Literature DB >> 26515258

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

W Jack Rejeski1, Anthony P Marsh2, Peter H Brubaker2, Matthew Buman3, Roger A Fielding4, Don Hire5, Todd Manini6, Alvito Rego7, Michael E Miller5.   

Abstract

BACKGROUND: Accelerometry has become the gold standard for evaluating physical activity in the health sciences. An important feature of using this technology is the cutpoint for determining moderate to vigorous physical activity (MVPA) because this is a key component of exercise prescription. This article focused on evaluating what cutpoint is appropriate for use with older adults 70-89 years who are physically compromised.
METHODS: The analyses are based on data collected from the Lifestyle Interventions and Independence for Elders (LIFE) study. Accelerometry data were collected during a 40-minute, overground, walking exercise session in a subset of participants at four sites; we also used 1-week baseline and 6-month accelerometry data collected in the main trial.
RESULTS: There was extreme variability in median counts per minute (CPM) achieved during a controlled bout of exercise (n = 140; median = 1,220 CPM (25th, 75th percentile = 715, 1,930 CPM). An equation combining age, age(2), and 400 m gait speed explained 61% of the variance in CPM achieved during this session. When applied to the LIFE accelerometry data (n = 1,448), the use of an individually tailored cutpoint based on this equation resulted in markedly different patterns of MVPA as compared with using standard fixed cutpoints.
CONCLUSIONS: The findings of this study have important implications for the use and interpretations of accelerometry data and in the design/delivery of physical activity interventions with older adults.
© The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Accelerometry; Cutpoints; LIFE-study; Mobility disability; Older adults

Mesh:

Year:  2015        PMID: 26515258      PMCID: PMC5175451          DOI: 10.1093/gerona/glv204

Source DB:  PubMed          Journal:  J Gerontol A Biol Sci Med Sci        ISSN: 1079-5006            Impact factor:   6.053


  20 in total

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Review 2.  Calibration of accelerometer output for adults.

Authors:  Charles E Matthew
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

3.  Validation of the Kenz Lifecorder EX and ActiGraph GT1M accelerometers for walking and running in adults.

Authors:  Mark G Abel; James C Hannon; Katie Sell; Tia Lillie; Geri Conlin; David Anderson
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4.  Assessing the "physical cliff": detailed quantification of age-related differences in daily patterns of physical activity.

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Journal:  J Gerontol A Biol Sci Med Sci       Date:  2013-12-14       Impact factor: 6.053

5.  Motivators, barriers, and beliefs regarding physical activity in an older adult population.

Authors:  Ellen Costello; Marcia Kafchinski; JoEllen Vrazel; Patricia Sullivan
Journal:  J Geriatr Phys Ther       Date:  2011 Jul-Sep       Impact factor: 3.381

6.  A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.

Authors:  J M Guralnik; E M Simonsick; L Ferrucci; R J Glynn; L F Berkman; D G Blazer; P A Scherr; R B Wallace
Journal:  J Gerontol       Date:  1994-03

7.  Assessment of physical activity using wearable monitors: recommendations for monitor calibration and use in the field.

Authors:  Patty Freedson; Heather R Bowles; Richard Troiano; William Haskell
Journal:  Med Sci Sports Exerc       Date:  2012-01       Impact factor: 5.411

8.  Objectively measured light-intensity physical activity is independently associated with 2-h plasma glucose.

Authors:  Genevieve N Healy; David W Dunstan; Jo Salmon; Ester Cerin; Jonathan E Shaw; Paul Z Zimmet; Neville Owen
Journal:  Diabetes Care       Date:  2007-05-01       Impact factor: 19.112

9.  Accelerometer assessment of physical activity in active, healthy older adults.

Authors:  Jennifer L Copeland; Dale W Esliger
Journal:  J Aging Phys Act       Date:  2009-01       Impact factor: 1.961

10.  Lifestyle interventions and independence for elders study: recruitment and baseline characteristics.

Authors:  Anthony P Marsh; Laura C Lovato; Nancy W Glynn; Kimberly Kennedy; Cynthia Castro; Kathryn Domanchuk; Erica McDavitt; Ruben Rodate; Michael Marsiske; Joanne McGloin; Erik J Groessl; Marco Pahor; Jack M Guralnik
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2013-05-28       Impact factor: 6.053

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Journal:  Contemp Clin Trials       Date:  2017-07-22       Impact factor: 2.226

2.  A Case for Promoting Movement Medicine: Preventing Disability in the LIFE Randomized Controlled Trial.

Authors:  Jason Fanning; W Jack Rejeski; Shyh-Huei Chen; Barbara J Nicklas; Michael P Walkup; Robert S Axtell; Roger A Fielding; Nancy W Glynn; Abby C King; Todd M Manini; Mary M McDermott; Anne B Newman; Marco Pahor; Catrine Tudor-Locke; Michael E Miller
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3.  Active-to-Sedentary Behavior Transitions, Fatigability, and Physical Functioning in Older Adults.

Authors:  Jennifer A Schrack; Pei-Lun Kuo; Amal A Wanigatunga; Junrui Di; Eleanor M Simonsick; Adam P Spira; Luigi Ferrucci; Vadim Zipunnikov
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2019-03-14       Impact factor: 6.053

4.  Evaluating Walking Intensity with Hip-Worn Accelerometers in Elders.

Authors:  Duane B Corbett; Vincenzo Valiani; Jeffrey D Knaggs; Todd M Manini
Journal:  Med Sci Sports Exerc       Date:  2016-11       Impact factor: 5.411

5.  A comparison of accelerometry analysis methods for physical activity in older adult women and associations with health outcomes over time.

Authors:  Katie J Thralls; Suneeta Godbole; Todd M Manini; Eileen Johnson; Loki Natarajan; Jacqueline Kerr
Journal:  J Sports Sci       Date:  2019-06-14       Impact factor: 3.337

6.  Using Heart Rate and Accelerometry to Define Quantity and Intensity of Physical Activity in Older Adults.

Authors:  Jennifer A Schrack; Andrew Leroux; Jerome L Fleg; Vadim Zipunnikov; Eleanor M Simonsick; Stephanie A Studenski; Ciprian Crainiceanu; Luigi Ferrucci
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2018-04-17       Impact factor: 6.053

7.  Device-Measured Physical Activity As a Predictor of Disability in Mobility-Limited Older Adults.

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8.  Predictors of Change in Physical Function in Older Adults in Response to Long-Term, Structured Physical Activity: The LIFE Study.

Authors:  Andrew S Layne; Fang-Chi Hsu; Steven N Blair; Shyh-Huei Chen; Jennifer Dungan; Roger A Fielding; Nancy W Glynn; Alexandra M Hajduk; Abby C King; Todd M Manini; Anthony P Marsh; Marco Pahor; Christine A Pellegrini; Thomas W Buford
Journal:  Arch Phys Med Rehabil       Date:  2016-08-25       Impact factor: 3.966

9.  Relationships Between Profiles of Physical Activity and Major Mobility Disability in the LIFE Study.

Authors:  Jason Fanning; W Jack Rejeski; Shyh-Huei Chen; Jack Guralnik; Marco Pahor; Michael E Miller
Journal:  J Am Geriatr Soc       Date:  2020-03-20       Impact factor: 5.562

10.  Evaluating Accelerometry Thresholds for Detecting Changes in Levels of Moderate Physical Activity and Resulting Major Mobility Disability.

Authors:  W Jack Rejeski; Michael P Walkup; Roger A Fielding; Abby C King; Todd Manini; Anthony P Marsh; Mary McDermott; Emily Y Miller; Anne B Newman; Catrine Tudor-Locke; Robert S Axtell; Michael E Miller
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2018-04-17       Impact factor: 6.053

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