The Quality and Inflammatory Index of Diet in Patients With Migraine
Bibliographic record
Abstract
OBJECTIVES: This study aims to verify if the quality of diet and the Dietary Inflammatory Index (DII) of migraine patients differ from that consumed by healthy individuals, and whether the severity of migraine is associated with these parameters. METHODS: This cross-sectional study was conducted at the Neurology Outpatient Clinic, Hospital das Clinicas, Universidade Federal de Minas Gerais – UFMG (Belo Horizonte, MG, Brazil). Patients with episodic migraine of both sexes, aged between 18–65 years were enrolled. Healthy volunteers without a history of primary headaches were recruited through advertisements and invitation to participate. Disability and impact caused by migraine were evaluated, respectively, by the Migraine Disability Test (MIDAS) and the Headache Impact Test, version 6 (HIT-6) questionnaires. Dietary intake was assessed using a 24-hour dietary recall and/or a three-day non-consecutive dietary record. The quality of diet was calculated using the Healthy Eating Index (HEI)-2015, adapted to the Brazilian population and DII was calculated based on the method developed by Shivappa et al. (2014). RESULTS: Ninety patients with migraine and 62 individuals without migraine were included in the study. The groups did not differ regarding age, sex, marital status, years of schooling and anthropometric characteristics. Patients with migraine had lower HEI total score than controls [50.9 (23.9 – 83.2) vs. 44.6 (27.1 – 67.7); P < 0.01], indicating that these patients have poorer quality of diet. The scores of total fruits, whole fruits, total vegetables, added sugars, refined grains, and seafood and plant proteins were lower in the migraine group (P < 0.05). In agreement with that, patients with migraine had higher DII than controls [1.0 (–1.80 – 3.17) vs. 1.7 (–1.52 – 3.67); P = 0.02] indicating that the intake of pro-inflammatory type foods and nutrients was higher in the migraine group. The HEI and DII scores did not correlate with migraine impact or severity (P > 0.05). CONCLUSIONS: The quality and the inflammatory index of the diet may contribute to the physiopathology of migraine, but not necessarily to its severity. FUNDING SOURCES: Brazilian government funding agencies (CNPq and CAPES) and UTHealth Houston Department of Psychiatry and Behavioral Sciences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".