Cargando…

Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study

BACKGROUND: 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 adu...

Descripción completa

Detalles Bibliográficos
Autores principales: Shakibaei, Najmeh, Hassannejad, Razieh, Mohammadifard, Noushin, Marateb, Hamid Reza, Mansourian, Marjan, Mañanas, Miguel Angel, Sarrafzadegan, Nizal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487611/
https://www.ncbi.nlm.nih.gov/pubmed/32891168
http://dx.doi.org/10.1186/s12944-020-01375-8
_version_ 1783581522259869696
author Shakibaei, Najmeh
Hassannejad, Razieh
Mohammadifard, Noushin
Marateb, Hamid Reza
Mansourian, Marjan
Mañanas, Miguel Angel
Sarrafzadegan, Nizal
author_facet Shakibaei, Najmeh
Hassannejad, Razieh
Mohammadifard, Noushin
Marateb, Hamid Reza
Mansourian, Marjan
Mañanas, Miguel Angel
Sarrafzadegan, Nizal
author_sort Shakibaei, Najmeh
collection PubMed
description BACKGROUND: 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.
format Online
Article
Text
id pubmed-7487611
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-74876112020-09-16 Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study Shakibaei, Najmeh Hassannejad, Razieh Mohammadifard, Noushin Marateb, Hamid Reza Mansourian, Marjan Mañanas, Miguel Angel Sarrafzadegan, Nizal Lipids Health Dis Research BACKGROUND: 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. BioMed Central 2020-09-05 /pmc/articles/PMC7487611/ /pubmed/32891168 http://dx.doi.org/10.1186/s12944-020-01375-8 Text en © The Author(s) 2020 Open AccessThis 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. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research
Shakibaei, Najmeh
Hassannejad, Razieh
Mohammadifard, Noushin
Marateb, Hamid Reza
Mansourian, Marjan
Mañanas, Miguel Angel
Sarrafzadegan, Nizal
Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study
title Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study
title_full Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study
title_fullStr Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study
title_full_unstemmed Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study
title_short Pathways leading to prevention of fatal and non-fatal cardiovascular disease: An interaction model on 15 years population-based cohort study
title_sort pathways leading to prevention of fatal and non-fatal cardiovascular disease: an interaction model on 15 years population-based cohort study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487611/
https://www.ncbi.nlm.nih.gov/pubmed/32891168
http://dx.doi.org/10.1186/s12944-020-01375-8
work_keys_str_mv AT shakibaeinajmeh pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy
AT hassannejadrazieh pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy
AT mohammadifardnoushin pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy
AT maratebhamidreza pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy
AT mansourianmarjan pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy
AT mananasmiguelangel pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy
AT sarrafzadegannizal pathwaysleadingtopreventionoffatalandnonfatalcardiovasculardiseaseaninteractionmodelon15yearspopulationbasedcohortstudy