Correlates of exposure to secondhand smoke (SHS) at home among non-smoking adults in Bangladesh: findings from the ITC Bangladesh survey
Bibliographic record
Abstract
BACKGROUND: Exposure to secondhand smoke (SHS) is a serious global public health problem. Understanding the correlates of SHS exposure could guide the development of evidence based SHS exposure reduction interventions. The purpose of this study is to describe the pattern of and factors associated with SHS exposure among non-smoking adults in Bangladesh. METHODS: Data come from adult non-smokers who participated in the second wave (2010) of the International Tobacco Control Policy (ITC) Evaluation Bangladesh Survey conducted in all six administrative divisions of Bangladesh. A structured questionnaire gathered information on participants' demographic characteristics, pattern of SHS exposure, SHS knowledge, and attitudes towards tobacco control. Exposure to SHS at home was defined as non-smokers who lived with at least one smoker in their household and who reported having no home smoking ban. The data were analyzed using chi-square tests and logistic regression procedures. RESULTS: The SHS exposure rate at home among the participants (N=2813) was 43%. Several sociodemographic and attitudinal factors were associated with SHS exposure. Logistic regression analyses identified eight predictors of SHS exposure: being female (OR=2.35), being aged 15-24 (OR=2.17), being recruited from Dhaka slums (OR=5.19) or non-tribal/non-border areas outside Dhaka (OR=2.19) or tribal/border area (OR=4.36), having lower education (1-8 years: OR=2.45; illiterate: OR=3.00, having higher monthly household income (5000 to <10,000 Taka: OR=2.34; 10,000 Taka or more: OR=2.28), having a father who smoked in the past or currently smokes (OR=2.09), having lower concern about the harms of tobacco on children (unconcerned OR=3.99; moderate concern OR=2.26), and not knowing the fact that SHS causes lung cancer in non-smokers (OR=2.04). CONCLUSIONS: Almost half of non-smoking Bangladeshi adults are exposed to SHS at home. The findings suggest the need for comprehensive tobacco control measures that would improve public understanding about health hazards of SHS exposure at home and encourage educational initiatives to promote smoke-free homes. Interventions should deliver targeted messages to reach those in the low socioeconomic status group.
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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 | 0.001 |
| 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".