Associations of Legacy and Emerging Halogenated Flame Retardant Exposures with Childhood Attention Deficit/Hyperactivity Disorder-Related Traits and Brain Functional Connectivity in a Canadian Birth Cohort
Bibliographic record
Abstract
Halogenated flame retardants (HFRs) are widely used chemicals with potential neurotoxicity, yet limited epidemiologic evidence exists for their association with childhood neurodevelopment. We investigated associations between HFR exposures and attention-deficit/hyperactivity disorder (ADHD)-related traits and brain functional connectivity in 194 children aged 8-12 years from the GESTation and Environment (GESTE) birth cohort in Sherbrooke, Canada. We assessed 16 legacy and emerging HFRs in plasma and stool, with 5 in plasma and 9 in stool samples included in the final analysis. ADHD-related traits were assessed using behavioral questionnaires and the Conners Continuous Performance Test. Resting-state functional magnetic resonance imaging was used to assess brain functional connectivity in four ADHD-relevant brain networks. We applied covariate-adjusted linear regression models to examine associations between HFRs and outcomes, applying a false discovery rate correction of 0.1 for multiple comparisons. Several nominally significant associations were identified before correction, including a positive association between anti-DP and attention problems, negative associations between Dec602 and hyperactivity, and BB153 and hit reaction time variability. However, none remained significant after multiple comparison correction. Overall, we observed no significant associations between HFR concentrations in plasma or stool and ADHD-related traits or brain functional connectivity, suggesting that there is limited evidence for a link between them.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".