Maternal Environmental Exposures and Birth Weight in Canada: Reducing Adverse Infant Health Outcomes
Bibliographic record
Abstract
This thesis examined the relationship between environmental exposures and adverse birth outcomes. The first study was a scoping review that investigated the associations between fine particulate matter (PM2.5), nitrogen dioxide (NO2), and greenness with birth weight (BW), low birth weight (LBW), and small-for-gestational-age (SGA) in Canada. Increased exposure to air pollutants was associated with decreased BW while the opposite was true for greenness. A slight association was found between increased PM2.5 exposure and LBW and SGA. Increased exposure to greenness was associated with decreased odds of SGA. The second study used logistic regression models to investigate the associations between PM2.5, NO2, and greenness with LBW. It was found that increased greenness was associated with decreased odds of LBW in infants from low-risk pregnancies in Ontario. The results of this thesis suggest that the maintenance of and access to green areas may lead to improved birth outcomes in Canada.
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 | 0.000 | 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) | 0.000 | 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 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".