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Time-Use Patterns and Health-Related Quality of Life in Adolescents

Wong, Monica; Olds, Tim; Gold, Lisa; Lycett, Kate; Dumuid, Dorothea; Muller, Josh; Mensah, Fiona; Burgner, David; Carlin, John B; Edwards, Benjamin; Dwyer, Terence

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OBJECTIVES: To describe 24-hour time-use patterns and their association with health-related quality of life (HRQoL) in early adolescence. METHODS: The Child Health CheckPoint was a cross-sectional study nested between Waves 6 and 7 of the Longitudinal Study of Australian Children. The participants were 1455 11- to 12-year-olds (39% of Wave 6; 51% boys). The exposure was 24-hour time use measured across 259 activities using the Multimedia Activity Recall for Children and Adolescents....[Show more]

dc.contributor.authorWong, Monica
dc.contributor.authorOlds, Tim
dc.contributor.authorGold, Lisa
dc.contributor.authorLycett, Kate
dc.contributor.authorDumuid, Dorothea
dc.contributor.authorMuller, Josh
dc.contributor.authorMensah, Fiona
dc.contributor.authorBurgner, David
dc.contributor.authorCarlin, John B
dc.contributor.authorEdwards, Benjamin
dc.contributor.authorDwyer, Terence
dc.date.accessioned2019-10-15T23:28:43Z
dc.identifier.issn0031-4005
dc.identifier.urihttp://hdl.handle.net/1885/176994
dc.description.abstractOBJECTIVES: To describe 24-hour time-use patterns and their association with health-related quality of life (HRQoL) in early adolescence. METHODS: The Child Health CheckPoint was a cross-sectional study nested between Waves 6 and 7 of the Longitudinal Study of Australian Children. The participants were 1455 11- to 12-year-olds (39% of Wave 6; 51% boys). The exposure was 24-hour time use measured across 259 activities using the Multimedia Activity Recall for Children and Adolescents. “Average” days were generated from 1 school and 1 nonschool day. Time-use clusters were derived from cluster analysis with compositional inputs. The outcomes were self-reported HRQoL (Physical and Psychosocial Health [PedsQL] summary scores; Child Health Utility 9D [CHU9D] health utility). RESULTS: Four time-use clusters emerged: “studious actives” (22%; highest school-related time, low screen time), “techno-actives” (33%; highest physical activity, lowest school-related time), “stay home screenies” (23%; highest screen time, lowest passive transport), and “potterers” (21%; low physical activity). Linear regression models, adjusted for a priori confounders, showed that compared with the healthiest “studious actives” (mean [SD]: CHU9D 0.84 [0.14], PedsQL physical 86.8 [10.8], PedsQL psychosocial 79.9 [12.6]), HRQoL in “potterers” was 0.2 to 0.5 SDs lower (mean differences [95% confidence interval]: CHU9D −0.03 [−0.05 to −0.00], PedsQL physical −5.5 [−7.4 to −3.5], PedsQL psychosocial −5.8 [−8.0 to −3.5]). CONCLUSIONS: Discrete time-use patterns exist in Australian young adolescents. The cluster characterized by low physical activity and moderate screen time was associated with the lowest HRQoL. Whether this pattern translates into precursors of noncommunicable diseases remains to be determined.
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherAmerican Academy of Pediatrics
dc.rights© 2017 by the American Academy of Pediatrics
dc.sourcePediatrics
dc.titleTime-Use Patterns and Health-Related Quality of Life in Adolescents
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume140
dc.date.issued2017
local.identifier.absfor170102 - Developmental Psychology and Ageing
local.identifier.ariespublicationu1023009xPUB1
local.publisher.urlhttps://www.aap.org/en-us/Pages/Default.aspx
local.type.statusPublished Version
local.contributor.affiliationWong, Monica, University of Melbourne
local.contributor.affiliationOlds, Tim, University of South Australia
local.contributor.affiliationGold, Lisa, Deakin University
local.contributor.affiliationLycett, Kate, University of Melbourne
local.contributor.affiliationDumuid, Dorothea, University of South Australia
local.contributor.affiliationMuller, Josh, Murdoch Children Research Institute
local.contributor.affiliationMensah, Fiona, Murdoch Childrens Research Centre
local.contributor.affiliationBurgner, David, Murdoch Children Research Institute
local.contributor.affiliationCarlin, John B, University of Melbourne
local.contributor.affiliationEdwards, Benjamin, College of Arts and Social Sciences, ANU
local.contributor.affiliationDwyer, Terence, Murdoch Children's Research Institute
local.description.embargo2037-12-31
dc.relationhttp://purl.org/au-research/grants/nhmrc/1041352
dc.relationhttp://purl.org/au-research/grants/nhmrc/1109355
dc.relationhttp://purl.org/au-research/grants/nhmrc/1046518
dc.relationhttp://purl.org/au-research/grants/nhmrc/1035100
dc.relationhttp://purl.org/au-research/grants/nhmrc/1111160
local.bibliographicCitation.issue1
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage9
local.identifier.doi10.1542/peds.2016-3656.
local.identifier.absseo920501 - Child Health
dc.date.updated2019-05-05T09:02:32Z
CollectionsANU Research Publications

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