Ambient air pollution and incidence of early-onset paediatric type 1 diabetes: A retrospective population-based cohort study
Bibliographic record
Abstract
Studies have reported increasing incidence rates of paediatric diabetes, especially among those aged 0–5 years. Epidemiological evidence linking ambient air pollution to paediatric diabetes remains mixed. This study investigated the association between maternal and early-life exposures to common air pollutants (NO2, PM2.5, O3, and oxidant capacity [Ox; the redox-weighted average of O3 and NO2]) and the incidence of paediatric diabetes in children up to 6 years of age. All registered singleton births in Ontario, Ca nada occurring between April 1st, 2006 and March 31st, 2012 were included through linkage from health administrative data. Monthly exposures to NO2, PM2.5, O3, and Ox were estimated across trimesters, the entire pregnancy period and during childhood. Random effects Cox proportional hazards models were used to assess the relationships with paediatric diabetes incidence while controlling for important covariates. We also modelled the shape of concentration-response (CR) relationships. There were 1094 children out of a cohort of 754,698 diagnosed with diabetes before the age of six. O3 exposures during the first trimester of pregnancy were associated with paediatric diabetes incidence (hazard ratio (HR) per interquartile (IQR) increase = 2.00, 95% CI: 1.04–3.86). The CR relationship between O3 during the first trimester and paediatric diabetes incidence appeared to have a risk threshold, in which there was little-to-no risk below 25 ppb of O3, while above this level risk increased sigmoidally. No other associations were observed. O3 exposures during a critical period of development were associated with an increased risk of paediatric diabetes incidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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 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".