Equating accelerometer estimates among youth: The Rosetta Stone 2

• Published in: Journal of science and medicine in sport Vol. 19; no. 3; pp. 242 - 249
• Main Authors: Brazendale, Keith, Beets, Michael W, Bornstein, Daniel B, Moore, Justin B, Pate, Russell R, Weaver, Robert G, Falck, Ryan S, Chandler, Jessica L, Andersen, Lars B, Anderssen, Sigmund A, Cardon, Greet, Cooper, Ashley, Davey, Rachel, Froberg, Karsten, Hallal, Pedro C, Janz, Kathleen F, Kordas, Katarzyna, Kriemler, Susi, Puder, Jardena J, Reilly, John J, Salmon, Jo, Sardinha, Luis B, Timperio, Anna, van Sluijs, Esther M.F
• Format: Journal Article
• Language: English
• Published: Australia Elsevier Ltd 01.03.2016; Elsevier Limited
• Subjects: Accelerometers; Accelerometry - standards; Adolescent; Child; Child, Preschool; Children; Children & youth; Cutpoints; Estimates; Exercise; Female; Humans; Male; Measurement; MVPA; Physical Medicine and Rehabilitation; Policy; Public health; Reference Values; Researchers; Sports Medicine; Studies; Teenagers; Measurement; Policy; Children; Cutpoints; MVPA; Public health
• ISSN: 1440-2440; 1878-1861
• DOI: 10.1016/j.jsams.2015.02.006

Abstract Objectives Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints. Design Secondary data analysis. Methods Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3–18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values. Results Across the total sample, mean MVPA ranged from 29.7 MVPA min d−1 (Puyau) to 126.1 MVPA min d−1 (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was −0.110 min d−1 (limits of agreement (LOA), −2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76 min d−1 (LOA, −60.392 to 129.910). Conclusions For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA.