Air pollution and retinal vessel diameter and blood pressure in school-aged children in a region impacted by residential biomass burning
Bibliographic record
Abstract
Abstract Little is known about the early-life cardiovascular health impacts of fine particulate air pollution (PM2.5) and oxidant gases. A repeated-measures panel study was used to evaluate associations between outdoor PM2.5 and the combined oxidant capacity of O3 and NO2 (using a redox-weighted average, Ox) and retinal vessel diameter and blood pressure in children living in a region impacted by residential biomass burning. A median of 6 retinal vessel and blood pressure measurements were collected from 64 children (ages 4–12 years), for a total of 344 retinal measurements and 432 blood pressure measurements. Linear mixed-effect models were used to estimate associations between PM2.5 or Ox (same-day, 3-day, 7-day, and 21-day means) and retinal vessel diameter and blood pressure. Interactions between PM2.5 and Ox were also examined. Ox was inversely associated with retinal arteriolar diameter; the strongest association was observed for 7-day mean exposures, where each 10 ppb increase in Ox was associated with a 2.63 μm (95% CI − 4.63, − 0.63) decrease in arteriolar diameter. Moreover, Ox modified associations between PM2.5 and arteriolar diameter, with weak inverse associations observed between PM2.5 and arteriolar diameter only at higher concentrations of Ox. Our results suggest that outdoor air pollution impacts the retinal microvasculature of children and interactions between PM2.5 and Ox may play an important role in determining the magnitude and direction of these associations.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".