The impact of air pollution on the incidence of diabetes and survival among prevalent diabetes cases
Bibliographic record
Abstract
Growing evidence implicates ambient air pollutants in the development of major chronic diseases and premature mortality. However, epidemiologic evidence linking air pollution to diabetes remains inconclusive. This study sought to determine the relationships between selected air pollutants (nitrogen dioxide [NO2], fine particulate matter [PM2.5], ozone [O3], and oxidant capacity [Ox; the redox-weighted average of O3 and NO2]) and the incidence of diabetes, as well as the risk of cardiovascular or diabetes mortality among individuals with prevalent diabetes. We followed two cohorts, which included 4.8 million Ontario adults free of diabetes and 452,590 Ontario adults with prevalent diabetes, from 2001 to 2015. Area-level air pollution exposures were assigned to subjects’ residential areas, and outcomes were ascertained using health administrative data with validated algorithms. We estimated hazard ratios for the association between each air pollutant and outcome using Cox proportional hazards models, and modelled the shape of the concentration-response relationships. Over the study period, 790,461 individuals were diagnosed with diabetes. Among those with prevalent diabetes, 26,653 died from diabetes and 64,773 died from cardiovascular diseases. For incident diabetes, each IQR increase in NO2 had a hazard ratio of 1.04 (95% CI: 1.03–1.05). This relationship was relatively robust to all sensitivity analyses considered, and exhibited a near-linear shape. There were also positive associations between incident diabetes and PM2.5, O3, and Ox, but these estimates were somewhat sensitive to different models considered. Among those with prevalent diabetes, almost all pollutants were associated with increased diabetes and cardiovascular mortality risk. The strongest association was observed between diabetes mortality and exposure to NO2 (HR = 1.08, 95% CI: 1.02–1.13). Selected air pollutants, especially NO2, were linked to an increased risk of incident diabetes, as well as risk of cardiovascular or diabetes mortality among persons with prevalent diabetes. As NO2 is frequently used as a proxy for road traffic exposures, this result may indicate that traffic-related air pollution has the strongest effect on diabetes etiology and survival after diabetes development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".