Associations of prenatal exposure to residential greenspace and active living environments with cerebral palsy: A population-based cohort study in Ontario, Canada
Bibliographic record
Abstract
Background: Prenatal exposure to environmental factors, such as greenspace and active living environments, has been associated with numerous health benefits, including improved neurodevelopmental outcomes. Although cerebral palsy (CP) is not typically linked to these exposures, emerging evidence suggests that exposure to environmental factors during pregnancy may influence brain development, making it important to explore their potential role in CP risk. Methods: We conducted a retrospective cohort study using health administrative data from Ontario, Canada, between 1 April 2002 and 31 December 2020. We identified 1,436,411 mother-infant pairs, of which 2,883 were diagnosed with CP during the follow-up period. Exposures of interest included the Normalized Difference Vegetation Index (NDVI), Green View Index (GVI), and park proximity. The Canadian Active Living Environments index was also utilized. Cox proportional hazards models estimated hazard ratios (HRs) for CP risk associated with these environmental exposures, adjusting for potential confounders. Results: Interquartile range (IQR) increases in NDVI (HR = 1.040; 95% confidence interval [CI]: 0.987, 1.096; per IQR = 0.1) and GVI (HR =0.989; 95% CI: 0.943, 1.038; per IQR = 10.05%) were not significantly associated with CP risk. Similar results were found for quartile increases of NDVI and GVI. Residential proximity to parks at birth was associated with a reduction in CP risk (HR = 0.946; 95% CI: 0.904, 0.990; per 0.06 increase in park proximity index), after adjusting for active living environment and air pollution. Conclusions: Our study suggests that living closer to parks reduces the risk of CP. Further research should investigate these protective effects and consider other dimensions of greenspace quality and usability.
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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) | 0.001 | 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".