Parental smoking at home and the risk of childhood-onset multiple sclerosis in children
Bibliographic record
Abstract
The possibility of a link between active smoking and incident multiple sclerosis (MS) has been raised. However, possible links between incidence of MS and passive smoking, particularly in children, have not been analysed. We conducted a population-based, case-control study. The cases were patients with incident MS occurring between 1994 and 2003, before the age of 16 years, in France. Each case was matched for age, sex and geographic origin with 12 controls, randomly selected from the French general population. Information about the smoking history of the parents of the cases and controls was collected with a standardized questionnaire. Conditional logistic regression was used to estimate the rate ratio (RR) of MS associated with parental smoking at home. The 129 cases of MS were matched with 1038 controls. Information about parental smoking was obtained for all these cases and controls. Exposure to parental smoking was noted in 62.0% of cases and 45.1% of controls. The adjusted RR of a first episode of MS associated with exposure to parental smoking at home was 2.12 (95% confidence interval: 1.43-3.15). Stratification for age showed that this increase in risk was significantly associated with the longer duration of exposure in older cases (over 10 years of age at the time of the index episode)-RR 2.49 (1.53-4.08)-than in younger cases. Children exposed to parent smoking have a higher MS risk. The duration of exposure also affects the level of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".