Associations between dietary profiles and perfluoroalkyl acids in Inuit youth and adults
Bibliographic record
Abstract
BACKGROUND: Perfluoroalkyl acids (PFAAs), a subset of perfluoroalkyl substances (PFAS), are synthetic chemicals used in industrial and consumer applications. They are exceptionally stable and highly mobile in the environment, and were detected in high concentrations in Arctic wildlife and Nunavik Inuit. The study's objective was to study the association between dietary profiles in Nunavik and plasma PFAAs concentrations. METHODS: The study used data from the Qanuilirpitaa? 2017 Nunavik Inuit Health Survey (Q2017) (N = 1172) on Inuit adults aged 16-80 years. Nine PFAAs congeners were measured in plasma samples (six were detected). Dietary profiles were identified using latent profile analysis. Two sets of dietary profiles were included; the first included market (store-bought) and country foods (harvested/hunted from the land), and the second included only country foods. Multiple linear regression models regressed log-transformed PFAAs concentrations against the dietary profiles, adjusting for sociodemographic variables. RESULTS: We identified statistically significant 24.54-57.55 % increases in all PFAAs congeners (PFOA, PFNA, PFDA, PFUnDA, PFHxS, and PFOS) in the dietary profile defined by frequent country food consumption compared to the dietary profile defined by frequent market food consumption. Individuals defined by low consumption of foods (related to food insecurity) had higher concentrations of six PFAAs compared to individuals with frequent market food consumption. The associations were stronger with profiles defined by more frequent country food consumption, and particularly those with increased marine mammal consumption. PFDA, PFUnDA, and PFOS were particularly associated with high country food consumption frequency, such that their concentrations increased by approximately 67-83 % compared to those reporting no or very little consumption of any country foods. CONCLUSIONS: Increased country food consumption was strongly associated with higher PFAAs concentrations, particularly PFOS, PFDA, and PFUnDA. The results provide further evidence that the quality of country foods is being threatened by PFAAs contamination. Additional national and international regulations are required to protect the Arctic and its inhabitants from these pollutants.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".