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Korkmaz E, Aerts S, Coesoij R, Bhatt CR, Velghe M, Colussi L, Land D, Petroulakis N, Spirito M, Bolte J. A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications. ENVIRONMENTAL RESEARCH 2024; 260:119524. [PMID: 38972338 DOI: 10.1016/j.envres.2024.119524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/16/2024] [Accepted: 06/30/2024] [Indexed: 07/09/2024]
Abstract
This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as "sensors" or "sensor nodes", that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.
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Affiliation(s)
- Erdal Korkmaz
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands.
| | - Sam Aerts
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands
| | - Richard Coesoij
- Delft University of Technology, Department of Microelectronics, 2628 CN, Delft, The Netherlands
| | - Chhavi Raj Bhatt
- Australian Radiation Protection and Nuclear Safety Agency, VIC 3085, Yallambie, Australia
| | - Maarten Velghe
- National Institute for Public Health and the Environment, Centre for Sustainability, Environment and Health, 3720 BA, Bilthoven, The Netherlands
| | - Loek Colussi
- Dutch Authority for Digital Infrastructure, 9700 AL, Groningen, The Netherlands
| | - Derek Land
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands
| | - Nikolaos Petroulakis
- Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013, Heraklion, Greece
| | - Marco Spirito
- Delft University of Technology, Department of Microelectronics, 2628 CN, Delft, The Netherlands
| | - John Bolte
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands; National Institute for Public Health and the Environment, Centre for Sustainability, Environment and Health, 3720 BA, Bilthoven, The Netherlands
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2
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Rocha L, Ferreira S, Vivaldini KCT, Araújo J, Batalha I. Ziwi: indoor and outdoor planning network—framework to collection, modeling and network structure based on computational optimization and measurements. Soft comput 2022; 27:6761-6781. [PMID: 36475039 PMCID: PMC9716530 DOI: 10.1007/s00500-022-07682-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/18/2022] [Indexed: 12/03/2022]
Abstract
Society is increasingly connected, utilizing more data that demands greater capacity and better channel quality. Furthermore, wireless networks are being inserted into the population's daily lives. Therefore, solutions capable of transferring a high volume of data are increasingly needed. In this context, we present a framework that aims to network planning through data collection, modeling, and routers optimization in the environment. Ziwi framework can simulate wireless networks in indoor and outdoor environments with the main classical propagation models, obtain and calculate metrics and performance parameters. It is possible to measure data by cell phone and send it to the website quickly. Furthermore, it can model the data and compare with different propagation models. Also, optimize them using a genetic algorithm or permutation, choosing whether or not to consider sockets to turn on the routers and how many routers are needed to place in the environment. In addition, have a virtual reality environment aiming at greater interactivity with the data. We analyzed framework results comparing with Close-In propagation model, free space model, and statically using the root mean square error metric. Measurements were made in a real environment using the Ziwi mobile application, inserting data captured on Ziwi website to validate the framework.
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López I, Rivera M, Félix N, Maestú C. It is mandatory to review environmental radiofrequency electromagnetic field measurement protocols and exposure regulations: An opinion article. Front Public Health 2022; 10:992645. [PMID: 36353271 PMCID: PMC9639819 DOI: 10.3389/fpubh.2022.992645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 10/12/2022] [Indexed: 01/26/2023] Open
Affiliation(s)
- Isabel López
- Departamento de Fotónica y Bioingeniería (TFB), Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain,Laboratorio de Bioelectromagnetismo, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
| | - Marco Rivera
- Laboratorio de Bioelectromagnetismo, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
| | - Nazario Félix
- Laboratorio de Bioelectromagnetismo, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain,Departamento de Arquitectura y Tecnología de Sistemas Informáticos (DATSI), Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Madrid, Spain
| | - Ceferino Maestú
- Departamento de Fotónica y Bioingeniería (TFB), Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain,Laboratorio de Bioelectromagnetismo, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain,CIBER–BBN Centro de Investigación Biomédica en Red, Madrid, Spain,*Correspondence: Ceferino Maestú
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Instruments to measure environmental and personal radiofrequency-electromagnetic field exposures: an update. Phys Eng Sci Med 2022; 45:687-704. [PMID: 35737222 PMCID: PMC9448713 DOI: 10.1007/s13246-022-01146-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 05/26/2022] [Indexed: 11/03/2022]
Abstract
Modern human populations are exposed to anthropogenic sources of radiofrequency-electromagnetic fields (RF-EMFs), primarily to telecommunication and broadcasting technologies. As a result, ongoing concerns from some members of the public have arisen regarding potential health effects following RF-EMF exposures. In order to monitor human RF-EMF exposures and investigate potential health effects, an objective assessment of RF-EMF exposures is necessary. Accurate dosimetry is essential for any investigation of potential associations between RF-EMF exposure and health effects in human populations. This review updates state-of-the-art knowledge of currently available RF-EMF exposure assessment tools applicable in human epidemiological studies. These tools cater for assessing RF-EMF exposures in human environments; through mobile phone-based tools or other standalone tools. RF-EMF exposure assessment has been significantly improved through the application of some of these tools in recent years.
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5
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Boussad Y, Chen XL, Legout A, Chaintreau A, Dabbous W. Longitudinal study of exposure to radio frequencies at population scale. ENVIRONMENT INTERNATIONAL 2022; 162:107144. [PMID: 35339930 DOI: 10.1016/j.envint.2022.107144] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 02/03/2022] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Abstract
Evaluating exposure to radio frequencies (RF) at population-scale is important for conducting sound epidemiological studies about possible health impact of RF radiations. Numerous studies reported population exposure to RF radiations used in wireless telecommunication technologies, but used very small population samples. In this context, the real exposure of the population at scale remains poorly understood. Here, to the best of our knowledge, we report the largest crowd-based measurement of population exposure to RF produced by cellular antennas, Wi-Fi access points, and Bluetooth devices for 254,410 unique users in 13 countries from January 2017 to December 2020. First, we present methods to assess the population exposure to RF radiations using smartphone measurements obtained using the ElectroSmart Android app. Then, we use these methods to evaluate and characterize the evolution of RF exposure. We show that total exposure has been multiplied by 2.3 in the four-year period considered, with Wi-Fi as the largest contributor. The cellular exposure levels are orders of magnitude lower than regulation limits and are not correlated to national regulation policies. The population tends to be more exposed at home; for half of the study subjects, personal Wi-Fi routers and Bluetooth devices contributed to more than 50% of their total exposure. In this work, we showcase how crowdsource-based data allow large-scale and long-term assessment of population exposure to RF radiations.
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Affiliation(s)
- Yanis Boussad
- Université Côte d'Azur, Inria. Sophia Antipolis, 06902, France
| | | | - Arnaud Legout
- Université Côte d'Azur, Inria. Sophia Antipolis, 06902, France.
| | | | - Walid Dabbous
- Université Côte d'Azur, Inria. Sophia Antipolis, 06902, France
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Rivera González MX, Félix González N, López I, Ochoa Zambrano JS, Miranda Martínez A, Maestú Unturbe C. Compact Exposimeter Device for the Characterization and Recording of Electromagnetic Fields from 78 MHz to 6 GHz with Several Narrow Bands (300 kHz). SENSORS 2021; 21:s21217395. [PMID: 34770707 PMCID: PMC8588337 DOI: 10.3390/s21217395] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 10/31/2021] [Accepted: 11/04/2021] [Indexed: 12/23/2022]
Abstract
A novel compact device with spectrum analyzer characteristics has been designed, which allows the measuring of the maximum power received in multiple narrow frequency bands of 300 kHz, recording the entire spectrum from 78 MHz to 6 GHz; the device is capable of measuring the entire communications spectrum and detecting multiple sources of electromagnetic fields using the same communications band. The proposed device permits the evaluation of the cross-talk effect that, in conventional exposimeters, generates a mistake estimation of electromagnetic fields. The device was calibrated in an anechoic chamber for far-fields and was validated against a portable spectrum analyzer in a residential area. A strong correlation between the two devices with a confidence higher than 95% was obtained; indicating that the device could be considered as an important tool for electromagnetic field studies.
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Affiliation(s)
- Marco Xavier Rivera González
- Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; (N.F.G.); (I.L.); (A.M.M.); (C.M.U.)
- Correspondence:
| | - Nazario Félix González
- Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; (N.F.G.); (I.L.); (A.M.M.); (C.M.U.)
| | - Isabel López
- Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; (N.F.G.); (I.L.); (A.M.M.); (C.M.U.)
| | | | - Andrés Miranda Martínez
- Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; (N.F.G.); (I.L.); (A.M.M.); (C.M.U.)
| | - Ceferino Maestú Unturbe
- Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; (N.F.G.); (I.L.); (A.M.M.); (C.M.U.)
- Networking Research Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
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7
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Mahmoud NM, Gomaa RS, Salem AE. Activation of liver X receptors ameliorates alterations in testicular function in rats exposed to electromagnetic radiation. ALEXANDRIA JOURNAL OF MEDICINE 2021. [DOI: 10.1080/20905068.2021.1884333] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Affiliation(s)
| | - Randa Salah Gomaa
- Medical Physiology Department, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Amal Elsayd Salem
- Pharmacology Department, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
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8
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Brzozek C, Zeleke BM, Abramson MJ, Benke KK, Benke G. Radiofrequency electromagnetic field exposure assessment: a pilot study on mobile phone signal strength and transmitted power levels. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2021; 31:62-69. [PMID: 31641274 DOI: 10.1038/s41370-019-0178-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 07/22/2019] [Accepted: 08/26/2019] [Indexed: 06/10/2023]
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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Affiliation(s)
- Christopher Brzozek
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
| | - Berihun M Zeleke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Michael J Abramson
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Kurt K Benke
- School of Engineering, University of Melbourne, Parkville, VIC, Australia
- Centre for AgriBioscience, AgriBio, 5 Ring Rd, Bundoora, VIC, Australia
| | - Geza Benke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
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9
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Radio Base Stations and Electromagnetic Fields: GIS Applications and Models for Identifying Possible Risk Factors and Areas Exposed. Some Exemplifications in Rome. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2020. [DOI: 10.3390/ijgi10010003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This paper—which is contextualized in the discussion on the methodological pluralism and the main topics of medical geography, the complexity theory in geographies of health, the remaking of medical geography and ad hoc systems of data elaboration—focuses on radio base stations (RBSs) as sources of electromagnetic fields, to provide GIS applications and simplifying-prudential models that are able to identify areas that could potentially be exposed to hazard. After highlighting some specific aspects regarding RBSs and their characteristics and summarizing the results of a number of studies concerning the possible effects of electromagnetic fields on health, we have taken an area of north-east Rome with a high population and building density as a case study, and we have provided some methodological and applicative exemplifications for different situations and types of antennas. Through specific functionalities and criteria, drawing inspiration from a precautionary principle, these exemplifications show some particular cases in order to support: possible risk factor identification, surveillance and spatial analysis; correlation analysis between potential risk factors and outbreak of diseases and symptoms; measurement campaigns in heavily exposed areas and buildings; education policies and prevention actions. From an operative viewpoint, we have: conducted some field surveys and recorded data and images with specific geotechnological and geomatics instruments; retraced the routes by geobrowsers and basemaps and harmonized and joined up the materials in a GIS environment; used different functions to define, on aero-satellite images, concentric circular buffer zones starting from each RBS, and geographically and geometrically delimited the connected areas subject to high and different exposure levels; produced digital applications and tested prime three-dimensional models, in addition to a video from a bird’s eye view perspective, able to show the buildings in the different buffer zones and which are subject to a hazard hierarchy due to exposure to an RBS. A similar GIS-based model—reproposable with methodological adjustments to other polluting sources—can make it possible to conceive a dynamic and multiscale digital system functional in terms of strategic planning, decision-making and public health promotion in a performant digital health information system.
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Šuka D, Pejović P, Simić-Pejović M. APPLICATION OF TIME-AVERAGED AND INTEGRAL-BASED MEASURE FOR MEASUREMENT RESULTS VARIABILITY REDUCTION IN GSM/DCS/UMTS SYSTEMS. RADIATION PROTECTION DOSIMETRY 2019; 187:191-214. [PMID: 31297514 PMCID: PMC7203997 DOI: 10.1093/rpd/ncz154] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 05/22/2019] [Indexed: 06/10/2023]
Abstract
Since EMF levels from wireless telecommunication networks are non-stationary and exhibit large temporal variations, the use of continuous measurements during extended periods (preferably 24 h or longer) with a data-logging system is required. Because of the short-term variations of E field, the 6-min measurements and 6-min averaged results to obtain the mean level strength at a given place appear to be dependent on the time of measurements during the day. This paper presents a new (integral-based) measure to evaluate electromagnetic exposure. The new measure is a pure physical descriptor of the amount of exposed energy density (a parameter accumulated from instantaneous power density values in time). To confirm previous observations, continuous measurements with personal exposure metre were recorded 24 h a day for two weeks at every location in urban area, 14 different locations in total. Additionally, to check temporal variations and repeatability of exposure assessment, a week of prolonged measurements was taken 6 months later, making in total three weeks of measurements at 2 locations. Day-to-day repeatability of RF-EMF exposure was analysed through the time-averaged and integral-based measure. The analysis is based on approximately 5.1 million data samples (1.7 million for each band). The ratio between the maximum and minimum instantaneous (maximum and minimum 6-min averaged) E field values during the day could reach up to 25 dB (20 dB). Therefore, great variability in the results may occur. By applying the 24 h time-averaged and integral-based measure on a 24 h data set of measurements, the variability of daily exposure could stay within ±20% of the week mean level obtained either with the time-averaged or integral-based measure. Both, the time-averaged E field and integral-based power density exposures of the general public in all locations were found to be well below the general public exposure limits of the ICNIRP guidelines.
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Affiliation(s)
- Darko Šuka
- University of East Sarajevo, Faculty of Electrical Engineering, East Sarajevo, Bosnia and Herzegovina
| | - Predrag Pejović
- University of Belgrade, School of Electrical Engineering, Belgrade, Serbia
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Bolte JFB, Clahsen S, Vercruijsse W, Houtveen JH, Schipper CMA, van Kamp I, Bogers R. Ecological momentary assessment study of exposure to radiofrequency electromagnetic fields and non-specific physical symptoms with self-declared electrosensitives. ENVIRONMENT INTERNATIONAL 2019; 131:104948. [PMID: 31288182 DOI: 10.1016/j.envint.2019.104948] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 06/18/2019] [Accepted: 06/19/2019] [Indexed: 05/23/2023]
Abstract
The main objective of the study is to determine if non-specific physical symptoms (NSPS) in people with self-declared sensitivity to radiofrequency electromagnetic fields (RF EMF) can be explained (across subjects) by exposure to RF EMF. Furthermore, we pioneered whether analysis at the individual level or at the group level may lead to different conclusions. By our knowledge, this is the first longitudinal study exploring the data at the individual level. A group of 57 participants was equipped with a measurement set for five consecutive days. The measurement set consisted of a body worn exposimeter measuring the radiofrequency electromagnetic field in twelve frequency bands used for communication, a GPS logger, and an electronic diary giving cues at random intervals within a two to three hour interval. At every cue, a questionnaire on the most important health complaint and nine NSPS had to be filled out. We analysed the (time-lagged) associations between RF-EMF exposure in the included frequency bands and the total number of NSPS and self-rated severity of the most important health complaint. The manifestation of NSPS was studied during two different time lags - 0-1 h, and 1-4 h - after exposure and for different exposure metrics of RF EMF. The exposure was characterised by exposure metrics describing the central tendency and the intermittency of the signal, i.e. the time-weighted average exposure, the time above an exposure level or the rate of change metric. At group level, there was no statistically significant and relevant (fixed effect) association between the measured personal exposure to RF EMF and NSPS. At individual level, after correction for multiple testing and confounding, we found significant within-person associations between WiFi (the self-declared most important source) exposure metrics and the total NSPS score and severity of the most important complaint in one participant. However, it cannot be ruled out that this association is explained by residual confounding due to imperfect control for location or activities. Therefore, the outcomes have to be regarded very prudently. The significant associations were found for the short and the long time lag, but not always concurrently, so both provide complementary information. We also conclude that analyses at the individual level can lead to different findings when compared to an analysis at group level.
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Affiliation(s)
- John F B Bolte
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands; Smart Sensor Systems Research Group, Faculty of Technology, Innovation and Society, The Hague University of Applied Sciences (THUAS), Rotterdamseweg 137, 2628 AL Delft, the Netherlands.
| | - Sander Clahsen
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands; Institute for Risk Assessment Sciences (IRAS), Utrecht University, Yalelaan 2, 3584 CM Utrecht, the Netherlands
| | - Wendy Vercruijsse
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands
| | - Jan H Houtveen
- Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, the Netherlands
| | - C Maarten A Schipper
- Department of Statistics, Informatics and Mathematical Modelling, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands
| | - Irene van Kamp
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands
| | - Rik Bogers
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands
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Jalilian H, Eeftens M, Ziaei M, Röösli M. Public exposure to radiofrequency electromagnetic fields in everyday microenvironments: An updated systematic review for Europe. ENVIRONMENTAL RESEARCH 2019; 176:108517. [PMID: 31202043 DOI: 10.1016/j.envres.2019.05.048] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 05/29/2019] [Accepted: 05/30/2019] [Indexed: 06/09/2023]
Abstract
Communication technologies are rapidly changing and this may affect public exposure to radiofrequency electromagnetic fields (RF-EMF). This systematic review of literature aims to update a previous review on public everyday RF-EMF exposure in Europe, which covered publications until 2015. From 144 eligible records identified by means of a systematic search in PubMed, Embase and Web of Knowledge databases, published between May 2015 and 1 July 2018, 26 records met the inclusion criteria. We extracted quantitative data on public exposure in different indoors, outdoors and transport environments. The data was descriptively analyzed with respect to the exposure patterns between different types of environments. Mean RF-EMF exposure in homes, schools and offices were between 0.04 and 0.76 V/m. Mean outdoor exposure values ranged from 0.07 to 1.27 V/m with downlink signals from mobile phone base stations being the most relevant contributor. RF-EMF levels tended to increase with increasing urbanity. Levels in public transport (bus, train and tram) and cars were between 0.14 and 0.69 V/m. The highest levels, up to 1.97 V/m, were measured in public transport stations with downlink as the most relevant contributor. In line with previous studies, RF-EMF exposure levels were highest in the transportation systems followed by outdoor and private indoor environments. This review does not indicate a noticeable increase in everyday RF-EMF exposure since 2012 despite increasing use of wireless communication devices.
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Affiliation(s)
- Hamed Jalilian
- Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Marloes Eeftens
- Swiss Tropical and Public Health Institute, Socinstrasse 57, P.O. Box, CH-4002, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Mansour Ziaei
- School of Health and Nutrition, Bushehr University of Medical Sciences, Bushehr, Iran.
| | - Martin Röösli
- Swiss Tropical and Public Health Institute, Socinstrasse 57, P.O. Box, CH-4002, Basel, Switzerland; University of Basel, Basel, Switzerland
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Marynchenko L, Nizhelska A, Shirinyan A, Makara V. Prospects of Using Biological Test-Systems for Evaluation of Effects of Electromagnetic Fields. INNOVATIVE BIOSYSTEMS AND BIOENGINEERING 2019. [DOI: 10.20535/ibb.2019.3.2.169259] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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14
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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. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16132428. [PMID: 31288491 PMCID: PMC6651811 DOI: 10.3390/ijerph16132428] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 06/30/2019] [Accepted: 07/02/2019] [Indexed: 11/19/2022]
Abstract
Previous epidemiological studies on health effects of radiation exposure from mobile phones have produced inconsistent results. This may be due to experimental difficulties and various sources of uncertainty, such as statistical variability, measurement errors, and model uncertainty. An analytical technique known as the Monte Carlo simulation provides an additional approach to analysis by addressing uncertainty in model inputs using error probability distributions, rather than point-source data. The aim of this investigation was to demonstrate using Monte Carlo simulation of data from the ExPOSURE (Examination of Psychological Outcomes in Students using Radiofrequency dEvices) study to quantify uncertainty in the output of the model. Data were collected twice, approximately one year apart (between 2011 and 2013) for 412 primary school participants in Australia. Monte Carlo simulation was used to estimate output uncertainty in the model due to uncertainties in the call exposure data. Multiple linear regression models evaluated associations between mobile phone calls with cognitive function and found weak evidence of an association. Similar to previous longitudinal analysis, associations were found for the Go/No Go and Groton maze learning tasks, and a Stroop time ratio. However, with the introduction of uncertainty analysis, the results were closer to the null hypothesis.
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Chiaramello E, Bonato M, Fiocchi S, Tognola G, Parazzini M, Ravazzani P, Wiart J. Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:E955. [PMID: 30884917 PMCID: PMC6466609 DOI: 10.3390/ijerph16060955] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/05/2019] [Accepted: 03/14/2019] [Indexed: 12/24/2022]
Abstract
Exposure to radiofrequency (RF) electromagnetic fields (EMFs) in indoor environments depends on both outdoor sources such as radio, television and mobile phone antennas and indoor sources, such as mobile phones and wireless communications applications. Establishing the levels of exposure could be challenging due to differences in the approaches used in different studies. The goal of this study is to present an overview of the last ten years research efforts about RF EMF exposure in indoor environments, considering different RF-EMF sources found to cause exposure in indoor environments, different indoor environments and different approaches used to assess the exposure. The highest maximum mean levels of the exposure considering the whole RF-EMF frequency band was found in offices (1.14 V/m) and in public transports (0.97 V/m), while the lowest levels of exposure were observed in homes and apartments, with mean values in the range 0.13⁻0.43 V/m. The contribution of different RF-EMF sources to the total level of exposure was found to show slightly different patterns among the indoor environments, but this finding has to be considered as a time-dependent picture of the continuous evolving exposure to RF-EMF.
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Affiliation(s)
- Emma Chiaramello
- Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni IEIIT CNR, 20133 Milano, Italy.
| | - Marta Bonato
- Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni IEIIT CNR, 20133 Milano, Italy.
- Dipartimento di Elettronica, Informazione e Bioingegneria DEIB, Politecnico di Milano, 20133 Milano, Italy.
| | - Serena Fiocchi
- Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni IEIIT CNR, 20133 Milano, Italy.
| | - Gabriella Tognola
- Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni IEIIT CNR, 20133 Milano, Italy.
| | - Marta Parazzini
- Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni IEIIT CNR, 20133 Milano, Italy.
| | - Paolo Ravazzani
- Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni IEIIT CNR, 20133 Milano, Italy.
| | - Joe Wiart
- Télécom ParisTech, LTCI University Paris Saclay, Chair C2M, 75013 Paris, France.
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Eeftens M, Struchen B, Roser K, Zahner M, Fröhlich J, Röösli M. Dealing with crosstalk in electromagnetic field measurements of portable devices. Bioelectromagnetics 2018; 39:529-538. [DOI: 10.1002/bem.22142] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Accepted: 08/03/2018] [Indexed: 11/06/2022]
Affiliation(s)
- Marloes Eeftens
- Department of Epidemiology and Public Health; Swiss Tropical and Public Health Institute; Basel Switzerland
- University of Basel; Basel Switzerland
| | - Benjamin Struchen
- Department of Epidemiology and Public Health; Swiss Tropical and Public Health Institute; Basel Switzerland
- University of Basel; Basel Switzerland
| | - Katharina Roser
- Department of Epidemiology and Public Health; Swiss Tropical and Public Health Institute; Basel Switzerland
- University of Basel; Basel Switzerland
- University of Lucerne; Lucerne Switzerland
| | - Marco Zahner
- Fields at Work GmbH; Zurich Switzerland
- Institute of Electromagnetic Fields (IEF); ETH Zurich; Zurich Switzerland
| | | | - Martin Röösli
- Department of Epidemiology and Public Health; Swiss Tropical and Public Health Institute; Basel Switzerland
- University of Basel; Basel Switzerland
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Bhatt CR, Redmayne M, Abramson MJ, Sim MR, Brzozek C, Zeleke BM, Benke G. Estimating transmitted power density from mobile phone: an epidemiological pilot study with a software modified phone. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2018; 41:985-991. [DOI: 10.1007/s13246-018-0699-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 10/10/2018] [Indexed: 01/29/2023]
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18
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Zeleke BM, Brzozek C, Bhatt CR, Abramson MJ, Croft RJ, Freudenstein F, Wiedemann P, Benke G. Personal Exposure to Radio Frequency Electromagnetic Fields among Australian Adults. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15102234. [PMID: 30321997 PMCID: PMC6211035 DOI: 10.3390/ijerph15102234] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 10/03/2018] [Accepted: 10/08/2018] [Indexed: 11/16/2022]
Abstract
The measurement of personal exposure to radiofrequency electromagnetic fields (RF-EMFs) is important for epidemiological studies. RF-EMF exposure can be measured using personal exposimeters that register RF-EMFs over a wide range of frequency bands. This study aimed to measure and describe personal RF-EMF exposure levels from a wide range of frequency bands. Measurements were recorded from 63 participants over an average of 27.4 (±4.5) hours. RF-EMF exposure levels were computed for each frequency band, as well as from downlink (RF from mobile phone base station), uplink (RF from mobile phone handsets), broadcast, and Wi-Fi. Participants had a mean (±SD) age of 36.9 ± 12.5 years; 66.7% were women; and almost all (98.2%) from urban areas. A Wi-Fi router at home was reported by 61 participants (96.8%), with 38 (61.2%) having a Wi-Fi enabled smart TV. Overall, 26 (41.3%) participants had noticed the existence of a mobile phone base station in their neighborhood. On average, participants estimated the distance between the base station and their usual residence to be about 500 m. The median personal RF-EMF exposure was 208 mV/m. Downlink contributed 40.4% of the total RF-EMF exposure, followed by broadcast (22.4%), uplink (17.3%), and Wi-Fi (15.9%). RF-EMF exposure levels on weekdays were higher than weekends (p < 0.05). Downlink and broadcast are the main contributors to total RF-EMF personal exposure. Personal RF-EMF exposure levels vary according to day of the week and time of day.
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Affiliation(s)
- Berihun M Zeleke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
| | - Christopher Brzozek
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
| | - Chhavi Raj Bhatt
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
- Monash University Endocrine Surgery Unit, Alfred Hospital, 55 Commercial Rd, Melbourne, VIC 3004, Australia.
- Monash Emergency Service, Monash Health, Dandenong Hospital, 135 David Street, Melbourne, VIC 3175, Australia.
| | - Michael J Abramson
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
| | - Rodney J Croft
- Australian Centre for Electromagnetic Bioeffects Research, Illawarra Health and Medical Research Institute, School of Psychology, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.
| | - Frederik Freudenstein
- Australian Centre for Electromagnetic Bioeffects Research, Illawarra Health and Medical Research Institute, School of Psychology, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.
| | - Peter Wiedemann
- Australian Centre for Electromagnetic Bioeffects Research, Illawarra Health and Medical Research Institute, School of Psychology, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.
| | - Geza Benke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
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Rufo M, Antolín A, Paniagua JM, Jiménez A. Optimization and comparison of three spatial interpolation methods for electromagnetic levels in the AM band within an urban area. ENVIRONMENTAL RESEARCH 2018; 162:219-225. [PMID: 29407756 DOI: 10.1016/j.envres.2018.01.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 01/12/2018] [Accepted: 01/15/2018] [Indexed: 06/07/2023]
Abstract
A comparative study was made of three methods of interpolation - inverse distance weighting (IDW), spline and ordinary kriging - after optimization of their characteristic parameters. These interpolation methods were used to represent the electric field levels for three emission frequencies (774kHz, 900kHz, and 1107kHz) and for the electrical stimulation quotient, QE, characteristic of complex electromagnetic environments. Measurements were made with a spectrum analyser in a village in the vicinity of medium-wave radio broadcasting antennas. The accuracy of the models was quantified by comparing their predictions with levels measured at the control points not used to generate the models. The results showed that optimizing the characteristic parameters of each interpolation method allows any of them to be used. However, the best results in terms of the regression coefficient between each model's predictions and the actual control point field measurements were for the IDW method.
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Affiliation(s)
- Montaña Rufo
- Department of Applied Physics, School of Technology, University of Extremadura, Avda. de la Universidad s/n, 10003 Caceres, Spain.
| | - Alicia Antolín
- Department of Applied Physics, School of Technology, University of Extremadura, Avda. de la Universidad s/n, 10003 Caceres, Spain
| | - Jesús M Paniagua
- Department of Applied Physics, School of Technology, University of Extremadura, Avda. de la Universidad s/n, 10003 Caceres, Spain
| | - Antonio Jiménez
- Department of Applied Physics, School of Technology, University of Extremadura, Avda. de la Universidad s/n, 10003 Caceres, Spain
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Radiofrequency Electromagnetic Radiation and Memory Performance: Sources of Uncertainty in Epidemiological Cohort Studies. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15040592. [PMID: 29587425 PMCID: PMC5923634 DOI: 10.3390/ijerph15040592] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 03/21/2018] [Accepted: 03/23/2018] [Indexed: 12/23/2022]
Abstract
Uncertainty in experimental studies of exposure to radiation from mobile phones has in the past only been framed within the context of statistical variability. It is now becoming more apparent to researchers that epistemic or reducible uncertainties can also affect the total error in results. These uncertainties are derived from a wide range of sources including human error, such as data transcription, model structure, measurement and linguistic errors in communication. The issue of epistemic uncertainty is reviewed and interpreted in the context of the MoRPhEUS, ExPOSURE and HERMES cohort studies which investigate the effect of radiofrequency electromagnetic radiation from mobile phones on memory performance. Research into this field has found inconsistent results due to limitations from a range of epistemic sources. Potential analytic approaches are suggested based on quantification of epistemic error using Monte Carlo simulation. It is recommended that future studies investigating the relationship between radiofrequency electromagnetic radiation and memory performance pay more attention to treatment of epistemic uncertainties as well as further research into improving exposure assessment. Use of directed acyclic graphs is also encouraged to display the assumed covariate relationship.
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21
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Nemati E, Batteate C, Jerrett M. Opportunistic Environmental Sensing with Smartphones: a Critical Review of Current Literature and Applications. Curr Environ Health Rep 2017; 4:306-318. [PMID: 28879432 DOI: 10.1007/s40572-017-0158-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
PURPOSE OF REVIEW This review sought to summarize recent literature and applications of passive, or opportunistic, mobile sensing in the fields of exposure science in built environment settings; highlight innovative opportunistic sensing systems; and analyze their functionality, significant features, and limitations. RECENT FINDINGS Fifty-two papers related to opportunistic environmental sensing from 2009 or later were related to this review, of which 27 were included. An array of applications have emerged in environmental monitoring, employing anywhere from one to six of the phone's on-board sensors. The viability of an application is determined by several key factors: the number and quality of sensors on-board the smartphone; power and processing demand; algorithm complexity; data security; mobile network coverage; reliance on external data sources; minimum number of users required; and degree of user burden when using the application. Some factors are universal, while others are more context-specific. Future research should assess sensing applications based on these factors.
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Affiliation(s)
- Ebrahim Nemati
- Department of Electrical Engineering, UCLA ER Lab, Los Angeles, CA, USA
| | - Christina Batteate
- UCLA Center for Occupational and Environmental Health, Los Angeles, CA, USA
| | - Michael Jerrett
- UCLA Center for Occupational and Environmental Health, Los Angeles, CA, USA.
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, 650 Charles E. Young Drive, South 56-060 CHS, Los Angeles, CA, 90095, USA.
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Bhatt CR, Redmayne M, Billah B, Abramson MJ, Benke G. Radiofrequency-electromagnetic field exposures in kindergarten children. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2017; 27:497-504. [PMID: 27759027 DOI: 10.1038/jes.2016.55] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2016] [Accepted: 08/06/2016] [Indexed: 06/06/2023]
Abstract
The aim of this study was to assess environmental and personal radiofrequency-electromagnetic field (RF-EMF) exposures in kindergarten children. Ten children and 20 kindergartens in Melbourne, Australia participated in personal and environmental exposure measurements, respectively. Order statistics of RF-EMF exposures were computed for 16 frequency bands between 88 MHz and 5.8 GHz. Of the 16 bands, the three highest sources of environmental RF-EMF exposures were: Global System for Mobile Communications (GSM) 900 MHz downlink (82 mV/m); Universal Mobile Telecommunications System (UMTS) 2100MHz downlink (51 mV/m); and GSM 900 MHz uplink (45 mV/m). Similarly, the three highest personal exposure sources were: GSM 900 MHz downlink (50 mV/m); UMTS 2100 MHz downlink, GSM 900 MHz uplink and GSM 1800 MHz downlink (20 mV/m); and Frequency Modulation radio, Wi-Fi 2.4 GHz and Digital Video Broadcasting-Terrestrial (10 mV/m). The median environmental exposures were: 179 mV/m (total all bands), 123 mV/m (total mobile phone base station downlinks), 46 mV/m (total mobile phone base station uplinks), and 16 mV/m (Wi-Fi 2.4 GHz). Similarly, the median personal exposures were: 81 mV/m (total all bands), 62 mV/m (total mobile phone base station downlinks), 21 mV/m (total mobile phone base station uplinks), and 9 mV/m (Wi-Fi 2.4 GHz). The measurements showed that environmental RF-EMF exposure levels exceeded the personal RF-EMF exposure levels at kindergartens.
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Affiliation(s)
- Chhavi Raj Bhatt
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, Melbourne, Victoria, Australia
| | - Mary Redmayne
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, Melbourne, Victoria, Australia
| | - Baki Billah
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Michael J Abramson
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, Melbourne, Victoria, Australia
| | - Geza Benke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, Melbourne, Victoria, Australia
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Bhatt CR, Benke G, Smith CL, Redmayne M, Dimitriadis C, Dalecki A, Macleod S, Sim MR, Croft RJ, Wolfe R, Kaufman J, Abramson MJ. Use of mobile and cordless phones and change in cognitive function: a prospective cohort analysis of Australian primary school children. Environ Health 2017. [PMID: 28629417 PMCID: PMC5477374 DOI: 10.1186/s12940-017-0250-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
BACKGROUND Some previous studies have suggested an association between children's use of mobile phones (MPs)/cordless phones (CPs) and development of cognitive function. We evaluated possible longitudinal associations between the use of MPs and CPs in a cohort of primary school children and effects on their cognitive function. METHODS Data on children's socio-demographics, use of MPs and CPs, and cognitive function were collected at baseline (2010-2012) and follow-up (2012-2013). Cognitive outcomes were evaluated with the CogHealth™ test battery and Stroop Color-Word test. The change in the number of MP/CP voice calls weekly from baseline to follow-up was dichotomized: "an increase in calls" or a "decrease/no change in calls". Multiple linear regression analyses, adjusting for confounders and clustering by school, were performed to evaluate the associations between the change in cognitive outcomes and change in MP and CP exposures. RESULTS Of 412 children, a larger proportion of them used a CP (76% at baseline and follow-up), compared to a MP (31% at baseline and 43% at follow-up). Of 26 comparisons of changes in cognitive outcomes, four demonstrated significant associations. The increase in MP usage was associated with larger reduction in response time for response inhibition, smaller reduction in the number of total errors for spatial problem solving and larger increase in response time for a Stroop interference task. Except for the smaller reduction in detection task accuracy, the increase in CP usage had no effect on the changes in cognitive outcomes. CONCLUSION Our study shows that a larger proportion of children used CPs compared to MPs. We found limited evidence that change in the use of MPs or CPs in primary school children was associated with change in cognitive function.
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Affiliation(s)
- Chhavi Raj Bhatt
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Geza Benke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Catherine L. Smith
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Mary Redmayne
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Christina Dimitriadis
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Anna Dalecki
- Australian Centre for Electromagnetic Bioeffects Research, School of Psychology, University of Wollongong, Wollongong, NSW 2522 Australia
| | - Skye Macleod
- Australian Centre for Electromagnetic Bioeffects Research, School of Psychology, University of Wollongong, Wollongong, NSW 2522 Australia
| | - Malcolm R. Sim
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Rodney J. Croft
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
- Australian Centre for Electromagnetic Bioeffects Research, School of Psychology, University of Wollongong, Wollongong, NSW 2522 Australia
| | - Rory Wolfe
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
| | - Jordy Kaufman
- School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122 Australia
| | - Michael J. Abramson
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, VIC 3004 Melbourne, Australia
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Bhatt CR, Thielens A, Billah B, Redmayne M, Abramson MJ, Sim MR, Vermeulen R, Martens L, Joseph W, Benke G. Assessment of personal exposure from radiofrequency-electromagnetic fields in Australia and Belgium using on-body calibrated exposimeters. ENVIRONMENTAL RESEARCH 2016; 151:547-563. [PMID: 27588949 DOI: 10.1016/j.envres.2016.08.022] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2016] [Revised: 08/18/2016] [Accepted: 08/18/2016] [Indexed: 06/06/2023]
Abstract
The purposes of this study were: i) to demonstrate the assessment of personal exposure from various RF-EMF sources across different microenvironments in Australia and Belgium, with two on-body calibrated exposimeters, in contrast to earlier studies which employed single, non-on-body calibrated exposimeters; ii) to systematically evaluate the performance of the exposimeters using (on-body) calibration and cross-talk measurements; and iii) to compare the exposure levels measured for one site in each of several selected microenvironments in the two countries. A human subject took part in an on-body calibration of the exposimeter in an anechoic chamber. The same subject collected data on personal exposures across 38 microenvironments (19 in each country) situated in urban, suburban and rural regions. Median personal RF-EMF exposures were estimated: i) of all microenvironments, and ii) across each microenvironment, in two countries. The exposures were then compared across similar microenvironments in two countries (17 in each country). The three highest median total exposure levels were: city center (4.33V/m), residential outdoor (urban) (0.75V/m), and a park (0.75V/m) [Australia]; and a tram station (1.95V/m), city center (0.95V/m), and a park (0.90V/m) [Belgium]. The exposures across nine microenvironments in Melbourne, Australia were lower than the exposures across corresponding microenvironments in Ghent, Belgium (p<0.05). The personal exposures across urban microenvironments were higher than those for rural or suburban microenvironments. Similarly, the exposure levels across outdoor microenvironments were higher than those for indoor microenvironments.
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Affiliation(s)
- Chhavi Raj Bhatt
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Arno Thielens
- Department of Information Technology, Ghent University/iMinds, Technologiepark - Zwijnaarde 15, Ghent B-9052, Belgium.
| | - Baki Billah
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Mary Redmayne
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Michael J Abramson
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Malcolm R Sim
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), Division Environmental Epidemiology, Utrecht University, Yalelaan 2, 3584 CM Utrecht, The Netherlands; Julius Centre for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands; Imperial College, Department of Epidemiology and Public Health, London, United Kingdom.
| | - Luc Martens
- Department of Information Technology, Ghent University/iMinds, Technologiepark - Zwijnaarde 15, Ghent B-9052, Belgium.
| | - Wout Joseph
- Department of Information Technology, Ghent University/iMinds, Technologiepark - Zwijnaarde 15, Ghent B-9052, Belgium.
| | - Geza Benke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
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25
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Bolte JFB. Lessons learnt on biases and uncertainties in personal exposure measurement surveys of radiofrequency electromagnetic fields with exposimeters. ENVIRONMENT INTERNATIONAL 2016; 94:724-735. [PMID: 27356850 DOI: 10.1016/j.envint.2016.06.023] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Revised: 06/16/2016] [Accepted: 06/17/2016] [Indexed: 06/06/2023]
Abstract
Personal exposure measurements of radio frequency electromagnetic fields are important for epidemiological studies and developing prediction models. Minimizing biases and uncertainties and handling spatial and temporal variability are important aspects of these measurements. This paper reviews the lessons learnt from testing the different types of exposimeters and from personal exposure measurement surveys performed between 2005 and 2015. Applying them will improve the comparability and ranking of exposure levels for different microenvironments, activities or (groups of) people, such that epidemiological studies are better capable of finding potential weak correlations with health effects. Over 20 papers have been published on how to prevent biases and minimize uncertainties due to: mechanical errors; design of hardware and software filters; anisotropy; and influence of the body. A number of biases can be corrected for by determining multiplicative correction factors. In addition a good protocol on how to wear the exposimeter, a sufficiently small sampling interval and sufficiently long measurement duration will minimize biases. Corrections to biases are possible for: non-detects through detection limit, erroneous manufacturer calibration and temporal drift. Corrections not deemed necessary, because no significant biases have been observed, are: linearity in response and resolution. Corrections difficult to perform after measurements are for: modulation/duty cycle sensitivity; out of band response aka cross talk; temperature and humidity sensitivity. Corrections not possible to perform after measurements are for: multiple signals detection in one band; flatness of response within a frequency band; anisotropy to waves of different elevation angle. An analysis of 20 microenvironmental surveys showed that early studies using exposimeters with logarithmic detectors, overestimated exposure to signals with bursts, such as in uplink signals from mobile phones and WiFi appliances. Further, the possible corrections for biases have not been fully applied. The main findings are that if the biases are not corrected for, the actual exposure will on average be underestimated.
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Affiliation(s)
- John F B Bolte
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, The Netherlands; Faculty of Technology, Innovation and Society, The Hague University of Applied Sciences, The Netherlands.
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Bhatt CR, Thielens A, Redmayne M, Abramson MJ, Billah B, Sim MR, Vermeulen R, Martens L, Joseph W, Benke G. Measuring personal exposure from 900MHz mobile phone base stations in Australia and Belgium using a novel personal distributed exposimeter. ENVIRONMENT INTERNATIONAL 2016; 92-93:388-97. [PMID: 27136346 DOI: 10.1016/j.envint.2016.03.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Revised: 03/23/2016] [Accepted: 03/24/2016] [Indexed: 05/16/2023]
Abstract
The aims of this study were to: i) measure personal exposure in the Global System for Mobile communications (GSM) 900MHz downlink (DL) frequency band with two systems of exposimeters, a personal distributed exposimeter (PDE) and a pair of ExpoM-RFs, ii) compare the GSM 900MHz DL exposures across various microenvironments in Australia and Belgium, and iii) evaluate the correlation between the PDE and ExpoM-RFs measurements. Personal exposure data were collected using the PDE and two ExpoM-RFs simultaneously across 34 microenvironments (17 each in Australia and Belgium) located in urban, suburban and rural areas. Summary statistics of the electric field strengths (V/m) were computed and compared across similar microenvironments in Australia and Belgium. The personal exposures across urban microenvironments were higher than those in the rural or suburban microenvironments. Likewise, the exposure levels across the outdoor were higher than those for indoor microenvironments. The five highest median exposure levels were: city centre (0.248V/m), bus (0.124V/m), railway station (0.105V/m), mountain/forest (rural) (0.057V/m), and train (0.055V/m) [Australia]; and bicycle (urban) (0.238V/m), tram station (0.238V/m), city centre (0.156V/m), residential outdoor (urban) (0.139V/m) and park (0.124V/m) [Belgium]. Exposures in the GSM900 MHz frequency band across most of the microenvironments in Australia were significantly lower than the exposures across the microenvironments in Belgium. Overall correlations between the PDE and the ExpoM-RFs measurements were high. The measured exposure levels were far below the general public reference levels recommended in the guidelines of the ICNIRP and the ARPANSA.
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Affiliation(s)
- Chhavi Raj Bhatt
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Arno Thielens
- Department of Information Technology, Ghent University/iMinds, Gaston Crommenlaan 8 Box 201, Ghent B-9050, Belgium.
| | - Mary Redmayne
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Michael J Abramson
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Baki Billah
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Malcolm R Sim
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), Division Environmental Epidemiology, Utrecht University, Yalelaan 2, 3584 CM Utrecht, The Netherlands; Julius Centre for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands; Imperial College, Department of Epidemiology and Public Health, London, United Kingdom.
| | - Luc Martens
- Department of Information Technology, Ghent University/iMinds, Gaston Crommenlaan 8 Box 201, Ghent B-9050, Belgium.
| | - Wout Joseph
- Department of Information Technology, Ghent University/iMinds, Gaston Crommenlaan 8 Box 201, Ghent B-9050, Belgium.
| | - Geza Benke
- Centre for Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Melbourne, Australia.
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Redmayne M, Smith CL, Benke G, Croft RJ, Dalecki A, Dimitriadis C, Kaufman J, Macleod S, Sim MR, Wolfe R, Abramson MJ. Use of mobile and cordless phones and cognition in Australian primary school children: a prospective cohort study. Environ Health 2016; 15:26. [PMID: 26892106 PMCID: PMC4759913 DOI: 10.1186/s12940-016-0116-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Accepted: 02/05/2016] [Indexed: 05/20/2023]
Abstract
BACKGROUND Use of mobile (MP) and cordless phones (CP) is common among young children, but whether the resulting radiofrequency exposure affects development of cognitive skills is not known. Small changes have been found in older children. This study focused on children's exposures to MP and CP and cognitive development. The hypothesis was that children who used these phones would display differences in cognitive function compared to those who did not. METHODS We recruited 619 fourth-grade students (8-11 years) from 37 schools around Melbourne and Wollongong, Australia. Participants completed a short questionnaire, a computerised cognitive test battery, and the Stroop colour-word test. Parents completed exposure questionnaires on their child's behalf. Analysis used multiple linear regression. The principal exposure-metrics were the total number of reported MP and CP calls weekly categorised into no use ('None'); use less than or equal to the median amount ('Some'); and use more than the median ('More'). The median number of calls/week was 2.5 for MP and 2.0 for CP. RESULTS MP and CP use for calls was low; and only 5 of 78 comparisons of phone use with cognitive measures were statistically significant. The reaction time to the response-inhibition task was slower in those who used an MP 'More' compared to the 'Some' use group and non-users. For CP use, the response time to the Stroop interference task was slower in the 'More' group versus the 'Some' group, and accuracy was worse in visual recognition and episodic memory tasks and the identification task. In an additional exploratory analysis, there was some evidence of a gender effect on mean reaction times. The highest users for both phone types were girls. CONCLUSIONS Overall, there was little evidence cognitive function was associated with CP and MP use in this age group. Although there was some evidence that effects of MP and CP use on cognition may differ by gender, this needs further exploration. CP results may be more reliable as parents estimated children's phone use and the CPs were at home; results for CP use were broadly consistent with our earlier study of older children.
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Affiliation(s)
- Mary Redmayne
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
| | - Catherine L Smith
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
| | - Geza Benke
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
| | - Rodney J Croft
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
- School of Psychology, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia.
| | - Anna Dalecki
- School of Psychology, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia.
| | - Christina Dimitriadis
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
| | - Jordy Kaufman
- Swinburne University of Technology, John Street, Hawthorn, VIC, 3122, Australia.
| | - Skye Macleod
- School of Psychology, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia.
| | - Malcolm R Sim
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
| | - Rory Wolfe
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
| | - Michael J Abramson
- Population Health Research on Electromagnetic Energy (PRESEE), School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Melbourne, 3004, Australia.
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