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dc.contributor.authorThompson, Fintanen
dc.contributor.authorRussell, Sarahen
dc.contributor.authorQuigley, Rachelen
dc.contributor.authorSagigi, Bettyen
dc.contributor.authorMiller, Gavinen
dc.contributor.authorEsterman, Adrianen
dc.contributor.authorHarriss, Lintonen
dc.contributor.authorTaylor, Seanen
dc.contributor.authorMcDermott, Robynen
dc.contributor.authorStrivens, Edwarden
dc.date.accessioned2023-07-27T04:00:41Z-
dc.date.available2023-07-27T04:00:41Z-
dc.date.issued2023-
dc.identifier.citationThompson F, Russell S, Quigley R, Sagigi B, Miller G, Esterman A, Harriss LR, Taylor S, McDermott R, Strivens E. Dementia Risk Models in an Australian First Nations Population: Cross-Sectional Associations and Preparation for Follow-Up. J Alzheimers Dis Rep. 2023 Jun 5;7(1):543-555. doi: 10.3233/ADR-220093. PMID: 37313487; PMCID: PMC10259055.en
dc.identifier.urihttps://dora.health.qld.gov.au/qldresearchjspui/handle/1/5331-
dc.descriptionCairns & Hinterland Hospital and Health Service (CHHHS) affiliated authors: Fintan Thompson, Sarah Russell, Rachel Quigley, Gavin Miller, Linton R Harriss, Edward Strivensen
dc.description.abstractBackground: Reducing the burden of dementia in First Nations populations may be addressed through developing population specific methods to quantify future risk of dementia. Objective: To adapt existing dementia risk models to cross-sectional dementia prevalence data from a First Nations population in the Torres Strait region of Australia in preparation for follow-up of participants. To explore the diagnostic utility of these dementia risk models at detecting dementia. Methods: A literature review to identify existing externally validated dementia risk models. Adapting these models to cross-sectional data and assessing their diagnostic utility through area under the receiver operating characteristic curve (AUROC) analyses and calibration using Hosmer-Lemeshow Chi2. Results: Seven risk models could be adapted to the study data. The Aging, Cognition and Dementia (AgeCoDe) study, the Framingham Heart Study (FHS), and the Brief Dementia Screening Indicator (BDSI) had moderate diagnostic utility in identifying dementia (i.e., AUROC >0.70) before and after points for older age were removed. Conclusion: Seven existing dementia risk models could be adapted to this First Nations population, and three had some cross-sectional diagnostic utility. These models were designed to predict dementia incidence, so their applicability to identify prevalent cases would be limited. The risk scores derived in this study may have prognostic utility as participants are followed up over time. In the interim, this study highlights considerations when transporting and developing dementia risk models for First Nations populations.en
dc.language.isoenen
dc.relation.ispartofJournal of Alzheimer's disease reportsen
dc.subjectAlzheimer’s diseaseen
dc.subjectAustraliaen
dc.subjectFirst Nationsen
dc.subjectIndigenousen
dc.subjectdementiaen
dc.subjectdiagnosticen
dc.subjectrisk modelsen
dc.titleDementia Risk Models in an Australian First Nations Population: Cross-Sectional Associations and Preparation for Follow-Upen
dc.typeArticleen
dc.identifier.doi10.3233/ADR-220093-
dc.identifier.pmid37313487-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
Appears in Sites:Cairns & Hinterland HHS Publications
Torres & Cape HHS Publications
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