Relationships between exposure to air pollutants and subclinical indicators of cardiovascular disease risk in Canada and China
Why this work is in the frame
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Bibliographic record
Abstract
Next, I investigated the cross-sectional relation of air pollution and fasting plasma glucose (FPG) in 663 adults (ages 40-79 years) in the INTERMAP China Prospective Study, which included data from three provinces of China where household solid fuel burning is common.I used measured outdoor PM2.5 and personal exposures to PM2.5 and black carbon for 2-4 days, and one measure of FPG, to estimate associations for the same winter season as blood collection and for estimated annual weighted mean exposure across two seasons.I used mixed regression models with village-level random intercepts with inverse probability weighting to account for excluding participants without blood collection, adjusted for covariates.I did not find strong or consistent associations of FPG with personal exposure to PM2.5 or black carbon.Outdoor PM2.5 measured in the same season as FPG was associated with higher FPG (2.4%, 95% CI 0.2-4.5% per 100 g/m 3 ), with stronger associations among participants living in southern China, lower BMI, and without hypertension.Lastly, I analyzed data from a repeated measures study of 1,057 Chinese adults (ages 37 to 89 years) living in peri-urban Beijing and using solid fuel energy for cooking and heating, surveyed during two winter measurement campaigns in 2018-19 and 2019-20.I investigated the relation of PM2.5 air pollution and solid fuel energy use with FPG using mixed-effects regression, as well as diabetes status in a sub-set of participants using a mixed-effects prevalence ratio model, with village and participant-level random intercepts, adjusted for covariates.I found no evidence of detrimental relations between fuel use exposures and FPG, or diabetes status, and similarly no association between personal PM2.5 and these outcomes.These results were unchanged with adjustment for adiposity measures, lipids, and hypertension status, and no effect modification by sex, adiposity measures or hypertension was found.Weichenthal, for their academic support, perseverance, and for conducting data collection for the
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it