The association of ultra-processed food intake with neurodegenerative disorders: a systematic review and dose-response meta-analysis of large-scale cohorts
Why this work is in the frame
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Bibliographic record
Abstract
Objectives Our systematic review and meta-analysis aimed to uncover the relationship between UPFs intake and neurodegenerative disorders, including multiple sclerosis (MS), Parkinson’s disease (PD), Alzheimer’s disease (AD), cognitive impairment, and dementia.Setting A systematic search was conducted using the Scopus, PubMed/MEDLINE, and ISI Web of Science databases without any limitation until June 24, 2023. Relative risk (RR) and 95% confidence interval (CI) were pooled by using a random-effects model, while validated methods examined quality and publication bias via Newcastle-Ottawa Scale, Egger’s regression asymmetry, and Begg’s rank correlation tests, respectively.Results Analysis from 28 studies indicated that a higher UPFs intake was significantly related to an enhanced risk of MS (RR = 1.15; 95% CI: 1.00, 1.33; I2 = 37.5%; p = 0.050; n = 14), PD (RR = 1.56; 95% CI: 1.21, 2.02; I2 = 64.1%; p = 0.001; n = 15), and cognitive impairment (RR = 1.17; 95% CI: 1.06, 1.30; I2 = 74.1%; p = 0.003; n = 17), although not AD or dementia. We observed that a 25 g increment in UPFs intake was related to a 4% higher risk of MS (RR = 1.04; 95% CI: 1.01, 1.06; I2 = 0.0%; p = 0.013; n = 7), but not PD. The non-linear dose–response relationship indicated a positive non-linear association between UPF intake and the risk of MS (Pnonlinearity = 0.031, Pdose-response = 0.002). This association was not observed for the risk of PD (Pnonlinearity = 0.431, Pdose-response = 0.231).Conclusion These findings indicate that persistent overconsumption of UPFs may have an adverse impact on neurodegenerative conditions, potentially leading to a decline in quality of life and reduced independence as individuals age.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it