Gendered educational disparities and in-home smoking and use of electronic tobacco/nicotine devices among cohabiting couples: findings from a Hungarian cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Smoke-free and aerosol-free households (SAFHs) reduce exposure to secondhand smoke and aerosol and support prevention and cessation efforts. However, SAFHs are less common in disadvantaged households, where women often initiate but lack the bargaining power to enforce bans. This power disparity is influenced by education. Our study examines the relationship between educational disparities and in-home smoking and in-home use of electronic devices for tobacco or nicotine aerosol delivery (EDTNAD) among couples. METHOD: A cross-sectional, online survey was conducted among Hungarian adults from 15 November 2022 to 26 November 2022. Cohabiting couples (n=623) with no other adults in the households were included. Respondents provided information about themselves and their romantic partners. Self-reported permission for in-home smoking and in-home EDTNAD use, sociodemographic variables and tobacco/nicotine use were assessed. Couples were the unit of analysis, and data were analysed using z-tests, cross-tabulation and binomial Least Absolute Shrinkage and Selection Operator regression. RESULTS: Allowing in-home smoking was negatively correlated with both partners having a secondary or higher education (SoHE) and with female-only SoHE, but not with male-only SoHE couples. Allowing in-home smoking and in-home EDTNAD use were both positively correlated with financial deprivation and negatively correlated with the presence of minors. Male partners' smoking and EDTNAD use showed consistently stronger effects than female partners' status. CONCLUSIONS: Allowing in-home smoking and in-home EDTNAD use is more prevalent in disadvantaged communities. The correlation between women's educational advantage (relative to their male partners) and in-home smoking suggests increased bargaining power to establish smoke-free homes. Our findings underscore the importance of gender-sensitive approaches in interventions aimed at promoting SAFH.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".