A. V. Kontsevaya, S. A. Shalnova, Yu. A. Balanova, A. D. Deev, G. V. Artamonova, T. M. Gatagonova, Yu. I. Grinshtein, D. V. Duplyakov, A. Yu. Efanov, Yu. V. Zhernakova, V. A. Ilyin, A. O. Konradi, R. A. Libis, A. V. Minakov, V. A. Nevzorova, S. V. Nedogoda, R. G. Oganov, S. A. Romanchuk, O. P. Rotar, I. A. Trubacheva, E. V. Shlyakhto, S. A. Boytsov, E. I. Chazov, G. A. Muromtseva, T. V. Balakhonova, N. V. Gomyranova, A. B. Dobrovolsky, A. N. Dotsenko, S. E. Evstifeeva, R. A. Eganyan, A. V. Kapustina, V. V. Konstantinov, O. A. Litinskaya, M. N. Mamedov, V. P. Masenko, V. A. Metelskaya, A. N. Meshkov, E. P. Panchenko, A. Yu. Postnov, R. A. Potemkina, A. V. Pustelenin, A. N. Rogoza, G. V. Ryabykina, I. A. Skripnikova, E. I. Suvorova, V. N. Titov, O. N. Tkacheva, M. B. Khudyakov, E. I. Baranova, A. A. Kostareva, S. K. Gutnova, Z. A. Toguzova, G. V. Tolparov, Z. T. Astakhova, N. V. Kulakova, N. V. Shestakova, M. V. Mokshina, L. V. Rodionova, E. V. Chumachek, A. A. Ledyaeva, R. A. Kasimov, A. A. Shabunova, G. V. Leonidova, K. N. Kalashnikov, O. N. Kalachikova, A. I. Rossoshansky, N. A. Kondakova, A. V. Popov, K. A. Ustinova, G. I. Furmenko, N. I. Babenko, O. G. Azarin, L. V. Bondartsov, A. E. Khvostikova, O. A. Nazarova, O. A. Belova, E. A. Shutemova, L. V. Korulina, L. K. Danilova, A. A. Evsyukov, N. V. Topolskaya, V. V. Shabalin, A. I. Aristov, R. R. Ruf, A. A. Kosinova, E. N. Shmatova, D. S. Kaskaeva, E. N. Isaeva, I. R. Basyrova, V. Yu. Kondratenko, E. A. Lopina, D. V. Safonova, S. A. Gudkova, N. A. Cherepanova, R. S. Karpov, V. S. Kaveshnikov, V. N. Serebryakova, I. V. Medvedeva, V. P. Shava, M. A. Storozhok, S. V. Shalaev, O. L. Barbarash, A. E. Skripchenko, E. V. Indukaeva, T. A. Mulerova, S. A. Maksimov, N. V. Cherkass, M. V. Tabakaev, and Ya. V. Danilchenko
Aim. To study social and economic gradients — educational and occupational statuses, wealth level, behavioral risk factors (FR) in Russian population by the ESSE-RF data. Material and methods. The data for the analysis consisted of representative selections of 13 regions of RF (n=22906) participants of the study, incl. men (n=8353) and women (n=13553) of 25-64 y.o., with response 80%. We calculated the odds ratios for the presence of behavioral FR: smoking, excessive alcohol consumption, insufficient physical activity (IPA), nonrational food consumption, anxiety and depressive disorders, — in persons from different social and economic groups by education level, type of inhabitation, professional status, wealth level. Results. Higher education was associated with better FR profile, except IPA (negative association) and alcohol consumption (absence of association). "White in general had less FR probability than Blue, excl. IPA and psychoemotional deviations (in men). As for the wealth association with the FR there is backward gradient, i.e. lesser the income, higher the risk of FR presence, excl. IPA and excessive alcohol intake in women. For example, in very wealthy men the odds ratio for depressive states was 3,09 [95% CI 2,08-4,57] comparing to the persons with low income. The type of territory of inhabitance was associated with less behavioral FR in Russian population, as significant associations are found only for depression and excessive salt consumption in both genders and IPA in men. Conclusion. The significant social and economic gradients of behavioral FR prevalence are found, the direction of those is not necessary the same as in European countries. The analysis of association with social and economic parameters would help to develop the directed preventive interventions.