Widespread occurrence of pesticides in low-income housing
Bibliographic record
Abstract
Abstract Background Low socioeconomic status (SES) residents living in social housing, which is subsidized by government or government-funded agencies, may have higher exposures to pesticides used in indoor residences since pesticides are applied due to structural deficiencies, poor maintenance, etc. Objective To estimate exposure of residents in low-SES social housing built in the 1970s to legacy and current-use pesticides and to investigate factors related to exposures. Methods Twenty-eight particle-phase pesticides were measured in the indoor air of 46 units in seven low-income social housing, multi-unit residential buildings (MURBs) in Toronto, Canada using portable air cleaners deployed for 1 week in 2017. Pesticides analyzed were legacy and current use in the classes: organochlorines, organophosphates, pyrethroids, and strobilurins. Results At least one pesticide was detected in 89% of the units with detection frequencies (DF) for individual pesticides of up to 50%, including legacy organochlorines and current-use pesticides. Current-use pyrethroids had the highest DF and concentrations, with the highest particle-phase concentration for pyrethrin I at 32,000 pg/m 3 . Heptachlor, restricted for use in Canada in 1985, had the highest estimated maximum total air (particle plus gas phase) concentration of 443,000 pg/m 3 . Heptachlor, lindane, endosulfan I, chlorothalonil, allethrin, and permethrin (except in one study) had higher concentrations than those measured in low-income residences reported elsewhere. In addition to the intentional use of pesticides to control pests and their use in building materials and paints, tobacco smoking was significantly correlated with the concentrations of five pesticides used on tobacco crops. The distribution of pesticides with high DF in individual buildings suggested that pest eradication programs by the building management and/or pesticide use by residents were the major sources of measured pesticides. Impact Low-income social housing fills a much-needed demand, but the residences are prone to pest infestation and hence pesticide use. We found exposure to at least 1 of 28 particle-phase pesticides in 89% of all 46 units tested, with the highest DF and concentrations for current-use pyrethroids and long-banned organochlorines (e.g., DDT, heptachlor) due to very high persistence indoors. Also measured were several pesticides not registered for use indoors, e.g., strobilurins used to treat building materials and pesticides used on tobacco crops. These results, which are the first Canadian data for most pesticides indoors, show widespread exposure to numerous pesticides.
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 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".