Applying a meal coding system to 16-d weighed dietary record data in the Japanese context: towards the development of simple meal-based dietary assessment tools. (13th November 2018)

• Record Type: Journal Article
• Authors: Murakami, Kentaro; Livingstone, M. Barbara E.; Sasaki, Satoshi; Hirota, Naoko; Notsu, Akiko; Miura, Ayako; Todoriki, Hidemi; Fukui, Mitsuru; Date, Chigusa
• Is Part Of: Journal of nutritional science. Volume 7(2018)
• Publication Date: 2018-11-13
• Subjects: Meals, -- Meal coding, -- Meal patterns, -- Food combinations, -- Japan; Nutrition -- Periodicals; 612.305
• DOI: 10.1017/jns.2018.21
• Languages: English
• ISSNs: 2048-6790

Abstract

Abstract: 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.