title: Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.
abstract: BACKGROUND
  Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition.
  
  
  METHODS
  This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition.
  
  
  RESULTS
  At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern.
  
  
  CONCLUSIONS
  Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions.
authors: School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands; Department of Health Promotion, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands. Electronic address: michel.walthouwer@maastrichtuniversity.nl.
authors: Michel Jean Louis
authors: MJ
authors: Walthouwer
authors: School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands; Department of Health Promotion, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
authors: Anke
authors: A
authors: Oenema
authors: School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands; Department of Health Promotion, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
authors: Katja
authors: K
authors: Soetens
authors: School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands; Department of Psychology, Open University of the Netherlands, P.O. Box 2960, 6419 AT Heerlen, The Netherlands.
authors: Lilian
authors: L
authors: Lechner
authors: School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands; Department of Health Promotion, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
authors: Hein
authors: H
authors: de Vries
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D016000:Cluster Analysis; D004032:Diet / Q000639:trends*; D002149:Energy Intake; D005247:Feeding Behavior; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D055815:Young Adult
keywords: Adults; Cluster analysis; Determinants; Dietary patterns; Longitudinal study