Effects of man-made electromagnetic fields on heart rate variability parameters of general public: a systematic review and meta-analysis of experimental studies
Abstract
Objectives
The effects of man-made electromagnetic fields (EMFs) on the cardiovascular system have been investigated in many studies. In this regard, the cardiac autonomic nervous system (ANS) activity due to EMFs exposure, assessed by heart rate variability (HRV), was targeted in some studies. The studies investigating the relationship between EMFs and HRV have yielded conflicting results. We performed a systematic review and meta-analysis to assess the data’s consistency and identify the association between EMFs and HRV measures.
Content
Published literature from four electronic databases, including Web of Science, PubMed, Scopus, Embase, and Cochrane, were retrieved and screened. Initially, 1601 articles were retrieved. After the screening, 15 original studies were eligible to be included in the meta-analysis. The studies evaluated the association between EMFs and SDNN (standard deviation of NN intervals), SDANN (Standard deviation of the average NN intervals for each 5 min segment of a 24 h HRV recording), and PNN50 (percentage of successive RR intervals that differ by more than 50 ms).
Summary
There was a decrease in SDNN (ES=−0.227 [−0.389, −0.065], p=0.006), SDANN (ES=−0.526 [−1.001, −0.05], p=0.03) and PNN50 (ES=−0.287 [−0.549, −0.024]). However, there was no significant difference in LF (ES=0.061 (−0.267, 0.39), p=0.714) and HF (ES=−0.134 (0.581, 0.312), p=0.556). In addition, a significant difference was not observed in LF/HF (ES=0.079 (−0.191, 0.348), p=0.566).
Outlook
Our meta-analysis suggests that exposure to the environmental artificial EMFs could significantly correlate with SDNN, SDANN, and PNN50 indices. Therefore, lifestyle modification is essential in using the devices that emit EMs, such as cell phones, to decrease some signs and symptoms due to EMFs’ effect on HRV.
Funding source: Isfahan University of Medical Sciences
Award Identifier / Grant number: 140130
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Research funding: This study was funded by Isfahan University of Medical Sciences [grant number: 140130].
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: Authors state no conflict of interest.
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Informed consent: Informed consent is not applicable.
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Ethical approval: This study was approved by Research Ethics Committee of the “Alzahra Research Centers”.
References
1. Rubin, GJ, Hahn, G, Everitt, BS, Cleare, AJ, Wessely, S. Are some people sensitive to mobile phone signals? Within participants double blind randomised provocation study. BMJ 2006;332:886–91. https://doi.org/10.1136/bmj.38765.519850.55.Search in Google Scholar PubMed PubMed Central
2. Kaszuba-Zwoińska, J, Gremba, J, Gałdzińska-Calik, B, Wójcik-Piotrowicz, K, Thor, P. Electromagnetic field induced biological effects in humans. Przegl Lek 2015;72:636–41.Search in Google Scholar
3. Mansourian, M, Firoozabadi, M, Hassan, ZM. The role of 217-Hz ELF magnetic fields emitted from GSM mobile phones on electrochemotherapy mechanisms. Electromagn Biol Med 2020;39:239–49. https://doi.org/10.1080/15368378.2020.1762635.Search in Google Scholar PubMed
4. Mansourian, M, Marateb, HR, Vaseghi, G. The effect of extremely low-frequency magnetic field (50–60 Hz) exposure on spontaneous apoptosis: the results of a meta-analysis. Adv Biomed Res 2016;5:141–5. https://doi.org/10.4103/2277-9175.187375.Search in Google Scholar PubMed PubMed Central
5. Mansourian, M, Firoozabadi, SMP, Hassan, ZM. Effect of pulse-modulated GSM-900 MHz electromagnetic field on the electrochemotherapy efficacy of 4T-1 cells. Iran J Med Phys 2018;15:264–70.Search in Google Scholar
6. Mansourian, M, Firoozabadi, S, Hassan, ZM. The effect of 900 MHz electromagnetic fields on biological pathways induced by electrochemotherapy. Electromagn Biol Med 2021;40:158–68. https://doi.org/10.1080/15368378.2020.1856681.Search in Google Scholar PubMed
7. Mahdavi, M, Yekta, R, Tackallou, SH. Association between ELF and RF electromagnetic field and Leukemia. Arch Adv Biosci 2015;6:106–15.Search in Google Scholar
8. Kim, JH, Lee, J-K, Kim, H-G, Kim, K-B, Kim, HR. Possible effects of radiofrequency electromagnetic field exposure on central nerve system. Biomol Ther (Seoul) 2019;27:265–75. https://doi.org/10.4062/biomolther.2018.152.Search in Google Scholar PubMed PubMed Central
9. Taki, M, Watanabe, S. Biological and health effects of exposure to electromagnetic field from mobile communications systems. IATSS Res 2001;25:40–50. https://doi.org/10.1016/s0386-1112(14)60069-8.Search in Google Scholar
10. Schuermann, D, Mevissen, M. Manmade electromagnetic fields and oxidative stress—biological effects and consequences for health. Int J Mol Sci 2021;22:3772. https://doi.org/10.3390/ijms22073772.Search in Google Scholar PubMed PubMed Central
11. Hirata, A, Diao, Y, Onishi, T, Sasaki, K, Ahn, S, Colombi, D, et al.. Assessment of human exposure to electromagnetic fields: review and future directions. IEEE Trans Electromagn C 2021;63:1619–30. https://doi.org/10.1109/temc.2021.3109249.Search in Google Scholar
12. Deruelle, F. The different sources of electromagnetic fields: dangers are not limited to physical health. Electromagn Biol Med 2020;39:166–75. https://doi.org/10.1080/15368378.2020.1737811.Search in Google Scholar PubMed
13. D’Angelo, C, Costantini, E, Kamal, M, Reale, M. Experimental model for ELF-EMF exposure: concern for human health. Saudi J Biol Sci 2015;22:75–84. https://doi.org/10.1016/j.sjbs.2014.07.006.Search in Google Scholar PubMed PubMed Central
14. Savitz, DA, Liao, D, Sastre, A, Kleckner, RC, Kavet, R. Magnetic field exposure and cardiovascular disease mortality among electric utility workers. Am J Epidemiol 1999;149:135–42. https://doi.org/10.1093/oxfordjournals.aje.a009779.Search in Google Scholar PubMed
15. Zhang, Y, Li, L, Liu, X, Ding, L, Wu, X, Wang, J, et al.. Examination of the effect of a 50-Hz electromagnetic field at 500 μT on parameters related with the cardiovascular system in rats. Front Public Health 2020;8:1–9. https://doi.org/10.3389/fpubh.2020.00087.Search in Google Scholar PubMed PubMed Central
16. Jeong, J, Kim, J, Lee, B, Min, Y, Kim, D, Ryu, J, et al.. Influence of exposure to electromagnetic field on the cardiovascular system. Autonom Autacoid Pharmacol 2005;25:17–23. https://doi.org/10.1111/j.1474-8673.2004.00328.x.Search in Google Scholar PubMed
17. Elmas, O. Effects of electromagnetic field exposure on the heart:a systematic review. Toxicol Ind Health 2016;32:76–82. https://doi.org/10.1177/0748233713498444.Search in Google Scholar PubMed
18. Shaffer, F, Ginsberg, JP. An overview of heart rate variability metrics and norms. Front Public Health 2017;5:258. https://doi.org/10.3389/fpubh.2017.00258.Search in Google Scholar PubMed PubMed Central
19. Nam, KC, Lee, JH, Noh, HW, Cha, EJ, Kim, NH, Kim, DW. Hypersensitivity to RF fields emitted from CDMA cellular phones: a provocation study. Bioelectromagnetics 2009;30:641–50. https://doi.org/10.1002/bem.20518.Search in Google Scholar PubMed
20. Stephenson, MD, Thompson, AG, Merrigan, JJ, Stone, JD, Hagen, JA. Applying heart rate variability to monitor health and performance in tactical personnel: a narrative review. Int J Environ Res Publ Health 2021;18:8143. https://doi.org/10.3390/ijerph18158143.Search in Google Scholar PubMed PubMed Central
21. Scott, EE, LoTemplio, SB, McDonnell, AS, McNay, GD, Greenberg, K, McKinney, T, et al.. The autonomic nervous system in its natural environment: immersion in nature is associated with changes in heart rate and heart rate variability. Psychophysiology 2021;58:e13698. https://doi.org/10.1111/psyp.13698.Search in Google Scholar PubMed
22. Clifford, GD, Azuaje, F, McSharry, P. Advanced methods and tools for ECG data analysis. Boston: Artech house Boston; 2006.Search in Google Scholar
23. Bigger, JTJr, Kleiger, RE, Fleiss, JL, Rolnitzky, LM, Steinman, RC, Miller, JP. Components of heart rate variability measured during healing of acute myocardial infarction. Am J Cardiol 1988;61:208–15. https://doi.org/10.1016/0002-9149(88)90917-4.Search in Google Scholar PubMed
24. Mahmad Khairai, K, Abdul Wahab, MN, Sutarto, AP. Heart Rate Variability (HRV) as a physiological marker of stress among electronics assembly line workers. Human-centered technology for a better tomorrow. Wiesbaden: Springer; 2022:3–14 pp.10.1007/978-981-16-4115-2_1Search in Google Scholar
25. Spada, GE, Masiero, M, Pizzoli, SFM, Pravettoni, G. Heart rate variability biofeedback in cancer patients: a scoping review. Behav Sci 2022;12:389. https://doi.org/10.3390/bs12100389.Search in Google Scholar PubMed PubMed Central
26. Goldberger, JJ, Challapalli, S, Tung, R, Parker, MA, Kadish, AH. Relationship of heart rate variability to parasympathetic effect. Circulation 2001;103:1977–83. https://doi.org/10.1161/01.cir.103.15.1977.Search in Google Scholar PubMed
27. Verrier, RL, Lown, B. Experimental studies of psychophysiological factors in sudden cardiac death. Acta Med Scand 1982;211:57–68. https://doi.org/10.1111/j.0954-6820.1982.tb00361.x.Search in Google Scholar PubMed
28. Hughes, JW, Stoney, CM. Depressed mood is related to high-frequency heart rate variability during stressors. Psychosom Med 2000;62:796–803. https://doi.org/10.1097/00006842-200011000-00009.Search in Google Scholar PubMed
29. Shaffer, F, Ginsberg, JP. An overview of heart rate variability metrics and norms. Front Public Health 2017;5:258. https://doi.org/10.3389/fpubh.2017.00258.Search in Google Scholar PubMed PubMed Central
30. Xhyheri, B, Manfrini, O, Mazzolini, M, Pizzi, C, Bugiardini, R. Heart rate variability today. Prog Cardiovasc Dis 2012;55:321–31. https://doi.org/10.1016/j.pcad.2012.09.001.Search in Google Scholar PubMed
31. Stuckey, MI, Tulppo, MP, Kiviniemi, AM, Petrella, RJ. Heart rate variability and the metabolic syndrome: a systematic review of the literature. Diabetes/Metabol Res Rev 2014;30:784–93. https://doi.org/10.1002/dmrr.2555.Search in Google Scholar PubMed
32. Gouin, J-P, Thayer, JF, Deschênes, SS, MacNeil, S, Booij, L. Implicit affect, heart rate variability, and the metabolic syndrome. Psychosom Med 2021;83:24–32. https://doi.org/10.1097/psy.0000000000000879.Search in Google Scholar PubMed
33. Bassett, D. A literature review of heart rate variability in depressive and bipolar disorders. Aust N Z J Psychiatr 2016;50:511–9. https://doi.org/10.1177/0004867415622689.Search in Google Scholar PubMed
34. Stautland, A, Jakobsen, P, Fasmer, OB, Osnes, B, Torresen, J, Nordgreen, T, et al.. Heart rate variability as biomarker for bipolar disorder. medRxiv; 2022.10.1101/2022.02.14.22269413Search in Google Scholar
35. Koenig, J, Kemp, AH, Beauchaine, TP, Thayer, JF, Kaess, M. Depression and resting state heart rate variability in children and adolescents—a systematic review and meta-analysis. Clin Psychol Rev 2016;46:136–50. https://doi.org/10.1016/j.cpr.2016.04.013.Search in Google Scholar PubMed
36. Aimaier, G, Qian, K, Zheng, Z, Peng, W, Zhang, Z, Ding, J, et al.. Interictal heart rate variability as a biomarker for comorbid depressive disorders among people with epilepsy. Brain Sci 2022;12:671. https://doi.org/10.3390/brainsci12050671.Search in Google Scholar PubMed PubMed Central
37. Murray, AR. Examining heart rate variability and alpha-amylase levels in predicting PTSD in combat-experienced marines. Alhambra: Alliant International University, California School of Professional; 2012.Search in Google Scholar
38. Chrousos, GP, Papadopoulou-Marketou, N, Bacopoulou, F, Lucafò, M, Gallotta, A, Boschiero, D. Photoplethysmography (PPG)-determined heart rate variability (HRV) and extracellular water (ECW) in the evaluation of chronic stress and inflammation. Hormones (Basel) 2022:1–8. https://doi.org/10.1007/s42000-021-00341-y.Search in Google Scholar PubMed
39. Broucqsault-Dédrie, C, De Jonckheere, J, Jeanne, M, Nseir, S. Measurement of heart rate variability to assess pain in sedated critically ill patients: a prospective observational study. PLoS One 2016;11: e0147720. https://doi.org/10.1371/journal.pone.0147720.Search in Google Scholar PubMed PubMed Central
40. Jhang, D, Chu, Y, Cai, J, Tai, Y, Chuang, C. Pain monitoring using heart rate variability and photoplethysmograph-derived parameters by binary logistic regression. J Med Biol Eng 2021;41:669–77. https://doi.org/10.1007/s40846-021-00651-x.Search in Google Scholar
41. Catai, AM, Pastre, CM, Godoy, MF, Silva, E, Takahashi, ACM, Vanderlei, LCM. Heart rate variability: are you using it properly? Standardisation checklist of procedures. Braz J Phys Ther 2020;24:91–102. Epub 2019/02/26. https://doi.org/10.1016/j.bjpt.2019.02.006.Search in Google Scholar PubMed PubMed Central
42. Ekici, B, Tanındı, A, Ekici, G, Diker, E. The effects of the duration of mobile phone use on heart rate variability parameters in healthy subjects. Anatol J Cardiol 2016;16:833. https://doi.org/10.14744/AnatolJCardiol.2016.6717.Search in Google Scholar PubMed PubMed Central
43. Alassiri, M, Alanazi, A, Aldera, H, Alqahtani, SA, Alraddadi, AS, Alberreet, MS, et al.. Exposure to cell phones reduces heart rate variability in both normal-weight and obese normotensive medical students. Explore 2020;16:264–70. https://doi.org/10.1016/j.explore.2020.02.006.Search in Google Scholar PubMed
44. Kurokawa, Y, Nitta, H, Imai, H, Kabuto, M. Can extremely low frequency alternating magnetic fields modulate heart rate or its variability in humans? Auton Neurosci 2003;105:53–61. https://doi.org/10.1016/s1566-0702(02)00296-5.Search in Google Scholar
45. Tamer, A, Gunduz, H, Oezildirm, S. The cardiac effects of a mobile phone positioned closest to the heart. Anatol J Cardiol 2009;9:380–4.Search in Google Scholar
46. Wallace, J, Andrianome, S, Ghosn, R, Blanchard, ES, Telliez, F, Selmaoui, B. Heart rate variability in healthy young adults exposed to global system for mobile communication (GSM) 900-MHz radiofrequency signal from mobile phones. Environ Res 2020;191:110097. https://doi.org/10.1016/j.envres.2020.110097.Search in Google Scholar PubMed
47. Page, MJ, McKenzie, JE, Bossuyt, PM, Boutron, I, Hoffmann, TC, Mulrow, CD, et al.. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev 2021;10:1–11. https://doi.org/10.1016/j.ijsu.2021.105906.Search in Google Scholar PubMed
48. Higgins, JP. Cochrane handbook for systematic reviews of interventions version 5.0.1. The Cochrane Collaboration. http://www.cochrane-handbook.org; 2008.10.1002/9780470712184Search in Google Scholar
49. Ma, L-L, Wang, Y-Y, Yang, Z-H, Huang, D, Weng, H, Zeng, X-T. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better? Mil Med Res 2020;7:1–11. https://doi.org/10.1186/s40779-020-00238-8.Search in Google Scholar PubMed PubMed Central
50. Higgins, JP, Thompson, SG. Quantifying heterogeneity in a meta‐analysis. Stat Med 2002;21:1539–58. https://doi.org/10.1002/sim.1186.Search in Google Scholar PubMed
51. Sutton, AJ, Duval, SJ, Tweedie, R, Abrams, KR, Jones, DR. Empirical assessment of effect of publication bias on meta-analyses. BMJ 2000;320:1574–7. https://doi.org/10.1136/bmj.320.7249.1574.Search in Google Scholar PubMed PubMed Central
52. Siwindarto, P. Poincaré plot of RR-interval differences (PORRID) a new method for assessing heart rate variability. J Basic Appl Sci Res 2014;4:308–13.Search in Google Scholar
53. Carnethon, MR, Prineas, RJ, Temprosa, M, Zhang, ZM, Uwaifo, G, Molitch, ME. The association among autonomic nervous system function, incident diabetes, and intervention arm in the Diabetes Prevention Program. Diabetes Care 2006;29:914–9. https://doi.org/10.2337/diacare.29.04.06.dc05-1729.Search in Google Scholar PubMed PubMed Central
54. Dalise, AM, Prestano, R, Fasano, R, Gambardella, A, Barbieri, M, Rizzo, MR. Autonomic nervous system and cognitive impairment in older patients: evidence from long-term heart rate variability in real-life setting. Front Aging Neurosci 2020;12:40. https://doi.org/10.3389/fnagi.2020.00040.Search in Google Scholar PubMed PubMed Central
55. Vanderlei, LCM, Pastre, CM, Hoshi, RA, Carvalho, TD, Godoy, MF. Basic notions of heart rate variability and its clinical applicability. Braz J Cardiovasc Surg 2009;24:205–17. https://doi.org/10.1590/s0102-76382009000200018.Search in Google Scholar PubMed
56. Nantsupawat, T, Tungsuk, P, Gunaparn, S, Phrommintikul, A, Wongcharoen, W. Effects of prolonged working hours on heart rate variability in internal medicine physicians. Sci Rep 2022;12: 18563. https://doi.org/10.1038/s41598-022-23538-6.Search in Google Scholar PubMed PubMed Central
57. Ben Mrad, I, Ben Mrad, M, Besbes, B, Zairi, I, Ben Kahla, N, Kamoun, S, et al.. Heart rate variability as an indicator of autonomic nervous system disturbance in Behcet’s disease. Int J Gen Med 2021;14:4877–86. https://doi.org/10.2147/ijgm.s326549.Search in Google Scholar
58. Zygmunt, A, Stanczyk, J. Methods of evaluation of autonomic nervous system function. Arch Med Sci 2010;6:11–8. https://doi.org/10.5114/aoms.2010.13500.Search in Google Scholar PubMed PubMed Central
59. Koizumi, K, Terui, N, Kollai, M. Effect of cardiac vagal and sympathetic nerve activity on heart rate in rhythmic fluctuations. J Auton Nerv Syst 1985;12:251–9. https://doi.org/10.1016/0165-1838(85)90065-7.Search in Google Scholar PubMed
60. Andrzejak, R, Poręba, R, Poreba, M, Derkacz, A, Skalik, R, Gać, P, et al.. The influence of the call with a mobile phone on heart rate variability parameters in healthy volunteers. Ind Health 2008;46:409–17. https://doi.org/10.2486/indhealth.46.409.Search in Google Scholar PubMed
61. Parazzini, M, Ravazzani, P, Tognola, G, Thuroczy, G, Molnar, FB, Sacchettini, A, et al.. Electromagnetic fields produced by GSM cellular phones and heart rate variability. Bioelectromagnetics 2007;28:122–9. https://doi.org/10.1002/bem.20275.Search in Google Scholar PubMed
62. Vegad, AM, Kacha, YK, Varu, MS, Mehta, HB, Shah, CJ. Effects of mobile phone radiation on heart rate variability of healthy young subjects. Int J Clin Exp Pathol 2015;2:23–8. https://doi.org/10.4103/2348-8093.155508.Search in Google Scholar
63. Lombardi, F. Clinical implications of present physiological understanding of HRV components. Card Electrophysiol Rev 2002;6:245–9. https://doi.org/10.1023/a:1016329008921.10.1023/A:1016329008921Search in Google Scholar PubMed
64. Electrophysiology TFotESoCtNASoP. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation 1996;93:1043–65. https://doi.org/10.1161/01.cir.93.5.1043.Search in Google Scholar
65. Wu, W, Gil, Y, Lee, J. Combination of wearable multi-biosensor platform and resonance frequency training for stress management of the unemployed population. Sensors 2012;12:13225–48. https://doi.org/10.3390/s121013225.Search in Google Scholar PubMed PubMed Central
66. Kleiger, RE, Miller, JP, Bigger, JTJr, Moss, AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol 1987;59:256–62. https://doi.org/10.1016/0002-9149(87)90795-8.Search in Google Scholar PubMed
67. Marotta, J, Piano, C, Brunetti, V, Genovese, D, Bentivoglio, AR, Calabresi, P, et al.. Heart rate variability during wake and sleep in Huntington’s disease patients: an observational, cross-sectional, cohort study. Neurodegener Dis 2021;21:79–86.10.1159/000520754Search in Google Scholar PubMed
68. Itabashi, K, Morita, J, Hirayama, T, Mase, K, Yamada, K, editors. Interactive model-based reminiscence using a cognitive model and physiological indices. In: Proceedings of the 18th international conference on cognitive modelling; 2020.Search in Google Scholar
69. Nonka, T, Lebedeva, E, Repin, A. Possibilities of detecting and correcting decreased heart rate variability in patients with coronary artery disease in combination with depressive disorders in a cardiology department. J Bull Siberian Med 2021;2021:65–70. https://doi.org/10.20538/1682-0363-2021-2-65-70.Search in Google Scholar
70. Corino, VD, Mainardi, L, Husser, D, Bollmann, A, editors. Autonomic modulation of ventricular response by exercise and antiarrhythmic drugs during atrial fibrillation. In: 11th Mediterranean conference on medical and biomedical engineering and computing 2007. Wiesbaden: Springer; 2007.Search in Google Scholar
71. Freitas, IMG, Miranda, JA, Mira, PAC, Lanna, CMM, Lima, JRP, Laterza, MC. Cardiac autonomic dysfunction in obese normotensive children and adolescents. Revista Paulista de Pediatria 2014;32:244–9. https://doi.org/10.1590/0103-0582201432210213.Search in Google Scholar PubMed PubMed Central
72. Adeyemi, O, Akinlade, O, Ogunmodede, J, Kolo, P, Katibi, I, Omotoso, A. Heart rate variability parameters among acute heart failure patients in a tertiary center in Nigeria. World J Adv Res Rev 2020;7:178–87. https://doi.org/10.30574/wjarr.2020.7.2.0274.Search in Google Scholar
73. Thayer, JF, Lane, RD. The role of vagal function in the risk for cardiovascular disease and mortality. Biol Psychol 2007;74:224–42. https://doi.org/10.1016/j.biopsycho.2005.11.013.Search in Google Scholar PubMed
74. Schubert, C, Lambertz, M, Nelesen, R, Bardwell, W, Choi, J-B, Dimsdale, J. Effects of stress on heart rate complexity—a comparison between short-term and chronic stress. Biol Psychol 2009;80:325–32. https://doi.org/10.1016/j.biopsycho.2008.11.005.Search in Google Scholar PubMed PubMed Central
75. Friedman, BH. An autonomic flexibility–neurovisceral integration model of anxiety and cardiac vagal tone. Biol Psychol 2007;74:185–99. https://doi.org/10.1016/j.biopsycho.2005.08.009.Search in Google Scholar PubMed
76. Thayer, JF, Friedman, BH. Stop that! Inhibition, sensitization, and their neurovisceral concomitants. Scand J Psychol 2002;43:123–30. https://doi.org/10.1111/1467-9450.00277.Search in Google Scholar PubMed
77. Schneider, U, Frank, B, Fiedler, A, Kaehler, C, Hoyer, D, Liehr, M, et al.. Human fetal heart rate variability-characteristics of autonomic regulation in the third trimester of gestation. J Perinat Med 2008;36:433–41. https://doi.org/10.1515/jpm.2008.059.Search in Google Scholar
78. Reardon, M, Malik, M. Changes in heart rate variability with age. Pacing Clin Electrophysiol 1996;19:1863–6. https://doi.org/10.1111/j.1540-8159.1996.tb03241.x.Search in Google Scholar PubMed
79. Vegad, A, Kacha, Y, Varu, M, Mehta, H, Shah, C. Effects of mobile phone radiation on heart rate variability of healthy young subjects. Int J Clin Exp Pathol 2015;2:23. https://doi.org/10.4103/2348-8093.155508.Search in Google Scholar
80. Barutcu, I, Esen, AM, Kaya, D, Turkmen, M, Karakaya, O, Saglam, M, et al.. Do mobile phones pose a potential risk to autonomic modulation of the heart? PACE-Pacing Clin Electrophysiol 2011;34:1511–4. https://doi.org/10.1111/j.1540-8159.2011.03162.x.Search in Google Scholar PubMed
81. Bhagyalakshmi, K, Mantur, VS, Kumar, NA, Pai, SR. A pilot study on long term effects of mobile phone usage on heart rate variability in healthy young adult males. J Clin Diagn Res 2014;6:346–9.Search in Google Scholar
82. Tabor, Z, Michalski, J, Rokita, E. Influence of 50 Hz magnetic field on human heart rate variability: linear and nonlinear analysis. Bioelectromagnetics 2004;25:474–80. https://doi.org/10.1002/bem.20039.Search in Google Scholar PubMed
83. Sait, M, Wood, A, Kirsner, R. Effects of 50 Hz magnetic field exposure on human heart rate variability with passive tilting. Physiol Meas 2006;27:73–83. https://doi.org/10.1088/0967-3334/27/1/007.Search in Google Scholar PubMed
84. Sait, ML, Wood, AW, Sadafi, HA. A study of heart rate and heart rate variability in human subjects exposed to occupational levels of 50 Hz circularly polarised magnetic fields. Med Eng Phys 1999;21:361–9. https://doi.org/10.1016/s1350-4533(99)00062-4.Search in Google Scholar PubMed
85. Al-Hazimi, A. Effects of the call with the mobile phone on heart rate variability parameters of healthy young people. J Chem Pharmaceut Res 2011;3:734–40.Search in Google Scholar
86. Alhusseiny, A, Al-Nimer, M, Majeed, A. Electromagnetic energy radiated from mobile phone alters electrocardiographic records of patients with ischemic heart disease. Ann Med Health Sci Res 2012;2:146–51. https://doi.org/10.4103/2141-9248.105662.Search in Google Scholar PubMed PubMed Central
87. Beres, S, Nemeth, A, Ajtay, Z, Kiss, I, Nemeth, B, Hejjel, L. Cellular phone irradiation of the head affects heart rate variability depending on inspiration/expiration ratio. In Vivo 2018;32:1145–53. https://doi.org/10.21873/invivo.11357.Search in Google Scholar PubMed PubMed Central
88. Ghione, S, Del Seppia, C, Mezzasalma, L, Emdin, M, Luschi, P. Human head exposure to a 37 Hz electromagnetic field: effects on blood pressure, somatosensory perception, and related parameters. Bioelectromagnetics 2004;25:167–75. https://doi.org/10.1002/bem.10180.Search in Google Scholar PubMed
89. Misek, J, Belyaev, I, Jakusova, V, Tonhajzerova, I, Barabas, J, Jakus, J. Heart rate variability affected by radiofrequency electromagnetic field in adolescent students. Bioelectromagnetics 2018;39:277–88. https://doi.org/10.1002/bem.22115.Search in Google Scholar PubMed
90. Wilen, J, Johansson, A, Kalezic, N, Lyskov, E, Sandstrom, M. Psychophysiological tests and provocation subjects with mobile phone related symptoms. Bioelectromagnetics 2006;27:204–14. https://doi.org/10.1002/bem.20195.Search in Google Scholar PubMed
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- Potentially toxic elements in the environment – a review of sources, sinks, pathways and mitigation measures
- Assessment of medical waste generation rate in Viet Nam
- A scoping review of waterborne and water-related disease in the Florida environment from 1999 to 2022
- Effects of man-made electromagnetic fields on heart rate variability parameters of general public: a systematic review and meta-analysis of experimental studies
- Letter to the Editor
- Environmental perspectives of monkeypox virus: correspondence
Articles in the same Issue
- Frontmatter
- Reviews
- E-waste in Vietnam: a narrative review of environmental contaminants and potential health risks
- Knowledge mapping and research trends of the social determinants of health (SDoH): a scientometric analysis
- Hospital wastewater treatment methods and its impact on human health and environments
- Associated health risk assessment due to exposure to BTEX compounds in fuel station workers
- Associations between fine particulate matter and colorectal cancer: a systematic review and meta-analysis
- Health effects of air pollutant mixtures (volatile organic compounds, particulate matter, sulfur and nitrogen oxides) – a review of the literature
- Status and frontier analysis of indoor PM2.5-related health effects: a bibliometric analysis
- Relationship between parental exposure to radiofrequency electromagnetic fields and primarily hematopoietic neoplasms (lymphoma, leukemia) and tumors in the central nervous system in children: a systematic review
- Blood and hair copper levels in childhood autism spectrum disorder: a meta-analysis based on case-control studies
- Cellular and molecular effects of non-ionizing electromagnetic fields
- Benzo (a) pyrene in infant foods: a systematic review, meta-analysis, and health risk assessment
- Relationship between exposure to heavy metals on the increased health risk and carcinogenicity of urinary tract (kidney and bladder)
- The nexus between economic growth, health expenditure, environmental quality: a comparative study for E7 countries
- Potentially toxic elements in the environment – a review of sources, sinks, pathways and mitigation measures
- Assessment of medical waste generation rate in Viet Nam
- A scoping review of waterborne and water-related disease in the Florida environment from 1999 to 2022
- Effects of man-made electromagnetic fields on heart rate variability parameters of general public: a systematic review and meta-analysis of experimental studies
- Letter to the Editor
- Environmental perspectives of monkeypox virus: correspondence