Systemic inflammation, diet, and place of residence modify lung function in Greenland Inuit
Bibliographic record
Abstract
Background: The preservation of lung health requires an understanding of the modifiable risk factors involved in airflow limitation. We aimed to determine the association between lung function, diet and systemic inflammation in a genetically homogenous population of Inuits residing in the arctic (Greenland) or Western Europe (Denmark). Methods: Two unselected Inuit populations were recruited, one living in Greenland (Urban (Nuuk) n=288; Rural (Uummannaq) n=183) and the other in Denmark (n=613). Lung function was measured using spirometry, and expressed as forced expiratory volume in one second (FEV 1 )/height (Ht). Systemic inflammation was measured by commercial enzyme linked immunoassay of serum C reactive protein (CRP), interleukin (IL)-6 and soluble CD163. Diet was assessed by food frequency questionnaire. Predictors of airflow limitation were assessed using multiple linear regression models. Results: The dietary composition differed significantly in the two regions, with high fish intake and low fruit intake in the arctic region and the reverse in Denmark. Consumption of wild meat (p=0.020), fish (p=0.025), and fruit (p=0.020); were positive predictors of FEV 1 /Ht ratio. Whereas systemic inflammation, determined by a high CRP (p=0.0001), IL-6 (p=0.003) and sCD163 (p=0.001), was associated with lower lung function. Conclusions: Among Greenlandic Inuits, lung function is associated with potentially modifiable risk factors including systemic inflammation and dietary intake. Specifically, high wild meat, fish and fruit intake had independent positive effects on lung function. These factors may play an important role in determining overall lung health.
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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 | 0.000 | 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".