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Longitudinal comparisons of dietary patterns derived by cluster analysis in 7- to 13-year-old children

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)2050-2058
Number of pages9
JournalBritish Journal of Nutrition
Volume109
Issue number11
Early online date15 Oct 2012
DOIs
DateE-pub ahead of print - 15 Oct 2012
DatePublished (current) - Jun 2013

Abstract

Little is known about changes in dietary patterns over time. The present study aims to derive dietary patterns using cluster analysis at three ages in children and track these patterns over time. In all, 3 d diet diaries were completed for children from the Avon Longitudinal Study of Parents and Children at 7, 10 and 13 years. Children were grouped based on the similarities between average weight consumed (g/d) of sixty-two food groups using k-means cluster analysis. A total of four clusters were obtained at each age, with very similar patterns being described at each time point: Processed (high consumption of processed foods, chips and soft drinks), Healthy (high consumption of high-fibre bread, fruit, vegetables and water), Traditional (high consumption of meat, potatoes and vegetables) and Packed Lunch (high consumption of white bread, sandwich fillings and snacks). The number of children remaining in the same cluster at different ages was reasonably high: 50 and 43% of children in the Healthy and Processed clusters, respectively, at age 7 years were in the same clusters at age 13 years. Maternal education was the strongest predictor of remaining in the Healthy cluster at each time point – children whose mothers had the highest level of education were nine times more likely to remain in that cluster compared to those with the lowest. Cluster analysis provides a simple way of examining changes in dietary patterns over time, and similar underlying patterns of diet at two ages during late childhood, that persisted through to early adolescence.

    Research areas

  • Adolescent, Adult, Child, Cluster Analysis, Diet, Diet Records, Educational Status, Female, Food Analysis, Food Habits, Humans, Longitudinal Studies, Male, Mothers, Young Adult

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