Equating accelerometer estimates among youth: The Rosetta Stone 2.
- Brazendale K University of South Carolina, Department of Exercise Science, USA. Electronic address: brazendk@email.sc.edu.
- Beets MW University of South Carolina, Department of Exercise Science, USA.
- Bornstein DB University of South Carolina, Department of Exercise Science, USA.
- Moore JB University of South Carolina, Department of Health Promotion, Education, and Behavior, USA.
- Pate RR University of South Carolina, Department of Exercise Science, USA.
- Weaver RG University of South Carolina, Department of Exercise Science, USA.
- Falck RS University of South Carolina, Department of Exercise Science, USA.
- Chandler JL University of South Carolina, Department of Exercise Science, USA.
- Andersen LB University of Southern Denmark, Department of Sport Science and Clinical Biomechanics, Denmark; Norwegian School of Sport Science, Norway.
- Anderssen SA Norwegian School of Sport Science, Norway.
- Cardon G Ghent University, Department of Movement and Sports Sciences, Belgium.
- Cooper A University of Bristol, Centre for Exercise, Nutrition and Health Sciences/School of Social and Community Medicine, UK.
- Davey R University of Canberra, Centre for Research and Action in Public Health, Australia.
- Froberg K University of Southern Denmark, Department of Sport Science and Clinical Biomechanics, Denmark.
- Hallal PC Federal University of Pelotas, Brazil.
- Janz KF University of Iowa, Department of Health and Human Physiology, USA.
- Kordas K University of Bristol, Centre for Exercise, Nutrition and Health Sciences/School of Social and Community Medicine, UK.
- Kriemler S University of Zürich, Epidemiology, Biostatistics and Public Health Institute, Switzerland.
- Puder JJ University of Lausanne, Service of Endocrinology, Diabetes and Metabolism, Switzerland.
- Reilly JJ University of Glasgow, Division of Developmental Medicine, UK.
- Salmon J Deakin University, School of Exercise and Nutrition Sciences/Centre for Physical Activity and Nutrition Research, Australia.
- Sardinha LB Technical University of Lisbon, Faculty of Human Movement, Portugal.
- Timperio A University of Glasgow, Division of Developmental Medicine, UK.
- van Sluijs EMF University of Cambridge, MRC Epidemiology Unit, UK.
- 2015-03-10
Published in:
- Journal of science and medicine in sport. - 2016
Children
Cutpoints
MVPA
Measurement
Policy
Public health
Accelerometry
Adolescent
Child
Child, Preschool
Exercise
Female
Humans
Male
Reference Values
English
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 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-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 -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-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.
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 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-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 -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-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.
- Language
-
- English
- Open access status
- green
- Identifiers
-
- DOI 10.1016/j.jsams.2015.02.006
- PMID 25747468
- Persistent URL
- https://sonar.rero.ch/global/documents/228866
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