Electromagnetic fields of cellular communication as risk factors able to produce negative effects on the central nervous system of children and adolescents (review). Part 1. Modeling. parameters of electroencephalography and sensorimotor reactions

UDC: 
57.042+57.049+614
Authors: 

N.I. Khorseva1, P.E. Grigoriev2

Organization: 

1Emanuel Institute of Biochemical Physics of Russian Academy of Sciences, 4 Kosygina St., Moscow, 119334, Russian Federation
2Sevastopol State University, 33 Universitetskaya St., Sevastopol, 299053, Russian Federation

Abstract: 

It is quite relevant to investigate possible outcomes of exposure to radio frequency electromagnetic fields (RF EMF) since contemporary children and adolescents have become active users of the most advanced technologies. They are especially susceptible to electromagnetic factors; therefore, it is necessary to have a proper insight into outcomes of such exposures for the body.

The central nervous system (CNS) is one of the main targets under exposure to RF EMF. In most cases, users hold mobile phones close to their heads thereby directly exposing their brains to RF EMF.

As the analysis of literature data has shown, there are few studies in this area; however, proposed options for assessing the impact of RF EMF on children and adolescents are very diverse.

This part of the review focuses on various types of modeling. These are not only phantom, voxel models or the finite difference method but also new approaches such as distribution matrices, Monte Carlo simulations and an integrated radio frequency model based on the results of magnetic resonance imaging of the brain and other methods.

The review provides the results obtained by investigating encephalography under exposure to RF EMF created by mobile communication devices. They are rather contradictory; however, changes in the bioelectrical activity of the brain are detected in most cases, in particular, a decrease in the alpha rhyme.

Since the characteristics of sensorimotor reactions quite clearly reflect the power relations in the cerebral cortex, we analyzed changes in the parameters of simple auditory-motor and visual-motor reactions in children and adolescents who were mobile communication users. In addition, the review covers the results of changes in working capacity, fatigue, the duration of an individual minute and the reproduction of a given rhythm.

Keywords: 
radio frequency electromagnetic field, central nervous system, modeling, electroencephalography, psychophysiological indicators, children, adolescents, risk factor
Khorseva N.I., Grigoriev P.E. Electromagnetic fields of cellular communication as risk factors able to produce negative ef-fects on the central nervous system of children and adolescents (review). Part 1. Modeling. Parameters of electroencephalo-graphy and sensorimotor reactions. Health Risk Analysis, 2024, no. 2, pp. 162–169. DOI: 10.21668/health.risk/2024.2.15.eng
References: 
  1. Warille A.A., Onger M.E., Turkmen A.P., Deniz Ö.G., Altun G., Yurt K.K., Altunkaynak B.Z., Kaplan S. Controversies on electromagnetic field exposure and the nervous systems of children. Histol. Histopathol., 2016, vol. 31, no. 5, pp. 461–468. DOI: 10.14670/HH-11-707
  2. Grigoriev Yu.G., Grigoriev O.A. Sotovaya svyaz' i zdorov'e: elektromagnitnaya obstanovka, radiobiologicheskie i gi-gienicheskie problemy, prognoz opasnosti [Cellular communication and health. Electromagnetic environment. Radiobiological and hygienic issues]. Moscow, Ekonomika Publ., 2016, 574 p. (in Russian).
  3. Grigoriev Yu.G., Khorseva N.I. Mobil'naya svyaz' i zdorov'e detei. Otsenka opasnosti primeneniya mobil'noi svyazi det'mi i podrostkami. Rekomendatsii detyam i roditelyam [Mobile communication and children health. Assessment of the hazard of using mobile communications by children and teenagers. Recommendations for children and parents]. Moscow, Ekonomika Publ., 2014, 230 p. (in Russian).
  4. Grigoriev Y.G., Khorseva N.I. A Longitudinal Study of Psychophysiological Indicators in Pupils Users of Mobile Communications in Russia (2006–2017). In book: Mobile Communications and Public Health; M. Markov ed. Boca Raton, CRC Press Publ., 2018, pp. 237–253. DOI: 10.1201/b22486-10
  5. Kabali H.K., Irigoyen M.M., Nunez-Davis R., Budacki J.G., Mohanty S.H., Leister K.P., Bonner R.L. Jr. Exposure and Use of Mobile Media Devices by Young Children. Pediatrics, 2015, vol. 136, no. 6, pp. 1044–1050. DOI: 10.1542/peds.2015-2151
  6. Kılıç A.O., Sari E., Yucel H., Oğuz M.M., Polat E., Acoglu E.A., Senel S. Exposure to and use of mobile devices in children aged 1–60 months. Eur. J. Pediatr., 2019, vol. 178, no. 2, pp. 221–227. DOI: 10.1007/s00431-018-3284-x
  7. Dimbylow P., Bolch W. Whole-body-averaged SAR from 50 MHz to 4 GHz in the University of Florida child voxel phantoms. Phys. Med. Biol., 2007, vol. 52, no. 22, pp. 6639–6649. DOI: 10.1088/0031-9155/52/22/006
  8. Beard B.B., Kainz W. Review and standardization of cell phone exposure calculations using the SAM phantom and ana-tomically correct head models Meta-Analysis. Biomed. Eng. Online, 2004, vol. 3, no. 1, pp. 34. DOI: 10.1186/1475-925X-3-34
  9. Dimbylow P., Bolch W., Lee C. SAR calculations from 20 MHz to 6 GHz in the University of Florida newborn voxel phantom and their implications for dosimetry. Phys. Med. Biol., 2010, vol. 55, no. 5, pp. 1519–1530. DOI: 10.1088/0031-9155/55/5/017
  10. Findlay R.P., Dimbylow P.J. SAR in a child voxel phantom from exposure to wireless computer networks (Wi-Fi). Phys. Med. Biol., 2010, vol. 55, no. 15, pp. N405–N411. DOI: 10.1088/0031-9155/55/15/N01
  11. Gandhi O.P., Kang G. Calculation of induced current densities for humans by magnetic fields from electronic article surveillance devices. Phys. Med. Biol., 2001, vol. 46, no. 11, pp. 2759–2771. DOI: 10.1088/0031-9155/46/11/301
  12. Gandhi O.P. Electromagnetic fields: human safety issues. Annu. Rev. Biomed. Eng., 2002, vol. 4, pp. 211–234. DOI: 10.1146/annurev.bioeng.4.020702.153447
  13. Gandhi O.P., Morgan L.L., de Salles A.A., Han Y.-Y., Herberman R.B., Davis D.L. Exposure limits: the underes-timation of absorbed cell phone radiation, especially in children. Electromagn. Biol. Med., 2012, vol. 31, no. 1, pp. 34–51. DOI: 10.3109/15368378.2011.622827
  14. Gandhi O.P., Kang G. Some present problems and a proposed experimental phantom for SAR compliance testing of cellular telephones at 835 and 1900 MHz. Phys. Med. Biol., 2002, vol. 47, no. 9, pp. 1501–1518. DOI: 10.1088/0031-9155/47/9/306
  15. Keshvari J., Lang S. Comparison of radio frequency energy absorption in ear and eye region of children and adults at 900, 1800 and 2450 MHz. Phys. Med. Biol., 2005, vol. 50, no. 18, pp. 4355–4369. DOI: 10.1088/0031-9155/50/18/008
  16. Keshvari J., Keshvari R., Lang S. The effect of increase in dielectric values on specific absorption rate (SAR) in eye and head tissues following 900, 1800 and 2450 MHz radio frequency (RF) exposure. Phys. Med. Biol., 2006, vol. 51, no. 6, pp. 1463–1477. DOI: 10.1088/0031-9155/51/6/007
  17. Wiart J., Hadjem A., Gadi N., Bloch I., Wong M.F., Pradier A., Lautru D., Hanna V.F., Dale C. Modeling of RF head exposure in children. Bioelectromagnetics, 2005, suppl. 7, pp. S19–S30. DOI: 10.1002/bem.20155
  18. Wiart J., Hadjem A., Wong M.F., Bloch I. Analysis of RF exposure in the head tissues of children and adults. Phys. Med. Biol., 2008, vol. 53, no. 13, pp. 3681–3695. DOI: 10.1088/0031-9155/53/13/019
  19. Morelli M.S., Gallucci S., Siervo B., Hartwig V. Numerical Analysis of Electromagnetic Field Exposure from 5G Mobile Communications at 28 GHZ in Adults and Children Users for Real-World Exposure Scenarios. Int. J. Environ. Res. Public Health, 2021, vol. 18, no. 3, pp. 1073. DOI: 10.3390/ijerph18031073
  20. Vtornikova N.I., Babalyan A.V., Karelin A.A., Ivanov V.A. Evaluation of EMF exposure of mobile phones on human head. Uchenye zapiski SPbGMU im. akad. I.P. Pavlova, 2017, vol. 24, no. 4, pp. 75–81. DOI: 10.24884/1607-4181-2017-24-4-75-81 (in Russian).
  21. Brzozek C., Benke K.K., Zeleke B.M., Croft R.J., Dalecki A., Dimitriadis C., Kaufman J., Sim M.R. [et al.]. Uncertainty Analysis of Mobile Phone Use and Its Effect on Cognitive Function: The Application of Monte Carlo Simulation in a Cohort of Australian Primary School Children. Int. J. Environ. Res. Public Health, 2019, vol. 16, no. 13, pp. 2428. DOI: 10.3390/ijerph16132428
  22. Cabré-Riera A., El Marroun H., Muetzel R., van Wel L., Liorni I., Thielens A., Birks L.E., Pierotti L. [et al.]. Estimated whole-brain and lobe-specific radiofrequency electromagnetic fields doses and brain volumes in preadolescents. Environ. Int., 2020, vol. 142, pp. 105808. DOI: 10.1016/j.envint.2020.105808
  23. Birks L.E., van Wel L., Liorni I., Pierotti L., Guxens M., Huss A., Foerster M., Capstick M. [et al.]. Radiofrequency electromagnetic fields from mobile communication: Description of modeled dose in brain regions and the body in European children and adolescents. Environ. Res., 2021, vol. 193, pp. 110505. DOI: 10.1016/j.envres.2020.110505
  24. Eeftens M., Shen C., Sönksen J., Schmutz C., van Wel L., Liorni I., Vermeulen R., Cardis E. [et al.]. Modelling of daily radiofrequency electromagnetic field dose for a prospective adolescent cohort. Environ. Int., 2023, vol. 172, pp. 107737. DOI: 10.1016/j.envint.2023.107737
  25. Cabré-Riera A., van Wel L., Liorni I., Thielens A., Birks L.E., Pierotti L., Joseph W., González-Safont L. [et al.]. Association between estimated whole-brain radiofrequency electromagnetic fields dose and cognitive function in preadolescents and adolescents. Int. J. Hyg. Environ. Health, 2021, vol. 231, pp. 113659. DOI: 10.1016/j.ijheh.2020.113659
  26. Sacco G., Pisa S., Zhadobov M. Age-dependence of electromagnetic power and heat deposition in near-surface tissues in emerging 5G bands. Sci. Rep., 2021, vol. 11, no. 1, pp. 3983. DOI: 10.1038/s41598-021-82458-z
  27. Croft R.J., Leung S., McKenzie R.J., Loughran S.P., Iskra S., Hamblin D.L., Cooper N.R. Effects of 2G and 3G mobile phones on human alpha rhythms: Resting EEG in adolescents, young adults, and the elderly. Bioelectromagnetics, 2010, vol. 31, no. 6, pp. 434–444. DOI: 10.1002/bem.20583
  28. Leung S., Croft R.J., McKenzie R.J., Iskra S., Silber B., Cooper N.R., O'Neill B., Cropley V. [et al.]. Effects of 2G and 3G mobile phones on performance and electrophysiology in adolescents, young adults and older adults. Clin. Neurophysiol., 2011, vol. 122, no. 11, pp. 2203–2216. DOI: 10.1016/j.clinph.2011.04.006
  29. Vyatleva O.A., Teksheva L.M., Kurgansky A.M. Physiological and hygienic assessment of the impact of mobile phones with various radiation intensity on the functional state of brain of children and adolescents according to electroencephalographic data. Gigiena i sanitariya, 2016, vol. 95, no. 10, pp. 965–968. DOI: 10.18821/0016-9900-2016-95-10-965-968 (in Russian).
  30. Vyatleva O.A., Kurgansky A.M. Uroven' izlucheniya mobil'nykh telefonov, ispol'zuemykh sovremennymi shkol'ni-kami, i ego vliyanie na bioelektricheskuyu aktivnost' mozga i vegetativnuyu regulyatsiyu serdechnogo ritma detei [The level of radiation from mobile phones used by modern schoolchildren and its impact on the bioelectrical activity of the brain and autonomic regulation of the heart rate of children]. Ekologicheskie problemy sovremennosti: vyyavlenie i preduprezhdenie neblagopriyatnogo vozdeistviya antropogenno determinirovannykh faktorov i klimaticheskikh izmenenii na okruzhayushchuyu sredu i zdorov'e naseleniya: Materialy Mezhdunarodnogo Foruma Nauchnogo soveta Rossiiskoi Federatsii po ekologii cheloveka i gigiene okruzhayushchei sredy, Moscow, 2017, pp. 93–94 (in Russian).
  31. Vyatleva O.A. The impact of long-term mobile phone use at the right ear on the interhemispheric asymmetry of alpha rhythm and the auditory memory of young school children. Asimmetriya, 2019, vol. 13, no. 3, pp. 28–39. DOI: 10.25692/ASY.2019.13.3.003 (in Russian).
  32. Loughran S.P., Benz D.C., Schmid M.R., Murbach M., Kuster N., Achermann P. No increased sensitivity in brain activity of adolescents exposed to mobile phone-like emissions. Clin. Neurophysiol., 2013, vol. 124, no. 7, pp. 1303–1308. DOI: 10.1016/j.clinph.2013.01.010
  33. Loughran S.P., Verrender A., Dalecki A., Burdon C.A., Tagami K., Park J., Taylor N.A.S., Croft R.J. Radiofrequency Electromagnetic Field Exposure and the Resting EEG: Exploring the Thermal Mechanism Hypothesis. Int. J. Environ. Res. Public Health., 2019, vol. 16, no. 9, pp. 1505. DOI: 10.3390/ijerph16091505
  34. Gilev A.V., Gileva O.B. Influence of ICT learning technologies on the bioelectric activity of the brain of schoolchildren. Vestnik psikhofiziologii, 2022, no. 2, pp. 59–73. DOI: 10.34985/h7833-6875-6818-z (in Russian).
  35. Shutova S.V., Muravyova I.V. Sensorimotor reactions as characteristics of functional state of CNS. Vestnik tam-bovskogo universiteta. Seriya: Estestvennye i tekhnicheskie nauki, 2013, vol. 18, no. 5–3, pp. 2831–2840 (in Russian).
  36. Nekhoroshkova A.N., Gribanov A.V., Deputat I.S. Sensorimotor reactions in psychophysiological studies (review). Vestnik Severnogo (Arkticheskogo) federal'nogo universiteta. Seriya: Mediko-biologicheskie nauki, 2015, no. 1, pp. 38–48 (in Russian).
  37. Geertsen S.S., Thomas R., Larsen M.N., Dahn I.M., Andersen J.N., Krause-Jensen M., Korup V., Nielsen C.M. [et al.]. Motor Skills and Exercise Capacity Are Associated with Objective Measures of Cognitive Functions and Academic Performance in Preadolescent Children. PLoS One, 2016, vol. 11, no. 8, pp. e0161960. DOI: 10.1371/journal.pone.0161960
  38. Khorseva N.I., Al’-Kudri O.R., Grigoryev P.E., Islyamov R.N., Shulzhenko N.Yu. Mode of use by mobile phone and change of time of simple audio-motor reaction for users of mobile communication. Age related features of ipsilateral and contrala-teral effects. Biomeditsinskaya radioelektronika, 2021, vol. 24, no. 1, pp. 35–41. DOI: 10.18127/j15604136-202101-05 (in Russian).
  39. Khorseva N.I., Al’-Kurdi O.R., Shul’zhenko N.Yu. Sensocother reactions and individual minute duration of children-users of mobile communication. Vestnik Fiziko-tekhnicheskogo instituta Krymskogo federal'nogo universiteta im. V.I. Ver-nadskogo, 2017, vol. 1 (67–69), no. 1, pp. 66–85 (in Russian).
  40. Kalinina L.P., Kuz’min A.G. Correlation between visual-motor reaction parameters and visual event-related potentials in schoolchildren living in the north of Russia. Zhurnal mediko-biologicheskikh issledovanii, 2019, vol. 7, no. 4, pp. 487–490. DOI: 10.17238/issn2542-1298.2019.7.4.487 (in Russian).
  41. Kozlova P.I., Dzhos Yu.S. Sex-related characteristics of visual cognitive evoked potentials in schoolchildren aged 13–18 year. Vestnik Severnogo (Arkticheskogo) federal'nogo universiteta. Seriya: Estestvennye nauki, 2014, no. 1, pp. 64–71 (in Russian).
Received: 
24.09.2023
Approved: 
31.05.2024
Accepted for publication: 
20.06.2024

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