The impact of the polymorbidity factor on lifetime radiation risks of cancer mortality

«Radiation and Risk», 2024, vol. 33, No. 2, pp.34-43

DOI: 10.21870/0131-3878-2024-33-2-34-43

Authors

Menyajlo A.N. – Lead. Researcher, C. Sc., Biol. Contacts: 4 Korolyov str., Obninsk, Kaluga region, Russia, 249035. Tel.: (484) 399-32-81; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. .
Chekin S.Yu. – Head of Lab.
Maksioutov M.A. – Head of Dep., C. Sc., Tech.
Shchukina N.V. – Senior Researcher
Ivanov V.K. – Scientific Advisor of NRER, Chairman of RSCRP, Corresponding Member of RAS, D. Sc., Tech., Prof. A. Tsyb MRRC.
A. Tsyb MRRC, Obninsk

Abstract

The forecast of lifetime radiation risks in exposed cohorts is currently carried out without considering the heterogeneity of cohort members in terms of their degree of polymorbidity. Polymorbidity is characterized by a reduction in the life expectancy of a person in the presence of several chronic diseases. Therefore, considering the polymorbidity factor can significantly affect the estimate of lifetime radiation risk. The purpose of this study is to investigate the effect of the polymorbidity factor of patients on the estimates of lifetime radiation risks of mortality from malignant neoplasms, as well as to compare the impact of polymorbidity factors and uncertainty of radiation doses on these estimates. To calculate the lifetime attributable radiation risk (LAR) per 1 mSv, the radiation risk models recommended by Publication 103 of the International Commission on Radiological Protection were used. The calculations are based on official medical and statistical data of 2021 for the Russian population. The effect of polymorbidity on human lifespan and on LAR estimates was considered using the classic Charlson Comorbidity Index (CCI). To assess the effect of the uncertainty of radiation doses on the LAR value, an example of a lognormal dose distribution with a standard geometric deviation of 2.2 (i.e., with a 90% uncertainty factor of 3.6) was chosen, which is typical for the population living in the areas of the Kaluga and Bryansk regions of Russia contaminated as a result of the Chernobyl accident. Simulation modeling was used to assess the effect of radiation dose uncertainty. It is shown that the variability of estimates of the lifetime radiation risk of mortality from malignant neoplasms due to the polymorbidity factor is comparable to the variability of this radiation risk due to the uncertainty of doses with an 90% uncertainty factor of 3.6. Thus, when calculating radiation risks in persons exposed to radiation, it is necessary to consider the presence or absence of chronic diseases, since this significantly affects the final assessments of radiation risks. Underestimation or overestimation of risk can be from 1.5 times or more.

Key words
Chernobyl accident, Charlson index, polymorbidity, lifetime attributable risk, Russian population, radiation risk, radiobiological effects, radiation-induced cancer mortality, ICRP radiation risk models, effective dose, public health.

References

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Full-text article (in Russian)