Smoking and quit attempts during pregnancy and postpartum: a longitudinal UK cohort
Bibliographic record
Abstract
OBJECTIVES: Pregnancy motivates women to try stopping smoking, but little is known about timing of their quit attempts and how quitting intentions change during pregnancy and postpartum. Using longitudinal data, this study aimed to document women's smoking and quitting behaviour throughout pregnancy and after delivery. DESIGN: Longitudinal cohort survey with questionnaires at baseline (8-26 weeks' gestation), late pregnancy (34-36 weeks) and 3 months after delivery. SETTING: Two maternity hospitals in one National Health Service hospital trust, Nottingham, England. PARTICIPANTS: 850 pregnant women, aged 16 years or over, who were current smokers or had smoked in the 3 months before pregnancy, were recruited between August 2011 and August 2012. OUTCOME MEASURES: Self-reported smoking behaviour, quit attempts and quitting intentions. RESULTS: Smoking rates, adjusting for non-response at follow-up, were 57.4% (95% CI 54.1 to 60.7) at baseline, 59.1% (95% CI 54.9 to 63.4) in late pregnancy and 67.1% (95% CI 62.7 to 71.5) 3 months postpartum. At baseline, 272 of 488 current smokers had tried to quit since becoming pregnant (55.7%, 95% CI 51.3 to 60.1); 51.3% (95% CI 44.7 to 58.0) tried quitting between baseline and late pregnancy and 27.4% (95% CI 21.7 to 33.2) after childbirth. The percentage who intended to quit within the next month fell as pregnancy progressed, from 40.4% (95% CI 36.1 to 44.8) at baseline to 29.7% (95% CI 23.8 to 35.6) in late pregnancy and 14.2% (95% CI 10.0 to 18.3) postpartum. Postpartum relapse was lower among women who quit in the 3 months before pregnancy (17.8%, 95% CI 6.1 to 29.4) than those who stopped between baseline and late pregnancy (42.9%, 95% CI 24.6 to 61.3). CONCLUSIONS: Many pregnant smokers make quit attempts throughout pregnancy and postpartum, but intention to quit decreases over time; there is no evidence that smoking rates fall during gestation.
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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".