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Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Estimating physical activity from incomplete accelerometer data in field studies
Sofiya Alhassan1, John R Sirard, Tirzah R Spencer
1Dept of Kinesiology, University of Massachusetts, Amherts, MA 01003-0258, USA.
Background:
The purpose of this study was to develop a data-driven approach for analyzing incomplete accelerometer data from field-base studies.
Methods:
Multiple days of accelerometer data from the Stanford Girls health Enrichment Multi-site Studies (N = 294 African American girls) were summed across each minute of each day to produce a composite weekday and weekend day. Composite method estimates of physical activity were compared with those derived from methods typically described in the literature (comparison methods).
Results:
The composite method retained 99.7% and 100% of participants in weekday and weekend-day analysis, respectively, versus 84.7% to 94.2% and 28.6% to 99.0% for the comparison methods. Average wearing times for the composite method for weekday and weekend day were 99.6% and 98.6%, respectively, 91.7% to 93.9% and 82.3% to 95.4% for the comparison methods. Composite-method physical activity estimates were similar to comparison-methods estimates.
Conclusion:
The composite method used more available accelerometer data than standard approaches, reducing the need to exclude periods within a day, entire days, and participants from analysis.
