Please use this identifier to cite or link to this item: https://hdl.handle.net/10620/17820
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dc.contributor.authorThurber, K-
dc.contributor.authorBanwell, Cathy-
dc.contributor.authorThurber, Katherine-
dc.contributor.authorBanks, Emily-
dc.date.accessioned2019-04-13T03:38:33Zen
dc.date.accessioned2014-12-15T22:57:19Zen
dc.date.available2014-12-15T22:57:19Zen
dc.date.issued2014-11-28-
dc.identifier.urihttps://hdl.handle.net/10620/17820en
dc.identifier.urihttp://hdl.handle.net/10620/4075en
dc.description.abstractAim: Despite the burgeoning research interest in weight status, in parallel with the increase in obesity worldwide, research describing methods to optimise the validity and accuracy of measured anthropometric data is lacking. Even when ‘gold standard’ methods are employed, no data are 100% accurate, yet the accuracy of anthropometric data is critical to produce robust and interpretable findings. To date, described methods for identifying data that are likely to be inaccurate seem to be ad hoc or lacking in clear justification. Study type: Methods. Methods: This paper reviews approaches to evaluating the accuracy of cross-sectional and longitudinal data on height and weight in children, focusing on recommendations from the World Health Organization (WHO). This review, together with expert consultation, informed the development of a method for processing and verifying longitudinal anthropometric measurements of children. This approach was then applied to data from the Australian Longitudinal Study of Indigenous Children. Results: The review identified the need to assess the likely plausibility of data by (a) examining deviation from the WHO reference population by calculating age- and sex-adjusted height, weight and body mass index z-scores, and (b) examining changes in height and weight in individuals over time. The method developed identified extreme measurements and implausible intraindividual trajectories. It provides evidence-based criteria for the exclusion of data points that are most likely to be affected by measurement error. Conclusions: This paper presents a probabilistic approach to identifying anthropometric measurements that are likely to be implausible. This systematic, practical method is intended to be reproducible in other settings, including for validating large databases.en
dc.subjectChild Developmenten
dc.subjectChildren -- Indigenousen
dc.subjectHealth -- Body size, BMI, Body imageen
dc.titleApproaches to maximising the accuracy of anthropometric data on children: review and empirical evaluation using the Australian Longitudinal Study of Indigenous Childrenen
dc.typeJournal Articlesen
dc.identifier.urlhttp://www.phrp.com.au/issues/vol2512014/approaches-maximising-accuracy-anthropometric-data-children-review-empirical-evaluation-using-australian-longitudinal-study-indigenous-children/en
dc.identifier.surveyLSICen
dc.description.keywordsChild and adolescent healthen
dc.description.keywordsMethodsen
dc.description.keywordsAnthropometric dataen
dc.description.keywordsAboriginal and Torres Strait Islander healthen
dc.description.keywordsLSICen
dc.identifier.journalPublic Health Research & Practiceen
dc.identifier.volume25en
dc.description.pages8en
dc.identifier.issue1en
local.identifier.id4559en
dc.subject.dssChildhood and child developmenten
dc.subject.dssHealth and wellbeingen
dc.subject.dssmaincategoryChild Developmenten
dc.subject.dssmaincategoryChildrenen
dc.subject.dssmaincategoryHealthen
dc.subject.dsssubcategoryBody size, BMI, Body imageen
dc.subject.dsssubcategoryIndigenousen
dc.subject.flosseChildhood and child developmenten
dc.subject.flosseHealth and wellbeingen
dc.relation.surveyLSICen
dc.old.surveyvalueLSICen
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.openairetypeJournal Articles-
item.fulltextNo Fulltext-
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