Predicting growth potential in life expectancy at birth of the population in the Russian Federation based on scenario changes in socio-hygienic determinants using an artificial neural network
Authors:   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation, Zaitseva N.V. , Kleyn S.V. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation,   Perm State Medical University named after E.A. Wagner, 26 Petropavlovskaya Str., Perm, 614000, Russian Federation, Glukhikh М.V. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation, Kiryanov D.А. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation,   Perm State University, 15 Bukireva Str., Perm, 614990, Russian Federation, Kamaltdinov М.R. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation
Published: October 2022

The article presents the result produced by predicting growth potential in life expectancy at birth (LEB) of the RF Population. The predictions are based on scenario changes in social and hygienic determinants (SHD) identified by using an artificial neural network (ANN). This research is vital given the existing social strategies aimed at improving the medical and demographic situation in the Russian Federation. These strategies stipulate achieving targets set within the major national and federal projects. We identified an optimal ANN structure based on a four-layer perceptron with two inner layers containing eight and three neurons accordingly. This structure is able to produce results at the highest determination coefficient (R2= 0.78). Differences between actual LEB levels and predicted ones obtained by using the suggested model did not exceed 1.1 % (or 0.8 years). We established that average LEB in the RF would reach 75.06 years (by 2024) provided that the demographic situation in the country recovers in the nearest future, LEB level reaches its values detected in 2018–2019, and SHD values grow to their preset levels according to the target scenario. Therefore, the detected growth potential amounts to 3.0 years (1095 days) against 2018. “Lifestyle-related determinants” produce the greatest effects on the growth potential in LEB by 2024 (461 days). We also identified effects produced by such SHD groups as “Sanitary-epidemiological welfare on a given territory” (212 days), “Social and demographic indicators” (196 days), “Economic indicators” (131 days), “Indicators related to public healthcare” (70 days). An indicator that shows “A share of population doing physical exercises or sports” is the most significant determinant producing the greatest effects on potential changes in LEB. If it grows up to 55.0 %, a potential growth in LEB amounts to 243.5 days. If we do not consider COVID-related processes and rely only on the trends that are being observed now when predicting changes in the demographic situation by 2030, we can expect a possible additional growth in LEB that equals 286 days. The developed algorithm for determining growth potential in population LEB can be used as an instrument for determining and ranking priority health risk factors.