Smoking in Pregnancy and Fetal Growth: The Case for More Intensive Assessment
Bibliographic record
Abstract
INTRODUCTION: Many studies on prenatal tobacco exposure (PTE) effects have relied on single item retrospective measures of PTE. However, it is unclear how these single item measures may relate to more intensive maternal self-reports and to biological markers of maternal use and/or fetal exposure. It is also unclear whether these measures may be more valid predictors of fetal growth (gestational age, birthweight, head circumference, and birth length). METHODS: Data were obtained from 258 women during their pregnancy. PTE was assessed by four methods: a single item question, a calendar-based self-report measure from each trimester of pregnancy, maternal salivary cotinine assays, and nicotine and metabolites in infant meconium. We hypothesized that the more intensive measures and biological assays would account for additional variance in birth outcomes, above and beyond the single item measure. RESULTS: The single item self-report measure was not related to fetal growth. However, the more intensive calendar based self-report measure and the biological assays of PTE (ie, maternal salivary assays and infant meconium) were significant predictors of poor fetal growth, even with the single item measure in the model. CONCLUSIONS: The negative effects of PTE on important child outcomes may be greatly underestimated in the literature as many studies use single item self-report measures to ascertain PTE. Whereas more intensive self-report measures or biological assays may be cost prohibitive in large scale epidemiological studies, using a combination of measures when possible should be considered given their superiority both identifying prenatal smokers and predicting poor fetal growth. IMPLICATIONS: The present work underscores the importance of measurement issues when assessing associations between PTE and fetal growth. Results suggest that we may be greatly underestimating the negative effects of prenatal smoking on fetal growth and other important child outcomes if we rely solely on restricted single item self-report measures of prenatal smoking. Researchers should consider more intensive prospective self-report measures and biological assays as viable and superior alternatives to single item self-report measures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".