Prospective associations between early long-term household tobacco smoke exposure and antisocial behaviour in later childhood
Bibliographic record
Abstract
BACKGROUND: Using a prospective birth cohort design, we estimate the relative contribution of long-term postnatal nicotine exposure from 17 to 86 months on children's subsequent antisocial behaviour by the end of fourth grade. METHOD: Parents reported the amount of household smoke exposure (at 17, 41, 65 and 86 months) for all 2055 children from the Quebec Longitudinal Study of Child Development. Main outcome measures include teacher- and child-reported antisocial and physically aggressive behaviour (at 121 months). RESULTS: In terms of prevalence, 58% of parents reported that their children were never exposed to secondhand smoke in the home, while 34% and 8% of parents reported transient and continuous levels of secondhand smoke, respectively. When compared with never exposed children, children exposed to continuous secondhand smoke scored higher on self-reported aggressive behaviour and teacher-rated antisocial behaviour in fourth grade, B=0.336 (95% CI 0.155 to 0.517) and B=0.319 (95% CI 0.107 to 0.531), respectively. Similarly, children exposed to transient levels of secondhand smoke scored higher on aggressive and antisocial behaviour, B=0.714 (95% CI 0.456 to 0.972) and B=0.566 (95% CI 0.260 to 0.872), respectively. CONCLUSIONS: The observed prevalence is concordant with worldwide estimates of children's exposure to secondhand smoke. In comparison with their never exposed peers, children continuously and intermittently exposed to secondhand smoke in childhood showed an increased propensity toward physical aggression and antisocial behaviour by the end of fourth grade. We found no evidence of dose-dependence.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".