Thyroid autoimmunity in Greenlandic Inuit
Bibliographic record
Abstract
Objective: This study aimed to provide the first data on the occurrence of thyroid autoimmunity among Inuit in Greenland, a distinct ethnic group who is not iodine deficient. Design: This study is a population-based cross-sectional study. Methods: Data were collected in Nuuk in West Greenland and in Ammassalik district in East Greenland. Information on lifestyle, diet and diseases was obtained using questionnaires. Thyroid peroxidase antibody (TPOAb), thyroglobulin antibody (TGAb) and thyroid-stimulating hormone (TSH) were measured in serum. Iodine and creatinine were measured in spot urine samples. Results: The participation rate was 95% with 434 Inuit participants; 75% were smokers. Iodine excretion was 169 µg/24 h in urban West Greenland, 224 µg/24 h in the main town and 228 µg/24 h in settlements in rural East Greenland. TPOAb, TgAb or either of these was measured in the serum from 3.7, 5.9 and 8.3% of participants, respectively. TPOAb or TgAb was found in 9.3% of Inuit women and 7.5% of men and more frequently, in East Greenland Inuit with the higher iodine excretion (P = 0.02). There was some evidence suggesting that thyroid autoimmunity was more frequent among non-smokers (12.5%) compared to smokers (7.0%). Harbouring a thyroid autoantibody was most frequent in participants with TSH above 3.6 mIU/L (P < 0.001). Conclusion: Thyroid autoantibodies were rare among Greenland Inuit. While iodine nutrition was associated with autoimmunity similarly to other ethnic groups, the influence of sex and smoking was limited. This could suggest genetic component in Inuit, but the impact of cold, selenium and persistent organic pollutants needs to be elucidated.
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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 | 0.000 |
| 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) | 0.001 | 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".