Adherence to a healthy lifestyle and multiple sclerosis: a case–control study from the UK Biobank
Bibliographic record
Abstract
Background Multiple sclerosis (MS) is a common and disabling condition. The importance of healthy lifestyle for this disease is poorly explored.Objective To test whether adherence to healthier lifestyle patterns is associated with a lower presence of multiple sclerosis (MS).Methods By using a case–control design, we investigated the combined association of four healthy lifestyle-related factors (no current smoking, healthy diet, exercising regularly, body mass index <30 kg/m2) and the prevalence of MS. A logistic regression analysis, adjusted for potential confounders, was used and data reported as odds ratios (ORs) with their 95% confidence intervals (CIs).Results 728 participants with MS were matched with healthy controls (n = 2,912) using a propensity score approach. In a multivariable analysis, compared to those who scored low in the composite lifestyle score (0–1 healthy lifestyle factors), people who adopted all four low risk lifestyle factors showed a 71% lower odds of having MS (OR = 0.29; 95% CI: 0.15–0.56). Moreover, there was a strong linear trend, suggesting that the higher number of healthy lifestyle behaviors was associated with lower odds of having MS.Conclusion Following a healthy lifestyle is associated with a lower prevalence of MS. This association should be explored further in cohort studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".