Relationships of First-Trimester Body Mass Index and Weight Change with Persistent Organic Pollutant Concentrations in Pregnant Canadian Individuals
Bibliographic record
Abstract
Persistent organic pollutants (POPs) are toxic chemicals with demonstrable effects on pregnancy and neonatal outcomes. The associations of early pregnancy body mass index (BMI) and antenatal weight changes with circulating POP concentrations are poorly understood in the Canadian context. The aim of this study was to explore the relationship between maternal BMI in the first trimester, weight change from pre-pregnancy to 6–13 weeks of pregnancy, and first-trimester plasma POP concentrations among Canadian pregnant women. We analyzed data collected as part of the Maternal-Infant Research on Environmental Chemicals (MIREC) study and evaluated POP concentrations based on first-trimester BMI and early gestational weight change categories. We tested for overall differences using Kruskal-Wallis tests. The associations between first-trimester maternal BMI, weight change, and plasma concentrations of 41 POPs were evaluated using censored regression models. After controlling for potential confounders, first-trimester plasma levels of multiple POPs differed significantly across BMI categories, with the highest concentrations in underweight/normal-weight individuals and the lowest in class III obese individuals. Our findings provide preliminary evidence of higher circulating POP levels in individuals with obesity and align with previous findings of an inverse relationship between circulating POP concentrations and BMI in pregnancy. Future studies should prospectively evaluate the interplay between weight change and POP concentrations throughout pregnancy to inform gestational weight gain recommendations for pregnant individuals with obesity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".