Relative validity of an intelligent ordering system to estimate dietary intake among university students from a medical school in Shanghai, China.

IF 5.6 1区 医学 Q1 NUTRITION & DIETETICS International Journal of Behavioral Nutrition and Physical Activity Pub Date : 2024-07-04 DOI:10.1186/s12966-024-01619-1
Yimeng Zhang, Dantong Gu, Mengyun Luo, Shaojie Liu, Hong Peng, Yingnan Jia
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Abstract

Background: Dietary assessment methods have limitations in capturing real-time eating behaviour accurately. Equipped with automated dietary-data-collection capabilities, the "intelligent ordering system" (IOS) has potential applicability in obtaining long-term consecutive, relatively detailed on-campus dietary records among university students with little resource consumption. We investigated (1) the relative validity of IOS-derived nutrient/food intakes compared to those from the 7-day food diary (7DFD); (2) whether including a supplemental food frequency questionnaire (SFFQ) improves IOS accuracy; and (3) sex differences in IOS dietary intake estimation.

Methods: Medical students (n = 221; age = 22.2 ± 2.4 years; 38.5% male and 61.5% female) completed the 7DFD and SFFQ. During the consecutive 7-day survey period, students weighed and photographed each meal before and after consumption. Then, students reviewed their 3-month diet and completed the SFFQ, which includes eight underprovided school-canteen food items (e.g., dairy, fruits, nuts). Meanwhile, 9385 IOS dietary data entries were collected. We used Spearman coefficients and linear regression models to estimate the associations among the different dietary intake assessment methods. Individual- and group-level agreement was assessed using the Wilcoxon signed-rank test, cross-classification, and Bland‒Altman analysis.

Results: IOS mean daily energy, protein, fat, and carbohydrate intake estimations were significantly lower (-15-20%) than those of the 7DFD. The correlation coefficients varied from 0.52 (for added sugar) to 0.88 (for soybeans and nuts), with fruits (0.37) and dairy products (0.29) showing weaker correlations. Sixty-two (milk and dairy products) to 97% (soybeans and nuts) of participants were classified into the same or adjacent dietary intake distribution quartile using both methods. The energy and macronutrient intake differences between the IOS + SFFQ and 7DFD groups decreased substantially. The separate fruit intake measurements from each assessment method did not significantly differ from each other (p > 0.05). IOS and IOS + SFFQ regression models generally yielded higher R2 values for males than for females.

Conclusion: Despite estimation differences, the IOS can be reliable for medical student dietary habit assessment. The SFFQ is useful for measuring consumption of foods that are typically unavailable in school cafeterias, improving the overall dietary evaluation accuracy. The IOS assessment was more accurate for males than for females.

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智能点餐系统对中国上海某医学院校大学生膳食摄入量估算的相对有效性。
背景:饮食评估方法在准确捕捉实时饮食行为方面存在局限性。智能点餐系统"(IOS)具有自动收集膳食数据的功能,可用于在消耗少量资源的情况下获得大学生长期连续、相对详细的校内膳食记录。我们研究了(1)与 7 天食物日记(7DFD)相比,IOS 得出的营养素/食物摄入量的相对有效性;(2)加入补充食物频率问卷(SFFQ)是否能提高 IOS 的准确性;以及(3)IOS 膳食摄入量估算的性别差异:医学生(n = 221;年龄 = 22.2 ± 2.4 岁;男生占 38.5%,女生占 61.5%)完成 7DFD 和 SFFQ。在连续 7 天的调查期间,学生们对每餐进食前后进行称重和拍照。然后,学生们回顾了自己 3 个月的饮食情况,并填写了 SFFQ,其中包括 8 种学校食堂供应不足的食品(如奶制品、水果、坚果)。同时,我们还收集了 9385 项 IOS 饮食数据。我们使用斯皮尔曼系数和线性回归模型来估计不同膳食摄入量评估方法之间的关联。使用 Wilcoxon 符号秩检验、交叉分类和 Bland-Altman 分析评估了个体和群体层面的一致性:结果:IOS的日平均能量、蛋白质、脂肪和碳水化合物摄入量估计值明显低于7DFD(-15%-20%)。相关系数从 0.52(添加糖)到 0.88(大豆和坚果)不等,水果(0.37)和奶制品(0.29)的相关性较弱。使用这两种方法,62%(牛奶和乳制品)到 97%(大豆和坚果)的参与者被归入相同或相邻的膳食摄入分布四分位数。IOS + SFFQ 组和 7DFD 组之间的能量和宏量营养素摄入量差异大幅缩小。每种评估方法分别测量的水果摄入量没有显著差异(P > 0.05)。IOS和IOS + SFFQ回归模型对男性的R2值普遍高于女性:结论:尽管存在估计差异,但 IOS 仍可用于医学生饮食习惯评估。SFFQ可用于测量学校食堂通常没有的食物的摄入量,从而提高整体饮食评估的准确性。与女生相比,男生的 IOS 评估更为准确。
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来源期刊
CiteScore
13.80
自引率
3.40%
发文量
138
审稿时长
4-8 weeks
期刊介绍: International Journal of Behavioral Nutrition and Physical Activity (IJBNPA) is an open access, peer-reviewed journal offering high quality articles, rapid publication and wide diffusion in the public domain. IJBNPA is devoted to furthering the understanding of the behavioral aspects of diet and physical activity and is unique in its inclusion of multiple levels of analysis, including populations, groups and individuals and its inclusion of epidemiology, and behavioral, theoretical and measurement research areas.
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