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Record W2267946623 · doi:10.1016/j.envres.2016.01.040

Exposure to organophosphorus and organochlorine pesticides, perfluoroalkyl substances, and polychlorinated biphenyls in pregnancy and the association with impaired glucose tolerance and gestational diabetes mellitus: The MIREC Study

2016· article· en· W2267946623 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversity of ManitobaHealth CanadaDalhousie UniversityUniversité LavalUniversité de MontréalUniversité de SherbrookeCentre Hospitalier Universitaire Sainte-JustineMcGill University
FundersCanadian Institutes of Health ResearchPublic Health Agency of Canada
KeywordsGestational diabetesOrganochlorine pesticidePregnancyPesticideDiabetes mellitusEndocrinologyGestationChemistryInternal medicineEnvironmental chemistryMedicineToxicologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Studies report increases in rates of gestational diabetes mellitus (GDM) over recent decades. Environmental chemicals may increase the risk of diabetes through impacts on glucose metabolism, mitochondrial dysfunction, and endocrine-disrupting mechanisms including effects on pancreatic β-cell function and adiponectin release. OBJECTIVES: To determine the associations between pesticides, perfluoroalkyl substances (PFASs) and polychlorinated biphenyls (PCBs) measured in early pregnancy and impaired glucose tolerance (IGT) and GDM in a Canadian birth cohort. METHODS: Women enrolled in the Maternal-Infant Research on Environmental Chemicals (MIREC) Study were included if they had a singleton delivery and did not have pre-existing diabetes. Exposure variables included three organophosphorus (OP) pesticide metabolites detected in first-trimester urine samples, as well as three organochlorine (OC) pesticides, three PFASs, and four PCBs in first-trimester blood samples. Gestational IGT and GDM were assessed by chart review in accordance with published guidelines. Adjusted logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CI) for the association between quartiles of environmental chemicals and both gestational IGT and GDM. RESULTS: Of the 2001 women recruited into the MIREC cohort, 1274 met the inclusion criteria and had outcome and biomonitoring data available. Significantly lower odds of GDM were observed in the third and fourth quartiles of dimethylphosphate (DMP) and in the fourth quartile of dimethylthiophosphate (DMTP) in adjusted analyses (DMP Q3: OR=0.2, 95% CI=0.1-0.7; DMP Q4: OR=0.3, 95% CI=0.1-0.8; DMTP: OR=0.3, 95% CI=0.1-0.9). Significantly elevated odds of gestational IGT was observed in the second quartile of perfluorohexane sulfonate (PFHxS) (OR=3.5, 95% CI=1.4-8.9). No evidence of associations with GDM or IGT during pregnancy was observed for PCBs or OC pesticides. CONCLUSIONS: We did not find consistent evidence for any positive associations between the chemicals we examined and GDM or IGT during pregnancy. We observed statistical evidence of inverse relationships between urine concentrations of DMP and DMTP with GDM. We cannot rule out the influence of residual confounding due to unmeasured protective factors, such as nutritional benefits from fruit and vegetable consumption, also associated with pesticide exposure, on the observed inverse associations between maternal OP pesticide metabolites and GDM. These findings require further investigation.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.166
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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