Combined influence of epoch length, cut-point and bout duration on accelerometry-derived physical activity

Int J Behav Nutr Phys Act. 2014 Mar 10;11(1):34. doi: 10.1186/1479-5868-11-34.

Abstract

Background: It is difficult to compare accelerometer-derived estimates of moderate-to-vigorous physical activity (MVPA) between studies due to differences in data processing procedures. We aimed to evaluate the effects of accelerometer processing options on total and bout-accumulated time spent in MVPA in adults.

Methods: 267 participants from the ProActive Trial provided 1236 days of valid physical activity (PA) data, collected using a 5-s epoch with ActiGraph GT1M accelerometers. We integrated data over 5-s to 60-s epoch lengths (EL) and applied two-level mixed effects regression models to MVPA time, defined using 1500 to 2500 counts/minute (cpm) cut-points (CP) and bout durations (BD) from 1 to 15 min.

Results: Total MVPA time was lower on longer EL and higher CP (47 vs 26 min/day and 26 vs 5 min/day on 1500 vs 2500 cpm on 5-s and 60-s epoch, respectively); this could be approximated as MVPA=exp[2.197+0.279*log(CP)+6.120*log(EL) - 0.869*log(CP)*log(EL)] with an 800 min/day wear-time. In contrast, EL was positively associated with time spent in bout-accumulated MVPA; the approximating equation being MVPA=exp[54.679 - 6.268*log(CP)+6.387*log(EL) - 10.000*log(BD) - 0.162*log(EL)*log(BD) - 0.626*log(CP)*log(EL)+1.033*log(CP)*log(BD)]. BD and CP were inversely associated with MVPA, with higher values attenuating the influence of EL.

Conclusions: EL, CP and BD interact to influence estimates of accelerometer-determined MVPA. In general, higher CP and longer BD result in lower MVPA but the direction of association for EL depends on BD. Reporting scaling coefficients for these key parameters across their frequently used ranges would facilitate comparisons of population-level accelerometry estimates of MVPA.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accelerometry*
  • Adult
  • Body Mass Index
  • Data Interpretation, Statistical
  • Female
  • Humans
  • Male
  • Middle Aged
  • Motor Activity*
  • Time Factors

Associated data

  • ISRCTN/ISRCTN61323766