Comparison of physical behavior estimates from three different thigh-worn accelerometers brands: A proof-of-concept for the Prospective Physical Activity, Sitting, and Sleep consortium (ProPASS)
Crowley, Patrick; Skotte, Jørgen; Stamatakis, Emmanuel; Hamer, Mark; Aadahl, Mette; Stevens, Matthew L.; Rangul, Vegar; Mork, Paul Jarle; Holtermann, Andreas
Journal article, Peer reviewed
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Date
2019Metadata
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Original version
International Journal of Behavioral Nutrition and Physical Activity. 2019, 16:65 1-7. 10.1186/s12966-019-0835-0Abstract
Background: Pooling data from thigh-worn accelerometers across multiple studies has great potential to advance evidence on the health benefits of physical activity. This requires harmonization of information on body postures, physical activity types, volumes and time patterns across different brands of devices. The aim of this study is to compare the physical behavior estimates provided by three different brands of thigh-worn accelerometers. Methods: Twenty participants volunteered for a 7-day free-living measurement. Three accelerometers - ActiGraphGT3X+, Axivity AX3 and ActivPAL Micro4 - were randomly placed in a vertical line on the midsection of the right thigh. Raw data from each accelerometer was processed and classified into 8 physical activities and postures using the Acti4 software. Absolute differences between estimates and the respective coefficient of variation (CV) were calculated. Results: We observed very minor differences between physical behavior estimates from three different accelerometer brands. When averaged over 24 h (1,440 min), the absolute difference (CV) between accelerometers were: 1.2 mins(0.001) for lying/sitting, 3.4 mins (0.02) for standing, 3.5 mins (0.06) for moving, 1.9 mins (0.03) for walking, 0.1 mins(0.19) for running, 1.2 mins (0.19) for stair climbing, 1.9 mins (0.07) for cycling. Moreover, there was an average absolute difference of 282 steps (0.03) per 24 h. Conclusions: Physical behaviors were classified with negligible difference between the accelerometer brands. These results support harmonization of data from different thigh-worn accelerometers across multiple cohorts when analyzed in an identical manner. Keywords: Harmonization, Data pooling, Objective measurement, Tri-axial, Accelerometry, Health, Validation, Posture