Greenness and Health: Using Linked Data to Disentangle Effects from Spatially Crrelated Built Environment Factors
Bibliographic record
Abstract
Greenness and Health: Using Linked Data to Disentangle Effects from Spatially Crrelated Built Environment FactorsAbstract Number:2915 Michael Brauer* and Perry Hystad * Michael Brauer* The University of British Columbia, Canada, E-mail Address: [email protected] and Perry Hystad * Oregon State University, United States, E-mail Address: [email protected] AbstractBuilt environment features including greenness have been associated with improvements in a diverse range of health outcomes, including birth outcomes and adult chronic diseases; however, it is important to differentiate the effects of greenness from otherspatially correlated exposures related to the built environment which may also impact health. We examined associations between residential greenness (satellite-derived normalized difference vegetation index (NDVI) within 100 meters of study participants' homes), birth outcomes and adult cardiovascular disease in two linked population-based administrative data cohorts in Vancouver, British Columbia, Canada: a cohort of 64,705 singleton births and a cohort of 467,994 adults aged 45-85 years. We evaluatedassociations between greenness with birth outcomes and with cardiovascular mortality and hospitalization as well as their sensitivity to spatially correlated built environmental factors also associated with health, including exposure to air pollution and noise, neighborhood walkability and distance to the nearest park. An interquartile range increase in greenness [0.1 NDVI] was associated with an increase in term birth weight of 20.6 grams (95% CI: 16.5-24.7) as well as decreases in likelihood of being small for gestational age, and very (<30 weeks) and moderately (30-36 weeks) preterm birth. The greenness-birth outcome associations were robust to adjustment for air pollution and noise exposure, neighborhood walkability, and park proximity.Results for adult cardiovascular mortality and hospitalization will also be presented. Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors ? suggesting that alternative pathways (e.g. psychosocial and psychological mechanisms) may underlie associations between residential greenness and birth outcomes.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".