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Network Approach to Evaluate the Effect of Diet on Stroke or Myocardial Infarction Using Gaussian Graphical Model.

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This study used network analysis to find dietary patterns linked to stroke and myocardial infarction (MI) risk in Koreans. A High-Protein and Green Tea diet reduced risk, especially in women, while a Rice and High-Calorie Beverage diet increased MI risk.

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Area of Science:

  • Nutritional Epidemiology
  • Cardiovascular Disease Research
  • Network Analysis in Public Health

Background:

  • Traditional dietary research often overlooks complex eating patterns, focusing instead on individual foods.
  • Understanding dietary patterns is crucial for preventing cardiovascular diseases like stroke and myocardial infarction (MI).

Purpose of the Study:

  • To identify dietary patterns using network analysis in the Korean population.
  • To investigate the association between these dietary patterns and the incidence of stroke and/or MI.

Main Methods:

  • Employed Gaussian graphical models to identify dietary patterns and Cox proportional models to assess risk.
  • Utilized data from 84,729 participants in the Korean Genome and Epidemiological Study (KoGES).

Main Results:

  • Identified five distinct dietary patterns (communities) and nine unassociated food groups.
  • The High-Protein and Green Tea Community was associated with reduced stroke and MI risk, particularly in females.
  • A Rice and High-Calorie Beverages Community was linked to increased MI risk in the total population and females; no significant stroke associations were found in males for most communities.

Conclusions:

  • Network analysis reveals unique dietary patterns in the Korean population.
  • These findings offer novel insights into the relationship between dietary habits and cardiovascular disease risk.