Murakami Kentaro, Livingstone M Barbara E, Sasaki Satoshi, Hirota Naoko, Notsu Akiko, Miura Ayako, Todoriki Hidemi, Fukui Mitsuru, Date Chigusa
Department of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo, Japan.
Nutrition Innovation Centre for Food and Health, School of Biomedical Sciences, Ulster University, Coleraine, UK.
J Nutr Sci. 2018 Nov 13;7:e29. doi: 10.1017/jns.2018.21. eCollection 2018.
Data on the combination of foods consumed simultaneously at specific eating occasions are scarce, primarily due to a lack of assessment tools. We applied a recently developed meal coding system to multiple-day dietary intake data for assessing its ability to estimate food and nutrient intakes and characterise meal-based dietary patterns in the Japanese context. A total of 242 Japanese adults completed sixteen non-consecutive-day weighed dietary records, including 14 734 eating occasions (3788 breakfasts, 3823 lunches, 3856 dinners and 3267 snacks). Common food group combinations were identified by meal type to identify a range of generic meals. Dietary intake was calculated on the basis of not only the standard food composition database but also the substituted generic meal database. In total, eighty generic meals (twenty-three breakfasts, twenty-one lunches, twenty-four dinners and twelve snacks) were identified. The Spearman correlation coefficients between food group intakes calculated based on the standard food composition database and the substituted generic meal database ranged from 0·26 to 0·85 (median 0·69). The corresponding correlations for nutrient intakes ranged from 0·17 to 0·82 (median 0·61). A total of eleven meal patterns were established using principal components analysis, and these accounted for 39·1 % of total meal variance. Considerable variation in patterns was seen in meal type inclusion and choice of staple foods (bread, rice and noodles) and drinks, and also in meal constituents. In conclusion, this study demonstrated the usefulness of a meal coding system for assessing habitual diet, providing a scientific basis towards the development of simple meal-based dietary assessment tools.
关于特定用餐场合同时食用的食物组合的数据稀缺,主要是由于缺乏评估工具。我们将最近开发的膳食编码系统应用于多日膳食摄入数据,以评估其在日本背景下估计食物和营养素摄入量以及描述基于膳食的饮食模式的能力。共有242名日本成年人完成了16天不连续的称重膳食记录,包括14734个用餐场合(3788份早餐、3823份午餐、3856份晚餐和3267份零食)。通过膳食类型确定常见的食物组组合,以识别一系列通用膳食。膳食摄入量不仅根据标准食物成分数据库计算,还根据替代的通用膳食数据库计算。总共识别出80种通用膳食(23种早餐、21种午餐、24种晚餐和12种零食)。基于标准食物成分数据库和替代通用膳食数据库计算的食物组摄入量之间的斯皮尔曼相关系数在0.26至0.85之间(中位数为0.69)。营养素摄入量的相应相关性在0.17至0.82之间(中位数为0.61)。使用主成分分析建立了总共11种膳食模式,这些模式占膳食总方差的39.1%。在膳食类型包含、主食(面包、米饭和面条)和饮料的选择以及膳食成分方面,模式存在相当大的差异。总之,本研究证明了膳食编码系统在评估习惯性饮食方面的有用性,为开发简单的基于膳食的膳食评估工具提供了科学依据。