Association of depression and heart rate variability in medical staff exposed to various types of diagnostic non-ionizing radiation

Introduction. Magnetic resonance radiation and ultrasound are the most common types of nonionizing radiation (NIR). Existing data on the biological effects of these types of non-ionizing radiation on the cardiovascular system and nervous system are of an ambiguous nature. There are no universal tools for assessing the long-term biological effects of NIR.

Aim. To investigate the relationship between heart rate variability indicators and depression among healthcare professionals based on their professional exposure to various types of non-ionizing radiation: ultrasound and magnetic fields.

Materials and methods. The study included 60 healthcare workers from magnetic resonance imaging (n=22), ultrasound (n=20) and ophthalmology (n=18) rooms. All medical workers had professional contact only with one type of NIR. The level of depression in all subjects was assessed using the PHQ-9 scale and the heart rate variability (HRV) indicators.

Results and discussion. 60% of the medical workers had various levels of depression. In the group of ultrasound room workers, 60% had mild depression and 25% had moderate to severe depression. When assessing intergroup differences using the Mann-Whitney criterion, statistically significant differences were found in depression (p=0.0001) and HF (p=0.001). In conducting multiple multivariate logistic regression (control group – medical staff of ophthalmological rooms), depression lost its significance, and only HF in the group of MRI room medical workers retained statistical significance (p=0.049)

Conclusions. Overall, our results demonstrate a high level of depression among medical workers, and HRV serves as an objective indicator reflecting a decrease in vagus nerve tone associated with depression symptoms. Further research is needed to assess the biological effects of ultrasound and radiation from MRI devices on the health of medical workers, which will help develop preventive measures.

1. Chou CK. Controversy in Electromagnetic Safety. Int. J. Environ. Res. Public Health. 2022; 19: 16942. https://doi.org/10.3390/ijerph192416942

2. Vijayalaxmi F.M., Speck O. Magnetic resonance imaging (MRI): A review of genetic damage investigations. Magn. Reson. Rev. 2015; 36 (2): 93- 100. https://doi.org/10.1016/j.mrrev.2015.02.002

3. Franco G., Perduri R., Murolo A. Health effects of occupational exposure to static magnetic fields used in magnetic resonance imaging: a review. Med. Lav. 2008; 99 (1): 16-28.

4. Schaap K., Christopher-de Vries Y., Mason C.K., de Vocht F., Portengen L., Kromhout H. Occupational exposure of healthcare and research staff to static magnetic stray fields from 1.5-7 Tesla MRI scanners is associated with reporting of transient symptoms. Occup. Environ. Med. 2014; 71: 423- 429.

5. MRI Safety and Risks: Biological Effects of MRI. https://www.medical-professionals.com/en/risks-mri-biological/

6. Roberts D.C., Marcelli V., Gillen J.S., Carey J.P., Della Santina C.C., Zee D.S. MRI magnetic field stimulates rotational sensors of the brain. Curr. Biol. 2011; 21: 1635-1640.

7. Ham C.L., Engels J.M., van de Wiel G.T., Machielsen A. Peripheral nerve stimulation during MRI: effects of high gradient amplitudes and switching rates. Journal of Magnetic Resonance Imaging. 1997; 7 (5): 933-937. https://doi.org/10.1002/jmri.1880070524

8. International Electrotechnical Commission. Medical electrical equipment - particular requirements for the safety of magnetic resonance equipment for medical diagnosis. IEC 60601-2-33, 1995 revised 2002. https://webstore.iec.ch/en/publication/67211

9. de Vocht F., Stevens T., van Wendel-deJoode B., Engels H., Kromhout H. Acute neurobehavioral effects of exposure to static magnetic fields: analyses of exposureresponse relations. J. Magn. Reson. Imaging. 2006; 23: 291-297.

10. van Nierop L.E., Slottje P., van Zandvoort M.J., de Vocht F., Kromhout H. Effects of magnetic stray fields from a 7 Tesla MRI scanner on neurocognition: a double-blind randomised crossover study. Occup. Environ. Med. 2012; 69: 759-766.

11. Shellock F. Radiofrequency energyinduced heating during MR procedures: a review. Journal of Magnetic Resonance Imaging. 2000; 12 (1): 30-36.

12. Riesz P., Kondo T. Free radical formation induced by ultrasound and its biological implications. Free Radic. Biol. Med. 1992; 13: 247-270.

13. Feril L.B. Jr., Kondo T. Biological effects of low intensity ultrasound: The mechanism involved, and its implications on therapy and on biosafety of ultrasound. J. Radiat. Res. (Tokyo). 2004; 45: 479-489.

14. Izadifar Z., Babyn P., Chapman D. Mechanical and biological effects of ultrasound: A review of present knowledge. Ultrasound Med. Biol. 2017; 43 (6): 1085-1104.

15. Ciaravino V., Miller M.W., Carstensen E.L. Sister-chromatid exchanges in human lymphocytes exposed in vitro to therapeutic ultrasound. Mutat. Res. 1986; 172: 185-188.

16. Stella M., Trevisan L., Montaldi A. Induction of sister-chromatid exchanges in human lymphocytes exposed in vitro and in vivo to therapeutic ultrasound. Mutat. Res. 1984; 138: 75-85.

17. Ellisman M.H., Palmer D.E., Andr M.P. Diagnostic levels of ultrasound may disrupt myelination. Exp. Neurol. 1987; 98; 78-92.

18. Nowicki A. Safety of ultrasonic examinations; thermal and mechanical indices. Med. Ultrason. 2020; 22 (2): 203-210. https://doi.org/10.11152/mu-2372

19. Vanderlei L.C.M., Pastre C.M., Hoshi R.A., Carvalho T.D.de, Godoy M.F.de. Basic notions of heart rate variability and its clinical applicability. Rev Bras Cir. Cardiovasc. 2009; 24 (2): 205- 217. https://doi.org/10.1590/s0102-76382009000200018

20. Schnell I., Potchter O., Epstein Y., Yaakov Y., Hermesh H., Brenner S., Tirosh E. The effects of exposure to environmental factors on Heart Rate Variability: an ecological perspective. Environ. Pollut. 2013; 183: 7-13. https://doi.org/10.1016/j.envpol.2013.02.005. PMID: 23477780

21. Nkurikiyeyezu K.N., Suzuki Y., Lopez G.F. Heart rate variability as a predictive biomarker of thermal comfort. J. Ambient. Intell. Human. Comput. 2018; 9: 1465-1477. https://doi.org/10.1007/s12652-017-0567-4

22. Maurer D.M., Raymond T.J., Davis B.N. Depression: Screening and Diagnosis. Am. Fam. Physician. 2018; 98 (8): 508-515.

23. Fond G., Fernandes S., Lucas G., Greenberg N., Boyer L. Depression in healthcare workers: Results from the nationwide AMADEUS survey. Int. J. Nurs. Stud. 2022; 135: 104328. https://doi.org/10.1016/j.ijnurstu.2022.104328

24. Olaya B., Pérez-Moreno M., BuenoNotivol J., Gracia-García P., Lasheras I., Santabárbara J. Prevalence of depression among healthcare workers during the COVID19 outbreak: a systematic review and meta-analysis. J. Clin. Med. 2021; 10: 3406. https://doi.org/10.3390/jcm10153406

25. Asami Y., Goren A., Okumura Y. Work productivity loss with depression, diagnosed and undiagnosed, among employed respondents in an internet-based survey conducted in Japan. Value Health J. Int. Soc. Pharmacoecon. Outcomes Res. 2014; 17: A463. https://doi.org/10.1016/j.jval.2014.08.1289

26. Baker V.B., Sowers C.B., Hack N.K. Lost productivity associated with headache and depression: a quality improvement project identifying a patient population at risk. J. Headache Pain. 2020; 21: 50. https://doi.org/10.1186/s10194-020-01107-4

27. Beck A., Crain A.L., Solberg L.I., Unützer J., Glasgow R.E., Maciosek M.V., Whitebird R. Severity of depression and magnitude of productivity loss. Ann. Fam. Med. 2011; 9: 305-311. https://doi.org/10.1370/afm.1260

28. Patel R.S., Bachu R., Adikey A., Malik M., Shah M. Factors related to physician burnout and its consequences: a review. Behav. Sci. 2018; 8: 98. https://doi.org/10.3390/bs8110098

29. Enns V., Currie S., Wang J. Professional autonomy and work setting as contributing factors to depression and absenteeism in Canadian nurses. Nurs. Outlook. 2015; 63: 269-277. https://doi.org/10.1016/j.outlook.2014.12.014

30. Gi T.S., Devi K.M., Neo Kim E.A. A systematic review on the relationship between the nursing shortage and nurses’ job satisfaction, stress and burnout levels in oncology/haematology settings. JBI Libr. Syst. Rev. 2011; 9: 1603-1649. https:// doi.org/10.11124/01938924-201109390-00001

31. Huang H., Xia Y., Zeng X., Lü A. Prevalence of depression and depressive symptoms among intensive care nurses: A meta-analysis. Nurs. Crit. Care. 2022; 27 (6): 739-746. https://doi.org/10.1111/nicc.12734, PMID: 34989060

32. Power N., Deschênes S.S., Ferri F., Schmitz N. The association between job strain, depressive symptoms, and cardiovascular disease risk: results from a cross-sectional population-based study in Québec Canada. Int. Arch. Occup. Environ. Health. 2020; 93: 1013-1021. https://doi.org/10.1007/s00420-020-01550-5

33. Tsutsumi A., Kayaba K., Theorell T., Siegrist J. Association between job stress and depression among Japanese employees threatened by job loss in a comparison between two complementary job-stress models. Scand. J. Work Environ. Health. 2001; 27: 146-153. https://doi.org/10.5271/sjweh.602

34. Moyano D.B., Paraiso D.A., GonzálezLezcano R.A. Possible Effects on Health of Ultrasound Exposure, Risk Factors in the Work Environment and Occupational Safety Review. Healthcare (Basel). 2022; 10 (3): 423. https://doi.org/10.3390/healthcare10030423

35. Shaffer F., Ginsberg J.P. An Overview of Heart Rate Variability Metrics and Norms. Front. Public Health. 2017; 5: 258. https://doi.org/10.3389/fpubh.2017.00258

36. Kantarcı M., Aydın S., Oğul H., Kızılgöz V. New imaging techniques and trends in radiology. Diagn. Interv. Radiol. 2025; 31 (5): 505-517. https://doi.org/10.4274/dir.2024.242926