Locally derived traffic-related air pollution and fetal growth restriction: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Fetal growth restriction has been inconsistently associated with maternal exposure to elevated levels of traffic-related air pollution. OBJECTIVE: We investigated the relationship between an individualised measure of fetal growth and maternal exposure to a specific marker for traffic-related air pollution. METHODS: We estimated maternal residential exposure to a marker for traffic-related air pollution (nitrogen dioxide, NO2) during pregnancy for 23,452 births using temporally adjusted land-use regression. Logistic regression was used to investigate associations with small for gestational age and sex (SGA) and fetal growth restriction, defined as proportion of optimal birth weight (POBW) below the 10th percentile. Sub-populations investigated were: women who spent most time at home, women who did not move house, women with respiratory or circulatory morbidity, women living in low/middle/high socio-economic areas, women who delivered before 37 weeks gestation, and women who delivered from 37 weeks gestation. RESULTS: An IQR increase in traffic-related air pollution in the second trimester across all women was associated with an OR of 1.31 (95% CI 1.07 to 1.60) for fetal growth restriction. Effects on fetal growth restriction (low POBW) were highest among women who subsequently delivered before 37 weeks of gestation. Effects on SGA were highest among women who did not move house: OR 1.35 (95% CI 1.08 to 1.69). CONCLUSIONS: Larger effect sizes were observed for low POBW than for SGA. Exposure to traffic-related air pollution in mid to late pregnancy was associated with risk of SGA and low POBW in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".