Neighbourhood socioeconomic position and risks of major chronic diseases and all-cause mortality: a quasi-experimental study
Bibliographic record
Abstract
OBJECTIVES: This study estimated the health impacts of neighbourhood socioeconomic position (SEP) among public housing residents. Because applicants to public housing were assigned to housing projects primarily based on factors other than personal choice, we capitalised on a quasirandom source of variation in neighbourhood of residence to obtain more valid estimates of the health impacts of neighbourhood SEP. DESIGN: Quasiexperimental study. SETTING: Greater Metropolitan Toronto area, Canada. PARTICIPANTS: Residents (24 019-28 858 adults age ≥30 years in 1994 for all outcomes except for asthma, for which the sample was expanded to 66 627 individuals age ≥4 years) of public housing on 1 January 1994. OUTCOME MEASURES: Incident hypertension, diabetes, asthma, and acute myocardial infarction (MI) and all-cause mortality between 1 January 1994 and 31 December 2006. We used multivariate Cox proportional hazards models to estimate hazard ratios (HRs) for the associations between the quartile of census tract-level SEP and the risk of diagnosis of each health outcome as well as death from any cause. RESULTS: Living in a public housing project in the second highest neighbourhood SEP quartile (Q3) was associated with lower hazards of acute MI (HR=0.76, 95% CI 0.54 to 1.07; P=0.11), incident asthma (HR=0.80, 95% CI 0.67 to 0.96; P=0.02) and all-cause mortality (HR=0.86, 95% CI 0.73 to 1.01; P=0.06) compared to living in the lowest neighbourhood SEP quartile (Q1), although only the trend for incident asthma reached statistical significance (P for trend=0.04). By contrast, the associations corresponding to living in the highest versus lowest quartile of median household income (Q4 vs Q1) were neither consistent in direction nor significant. The inconsistent associations may partly be attributed to selection and status incongruity. CONCLUSION: This study provides new evidence compatible with protective influences of higher neighbourhood SEP on health outcomes, particularly asthma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".