Environmental stressors and cardio-metabolic disease: part II–mechanistic insights
Bibliographic record
Abstract
Environmental factors can act as facilitators of chronic non-communicable diseases. Ambient noise and air pollution collectively outrank all other environmental risk factors in importance, contributing to over 75% of the disease and disability burden associated with known environmental risk factors. In the first part of this review, we discussed the global burden and epidemiologic evidence supporting the importance of these novel risk factors as facilitators of cardiometabolic disease. In this part, we will discuss pathophysiological mechanisms responsible for noise and air pollution-mediated effects. Akin to traditional cardiovascular risk factors, a considerable body of evidence suggests that these environmental agents induce low-grade inflammation, oxidative stress, vascular dysfunction, and autonomic nervous system imbalance, thereby facilitating the development of diseases such as hypertension and diabetes. Through their impact on traditional risk factors and via additional novel mechanisms, environmental risk factors may have much larger impact on cardiovascular events than currently appreciated. In the second part of this review, we discuss deficiencies and gaps in knowledge and opportunities for new research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".