Demographic characteristics of the Russian population
Research Article
How to Cite
Gushcho Y.P. Demographic characteristics of the Russian population. Population. 2024. Vol. 27. No. 1. P. 95-108. DOI: https://doi.org/10.24412/1561-7785-2024-1-95-108 (in Russ.).
Abstract
The article deals with the results of numerical estimation of demographic characteristics of the Russian female and male populations using the example of the RF 2019 statistical materials with the help of the digital twin for population developed by the author with his colleagues. It demonstrates the capabilities of the digital twin to estimate the attainment of life expectancy limits and predict the demographic characteristics of any population based on previous statistical data of that population. There was used a hardware-software package with embedded the digital twin for the Russian population on the basis of thirty-three years of statistical research into the effects of the total lifestyle index on longevity, workability, ageing and other population characteristics. The life expectancy of the Russian Federation population with the demographic characteristics for 2019 tends to 79 years for men and 122 years for women, with a maximum possible total lifestyle index. For the current demographic characteristics of the population, the rate of population aging from time for different total lifestyle indices has at least one maximum. The possibility of numerical calculation of life expectancy as a function of changes in the average weight of the male and female population is shown. The possibility of controlling the biological age of a population member depending on his total lifestyle index is shown. Developed hardware-software complex based on digital twin for population estimation of demographic characteristics of populations can be used to calculate and predict the demographic characteristics of any population on the basis of previous statistical data of this population. Hardware-software complex can be useful for public and state organizations, statistical agencies, medical organizations of different profiles. insurance companies, staff recruitment companies, pension funds, venture capital funds, private finance funds, private banks and capital management organizations.
Keywords:
population, digital twin, biological age, life expectancy, workability, aging rate, lifestyle, health resource, quality of life
References
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2. Gushcho Yu. P. 12 kluchey ot seifa dolgoletiya [Twelve Keys to the Safe Longevity]. Moscow. 2020. 420 р. Available at: https://order.yuryguscho.ru/buy/310002 (in Russ.). (Accessed: 10 July 2023) (in Russ.)
3. Gushcho Yu. P. Kak stat’ schastlivym golfistom [How to Be a Happy Golfer]. Moscow. 2021. 392 р. Available at: https://order.yuryguscho.ru/buy/474823. (Accessed: 10 July 2023) (in Russ.)
4. Rimashevskaya N. M. Chelovek i reformy: sekrety vyzhivaniya [Person and Reforms: The Secrets of Survival]. Moscow. ISEPN RAN [Institute of Socio-Economic Studies of Population RAS]. 2003. 392 p. (in Russ.)
5. Börger M., Freimann A., Ruß J. A combined analysis of hedge effectiveness and capital efficiency in longevity hedging. Insurance: Mathematics and Economics. 2021. Vol. 99. P. 309–326. DOI: 10.1016/j.insmatheco.2021 .03.023.
6. Li J. S.—H., Liu Y. Recent declines in life expectancy: Implication on longevity risk hedging. Insurance: Mathematics and Economics. 2021. Vol. 99 (C). P. 376–394. DOI: 10.1016/j.insmatheco.2021.03.028
7. Li H., Shi Y. Forecasting mortality with international linkages. A global vector-autoregression approach. Insurance Mathematics and Economics. 2021. Vol. 100. P. 59–75. DOI: 10.1016/j.insmatheco.2021.04.006
8. Li H., Hyndman R. G. Assessing mortality inequality in the U.S.: What can be said about the future? Insurance: Mathematics and Economics. 2021. Vol. 99. P. 152–162. DOI: 10.1016/j.insmatheco.2021.03.014
9. Majer I. M., Stevens R., Nusselder W. J., Mackenbach J. P., van Baal P. H. M. Modeling and forecasting health expectancy: theoretical framework and application. Demography. 2013. No. 50(2). P. 673–697. DOI: 10.1007/s13524–012–0156–2
10. Gushcho Yu. P., Gushcho M. A. Statisticheskaya gerontologiya i upravleniye rabotosposobnostyu [Statistical gerontology and workability management]. Meditsina i fizicheskaya kultura: nauka i praktika [Medicine and Physical Education: Science and Practice]. 2019. Vol. 1. No. 3. P. 34–40. DOI: 10.20310/2658–7688–2019–1–3–34–40 (in Russ.)
11. Suprun A. P., Gushcho Yu. P., Gushcho M. A., Kusnetzov V. V. Programma online optimisatsii rabotosposobnosti sotrudnikov kompaniy [Online workability optimisation programme for company employees, athletes and health centre patients] Meditsina i fizicheskaya kultura: nauka i praktika [Medicine and Physical Education: Science and Practice]. 2019. Vol. 1. No. 4. P. 31–36. DOI: 10.20310/2658–7688–2019–1–4–31–36 (in Russ.)
12. Medvedev A. V. Tsifrovyye dvoyniki territoriy dlya podderzki prinatiya resheniy v sfere regionalnogo sotsial’no-ekonomicheskogo razvitiya [Digital twins of territories to support decision-making in regional socio-economic development]. Zhurnal Sovremennyye naukoyemkiye tekhnologii [Journal of Modern High Technologies]. 2020. No. 6 (part 1). P. 61–66. (in Russ.)
13. Artsikov V. G. Istoriya AvtoVAZa v litsakh [The History of AvtoVAZ in Persons]. Izdatel’skiy dom Sem’ Vyorst. [Publishing House Seven Verst].Togliatti. 2021. P. 74–76. (in Russ.)
14. Pak K., Dorien T. A., Kooij M. Laboring Work and Healthy Aging. Encyclopedia of Gerontology and Population Aging. 2021. P. 2837–2838. DOI: 10.1007/978–3–030–22009–9
Article
Received: 14.07.2023
Accepted: 27.03.2024
Citation Formats
Other cite formats:
APA
Gushcho, Y. P. (2024). Demographic characteristics of the Russian population. Population, 27(1), 95-108. https://doi.org/10.24412/1561-7785-2024-1-95-108
Section
DEMOGRAPHY: THEORY AND PRACTICE ISSUES
