Relation between income, air pollution and mortality: a cohort study.
Bibliographic record
Abstract
BACKGROUND: Community levels of air pollution have been associated with variability in mortality rates, but previous studies have inferred exposure to pollutants on a citywide basis. We investigated mortality in relation to neighbourhood levels of income and air pollution in an urban area. METHODS: We identified 5228 people in the Hamilton-Burlington area of southern Ontario who had been referred for pulmonary function testing between 1985 and 1999. Nonaccidental deaths that occurred in this group between 1992 and 1999 were ascertained from the Ontario Mortality Registry. Mean household income was estimated by linking the subjects' postal codes with the 1996 census. Mean neighbourhood levels of total suspended particulates and sulfur dioxide were estimated by interpolation from data from a network of sampling stations. We used proportional hazards regression models to compute mortality risk in relation to income and pollutant levels, while adjusting for pulmonary function, body mass index and diagnoses of chronic disease. Household incomes and pollutant levels were each divided into 2 risk categories (low and high) at the median. RESULTS: Mean pollutant levels tended to be higher in lower-income neighbourhoods. Both income and pollutant levels were associated with mortality differences. Compared with people in the most favourable category (higher incomes and lower particulate levels), those with all other income-particulate combinations had a higher risk of death from nonaccidental causes (lower incomes and higher particulate levels: relative risk [RR] 2.62, 95% confidence interval [CI] 1.67-4.13; lower incomes and lower particulate levels: RR 1.82, 95% CI 1.30-2.55; higher incomes and higher particulate levels: RR 1.33, 95% CI 1.12-1.57). Similar results were observed for sulfur dioxide. The relative risk was lower at older ages. INTERPRETATION: Mortality rates varied by neighbourhood of residence in this cohort of people whose lung function was tested. Two of the broader determinants of health--income and air pollution levels--were important correlates of mortality in this population.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".