Literature DB >> 31968305

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

Claire L Cleland, Sara Ferguson, Paul McCrorie, Jasper Schipperijn, Geraint Ellis, Ruth F Hunter.   

Abstract

Processing decisions for accelerometry data can have important implications for outcome measures, yet little evidence exists exploring these in older adults. The aim of the current study was to investigate the impact of three potentially important criteria on older adults, physical activity, and sedentary time. Participants (n = 222: mean age 71.75 years [SD = 6.58], 57% male) wore ActiGraph GT3X+ for 7 days. Eight data processing combinations from three criteria were explored: low-frequency extension (on/off), nonwear time (90/120 min), and intensity cut points (moderate-to-vigorous physical activity ≥1,041 and >2,000 counts/min). Analyses included Wilcoxon signed-rank test, paired t tests, and correlation coefficients (significance, p < .05). Results for low-frequency extension on 90-min nonwear time and >1,041 counts/min showed significantly higher light and moderate-to-vigorous physical activity and lower sedentary time. Cut points had the greatest impact on physical activity and sedentary time. Processing criteria can significantly impact physical activity and/or sedentary time, potentially leading to data inaccuracies, preventing cross-study comparisons and influencing the accuracy of population surveillance.

Entities:  

Keywords:  accelerometer processing; light physical activity; methodology; moderate-to-vigorous physical activity; sedentary behavior

Year:  2020        PMID: 31968305     DOI: 10.1123/japa.2019-0244

Source DB:  PubMed          Journal:  J Aging Phys Act        ISSN: 1063-8652            Impact factor:   2.109


  3 in total

1.  Measuring sedentary behavior using waist- and thigh-worn accelerometers and inclinometers - are the results comparable?

Authors:  Tobias Kalisch; Christoph Theil; Georg Gosheger; Thomas Ackmann; Isabell Schoenhals; Burkhard Moellenbeck
Journal:  Ther Adv Musculoskelet Dis       Date:  2022-03-15       Impact factor: 5.346

2.  A Comparative Study on the Influence of Undersampling and Oversampling Techniques for the Classification of Physical Activities Using an Imbalanced Accelerometer Dataset.

Authors:  Dong-Hwa Jeong; Se-Eun Kim; Woo-Hyeok Choi; Seong-Ho Ahn
Journal:  Healthcare (Basel)       Date:  2022-07-05

3.  Comparative assessment of ActiGraph data processing techniques for measuring sedentary behavior in adults with COPD.

Authors:  Katelyn E Webster; Natalie Colabianchi; Robert Ploutz-Snyder; Neha Gothe; Ellen Lavoie Smith; Janet L Larson
Journal:  Physiol Meas       Date:  2021-08-27       Impact factor: 2.688

  3 in total

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