Literature DB >> 22895373

Effects of filter choice in GT3X accelerometer assessments of free-living activity.

Miriam Wanner1, Brian W Martin, Flurina Meier, Nicole Probst-Hensch, Susi Kriemler.   

Abstract

PURPOSE: ActiGraph accelerometers are widely used devices to objectively assess physical activity. The GT3X version has two filter options to be selected before data assessment (normal and low-frequency extension filter option). It is not clear whether the resulting physical activity levels differ depending on the choice of the filter. The aims were to compare GT3X data collected using the different filter options during free-living activities and to establish correction factors if the results were not comparable.
METHODS: Sixty-five participants of the population-based SAPALDIA-cohort (50.8% women, age range = 40-80 yr) wore two GT3X accelerometers with different filter selections simultaneously during 8 d. Spearman correlations, Wilcoxon rank sum tests, McNemar tests, scatter plots, and Bland-Altman plots were used to compare the data. Correction factors were established using linear regression models.
RESULTS: Although Spearman correlations were high (r ≥ 0.93), there were significant differences in minutes per day between filter options for nonwearing time and time spent in sedentary, light, and moderate-to-vigorous physical activity (all P < 0.001), with more remarkable differences in the lower range of activity (sedentary and light activities). Mean counts per minute and steps per day were significantly higher using the low-frequency extension filter (P < 0.001). Most differences could be resolved using the correction factors.
CONCLUSIONS: The observed differences are especially important when research is focusing on sedentary and light activities. In future studies, it is important to carefully evaluate the suitable filter option and to specify the filter choice in publications. The correction factors can be used to make data assessed using the low-frequency extension filter comparable to data assessed using the normal filter option.

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Mesh:

Year:  2013        PMID: 22895373     DOI: 10.1249/MSS.0b013e31826c2cf1

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  18 in total

1.  Self-Selected Walking Speed is Predictive of Daily Ambulatory Activity in Older Adults.

Authors:  Addie Middleton; George D Fulk; Michael W Beets; Troy M Herter; Stacy L Fritz
Journal:  J Aging Phys Act       Date:  2015-09-15       Impact factor: 1.961

2.  Physical Activity Assessment with the ActiGraph GT3X and Doubly Labeled Water.

Authors:  Andrea K Chomistek; Changzheng Yuan; Charles E Matthews; Richard P Troiano; Heather R Bowles; Jennifer Rood; Junaidah B Barnett; Walter C Willett; Eric B Rimm; David R Bassett
Journal:  Med Sci Sports Exerc       Date:  2017-09       Impact factor: 5.411

3.  Associations of Sedentary Time with Energy Expenditure and Anthropometric Measures.

Authors:  Stephanie E Bonn; Eric B Rimm; Charles E Matthews; Richard P Troiano; Heather R Bowles; Jennifer Rood; Junaidah B Barnett; Walter C Willett; Andrea K Chomistek
Journal:  Med Sci Sports Exerc       Date:  2018-12       Impact factor: 5.411

Review 4.  Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis.

Authors:  E Gorman; H M Hanson; P H Yang; K M Khan; T Liu-Ambrose; M C Ashe
Journal:  Eur Rev Aging Phys Act       Date:  2013-09-17       Impact factor: 3.878

5.  Accelerometer data reduction in adolescents: effects on sample retention and bias.

Authors:  Mette Toftager; Peter Lund Kristensen; Melody Oliver; Scott Duncan; Lars Breum Christiansen; Eleanor Boyle; Jan Christian Brønd; Jens Troelsen
Journal:  Int J Behav Nutr Phys Act       Date:  2013-12-23       Impact factor: 6.457

6.  Active transportation and public transportation use to achieve physical activity recommendations? A combined GPS, accelerometer, and mobility survey study.

Authors:  Basile Chaix; Yan Kestens; Scott Duncan; Claire Merrien; Benoît Thierry; Bruno Pannier; Ruben Brondeel; Antoine Lewin; Noëlla Karusisi; Camille Perchoux; Frédérique Thomas; Julie Méline
Journal:  Int J Behav Nutr Phys Act       Date:  2014-09-27       Impact factor: 6.457

Review 7.  Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations.

Authors:  Jairo H Migueles; Cristina Cadenas-Sanchez; Ulf Ekelund; Christine Delisle Nyström; Jose Mora-Gonzalez; Marie Löf; Idoia Labayen; Jonatan R Ruiz; Francisco B Ortega
Journal:  Sports Med       Date:  2017-09       Impact factor: 11.136

8.  Comparison of older and newer generations of ActiGraph accelerometers with the normal filter and the low frequency extension.

Authors:  Kelli L Cain; Terry L Conway; Marc A Adams; Lisa E Husak; James F Sallis
Journal:  Int J Behav Nutr Phys Act       Date:  2013-04-25       Impact factor: 6.457

9.  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

10.  Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The Women's Health Initiative OPACH Calibration Study.

Authors:  Kelly R Evenson; Fang Wen; Amy H Herring; Chongzhi Di; Michael J LaMonte; Lesley Fels Tinker; I-Min Lee; Eileen Rillamas-Sun; Andrea Z LaCroix; David M Buchner
Journal:  Prev Med Rep       Date:  2015
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