ON ASSESSING THE GROWTH POTENTIAL OF THE LIFE EXPECTANCY OF THE POPULATION AS A RESULT OF IMPLEMENTING INTEGRATED MEASURES (ON THE EXAMPLE OF A CONSTITUENT ENTITY OF THE RUSSIAN FEDERATION)

Abstract

The development vector of the current government policy in the Russian Federation aimed at improving social conditions – one of the critical indicators of which is life expectancy at birth [LE] – dictates the research relevance. Currently, the search and testing of new analytical systems capable of forecasting LE, considering the multifactorial influence on this indicator, remains relevant and timely. The research goal is to establish the growth potential of LE of the population estimation on the example of one of the constituent entities of the Russian Federation, considering integrated heterogeneous factors that possess a modifying effect on LE. The estimation includes modeling cause-and-effect relationships between indicators of habitat, quality of life, and life patterns – determinants of population health. The utilized model is a set of algebraic equations in the form of a factor transformation of independent variables and an artificial neural network and is implemented in three stages. They include (1) developing the basic scenario and calculating LE, (2) developing the target scenario and calculating LE, and (3) calculating the growth potential of LE as the difference between the indicators obtained at previous stages. The developed model and the three-stage algorithm application allows one to obtain the growth potential of LE on the example of one constituent entity of the Russian Federation in the context of a single change in determinants by 2024, which amounts to +1.24 years (453.0 days) relative to the baseline scenario (the actual LE value in 2018). The forecast value of LE is 70.47 years. Ranking of individual indicator groups according to their isolated effect on LE demonstrates that the most significant determinant groups are (1) socio-demographic indicators (2.6 years – 949.0 days), (2) indicators of sanitary and epidemiological safety (1.75 years – 638.75 days), and the (3) population lifestyle indicators (1.41 years – 514.65 days). The obtained results confirm the predominance of the influence of social indicators on population health in the form of LE on the example of the analysis of changes in the indicators of one of the constituent entities of the Russian Federation. The research relevance implies studying the combined influence of heterogeneous factors of the environment and lifestyle on the indicative indicator of population health (LE), a complex system with the properties of emergence, variability, opposite influence, and adaptation.

Keywords

• life expectancy
• neural network
• modifying determinants