Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations

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URI: https://hdl.handle.net/10481/99733
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Hidalgo Migueles, Jairo; Cadenas Sánchez, Cristina; Ekelund, Ulf; Delisle Nyström, Christine; Mora González, José Rafael; Löf, Marie; Labayen, Idoia; Ruiz Ruiz, Jonatan; Ortega Porcel, Francisco Bartolomé
Editorial
Springer Nature
Materia
Indirect Calorimetry
 
Multivariate Adaptive Regression Spline
 
Physical Activity Intensity
 
Sedentary Time
 
Vigorous Physical Activity
 
Date
2017-03-16
Referencia bibliográfica
Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nyström C, Mora-Gonzalez J, Löf M, Labayen I, Ruiz JR, Ortega FB. Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations. Sports Med. 2017 Sep;47(9):1821-1845. doi: 10.1007/s40279-017-0716-0. PMID: 28303543; PMCID: PMC6231536.
Sponsorship
This study was supported by the Spanish Ministry of Economy and Competitiveness (DEP2013-47540, DEP2016-79512-R & PSI2012- 3929), the Alicia Kolplowitz Foundation and for the Spanish Ministry of Science and Innovation (RYC-2011-09011 & FJCI-2014-19563). IE-C received a scholarship from the Alicia Koplowitz Foundation and a Jose Castillejo scholarship (CAS17/00320) for a brief stay in the Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Australia. CC-S is supported by a grant from the Spanish Ministry of Economy and Competitiveness (BES-2014-068829). JM-G and JHM are supported by the Spanish Ministry of Education, Culture and Sport (FPU14/06837 and FPU15/02645, respectively). PH is supported by a grant from the Strategic Research Area Health Care Science, Karolinska Institutet/Umeå University. OC-R is supported by a Postdoctoral “PERIS” Contract (SLT006/17/00236) from the Catalan Government, 2017, Spain. JVR is supported by a postdoctoral fellowship from the Junta de Andalucía (P10-HUM-6635). This study takes place thanks to the additional funding from the University of Granada, Plan Propio de Investigación 2016, Excellence actions: Units of Excellence; Unit of Excellence on Exercise and Health (UCEES). Additional funding from the EXERNET Research Network on Exercise and Health in Special Populations (DEP2005-00046/ACTI, the SAMID III network, RETICS, funded by the PN IþDþI 2017–2021 (Spain), ISCIII- Sub-Directorate General for Research Assessment and Promotion and the European Regional Development Fund (ERDF) (Ref. RD16/0022).
Abstract
Background: Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus. Objectives: The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified. Methods: Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015. Results: The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific. Conclusion: This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.
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