Predictors of smoking cessation behavior among Bangladeshi adults: findings from ITC Bangladesh survey
Notice bibliographique
Résumé
BACKGROUND: Research findings on the predictors of smoking cessation behavior identified in Western countries may not be generalizable to smokers in the Southeast Asian countries (i.e., Bangladesh). This study examined the factors associated with smoking cessation behavior (quit attempts and smoking cessation) among a representative sample of Bangladeshi adults. METHODS: Data from Wave 1 (2009) and Wave 2 (2010) of the International Tobacco Control (ITC) Survey in Bangladesh, a face-to-face survey of adult smokers, were analysed. Households were sampled using a stratified multistage design and interviewed using a structured questionnaire. Respondents included in the study are 1,861 adult daily smokers (cigarette only or dual use of cigarette and bidi) in the Wave 1 survey who completed the Wave 2 follow up. RESULTS: Of the smokers (N = 1,861), 98 % were male, 18 % illiterate, 78 % married and 42 % were aged 40 or above; 89 % were cigarette smokers and 11 % were dual users (cigarette & bidi). Overall, 21.8 % of the baseline smokers made quit attempts (that is, making at least one quit attempt that lasted for at least 24 hours) during the 11- to 12-month interval between Waves 1 and 2 with only 4.1 % quitting successfully (that is, smokers who had stopped smoking for at least 6 months at the time of the Wave 2 survey). Significant predictors of attempts to quit included: residing areas outside Dhaka (OR = 3.41), being aged 40 or older (OR = 1.53), having a monthly income of above BDT10,000 (US$126) versus below BDT 5,000 (US$63) (OR = 1.57), intending to quit sometime in the future (OR = 1.73). Respondents not working indoors/outside the home were less likely to have made a quit attempt than those with no workplace restrictions on smoking (OR = 0.62). Predictors of successful smoking cessation included: being aged 40 or older (OR = 3.11), perceiving self-rated health as good or excellent (OR = 2.40), and an increased level of self-efficacy (OR = 1.75). Smokers who made a quit attempt not so recently (6 months ago or earlier) were less likely to quit than those who made a more recent (in last 6 months) quit attempt (OR = 0.23). CONCLUSION: Among Bangladeshi smokers, different factors were associated with quit attempt or successful cessation. Population based smoking cessation programs should take these factors into consideration in the design of smoking cessation interventions. At the same time, measures are necessary to encourage more smokers to make quit attempts.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».