Risk Factors for Cardiovascular Disease in Homeless Adults
Bibliographic record
Abstract
BACKGROUND: Homeless people represent an extremely disadvantaged group in North America. Among older homeless men, cardiovascular disease (CVD) is the leading cause of death. The objective of this study was to examine cardiovascular risk factors in a representative sample of homeless adults and identify opportunities for improved risk factor modification. METHODS AND RESULTS: Homeless persons were randomly selected at shelters for single adults in Toronto. Response rate was 79%. Participants (n=202) underwent interviews, physical measurements, and blood sampling. The mean age of participants was 42 years, and 89% were men. The prevalence of smoking among homeless subjects (78%; 95% confidence interval [CI], 72% to 84%) was significantly higher than in the general population (standardized morbidity ratio [SMR], 254; 95% CI, 216 to 297). Hypertension, high cholesterol, and diabetes were not more prevalent than in the general population but were often poorly controlled. Homeless men were significantly less likely to be overweight or obese than men in the general population (SMR, 79; 95% CI, 63 to 98). Cocaine use in the last year was reported by 29% of subjects (95% CI, 23% to 36%). CVD was reported by 15% of subjects, fewer than one third of whom reported taking aspirin or cholesterol-lowering medication. According to multiple-risk-factor equations, the median estimated 10-year absolute risk of myocardial infarction or coronary death among homeless men aged 30 to 74 years was 5% (interquartile range, 3% to 9%). CONCLUSIONS: Cardiovascular risk factor modification is suboptimal among homeless adults in Toronto, despite universal health insurance. Multiple risk factor equations may underestimate true risk in this population because of inadequate accounting for factors such as cocaine use and heavy smoking.
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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 | 0.000 | 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) | 0.001 | 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".