Macroregional Differences in the Determinants of Life Expectancy in Russia
DOI:
https://doi.org/10.17059/ekon.reg.2026-2-10Keywords:
life expectancy, macro-regions, socio-economic environment, population, behavioural strategies, correlation analysis, tree algorithmsAbstract
Russia’s national target of raising life expectancy to 78 years by 2030 faces a key challenge: significant territorial disparities driven by the combined influence of socioeconomic, environmental, and behavioural factors. This study hypothesizes that life expectancy in each of Russia’s macroregions is persistently shaped by a distinct combination of such factors. Using macroregional panel data, we apply correlation and regression analysis alongside tree-based machine learning algorithms to quantify the contributions of socioeconomic conditions, healthcare accessibility, and population behaviour, accounting for regional specificity and nonlinear relationships. The analysis covers 12 macroregions, delineated by combining principles of administrative division with economic zoning as used in spatial and socioeconomic development strategies and territorial planning. The results reveal clear macroregional patterns. In low-urbanization macroregions (Central Chernozem, Southern), life expectancy is driven primarily by healthcare accessibility and socioeconomic conditions. In industrial macroregions (Volga-Ural, Ural-Siberian, South Siberian), behavioural risks are the dominant influence, with the prevention of deviant behaviour and promotion of health-preserving practices consistently ranking among the top three factors. We identify clusters of macroregions with similar factor-influence profiles, with differences attributable to established behavioural patterns, institutional environment, and income levels. These findings can inform federal and regional policy-makers in tailoring socioeconomic strategies to promote health-preserving behaviours and advance national life expectancy goals.
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