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Area of Science:

  • Nutritional Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Dietary patterns are frequently derived using principal component analysis (PCA) and cluster analysis.
  • Determining the optimal number of dietary patterns is often subjective, leading to variability in food composition and disease associations.
  • Limited research exists on the reliability of different dietary pattern solutions.

Purpose of the Study:

  • To assess the reliability of various dietary pattern solutions (2-6 patterns) derived using PCA and cluster analysis.
  • To evaluate the influence of different pattern solutions on disease outcome associations, specifically coronary heart disease.
  • To determine the utility of quantitative criteria for selecting the number of patterns.

Main Methods:

  • Utilized data from 39,678 participants in the European Prospective Investigation into Cancer and Nutrition-The Netherlands (EPIC-NL) cohort.
  • Employed principal component analysis (PCA) and cluster analysis to derive dietary patterns from 31 food groups.
  • Assessed PCA solution reliability via confirmatory factor analysis in a split sample; evaluated cluster analysis stability and reproducibility.

Main Results:

  • PCA: The 3-component solution showed best replication, but all solutions had poorly confirmed components; disease associations varied significantly.
  • Cluster Analysis: All solutions demonstrated excellent stability and reproducibility; quantitative criteria consistently identified the 2-cluster solution as optimal.
  • Disease associations were comparable across different cluster solutions, unlike PCA.

Conclusions:

  • Dietary pattern reliability differs substantially between PCA and cluster analysis solutions.
  • Cluster analysis provides generally stable and reproducible patterns, with quantitative criteria proving valuable for selection.
  • The number of retained patterns, particularly with PCA, influences disease risk associations, necessitating transparent reporting of selection criteria.