Abstract
This study examines the importance of income in determining the diet quality of Canadian adults measured based on Nutrient Rich Food Index version 9.3. We used the latest available data on Canadians' consumption of foods and nutrients from the Canadian Community Health Survey-Nutrition 2015. The Canada' Food Guide classification was used for categorizing food groups based on types of food and their healthiness. Unsupervised and supervised machine learning models were employed in order to examine the links between income and the choice of foods. We first employed cluster analysis to identify the dietary patterns among individuals included in the sample and then we examined whether the intakes of various food groups across the identified clusters vary by income levels. Further, we evaluated the association between diet quality and income using Lasso Regression to determine the most important predictors of diet quality among adults in Canada. The results of both cluster analysis and regularized regression model suggested that behavioral factors and cultural backgrounds are more important determinants of diet quality among adults in Canada.