Exposure to phthalates, bisphenol A and metals in pregnancy and the association with impaired glucose tolerance and gestational diabetes mellitus: The MIREC study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Studies from several countries report increases in rates of gestational diabetes mellitus (GDM) over recent decades. Exposure to environmental chemicals could contribute to this trend. OBJECTIVES: To determine the associations between plasticisers and metals measured in early pregnancy with impaired glucose tolerance (IGT) and GDM in a Canadian pregnancy 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. Eleven phthalate metabolites and total bisphenol A (BPA) were measured in first-trimester urine samples, and four metals (lead, cadmium, mercury and arsenic) were measured in first-trimester blood samples. IGT and GDM were assessed in accordance with standard guidelines by chart review. Chemical concentrations were grouped by quartiles, and associations with outcomes were examined using logistic regression with adjustment for maternal age, race, pre-pregnancy BMI, and education. Restricted cubic spline analysis was performed to help assess linearity and nature of any dose-response relationships. RESULTS: Of 2001 women recruited into the MIREC cohort, 1274 met the inclusion criteria and had outcome data and biomonitoring data measured for at least one of the chemicals we examined. Elevated odds of GDM were observed in the highest quartile of arsenic exposure (OR = 3.7, 95% CI = 1.4-9.6) in the adjusted analyses. A significant dose-response relationship was observed in a cubic spline model between arsenic and odds of GDM (p < 0.01). No statistically significant associations were observed between phthalates or BPA or other metals with IGT or GDM. CONCLUSIONS: Our findings add to the growing body of evidence supporting the role of maternal arsenic exposure as a risk factor for gestational diabetes.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it