Mortality from treatable illnesses in marginally housed adults: a prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Socially disadvantaged people experience greater risk for illnesses that may contribute to premature death. This study aimed to evaluate the impact of treatable illnesses on mortality among adults living in precarious housing. DESIGN: A prospective cohort based in a community sample. SETTING: A socially disadvantaged neighbourhood in Vancouver, Canada. PARTICIPANTS: Adults (N=371) living in single room occupancy hotels or recruited from the Downtown Community Court and followed for median 3.8 years. MAIN OUTCOME MEASURES: Participants were assessed for physical and mental illnesses for which treatment is currently available. We compared cohort mortality rates with 2009 Canadian rates. Left-truncated Cox proportional hazards modelling with age as the time scale was used to assess risk factors for earlier mortality. RESULTS: During 1269 person-years of observation, 31/371 (8%) of participants died. Compared with age-matched and sex-matched Canadians, the standardised mortality ratio was 8.29 (95% CI 5.83 to 11.79). Compared with those that had cleared the virus, active hepatitis C infection was a significant predictor for hepatic fibrosis adjusting for alcohol dependence and age (OR=2.96, CI 1.37 to 7.08). Among participants <55 years of age, psychosis (HR=8.12, CI 1.55 to 42.47) and hepatic fibrosis (HR=13.01, CI 3.56 to 47.57) were associated with earlier mortality. Treatment rates for these illnesses were low (psychosis: 32%, hepatitis C virus: 0%) compared with other common disorders (HIV: 57%, opioid dependence: 61%) in this population. CONCLUSIONS: Hepatic fibrosis and psychosis are associated with increased mortality in people living in marginal conditions. Timely diagnosis and intervention could reduce the high mortality in marginalised inner city populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".