Development and Evaluation of the Dietary Pattern Calculator (DiPaC) for Personalized Assessment and Feedback

Abstract

This study aimed to develop and validate a diet assessment screener - the Dietary Pattern Calculator (DiPaC). A scoping review identified currently available short diet quality assessment tools. Twenty-one articles covering 19 unique tools were included. The current tools mainly focused on individual nutrients or food groups or were developed for a specific population, and few ascertained overall dietary patterns. The 24-hour dietary recalls from the nationally representative Canadian Community Health Survey (CCHS)-Nutrition 2015 (n = 13,958) were used to derive and validate a personalized dietary pattern informed by the scoping review using weighted partial least squares. The dominant dietary pattern in CCHS-Nutrition 2015 was characterized by high consumption of fast foods, carbonated drinks, and salty snacks and low consumption of whole fruits, orange vegetables, other vegetables and juices, whole grains, dark green vegetables, legumes, and soy. The dietary pattern assessment was used to create and evaluate DiPaC following an agile and user-centred research and development approach. DiPaC, which demonstrated high validity and intermediate reliability (internal consistency = 0.47-0.51), is publicly available at https://www.projectbiglife.ca/. DiPaC can be used by the public, clinicians, and researchers for quick and robust assessment of diet quality, providing immediate feedback with the advantage of being easy to implement.

Keywords: Canadian population; calculatrice Web; diet quality; dietary patterns; modèles alimentaires; moindres carrés partiels; outils d’évaluation de l’alimentation courts; partial least squares; population canadienne; qualité de l’alimentation; short dietary assessment screeners; web-based calculator.