Mortality among residents of shelters, rooming houses, and hotels in Canada: 11 year follow-up study
Bibliographic record
Abstract
OBJECTIVE: To examine mortality in a representative nationwide sample of homeless and marginally housed people living in shelters, rooming houses, and hotels. DESIGN: Follow-up study. SETTING: Canada 1991-2001. PARTICIPANTS: 15 100 homeless and marginally housed people enumerated in 1991 census. MAIN OUTCOME MEASURES: Age specific and age standardised mortality rates, remaining life expectancies at age 25, and probabilities of survival from age 25 to 75. Data were compared with data from the poorest and richest income fifths as well as with data for the entire cohort RESULTS: Of the homeless and marginally housed people, 3280 died. Mortality rates among these people were substantially higher than rates in the poorest income fifth, with the highest rate ratios seen at younger ages. Among those who were homeless or marginally housed, the probability of survival to age 75 was 32% (95% confidence interval 30% to 34%) in men and 60% (56% to 63%) in women. Remaining life expectancy at age 25 was 42 years (42 to 43) and 52 years (50 to 53), respectively. Compared with the entire cohort, mortality rate ratios for men and women, respectively, were 11.5 (8.8 to 15.0) and 9.2 (5.5 to 15.2) for drug related deaths, 6.4 (5.3 to 7.7) and 8.2 (5.0 to 13.4) for alcohol related deaths, 4.8 (3.9 to 5.9) and 3.8 (2.7 to 5.4) for mental disorders, and 2.3 (1.8 to 3.1) and 5.6 (3.2 to 9.6) for suicide. For both sexes, the largest differences in mortality rates were for smoking related diseases, ischaemic heart disease, and respiratory diseases. CONCLUSIONS: Living in shelters, rooming houses, and hotels is associated with much higher mortality than expected on the basis of low income alone. Reducing the excessively high rates of premature mortality in this population would require interventions to address deaths related to smoking, alcohol, and drugs, and mental disorders and suicide, among other causes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".