Christopher Brzozek

Objective: Due to the negative connotations around radiation, there is a great deal of angst in the community regarding radiation exposure and health; especially electromagnetic radiation (EMR) sources such as powerlines, mobile phone towers and the rollout of the 5G network. As such, it is important for health authorities to provide the public with information and assurances regarding radiation safety. The Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) set up community engagement programs to address community concerns. Type of program or service: From 2003 until April 2022, ARPANSA operated a Health Complaints Register, which collected reports of health complaints from members of the public related to possible EMR exposures. Methods: Collected data was used to produce annual statistical summaries on the nature and level of complaints received. Since 2016, ARPANSA has also run the Talk to a Scientist program, which allows the public to communicate directly with scientists on issues about radiation exposure, health and protection in Australia. Data is collected on the type of radiation and radiation source. Results: There was a low level of interest in the Register, with only 180 reports received over the duration of its operation. Smart meters were the most common source of EMR exposure reported to be responsible for adverse health effects. The most common adverse health effect reported was headaches. The Register was closed in April 2022 due to a lack of interest. In contrast, the Talk to a Scientist program has responded to 6546 enquiries since 2016, most of which have been on EMR sources and the success of the Talk to a Scientist program, which rendered the Register obsolete. Lessons learnt: The EMR Health Complaints Register never received much interest from the public, potentially due to a perceived lack of engagement with authorities. The Talk to a Scientist program, which facilitated direct interaction with subject matter experts, has been much more successful in engaging with the public and addressing community concerns on radiation safety.

In September 2020, Choi et al. published their paper “Cellular Phone Use and Risk of Tumors: Systematic Review and Meta-Analysis” in the International Journal of Environmental Research and Public Health

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.

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.

The aims of this study were to evaluate the weekly and annual cumulative radiofrequency-electromagnetic field (RF-EMF) exposure attributed to mobile phone (MP) use, and assess whether a novel app (Quanta Monitor™) could be employed in a small human sample to characterise the RF-EMF exposures associated with the use of MPs. Ten participants provided their two months’ daily objective data on their MP exposures (i.e. transmitted and received power densities) attributed to different modes of MP usage such as cellular calls, cellular data and Wi-Fi. The results demonstrated that total transmitted power density (cellular phone calls, data and Wi-Fi surfing) could be many orders of magnitude higher than that from the total received power density. Of the total transmitted power density, cellular data use contributed the largest portion. Our study showed that Quanta Monitor™ could be employed in prospective assessment of exposures to MPs in epidemiological studies.