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

Int J Food Sci Nutr. 2019 Sep;70(6):738-748. doi: 10.1080/09637486.2019.1566445. Epub 2019 Feb 22.

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

MeSH terms

  • Factor Analysis, Statistical
  • Food
  • Food Analysis*
  • Humans
  • Models, Statistical
  • Nutrients / analysis*
  • Principal Component Analysis / methods*
  • Psychometrics
  • Surveys and Questionnaires