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Dietary Patterns in ALSPAC Cohort: Cluster Analysis Insights from the 2011 EUCCONET Workshop

This presentation by Andrew Smith and colleagues at the EUCCONET International Workshop discusses the clustering of dietary patterns using data from the ALSPAC cohort. It highlights methods like Principal Component Analysis (PCA) and k-means clustering to examine dietary intake through food frequency questionnaires (FFQs) and diet diaries. The analysis covers a substantial sample size, revealing three main dietary clusters: Processed, Plant-based, and Traditional British. The findings showcase both the strengths and limitations of dietary pattern analysis in relation to childhood health outcomes.

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Dietary Patterns in ALSPAC Cohort: Cluster Analysis Insights from the 2011 EUCCONET Workshop

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  1. Andrew Smith Dietary patterns in the ALSPAC cohort: Cluster analysis EUCCONET International Workshop 18th October 2011

  2. Andrew Smith Pauline EmmettP. K. NewbyKate Northstone World Cancer Research Fund Dietary patterns in the ALSPAC cohort: Cluster analysis

  3. Dietary patterns • Examine diet as a whole • Start with many variables(e.g. FFQ, diet diary) • Express as a small number of variables Image: Paul / FreeDigitalPhotos.net

  4. Principal components analysis (PCA) • Examine diet as a whole • Start with many variables(e.g. FFQ, diet diary) • Use correlations between foods • Express as a small number of components Image: Paul / FreeDigitalPhotos.net

  5. Cluster analysis • Examine diet as a whole • Start with many variables(e.g. FFQ, diet diary) • Use similarities between people • Express as a small number of clusters Image: Paul / FreeDigitalPhotos.net

  6. Dietary patterns studies in ALSPAC

  7. Case study: PCA of FFQ age 7 Junk Northstone and Emmett, 2005 Traditional Health conscious Image: Suat Eman, winnond / FreeDigitalPhotos.net

  8. Dietary patterns studies in ALSPAC

  9. Cluster analysis • k-means is most widely-used method • Must avoid pitfalls • Standardization • Algorithm • Reliability Image: Boaz Yiftach / FreeDigitalPhotos.net

  10. Dietary patterns studies in ALSPAC

  11. Case study: cluster analysis of FFQ age 7 • FFQ administered to ALSPAC children at 81 months of age • Input variables are the same as PCA (Northstone, Emmett et al. 2005) • 8,279 children • 3 clusters • Smith et al. 2011

  12. Case study: cluster analysis of FFQ age 7

  13. Similarities with PCA

  14. Cluster analysis of diet diary data • 7473 children aged 10 • Advantages • Similar 3-cluster solution(Processed, Plant-based, Traditional British) • Good separation between clusters • Disadvantages • Not robust to under-reporting • PCA shows better associations with fat mass

  15. Dietary patterns studies in ALSPAC

  16. Dietary patterns studies in ALSPAC

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