Pre- and postnatal exposure to secondhand tobacco smoke and cardiometabolic risk at 12 years: Periods of susceptibility
Bibliographic record
Abstract
BACKGROUND: To identify periods of heightened susceptibility to the association of secondhand tobacco smoke (SHS) exposure with cardiometabolic (CM) risk at age 12 years. METHODS: We used data from 212 adolescents from the HOME Study, a prospective pregnancy and birth cohort in Cincinnati, OH. Using multiple informant models, we estimated associations of maternal serum cotinine (mean of concentrations at 16 and 26 weeks of pregnancy) and children's serum cotinine concentrations (mean of concentrations at ages 1, 2, 3, and 4 years) with a CM risk summary score constructed of five risk components measured at age 12 years. We determined if these associations differed for pre- and postnatal exposure periods, and adolescent's sex. RESULTS: We found some evidence that the cotinine-outcome associations differed by exposure period and sex. Postnatal, but not prenatal, cotinine was associated with higher CM risk scores and individual CM risk component values (interaction p-values = 0.04 to 0.35). Each 10-fold increase in postnatal cotinine was associated with 0.57 (95% CI: 0.32, 1.45), 0.09 (95% CI: 0.13, 0.31), 0.14 (-0.08, 0.35), 0.07 (95% CI: 0.34, 0.48), and 0.11 (95% CI: 0.04, 0.27) higher CM risk, HOMA-IR, TG to HDL-C ratio, leptin to adiponectin ratio, and visceral fat area. Postnatal cotinine was associated with higher visceral fat area among females but not males (sex × period × cotinine interaction p-value = 0.01). CONCLUSIONS: Serum cotinine concentrations during the postnatal period had greater influence on adolescent's CM risk compared to the prenatal period, and these associations may be sex-specific. This study reinforces the need for ongoing public health interventions to minimize children's exposure to SHS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".