Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women

Basit Öğe Kaydı
dc.contributor.authorAkkus, Z
dc.contributor.authorCamdeviren, H
dc.contributor.authorCelik, F
dc.contributor.authorGur, A
dc.contributor.authorNas, K
dc.date.accessioned2024-04-24T17:47:43Z
dc.date.available2024-04-24T17:47:43Z
dc.date.issued2005
dc.departmentDicle Üniversitesien_US
dc.description.abstractObjectives: To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. Methods: We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. Results: We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smimow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Conclusion: Adequate dietary calcium intake in combination with maintaining a daily physical, activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.en_US
dc.identifier.endpage1359en_US
dc.identifier.issn0379-5284
dc.identifier.issue9en_US
dc.identifier.pmid16155647
dc.identifier.startpage1351en_US
dc.identifier.urihttps://hdl.handle.net/11468/22701
dc.identifier.volume26en_US
dc.identifier.wosWOS:000232566300004
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakPubMed
dc.language.isoenen_US
dc.publisherSaudi Med Jen_US
dc.relation.ispartofSaudi Medical Journal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keyword]en_US
dc.titleDetermination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish womenen_US
dc.titleDetermination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayın Koleksiyonu