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Empirically derived eating patterns using factor or cluster analysis: a review.

P K Newby1, Katherine L Tucker

  • 1Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA. pknewby@post.harvard.edu

Nutrition Reviews
|June 24, 2004
PubMed
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This review of 93 studies shows that cluster or factor analysis can identify dietary patterns linked to health outcomes. Both methods reveal eating patterns, suggesting refinement will establish them as a robust dietary assessment tool.

Area of Science:

  • Nutritional epidemiology
  • Dietary assessment methods

Background:

  • Empirical derivation of eating patterns is crucial for nutritional research.
  • Cluster and factor analysis are statistical methods used to define dietary patterns.

Purpose of the Study:

  • To review studies employing cluster or factor analysis to derive eating patterns.
  • To assess the association between eating patterns and disease outcomes or biomarkers.

Main Methods:

  • Systematic review of studies published since 1980 using cluster or factor analysis.
  • Analysis of 93 studies, with 65 examining associations between dietary patterns and health outcomes.

Main Results:

  • Numerous studies across diverse populations utilize these methods to define dietary exposures.

Related Experiment Videos

  • Identified eating patterns are associated with various biomarkers and disease outcomes.
  • Both cluster and factor analysis appear to reveal underlying eating patterns.

    • Conclusions:

    • Cluster and factor analysis are valuable for identifying eating patterns.
    • Further refinement of these analytical methods will strengthen their utility in dietary assessment.
    • A significant body of literature supports the use of these methods in nutritional epidemiology.