Neighborhood greenness, but not walkability, is associated with self-rated measures of health in older adults: An analysis of the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
The purpose of this analysis was to determine whether older Canadians residing in neighborhoods characterized by denser greenness or higher walkability have better self-reported health outcomes at 3-year follow-up. Data on self-reported chronic diseases (composite score of 10 conditions) and self-rated measures of health (general health, mental health, and healthy aging) from the Canadian Longitudinal Study on Aging (CLSA) were used as outcomes. The CLSA database was linked with the Canadian Active Living Environments (Can-ALE), a measure of walkability, and Normalized Difference Vegetation Index (NDVI), a measure of greenness. The analytic sample consisted of adults aged 65 and older (n = 15339, age 72.9 ± 5.6, 50 % female). Crude and adjusted associations were assessed using Poisson regression and proportional odds regression modelling. The 4th quartile of greenness was associated with the chronic disease index and all three measures of self-rated health (general health, mental health, and healthy aging); living in a neighborhood with the highest greenness was associated with better health three years later when compared to those in the lowest quartile of greenness. After adjustment for covariates of age, sex, income, education, and physical activity levels, only the association for the 3rd quartile of greenness was significantly associated with general health (OR: 0.90, 95 %CI: 0.81–0.99) and mental health (OR: 0.88, 95 %CI: 0.79-0.97). Can-ALE was not associated with any of the outcomes assessed. Future research assessing perceived environmental walkability and geriatric relevant health outcomes rather than chronic disease may provide greater insight into our understanding of age-friendly environments.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".