Evidence mapPaperPMID 40346772Full record

ArticleMolecular nutrition & food research2025

Consumption of Ultra-Processed Food and Risk of Non-Alcoholic Fatty Liver Disease: A Prospective Analysis of the Korean Genome and Epidemiology Study.

Jialei Fu, Li-Juan Tan, Sangah Shin

Abstract read
In one paragraph

Article in Molecular nutrition & food research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
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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

3 authors.

Jialei FuVanke School of Public Health, Tsinghua University, Beijing, China.
Li-Juan TanDepartment of Critical Care Medicine, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0002-8970-0884
Sangah ShinDepartment of Food and Nutrition, Chung-Ang University, Gyeonggi-do, South Korea.ORCID 0000-0003-0094-1014

Funding

Korea government (MSIT) RS-2025-00556573National Research Foundation of Korea
6 · The paper itself

Abstract

The association between ultra-processed foods (UPFs) consumption and non-alcoholic fatty liver disease (NAFLD) remains unclear; therefore, we investigated the association between UPF consumption and the risk of NAFLD among Korean adults. This cohort study included 44 642 Korean adults aged 40-69 years, utilizing data from the Health Examinees database. UPF were categorized according to the NOVA classification system based on the degree of processing. A multivariable Cox proportional hazards model assessed the association between UPF consumption and NAFLD risk. Over a 4.2-year follow-up period, 1562 (3.5%) participants developed NAFLD. After adjusting for potential confounders, higher UPF consumption was associated with a 35% (6%, 71%) and 48% (19%, 86%) increased risk of NAFLD in men and women, respectively. Similar results were observed in both continuous and sensitivity analyses. Among the diverse UPF subtypes, ramen consumption showed the strongest adverse association with NAFLD risk in both men and women (hazard ratio = 2.05 [1.59, 2.65] in men; 1.80 [1.48, 2.19] in women). Our findings suggest that higher UPF consumption is linked to an increased risk of NAFLD. Further comprehensive investigations in a broader spectrum of populations are warranted to corroborate and fortify these results.

Indexed as

Fast FoodsNon-alcoholic Fatty Liver DiseaseAdultAgedDietFemaleFood, ProcessedHumansMaleMiddle AgedProportional Hazards ModelsProspective StudiesRepublic of KoreaRisk FactorsfoodhepatocytesKoreanon‐alcoholic fatty liver diseaseprocessed

Identifiers

PMID40346772
PMCPMC12236129

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.