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Association of Parental Preconception Exposure to Phthalates and Phthalate Substitutes With Preterm Birth

2020· article· en· W3014395271 on OpenAlexfundno aff
Yu Zhang, Vicente Mustieles, Jennifer J. Yland, Joseph M. Braun, Paige L. Williams, Jill Attaman, Jennifer B. Ford, Antonia M. Calafat, Russ Hauser, Carmen Messerlian

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsPhthalateMedicinePregnancyObstetricsOffspringGestationGestational ageProspective cohort studyGynecologyInternal medicineBiologyChemistry

Abstract

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Importance: Although phthalate exposure during pregnancy has been associated with preterm birth, the association of preconception exposure in either parent with preterm birth constitutes a knowledge gap. Objective: To examine the association of paternal and maternal preconception urinary concentrations of biomarkers of phthalates and phthalate substitutes with singleton preterm birth. Design, Setting, and Participants: This study, conducted at an academic fertility center in Boston, Massachusetts, included a prospective preconception cohort of subfertile couples comprising 419 mothers and 229 fathers and their 420 live-born singleton offspring born between January 1, 2005, and December 31, 2018. Statistical analysis was performed from August 1 to October 31, 2019. Exposures: Urinary concentrations of metabolites of phthalates and phthalate substitutes obtained before conception. Main Outcomes and Measures: Gestational age was abstracted from delivery records and validated using the American College of Obstetricians and Gynecologists guidelines for births after medically assisted reproduction. The risk ratio (RR) of preterm birth (live birth before 37 completed weeks' gestation) was estimated in association with urinary concentrations of 11 individual phthalate metabolites, the molar sum of 4 di-(2-ethylhexyl) phthalate (ΣDEHP) metabolites, and 2 metabolites of 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH, a nonphthalate plasticizer substitute) using modified Poisson regression models adjusted for covariates. Results: The mean (SD) age of the 419 mothers was 34.7 (4.0) years, the mean (SD) age of the 229 fathers was 36.0 (4.5) years, and the mean (SD) gestational age of the 420 singleton children (217 boys) was 39.3 (1.7) weeks, with 34 (8%) born preterm. In adjusted models, maternal preconception ΣDEHP concentrations (RR, 1.50; 95% CI, 1.09-2.06; P = .01) and cyclohexane-1,2-dicarboxylic acid monohydroxy isononyl ester (MHiNCH, a metabolite of DINCH) concentrations (RR, 1.70; 95% CI, 0.89-3.24; P = .11) were associated with an increased risk of preterm birth. After additional adjustment for prenatal ΣDEHP or MHiNCH concentrations, the association of maternal preconception exposure to ΣDEHP and preterm birth remained robust (RR, 1.69; 95% CI, 1.17-2.44; P = .006), while the association of maternal preconception exposure to MHiNCH and preterm birth was attenuated (RR, 1.17; 95% CI, 0.49-2.81; P = .72). The remaining urinary metabolites examined in either parent showed no association with preterm birth. Conclusions and Relevance: In this prospective cohort of subfertile couples, maternal preconception exposure to ΣDEHP metabolites was associated with an increased risk of preterm birth. The results suggest that female exposure to select phthalate plasticizers during the preconception period may be a potential risk factor for adverse pregnancy outcomes, which may need to be considered in preconception care strategies.

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)0.005
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.284
Teacher spread0.272 · 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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Citations61
Published2020
Admission routes1
Has abstractyes

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