Physical activity is associated with a decreased multiple sclerosis risk: The EnvIMS study
Bibliographic record
Abstract
BACKGROUND: The lifestyle factors smoking and obesity have been associated with the risk of multiple sclerosis (MS). Physical activity (PA) may also be of importance. OBJECTIVE: To examine the association between PA and MS risk in Italy, Norway, and Sweden and to evaluate the possible influence by established risk factors. METHODS: In this case-control study, 1904 cases and 3694 controls were asked to report their average weekly amounts of light and vigorous PA during adolescence on a scale ranging from none to more than 3 hours activity. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) and adjusted for potential confounders. RESULTS: Vigorous PA was inversely associated with MS risk in the pooled analysis ( p-trend < 0.001) with an age- and sex-adjusted OR of 0.74 (95% CI: 0.63-0.87) when comparing the highest and lowest levels. Adjusting for outdoor activity, infectious mononucleosis, body size, and smoking yielded similar results. The association was present in all countries and was not affected by exclusion of patients with early disease onset. Light PA was not associated with the risk of MS. CONCLUSION: Our findings suggest that vigorous PA can modify the risk of developing MS independent of established risk factors.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".