Food or nutrient pattern assessment using the principal component analysis applied to food questionnaires. Pitfalls, tips and tricks

Abstract

We considered the Blom’s transformation, a statistical method aimed to normalise and standardise food intakes before principal component analysis. A simulation study was performed to evaluate the eigenvalue distribution of a correlation matrix under common conditions in food questionnaire analysis. The scree plot visual inspection and the Guttman–Kaiser (GK) criterion were compared to Horn’s parallel analysis to evaluate their efficacy in food pattern identification. The scree plot results as a monotone continuous series when no food patterns are present. In this situation, about 50% of the eigenvalues assume a value higher than one, showing a first fallacy of the GK. When three food patterns are simulated a clear discontinuity appears after the third eigenvalue, showing that the scree-plot visual inspection is a suitable method to identify food patterns. Finally, according to the present work it appears that the GK generates a number of false-positive food patterns.

Keywords:

• Principal component analysis
• foods/nutrients pattern recognition
• food intake questionnaires
• scree plot visual inspection
• Guttman–Kaiser criterion

Acknowledgements

The present work was inspired by the wisdom and great charisma of professor Silvano Milani, recently deceased.

Disclosure statement

The authors have no conflict of interest to declare. The present work has to be considered as spontaneous research and no one of the authors received any grant.