@article{852ed0e7bb86495e8c212b10aa7a58f7,
title = "Equating accelerometer estimates among youth: The Rosetta Stone 2",
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.",
keywords = "Children, Cutpoints, Measurement, MVPA, Policy, Public health",
author = "{On behalf of the International Children�s Accelerometry Database (ICAD) Collaborators} and Keith Brazendale and Beets, {Michael W.} and Bornstein, {Daniel B.} and Moore, {Justin B.} and Pate, {Russell R.} and Weaver, {Robert G.} and Falck, {Ryan S.} and Chandler, {Jessica L.} and Andersen, {Lars B.} and Anderssen, {Sigmund A.} and Greet Cardon and Ashley Cooper and Rachel Davey and Karsten Froberg and Hallal, {Pedro C.} and Janz, {Kathleen F.} and Katarzyna Kordas and Susi Kriemler and Puder, {Jardena J.} and Reilly, {John J.} and Jo Salmon and Sardinha, {Luis B.} and Anna Timperio and {van Sluijs}, {Esther M.F.}",
note = "Funding Information: No financial assistance was provided for the secondary data analysis of this project. The pooling of the data was funded through a grant from the National Prevention Research Initiative (grant number: G0701877) ( http://www.mrc.ac.uk/Ourresearch/Resourceservices/NPRI/index.htm ). The funding partners relevant to this award are: British Heart Foundation ; Cancer Research UK ; Department of Health, Diabetes UK ; Economic and Social Research Council ; Medical Research Council ; Research and Development Office for the Northern Ireland Health and Social Services ; Chief Scientist Office, Scottish Executive Health Department, The Stroke Association ; Welsh Assembly Government and World Cancer Research Fund . This work was additionally supported by the Medical Research Council [ MC_UU_12015/3 ; MC_UU_12015/7 ], Bristol University , Lougborough University and Norwegian School of Sport Sciences . We also gratefully acknowledge the contribution of Professor Chris Riddoch, Professor Ken Judge and Dr Pippa Griew to the development of ICAD. Jo Salmon is supported by an Australian National Health & Medical Research Council Principal Research Fellowship ( APP1026216 ); Anna Timperio is supported by a National National Heart Foundation of Australia Future Leader Fellowship (Award ID 100046 ). Funding Information: We would like to thank all participants of the original studies that contributed data to ICAD.No financial assistance was provided for the secondary data analysis of this project. The pooling of the data was funded through a grant from the National Prevention Research Initiative (grant number: G0701877) (http://www.mrc.ac.uk/Ourresearch/Resourceservices/NPRI/index.htm). The funding partners relevant to this award are: British Heart Foundation; Cancer Research UK; Department of Health, Diabetes UK; Economic and Social Research Council; Medical Research Council; Research and Development Office for the Northern Ireland Health and Social Services; Chief Scientist Office, Scottish Executive Health Department, The Stroke Association; Welsh Assembly Government and World Cancer Research Fund. This work was additionally supported by the Medical Research Council [MC_UU_12015/3; MC_UU_12015/7], Bristol University, Lougborough University and Norwegian School of Sport Sciences. We also gratefully acknowledge the contribution of Professor Chris Riddoch, Professor Ken Judge and Dr Pippa Griew to the development of ICAD. Jo Salmon is supported by an Australian National Health & Medical Research Council Principal Research Fellowship (APP1026216); Anna Timperio is supported by a National National Heart Foundation of Australia Future Leader Fellowship (Award ID 100046). Publisher Copyright: {\textcopyright} 2015 Sports Medicine Australia.",
year = "2016",
month = mar,
day = "1",
doi = "10.1016/j.jsams.2015.02.006",
language = "English (US)",
volume = "19",
pages = "242--249",
journal = "Journal of Science and Medicine in Sport",
issn = "1440-2440",
publisher = "Elsevier BV",
number = "3",
}