Background: Health is a key driver of the United Nations Sustainable Development Goals. This study examined the relationships between economic indicators, demographic metrics, and health system factors and morbidity due to non-communicable diseases, such as diseases of the circulatory system, in Kazakhstan.

Methods: This retrospective ecological study utilized regionally aggregated data from 2010 to 2020 for all 14 regions in Kazakhstan. Data on incidence rates of diseases of the circulatory system (DCS) and socioeconomic, demographic, and healthcare variables were sourced from the Bureau of National Statistics and the Ministry of Health. Variables included gross regional product per capita, population density, living wage, unemployment rates, average monthly salary, Gini coefficient, income below subsistence level, housing space per capita, average monthly wage in healthcare, doctor and nurse densities per 10,000 population, and number of hospital beds. A correlation analysis was performed followed by stepwise regression to identify significant predictors.

Results: The analysis identified that higher living wages (β = 0.7), population density (β = 0.275), nurse density (β = 0.212), and average monthly salary (β = 0.502) were positively associated with higher DCS incidence rates. Conversely, gross regional product per capita (β = -0.68), housing space per capita (β = -0.441), and income below the subsistence level (β = -0.161) were negatively associated with DCS incidence. The model explained approximately 63.7% of variance in DCS incidence.

Conclusions: Socioeconomic and healthcare factors significantly influence the incidence of circulatory diseases in Kazakhstan. Policies aimed at improving economic conditions such as increasing living wages and reducing unemployment may help lower DCS morbidity. Additionally, equitable distribution of healthcare resources like nurses could enhance early detection and management of circulatory diseases, contributing to better public health outcomes in a middle-income country setting.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11590314PMC
http://dx.doi.org/10.1186/s41043-024-00697-yDOI Listing

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