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Population-based dementia prediction model using Korean public health examination data: A cohort study

DC Field Value Language
dc.contributor.author남궁기-
dc.contributor.author성지민-
dc.contributor.author안석균-
dc.contributor.author이은-
dc.contributor.author장혁재-
dc.contributor.author박경미-
dc.date.accessioned2019-03-15T02:30:48Z-
dc.date.available2019-03-15T02:30:48Z-
dc.date.issued2019-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/167549-
dc.description.abstractThe early identification and prevention of dementia is important for reducing its worldwide burden and increasing individuals' quality of life. Although several dementia prediction models have been developed, there remains a need for a practical and precise model targeted to middle-aged and Asian populations. Here, we used national Korean health examination data from adults (331,126 individuals, 40-69 years of age, mean age: 52 years) from 2002-2003 to predict the incidence of dementia after 10 years. We divided the dataset into two cohorts to develop and validate of our prediction model. Cox proportional hazards models were used to construct dementia prediction models for the total group and sex-specific subgroups. Receiver operating characteristics curves, C-statistics, calibration plots, and cumulative hazards were used to validate model performance. Discriminative accuracy as measured by C-statistics was 0.81 in the total group (95% confidence interval (CI) = 0.81 to 0.82), 0.81 in the male subgroup (CI = 0.80 to 0.82), and 0.81 in the female subgroup (CI = 0.80 to 0.82). Significant risk factors for dementia in the total group were age; female sex; underweight; current hypertension; comorbid psychiatric or neurological disorder; past medical history of cardiovascular disease, diabetes mellitus, or hypertension; current smoking; and no exercise. All identified risk factors were statistically significant in the sex-specific subgroups except for low body weight and current hypertension in the female subgroup. These results suggest that public health examination data can be effectively used to predict dementia and facilitate the early identification of dementia within a middle-aged Asian population.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherPublic Library of Science-
dc.relation.isPartOfPLOS ONE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.titlePopulation-based dementia prediction model using Korean public health examination data: A cohort study-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Psychiatry (정신과학교실)-
dc.contributor.googleauthorKyung Mee Park-
dc.contributor.googleauthorJi Min Sung-
dc.contributor.googleauthorWoo Jung Kim-
dc.contributor.googleauthorSuk Kyoon An-
dc.contributor.googleauthorKee Namkoong-
dc.contributor.googleauthorEun Lee-
dc.contributor.googleauthorHyuk-Jae Chang-
dc.identifier.doi10.1371/journal.pone.0211957-
dc.contributor.localIdA01240-
dc.contributor.localIdA01955-
dc.contributor.localIdA02227-
dc.contributor.localIdA03032-
dc.contributor.localIdA03490-
dc.relation.journalcodeJ02540-
dc.identifier.eissn1932-6203-
dc.identifier.pmid30753205-
dc.contributor.alternativeNameNamkoong, Kee-
dc.contributor.affiliatedAuthor남궁기-
dc.contributor.affiliatedAuthor성지민-
dc.contributor.affiliatedAuthor안석균-
dc.contributor.affiliatedAuthor이은-
dc.contributor.affiliatedAuthor장혁재-
dc.citation.volume14-
dc.citation.number2-
dc.citation.startPagee0211957-
dc.identifier.bibliographicCitationPLOS ONE, Vol.14(2) : e0211957, 2019-
dc.identifier.rimsid42885-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Hospital Medicine (입원의학과) > 1. Journal Papers
1. College of Medicine (의과대학) > Research Institute (부설연구소) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Psychiatry (정신과학교실) > 1. Journal Papers

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