Comparison of wrist-worn Fitbit Flex and waist-worn ActiGraph for measuring steps in free-living adults

Abstract

IntroductionAccelerometers are commonly used to assess physical activity. Consumer activity trackers have become increasingly popular today, such as the Fitbit. This study aimed to compare the average number of steps per day using the wrist-worn Fitbit Flex and waist-worn ActiGraph (wGT3X-BT) in free-living conditions.Methods104 adult participants (n = 35 males; n = 69 females) were asked to wear a Fitbit Flex and an ActiGraph concurrently for 7 days. Daily step counts were used to classify inactive (<10,000 steps) and active (≥10,000 steps) days, which is one of the commonly used physical activity guidelines to maintain health. Proportion of agreement between physical activity categorizations from ActiGraph and Fitbit Flex was assessed. Statistical analyses included Spearman’s rho, intraclass correlation (ICC), median absolute percentage error (MAPE), Kappa statistics, and Bland-Altman plots. Analyses were performed among all participants, by each step-defined daily physical activity category and gender.ResultsThe median average steps/day recorded by Fitbit Flex and ActiGraph were 10193 and 8812, respectively. Strong positive correlations and agreement were found for all participants, both genders, as well as daily physical activity categories (Spearman's rho: 0.76–0.91; ICC: 0.73–0.87). The MAPE was: 15.5% (95% confidence interval [CI]: 5.8–28.1%) for overall steps, 16.9% (6.8–30.3%) vs. 15.1% (4.5–27.3%) in males and females, and 20.4% (8.7–35.9%) vs. 9.6% (1.0–18.4%) during inactive days and active days. Bland-Altman plot indicated a median overestimation of 1300 steps/day by the Fitbit Flex in all participants. Fitbit Flex and ActiGraph respectively classified 51.5% and 37.5% of the days as active (Kappa: 0.66).ConclusionsThere were high correlations and agreement in steps between Fitbit Flex and ActiGraph. However, findings suggested discrepancies in steps between devices. This imposed a challenge that needs to be considered when using Fibit Flex in research and health promotion programs.

A Comparison of Activity Monitor Data from Devices Worn on the Wrist and the Waist in People with Parkinson's Disease

“…We found that the monitor worn on the wrist detected a higher number of steps and activity counts as well as more percentage of time in physical activity and more percentage of time walking at moderate speed (1.05–1.3 m/s) when compared with the monitor worn on the waist. Similar results have been found in adults in the general population, where higher step counts have been reported from devices worn on the wrist when compared with the waist . Notably, studies with younger adults have reported smaller differences in the step count (median age 31 years, step difference 1381/median age 27 years, step difference 2558) when compared with the present study (mean age 68 years, step difference 3912) and a study conducted with older participants (mean age 72 years, step difference 4729).…”

“…Similar results have been found in adults in the general population, where higher step counts have been reported from devices worn on the wrist when compared with the waist . Notably, studies with younger adults have reported smaller differences in the step count (median age 31 years, step difference 1381/median age 27 years, step difference 2558) when compared with the present study (mean age 68 years, step difference 3912) and a study conducted with older participants (mean age 72 years, step difference 4729). The reason for this increase in difference in older people is unclear and may be the result of age‐related factors, including increased sedentary time producing more activity at the wrist compared with the waist.…”

Comparison of Physical Activity Measures Derived From the Fitbit Flex and the ActiGraph GT3X+ in an Employee Population With Chronic Knee Symptoms

“…One potential confounder includes the wrist versus waist location of the monitoring devices during data collection, although this arrangement is consistent with that of similar studies that compared data from these devices (2)(3)(4)10,(13)(14)(15)(16). The study could not control for wear time of the consumer devices, and this might have impacted results.…”

How Sensors Might Help Define the External Exposome

“…Fitbit, for example, an extremely popular fitness tracker, has been found to have low percent error compared with reference methods for energy expenditure estimation and step counting in some studies [39,45,46,47], but could be more biased in others [40]. …”