Identifying sedentary time using automated estimates of accelerometer wear time

Winkler, Elisabeth A. H., Gardiner, Paul A., Clark, Bronwyn K., Matthews, Charles E., Owen, Neville and Healy, Genevieve N. (2012) Identifying sedentary time using automated estimates of accelerometer wear time. British Journal of Sports Medicine, 46 6: 436-442. doi:10.1136/bjsm.2010.079699

Author Winkler, Elisabeth A. H.
Gardiner, Paul A.
Clark, Bronwyn K.
Matthews, Charles E.
Owen, Neville
Healy, Genevieve N.
Title Identifying sedentary time using automated estimates of accelerometer wear time
Journal name British Journal of Sports Medicine   Check publisher's open access policy
ISSN 0306-3674
Publication date 2012-05
Year available 2011
Sub-type Article (original research)
DOI 10.1136/bjsm.2010.079699
Volume 46
Issue 6
Start page 436
End page 442
Total pages 7
Place of publication London, United Kingdom
Publisher BMJ Group
Collection year 2012
Language eng
Formatted abstract
Purpose The authors evaluated the accuracy of three automated accelerometer wear-time estimation algorithms against self-report. Direct effects on sedentary time (<100 cpm) and indirect effects on moderate-to-vigorous physical activity (MVPA, ≥1952 cpm) time were examined.

Methods A subsample from the 2004/2005 Australian Diabetes, Obesity and Lifestyle Study (n=148) completed activity logs and wore accelerometers for a total of 987 days. A published algorithm that allows movement within non-wear periods (Algorithm 1) was compared with one that allows less movement (Algorithm 2) or no movement (Algorithm 3). Implications for population estimates were examined using 2003/2004 US National Health and Nutrition Examination Survey data.

Mean difference per day between the criterion and estimated wear time was negligible for all three algorithms (≤11 min), but 95% limits of agreement (LOA) were wide (±≥2 h). Respectively, the algorithms (1, 2 and 3) misclassified sedentary time as non-wear on 31.9%, 19.4% and 18% of days and misclassified nonwear time as sedentary on 42.8%, 43.7% and 51.3% of days. Use of Algorithm 2 (compared with Algorithm 1) affected population estimates of sedentary time (higher by 20 min/day) but not MVPA time. Agreement between Algorithms 1 and 2 was good for MVPA time (mean difference −0.08, LOA: −2.08, 1.91 min), but not for wear time or sedentary time.

Accelerometer wear time can be estimated accurately on average; however, misclassification can be substantial for individuals. Algorithm choice affects estimates of sedentary time. Allowing very limited movement within non-wear periods can improve accuracy.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published Online First 18 April 2011

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
School of Public Health Publications
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Created: Fri, 16 Mar 2012, 11:19:28 EST by Geraldine Fitzgerald on behalf of School of Public Health