Determinants of polyfluoroalkyl substances and perfluoroalkyl substances (PFAS) biomarkers in First Nations Communities of the Northwest Territories and Yukon
Bibliographic record
Abstract
Background and Aim: Polyfluoroalkyl substances and perfluoroalkyl substances (PFAS) include numerous anthropogenic chemicals used in firefighting foams, non-stick cookware, food packaging, and waterproof clothing. Research has shown some PFAS exposures appear to be decreasing in the general population of Canada. In contrast, prior to a human biomonitoring research completed in Old Crow, Yukon and the Mackenzie Valley, Northwest Territories, much less was known on exposure patterns for Dene and Gwich’in populations. This research aims to describe exposure patterns among these populations by identifying determinants and potential sources of PFAS exposure for participants. Method: Nine PFAS (including: perfluorooctanoic acid (PFOA), perfluorooctane sulphonic acid (PFOS), perfluorohexane sulphonic acid (PFHxS), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluoroundecanoic acid (PFUdA), perfluorobutanoic acid (PFBA), perfluorohexanoic acid (PFHxA), and perfluorobutane sulphonic acid (PFBS)) were quantified using liquid chromatography mass spectrometry in blood samples collected in Old Crow (n=54) and the Dehcho Region, Northwest Territories (n=125). Results: This research showed that, for most PFAS, levels in Old Crow and the Dehcho Region, Northwest Territories were similar or lower to those observed in the Canadian Health Measures Survey. The key exception to this was perfluorononanoic acid (PFNA) which, relative to the CHMS (0.51 μg/L), was approximately 1.8 times higher in Old Crow (0.94 μg/L) and 2.8 times higher in Dehcho (1.42 μg/L) than observed in the general Canadian population. This presentation will report results describing the associations, using multivariable logistic regression, between PFAS levels and consumption of traditional food, lifestyle factors, and demographics. Conclusions: The results highlight the importance of expanding PFAS analytical suites beyond PFOS and PFOA for both human biomonitoring as well as environmental sampling in northern environments. Keywords: Biomonitoring; Contaminants; Indigenous; Traditional Foods; PFAS; PFNA
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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".