Literature DB >> 31688655

Reproducibility of Accelerometer and Posture-derived Measures of Physical Activity.

Pedro F Saint-Maurice1, Joshua N Sampson1, Sarah Kozey Keadle2, Erik A Willis, Richard P Troiano3, Charles E Matthews1.   

Abstract

PURPOSE: The present study estimated the long-term reproducibility of accelerometer-based measures over 6 months in adults and the implications for statistical power, and attenuation in regression coefficients for future activity-disease studies.
METHODS: We used data from 914 adults in the Interactive Diet and Activity Tracking in AARP study. Participants wore an activPAL 3 (AP) and an ActiGraph GT3X (AG) twice, 6 months apart. AP measures included time spent sitting or lying, standing, and stepping, whereas AG measures included time spent in sedentary, light, and moderate-to-vigorous physical activity (PA). Reproducibility of each metric and implications for epidemiological studies were determined based on intraclass correlation coefficients (ICC; 95% confidence interval).
RESULTS: The ICC values for AP estimates were 0.58 (95% confidence interval, 0.53-0.63) for sitting, 0.62 (0.57-0.67) for standing, and 0.57 (0.51-0.62) for stepping. The ICC values for AG were 0.56 (0.50-0.61) for sedentary, 0.54 (0.49-0.60) for light PA, and 0.58 (0.52-0.63) for moderate-to-vigorous PA. Modeling showed that increasing the number of replicate administrations to two or three resulted in the most noticeable increases in ICC values, statistical power, and reductions in attenuation coefficients. For example, administering the AP twice reduced within-subject variability by half and resulted in an increase in the ICC associated with sitting time from 0.58 to 0.74. Similar comparisons for AG and measure of sedentary time resulted in an increase in ICC values from 0.56 to 0.72. Increasing the number of replicate administrations from one to two reduced the attenuation in activity-outcome associations from 40% to 25%.
CONCLUSION: Accelerometer-based classifications of activity are moderately stable over time, but there is considerable within-subject variability that needs to be considered when estimating usual activity in future studies.

Entities:  

Mesh:

Year:  2020        PMID: 31688655      PMCID: PMC7078017          DOI: 10.1249/MSS.0000000000002206

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


  38 in total

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4.  Measurement error correction for logistic regression models with an "alloyed gold standard".

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5.  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
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6.  Reliability of accelerometry-based activity monitors: a generalizability study.

Authors:  Gregory J Welk; Jodee A Schaben; James R Morrow
Journal:  Med Sci Sports Exerc       Date:  2004-09       Impact factor: 5.411

7.  A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003-2006.

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Review 9.  Systematic review of statistical approaches to quantify, or correct for, measurement error in a continuous exposure in nutritional epidemiology.

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Journal:  Int J Behav Nutr Phys Act       Date:  2016-03-01       Impact factor: 6.457

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6.  Accelerometer measured physical activity and the incidence of cardiovascular disease: Evidence from the UK Biobank cohort study.

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  9 in total

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