Cigarette consumption and biomarkers of nicotine exposure during pregnancy and postpartum
Bibliographic record
Abstract
Abstract Background and Aims Smokers can regulate their nicotine intake by altering the number of cigarettes smoked per day (CPD) and their smoking intensity. The current study aimed to compare the utility of self‐reported CPD, total nicotine equivalents (TNE) and urinary cotinine to estimate nicotine intake during pregnancy. Design Longitudinal smoking behavior and biomarker data were collected at early pregnancy, late pregnancy and at postpartum as part of a smoking cessation trial to examine voucher‐based incentives for decreasing smoking. Setting Obstetric practices in Burlington, Vermont, United States. Participants A subset of participants ( n = 47) from the parent trial, recruited between December 2006 and June 2012, who provided a urine sample at each assessment during early pregnancy, late pregnancy and postpartum. Measurements Smoking was assessed using self‐reported CPD, TNE, TNE/CPD and urinary cotinine. Findings Pregnant smokers reported smoking 10.4 CPD at early pregnancy, 7.2 CPD at late pregnancy (a 31% reduction at late pregnancy, P = 0.001) and 8.6 CPD at postpartum (a 19% increase from late pregnancy, P = 0.08). TNE exposure was 41% ( P = 0.07) and 48% ( P = 0.03) lower at early and late pregnancy, respectively, compared to postpartum. TNE/CPD was on average 167% higher at late pregnancy compared to early pregnancy ( P = 0.01) and remained high at postpartum, where it was 111% higher compared to early pregnancy ( P = 0.007). Uriniary cotinine underestimated nicotine intake by 55% during early pregnancy and by 65% during late pregnancy compared to postpartum ( P interaction < 0.001); the underestimation was greater in slower ( P interaction < 0.001) versus faster ( P interaction = 0.04) nicotine metabolizers. Conclusions Neither cigarettes smoked per day (CPD) nor cotinine provides an accurate estimate of nicotine exposure during pregnancy. CPD underestimates nicotine intake substantially due to under‐reporting and/or higher intensity of smoking, while cotinine underestimates nicotine intake markedly due to accelerated nicotine (and cotinine) metabolism during pregnancy.
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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 | 0.000 | 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".