Evidence map›Paper›PMID 41245532›Full record

ArticleEClinicalMedicine2025

Association between different dietary patterns and the risk of major brain disorders: a prospective multi-cohort study.

Yisen Shi, Yixiang Lin, Yiling Zheng, Xinxi Yu, Binfan Ou, Kaitai Yang, Fabin Lin, Xinyang Zou, Jiayi Zheng, Ruitian Zeng and 5 more

Abstract read
In one paragraph

Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 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, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. 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

15 authors.

Yisen ShiDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Yixiang LinDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Yiling ZhengDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Xinxi YuDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Binfan OuDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Kaitai YangDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Fabin LinDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Xinyang ZouDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Jiayi ZhengDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Ruitian ZengDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Xuan LinDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Qinyong YeDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Lina ChenDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Yuqi ZengDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
Guoen CaiDepartment of Neurology, Institute of Clinical Neurology, Centre for Cognitive Neurology, Fujian Medical University Union Hospital, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: While diverse dietary patterns are emerging from nutritional research, comprehensive comparisons of their effects on brain health are lacking. Furthermore, the underlying biological mechanisms through which diet influences neurological and psychiatric outcomes remain largely unclear. Methods: Using data from the UK Biobank, a large-scale prospective cohort (with participant enrolled between April, 2009, and June, 2012), we used Cox proportional hazards models to analyse the associations between ten dietary patterns (including the Mediterranean diet, the Dietary Approaches to Stop Hypertension (DASH) diet, and the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet, the alternative healthy eating index (AHEI), the healthful plant-based dietary index (hPDI), the planetary health diet index (PHDI), the healthy low-carbohydrate diet (HLCD), the healthy low-fat diet (HLFD), the dietary index for gut microbiota (DI-GM), and the reversed energy-adjusted diet inflammatory index (rEDII)) and ultra-processed food (UPF) intake with the incident risk of five major brain disorders, including dementia, stroke, depression, anxiety, and Parkinson's disease (PD) in participants with available dietary data who were free of major brain disorders at baseline. The most neuroprotective diet identified was then validated for its associations with a range of brain health outcomes in the U.S. Health and Retirement Study (HRS, with participant data collected between 2013 and 2014) and the Chinese Longitudinal Healthy Longevity Survey (CLHLS, with participant data collected in 2018) using generalized linear models to analyze the data. Participants from these two cohorts were required to have complete data on diet, outcomes, and covariates. Finally, we employed a four-way decomposition model with multi-omics data as mediators to explore the underlying mechanisms. Findings: In the UK Biobank cohort (N = 166,916), MIND diet demonstrated the broadest neuroprotective effects. Over a median follow-up of 10·5 years, 1870 participants were diagnosed with dementia, 980 with PD, 3121 with stroke, 5113 with depression, and 5697 with anxiety. Adherence to the MIND diet was significantly associated with a reduced risk of dementia (hazard ratio [HR] = 0·87, 95% confidence interval [CI] = 0·77-0·98), stroke (HR = 0·89, 95% CI = 0·81-0·98), depression (HR = 0·77, 95% CI = 0·71-0·82), and anxiety (HR = 0·82, 95% CI = 0·76-0·88), but not PD (HR = 0·94, 95% CI = 0·80-1·11). In the HRS (n = 4496) and CLHLS (n = 9099) validation cohorts, the MIND diet remained significantly associated with lower risks of depression and anxiety, as well as better cognitive performance (in HRS: better cognitive function (β = 0·78, 95% CI = 0·47-1·10), fewer depressive symptoms (β = -0·22, 95% CI = -0·39 to -0·06), and fewer anxiety symptoms (β = -0·40, 95% CI = -0·78 to -0·02); in CLHLS: lower odds of cognitive impairment (odds ratio [OR] = 0·45, 95% CI = 0·37-0·55), depression (OR = 0·44, 95% CI = 0·38-0·52), and anxiety (OR = 0·49, 95% CI = 0·41-0·60)). In contrast, the intake of UPF was associated with an increased risk for dementia (HR = 1·40, 95% CI = 1·25-1·56), PD (HR = 1·26, 95% CI = 1·08-1·47), depression (HR = 1·42, 95% CI = 1·34-1·50), and anxiety (HR = 1·26, 95% CI = 1·19-1.33) in the UK Biobank cohort. Mechanistically, multi-omics analyses revealed that the MIND diet's protective effects were mediated through several key pathways. A favourable metabolic signature explained a substantial proportion of the reduced risk for stroke (proportion mediated = 60·63%), depression (38·97%), and anxiety (26·06%). Furthermore, slower biological ageing significantly mediated the reduced risk of dementia (19·40%). A structural equation model confirmed the overall protective pathway linking the MIND diet to better brain health via these mediators. Conversely, higher UPF intake was found to increase brain disease risk through detrimental changes in these same metabolic, and ageing pathways. Interpretation: This study supports the MIND diet as a promising intervention for promoting brain health and mitigating neuropsychiatric disorders, while highlighting UPF intake as a significant modifiable risk factor. By identifying specific metabolic, inflammatory, and ageing-related biological pathways, our findings provide potential targets for future research and targeted interventions. However, these observational associations require definitive confirmation through further experimental studies, such as randomised controlled trials. Funding: National Natural Science Foundation of China and the Fujian Provincial Science and Technology Plan Project.

Indexed as

AgeingBrain disordersCohort studyDietary patternMetabolomicsProteomics

Identifiers

PMID41245532
PMCPMC12615346

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.