Moving Forward with Backward Compatibility: Translating Wrist Accelerometer Data.
This study aimed to provide a means for calibrating raw acceleration data from wrist-worn accelerometers in relation to past estimates of children's moderate-to-vigorous physical activity (MVPA) from a range of cut points applied to hip-worn ActiGraph data.



This is a secondary analysis of three studies with concurrent 7-d accelerometer wear at the wrist (GENEActiv) and hip (ActiGraph) in 238 children age 9-12 yr. The time spent above acceleration (ENMO) thresholds of 100, 150, 200, 250, 300, 350, and 400 mg from wrist acceleration data (≤5-s epoch) was calculated for comparison with MVPA estimated from widely used children's hip-worn ActiGraph MVPA cut points (Freedson/Trost, 1100 counts per minute; Pate, 1680 counts per minute; Evenson, 2296 counts per minute; Puyau, 3200 counts per minute) with epochs of ≤5, 15, and 60 s.



The optimal ENMO thresholds for alignment with MVPA estimates from ActiGraph cut points determined from 70% of the sample and cross validated with the remaining 30% were as follows: Freedson/Trost = ENMO 150+ mg, irrespective of ActiGraph epoch (intraclass correlation [ICC] ≥ 0.65); Pate = ENMO 200+ mg, irrespective of ActiGraph epoch (ICC ≥ 0.67); Evenson = ENMO 250+ mg for ≤5- and 15-s epochs (ICC ≥ 0.69) and ENMO 300+ mg for 60-s epochs (ICC = 0.73); Puyau = ENMO 300+ mg for ≤5-s epochs (ICC = 0.73), ENMO 350+ mg for 15-s epochs (ICC = 0.73), and ENMO 400+ mg for 60-s epochs (ICC = 0.65). Agreement was robust with cross-validation ICC = 0.62-0.71 and means within ∣7.8∣% ± 4.9% of MVPA estimates from ActiGraph cut points, except Puyau 60-s epochs (ICC = 0.42).



Incremental ENMO thresholds enable children's acceleration data measured at the wrist to be simply and directly compared, at a group level, with past estimates of MVPA from hip-worn ActiGraphs across a range of cut points.
1Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UNITED KINGDOM; 2NIHR Leicester-Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Unit, UNITED KINGDOM; 3Division of Health Sciences, Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, University of South Australia, Adelaide, AUSTRALIA; 4School of Education, Faculty of Social Sciences, Early Start Research Institute, University of Wollongong, Wollongong, NSW, AUSTRALIA; 5Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UNITED KINGDOM; 6Department of Physical Education and Sport Sciences, University of Limerick, Limerick, IRELAND; 7Physical Activity Exchange, Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UNITED KINGDOM; and 8Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC.
Alex V
AV
Rowlands
Dylan P
DP
Cliff
Stuart J
SJ
Fairclough
Lynne M
LM
Boddy
Tim S
TS
Olds
Gaynor
G
Parfitt
Rob J
RJ
Noonan
Samantha J
SJ
Downs
Zoe R
ZR
Knowles
Michael W
MW
Beets
D000054:Acceleration; D061725:Accelerometry / Q000379:methods*; D002648:Child; D015444:Exercise / Q000502:physiology*; D005260:Female; D006615:Hip; D006801:Humans; D008297:Male; D009068:Movement / Q000502:physiology; D015203:Reproducibility of Results; D014953:Wrist