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dc.contributor.authorWinkler, E.
dc.contributor.authorGardiner, P.
dc.contributor.authorClark, B.
dc.contributor.authorMatthews, C.
dc.contributor.authorOwen, N.
dc.contributor.authorHealy, Genevieve
dc.date.accessioned2017-01-30T12:57:36Z
dc.date.available2017-01-30T12:57:36Z
dc.date.created2015-10-29T04:09:35Z
dc.date.issued2012
dc.identifier.citationWinkler, E. and Gardiner, P. and Clark, B. and Matthews, C. and Owen, N. and Healy, G. 2012. Identifying sedentary time using automated estimates of accelerometer wear time. British Journal of Sports Medicine. 46 (6): pp. 436-442.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/27201
dc.identifier.doi10.1136/bjsm.2010.079699
dc.description.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. Results: 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 non-wear 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. Conclusion: 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.

dc.titleIdentifying sedentary time using automated estimates of accelerometer wear time
dc.typeJournal Article
dcterms.source.volume46
dcterms.source.number6
dcterms.source.startPage436
dcterms.source.endPage442
dcterms.source.issn0306-3674
dcterms.source.titleBritish Journal of Sports Medicine
curtin.departmentSchool of Physiotherapy and Exercise Science
curtin.accessStatusFulltext not available


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