The Intersection of Sexual Orientation, Substance Use, and Mental Health: Findings from Hints 5
Bibliographic record
Abstract
In this study, we aimed to investigate (1) the association of tobacco and e-cigarette use with sexual orientation (LGBTQ and heterosexual individuals) and (2) the difference in the association of tobacco and e-cigarette use with self-reported depression by sexual orientation. METHODS: The data for this study were obtained from the Health Information National Trends Survey (HINTS 5, Cycle 4). Sample participants included 3583 adults (93.87% heterosexuals). We used multinomial regression to measure the relative risk ratios (RRRs) of being a former and current user versus never a user of tobacco and e-cigarettes and binomial regression to measure the odds ratios of depression between the LGBTQ and heterosexuals. RESULTS: Current smoking prevalence is higher among LGBTQ participants (17.3%) compared to heterosexuals (11.0%). The disparity is even greater for e-cigarette use, with 7.3% of LGBTQ participants being current users versus 2.8% of heterosexuals and 24.5% of LGBTQ participants being former users compared to 9.3% of heterosexuals. Compared to heterosexuals, the relative risk ratio of being a current tobacco user among the LGBTQ participants was about 1.75 times higher [RRR = 1.75, 95%CI = 1.16, 2.64], and that of e-cigarette use was about 2.8 times higher [RRR = 2.81, 95%CI = 1.57, 5.05]. Among current e-cigarette users, heterosexual participants had 1.9 percentage points [risk difference = 1.94, 95%CI = 1.20, 3.13] higher probability of depression, whereas among the LGBTQ participants, the risk was about 3.7 times higher [OR = 3.67, 95%CI = 1.06, 12.74]. CONCLUSIONS: Our findings conclude that the LGBTQ are more likely to use tobacco and e-cigarettes compared to heterosexuals and that the risk of depression from e-cigarette smoking is more pronounced among the LGBTQ participants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".