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Background It has been found that a community’s socio-economic environment affects the smoking habits within it; however, there is no convincing evidence with regard to large territorial entities and other non-socio-economic characteristics. Our study evaluated the impact of a wide range of characteristics of large administrative regions on the individual level of cigarette smoking in the Russian adult population. Methods The pool of participants included 20 303 individuals aged 25–64 years the same individuals having been subjects of the cross-sectional analysis within the framework of the Russian “Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation” (ESSE-RF) study conducted in 2013–2014. We applied 64 characteristics of the 12 Russian regions under study for 2010–2014 listed on the official website of the Russian Federal State Statistics Service. Using principal component analysis, we deduced five evidence-based composite indices of the regions. We applied the generalized estimating equation to determine associations between the regional indices and the individual level of smoking. Results The increased Industrial index in the region is associated with the probability of smoking (odds ratio = 1.15; 95% confidence interval = 1.06–1.24), the same association also being observed in interaction with individual characteristics. The other indices show associations with smoking only in separate sex and educational groups. In terms of alcohol consumption and a number of social conditions, living in disadvantageous regions is associated with an increased individual probability of smoking among women, people of low education and qualification levels, and older persons. Living in demographically depressed regions is associated with an increased individual probability of smoking among women. We found a number of associations for the Mixed index, which, unfortunately, are difficult to interpret. Surprisingly, it was found that the Economic index has no associations with the probability of smoking in either the total sample size or stratification analyses. Conclusions We evaluated the key associations of the territorial indices with the individual probability of smoking, as well as the mutual influence between the territorial indices and individual factors.