Related Experiment Videos
Are we missing the sitting? Agreement between accelerometer non-wear time validation methods used with older adults'
Anna M Chudyk1,2, Megan M McAllister1,2, Hiu Kan Cheung1
1Centre for Hip Health and Mobility, 2635 Laurel Street, Vancouver, British Columbia, Canada V5Z 1M9.
Cogent Medicine
|January 9, 2018
Summary
Accurate measurement of sedentary behavior in older adults is crucial. Algorithms using longer non-wear time definitions (≥90 minutes) better estimate sedentary behavior and wear time compared to shorter definitions.
Area of Science:
- Gerontology
- Physical Activity Measurement
- Biomedical Engineering
Background:
- Sedentary behavior is a significant health risk for older adults.
- Accurate measurement of sedentary behavior and wear time is essential for health interventions.
- Existing methods for estimating sedentary behavior using accelerometry have limitations.
Purpose of the Study:
- To compare the agreement between a self-report diary and various non-wear time algorithms for estimating sedentary behavior and wear time in older adults.
- To evaluate the performance of the Troiano algorithm and algorithms defining non-wear time by ≥90 minutes of consecutive zeroes.
Main Methods:
- Bland Altman plots were used to assess agreement.
- Data from 106 community-dwelling older adults were analyzed.
- Five non-wear time algorithms were compared against a self-report diary and accelerometry.
Main Results:
- The Troiano algorithm (≥60 minutes of zeroes) may overestimate sedentary behavior and wear time by ≥30 min/day.
- Algorithms using ≥90 minutes of consecutive zeroes showed closer approximation to self-reported sedentary behavior and wear time.
- While mean differences were small, wide 95% limits of agreement indicated substantial variation in estimates across all comparisons.
Conclusions:
- Algorithms defining non-wear time using ≥90 minutes of continuous zeroes are more suitable for estimating sedentary behavior and wear time in older adults.
- There is a critical need for accurate measurement approaches to inform interventions aimed at reducing sedentary behavior in this population.