Sun exposure and multiple sclerosis risk in Norway and Italy: The EnvIMS study
Bibliographic record
Abstract
OBJECTIVES: The objective of this paper is to estimate the association between multiple sclerosis (MS) and measures of sun exposure in specific age periods in Norway and Italy. METHODS: A total of 1660 MS patients and 3050 controls from Italy and Norway who participated in a multinational case-control study (EnvIMS) reported sun habits during childhood and adolescence. RESULTS: A significant association between infrequent summer outdoor activity and increased MS risk was found in Norway and in Italy. The association was strongest between the ages of 16 and 18 years in Norway (odds ratio (OR) 1.83, 95% confidence interval (CI) 1.30-2.59), and between birth and age 5 years in Italy (OR 1.56, 95% CI 1.16-2.10). In Italy a significant association was also found during winter (OR 1.42, 95% CI 1.03-1.97). Frequent sunscreen use between birth and the age of 6 years was associated with MS in Norway (OR 1.44, 95% CI 1.08-1.93) after adjusting for outdoor activity during the same period. Red hair (OR 1.67, 95% CI 1.06-2.63) and blonde hair (OR 1.36, 95% CI 1.09-1.70) were associated with MS after adjusting for outdoor activity and sunscreen use. CONCLUSION: Converging evidence from different measures underlines the beneficial effect of sun exposure on MS risk.
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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 | 0.001 | 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".