Institute of Nutrition and Functional Foods, Laval University, Québec, Canada.
School of Nutrition, Laval University, Québec, Canada.
Int J Behav Nutr Phys Act. 2019 Aug 6;16(1):61. doi: 10.1186/s12966-019-0821-6.
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.
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).
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.
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.
本研究旨在开发和验证一种简短的自我管理问卷，以评估临床环境中的饮食质量，使用替代健康饮食指数（AHEI）作为参考。
共有 1040 名男性和女性（年龄 44.6±14.4 岁）完成了经过验证的基于网络的食物频率问卷（webFFQ），并测量了他们的身高和体重（开发样本）。根据 webFFQ 的饮食摄入数据，参与者根据饮食质量任意分为两组（高：AHEI 评分≥65/110，低：AHEI 评分<65/110）。使用分类回归树（CART）方法和参与者中报告的能量摄入与基础代谢率之比≥1.2 和<2.4 的合理能量摄入的个体答案（n=1040）开发了简要饮食质量评估工具。第二项 3344 名老年人（年龄 66.5±6.4 岁）的样本用于测试简要饮食质量评估工具的外部有效性（外部验证样本）。
决策树包括 3 到 6 个二进制问题的序列，产生 21 种不同的路径，将饮食质量分类为高或低。在开发样本中，预测模型的接收者操作特征（ROC）曲线下面积为 0.92，敏感性、特异性和一致性值分别为 89.5%、83.9%和 87.2%。与根据简要饮食质量评估工具被归类为低质量饮食的个体（平均 AHEI 56.7±11.4）相比，被归类为高质量饮食的个体（平均 AHEI 71.3±11.0）年龄更大，BMI、体脂百分比和腰围更低，血压、甘油三酯、胆固醇/高密度脂蛋白比值和空腹胰岛素水平更低，高密度脂蛋白胆固醇浓度更高（所有 P<0.05）。在外部验证样本中也观察到了类似的结果，尽管简要饮食质量评估工具的整体性能略低于开发样本，ROC 曲线下面积为 0.79，敏感性、特异性和一致性值分别为 73.0%、69.0%和 71.3%。
CART 方法产生了一种简单快捷的简要饮食质量评估工具，可以识别出饮食质量低的个体。需要进一步的研究来测试该工具在初级保健环境中的性能。
