Hostname: page-component-7479d7b7d-qlrfm Total loading time: 0 Render date: 2024-07-12T22:22:42.493Z Has data issue: false hasContentIssue false

Mathematical Modeling and Quantitative Analysis of the Demographic and Ecological Aspects of Russian Supermortality

Published online by Cambridge University Press:  07 January 2011

A. K. Cherkashin*
Affiliation:
V.B. Sochava Institute of Geography SB RAS, Irkutsk, Russia
Ya. A. Leshchenko
Affiliation:
Angarsk Branch of the East-Siberian Center for Human Ecology SB RAMS Research Institute of Labor Medicine and Human Ecology, Angarsk, Russia
*
* Corresponding author. E-mail: cherk@mail.icc.ru
Get access

Abstract

We have carried out a polysystem analysis of the population dynamics by using a variety of hypotheses and their respective models based on different system interpretations of the phenomenon under investigation. Each of the models supplements standard dynamic equations for explaining the effects observed. A qualitative model-based analysis is made of the age-specific male mortality for a Siberian industrial city. The study revealed the tendencies for background mortality to increase with age and over time, which characterizes in an integral manner the influence of socio-ecological factors on the decline in population viability. It is shown that these tendencies are similar for different years and for different population age groups.

Type
Research Article
Copyright
© EDP Sciences, 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Références

S. Preston, P. Heuveline, M. Guillot. Demography: Measuring and Modeling Population Processes, Wiley-Blackwell, 2000.
Yashin, A. I., Yachin, I.A., Begun, A.S.. Mortality modeling: A review , Mathematical Population Studies, 4 (2000), 305-332. CrossRefGoogle Scholar
S.D. Tuljapurkar. Population Dynamics in Variable Environments. Lecture Notes in Biomathematics, N 85, New York, Springer, 1990.
J.L. Bobadilla, C.A. Costello, F. Mitchell (Ed.) Premature Death in the New Independent States, Washington, National Academy Press, 1997.
B.T. Velichkovsky. Viability of the Nation. Role of Social Stress and Genetic Processes in a Population in the Development of a Demographic Crisis and Change of Russia’s Population Health Status, Moscow, RAMN, 2008.
I.A. Gundarov. Demographic Catastrophe in Russia, Moscow, URSS, 2001.
Ya.A. Leshchenko. Crisis in Public Health and Socio-Demographic Development, Causes, Conditions of Overcoming, Irkutsk, East-Siberian Scientific Center of the Siberian Branch RAMS, 2006.
Ya.A. Leshchenko (Ed.). Public Health as a Crucial Component of Human Capital, Irkutsk, Reproduction Center, 2005.
L.A. Gavrilov, N.S. Gavrilova. The Biology of Lifetime, Moscow, Nauka, 1991.
V.N. Yarygin. Health as a Biological Category: Basic mechanisms and Evolutionary Strategy, Selected Lectures for Practitioners, Moscow, 2002, 322-310.
A.K. Cherkashin. Polysystem Analysis and Synthesis. Application in Geography, Novosibirsk, Nauka, 1997.
A.K. Cherkashin. Polysystem Modelling, Novosibirsk, Nauka, 2005.
Cherkashin, A.K.. Polysystem Modelling of Geographical Processes and Phenomena in Nature and Society , Mathematical Modelling of Natural Phenomena, 5 (2009), 4-20. CrossRefGoogle Scholar
D.R. Anderson. Model based Inference in the life sciences, New York-Berlin-Heidelberg, Springer Verlag, 2008.
K.P. Burnham, D.R. Anderson. Model Selection and Multimodel Inference: A Practical Information Theoretic Approach, New York-Berlin-Heidelberg, 2nd ed., Springer Verlag, 2002.
See, L., Openshaw, S.. A hybrid multi-model approach to river level forecasting . Hydrological Sciences-Journal-des Sciences Hydrologiques, 45, 4 (2000), 523-536. CrossRefGoogle Scholar
Palmer, T.N., Alessandri, A., Andersen, U., Cantelaube, P., Davey, M., Delecluse, P., Deque, M., Diez, E., Doblas-Reyes, F.J., Feddersen, H., Graham, R., Gualdi, S., Gueremy, J.-F., Hagedorn, R., Hoshen, M., Keenlyside, N., Latif, M., Lazar, A., Maisonnave, E., Marletto, V., Morse, A.P., Orfila, B., Rogel, P., Terres, J.-M., Thomson, M.C.. Development of a european multimodel ensemble system for seasonal-to-interannual prediction (DEMETER) , Bull. Amer. Meteor. Soc., 85 (2004), 853-872. CrossRefGoogle Scholar
A.G. Vishnevsky (Ed.). The Population of Russia 1997. The Fifth Annual Demographic Report, Moscow, INP RAN, Center for Demography and Human Ecology, Moscow, 1998.
B.T. Velichkovsky. Social Stress, Labor Motivation and Health, Moscow, Zashchita, 2005.
V. Shkolnikov, E. Andreyev, T. Moleva (Eds). Inequality and Mortality in Russia, Moscow, Carnegie Moscow Center, 2000.
L.L. Rybakovsky. Applied Demography, Moscow, ISPI RAN, 2003.
Rudenko, V.N.. The demographic crisis in Russia: causes and consequences , Vestnik Uralskogo otdeleniya RAN, 1 (2007), 103-118. Google Scholar
Shafirkin, A.V.. Influence of chronic psychoemotional stress on population health , Avikosmicheskaya i ekologicheskaya meditsina, 3 (2003), 31-38. Google Scholar
Tishuk, E.A.. Some questions concerning health status of the population of the Russian Federation , Problemy sotsialnoi gigieny, zdravookhraneniya i istorii medistiny, 6 (2001), 3-8. Google Scholar
W.C. Cockerham. Health and social change in Russia and eastern Europe, New York, Routledge, 1999.
Chkolnikov, V., McKee, M., Leon, D.A.. Changes in life expectancy in Russia in the mid-1990s, Lancet, 357 (2001), 917-921. Google Scholar
P.V. Simonov. The Emotional Brain, Moscow, Nauka, 1981.
Simonov, P.V.. The necessities-and-information theory of emotions , Voprosy psikhologii, 6 (1982), 44-56. Google Scholar
Shen, J.. On the foundations of vision modeling : I. Weber’s law and Weberized TV restoration , Physica D: Nonlinear Phenomena, 3-4 (2003), 241-251.CrossRefGoogle Scholar