold measurements, SFM; bio-electrical impedance, BIA; LeanScreenTM mobile application, LSA). Intra-method reproducibility was assessed using intra-class correlation coefficients (ICC), coefficient of variance (CV) and typical error of measurement (TEM). The average measurement for each method were also compared. Results: There were no significant differences between the methods for estimated %BF (p = 0.818) and the reliability of each method as assessed via ICC was good (≥0.974). However the absolute reproducibility, as measured by CV and TEM, was much higher in SFM and BIA (≤1.07 and ≤0.37 respectively) compared with LSA (CV 6.47, TEM 1.6). Conclusion: LSA may offer an alternative to other field-based measures for practitioners, however individual variance should be considered to develop an understanding of minimal worthwhile change, as it may not be suitable for a one-off measurement.

Comparison of a mobile application to estimate percentage body fat to other non-laboratory based measurements

Biomedical Human Kinetics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Study aim: The measurement of body composition is important from a population perspective as it is a variable associated with a person’s health, and also from...

Comparison of a mobile application to estimate percentage body fat to other non-laboratory based measurements

Publicado en línea: 19 jul 2017

Páginas: 94 - 98

Recibido: 02 mar 2017

Aceptado: 07 jun 2017

DOI: https://doi.org/10.1515/bhk-2017-0014

Palabras clave
Mobile technology - Field testing - Body composition - Reproducibility

© Matthew P. Shaw, Joshua Robinson, Daniel J. Peart

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Comparison of a mobile application to estimate percentage body fat to other non-laboratory based measurements

Publicado en línea: 19 jul 2017

Páginas: 94 - 98

Recibido: 02 mar 2017

Aceptado: 07 jun 2017

DOI: https://doi.org/10.1515/bhk-2017-0014

Palabras claveMobile technology - Field testing - Body composition - Reproducibility

© Matthew P. Shaw, Joshua Robinson, Daniel J. Peart

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Palabras clave
Mobile technology - Field testing - Body composition - Reproducibility