Body size and the risk of multiple sclerosis in Norway and Italy: The EnvIMS study
Bibliographic record
Abstract
BACKGROUND: Obesity may be a risk factor for developing multiple sclerosis (MS). OBJECTIVE: We examined if body size influences the risk of MS in a population-based, case control study. METHODS: A total of 953 cases and 1717 controls from Norway and 707 cases and 1333 controls from Italy reported their body size by choosing a silhouette 1 to 9 (largest) every fifth year from age 5 to 30 and at time of study. The body size-related MS risk was defined by odds ratios (ORs) in logistic regression analyses adjusting for age, smoking and outdoor activity. RESULTS: In Norway a large body size (silhouettes 6-9) compared to silhouette 3 increased the risk of MS, especially at age 25 (OR 2.21; 95% CI 1.09-4.46 for men and OR 1.43; 95% CI 0.90-2.27 for women). When comparing silhouette 9 to 1, we found a significant dose-response from age 10 until age 30 peaking at age 25 (sex-adjusted OR 2.83; 95% CI 1.68-4.78). The association was present for at least 15 years prior to disease onset. No significant associations were found in Italy. CONCLUSIONS: Obesity from childhood until young adulthood is a likely risk factor for MS with a seemingly stronger effect in Norway than in Italy.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".