Center for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain
Join us on March 2nd for an ActiGraph webinar:
Wearable Data Gone Awry: Cautionary Tales from the Clinical Research Trenches.Register Now
Comparison of Physical Activity Measures Using Mobile Phone-Based CalFit and Actigraph
- Published on June 13, 2013
Background Epidemiological studies on physical activity often lack inexpensive, objective, valid, and reproducible tools for measuring physical activity levels of participants. Novel sensing technologies built into smartphones offer the potential to fill this gap.
Objectives We sought to validate estimates of physical activity and determine the usability for large population-based studies of the smartphone-based CalFit software.
Methods A sample of 36 participants from Barcelona, Spain, wore a smartphone with CalFit software and an Actigraph GT3X accelerometer for 5 days. The ease of use (usability) and physical activity measures from both devices were compared, including vertical axis counts (VT) and duration and energy expenditure predictions for light, moderate, and vigorous intensity from Freedson’s algorithm. Statistical analyses included (1) Kruskal-Wallis rank sum test for usability measures, (2) Spearman correlation and linear regression for VT counts, (3) concordance correlation coefficient (CCC), and (4) Bland-Altman plots for duration and energy expenditure measures.
Results Approximately 64% (23/36) of participants were women. Mean age was 31 years (SD 8) and mean body mass index was 22 kg/m2 (SD 2). In total, 25/36 (69%) participants recorded at least 3 days with at least 10 recorded hours of physical activity using CalFit. The linear association and correlations for VT counts were high (adjusted R2=0.85; correlation coefficient .932, 95% CI 0.931-0.933). CCCs showed high agreement for duration and energy expenditure measures (from 0.83 to 0.91).
Conclusions The CalFit system had lower usability than the Actigraph GT3X because the application lacked a means to turn itself on each time the smartphone was powered on. The CalFit system may provide valid estimates to quantify and classify physical activity. CalFit may prove to be more cost-effective and easily deployed for large-scale population health studies than other specialized instruments because cell phones are already carried by many people.
- David Donaire-Gonzalez 1, 2, 3, 4
- Audrey de Nazelle 1, 2, 3, 5
- Edmund Seto 6
- Michelle Mendez 1, 2, 3, 7
- Mark J Nieuwenhuijsen 1, 2, 3
- Michael Jerrett 6
Hospital del Mar Research Institute (IMIM), Barcelona, Catalonia, Spain
Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Barcelona, Catalonia, Spain
Physical Activity and Sports Sciences Department, Fundació Blanquerna, Ramon Llull University, Barcelona, Catalonia, Spain
Center for Environmental Policy, Imperial College London, London, United Kingdom
Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, United State
Department of Nutrition, University of North Carolina, Chapel Hill, NC, United States
Journal of Medical Internet Research