Suicide and HIV as leading causes of death among gay and bisexual men: a comparison of estimated mortality and published research
Bibliographic record
Abstract
Gay and bisexual men experience numerous health disparities relative to heterosexual men, including high rates of HIV and suicidal behavior. Systematic community health assessments could provide direct comparisons of the burden of mortality across diseases and thus facilitate the prioritization of public health activities; however, such assessments have been precluded by the absence of sexual orientation information in vital statistics records. In this context, we used population attributable fraction to derive and compare indirect estimates of mortality for both HIV and suicide. Assuming that 2% of Canadian men are gay or bisexual, and that these men are 42 times more likely to die from HIV and 4 times more likely to die from suicide, we estimated that in 2011, suicide resulted in 46 deaths per 100,000 gay and bisexual men, while HIV resulted in 30 deaths per 100,000. Based on these estimates, suicide surpassed HIV as a leading cause of premature mortality for gay and bisexual men in 2007. Despite the large burden of suicide among gay and bisexual men, research attending to the issue in biomedical, psychology, and social science literatures is sparse, with at least 10 times fewer citations than for HIV between 2003 and 2012. We urge researchers, practitioners, and community leaders to broaden the scope of gay and bisexual men’s public health priorities to include suicide and other high burden health inequities.
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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 | 0.019 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.021 | 0.015 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".