A comparison of three statistical methods applied in the identification of eating patterns

Abstract

This work aimed to compare the results of three statistical methods applied in the identification of dietary patterns. Data from 1,009 adults between the ages of 20 and 65 (339 males and 670 females) were collected in a population-based cross-sectional survey in the Metropolitan Region of Rio de Janeiro, Brazil. Information on food consumption was obtained using a semi-quantitative food frequency questionnaire. A factor analysis, cluster analysis, and reduced rank regression (RRR) analysis were applied to identify dietary patterns. The patterns identified by the three methods were similar. The factor analysis identified "mixed", "Western", and "traditional" eating patterns and explained 35% of the data variance. The cluster analysis identified "mixed" and "traditional" patterns. In the RRR, the consumption of carbohydrates and lipids were included as response variables and again "mixed" and "traditional" patterns were identified. Studies comparing these methods can help to inform decisions as to which procedures best suit a specific research scenario.