Neighbourhood and Individual-Level Socially-Patterned Risk Factors Interact with Particulate Air Pollution to Modify Birth Weight: a Multilevel Analysis in British Columbia, Canada
Bibliographic record
Abstract
Introduction: Exposure to particulate air pollution is increasingly being recognized as an important risk factor in adverse perinatal outcomes; however, its potential interaction with socially-patterned risk factors such as maternal smoking, body mass index and neighbourhood deprivation could lead to synergistic effects. The purpose of this research is to examine the relationship between particulate matter (PM2.5) and birth weight and its potential interaction with socially-patterned risk factors. Methods: Birth records with several individual-level covariates were obtained from Perinatal Services British Columbia (N=98,563). The modeled PM2.5 (from a national land-use regression model) and deprivation index are validated 3rd party datasets and were linked to the individual births using 6-digit maternal residential postal codes. Linear random-coefficient models were employed to estimate the fixed effects and between-area variability of PM2.5 and neighbourhood deprivation on birth weight with several cross-level interactions being tested. Model residuals were mapped to test for spatial auto-correlation and model misspecification. Results: After controlling for individual-level covariates, deprivation was significantly associated with reduced birth weight (-8.3 grams, 95%CI=-9.4 to -7.2 per decile) and explained 36% of the between-area differences in birth weight. Adding PM2.5 into the model further explained 10% of the between-area variability and reduced birth weight by -27.3 grams (95%CI=-32.7 to -21.9) per unit increase (µg/m3). Significant ameliorative cross-level interaction effects were revealed between PM2.5 and maternal heavy smoking and with obesity, as well as between deprivation and PM2.5. Mapping model residuals showed areas of significant local spatial auto-correlation. Conclusion: We show evidence that heavy smoking and obesity interact with PM2.5 to modify its negative effect on birth weight. Research is ongoing to confirm these results.
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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 | 0.001 | 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".