Classification of nicotine-dependent users in India: a decision-tree approach

Abstract

India has been predicted to have the fastest increase in deaths attributable to tobacco in the first 2 decades of the twenty-first century. Consequently, it is imperative to examine the extent of nicotine dependency among adults in India. The main objective of the present article is to characterize nicotine dependency related to smoking and smokeless tobacco among adults according to age, education level, duration of use and other socioeconomic characteristics. We analyzed Global Adult Tobacco Survey (GATS) 2010 data for 9190 smokers and 13,357 smokeless tobacco users who were 15 years of age or older. Time to first tobacco use of the day was used as a measure of nicotine dependence. We employed a decision tree algorithm from SAS Enterprise Miner to conduct classification analysis to establish the relationship among nicotine dependency for smoking, smokeless tobacco use, and its predictors. More than 65% of smokers and 54.3% of smokeless tobacco users were nicotine dependent. The decision tree results showed that the most important explanatory variable for the prediction of smoking dependency was duration of smoking followed by education, gender and region. For smokeless tobacco use, duration of smokeless tobacco use was also the most important explanatory variable followed by education, occupation and age. Smoking and smokeless tobacco use dependencies are driven by different sets of demographic and socioeconomic predictors. Suitable plans for tobacco cessation need to be implemented based on the type of tobacco and particularly duration of use, which was found to be the most important determinant of quitting.