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. 2019 Oct 11;1(9):585-592.
doi: 10.1002/acr2.11080. eCollection 2019 Nov.

Validating Fitbit for Evaluation of Physical Activity in Patients with Knee Osteoarthritis: Do Thresholds Matter?

Genevieve S Silva  1 , Heidi Yang  1 , Jamie E Collins  2 , Elena Losina  2
Affiliations

Validating Fitbit for Evaluation of Physical Activity in Patients with Knee Osteoarthritis: Do Thresholds Matter?

Genevieve S Silva et al. ACR Open Rheumatol. .

Abstract

Objective: We sought to evaluate the performance of Fitbit in estimating ActiGraph-derived moderate-to-vigorous physical activity (MVPA) and sedentary time in the knee osteoarthritis (OA) population.

Methods: We used data from two weeks of Fitbit and ActiGraph wear among knee OA subjects. In primary analyses, we used literature-based ActiGraph thresholds of 200 and 1924 counts/min (triaxial vector magnitude) for sedentary and MVPA time as the gold standard to which we compared three sets of Fitbit thresholds informed by literature and data (Youden index). We also considered personalized, stride length-based Fitbit thresholds. In sensitivity analyses, we used uniaxial, vertical axis-based as well as personalized, BMI-based ActiGraph thresholds. We calculated agreement, sensitivity, and specificity of Fitbit in classifying sedentary and MVPA time.

Results: In the primary analysis (vector magnitude thresholds), maximum agreement for sedentary and MVPA time was 67.0% from the Youden index-based and 91.1% from the stride length-based Fitbit thresholds. For sedentary time, the 20 strides/min threshold had the highest sensitivity (97.6%), and Youden-derived 1 stride/min had the highest specificity (51.6%). For MVPA, Youden-derived 14 strides/min yielded 72.8% sensitivity, and using stride length yielded 98.6% specificity. MVPA time ranged from 49-323 min/d, depending on threshold used, with literature-based and personalized thresholds leading to more conservative estimates of MVPA than Youden-derived thresholds.

Conclusion: Using Fitbit for MVPA and sedentary time assessment may lead to inaccurate estimates of both. Fitbit MVPA estimates were generally more conservative than ActiGraph estimates. Incorporating individuals' characteristics did not meaningfully improve Fitbit performance. Caution should be exercised when measuring activity using Fitbit.

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Figures

Figure 1
Figure 1
Distribution of Fitbit strides and triaxial ActiGraph counts per minute. The scatterplot describes triaxial ActiGraph counts/minute on the y‐axis and Fitbit strides/min on the x‐axis. We divide the plot into four quadrants using literature‐based MVPA thresholds for each device (67 strides/min and 1924 counts/min) to visualize the distribution of minutes based on these classifications of MVPA versus non‐MVPA. Quadrants 2 (Q2) and 3 (Q3) represent agreement between the two devices in classifying time in MVPA (Q2) and non‐MVPA (light physical activity and sedentary) (Q3).
Figure 2
Figure 2
Distribution of the average daily minutes in MVPA, by Fitbit and triaxial ActiGraph threshold scenario. The boxplot represents the distribution of the average minutes per day classified as time in MVPA under the Fitbit and triaxial ActiGraph threshold scenarios. The circle within each rectangle represents the mean of this distribution, and the midline of each rectangle represents the median of this distribution. The top and the bottom of each rectangle correspond to the 75th and 25th quartiles, respectively. Each rectangle of the boxplot represents a device and threshold for MVPA time used. We considered four Fitbit stride/min thresholds, along with a stride‐length based threshold, and two triaxial (vector magnitude) and uniaxial (vertical axis) ActiGraph count/min thresholds for the lower bound of MVPA. Fitbit‐based thresholds are represented by a purple color scheme, and ActiGraph‐based thresholds are represented by a blue color scheme.
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