Hardcore Smoking in Three South-East Asian Countries: Results from the Global Adult Tobacco Survey

  • Published : 2013.02.28


Background: Hardcore smoking is represented by a subset of daily smokers with high nicotine dependence, inability to quit and unwillingness to quit. Estimating the related burden could help us in identifying a high risk population prone to tobacco induced diseases and improve cessation planning for them. This study assessed the prevalence and associated factors of hardcore smoking in three South-East Asian countries and discussed its implication for smoking cessation intervention in this region. Materials and Methods: Global Adult Tobacco Survey (GATS) data of India, Bangladesh and Thailand were analyzed to quantify the hardcore smoking prevalence in the region. On the basis of review, an operational definition of hardcore smoking was adopted that includes (1) current daily smoker, (2) no quit attempt in the past 12 months of survey or last quit attempt of less than 24 hours duration, (3) no intention to quit in next 12 months or not interested in quitting, (4) time to first smoke within 30 minutes of waking up, and (5) knowledge of smoking hazards. Logistic regression analysis was carried out using hardcore smoking status as response variable and gender, type of residence, occupation, education, wealth index and age-group as possible predictors. Results: There were 31.3 million hardcore smokers in the three Asian countries. The adult prevalence of hardcore smoking in these countries ranges between 3.1% in India to 6% in Thailand. These hardcore smokers constitute 18.3-29.7% of daily smokers. The logistic regression model indicated that age, gender, occupation and wealth index are the major predictors of hardcore smoking with varied influence across countries. Conclusions: Presence of a higher number of hardcore smoking populations in Asia is a major public health challenge for tobacco control and cancer prevention. There is need of intensive cessation interventions with due consideration of contextual predictors.



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