title: Empirically derived eating patterns using factor or cluster analysis: a review.
abstract: This paper reviews studies performed to date that have employed cluster or factor analysis to empirically derive eating patterns. Since 1980, at least 93 studies were published that used cluster or factor analysis to define dietary exposures, of which 65 were used to test hypotheses or examine associations between patterns and disease outcomes or biomarkers. Studies were conducted in diverse populations across many countries and continents and suggest that patterns are associated with many different biomarkers and disease outcomes, whether measured by cluster or factor analysis. Despite clear differences in approaches and interpretations, there is some evidence that underlying eating patterns are revealed by either method. Although the research considered herein has created a meaningful body of literature, refining both the factor and cluster analysis methods will help to further establish eating patterns as a sound dietary assessment method.
authors.affiliation: Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA. pknewby@post.harvard.edu
authors.forename: P K
authors.initials: PK
authors.lastname: Newby
authors.forename: Katherine L
authors.initials: KL
authors.lastname: Tucker
mesh_terms: D016000:Cluster Analysis; D004032:Diet; D005163:Factor Analysis, Statistical; D005518:Food Preferences; D006304:Health Status; D006801:Humans; D015596:Nutrition Assessment; D012107:Research Design