Twin growth discordance in association with maternal exposure to fine particulate matter and its chemical constituents during late pregnancy
Bibliographic record
Abstract
Twin growth discordance is one of the leading causes of perinatal mortality in twin pregnancies. Whether prenatal exposure to fine particle (PM2.5) air pollution is associated with twin growth discordance have not been studied yet. To evaluate the associations of prenatal exposure to PM2.5 and its chemical constituents with twin growth discordance. This study included 1917 twin pairs and their mothers drawn from a previous twin birth cohort at the Shanghai First Maternity and Infant hospital in Shanghai, China. Exposure to PM2.5 total mass and 6 key chemical constituents during the whole pregnancy and each trimester of pregnancy was represented by satellite-based models. Maternal exposures to PM2.5 total mass and chemical constituents of sulfate (SO42−) and ammonium (NH4+) during the third trimester were significantly associated with increased within-pair birth weight difference and intertwin birth weight discordance. The within-pair birth weight difference increased by 30.6 g (β = 30.6, 95% CI, 4.4–56.9), 19.2 g (β = 19.2, 95% CI, 0.2–38.1) and 33.2 g (β = 33.2, 95% CI, 7.9–58.6) for an IQR increase in PM2.5 total mass, SO42− and NH4+ exposure, respectively. While the intertwin birth weight discordance increased by 1.3% (β = 1.3, 95% CI, 0.3–2.2), 0.9% (β = 0.9, 95% CI, 0.2–1.6) and 1.4% (β = 1.4, 95% CI, 0.4–2.3) for the same exposure metrics. Moreover, higher SO42− and NH4+ exposure was also associated with increased risk of twin growth discordance in linear dose-response manners. Compared to the lowest quartile of SO42− (OR = 2.51, 95% CI, 1.08–5.82) and NH4+ (OR = 2.97, 95% CI, 1.16–7.58) exposure, the odds of twin growth discordance were doubled in highest quartile of exposure. Our results suggest that fine particle air pollution may be a risk factor for twin growth discordance. Late pregnancy seems to be a critical window for the effects of PM2.5 exposure on fetal growth in twins.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".