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dc.contributor.authorOkabayashi, Satoeen
dc.contributor.authorKawamura, Takashien
dc.contributor.authorNoma, Hisashien
dc.contributor.authorWakai, Kenjien
dc.contributor.authorAndo, Masahikoen
dc.contributor.authorTsushita, Kazuyoen
dc.contributor.authorOhira, Hidekien
dc.contributor.authorUkawa, Shigekazuen
dc.contributor.authorTamakoshi, Akikoen
dc.contributor.alternative岡林, 里枝ja
dc.contributor.alternative川村, 孝ja
dc.date.accessioned2022-10-05T01:51:06Z-
dc.date.available2022-10-05T01:51:06Z-
dc.date.issued2021-
dc.identifier.urihttp://hdl.handle.net/2433/276567-
dc.description.abstractBACKGROUND: Predicting adverse health events and implementing preventative measures are a necessary challenge. It is important for healthcare planners and policymakers to allocate the limited resource to high-risk persons. Prediction is also important for older individuals, their family members, and clinicians to prepare mentally and financially. The aim of this study is to develop a prediction model for within 11-year dependent status requiring long-term nursing care or death in older adults for each sex. METHODS: We carried out age-specified cohort study of community dwellers in Nisshin City, Japan. The older adults aged 64 years who underwent medical check-up between 1996 and 2000 were included in the study. The primary outcome was the incidence of the psychophysically dependent status or death or by the end of the year of age 75 years. Univariable logistic regression analyses were performed to assess the associations between candidate predictors and the outcome. Using the variables with p-values less than 0.1, multivariable logistic regression analyses were then performed with backward stepwise elimination to determine the final predictors for the model. RESULTS: Of the 1525 female participants at baseline, 105 had an incidence of the study outcome. The final prediction model consisted of 15 variables, and the c-statistics for predicting the outcome was 0.763 (95% confidence interval [CI] 0.714-0.813). Of the 1548 male participants at baseline, 211 had incidence of the study outcome. The final prediction model consisted of 16 variables, and the c-statistics for predicting the outcome was 0.735 (95% CI 0.699-0.771). CONCLUSIONS: We developed a prediction model for older adults to forecast 11-year incidence of dependent status requiring nursing care or death in each sex. The predictability was fair, but we could not evaluate the external validity of this model. It could be of some help for healthcare planners, policy makers, clinicians, older individuals, and their family members to weigh the priority of support.en
dc.language.isoeng-
dc.publisherSpringer Natureen
dc.publisherBMCen
dc.rights© The Author(s). 2021en
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/-
dc.subjectAgeden
dc.subjectCohort studiesen
dc.subjectDeathen
dc.subjectForecastingen
dc.subjectNursing careen
dc.titlePrediction of 11-year incidence of psychophysically dependent status or death among community-dwelling younger elderlies: from an age-specified community-based cohort study (the NISSIN project)en
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleEnvironmental Health and Preventive Medicineen
dc.identifier.volume26-
dc.relation.doi10.1186/s12199-021-00968-8-
dc.textversionpublisher-
dc.identifier.artnum45-
dc.identifier.pmid33838644-
dcterms.accessRightsopen access-
datacite.awardNumber15390197-
datacite.awardNumber26520105-
datacite.awardNumber20K02392-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-15390197/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-26520105/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20K02392/-
dc.identifier.eissn1342-078X-
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitle健やかな老い関連要因検討のための追跡研究ja
jpcoar.awardTitle前高齢期から高齢期を見通し、予防医療や行政施策を個別化するための予測モデルの作成ja
jpcoar.awardTitle前期高齢者のボランティア参加と認知症発症に関するパネルデータ研究ja
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