Estimating physical activity and sedentary behavior in a free-living context: a pragmatic comparison of consumer-based activity trackers and ActiGraph accelerometry

Gomersall, Sjaan R., Ng, Norman, Burton, Nicola W., Pavey, Toby G., Gilson, Nicholas D. and Brown, Wendy J. (2016) Estimating physical activity and sedentary behavior in a free-living context: a pragmatic comparison of consumer-based activity trackers and ActiGraph accelerometry. Journal of Medical Internet Research, 18 9: e239.1-e239.12. doi:10.2196/jmir.5531


Author Gomersall, Sjaan R.
Ng, Norman
Burton, Nicola W.
Pavey, Toby G.
Gilson, Nicholas D.
Brown, Wendy J.
Title Estimating physical activity and sedentary behavior in a free-living context: a pragmatic comparison of consumer-based activity trackers and ActiGraph accelerometry
Journal name Journal of Medical Internet Research   Check publisher's open access policy
ISSN 1438-8871
1439-4456
Publication date 2016-09-07
Year available 2016
Sub-type Article (original research)
DOI 10.2196/jmir.5531
Open Access Status DOI
Volume 18
Issue 9
Start page e239.1
End page e239.12
Total pages 12
Place of publication Toronto, ON, Canada
Publisher J M I R Publications
Language eng
Abstract Activity trackers are increasingly popular with both consumers and researchers for monitoring activity and for promoting positive behavior change. However, there is a lack of research investigating the performance of these devices in free-living contexts, for which findings are likely to vary from studies conducted in well-controlled laboratory settings.
Formatted abstract
Background: Activity trackers are increasingly popular with both consumers and researchers for monitoring activity and for
promoting positive behavior change. However, there is a lack of research investigating the performance of these devices in
free-living contexts, for which findings are likely to vary from studies conducted in well-controlled laboratory settings.

Objective: The aim was to compare Fitbit One and Jawbone UP estimates of steps, moderate-to-vigorous physical activity
(MVPA), and sedentary behavior with data from the ActiGraph GT3X+ accelerometer in a free-living context.
Methods: Thirty-two participants were recruited using convenience sampling; 29 provided valid data for this study (female:
90%, 26/29; age: mean 39.6, SD 11.0 years). On two occasions for 7 days each, participants wore an ActiGraph GT3X+
accelerometer on their right hip and either a hip-worn Fitbit One (n=14) or wrist-worn Jawbone UP (n=15) activity tracker. Daily estimates of steps and very active minutes were derived from the Fitbit One (n=135 days) and steps, active time, and longest idle time from the Jawbone UP (n=154 days). Daily estimates of steps, MVPA, and longest sedentary bout were derived from the corresponding days of ActiGraph data. Correlation coefficients and Bland-Altman plots with examination of systematic bias were used to assess convergent validity and agreement between the devices and the ActiGraph. Cohen’s kappa was used to assess the agreement between each device and the ActiGraph for classification of active versus inactive (≥10,000 steps per day and ≥30 min/day of MVPA) comparable with public health guidelines.

Results: Correlations with ActiGraph estimates of steps and MVPA ranged between .72 and .90 for Fitbit One and .56 and .75
for Jawbone UP. Compared with ActiGraph estimates, both devices overestimated daily steps by 8% (Fitbit One) and 14%
(Jawbone UP). However, mean differences were larger for daily MVPA (Fitbit One: underestimated by 46%; Jawbone UP:
overestimated by 50%). There was systematic bias across all outcomes for both devices. Correlations with ActiGraph data for
longest idle time (Jawbone UP) ranged from .08 to .19. Agreement for classifying days as active or inactive using the ≥10,000 steps/day criterion was substantial (Fitbit One: κ=.68; Jawbone UP: κ=.52) and slight-fair using the criterion of ≥30 min/day of MVPA (Fitbit One: κ=.40; Jawbone UP: κ=.14).

Conclusions: There was moderate-strong agreement between the ActiGraph and both Fitbit One and Jawbone UP for the estimation of daily steps. However, due to modest accuracy and systematic bias, they are better suited for consumer based self-monitoring (eg, for the public consumer or in behavior change interventions) rather than to evaluate research outcomes. The outcomes that relate to health-enhancing MVPA (eg, “very active minutes” for Fitbit One or “active time” for Jawbone UP) and sedentary behavior (“idle time” for Jawbone UP) should be used with caution by consumers and researchers alike.
Keyword Activity tracker
Physical activity
Sedentary behavior
Accelerometry
Fitbit
Jawbone
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID 569940
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Human Movement and Nutrition Sciences Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 4 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 09 Sep 2016, 00:25:31 EST by Dr Norman Ng on behalf of School of Human Movement and Nutrition Sciences