Association between physical multimorbidity and suicidal ideation in young adults with obesity
Bibliographic record
Abstract
Obesity is considered as one of the entrance point of multimorbidity and has an impact on physical and mental health. While some evidence points out to a possible relationship between obesity, multimorbidity and suicidal spectrum, little provide a direct association. Thus, the aim of the present study was to examine the co-occurring effect of both multimorbidity and obesity on suicidal ideation. Methods A cross-sectional analysis of the Canadian Community Health Survey data was conducted. A weighted sample of young adults (18 to 30 years-old) with obesity, from the province of Quebec, of the 2005 (n=394) and 2015–2016 (n=295) cycles were investigated independently. Multimorbidity, suicidal ideation, and health behaviours were self-reported. Results The prevalence of physical multimorbidity was 15% in 2005 and 18% in 2015–2016. Adjusted logistic regressions showed an association between multimorbidity and suicidal ideation (2005: OR 3.59, 95% CI 1.89-6.81; 2015–2016: OR 3.72, 95% CI 1.88-7.36). Among covariates, the significant association of sex (OR 1.98; 95% CI 1.16-3.37) and educational status (OR 3.27; 95% CI 1.49-7.18) in the 2005 cycle, were not replicated in the 2015–2016 cycle (education: OR 0.93; 95% CI 0.46-1.87; sex (OR 0.90; 95% CI 0.48-1.69). Finally, our results suggest no consistent association between health behaviours and suicidal ideation.Conclusion Multimorbidity seems to be associated with suicidal ideation among those with obesity. Attention should be given to multimorbidity management within obesity-related interventions for young people, as the development of suicidal ideation may also be prevented.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".