Network Approach to Evaluate the Effect of Diet on Stroke or Myocardial Infarction Using Gaussian Graphical Model
Jaca Maison Lailo, Jiae Shin, Giulia Menichetti, Sang-Ah Lee

TL;DR
This study uses a network approach to analyze how different dietary patterns in the Korean population are linked to the risk of stroke and heart attack.
Contribution
The study introduces a novel network-based method using Gaussian graphical models to identify dietary patterns and their health impacts.
Findings
Five dietary patterns were identified, with the High-Protein and Green Tea pattern reducing stroke and MI risk in females.
The Rice and High-Calorie Beverages pattern increased MI risk in both the total population and females.
Most dietary patterns showed no significant association with stroke risk in males.
Abstract
Background/Objectives/Methods: Current research on the link between diet and stroke or myocardial infarction primarily focuses on individual food items. However, people’s eating habits involve complex combinations of various foods. By employing an innovative approach known as the Gaussian graphical model to identify dietary patterns along with the Cox proportional model, the study aimed to identify dietary networks and explore their relationship with the incidence of stroke and/or myocardial infarction in the Korean population. The research utilized data from 84,729 participants in the Korean Genome and Epidemiological Study (KoGES), including the HEXA cohort (61,140 participants), CAVAS cohort (15,419 participants), and Ansan-Ansung cohort (8170 participants). Results: The network identified five dietary patterns or communities consisting of different food groups, while nine food…
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Taxonomy
TopicsNutritional Studies and Diet · Diet and metabolism studies · Cardiovascular Health and Risk Factors
