Literature DB >> 22936409

Impact of accelerometer wear time on physical activity data: a NHANES semisimulation data approach.

Stephen D Herrmann1, Tiago V Barreira, Minsoo Kang, Barbara E Ainsworth.   

Abstract

BACKGROUND: Current research practice employs wide-ranging accelerometer wear time criteria to identify a valid day of physical activity (PA) measurement.
OBJECTIVE: To evaluate the effects of varying amounts of daily accelerometer wear time on PA data.
METHODS: A total of 1000 days of accelerometer data from 1000 participants (age=38.7 ± 14.3 years; body mass index=28.2 ± 6.7 kg/m(2)) were selected from the 2005-2006 National Health and Nutrition Examination Study data set. A reference data set was created using 200 random days with 14 h/day of wear time. Four additional samples of 200 days were randomly selected with a wear time of 10, 11, 12 and 13 h/day(1). These data sets were used in day-to-day comparison to create four semisimulation data sets (10, 11, 12, 13 h/day) from the reference data set. Differences in step count and time spent in inactivity (<100 cts/min), light (100-1951 cts/min), moderate (1952-5724 cts/min) and vigorous (≥5725 cts/min) intensity PA were assessed using repeated-measures analysis of variance and absolute percent error (APE).
RESULTS: There were significant differences for moderate intensity PA between the reference data set and semisimulation data sets of 10 and 11 h/day. Differences were observed in 10-13 h/day(1) for inactivity and light intensity PA, and 10-12 h/day for steps (all p values <0.05). APE increased with shorter wear time (13 h/day=3.9-14.1%; 12 h/day=9.9-15.2%, 11 h/day=17.1-35.5%; 10 h/day=24.6-40.3%). DISCUSSION: These data suggest that using accelerometer wear time criteria of 12 h/day or less may underestimate step count and time spent in various PA levels.

Entities:  

Keywords:  Measurement; Physical activity and exercise methodology; Physical activity measurement

Mesh:

Year:  2012        PMID: 22936409     DOI: 10.1136/bjsports-2012-091410

Source DB:  PubMed          Journal:  Br J Sports Med        ISSN: 0306-3674            Impact factor:   13.800


  42 in total

1.  Analysis and Interpretation of Accelerometry Data in Older Adults: The LIFE Study.

Authors:  W Jack Rejeski; Anthony P Marsh; Peter H Brubaker; Matthew Buman; Roger A Fielding; Don Hire; Todd Manini; Alvito Rego; Michael E Miller
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2015-10-29       Impact factor: 6.053

2.  Total energy expenditure in patients with colorectal cancer: associations with body composition, physical activity, and energy recommendations.

Authors:  Sarah A Purcell; Sarah A Elliott; Peter J Walter; Tom Preston; Hongyi Cai; Richard J E Skipworth; Michael B Sawyer; Carla M Prado
Journal:  Am J Clin Nutr       Date:  2019-08-01       Impact factor: 7.045

3.  Neighborhood Recreation Facilities and Facility Membership Are Jointly Associated with Objectively Measured Physical Activity.

Authors:  Tanya K Kaufman; Andrew Rundle; Kathryn M Neckerman; Daniel M Sheehan; Gina S Lovasi; Jana A Hirsch
Journal:  J Urban Health       Date:  2019-08       Impact factor: 3.671

4.  Reproducibility of Accelerometer-Assessed Physical Activity and Sedentary Time.

Authors:  Sarah Kozey Keadle; Eric J Shiroma; Masamitsu Kamada; Charles E Matthews; Tamara B Harris; I-Min Lee
Journal:  Am J Prev Med       Date:  2017-01-03       Impact factor: 5.043

Review 5.  Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review.

Authors:  S Jeran; A Steinbrecher; T Pischon
Journal:  Int J Obes (Lond)       Date:  2016-02-02       Impact factor: 5.095

6.  A comparison of total and domain-specific sedentary time in breast cancer survivors and age-matched healthy controls.

Authors:  Allyson Tabaczynski; Alexis Whitehorn; Edward McAuley; Linda Trinh
Journal:  J Behav Med       Date:  2020-11-13

7.  Sedentary behavior and blood pressure control among osteoarthritis initiative participants.

Authors:  M-W Sohn; L M Manheim; R W Chang; P Greenland; M C Hochberg; M C Nevitt; P A Semanik; D D Dunlop
Journal:  Osteoarthritis Cartilage       Date:  2014-07-18       Impact factor: 6.576

8.  Step-Based Physical Activity Metrics and Cardiometabolic Risk: NHANES 2005-2006.

Authors:  Catrine Tudor-Locke; John M Schuna; H O Han; Elroy J Aguiar; Michael A Green; Michael A Busa; Sandra Larrivee; William D Johnson
Journal:  Med Sci Sports Exerc       Date:  2017-02       Impact factor: 5.411

9.  Ankle Accelerometry for Assessing Physical Activity Among Adolescent Girls: Threshold Determination, Validity, Reliability, and Feasibility.

Authors:  Erin R Hager; Margarita S Treuth; Candice Gormely; LaShawna Epps; Soren Snitker; Maureen M Black
Journal:  Res Q Exerc Sport       Date:  2015-08-19       Impact factor: 2.500

10.  Association between Objectively Measured Physical Activity and Mortality in NHANES.

Authors:  Ezra I Fishman; Jeremy A Steeves; Vadim Zipunnikov; Annemarie Koster; David Berrigan; Tamara A Harris; Rachel Murphy
Journal:  Med Sci Sports Exerc       Date:  2016-07       Impact factor: 5.411

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