The Contribution of Neighbourhood Material and Social Deprivation to Survival: A 22-Year Follow-up of More than 500,000 Canadians
Bibliographic record
Abstract
BACKGROUND: We examined the incremental influence on survival of neighbourhood material and social deprivation while accounting for individual level socioeconomic status in a large population-based cohort of Canadians. METHODS: More than 500,000 adults were followed for 22 years between 1982 and 2004. Tax records provided information on sex, income, marital status and postal code while a linkage was used to determine vital status. Cox models were used to estimate hazard ratios (HR) for quintiles of neighbourhood material and social deprivation. RESULTS: There were 180,000 deaths over the follow-up period. In unadjusted analyses, those living in the most materially deprived neighbourhoods had elevated risks of mortality (HR(males) 1.37, 95% CI: 1.33-1.41; HR(females) 1.20, 95% CI: 1.16-1.24) when compared with those living in the least deprived neighbourhoods. Mortality risk was also elevated for those living in socially deprived neighbourhoods (HR(males) 1.15, CI: 1.12-1.18; HR(females) 1.15, CI: 1.12-1.19). Mortality risk associated with material deprivation remained elevated in models that adjusted for individual factors (HR(males) 1.20, CI: 1.17-1.24; HR(females) 1.16, CI: 1.13-1.20) and this was also the case for social deprivation (HR(males) 1.12, CI: 1.09-1.15; HR(females) 1.09, CI: 1.05-1.12). Immigrant neighbourhoods were protective of mortality risk for both sexes. Being poor and living in the most socially advantageous neighbourhoods translated into a survival gap of 10% over those in the most socially deprived neighbourhoods. The gap for material neighbourhood deprivation was 7%. CONCLUSIONS: Living in socially and materially deprived Canadian neighbourhoods was associated with elevated mortality risk while we noted a "healthy immigrant neighbourhood effect". For those with low family incomes, living in socially and materially deprived areas negatively affected survival beyond their individual circumstances.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".