Evidence map›Paper›PMID 30459946›Full record

ArticleJournal of nutritional science2018

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.

Kentaro Murakami, M Barbara E Livingstone, Satoshi Sasaki, Naoko Hirota, Akiko Notsu, Ayako Miura, Hidemi Todoriki, Mitsuru Fukui, Chigusa Date

Abstract read
In one paragraph

Article in Journal of nutritional science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kentaro MurakamiDepartment of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo, Japan.
M Barbara E LivingstoneNutrition Innovation Centre for Food and Health, School of Biomedical Sciences, Ulster University, Coleraine, UK.
Satoshi SasakiDepartment of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo, Japan.
Naoko HirotaGraduate School of Health Science, Matsumoto University, Nagano, Japan.
Akiko NotsuDepartment of Food Science and Nutrition, Tottori College, Tottori, Japan.
Ayako MiuraDepartment of Health and Nutritional Sciences, Faculty of Health Promotional Sciences, Tokoha University, Shizuoka, Japan.
Hidemi TodorikiTropical Biosphere Research Center, University of the Ryukyus, Okinawa, Japan.
Mitsuru FukuiLaboratory of Statistics, Osaka City University Medical School, Osaka, Japan.
Chigusa DateDepartment of Food Science and Nutrition, School of Human Science and Environment, University of Hyogo, Hyogo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Food combinationsJapanMeal codingMeal patternsMealsPCA, principal components analysisPC, principal component

Identifiers

PMID30459946
PMCPMC6238120

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.