title: Food intake patterns and body mass index in observational studies.
abstract: OBJECTIVE
  To review studies of patterns of food intake, as assessed by diet index, factor analysis or cluster analysis, and their associations with body mass index or obesity (BMI/Ob).
  
  
  METHODS
  Systematic literature review MEDLINE search with crosscheck of references.
  
  
  METHODS
  Thirty observational studies relating food intake patterns to anthropometric information were identified and reviewed. Food intake patterns were defined using a diet index, factor or cluster analysis in 12, nine and nine studies, respectively. Measures of body mass were made concurrently with the diet assessment in all studies, and only in a few cases were the primary outcomes related to BMI/Ob.
  
  
  RESULTS
  The food intake patterns identified could, in most factor or cluster analysis studies, be categorised as: (a) meat, fatty, sweet or energy dense foods; (b) vegetables, fruit, whole grain and low-fat foods; or (c) by high alcohol consumption. The diet indexes were designed to capture a high diversity and/or food combinations matching the recommendations. The relationships with BMI/Ob were inconsistent-ten studies found that intake patterns, which we categorised as fatty, sweet or energy dense were positively associated with BMI/Ob, while similar patterns in four other studies were negatively associated with BMI. The significant associations between diet index score and BMI/Ob were consistently negative, while the associations between factor scores or cluster membership and BMI/Ob were less clear in terms of food intake pattern. Men and women had similar food intake patterns, but food intake patterns were less often positively associated with BMI/Ob in women. In 11 studies, there were no significant associations between food intake pattern and BMI/Ob.
  
  
  CONCLUSIONS
  This review showed that no consistent associations could be identified between BMI or Ob and food intake patterns, derived from diet index, factor analysis or cluster analysis. However, the heterogeneity of food intake patterns identified by such analyses and the lack of gold standards for the application of these techniques hampers consistent analysis of a relation between food intake patterns and health.
authors.affiliation: Centre for Preventive Medicine, Research Unit for Dietary Studies, Glostrup University Hospital, Glostrup, Denmark. peto@glostruphosp.kbhamt.dk
authors.forename: P
authors.initials: P
authors.lastname: Togo
authors.forename: M
authors.initials: M
authors.lastname: Osler
authors.forename: T I
authors.initials: TI
authors.lastname: Sørensen
authors.forename: B L
authors.initials: BL
authors.lastname: Heitmann
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D004032:Diet; D015930:Diet Records; D005163:Factor Analysis, Statistical; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D016239:MEDLINE; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology / Q000209:etiology*