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Considerations in Processing Accelerometry Data to Explore Physical Activity and Sedentary Time in Older Adults.

Claire L Cleland, Sara Ferguson, Paul McCrorie

    Journal of Aging and Physical Activity
    |January 23, 2020
    PubMed
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    Processing accelerometry data affects physical activity and sedentary time in older adults. Different processing choices significantly alter results, impacting research comparisons and surveillance accuracy.

    Area of Science:

    • Gerontology
    • Biomedical Engineering
    • Physical Activity Epidemiology

    Background:

    • Accelerometry is crucial for measuring physical activity and sedentary behavior in older adults.
    • Data processing choices can significantly influence outcome measures.
    • Limited evidence exists on these impacts specifically within the older adult population.

    Purpose of the Study:

    • To investigate the impact of key data processing criteria on physical activity and sedentary time measurements in older adults.
    • To compare the effects of different low-frequency extension, nonwear time, and intensity cut-point settings.

    Main Methods:

    • Participants (n=222, mean age 71.75 years) wore ActiGraph GT3X+ accelerometers for 7 days.
    • Eight data processing combinations were analyzed, varying low-frequency extension (on/off), nonwear time (90/120 min), and intensity cut points (≥1,041 vs. >2,000 counts/min).
    Keywords:
    accelerometer processinglight physical activitymethodologymoderate-to-vigorous physical activitysedentary behavior

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  • Statistical analyses included Wilcoxon signed-rank test, paired t tests, and correlation coefficients.

    • Main Results:

    • Activating low-frequency extension with 90-minute nonwear time and a cut point of >1,041 counts/min significantly increased light and moderate-to-vigorous physical activity.
    • This combination also resulted in significantly lower sedentary time.
    • Intensity cut points demonstrated the most substantial impact on physical activity and sedentary time outcomes.

    Conclusions:

    • Accelerometry data processing criteria significantly influence physical activity and sedentary time metrics in older adults.
    • Inconsistent processing can lead to data inaccuracies and hinder cross-study comparability.
    • Standardizing processing methods is essential for accurate population surveillance and research in this demographic.