The article presents an analysis of the demographic characteristics of population aging in different regions of Russia with a study of middle age and its dynamics. The aim of the study is to analyze the regional characteristics of population aging and differentiation according to this process to assess its impact on the quality of life and human potential of territories. The scientific novelty lies in the application of a dynamic approach that takes into account not only the level of average age, but also its growth rate, which makes it possible to identify new types of demographic trajectories. The first part of the article discusses research on the analysis of aging processes in Russian regions using various classification and grouping methods. For comparison, examples of international approaches to the typification of aging territories by both macro-regions and regions within the country are given. The second part analyzes the average age of the population and its dynamics in Russian regions for the period from 2010 to 2024. The study revealed regional differences in the levels and rates of increase in the average age of the population due to factors of fertility, mortality, migration and cultural characteristics. The oldest regions are concentrated in the Central and Volga Federal Districts, where the average age is highest, while the regions of the North Caucasus Federal District and the Republic of Tuva show a low average age due to high birth rates and traditional family values. An analysis of gender and territorial differences shows that women age more slowly than men, and the urban population as a whole ages faster than the rural population. Within the framework of the classification, seven groups of regions are identified according to the level and dynamics of average age, which makes it possible to systematize the features of the demographic situation in different parts of the country. In conclusion, the article draws conclusions on the situation with the aging of the population in the Russian Federation and formulates proposals for a differentiated regional policy
Keywords
population aging, regional differentiation, elderly population