No association between ambient particulate matter exposure during pregnancy and stillbirth risk in the north of England, 1962–1992
Bibliographic record
Abstract
OBJECTIVES: Research evidence suggests that exposure to ambient air pollutants can adversely affect the growth and development of the foetus and infant survival. Much less is known regarding the potential for an association between black smoke air pollution and stillbirth risk. This potential association was examined using data from the historical cohort UK Particulate Matter and Perinatal Events Research (PAMPER) study. METHODS: Using data from paper-based neonatal records from the two major maternity hospitals in Newcastle upon Tyne (UK), a birth record database of all singletons born during 1961-1992 to mothers resident in the city was constructed. Weekly black smoke levels were obtained from routine data recorded at 20 air pollution monitoring stations over the study period. A two-stage statistical modelling strategy was used, incorporating temporally and spatially varying covariates to estimate black smoke exposure during each trimester and for the whole pregnancy period for each individual pregnancy. Conditional logistic regression models, with stratification on year of birth, were used to assess potential associations between black smoke exposures in pregnancy and stillbirth risk. RESULTS: The PAMPER database consists of 90,537 births, between 1962 and 1992, with complete gestational age and residential address information, of which 812 were stillborn. There was no association between black smoke exposures in any trimester or across whole pregnancy and risk of stillbirth. Adjustment for potential confounders did not alter these results. CONCLUSIONS: While black smoke in pregnancy is likely to be related to other pregnancy outcomes, our findings do not suggest that black smoke air pollution exposure during pregnancy increases the risk of stillbirth.
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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) | 0.001 | 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".