Compositional Data Analysis in Time-Use Epidemiology: What, Why, How
dc.contributor.author
dc.date.accessioned
2020-03-30T09:27:25Z
dc.date.available
2020-03-30T09:27:25Z
dc.date.issued
2020-03-26
dc.identifier.issn
1661-7827
dc.identifier.uri
dc.description.abstract
In recent years, the focus of activity behavior research has shifted away from univariate paradigms (e.g., physical activity, sedentary behavior and sleep) to a 24-h time-use paradigm that integrates all daily activity behaviors. Behaviors are analyzed relative to each other, rather than as individual entities. Compositional data analysis (CoDA) is increasingly used for the analysis of time-use data because it is intended for data that convey relative information. While CoDA has brought new understanding of how time use is associated with health, it has also raised challenges in how this methodology is applied, and how the findings are interpreted. In this paper we provide a brief overview of CoDA for time-use data, summarize current CoDA research in time-use epidemiology and discuss challenges and future directions. We use 24-h time-use diary data from Wave 6 of the Longitudinal Study of Australian Children (birth cohort, n = 3228, aged 10.9 ± 0.3 years) to demonstrate descriptive analyses of time-use compositions and how to explore the relationship between daily time use (sleep, sedentary behavior and physical activity) and a health outcome (in this example, adiposity). We illustrate how to comprehensively interpret the CoDA findings in a meaningful way
dc.description.sponsorship
D.D. was supported by the National Health and Medical Research Council (APP1162166) and the
National Heart Foundation of Australia (ID102084). J.P.-A. and J.A.M.-F. were supported by the Spanish Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-095518-B-C21, 2019-2021). J.P.-A. was partly supported by the Scottish Government’s Rural and Environment Science and Analytical Services Division. K.H. was funded by a research grant from the Czech Science Foundation no. 18-09188S
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation
RTI2018-095518-B-C21
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.3390/ijerph17072220
dc.relation.ispartof
International Journal of Environmental Research and Public Health, 2020, vol. 17, núm. 7, p. 2220
dc.relation.ispartofseries
Articles publicats (D-IMA)
dc.rights
Attribution 4.0 International
dc.rights.uri
dc.subject
dc.title
Compositional Data Analysis in Time-Use Epidemiology: What, Why, How
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.relation.projectID
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095518-B-C21/ES/METODOS DEL ANALISIS COMPOSICIONAL DE DATOS/
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
032497
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
1660-4601