The influence of persistent organic pollutants in the traditional Inuit diet on markers of inflammation
Bibliographic record
Abstract
Concentrations of persistent organic pollutants (POPs) are high in Inuit living predominately on the traditional marine diet. Adverse effects of POPs include disruption of the immune system and cardiovascular diseases that are frequent in Greenland Inuit. We aimed to assess the association between exposure to POPs from the marine diet and inflammation, taking into account other factors such as vitamin D. We invited Inuit and non-Inuit living in settlements or the town in rural East Greenland or in the capital city Nuuk. Participants completed a food frequency questionnaire and donated a blood sample for measurement of the two markers of inflammation YKL-40 and hsCRP, 25-hydroxy-vitamin D, eleven organochlorine pesticides (OCPs), fourteen polychlorinated biphenyls (PCBs), one polybrominated biphenyl, and nine polybrominated diphenyl ethers (PBDEs) adjusted to the serum lipid content. Participants were 50 through 69 years old, living in settlements, town or city (n = 151/173/211; 95% participation rate). ΣOCP, ΣPCB and ΣPBDE serum levels were higher in Inuit than in non-Inuit (p<0.001/ p<0.001/ p<0.001), in older individuals (p<0.001/p<0.001/p = 0.002) and in participants with the highest intake of Greenlandic food items (p<0.001/p<0.001/p<0.001). Both YKL-40 and hsCRP serum levels were higher in Inuit compared to non-Inuit (p<0.001/p = 0.001), and increased with age (p<0.001/p = 0.001) and with the intake of Greenlandic food items (p<0.001/p = 0.002). Multivariate analysis conformed to a marked influence on both YKL-40 and hsCRP by ΣOCP (p<0.001/p<0.001) and ΣPCBs (p<0.001/p = 0.001) after adjusting for age, BMI, vitamin D, alcohol and smoking. POP levels were associated with the intake of the traditional Inuit diet and with markers of inflammation. This supports a pro-inflammatory role of POPs to promote chronic diseases common to populations in Greenland. These data inform guidelines on 'the Arctic dilemma' and encourage follow-up on the ageing Arctic populations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".