Evidence map›Paper›PMID 36904297›Full record

ArticleNutrients2023

Highly Processed Food Consumption and Its Association with Anthropometric, Sociodemographic, and Behavioral Characteristics in a Nationwide Sample of 2742 Japanese Adults: An Analysis Based on 8-Day Weighed Dietary Records.

Nana Shinozaki, Kentaro Murakami, Shizuko Masayasu, Satoshi Sasaki

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In one paragraph

Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Ecological momentary assessment of meal context and food types contributing to salt intake at meals.The international journal of behavioral nutrition and physical activity · 2025
    Article
  3. Article
  4. Article
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

4 authors.

Nana ShinozakiDepartment of Social and Preventive Epidemiology, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Kentaro MurakamiDepartment of Social and Preventive Epidemiology, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.ORCID 0000-0002-4189-7753
Shizuko MasayasuIkurien-naka, 3799-6 Sugaya, Naka-shi 311-0105, Ibaraki, Japan.
Satoshi SasakiDepartment of Social and Preventive Epidemiology, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.

Funding

Ministry of Health, Labour and Welfare 20KA1009
6 · The paper itself

Abstract

This cross-sectional study assessed highly processed food (HPF) consumption and its association with individual characteristics in a nationwide sample of Japanese adults. Eight-day weighed dietary records were obtained from 2742 free-living adults aged 18-79 years across Japan. HPFs were identified based on a classification method developed by researchers at the University of North Carolina at Chapel Hill. The basic characteristics of the participants were assessed using a questionnaire. On average, HPF contributed to 27.9% of daily energy intake. The contribution of HPF to the daily intake of 31 nutrients ranged from 5.7% for vitamin C to 99.8% for alcohol (median, 19.9%). Cereals and starchy foods were the main food groups that contributed to the total energy intake of HPF. Multiple regression analysis showed that the older group (60-79 years) had a lower HPF energy contribution than the younger group (18-39 y) (regression coefficient (β) = -3.55,

Indexed as

DietFood, ProcessedAdultCross-Sectional StudiesDiet RecordsEast Asian PeopleEnergy IntakeFast FoodsFood HandlingHumansVitaminsVitaminsdietary recordhighly processed foodsJapanJapaneseultra-processed foods

Identifiers

PMID36904297
PMCPMC10005625

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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.