A prospective cohort study of biomarkers of prenatal tobacco smoke exposure: the correlation between serum and meconium and their association with infant birth weight
Bibliographic record
Abstract
BACKGROUND: The evaluation of infant meconium as a cumulative matrix of prenatal toxicant exposure requires comparison to established biomarkers of prenatal exposure. METHODS: We calculated the frequency of detection and concentration of tobacco smoke metabolites measured in meconium (nicotine, cotinine, and trans-3'-hydroxycotinine concentrations) and three serial serum cotinine concentrations taken during the latter two-thirds of pregnancy among 337 mother-infant dyads. We estimated the duration and intensity of prenatal tobacco smoke exposure using serial serum cotinine concentrations and calculated geometric mean meconium tobacco smoke metabolite concentrations according to prenatal exposure. We also compared the estimated associations between these prenatal biomarkers and infant birth weight using linear regression. RESULTS: We detected nicotine (80%), cotinine (69%), and trans-3'-hydroxycotinine (57%) in most meconium samples. Meconium tobacco smoke metabolite concentrations were positively associated with serum cotinine concentrations and increased with the number of serum cotinine measurements consistent with secondhand or active tobacco smoke exposure. Like serum cotinine, meconium tobacco smoke metabolites were inversely associated with birth weight. CONCLUSIONS: Meconium is a useful biological matrix for measuring prenatal tobacco smoke exposure and could be used in epidemiological studies that enroll women and infants at birth. Meconium holds promise as a biological matrix for measuring the intensity and duration of environmental toxicant exposure and future studies should validate the utility of meconium using other environmental toxicants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".