Prenatal exposure to fine particles, premature rupture of membranes and gestational age: A prospective cohort study
Bibliographic record
Abstract
The associations between maternal exposure to fine particles with aerodynamic diameter ≤ 2.5 μm (PM2.5) and gestational age as well as premature rupture of membranes (PROM) remain unclear. Few studies have focused on preconception exposure and components of fine particles in China. A total of 1715 pregnant women were enrolled at hospitals affiliated with Nanjing Medical University from 2014 to 2015. Personal exposure to PM2.5 was estimated from preconception to the first trimester. Gestational age and PROM were investigated to explore their associations with PM2.5 and its components. From 12 weeks before conception to the end of the first trimester, the gestational age was reduced by 0.89 days (95% CI: −1.37, −0.40) per 10 μg/m3 increment in PM2.5 exposure. After the exposure period was separated into two groups, PM2.5 exposure reduced the gestational age by 0.35 days (95% CI: −0.59, −0.11) in the 12 weeks before pregnancy. With maternal exposure to PM2.5 early in the first trimester, gestational age was reduced by 0.62 days (95% CI: −1.09, −0.14). After mediation analysis, we found that PROM mediated the association between PM2.5 and gestational age from preconception to the first trimester. Components analysis indicated that exposure to black carbon, organic matter, and nitrate increased the risk of PROM and decreased gestational age. Exposure to PM2.5 as well as some components of PM2.5 before and during early pregnancy was associated with PROM and gestational age. PROM might be a potential mediator in associations between PM2.5 as well as various components and gestational age.
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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) | 0.003 | 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".