Drug, Healthcare and Patient Safety (May 2015)

Determinant factors of tobacco use among ever-married men in Bangladesh

  • Rahman MS,
  • Mondal MNI,
  • Islam MR,
  • Rahman MM,
  • Hoque MN,
  • Alam MS

Journal volume & issue
Vol. 2015, no. default
pp. 77 – 85

Abstract

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Md Shafiur Rahman,1,2 Md Nazrul Islam Mondal,2 Md Rafiqul Islam,2 Md Mizanur Rahman,2 M Nazrul Hoque,3 Md Shamsher Alam4 1Department of Public Health, First Capital University of Bangladesh, Chuadanga, Bangladesh; 2Department of Population Science and Human Resource Development, University of Rajshahi, Rajshahi, Bangladesh; 3Hobby Center for Public Policy, University of Houston, Houston, TX, USA; 4Faculty of Ecology, Peoples’ Friendship University of Russia, Moscow, Russia Background: The burden of tobacco use is shifting from developed to developing countries. This study aimed to explore the different types of tobacco use, and to identify the determinant factors associated with the tobacco use among ever-married men in Bangladesh. Data and methods: Data of 3,771 ever-married men, 15–54 years of age were extracted from the Bangladesh Demographic and Health Survey 2007. Prevalence rate, chi-square (Χ2) test, and binary logistic regression analysis were used as the statistical tools to analyze the data. Results: Tobacco use through smoking (58.68%) was found to be higher than that of chewing (21.63%) among men, which was significantly more prevalent among the poorest, less educated, and businessmen. In bivariate analysis, all the socioeconomic factors were found significantly associated with tobacco use; while in multivariate analysis, age, education, wealth index, and occupation were identified as the significant predictors. Conclusion: Tobacco use was found to be remarkably common among males in Bangladesh. The high prevalence of tobacco use suggests that there is an urgent need for developing intervention plans to address this major public health problem in Bangladesh. Keywords: tobacco use, smoking tobacco, chewing tobacco, prevalence rate, logistic regression model