Investigating Associations of Omega-3 Fatty Acids, Lung Function Decline, and Airway Obstruction
Bibliographic record
Abstract
Abstract Rationale Inflammation contributes to lung function decline and the development of chronic obstructive pulmonary disease. Omega-3 fatty acids have antiinflammatory properties and may benefit lung health. Objectives To investigate associations of omega-3 fatty acids with lung function decline and incident airway obstruction in a diverse sample of adults from general-population cohorts. Methods Complementary study designs: 1) longitudinal study of plasma phospholipid omega-3 fatty acids and repeated FEV1 and FVC measures in the NHLBI Pooled Cohorts Study and 2) two-sample Mendelian randomization (MR) study of genetically predicted omega-3 fatty acids and lung function parameters. Measurements and Main Results The longitudinal study found that higher omega-3 fatty acid levels were associated with attenuated lung function decline in 15,063 participants, with the largest effect sizes for the most metabolically downstream omega-3 fatty acid, docosahexaenoic acid (DHA). An increase in DHA of 1% of total fatty acids was associated with attenuations of 1.4 ml/yr for FEV1 (95% confidence interval [CI], 1.1–1.8) and 2.0 ml/yr for FVC (95% CI, 1.6–2.4) and a 7% lower incidence of spirometry-defined airway obstruction (95% CI, 0.89–0.97). DHA associations persisted across sexes and smoking histories and in Black, White, and Hispanic participants, with associations of the largest magnitude in former smokers and Hispanic participants. The MR study showed similar trends toward positive associations of genetically predicted downstream omega-3 fatty acids with FEV1 and FVC. Conclusions The longitudinal and MR studies provide evidence supporting beneficial effects of higher levels of downstream omega-3 fatty acids, especially DHA, on 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".