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    Capturing the pattern of physical activity and sedentary behavior: exposure variation analysis of accelerometer data

    199485_122229_Capturing_the_pattern_of_physical_activity.pdf (366.4Kb)
    Access Status
    Open access
    Authors
    Straker, Leon
    Campbell, Amity
    Mathiassen, S.
    Abbott, R.
    Parry, Sharon
    Davey, Paul
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Straker, L. and Campbell, A. and Mathiassen, S. and Abbott, R. and Parry, S. and Davey, P. 2014. Capturing the pattern of physical activity and sedentary behavior: exposure variation analysis of accelerometer data. Journal of Physical Activity and Health. 11 (3): pp. 614-625.
    Source Title
    Journal of Physical Activity and Health
    DOI
    10.1123/jpah.2012-0105
    ISSN
    1543-3080
    URI
    http://hdl.handle.net/20.500.11937/17556
    Collection
    • Curtin Research Publications
    Abstract

    Background: Capturing the complex time pattern of physical activity (PA) and sedentary behavior (SB) using accelerometry remains a challenge. Research from occupational health suggests exposure variation analysis (EVA) could provide a meaningful tool. This paper (1) explains the application of EVA to accelerometer data, (2) demonstrates how EVA thresholds and derivatives could be chosen and used to examine adherence to PA and SB guidelines, and (3) explores the validity of EVA outputs. Methods: EVA outputs are compared with accelerometer data from 4 individuals (Study 1a and1b) and 3 occupational groups (Study 2): seated workstation office workers (n = 8), standing workstation office workers (n = 8), and teachers (n = 8). Results: Line graphs and related EVA graphs highlight the use of EVA derivatives for examining compliance with guidelines. EVA derivatives of occupational groups confirm no difference in bouts of activity but clear differences as expected in extended bouts of SB and brief bursts of activity, thus providing evidence of construct validity. Conclusions: EVA offers a unique and comprehensive generic method that is able, for the first time, to capture the time pattern (both frequency and intensity) of PA and SB, which can be tailored for both occupational and public health research.

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