Abstract
In many epidemiological studies mobile phone use has been used as an exposure proxy for radiofrequency electromagnetic field (RF-EMF) exposure. However, RF-EMF exposure assessment from mobile phone use is prone to measurement errors limiting epidemiological research. An often-overlooked aspect is received signal strength levels from base stations and its correlation with mobile phone transmit (Tx) power. The Qualipoc android phone is a tool that provides information on both signal strength and Tx power. The phone produces simultaneous measurements of Received Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Received Signal Code Power (RSCP), and Tx power on the 3G and 4G networks. Measurements taken in the greater Melbourne area found a wide range of signal strength levels. The correlations between multiple signal strength indicators and Tx power were assessed with strong negative correlations found for 3G and 4G data technologies (3G RSSI −0.93, RSCP −0.93; 4G RSSI −0.85, RSRP −0.87). Variations in Tx power over categorical levels of signal strength were quantified and showed large increases in Tx power as signal level decreased. Future epidemiological studies should control for signal strength or factors influencing signal strength to reduce RF-EMF exposure measurement error.
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References
Ahlbom A, Bridges J, de Seze R, Hillert L, Juutilainen J, Mattsson MO, et al. Possible effects of electromagnetic fields (EMF) on human health–opinion of the scientific committee on emerging and newly identified health risks (SCENIHR). Toxicology. 2008;246:248–50.
van Deventer E, van Rongen E, Saunders R. WHO research agenda for radiofrequency fields. Bioelectromagnetics. 2011;32:417–21.
Roser K, Schoeni A, Burgi A, Roosli M. Development of an RF-EMF exposure surrogate for epidemiologic research. Int J Environ Res Public Health. 2015;12:5634–56.
Abramson MJ, Benke GP, Dimitriadis C, Inyang IO, Sim MR, Wolfe RS, et al. Mobile telephone use is associated with changes in cognitive function in young adolescents. Bioelectromagnetics. 2009;30:678–86.
Bhatt CR, Benke G, Smith CL, Redmayne M, Dimitriadis C, Dalecki A, et al. Use of mobile and cordless phones and change in cognitive function: a prospective cohort analysis of Australian primary school children. Environ Health. 2017;16:62.
Redmayne M, Smith CL, Benke G, Croft RJ, Dalecki A, Dimitriadis C, et al. Use of mobile and cordless phones and cognition in Australian primary school children: a prospective cohort study. Environ Health. 2016;15:26.
Roser K, Schoeni A, Roosli M. Mobile phone use, behavioural problems and concentration capacity in adolescents: a prospective study. Int J Hyg Environ Health. 2016;219:759–69.
Sadetzki S, Langer CE, Bruchim R, Kundi M, Merletti F, Vermeulen R, et al. The MOBI-Kids study protocol: challenges in assessing childhood and adolescent exposure to electromagnetic fields from wireless telecommunication technologies and possible association with brain tumor risk. Front Public Health. 2014;2:124.
Schoeni A, Roser K, Roosli M. Memory performance, wireless communication and exposure to radiofrequency electromagnetic fields: a prospective cohort study in adolescents. Environ Int. 2015;85:343–51.
Thomas S, Benke G, Dimitriadis C, Inyang I, Sim MR, Wolfe R, et al. Use of mobile phones and changes in cognitive function in adolescents. Occup Environ Med. 2010;67:861–6.
Cardis E, Deltour I, Vrijheid M, Combalot E, Moissonnier M, Tardy H, et al. Brain tumour risk in relation to mobile telephone use: results of the INTERPHONE international case-control study. Int J Epidemiol. 2010;39:675–94.
Goedhart G, Kromhout H, Wiart J, Vermeulen R. Validating self-reported mobile phone use in adults using a newly developed smartphone application. Occup Environ Med. 2015;72:812–8.
Inyang I, Benke G, Morrissey J, McKenzie R, Abramson M. How well do adolescents recall use of mobile telephones? Results of a validation study. BMC Med Res Methodol. 2009;9:36.
Vrijheid M, Cardis E, Armstrong BK, Auvinen A, Berg G, Blaasaas KG, et al. Validation of short term recall of mobile phone use for the Interphone study. Occup Environ Med. 2006;63:237–43.
Brzozek C, Benke KK, Zeleke BM, Abramson MJ, Benke G. Radiofrequency electromagnetic radiation and memory performance: sources of uncertainty in epidemiological cohort studies. Int J Environ Res Public Health. 2018;15: pii: E592. https://doi.org/10.3390/ijerph15040592
Lönn S, Forssén U, Vecchia P, Ahlbom A, Feychting M. Output power levels from mobile phones in different geographical areas; implications for exposure assessment. Occup Environ Med. 2004;61:769–72.
Hillert L, Ahlbom A, Neasham D, Feychting M, Järup L, Navin R, et al. Call-related factors influencing output power from mobile phones. J Expo Sci Environ Epidemiol. 2006;16:507.
Persson T, Törnevik C, Larsson LE, Lovén J. Output power distributions of terminals in a 3G mobile communication network. Bioelectromagnetics. 2012;33:320–5.
Gati A, Conil E, Wong M-F, Wiart J. Duality between uplink local and downlink whole-body exposures in operating networks. IEEE Trans Electromagn Compat. 2010;52:829–36.
Gati A, Hadjem A, Wong M-F, Wiart J. Exposure induced by WCDMA mobiles phones in operating networks. IEEE Trans Wirel Commun. 2009;8:5723–7.
Joshi P, Agrawal M, Thors B, Colombi D, Kumar A, Törnevik C. Power level distributions of radio base station equipment and user devices in a 3G mobile communication network in India and the impact on assessments of realistic RF EMF exposure. IEEE Access. 2015;3:1051–9.
Joshi P, Colombi D, Thors B, Larsson L-E, Törnevik C. Output power levels of 4G user equipment and implications on realistic RF EMF exposure assessments. IEEE Access. 2017;5:4545–50.
Beekhuizen J, Vermeulen R, van Eijsden M, van Strien R, Burgi A, Loomans E, et al. Modelling indoor electromagnetic fields (EMF) from mobile phone base stations for epidemiological studies. Environ Int. 2014;67:22–6.
Bhatt CR, Redmayne M, Abramson MJ, Benke G. Instruments to assess and measure personal and environmental radiofrequency-electromagnetic field exposures. Australas Phys Eng Sci Med. 2016;39:29–42.
Lauridsen M, Rodriguez I, Mikkelsen LM, Gimenez LC, Mogensen P, eds. Verification of 3G and 4G received power measurements in a crowdsourcing Android app. 2016 IEEE Wireless Communications and Networking Conference; Doha, Qatar: IEEE; 2016. https://doi.org/10.1109/WCNC.2016.7564930
Enami R, Shi Y, Rajan D, Camp J. Pre-crowdsourcing: predicting wireless propagation with phone-based channel quality measurements. Comput Commun. 2018;132:96–110.
Lauridsen M, Kolding T, Pocovi G, Mogensen P, eds. Reducing handover outage for autonomous vehicles with LTE hybrid access. 2018 IEEE International Conference on Communications (ICC); Kansas City, MO, USA: IEEE; 2018. https://doi.org/10.1109/ICC.2018.8422737
Alvarez A, Díaz A, Merino P, Rivas FJ eds. Field measurements of mobile services with Android smartphones. 2012 IEEE Consumer Communications and Networking Conference (CCNC); Las Vegas, NV, USA: IEEE: 2012.
Welch K. Evolving cellular technologies for safer drone operation. Qualcomm, San Diego, CA, USA: Qualcomm 5G White Paper and Presentations, Tech Rep; 2016.
Simpson O, Sun Y. LTE RSRP, RSRQ, RSSNR and local topography profile data for RF propagation planning and network optimization in an urban propagation environment. Data Brief. 2018;21:1724–37.
Beekhuizen J, Kromhout H, Burgi A, Huss A, Vermeulen R. What input data are needed to accurately model electromagnetic fields from mobile phone base stations? J Expo Sci Environ Epidemiol. 2015;25:53–7.
Thielens A, Van den Bossche M, Brzozek C, Bhatt CR, Abramson MJ, Benke G, et al. Representativeness and repeatability of microenvironmental personal and head exposures to radio-frequency electromagnetic fields. Environ Res. 2018;162:81–96.
Acknowledgements
The study was funded by the National Health and Medical Research Council, Australia (grant number APP 545927).
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Michael Abramson owns a small parcel of shares in Telstra, which operates a mobile telephone network in Australia. The other authors declare that they have no conflicts of interest.
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Brzozek, C., Zeleke, B.M., Abramson, M.J. et al. Radiofrequency electromagnetic field exposure assessment: a pilot study on mobile phone signal strength and transmitted power levels. J Expo Sci Environ Epidemiol 31, 62–69 (2021). https://doi.org/10.1038/s41370-019-0178-6
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DOI: https://doi.org/10.1038/s41370-019-0178-6
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