Please use this identifier to cite or link to this item: https://hdl.handle.net/10620/18310
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dc.contributor.authorOlds, Tim-
dc.contributor.authorMensah, Fiona K-
dc.contributor.authorAzzopardi, Peter-
dc.contributor.authorCarlin, John B-
dc.contributor.authorEdwards, Ben-
dc.contributor.authorDwyer, Terence-
dc.contributor.authorGold, Lisa-
dc.contributor.authorMuller, Josh-
dc.contributor.authorLycett, Kate-
dc.contributor.authorDwyner, Terence-
dc.contributor.authorWong, Monica-
dc.contributor.authorDumuid, Dorothea-
dc.contributor.authorWake, Melissa-
dc.contributor.authorBurgner, David-
dc.date.accessioned2019-04-13T03:42:58Zen
dc.date.accessioned2018-03-09T03:10:47Zen
dc.date.available2018-03-09T03:10:47Zen
dc.date.issued2017-07-01-
dc.identifier.urihttps://hdl.handle.net/10620/18310en
dc.identifier.urihttp://hdl.handle.net/10620/4397en
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.en
dc.titleTime-Use Patterns and Health-Related Quality of Life in Adolescentsen
dc.typeJournal Articlesen
dc.identifier.doi10.1542/peds.2016-3656en
dc.identifier.urlhttp://pediatrics.aappublications.org/content/early/2017/05/30/peds.2016-3656en
dc.identifier.surveyLSACen
dc.description.keywordsAdolescent Health/Medicineen
dc.description.keywordsCommunity Pediatricsen
dc.identifier.journalPediatricsen
dc.identifier.volume140en
dc.description.pagese20163656en
dc.identifier.issue1en
local.identifier.id4942en
dc.title.bookPediatricsen
dc.subject.dssHealth and wellbeingen
dc.subject.flosseHealth and wellbeingen
dc.relation.surveyLSACen
dc.old.surveyvalueLSACen
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeJournal Articles-
item.cerifentitytypePublications-
Appears in Collections:Journal Articles
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