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Record W4390277802 · doi:10.1016/j.envres.2023.118067

Ambient air pollution and rate of spontaneous abortion

2023· article· en· W4390277802 on OpenAlexaboutno aff
Amelia K. Wesselink, Kipruto Kirwa, Perry Hystad, Joel D. Kaufman, Adam A. Szpiro, Mary D. Willis, David A. Savitz, Jonathan I. Levy, Kenneth J. Rothman, Ellen M. Mikkelsen, Anne Sofie Dam Laursen, Elizabeth E. Hatch, Lauren A. Wise

Bibliographic record

VenueEnvironmental Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersNational Institute of Child Health and Human DevelopmentNational Institute of Environmental Health SciencesAbbVieEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBill and Melinda Gates Foundation
KeywordsPregnancyHazard ratioAbortionMedicineProportional hazards modelConfidence intervalIncidence (geometry)GestationDemographyCohort studyCohortObstetricsEnvironmental healthFertilityPopulationInternal medicine

Abstract

fetched live from OpenAlex

Spontaneous abortion (SAB), defined as a pregnancy loss before 20 weeks of gestation , affects up to 30% of conceptions, yet few modifiable risk factors have been identified. We estimated the effect of ambient air pollution exposure on SAB incidence in Pregnancy Study Online (PRESTO), a preconception cohort study of North American couples who were trying to conceive. Participants completed questionnaires at baseline, every 8 weeks during preconception follow-up, and in early and late pregnancy . We analyzed data on 4643 United States (U.S.) participants and 851 Canadian participants who enrolled during 2013–2019 and conceived during 12 months of follow-up. We used country-specific national spatiotemporal models to estimate concentrations of particulate matter <2.5 μm (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) during the preconception and prenatal periods at each participant's residential address. On follow-up and pregnancy questionnaires, participants reported information on pregnancy status, including SAB incidence and timing. We fit Cox proportional hazards regression models with gestational weeks as the time scale to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of time-varying prenatal concentrations of PM 2.5 , NO 2 , and O 3 with rate of SAB, adjusting for individual- and neighborhood-level factors. Nineteen percent of pregnancies ended in SAB. Greater PM 2.5 concentrations were associated with a higher incidence of SAB in Canada, but not in the U.S. (HRs for a 5 μg/m 3 increase = 1.29, 95% CI: 0.99, 1.68 and 0.94, 95% CI: 0.83, 1.08, respectively). NO 2 and O 3 concentrations were not appreciably associated with SAB incidence. Results did not vary substantially by gestational weeks or season at risk. In summary, we found little evidence for an effect of residential ambient PM 2.5 , NO 2 , and O 3 concentrations on SAB incidence in the U.S., but a moderate positive association of PM 2.5 with SAB incidence in Canada. • We found a positive association of ambient PM 2.5 concentrations with spontaneous abortion in Canada, but not the USA. • NO 2 and O 3 concentrations were not appreciably associated with rate of SAB. • Results were relatively consistent across season and weeks of gestation. • Protection of pregnant individuals from air pollutionis an important measure to safeguard maternal and fetal health.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.071
GPT teacher head0.373
Teacher spread0.302 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2023
Admission routes1
Has abstractyes

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