Lung function measurements in the Greenlandic Inuit population: results from the Greenlandic health survey 2017–2019
Bibliographic record
Abstract
Background Little is known about lung function in Inuit. The aim of this study was to describe lung function and the prevalence of obstructive and restrictive lung disease among Inuit in GreenlandMethods During the 2017–2019 Health Survey, spirometry, with forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio in liters (L), and percent of predicted value (pred%) were recorded according to Global Lung function Initiative standard reference values (GLI). Smoking history was obtained. Obstructive spirometry was defined as FEV1/FVC <70%. Restrictive spirometry was proposed by FVC < 80% and FEV1/FVC >90%.Results Based on validated spirometries, 795/2084 persons were included in this cross-sectional, descriptive study. Of those, 54.6% were current- and 27.7% former smokers. In Inuit, normal lung function was higher than predicted GLI (FEV1 107.2 pred%/FVC 113.5 pred%). In total, 106 (13.3%) were found to have an obstructive lung function measurement and 11 (1.4%) had a restrictive pattern. Among current smokers, the prevalence of obstructive lung function was 16.4%. An accelerated decline in lung function was observed > 50 years old (y.o), compared to <50 y.o.Conclusion This study indicates that Inuit has higher absolute lung function values than standard GLI, despite the large proportion of smokers, which indicate a need for Inuit reference values in the daily clinical praxis. The high prevalence of obstructive lung function and rapid decline in lung function indicates the need for fucus on health issues that may affect lung health in Greenland.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".