Smoking in pregnancy, adolescent mental health and cognitive performance in young adult offspring: results from a matched sample within a Finnish cohort
Bibliographic record
Abstract
BACKGROUND: The association between prenatal exposure to maternal cigarette smoking (PEMCS) and adult cognition is debated, including if there are differences according to sex. We aimed to determine if there are associations between PEMCS and cognition in early adulthood in men and women and examine if observed associations were mediated by adolescent mental health factors that are associated with cognition, namely psychotic-like experiences (PLEs), inattention and hyperactivity, and other externalizing behaviors. METHODS: Participants were 471 individuals drawn from the general population-based Northern Finland 1986 Birth Cohort (NFBC 1986) followed up from pregnancy and birth to early adulthood; individuals with PEMCS were matched with those without PEMCS by socioeconomic and demographic factors. Cognitive performance in adulthood was assessed with a range of tests and their association with PEMCS was measured by sex using hierarchical linear regression, unadjusted and then controlling for potential confounders, mediators and moderators, including adolescent mental health factors. RESULTS: There were no associations between PEMCS and cognitive scores in females. In males, there were associations with vocabulary (beta = -0.444, 95% CI: -0.783, -0.104) and matrix reasoning (beta = -0.379, 95% CI: -0.711, -0.047). CONCLUSIONS: While associations between PEMCS and cognition were limited, observed findings with measures of general intelligence in males contribute to suggestions of differences in response to PEMCS by sex. Furthermore, observed associations may be partly mediated by earlier inattention and hyperactivity. Findings add support to efforts aimed to eliminate smoking in pregnancy.
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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 | 0.001 | 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) | 0.002 | 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".