Gestational endocrine disrupting chemical exposure and autistic behaviors in 4 to 5 year old children from Cincinnati OH
Bibliographic record
Abstract
Background: Endocrine disrupting chemicals (EDCs) may increase the risk of autism, possibly by perturbing fetal hormone signaling or metabolism, but this complex exposure mixture makes identifying the most relevant EDCs difficult. Aims: To identify gestational EDC exposures associated with autistic behaviors. Methods: We measured the concentrations of 52 EDCs including 8 phthalate metabolites, bisphenol A (BPA), 25 polychlorinated biphenyls (PCBs), 6 organochlorine pesticides, 8 brominated flame retardants, and 4 perfluorinated chemicals in blood or urine samples from 175 pregnant women from the HOME Study (Cincinnati, OH). When children were 4 and 5 years old, mothers completed the Social Responsiveness Scale (SRS), a valid/reliable measure of autistic behaviors including interpersonal behavior/communication deficits and repetitive/stereotypic behaviors (mean:50, SD:10). We estimated the association between SRS scores with increasing EDC concentrations using a 2-stage semi-Bayesian hierarchical analysis to adjust for sociodemographic, perinatal, and maternal factors, as well as co-pollutant confounding. Results: The absolute difference in SRS scores associated with most EDCs was negligible (~1 point). Notable exceptions included better SRS scores among children born to women with detectable vs. non-detectable serum PCB-178 (beta:-3.3; 95% confidence interval [CI]:-6.5, -0.1) or b-hexachlorocyclohexane (beta-HCH) concentrations (beta:-3.0; CI:-5.8, -0.2), and increasing serum perfluoroctane (PFOA) concentrations (beta:-1.9; CI:-4.3, 0.5). Higher serum polybrominated diphenyl ether-28 (PBDE-28; beta:2.5; CI:-0.6, 5.6) and trans-nonachlor (beta:4.0; CI:0.7, 7.2) concentrations were associated with worse SRS scores. Conclusion:Although our modest sample size precludes us from dismissing chemicals as risk factors for autistic-like behaviors, we conclude that beta-HCH, PCB-178, PBDE-28, PFOA, and trans-nonachlor deserve additional scrutiny as factors that may increase or decrease the risk of autism in children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".