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dc.contributor.authorIto, Hiromuen
dc.contributor.authorTominari, Shinjiroen
dc.contributor.authorTabara, Yasuharuen
dc.contributor.authorNakayama, Takeoen
dc.contributor.authorFuru, Moritoshien
dc.contributor.authorKawata, Tomotoshien
dc.contributor.authorAzukizawa, Masayukien
dc.contributor.authorSetoh, Kazuyaen
dc.contributor.authorKawaguchi, Takahisaen
dc.contributor.authorMatsuda, Fumihikoen
dc.contributor.authorMatsuda, Shuichien
dc.contributor.authorTakahashi, Yoshimitsuen
dc.contributor.authorKosugi, Shinjien
dc.contributor.alternative伊藤, 宣ja
dc.contributor.alternative富成, 伸次郎ja
dc.contributor.alternative田原, 康玄ja
dc.contributor.alternative中山, 健夫ja
dc.contributor.alternative瀬藤, 和也ja
dc.contributor.alternative川口, 喬久ja
dc.contributor.alternative松田, 文彦ja
dc.contributor.alternative松田, 秀一ja
dc.date.accessioned2019-05-14T05:06:23Z-
dc.date.available2019-05-14T05:06:23Z-
dc.date.issued2019-04-15-
dc.identifier.issn1478-6354-
dc.identifier.issn1478-6362-
dc.identifier.urihttp://hdl.handle.net/2433/241360-
dc.description.abstractBackground: To investigate the association between knee pain and risk factors including low back pain and to develop a score to predict new knee pain in an older population, using population-based longitudinal cohort data. Methods: We collected a questionnaire on self-reported knee pain and demographic data in a systematic manner from community residents aged ≥ 50 years twice, at baseline, and after 5 years. Multivariate logistic regression analyses were performed to investigate the association between knee pain and risk factors and to build a predictive model that would enable calculation of the risk of the development of knee pain within 5 years. The model is presented in the form of score charts. Results: A total of 5932 residents aged ≥ 50 years from the cohort of 9764 that completed the first questionnaire were enrolled in the second survey. After exclusions, paired data for the two time points an average of 5.4 years apart were analyzed for 4638 participants. Multivariate analyses showed older age, female sex, higher BMI, weight increase, lower mental health score, and higher back pain/disability score were independent risk factors for knee pain. The predictive score comprised six factors: age, sex, BMI, weight increase, mental health, and low back pain/disability. The risk of developing knee pain ranged from 11.0 to 63.2% depending on the total score. Conclusion: This study demonstrated a significant association between knee and low back pain/disability along with other risk factors. The score we developed can be used to identify a population without any imaging modality who are at high risk of developing knee pain.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherBioMed Central Ltd.en
dc.rights© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en
dc.subjectKnee painen
dc.subjectLow back painen
dc.subjectMental healthen
dc.subjectPredictive scoreen
dc.subjectRisk factoren
dc.titleLow back pain precedes the development of new knee pain in the elderly population; A novel predictive score from a longitudinal cohort studyen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleArthritis Research and Therapyen
dc.identifier.volume21-
dc.relation.doi10.1186/s13075-019-1884-0-
dc.textversionpublisher-
dc.identifier.artnum98-
dc.addressDepartment of Orthopaedic Surgery, Kyoto University Graduate School of Medicineen
dc.addressDepartment of Health Informatics, Kyoto University Graduate School of Medicineen
dc.addressCenter for Genomic Medicine, Kyoto University Graduate School of Medicineen
dc.addressDepartment of Health Informatics, Kyoto University Graduate School of Medicineen
dc.addressDepartment of Orthopaedic Surgery, Kyoto University Graduate School of Medicineen
dc.addressDepartment of Orthopaedic Surgery, Kyoto University Graduate School of Medicineen
dc.addressDepartment of Orthopaedic Surgery, Kyoto University Graduate School of Medicineen
dc.addressCenter for Genomic Medicine, Kyoto University Graduate School of Medicineen
dc.addressCenter for Genomic Medicine, Kyoto University Graduate School of Medicineen
dc.addressCenter for Genomic Medicine, Kyoto University Graduate School of Medicineen
dc.addressDepartment of Orthopaedic Surgery, Kyoto University Graduate School of Medicineen
dc.identifier.pmid30987680-
dcterms.accessRightsopen access-
datacite.awardNumber25293141-
datacite.awardNumber26670313-
datacite.awardNumber26293198-
datacite.awardNumber17H04182-
datacite.awardNumber17H04126-
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.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName.alternativeJapan Society for the Promotion of Science (JSPS)en
jpcoar.funderName.alternativeJapan Society for the Promotion of Science (JSPS)en
jpcoar.funderName.alternativeJapan Society for the Promotion of Science (JSPS)en
jpcoar.funderName.alternativeJapan Society for the Promotion of Science (JSPS)en
jpcoar.funderName.alternativeJapan Society for the Promotion of Science (JSPS)en
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