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Record W2973221449 · doi:10.1016/j.envint.2019.105148

Twin growth discordance in association with maternal exposure to fine particulate matter and its chemical constituents during late pregnancy

2019· article· en· W2973221449 on OpenAlexaff
Ping Qiao, Yan Zhao, Jing Cai, Aaron van Donkelaar, Randall V. Martin, Hao Ying, Haidong Kan

Bibliographic record

VenueEnvironment International · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsDalhousie University
FundersShanghai Hospital Development CenterTongji UniversityShanghai Municipal Health BureauNational Natural Science Foundation of ChinaScience and Technology Commission of Shanghai MunicipalityNatural Science Foundation of Shanghai
KeywordsParticulatesPregnancyEnvironmental chemistryTwin studyEnvironmental healthEnvironmental scienceMedicineChemistryBiologyGeneticsEcology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.009
GPT teacher head0.229
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2019
Admission routes1
Has abstractyes

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