Indoor environment, physiological factors, and diet as predictors of halogenated flame retardant levels in stool and plasma of children from a Canadian cohort
Bibliographic record
Abstract
Exposure to halogenated flame retardants (HFRs) has been associated with various adverse effects on human health. Human exposure to HFRs mainly occurs through diet, ingesting contaminated dust, and inhaling contaminated air. Understanding and characterizing the variables linked to these exposure pathways is essential for developing effective risk assessment and mitigation strategies. We investigated indoor environment quality, physiological factors, and diet as potential predictors of HFRs concentration in children's plasma and stool. A selected number of HFRs, including polybrominated diphenyl ethers (PBDEs), Dechlorane-like compounds, and emerging halogenated flame retardants, were measured in children from eastern Quebec (Canada). Information on indoor environment quality, physiological factors, and diet was obtained through self-report questionnaires. Our results show that lower brominated compounds, which are more volatile, were primarily correlated to indoor environment quality. Notably, the use of air purifiers was associated with lower BDE47 and BDE100 levels in blood and newer residential buildings were associated with higher concentrations of BDE47. A significant seasonal variation was found in stool samples, with higher levels of lower brominated PBDEs (BDE47 and BDE100) in samples collected during summer. No association between household income or maternal education degree and HFRs was found. Among emerging compounds, Dec602 and Dec603 were associated with the most variables, including the use of air dehumidifiers, air conditioning, and air purifiers, and the child's age and body fat percentage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".