Empirically derived cut-points for sedentary behaviour for weekdays and weekends : are we sitting differently?

Clarke-Cornwell, AM ORCID: https://orcid.org/0000-0001-9510-7676, Farragher, TM, Cook, PA ORCID: https://orcid.org/0000-0001-6435-8050, Dugdill, L and Granat, MH ORCID: https://orcid.org/0000-0002-0722-2760 2015, Empirically derived cut-points for sedentary behaviour for weekdays and weekends : are we sitting differently? , in: International Conference on Ambulatory Monitoring of Physical Activity and Movement, 10-12 June 2015, Limerick, Ireland.

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Introduction: Sedentary behaviour (SB) is associated with many adverse health outcomes. Studies that have used accelerometers to define sedentary time usually adopt a <100 counts per minute (cpm) threshold for classifying SB; however, this cut-point was not empirically derived for adults. We aimed to 1: empirically derive an optimal threshold for correctly classifying SB, using the cpm output from the ActiGraph GT3X%2B (AG), when compared to the sedentary classification from the activPAL (AP); and 2: determine whether this changed depending on type of day.

Methods: A sample of 30 university employees (10 males and 30 females, 40.5±11.0 years old) wore the AG and AP devices simultaneously for 7 days. An activity diary was used to record non-wear time (sleeping hours, work time, removal of devices). Data were downloaded in 60s epochs; non-wear time was removed and the Choi¹ algorithm applied. Multivariable fractional polynomial models with generalised estimating equations were used to make minute by minute comparisons of sedentary time from the 2 devices (each day), allowing for both the change in cpm over time and the correlation of cpm with adjacent minutes. The cut-points derived from these regression models were tested using the split-sample method compared to the 100 cpm cut-point.

Results: After data reduction, participants provided on average 12 hours 6 minutes of data per day (SD=2 hours 4 minutes, 82% of awake hours). The model-derived cut-points ranged from 70-96 cpm for weekdays, and were significantly higher at the weekend (118 cpm). These cut-points performed better than the 100 cut-point (area under the curve analysis).

Discussion & Conclusion: Different cut-points for SB classification were found for weekdays and the weekend. This is the first study to show that cut-points can depend on day; with independent links to health outcomes, it is imperative to have accurate and reliable measures of SB.

Item Type: Conference or Workshop Item (Speech)
Schools: Schools > School of Health and Society > Centre for Health Sciences Research
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Depositing User: AM Clarke-Cornwell
Date Deposited: 09 Apr 2019 15:31
Last Modified: 27 Aug 2021 21:23
URI: http://usir.salford.ac.uk/id/eprint/51003

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