M. L. Vartanova. Cluster Analysis of Russia's Food Security Taking into Account the Demographic Profiles of the Regions

https://doi.org/10.15507/2413-1407.26342.305-327
EDN: https://elibrary.ru/lbyrvp ISSN 2413-1407
УДК / UDC 33-025.27-027.45(470+571) ISSN 2587-8549

Abstract

Introduction. Food security is a key indicator of the socioeconomic development of Russia's regions. Given interregional differentiation, the importance of identifying stable typological groups of territories, taking into account not only agrarian and economic but also demographic characteristics, is increasing. The aim of this study is to identify systemic relationships between demographic and economic parameters and the level of food security, with the subsequent development of an empirical typology of Russian regions.

Materials and Methods. Using data from Rosstat and the Ministry of Agriculture (2014–2022), k-means and hierarchical clustering (Ward's method) were used to group regions. An integrated indicator was calculated based on specific indicators of nutrient adequacy, food ecosystem stability, food availability, and food safety. Cluster analysis, taking into account the demographic profiles of the territories, was used to identify homogeneous groups of regions.

Results. A stable typology of regions was discovered, forming a hierarchy from suppliers with high agricultural potential to consumers dependent on external supplies. Four clusters were identified. Only one region (Republic of Bashkortostan) has a high level of food security (an integrated indicator of 0.83), five (Belgorod Region, Krasnodar Territory, Republic of Tatarstan, Voronezh and Rostov Regions) have an average level; seven regions (Republic of Dagestan, Stavropol and Altai Territories, Kursk, Saratov, Novosibirsk and Omsk Regions) have a low level. No regions with a critical level were identified. Between 2014 and 2022, the integrated indicator increased, for example, in Krasnodar Territory from 0.64 to 0.74. A more meaningful empirical typology of the constituent entities of the Russian Federation is proposed and a differentiated approach to management is substantiated.

Conclusion. Key factors determining the place of regions in the food security hierarchy were identified. A set of targeted management recommendations was developed for each group of territories (leading regions, balanced regions, zones with low stability, and urban agglomerations) aimed at ensuring self-sufficiency, import substitution, and the development of the agro-industrial complex, taking into account demographic characteristics. The obtained results confirm that the demographic profiles of regions are a significant factor in the empirical typology of food security. The use of a cluster approach allows for a more accurate identification of spatial differentiation and can be used in the development of regional food security policies.

Keywords: demographic policy, food supply, cluster analysis of regions, classification of constituent entities of the Russian Federation, food security, national security, regions of the Russian Federation, sustai­nable development of regions

Conflict of interest. The author declares no conflict of interest.

For citation: Vartanova М.L. Cluster Analysis of Russia's Food Security Taking into Account the Demographic Profiles of the Regions. Russian Journal of Regional Studies. 2026;34(2):305–327. https://doi.org/10.15507/2413-1407.26342.305-327

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About the author:

Marina L. Vartanova, Dr.Sci. (Econ.), Associate Professor, Chief Researcher at the Center for Comparative (International) Demographic Research, Institute of Social Demography of the Federal Research Sociological Center of the Russian Academy of Sciences (6 Fotieva St., Block 1, Moscow 119333, Russian Federation), ORCID: https://orcid.org/0000-0002-9853-5817, Researcher ID: J-7641-2018, Scopus ID: , SPIN-code: ,

Availability of data and materials. The datasets used and/or analyzed during the current study are available from the author on reasonable request.

The author has read and approved the final manuscript.

Submitted 20.02.2025; revised 18.09.2025; accepted 03.10.2025.