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

Introduction: Sedentary behaviour (SB) is associated with many adverse health outcomes. Studies that have used accelerometers to define sedentary time usually adopt a 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.