Risk Management and Healthcare Policy (Apr 2023)
Socioeconomic and Behavioral Determinants of Cardiovascular Risk in Russia: A Structural Equation Modeling Approach
Abstract
Maria Kaneva,1,* Mihajlo Jakovljevic2– 4,* 1Institute of Economics and Industrial Engineering of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia; 2Institute of Advanced Manufacturing Technologies Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia; 3Institute of Comparative Economic Studies, Hosei University Faculty of Economics, Tokyo, Japan; 4Department of Global Health Economics and Policy, University of Kragujevac, Kragujevac, Serbia*These authors contributed equally to this workCorrespondence: Maria Kaneva, Institute of Economics and Industrial Engineering of the Siberian Branch of the RAS, 17 Academician Lavrentiev Avenue, office 373, Novosibirsk, Russia, Tel +7 993 028 8421, Email [email protected]: Despite much attention within the literature, the multiple risk factors associated with CVD mortality in Russia are still not fully understood. Drawing on the Health Belief Model as a theoretical framework, we aim to elicit socioeconomic and behavioral determinants of cardiovascular risks in Russian men and women.Methods: Using the Know Your Heart project data, we utilize regression analysis and then structural equation modeling (latent class analysis and mediation analysis) to study the determinants of CVD risks.Results: OLS and ordered logit regressions show that the key factors defining cardiovascular health behaviors in Russia are health-related actions to reduce the perceived threat of diseases (physical activity and GP visits), perceived barriers to behavioral change (financial constraints), and cues to action (awareness of the federal health check-up program). The latent class analysis further identifies three distinct groups of the population with different CVD risk levels. Over one-third of respondents belong to the “high CVD risk” class characterized by the highest share of smokers and alcohol abusers who evade contact with primary care and face financial constraints. In the mediation analysis, we find that employment mediates the relationship between physical activity and CVD risks: physically active individuals have a greater chance of employment, and employment further mitigates CVD risks. We also find an indication of the selection of the healthy into employment in the causal relationship between GP visits, having a job, and CVD risks.Conclusion: A corresponding set of policy actions stem from these findings. These include reinforcing the change of perceptions of CVD risks and lowering barriers to health care; raising awareness of the free preventive check-up program in the “high CVD risk” group; making sports and exercise accessible to the elderly; and using off-putting labels on alcohol products as behavioral nudges among “physically active but drinking” males.Keywords: Health Belief Model, cardiovascular risks, health behaviors, structural equation modeling, Russia
