Association of secondhand smoke exposure with mental health in men and women: Cross-sectional and prospective analyses using the UK Health and Lifestyle Survey
Bibliographic record
Abstract
OBJECTIVES: We examine cross-sectional and prospective associations between objectively measured SHS exposure and mental health using data from the Health and Lifestyle Survey (HALS), a large, UK-wide, general population-based, prospective cohort study with measurements of carbon monoxide or salivary cotinine levels. METHODS: Mental health was assessed using the 30-item version of the General Health Questionnaire (GHQ). Multivariate logistic regression models adjusting for age, sex, height, body mass index, alcohol intake, social status, and longstanding illness were used to analyze the association between exposure to SHS (exhaled CO and salivary cotinine categories) and psychological distress (≥5GHQ). RESULTS: Fully adjusted cross-sectional analysis revealed a positive relationship between exhaled carbon monoxide and psychological distress among smokers (OR 1.36; 95% CI 1.04-1.78) but not among non-smoking adults. In a similar cross-sectional analysis between cotinine level and psychological distress, non-significant associations were found among smokers and non-smokers. Prospective analyses of the cotinine-psychological distress relationship among participants without psychological distress at baseline showed no significant increased risk of psychological distress among both smokers and non-smokers. In a prospective analysis of poor mental health outcome with respect to self-report smoking and SHS status, smokers had an increased risk of psychological distress while SHS and non-smokers did not. CONCLUSIONS: A non-significant association between objectively measured SHS exposure and poor mental health was found in this study. Our findings show discrepancies with recent studies suggesting the need for additional future research in this growing field of study.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".