GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies Migueles Hidalgo, Jairo Ortega Porcel, Francisco Bartolomé External review group Physical activity Epidemiology Statistics Accelerometer Sedentary This study was conducted under the umbrella of the ActiveBrains and the SmarterMove projects supported by the MINECO/FEDER (DEP2013-47540, DEP2016-79512-R, RYC-2011-09011) and the CoCA project supported by the European Union's 2020 research and innovation programme (667302). JHM is supported by a grant from the Spanish Ministry of Education, Culture and Sport (FPU15/02645). AR is supported by the NIHR Leicester Biomedical Research Centre, and the Collaboration for leadership in Applied Health Research and Care (CLAHRC) East Midlands. SS is supported by the French National Research Agency (ANR-19-CE36-0004-01). RW is supported by a Medical Research Council Industrial Strategy Studentship (MR/S502509/1). Additional funding was obtained from the Andalusian Operational Programme supported with European Regional Development Funds (ERDF in English, FEDER in Spanish, project ref: B-CTS-355-UGR18), the University of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of Excellence; Scientific Excellence Unit on Exercise and Health (UCEES), Junta de Andalucia,Consejeria de Conocimiento, Investigacion y Universidades and European Regional Development Funds (ref. SOMM17/6107/UGR). In addition, funding was provided by the SAMID III network, RETICS, funded by the PN I+D+I 2017-2021 (Spain), ISCIIISub-Directorate General for Research Assessment and Promotion, the European Regional Development Fund (ERDF) (Ref. RD16/0022), the EXERNET Research Network on Exercise and Health in Special Populations (DEP2005-00046/ACTI). The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines. 2021-12-20T09:33:52Z 2021-12-20T09:33:52Z 2021-04-12 journal article Migueles JH... [et al.]. GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. British Journal of Sports Medicine Published Online First: 12 April 2021. doi: [10.1136/bjsports-2020-103604] http://hdl.handle.net/10481/72127 10.1136/bjsports-2020-103604 eng info:eu-repo/grantAgreement/EC/H2020/667302 http://creativecommons.org/licenses/by-nc/3.0/es/ open access Atribución-NoComercial 3.0 España BMJ