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dc.contributor.authorTagder P
dc.contributor.authorAlfonso-Mora M.L
dc.contributor.authorDíaz-Vidal D
dc.contributor.authorQuino-Ávila A.C
dc.contributor.authorMéndez J.L
dc.contributor.authorSandoval-Cuellar C
dc.contributor.authorMonsalve-Jaramillo E
dc.contributor.authorGiné-Garriga M.
dc.date.accessioned2024-11-01T14:34:41Z
dc.date.available2024-11-01T14:34:41Z
dc.date.issued2024
dc.identifier.issn19326203
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85190832773&doi=10.1371%2fjournal.pone.0299032&partnerID=40&md5=8bc5daecfd2845ac9d3686b9ff6ed153
dc.identifier.urihttp://hdl.handle.net/10818/62200
dc.description.abstractThe accurate monitoring of metabolic syndrome in older adults is relevant in terms of its early detection, and its management. This study aimed at proposing a novel semiparametric modeling for a cardiometabolic risk index (CMRI) and individual risk factors in older adults. Methods: Multivariate semiparametric regression models were used to study the association between the CMRI with the individual risk factors, which was achieved using secondary analysis the data from the SABE study (Survey on Health, Well-Being, and Aging in Colombia, 2015). Results: The risk factors were selected through a stepwise procedure. The covariates included showed evidence of non-linear relationships with the CMRI, revealing non-linear interactions between: BMI and age (p< 0.00); arm and calf circumferences (p<0.00); age and females (p<0.00); walking speed and joint pain (p<0.02); and arm circumference and joint pain (p<0.00). Conclusions: Semiparametric modeling explained 24.5% of the observed deviance, which was higher than the 18.2% explained by the linear model. Copyright: © 2024 Tagder et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.formatapplication/pdfes_CO
dc.language.isoenges_CO
dc.publisherPLoS ONEes_CO
dc.relation.ispartofseriesPLoS ONE Vol. 19 N° 4 April
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceUniversidad de La Sabanaes_CO
dc.sourceIntellectum Repositorio Universidad de La Sabanaes_CO
dc.subject.otherBiological markeren
dc.subject.otherGlucoseen
dc.subject.otherHigh density lipoproteinen
dc.subject.otherTriacylglycerolen
dc.subject.otherAdulten
dc.subject.otherAgeden
dc.subject.otherAlcohol consumptionen
dc.subject.otherArticleen
dc.subject.otherBody massen
dc.titleSemiparametric modeling for the cardiometabolic risk index and individual risk factors in the older adult population: a novel proposalen
dc.typejournal articlees_CO
dc.type.hasVersionpublishedVersiones_CO
dc.rights.accessRightsopenAccesses_CO
dc.identifier.doi10.1371/journal.pone.0299032


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