Xu Xiaowei, Wang Ju, Hou Li, Guo Zhen, Li Jiao
Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Beijing, China.
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
JMIR Mhealth Uhealth. 2018 Aug 14;6(8):e166. doi: 10.2196/mhealth.7674.
Dietary management is important for personal health. However, it is challenging to record quantified food information in an efficient, accurate, and sustainable manner, particularly for the consumption of Chinese food.
The objective of this study was to develop a dietary management system to record information on consumption of Chinese food, which can help in assessing individuals' dietary intake and maintaining healthy eating behaviors. We proposed to use plates embedded with radio-frequency identification chips to carry Chinese foods and collect food consumption data.
We obtained food composition and nutrient (eg, carbohydrate, fat, fiber) data from the Chinese Recipe Database and China Food Composition Database. To test the feasibility of the dietary management system at a population level, we applied it to collect data on 489 Chinese foods that were consumed at lunchtime across 7 weeks by 10,528 individuals. To test individual-level output, we selected an individual participant with completed 20-day dietary data for analysis. We examined the system's nutrient calculation performance by comparing the nutrient values of 3 selected Chinese dishes calculated by our method with the results of chemical measurements.
We collected the dietary intake for a group of 10,528 individuals aged from 20 to 40 years having lunch in a restaurant across 7 weeks. A total of 489 Chinese dishes were identified. We analyzed a specified customer's diet recordings and broke his or her 20 lunch diet recordings down to ingredients and then to nutrient intake. We compared the nutrient value of a given Chinese dish (eg, garlic puree cooked pork leg) calculated by our method with the results of chemical measurements. The mean absolute percentage deviation showed that our method enabled collection of dietary intake for Chinese foods.
This preliminary study demonstrated the feasibility of radio-frequency identification-based dietary management for Chinese food consumption. In future, we will investigate factors such as preparation method, weight of food consumed, and auxiliary ingredients to improve dietary assessment accuracy.
饮食管理对个人健康很重要。然而，以高效、准确和可持续的方式记录量化的食物信息具有挑战性，尤其是对于中餐的消费情况。
本研究的目的是开发一种饮食管理系统，用于记录中餐的消费信息，这有助于评估个人的饮食摄入量并维持健康的饮食行为。我们提议使用嵌入射频识别芯片的盘子来盛放中餐并收集食物消费数据。
我们从《中国菜谱数据库》和《中国食物成分数据库》中获取了食物成分和营养素（如碳水化合物、脂肪、纤维）数据。为了在人群层面测试饮食管理系统的可行性，我们应用该系统收集了10528名个体在7周内午餐时食用的489种中餐的数据。为了测试个体层面的输出结果，我们选择了一名有完整20天饮食数据的个体参与者进行分析。我们通过比较我们的方法计算出的3种选定中餐菜肴的营养素值与化学测量结果，来检验该系统的营养素计算性能。
我们收集了10528名年龄在20至40岁之间的个体在一家餐厅7周内午餐的饮食摄入量。共识别出489种中餐菜肴。我们分析了一位特定顾客的饮食记录，将其20次午餐饮食记录分解为食材，然后再分析营养素摄入量。我们将我们的方法计算出的一道给定中餐菜肴（如蒜泥白肉）的营养素值与化学测量结果进行了比较。平均绝对百分比偏差表明我们的方法能够收集中餐的饮食摄入量。
这项初步研究证明了基于射频识别的中餐消费饮食管理的可行性。未来，我们将研究诸如制备方法、食物食用重量和辅助食材等因素，以提高饮食评估的准确性。
