Age-Specific Dynamics of Risks of COVID-19 of Different Severity among Healthcare and Industrial Workers
https://doi.org/10.35627/2219-5238/2023-31-5-78-84
Abstract
Introduction: The relevance of the issue of human age-specific vulnerability to effects of environmental factors, especially biological agents, including viral infections, for public health is attributed to the aging of the population and the requirements for considering individual characteristics for a more accurate risk assessment.
Objective: To establish age-specific patterns of the COVID-19 risk among healthcare and industrial workers.
Materials and methods: We have analyzed the incidence and course of COVID-19 among 729 healthcare workers and 880 industrial workers in 2021–2022. The risk of mild, moderate and severe course of COVID-19 was determined in each age group. The age-specific dynamics of the COVID-19 risk was characterized by its change per year of age of the employees.
Results: We established that the incidence of COVID-19 among healthcare workers was 1.6 times higher than among industrial workers. We also observed regularities of the age-specific dynamics of risk of COVID-19 of different severity among healthcare and industrial workers. For the mild course of the disease, the risk was approximated by the following regressions: healthcare Ri 1 (%) = –0.15 × (Age – 20, years) + 34.06; industry Ri 1 (%) = –0.24 × (Age – 20) + 27.21. For the moderate and severe course, the regressions were as follows: healthcare Ri 2,3 (%) = 0.23 × (Age – 20) + 2.46; industry Ri 2.3(%) = 0.14×(Age – 20) – 1.29.
Conclusions: In different age groups, the relative risk of a mild course of COVID-19 in healthcare workers is 1.2–2.1 times higher than in industrial workers while that of a moderate and severe course is already 3 to 9 times higher. The direction of the age-specific COVID-19 risk depends on the disease severity. As for the mild course, a one-year increase in age is associated with a decrease in the disease risk by an average of 0.15 % in healthcare workers and 0.24 % in industrial workers. As for the moderate and severe courses, a one-year increase in age is associated with an increase in the COVID-19 risk by 0.23 % and 0.14 % in healthcare and industrial workers, respectively.
About the Authors
G. A. SorokinRussian Federation
Gennady A. Sorokin, Dr. Sci. (Biol.), Leading Researcher, Department of Health Risk Analysis
4, 2nd Sovetskaya Street, Saint Petersburg, 191036
N. D. Chistyakov
Russian Federation
Nikolay D. Chistyakov, Cand. Sci. (Med.), Dermatovenereologist, Clinical Research Department
4, 2nd Sovetskaya Street, Saint Petersburg, 191036
M. P. Chernysheva
Russian Federation
Marina P. Chernysheva, Dr. Sci. (Biol.), Professor
72A, Kondratievsky Avenue, Saint Petersburg, 195009
M. N. Kir'yanova
Russian Federation
Marina N. Kir'yanova, Cand. Sci. (Med.), Senior Researcher, Department of Health Risk Analysis
4, 2nd Sovetskaya Street, Saint Petersburg, 191036
References
1. van Kamp I, Davies H. Noise and health in vulnerable groups: a review. Noise Health. 2013;15(64):153-159. doi: 10.4103/1463-1741.112361
2. Sorokin GA, Chistyakov ND, Shilov VV. Age-related vulnerability of employees to factors of the occupation environment. Gigiena i Sanitariya. 2021;99(8):807-811. (In Russ.) doi: 10.47470/0016-9900-2021-100-8-807-811
3. Sorokin GA, Plekhanov VP, Chistyakov ND. [Age-related vulnerability of a person's working capacity and well-being to environmental factors.] Zdorov’e – Osnova Chelovecheskogo Potentsiala: Problemy i Puti Ikh Resheniya. 2022;17(1):356-370. (In Russ.)
4. Redmayne M, Johansson O. Radiofrequency exposure in young and old: different sensitivities in light of age-relevant natural differences. Rev Environ Health. 2015;30(4):323-335. doi: 10.1515/reveh-2015-0030
5. Baliatsas C, Bolte J, Yzermans J, et al. Actual and perceived exposure to electromagnetic fields and non-specific physical symptoms: an epidemiological study based on self-reported data and electronic medical records. Int J Hyg Environ Health. 2015;218(3):331-344. doi: 10.1016/j.ijheh.2015.02.001
6. Rubik B, Brown RR. Evidence for a connection between coronavirus disease-19 and exposure to radiofrequency radiation from wireless communications including 5G. J Clin Transl Res. 2021;7(5):666-681.
7. Paavola J. Health impacts of climate change and health and social inequalities in the UK. Environ Health. 2017;16(Suppl 1):113. doi: 10.1186/s12940-017-0328-z
8. Simoni M, Baldacci S, Maio S, Cerrai S, Sarno G, Viegi G. Adverse effects of outdoor pollution in the elderly. J Thorac Dis. 2015;7(1):34-45. doi: 10.3978/j.issn.2072-1439.2014.12.10
9. Bell ML, Zanobetti A, Dominici F. Evidence on vulnerability and susceptibility to health risks associated with short-term exposure to particulate matter: a systematic review and meta-analysis. Am J Epidemiol. 2013;178(6):865-876. doi: 10.1093/aje/kwt090
10. Bell ML, Zanobetti A, Dominici F. Who is more affected by ozone pollution? A systematic review and meta-analysis. Am J Epidemiol. 2014;180(1):15-28. doi: 10.1093/aje/kwu115
11. Costa LG, Cole TB, Dao K, Chang YC, Garrick JM. Developmental impact of air pollution on brain function. Neurochem Int. 2019;131:104580. doi: 10.1016/j.neuint.2019.104580
12. Costa LG, Cole TB, Dao K, Chang YC, Coburn J, Garrick JM. Effects of air pollution on the nervous system and its possible role in neurodevelopmental and neurodegenerative disorders. Pharmacol Ther. 2020;210:107523. doi: 10.1016/j.pharmthera.2020.107523
13. Sorokin GA, Shilov VV. Dynamics of indices of the workers’ health in different labor intensity. Gigiena i Sanitariya. 2020;99(6):618-623. (In Russ.) doi: 10.47470/0016-9900-2020-99-6-618-623
14. Parakhonsky AP. [Aging of the immune system.] Mezhdunarodnyy Zhurnal Prikladnykh i Fundamental’nykh Issledovaniy. 2011;(6-1):73-74. (In Russ.)
15. Sorokin GA. [Methodology for determining the optimal duration of the working day and week based on chronobiology of performance and fatigue.] Dr. Sci. (Biol.) thesis. N.F. Izmerov Research Institute of Occupational Medicine; 2020. (In Russ.) Accessed May 25, 2023. https://www.dissercat.com/content/metodologiya-opredeleniya-optimalnoi-prodolzhitelnosti-rabochego-dnya-i-nedeli-na-osnove-khr/read
16. Sigahi TFAC, Kawasaki BC, Bolis I, Morioka SN. A systematic review on the impacts of Covid-19 on work: Contributions and a path forward from the perspectives of ergonomics and psychodynamics of work. Hum Factors Ergon Manuf. 2021;31(4):375-388. doi: 10.1002/hfm.20889
17. Žaja R, Kerner I, Macan J, Milošević M. Characteristics of work-related COVID-19 in Croatian healthcare workers: a preliminary report. Arh Hig Rada Toksikol. 2021;72(1):36-41. doi: 10.2478/aiht-2021-72-3530
18. Mihai AM, Barben J, Dipanda M, et al. Analysis of COVID-19 in professionals working in geriatric environment: Multicenter prospective study. Int J Environ Res Public Health. 2021;18(18):9735. doi: 10.3390/ijerph18189735
19. Ochoa-Leite C, Bento J, Rocha DR, et al. Occupational management of healthcare workers exposed to COVID-19. Occup Med (Lond). 2021;71(8):359-365. doi: 10.1093/occmed/kqab117
20. Sorokin GA, Chistyakov ND, Chernysheva MP, Chalkina ON. Professionally caused circadian rhythm disorders and the risk of COVID-19 in medical workers. Sotsial'nye Aspekty Zdorov'ya Naseleniya. 2022;68(1):2. (In Russ.) doi: 10.21045/2071-5021-2022-68-1-2
Review
For citations:
Sorokin G.A., Chistyakov N.D., Chernysheva M.P., Kir'yanova M.N. Age-Specific Dynamics of Risks of COVID-19 of Different Severity among Healthcare and Industrial Workers. Public Health and Life Environment – PH&LE. 2023;31(5):78-84. (In Russ.) https://doi.org/10.35627/2219-5238/2023-31-5-78-84