Early-Life Phthalate Exposure and Adiposity at 8 Years of Age
Bibliographic record
Abstract
BACKGROUND: Early-life phthalate exposure may influence child adiposity, but prior studies have not determined if there are periods of enhanced vulnerability to phthalates. OBJECTIVE: To examine the relationship between child adiposity at 8 y of age and repeated urinary biomarkers of phthalate exposure from gestation through childhood to determine if there are distinct periods of vulnerability. METHODS: In 219 mother-child pairs from Cincinnati, Ohio, we quantified nine urinary phthalate metabolites up to two times prenatally and six times from 1-8 y of age. We measured child body mass index (BMI), waist circumference, and percent body fat at 8 y of age. To identify periods of vulnerability, we used two statistical methods to estimate phthalate-adiposity associations at each visit, test differences in phthalate-adiposity associations across visits, and model trajectories of phthalate concentrations for children at different levels of adiposity. RESULTS: Prenatal phthalate concentrations were not associated with excess child adiposity. Monobenzyl phthalate (MBzP) concentrations during pregnancy and childhood were inversely associated with adiposity. The associations of di(2-ethylhexyl) phthalate (∑DEHP) metabolites and monoethyl phthalate (MEP) with child adiposity depended on the timing of exposure. A 10-fold increase in ∑DEHP at 1 and 5 y was associated with a 2.7% decrease [95% confidence interval (CI): -4.8, -0.5] and 2.9% increase (95% CI: 0.3, 5.5) in body fat, respectively. MEP concentrations at 5 and 8 y of age were associated with higher child adiposity, but earlier childhood concentrations were not. CONCLUSION: In this cohort, we did not find evidence of an obesogenic effect of prenatal phthalate exposure. Positive associations between postnatal MEP and ∑DEHP concentrations depended on the timing of exposure. https://doi.org/10.1289/EHP1022.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".