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Chemical Mixture Exposures during Pregnancy and Birth Outcomes

2018· article· en· W2924812799 on OpenAlexaff
Geetika Kalloo, Gregory A. Wellenius, Lawrence C. McCandless, Antonia Calafat, Andreas Sjödin, Margaret R. Karagas, Aimin Chen, Kimberly Yolton, Bruce P. Lanphear, Joseph M. Braun

Bibliographic record

VenueISEE Conference Abstracts · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMedicinePregnancyCotinineBirth weightPhthalateGestational ageBiomarkerUrineCohort studyProspective cohort studyObstetricsPhysiologyChemistryInternal medicineBiology

Abstract

fetched live from OpenAlex

Exposure to environmental chemical mixtures, which is prevalent among pregnant women, may be associated with altered fetal growth and gestational duration. In a prospective cohort of 380 pregnant women from Cincinnati, OH (enrolled 2003-2006), we quantified biomarker concentrations in urine and blood of 35 organic pollutants, cotinine, and 4 metals. We used K-means clustering and non-negative principal component (PC) analysis to characterize chemical mixtures among pregnant women. Then, we used multivariable linear regression to estimate and compare the covariate-adjusted associations of cluster membership or PC scores with gestational-age-specific birth weight z-score, birth length, head circumference, and gestational duration. Geometric mean biomarker concentrations were generally higher among women in cluster 1, intermediate among women in cluster 2, and lowest among women in cluster 3. Chemical biomarkers in the same structural or commercial family loaded onto the same PC. Compared with children born to women in cluster 3, children born to women in clusters 1 and 2 had 0.28 cm (95% CI: -0.86, 0.30) and 0.13 cm (95% CI:-0.65, 0.38) shorter birth length, respectively. Each standard deviation increase in PC 4 (correlated with organochlorine pesticides, cadmium, and lead) and PC 6 (correlated with mercury and monoethyl phthalate (MEP)) was associated with a 0.24 cm (95% CI: -0.49, 0.02) and 0.14 cm (95% CI: -0.42, 0.14) decrease in birth length, respectively. Chemical biomarkers with higher concentrations among women in clusters 1 and 2 loaded more strongly on both PC 4 and PC 6 than other PCs. Neither cluster membership nor PC scores were associated with birth weight z-score, head circumference, or gestational duration. In this cohort, cluster membership and PC scores reflecting exposure to cadmium, mercury, lead, organochlorine pesticides, and MEP were both inversely associated with birth length, but not other fetal growth measures or gestational duration.

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)0.004
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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