Dental problems and chronic diseases in mentally ill homeless adults: a cross-sectional study
Bibliographic record
Abstract
Abstract Background Dental problems (DPs) and physical chronic diseases (CDs) are highly prevalent and incident in people with low socioeconomic status such as homeless individuals. Yet, evidence on the association between DPs and physical CDs in this population is limited. In the present study, we assessed the association between DPs and type and number of CDs in individuals experienced chronic homelessness and serious mental health problems. Methods We analyzed cross-sectional baseline data from 575 homeless adults with serious mental health problems participating in the Toronto site of the At Home/Chez Soi randomized controlled trial. Chronic DPs (lasting at least 6 months) were the primary exposure variable. Presence of self-reported CDs, including heart disease, effect of stroke, hypertension, diabetes, asthma, chronic bronchitis/emphysema, stomach or intestinal ulcer, inflammatory bowel disease, migraine, thyroid problems, arthritis, kidney/bladder problems, liver disease (other than hepatitis), and iron-deficiency anemia, were the primary outcomes. The total number of CDs was also analyzed as a secondary outcome. Logistic regression models were used to assess the association between DPs with each of the studied CDs, and negative binomial regression was used to test the association between DPs with the number of CDs. Results In our 575 homeless participants (68.5% males) with mean age 40.3 (11.8) years, a high proportion had DPs (42.5%). The presence of DPs was positively associated with heart disease (adjusted odds ratio (AOR):4.19,1.67–10.52), diabetes (AOR:2.17,1.13–4.17), chronic bronchitis (AOR:2.34,1.28–4.29), stomach or intestinal ulcer (AOR:3.48,1.80–6.73), inflammatory bowel disease (AOR:2.52,1.38–4.60), migraine (AOR:1.80,1.20–2.72), arthritis (AOR:2.71,1.71–4.29), kidney/bladder problems (AOR:2.43,1.30–4.54), and iron-deficiency anemia (AOR:3.28,1.90–5.65). DPs were also associated with a higher number of CDs (IRR: 1.62,1.38–1.90). Conclusion Dental health problems in homeless individuals with serious mental disorders are associated with several CDs. Dental care should be better integrated into existing social and health programs serving this population to improve their overall health status. The AH/CS study is registered with the International Standard Randomized Control Trial Number Register (ISRCTN42520374).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".