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Int J Behav Nutr Phys Act. 2019 Aug 6;16(1):61. doi: 10.1186/s12966-019-0821-6.

Development and validation of a Brief Diet Quality Assessment Tool in the French-speaking adults from Quebec.

Author information

1
Institute of Nutrition and Functional Foods, Laval University, Québec, Canada.
2
School of Nutrition, Laval University, Québec, Canada.
3
Population Health and Optimal Health Practices Research Unit, CHU de Québec-Laval University Research Center, Québec, Canada.
4
Faculty of Pharmacy, Laval University, Québec, Canada.
5
Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, Québec, Canada.
6
Endocrinology and Nephrology unit, Centre de recherche du CHU de Québec, Laval University, Québec, Canada.
7
Institute of Nutrition and Functional Foods, Laval University, Québec, Canada. benoit.lamarche@fsaa.ulaval.ca.
8
School of Nutrition, Laval University, Québec, Canada. benoit.lamarche@fsaa.ulaval.ca.

Abstract

BACKGROUND:

The objective of this study was to develop and validate a short, self-administered questionnaire to assess diet quality in clinical settings, using the Alternative Healthy Eating Index (AHEI) as reference.

METHODS:

A total of 1040 men and women (aged 44.6 ± 14.4 y) completed a validated web-based food frequency questionnaire (webFFQ) and had their height and weight measured (development sample). Participants were categorized arbitrarily according to diet quality (high: AHEI score ≥ 65/110, low: AHEI score < 65/110) based on dietary intake data from the webFFQ. The Brief Diet Quality Assessment Tool was developed using a classification and regression tree (CART) approach and individual answers to the webFFQ among participants considered to have a plausible energy intake (ratio of reported energy intake to basal metabolic rate ≥ 1.2 and < 2.4; n = 1040). A second sample of 3344 older adults (aged 66.5 ± 6.4 y) was used to test the external validity of the Brief Diet Quality Assessment Tool (external validation sample).

RESULTS:

The decision tree included sequences of 3 to 6 binary questions, yielding 21 different pathways classifying diet quality as being high or low. In the development sample, the area under the receiver operating characteristic (ROC) curve of the predictive model was 0.92, with sensitivity, specificity and agreement values of 89.5, 83.9 and 87.2%. Compared with individuals having a low-quality diet according to the Brief Diet Quality Assessment Tool (mean AHEI 56.7 ± 11.4), individuals classified as having a high-quality diet (mean AHEI 71.3 ± 11.0) were significantly older, and had lower BMI, percent body fat and waist circumference, and had lower blood pressure, triglycerides, cholesterol/HDL ratio and fasting insulin as well as higher HDL-cholesterol concentrations (all P < 0.05). Similar results were observed in the external validation sample, although overall performance of the Brief Diet Quality Assessment Tool was slightly lower than in the development sample, with an area under the ROC curve of 0.79 and sensitivity, specificity and agreement values of 73.0, 69.0 and 71.3%, respectively.

CONCLUSION:

The CART approach yielded a simple and rapid Brief Diet Quality Assessment Tool that identifies individuals at risk of having a low-quality diet. Further studies are needed to test the performance of this tool in primary care settings.

KEYWORDS:

Alternative healthy eating index; Brief diet quality assessment tool; Classification and regression tree; Diet quality

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