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.

Low-frequency electromagnetic fields have grown exponentially in recent years due to technological development and modernization. The World Health Organization (WHO)/International Agency for Research on Cancer (IARC) has classified radiofrequency electromagnetic fields (RF-EMFs) as possibly carcinogenic to humans (Group 2B), and recent studies have investigated the association between exposure to electromagnetic fields in parents and possible health effects in children, especially the development of tumours of the central nervous system (CNS). The objective of this systematic review was to collate all evidence on the relationship between parental occupational exposure to electromagnetic fields and the development of CNS cancer in children and to evaluate this association. This review was prepared according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Embase, and Web of Science were searched from January 1990 to April 2021. The search was conducted using the following search string: "occupational" AND "child" AND "electromagnetic" AND "cancer". Seventeen articles met our inclusion criteria: 13 case-control studies, two cohort studies, and 2 meta-analyses. Most of the studies showed several methodological weaknesses that limited their results. Due to a lack of consistency regarding the outcome as well as the heterogeneity in the reviewed studies, the body of evidence for the effects of parental exposure to electromagnetic fields is not clear. Methodological heterogeneity in the way that studies were conducted could be responsible for the lack of consistency in the findings. Overall, the body of evidence allows no conclusion on the relationship between parental exposure to electromagnetic fields and the occurrence of CNS tumours in children.

Electromagnetic Fields Exposure Assessment in Europe Utilizing Publicly Available Data.

The ever-increasing use of wireless communication systems during the last few decades has raised concerns about the potential health effects of electromagnetic fields (EMFs) on humans. Safety limits and exposure assessment methods were developed and are regularly updated to mitigate health risks. Continuous radiofrequency EMF monitoring networks and in situ measurement campaigns provide useful information about environmental EMF levels and their variations over time and in different microenvironments. In this study, published data from the five largest monitoring networks and from two extensive in situ measurement campaigns in different European countries were gathered and processed. Median electric field values for monitoring networks across different countries lay in the interval of 0.67-1.51 V/m. The median electric field value across different microenvironments, as evaluated from in situ measurements, varied from 0.10 V/m to 1.42 V/m. The differences between networks were identified and mainly attributed to variations in population density. No significant trends in the temporal evolution of EMF levels were observed. The influences of parameters such as population density, type of microenvironment, and height of measurement on EMF levels were investigated.

Towards Environmental RF-EMF Assessment of mmWave High-Node Density Complex Heterogeneous Environments.

The densification of multiple wireless communication systems that coexist nowadays, as well as the 5G new generation cellular systems advent towards the millimeter wave (mmWave) frequency range, give rise to complex context-aware scenarios with high-node density heterogeneous networks. In this work, a radiofrequency electromagnetic field (RF-EMF) exposure assessment from an empirical and modeling approach for a large, complex indoor setting with high node density and traffic is presented. For that purpose, an intensive and comprehensive in-depth RF-EMF E-field characterization study is provided in a public library study case, considering dense personal mobile communications (5G FR2 @28 GHz) and wireless 802.11ay (@60 GHz) data access services on the mmWave frequency range. By means of an enhanced in-house deterministic 3D ray launching (3D-RL) simulation tool for RF-EMF exposure assessment, different complex heterogenous scenarios of high complexity are assessed in realistic operation conditions, considering different user distributions and densities. The use of directive antennas and MIMO beamforming techniques, as well as all the corresponding features in terms of radio wave propagation, such as the body shielding effect, dispersive material properties of obstacles, the impact of the distribution of scatterers and the associated electromagnetic propagation phenomena, are considered for simulation. Discussion regarding the contribution and impact of the coexistence of multiple heterogeneous networks and services is presented, verifying compliance with the current established international regulation limits with exposure levels far below the aforementioned limits. Finally, the proposed simulation technique is validated with a complete empirical campaign of measurements, showing good agreement. In consequence, the obtained datasets and simulation estimations, along with the proposed RF-EMF simulation tool, could be a reference approach for the design, deployment and exposure assessment of the current and future wireless communication technologies on the mmWave spectrum, where massive high-node density heterogeneous networks are expected.

Tracking Devices for Pets: Health Risk Assessment for Exposure to Radiofrequency Electromagnetic Fields.

Every year, approximately 3% of cats and dogs are lost. In addition to passive methods for identifying pets, radiofrequency tracking devices (TDs) are available. These TDs can track a pet's geographic position, which is transmitted by radio frequencies. The health risk to the animals from continuous exposure to radiofrequency electromagnetic fields (RF-EMFs) was reviewed. Fourteen out of twenty-one commercially available TDs use 2G, 3G, or 4G mobile networks, and the others work with public frequencies, WLAN, Bluetooth, etc. The exposure of pets to RF-EMFs was assessed, including ambient exposure (radios, TVs, and base stations of mobile networks), exposure from indoor devices (DECT, WLAN, Bluetooth, etc.), and the exposure from TDs. The exposure levels of the three areas were found to be distinctly below the International Commission on Non-Ionising Radiation Protection (ICNIRP) reference levels, which assure far-reaching protection from adverse health effects. The highest uncertainty regarding the exposure of pets was related to that caused by indoor RF-emitting devices using WLAN and DECT. This exposure can be limited considerably through a reduction in the exposure time and an increase in the distance between the animal and the RF-emitting device. Even though the total RF-EMF exposure level experienced by pets was found to be below the reference limits, recommendations were derived to reduce potential risks from exposure to TDs and indoor devices.

Personal Exposure Assessment to Wi-Fi Radiofrequency Electromagnetic Fields in Mexican Microenvironments.

In recent years, personal exposure to Radiofrequency Electromagnetic Fields (RF-EMF) has substantially increased, and most studies about RF-EMF with volunteers have been developed in Europe. To the best of our knowledge, this is the first study carried out in Mexico with personal exposimeters. The main objective was to measure personal exposure to RF-EMF from Wireless Fidelity or wireless Internet connection (Wi-Fi) frequency bands in Tamazunchale, San Luis Potosi, Mexico, to compare results with maximum levels permitted by international recommendations and to find if there are differences in the microenvironments subject to measurements. The study was conducted with 63 volunteers in different microenvironments: home, workplace, outside, schools, travel, and shopping. The mean minimum values registered were 146.5 µW/m2 in travel from the Wi-Fi 2G band and 116.8 µW/m2 at home from the Wi-Fi 5G band, and the maximum values registered were 499.7 µW/m2 and 264.9 µW/m2 at the workplace for the Wi-Fi 2G band and the Wi-Fi 5G band, respectively. In addition, by time period and type of day, minimum values were registered at nighttime, these values being 129.4 µW/m2 and 93.9 µW/m2, and maximum values were registered in the daytime, these values being 303.1 µW/m2 and 168.3 µW/m2 for the Wi-Fi 2G and Wi-Fi 5G bands, respectively. In no case, values exceeded limits established by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). Of the study participants (n = 63), a subgroup (n = 35) answered a survey on risk perception. According to these results, the Tamazunchale (Mexico) population is worried about this situation in comparison with several European cities; however, the risk perception changes when they are informed about the results for the study.

Spatial and temporal assessment of radiofrequency electromagnetic fields emitted by smart meters and smart meter banks in urban environments.

This paper describes radiofrequency (RF) electromagnetic field (EMF) measurements in the vicinity of single and banks of advanced metering infrastructure (AMI) smart meters. The measurements were performed in a meter testing and distribution facility as well as in-situ at five urban locations. The measurements consisted of gauging the RF environment at the place of assessment, evaluating the worst-case electric-field levels at various positions around the assessed AMI meter configuration (spatial assessment), which ranged from a single meter to a bank of 81 m, and calculating the duty cycle of the system, i.e. the fraction of time that the AMI meters were actually transmitting (12-h temporal assessment). Both in-situ and in the meter facility, the maximum field levels at 0.3 m from the meter configurations were 10-13 V/m for a single meter and 18-38 V/m for meter banks with 20-81 m. Furthermore, 6-min average duty cycles of 0.01% (1 m) up to 13% (81-m bank) were observed. Next, two general statistical models (one for a single meter and one for a meter bank) were constructed to predict the electric-field strength as a function of distance to any configuration of the assessed AMI meters. For all scenarios, the measured exposure levels (at a minimum distance of 0.3 m) were well below the maximum permissible exposure limits issued by the International Commission on Non-Ionizing Radiation Protection (ICNIRP), the U.S. Federal Communications Commission (FCC), and the Institute of Electrical and Electronics Engineers (IEEE). Indeed, the worst-case time-average exposure level at a distance of 0.3 m from an AMI installation was 5.39% of the FCC/IEEE and 9.43% of the ICNIRP reference levels.

A real-world quality assessment study in six ExpoM-RF measurement devices.

Exposimeters measuring radiofrequency electromagnetic fields (RF-EMF) are commonly used to assess personal exposure to RF-EMF in real-life environments. They are usually calibrated in an anechoic chamber using single, well-defined signals such as the center frequency of each band, and standardized orientations, but it is not clear how different devices compare in the real environment where complex mixtures of signals from all directions are present. We thus tested the comparability of six ExpoM-RF exposimeters before and after calibration in an anechoic chamber by varying their position and orientation while repeatedly measuring 15 microenvironments (9 walking routes, 4 tram routes and 2 bus routes) on 6 different days. We modelled the geometric mean levels of RF-EMF as a function of orientation, position, device ID, whether the device was recently calibrated, correcting for the microenvironment in which each measurement took place. We found that systematic differences introduced by device ID, calibration, day of the week, orientation and position are relatively small compared to exposure differences between microenvironments. Any corrections (if desired) should include both device ID and calibration session, but would have a small impact considering the negligible differences between devices. This supports the validity of previous exposure measurement studies relying on ExpoM-RF devices, which did not correct for device ID. We further found that summarizing the exposure per microenvironment as geometric means results in better models than arithmetic means and medians, and recommend that further exposure assessment studies report observed levels as geometric means.

Ecological momentary assessment study of exposure to radiofrequency electromagnetic fields and non-specific physical symptoms with self-declared electrosensitives.

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.

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.

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.

Characterisation of personal exposure to environmental radiofrequency electromagnetic fields in Albacete (Spain) and assessment of risk perception.

In the last decades, exposure to radiofrequency electromagnetic fields (RF-EMF) has substantially increased as new wireless technologies have been introduced. Society has become more concerned about the possible effects of RF-EMF on human health in parallel to the increase in their exposure. The appearance of personal exposimeters opens up wide-ranging research possibilities. Despite studies having characterised personal exposure to RF-EMF, part of the population is still worried, to the extent that psychogenic diseases ("nocebo" effect) appear, and patients suffer. It could be interesting to share personal exposure results with the population to better understand and promote public health. The main objective was to characterise personal exposure to environmental RF-EMF in Albacete (166,000 inhabitants, SE Spain), and assess the effect of sharing the results of the study on participants' risk perception. Measurements were taken by a personal Satimo EME SPY 140 exposimeter, which was programmed every 10 s for 24 h. To measure personal exposure to RF-EMF, we worked with 75 volunteers. Their personal exposure, 14 microenvironments in the city, e.g., home, outdoors, work, etc., and possible time differences were analysed. After participating in the study, 35 participants completed a questionnaire about their RF-EMF risk perception, which was also answered by a control sample to compare the results (N = 36). The total average exposure of 14 bands was 37.7 µW/m2, and individual ranges fell between 0.2 µW/m2, recorded in TV4&5, and a maximum of 264.7 µW/m2 in DECT. For Friday, we recorded a mean of 53.9 µW/m2 as opposed to 23.4 µW/m2 obtained on Saturday. The recorded night-time value was 27.5 µW/m2 versus 43.8 µW/m2 recorded in the daytime. The mean personal exposure value also showed differences between weekdays and weekend days, with 39.7 µW/m2 and 26.9 µW/m2, respectively. The main source that contributed to the mean total personal exposure was enhanced cordless telecommunications (DECT) with 50.2%, followed by mobile phones with 18.4% and mobile stations with 11.0% (GSM, DCS and UMTS), while WiFi signals gave 12.5%. In the analysed microenvironments, the mean exposure of homes and workplaces was 34.3 µW/m2 and 55.2 µW/m2, respectively. Outdoors, the mean value was 34.2 µW/m2 and the main sources were DECT, WiFi and mobile phone stations, depending on the place. The risk perception analysis found that 54% of the participants perceived that RF-EMF were less dangerous than before participating in the study, while 43% reported no change in their perceptions. Only 9% of the volunteers who received information about their measurements after the study assessed the possible RF-EMF risk with a value over or equal to 4 (on a scale from 1 to 5) versus 39% of the non-participant controls. We conclude that personal exposure to RF-EMF fell well below the limits recommended by ICNIRP and showed wide temporal and spatial variability. The main exposure sources were DECT, followed by mobile phones and WiFi. Sharing exposure results with participants lowered their risk perception.

Estimation of TETRA radio use in the Airwave Health Monitoring Study of the British police forces.

BACKGROUND: The Airwave Health Monitoring Study aims to investigate the possible long-term health effects of Terrestrial Trunked Radio (TETRA) use among the police forces in Great Britain. Here, we investigate whether objective data from the network operator could be used to correct for misreporting in self-reported data and expand the radio usage availability in our cohort. METHODS: We estimated average monthly usage of personal radio in the 12 months prior to enrolment from a missing value imputation model and evaluated its performance against objective and self-reported data. Factors associated with TETRA radio usage variables were investigated using Chi-square tests and analysis of variance. RESULTS: The imputed data were better correlated with objective than self-reported usage (Spearman correlation coefficient = 0.72 vs. 0. 52 and kappa 0.56 [95% confidence interval 0.55, 0.56] vs. 0.46 [0.45, 0.47]), although the imputation model tended to under-estimate use for higher users. Participants with higher personal radio usage were more likely to be younger, men vs. women and officer vs. staff. The median average monthly usage level for the entire cohort was estimated to be 29.3 min (95% CI: [7.2, 66.6]). CONCLUSION: The availability of objective personal radio records for a large proportion of users allowed us to develop a robust imputation model and hence obtain personal radio usage estimates for ~50,000 participants. This substantially reduced exposure misclassification compared to using self-reported data and will allow us to carry out analyses of TETRA usage for the entire cohort in future work.

Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure.

As both the environment and telecommunications networks are inherently dynamic, our exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) at an arbitrary location is not at all constant in time. In this study, more than a year's worth of measurement data collected in a fixed low-cost exposimeter network distributed over an urban environment was analysed and used to build, for the first time, a full spatio-temporal surrogate model of outdoor exposure to downlink Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) signals. Though no global trend was discovered over the measuring period, the difference in measured exposure between two instances could reach up to 42dB (a factor 12,000 in power density). Furthermore, it was found that, taking into account the hour and day of the measurement, the accuracy of the surrogate model in the area under study was improved by up to 50% compared to models that neglect the daily temporal variability of the RF signals. However, further study is required to assess the extent to which the results obtained in the considered environment can be extrapolated to other geographic locations.

Assessment of radiofrequency electromagnetic field exposure from personal measurements considering the body shadowing effect in Korean children and parents.

We aimed to assess the personal radiofrequency electromagnetic field (RF-EMF) exposure levels of children and adults through their activities, with consideration to the body shadowing effect. We recruited 50 child-adult pairs, living in Seoul, Cheonan, and Ulsan, South Korea. RF-EMF measurements were performed between September and December 2016, using a portable exposure meter tailored to capture 14 Korean radiofrequency (RF) bands ranging from 87.5 to 5875MHz. The participants carried the device for 48h and kept a time-activity diary using a smartphone application in flight mode. To enhance accuracy of the exposure assessment, the body shadowing effect was compensated during the statistical analysis with the measured RF-EMF exposure. The compensation was conducted using the hybrid model that represents the decrease of the exposure level due to the body shadowing effect. A generalized linear mixed model was used to compare the RF-EMF exposure levels by subjects and activities. The arithmetic (geometric) means of the total power density were 174.9 (36.6) µW/m2 for all participants, 226.9 (44.6) for fathers, 245.4 (44.8) for mothers, and 116.2 (30.1) for children. By compensating for the body shadowing effect, the total RF-EMF exposure increased marginally, approximately 1.4 times. Each frequency band contribution to total RF-EMF exposure consisted of 76.7%, 2.4%, 9.9%, 5.0%, 3.3%, and 2.6% for downlink, uplink, WiFi, FM Radio, TV, and WiBro bands, respectively. Among the three regions, total RF-EMF exposure was highest in Seoul, and among the activities, it was highest in the metro, followed by foot/bicycle, bus/car, and outside. The contribution of base-station exposure to total RF-EMF exposure was the highest both in parents and children. Total and base-station RF-EMF exposure levels in Korea were higher than those reported in European countries.

Assessment of human body influence on exposure measurements of electric field in indoor enclosures.

Personal exposure meters (PEMs) used for measuring exposure to electromagnetic fields (EMF) are typically used in epidemiological studies. As is well known, these measurement devices cause a perturbation of real EMF exposure levels due to the presence of the human body in the immediate proximity. This paper aims to model the alteration caused by the body shadow effect (BSE) in motion conditions and in indoor enclosures at the Wi-Fi frequency of 2.4 GHz. For this purpose, simulation techniques based on ray-tracing have been carried out, and their results have been verified experimentally. A good agreement exists between simulation and experimental results in terms of electric field (E-field) levels, and taking into account the cumulative distribution function (CDF) of the spatial distribution of amplitude. The Kolmogorov-Smirnov (KS) test provides a P-value greater than 0.05, in fact close to 1. It has been found that the influence of the presence of the human body can be characterized as an angle of shadow that depends on the dimensions of the indoor enclosure. The CDFs show that the E-field levels in indoor conditions follow a lognormal distribution in the absence of the human body and under the influence of BSE. In conclusion, the perturbation caused by BSE in PEMs readings cannot be compensated for by correction factors. Although the mean value is well adjusted, BSE causes changes in CDF that would require improvements in measurement protocols and in the design of measuring devices to subsequently avoid systematic errors.

Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling.

In this study, a novel methodology is proposed to create heat maps that accurately pinpoint the outdoor locations with elevated exposure to radiofrequency electromagnetic fields (RF-EMF) in an extensive urban region (or, hotspots), and that would allow local authorities and epidemiologists to efficiently assess the locations and spectral composition of these hotspots, while at the same time developing a global picture of the exposure in the area. Moreover, no prior knowledge about the presence of radiofrequency radiation sources (e.g., base station parameters) is required. After building a surrogate model from the available data using kriging, the proposed method makes use of an iterative sampling strategy that selects new measurement locations at spots which are deemed to contain the most valuable information-inside hotspots or in search of them-based on the prediction uncertainty of the model. The method was tested and validated in an urban subarea of Ghent, Belgium with a size of approximately 1 km2. In total, 600 input and 50 validation measurements were performed using a broadband probe. Five hotspots were discovered and assessed, with maximum total electric-field strengths ranging from 1.3 to 3.1 V/m, satisfying the reference levels issued by the International Commission on Non-Ionizing Radiation Protection for exposure of the general public to RF-EMF. Spectrum analyzer measurements in these hotspots revealed five radiofrequency signals with a relevant contribution to the exposure. The radiofrequency radiation emitted by 900 MHz Global System for Mobile Communications (GSM) base stations was always dominant, with contributions ranging from 45% to 100%. Finally, validation of the subsequent surrogate models shows high prediction accuracy, with the final model featuring an average relative error of less than 2dB (factor 1.26 in electric-field strength), a correlation coefficient of 0.7, and a specificity of 0.96.