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dc.contributor.authorShakibaei, Najmeh
dc.contributor.authorHassannejad, Razieh
dc.contributor.authorMohammadifard, Noushin
dc.contributor.authorMarateb, Hamid Reza
dc.contributor.authorMansourian Gharakozlou, Marjan
dc.contributor.authorMañanas Villanueva, Miguel Ángel
dc.contributor.authorSarrafzadegan, Nizal
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2020-12-22T08:34:36Z
dc.date.available2020-12-22T08:34:36Z
dc.date.issued2020-09-05
dc.identifier.citationShakibaei, N. [et al.]. Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years populationbased cohort study. "Lipids in health and disease", 5 Setembre 2020, vol. 19, p. 203:1-203:12.
dc.identifier.issn1476-511X
dc.identifier.otherhttps://europepmc.org/article/ppr/ppr178870
dc.identifier.urihttp://hdl.handle.net/2117/334750
dc.description.abstractBACKGROUND: A comprehensive study on the interaction of cardiovascular disease (CVD) risk factors is critical to prevent cardiovascular events. The main focus of this study is thus to understand direct and indirect relationships between different CVD risk factors. METHODS: A longitudinal data on adults aged =35¿years, who were free of CVD at baseline, were used in this study. The endpoints were CVD events, whereas their measurements were demographic, lifestyle components, socio-economics, anthropometric measures, laboratory findings, quality of life status, and psychological factors. A Bayesian structural equation modelling was used to determine the relationships among 21 relevant factors associated with total CVD, stroke, acute coronary syndrome (ACS), and fatal CVDs. RESULTS: In this study, a total of 3161 individuals with complete information were involved in the study. A total of 407 CVD events, with an average age of 54.77(10.66) years, occurred during follow-up. The causal associations between six latent variables were identified in the causal network for fatal and non-fatal CVDs. Lipid profile, with the coefficient of 0.26 (0.01), influenced the occurrence of CVD events as the most critical factor, while it was indirectly mediated through risky behaviours and comorbidities. Lipid profile at baseline was influenced by a wide range of other protective factors, such as quality of life and healthy lifestyle components. CONCLUSIONS: Analysing a causal network of risk factors revealed the flow of information in direct and indirect paths. It also determined predictors and demonstrated the utility of integrating multi-factor data in a complex framework to identify novel preventable pathways to reduce the risk of CVDs.
dc.language.isoeng
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Ciències de la salut
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària
dc.subject.lcshCardiovascular system -- Diseases
dc.subject.lcshBayesian statistical decision theory
dc.subject.otherAcute coronary syndrome
dc.subject.otherBayesian approach
dc.subject.otherCardiovascular disease
dc.subject.otherStroke
dc.subject.otherStructural equation models
dc.titlePathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years populationbased cohort study
dc.typeArticle
dc.subject.lemacSistema cardiovascular -- Malalties
dc.subject.lemacCardiopatia coronària -- Tractament
dc.subject.lemacEstadística bayesiana
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
dc.identifier.doi10.1186/s12944-020-01375-8
dc.relation.publisherversionhttps://lipidworld.biomedcentral.com/articles/10.1186/s12944-020-01375-8
dc.rights.accessOpen Access
local.identifier.drac29884605
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2017-83989-R/ES/ANALISIS MULTIMODAL PARA LA EVALUACION Y REHABILITACION DE TRASTORNOS NEUROLOGICOS DISCAPACITANTES/
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/712949/EU/ACCIÓ programme to foster mobility of researchers with a focus in applied research and technology transfer/TECNIOspring PLUS
local.citation.authorShakibaei, N.; Hassannejad, R.; Mohammadifard, N.; Marateb, H.R.; Mansourian, M.; Mañanas, M.A.; Sarrafzadegan, N.
local.citation.publicationNameLipids in health and disease
local.citation.volume19
local.citation.startingPage203:1
local.citation.endingPage203:12


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