Timing of use of cod liver oil, a vitamin D source, and multiple sclerosis risk: The EnvIMS study
Bibliographic record
Abstract
BACKGROUND: Low vitamin D levels have been associated with an increased risk of multiple sclerosis (MS), although it remains unknown whether this relationship varies by age. OBJECTIVE: The objective of this paper is to investigate the association between vitamin D3 supplementation through cod liver oil at different postnatal ages and MS risk. METHODS: In the Norwegian component of the multinational case-control study Environmental Factors In Multiple Sclerosis (EnvIMS), a total of 953 MS patients with maximum disease duration of 10 years and 1717 controls reported their cod liver oil use from childhood to adulthood. RESULTS: Self-reported supplement use at ages 13-18 was associated with a reduced risk of MS (OR 0.67, 95% CI 0.52-0.86), whereas supplementation during childhood was not found to alter MS risk (OR 1.01, 95% CI 0.81-1.26), each compared to non-use during the respective period. An inverse association was found between MS risk and the dose of cod liver oil during adolescence, suggesting a dose-response relationship (p trend = 0.001) with the strongest effect for an estimated vitamin D3 intake of 600-800 IU/d (OR 0.46, 95% CI 0.31-0.70). CONCLUSIONS: These findings not only support the hypothesis relating to low vitamin D as a risk factor for MS, but further point to adolescence as an important susceptibility period for adult-onset MS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".