Exposure to Particulate Matter of Different Fraction Sizes and Blood Glucose in Children and Adolescents
Bibliographic record
Abstract
PDS 67: Outdoor air pollution cardiometabolic effects, Exhibition Hall (PDS), Ground floor, August 27, 2019, 4:30 PM - 5:30 PM Background: The health effects of particulate matter (PM) air pollution on glucose metabolism have been rarely examined in children and adolescents. We investigated the associations between long-term PM exposure and blood glucose and prevalence of impaired fasting glucose in a large population of Chinese children and adolescents. Methods: In 2013, a total of 11,814 children and adolescents aged 7 to 18 years were recruited from seven provinces in China. Fasting blood sample was taken for the measurement of blood glucose. Satellite-based spatial-temporal models were used to estimate exposure to ambient submicrometer particles (PM1), fine particles (PM2.5) and thoracic particles (PM10). Cross-sectional analyses were performed using multivariable linear and logistic regression models. Results: After adjustment for a range of covariates, every 10 µg/m3 increment in PM1 and PM2.5 concentrations was associated with 0.109 [95% confidence interval (CI): 0.092,0.126] and 0.078 (95% CI: 0.063,0.093) mmol/L higher blood glucose levels, respectively. Consistently, PM1 and PM2.5 were associated with higher prevalence of impaired fasting glucose [odds ratio per 10 µg/m3 increment in PM1 and PM2.5: 1.38 (1.14, 1.65) and 1.17 (1.02, 1.36), respectively]. No significant associations were found for PM10. Conclusions: We found that long-term exposure to PM1 and PM2.5 air pollution was associated with increased levels of blood glucose and higher prevalence of impaired fasting glucose in children and adolescents. The smaller fraction size of PM, the stronger impacts.
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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 | 0.000 | 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) | 0.001 | 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".