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Comparing digital anthropometrics from mobile applications to reference methods: a scoping review.

Irismar Gonçalves Almeida da Encarnação1,2, Matheus Santos Cerqueira3, Paulo Henrique Ribeiro Fernandes Almeida4

  • 1Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Brazil. irismar.encarnacao@ufv.br.

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Summary
This summary is machine-generated.

Digital anthropometry by mobile applications (DAM) shows good average accuracy for body measurements but is less reliable for individual assessments or tracking changes. Caution is advised for precise individual body composition analysis.

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Area of Science:

  • Biomedical Engineering
  • Human Physiology
  • Health Informatics

Background:

  • Digital anthropometry by mobile applications (DAM) is emerging for body measurements.
  • Reference methods like tape measures, scales, and DXA are established standards.
  • Assessing DAM's accuracy against these standards is crucial for reliable health data.

Purpose of the Study:

  • To evaluate the repeatability and accuracy of Digital Anthropometry by Mobile Applications (DAM).
  • To compare DAM estimations of body dimensions, volume, and composition against established reference methods.
  • To identify the strengths and limitations of DAM in anthropometric assessments.

Main Methods:

  • Conducted a scoping review of 23 studies, analyzing 14 different DAMs.
  • Compared DAMs against reference methods: tape measure, calibrated scale, stadiometer, Underwater Weighing (UWW), DXA, BOD POD, and multi-compartment models.
  • Focused on anthropometric dimensions, body volume (BV), and body composition (body fat percentage, fat mass, fat-free mass, appendicular lean mass).

Main Results:

  • DAMs demonstrated high repeatability and mean-level accuracy across most studies.
  • Accuracy decreased significantly at the individual analysis level and for tracking changes over time.
  • Estimated body volume (BV) showed high accuracy compared to UWW (SEE=0.68).
  • BV-derived DAMs integrated into multi-compartment models also showed good accuracy.

Conclusions:

  • DAMs offer promising potential for anthropometric assessment, especially for average measurements.
  • Current DAM accuracy is insufficient for precise individual-level body composition analysis or longitudinal tracking.
  • Further research and validation are needed to improve DAM accuracy and reliability for clinical and research applications.