Association between physical multimorbidity and suicidal ideation in young adults with obesity
Bibliographic record
Abstract
Background Through obesity, unhealthy lifestyle behaviors (such as sedentarism, poor diet, excessive tobacco and alcohol consumption) affect mental health and ultimately increase suicide risk. As a matter of fact, obesity is considered as an entrance point of multimorbidity (co-occurrence of two comorbidities or more) given its impact on physical and mental health. Regardless of proven individual links between obesity, multimorbidity and suicide-related risk, their effect on suicidal ideation was minimally investigated. Thus, the purpose of the present study was to explore the co-occurrence effect of physical multimorbidity and obesity on suicidal ideation. Methods Cross-sectional study on a sample of young adults with obesity in Quebec, extracted from the 2005 and 2015-2016 Canadian Community Health Survey. Health behaviors (tobacco consumption and physical activity) were assessed. Multimorbidity and obesity were objectively measured. Suicidal ideation was self-reported based on personal experiences with death thoughts during the previous year. Results Between the 2 cycles, a slight difference in physical multimorbidity prevalence was observed. Adjusted logistic regressions demonstrated replicated links between multimorbidity and suicidal ideation. Moreover, no consistent impact of health behaviors or covariates (sex, age and education) on suicidal ideation was found. Conclusion Multimorbidity appears to be associated with suicidal ideation amongst those with obesity. Multimorbidity management should therefore be highlighted within obesity-related interventions for young people, in hopes of preventing suicidal thoughts.
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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 | 0.000 |
| 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".