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dc.contributor.authorZhao, Jen_NZ
dc.contributor.authorMackay, Len_NZ
dc.contributor.authorChang, Ken_NZ
dc.contributor.authorMavoa, Sen_NZ
dc.contributor.authorStewart, Ten_NZ
dc.contributor.authorIkeda, Een_NZ
dc.contributor.authorDonnellan, Nen_NZ
dc.contributor.authorSmith, Men_NZ
dc.date.accessioned2019-05-22T21:03:13Z
dc.date.available2019-05-22T21:03:13Z
dc.date.copyright2019-03-01en_NZ
dc.identifier.citationInternational Journal of Environmental Research and Public Health, 16(5), 897. MDPI AG. Retrieved from http://dx.doi.org/10.3390/ijerph16050897
dc.identifier.issn1661-7827en_NZ
dc.identifier.issn1660-4601en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/12524
dc.description.abstractCompositional data techniques are an emerging method in physical activity research. These techniques account for the complexities of, and interrelationships between, behaviours that occur throughout a day (e.g., physical activity, sitting, and sleep). The field of health geography research is also developing rapidly. Novel spatial techniques and data visualisation approaches are increasingly being recognised for their utility in understanding health from a socio-ecological perspective. Linking compositional data approaches with geospatial datasets can yield insights into the role of environments in promoting or hindering the health implications of the daily time-use composition of behaviours. The 7-day behaviour data used in this study were derived from accelerometer data for 882 Auckland school children and linked to weight status and neighbourhood deprivation. We developed novel geospatial visualisation techniques to explore activity composition over a day and generated new insights into links between environments and child health behaviours and outcomes. Visualisation strategies that integrate compositional activities, time of day, weight status, and neighbourhood deprivation information were devised. They include a ringmap overview, small-multiple ringmaps, and individual and aggregated time–activity diagrams. Simultaneous visualisation of geospatial and compositional behaviour data can be useful for triangulating data from diverse disciplines, making sense of complex issues, and for effective knowledge translation.en_NZ
dc.publisherMDPI
dc.relation.urihttps://www.mdpi.com/1660-4601/16/5/897
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
dc.subjectTime use; Accelerometer data; Physical activity; Sedentary behaviour; Sleep; Neighbourhood context; Weight status; School children; Compositional analysis; Visualisation
dc.titleVisualising Combined Time Use Patterns of Children’s Activities and Their Association With Weight Status and Neighbourhood Contexten_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.3390/ijerph16050897en_NZ
aut.relation.issue5en_NZ
aut.relation.volume16en_NZ
pubs.elements-id354679
aut.relation.journalInternational Journal of Environmental Research and Public Healthen_NZ


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