Association of a Combination of Healthy Lifestyle Behaviors With Reduced Risk of Incident Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: While previous studies have demonstrated an association between individual factors related to lifestyle and the risk of systemic lupus erythematosus (SLE), it is unclear how the combination of these factors might affect the risk of incident SLE. This study was undertaken to prospectively evaluate whether a combination of healthy lifestyle factors is associated with a lower risk of incident SLE and its subtypes (anti-double-stranded DNA [anti-dsDNA]-positive and anti-dsDNA-negative SLE). METHODS: The study included 185,962 women from the Nurses' Health Study (NHS) and NHSII cohorts, among whom there were 203 incident cases of SLE (96 with anti-dsDNA-positive SLE, 107 with anti-dsDNA-negative SLE) during 4,649,477 person-years of follow-up. The Healthy Lifestyle Index Score (HLIS) was calculated at baseline and approximately every 2 years during follow-up, with scores assigned for 5 healthy lifestyle factors: alcohol consumption, body mass index, smoking, diet, and exercise. A time-varying Cox proportional hazards regression model was used to estimate the adjusted hazard ratios (HRs) with 95% confidence intervals (95% CIs) for the risk of SLE. In addition, the percentage of partial population attributable risk (PAR%) of SLE development was calculated. RESULTS: A higher HLIS was associated with a lower risk of SLE overall (HR 0.81 [95% CI 0.71-0.94]) and a lower risk of anti-dsDNA-positive SLE (HR 0.78 [95% CI 0.63-0.95]). Women with ≥4 healthy lifestyle factors had the lowest risk of SLE overall (HR 0.42, 95% CI 0.25-0.70) and lowest risk of anti-dsDNA-positive SLE (HR 0.35, 95% CI 0.17-0.75) as compared to women with only 1 healthy behavior or no healthy behaviors. The PAR% of SLE development was 47.7% (95% CI 23.1-66.6%), assuming that the entire population had adhered to at least 4 healthy lifestyle behaviors. CONCLUSION: These results indicate that the risk of developing SLE, a disease in which significant evidence of genetic involvement has been established, might be reduced by nearly 50% with adherence to modifiable healthy lifestyle behaviors.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".