Young Children’s Exposure to Chemicals of Concern in Their Sleeping Environment: An In-Home Study
Bibliographic record
Abstract
Sleeping microenvironments (SMEs) can expose young children to chemicals of concern. Using passive samplers, we measured the concentrations of ortho-phthalates (PAEs), organophosphate esters (OPEs), and UV-filters (benzophenones, salicylates, and phenolic benzotriazoles) in the bedroom air, SME, and released from mattresses in 25 bedrooms of children aged 6 months to 4 years in Toronto and Ottawa, Canada. We detected 28, 31, and 30 compounds in bedroom air, SME air, and mattresses, respectively. SME exceeded bedroom air concentrations, indicating elevated exposure while sleeping and sources from SME contents, with two exceptions. Higher concentrations of two PAEs and five OPEs (including isomers) in mattress versus SME samplers indicated that mattresses were a source. Bedding items were likely sources of tris(2-butoxyethyl) phosphate (TBOEP) where SME concentrations were significantly higher than those in mattress samplers. Older mattresses had higher concentrations of di-2-ethylhexyl phthalate (DEHP) and benzyl butyl phthalate (BzBP). These results indicate children's exposure to a range of chemicals of concern while sleeping, at higher concentrations than in their bedrooms. Practical steps to reduce exposure include limiting items in SMEs such as toys and frequently washing bedding. Also, these results should prompt stricter regulations and greater producer responsibility regarding harmful chemicals used in mattresses and SME articles.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".