Principal component analysis (PCA) is a data reduction where new dietary pattern variables are derived on the basis of the correlation matrix of the original food variables. The use of principal components analysis to derive dietary patterns requires several arbitrary choices such as the original variables to include and the number of dietary patterns to identify. A component of PCA, is factor analysis or cluster analysis which is a data driven approach that uses mathematics to derive food intake patterns . Data used come from food frequency questionnaires (FFQs), 24-hour recalls and diet records. Individuals receive factor scores for each derived factor. More specifically cluster analysis derives patterns by aggregating individuals based
