Speaker 1: Ken Karipidis

Australian Radiation Protection and Nuclear Safety Agency (ARPANSA), Australia

Associate Professor Ken Karipidis is the assistant director of Health Impact Assessment at the Australian Radiation Protection and Nuclear Safety Agency where he is heavily involved in the scientific and regulatory aspects of radiation protection from non-ionising radiation sources. He also provides expert advice and information on radiation protection to government, the public and other relevant stakeholders and leads the development of policy initiatives and best practice. Ken has a number of eminent appointments including being an adjunct Associate Professor at Monash University as well as Swinburne University of Technology and is the Vice Chair of the International Commission on Non-Ionizing Radiation Protection.

Title:

The WHO Systematic Review on Cancer: What is it and What did it find?

Summary:

Radiofrequency (RF) electromagnetic fields (EMF) are mainly used for telecommunications purposes such as radio and television broadcasting, mobile telephony, and other wireless communications. Concern has been raised regarding possible adverse effects to human health, such as cancer, from RF-EMF exposure, recently from emerging technologies like the 5G mobile network. It is therefore crucial to perform a health risk assessment to support decision-makers and the general public.

The World Health Organization (WHO) has an ongoing project to assess potential health effects of exposure to RF-EMF in the general and working population. The WHO is currently developing a monograph as part of its Environmental Health Criteria (EHC) series which will assess the available evidence on RF EMF and health. The monograph will be informed, among other things, by a set of commissioned systematic reviews related to several priority health outcomes, including cancer investigated in human observational studies.

The current systematic review included 86 cohort and case-control studies investigating RF EMF exposure and various cancers. The meta-analysis yielded no associations between RF EMF exposure from mobile phones, telecommunications antennas or occupational exposure and the various cancers investigated. The certainty in the evidence was variable across the specific RF EMF exposure sources and various cancers investigated.

While narrative reviews can be valuable for providing expert opinions and discussing complex topics, systematic reviews offer a more rigorous, transparent, and comprehensive synthesis of existing evidence, making them preferable for formulating evidence-based decisions in research, and policy-making for topics like the health risk assessment of RF EMF.

Speaker 2: Maria Feychting

Karolinska Institutet, Institute of Environmental Medicine, Sweden

Maria Feychting is Professor of Epidemiology at Karolinska Institutet, Institute of Environmental Medicine, Stockholm, Sweden, and Head of the Unit of Epidemiology. Her research is focused on risk factors for chronic diseases, primarily cancer. She has a specific interest in childhood cancer and adult brain tumors, both in terms of risk factors such as environmental and genetic factors, and factors affecting survival. She has conducted research on potential health effects of non-ionizing radiation since the late 1980s, and she is the PI for the Swedish parts of the COSMOS study, the Cefalo study, the Sotan study and the Interphone study. She has published ~ 400 original articles, brief communications, review articles, editorials, letters, book chapters and reports, with ~ 300 listed in PubMed (WoS H-index: 62, Google Scholar H-index: 84). She has been invited expert in several national and international health risk assessment expert groups. She was member of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) during 2008 to 2020 and vice chairman 2012-2020. ICNIRP is an independent body suggesting science-based guidelines for non-ionizing radiation protection, which are used by many countries. 

Title: 

RF EXPOSURE AND CANCER: EPIDEMIOLOGICAL PERSPECTIVES – IMPLICATIONS OF DIFFERENT STUDY DESIGNS

Summary:

Over the last decades, considerable scientific efforts have been made to determine whether exposure to radiofrequency electromagnetic fields (RF-EMF) below guideline levels may affect cancer risk. The widespread use of handheld mobile phones in the general population, that developed from none to essentially 100% in less than two decades, makes this a potentially very important public health issue. The research field has to a large extent been driven by epidemiological studies, some of which reported increased risks of brain tumours, while others found no associations. Notably, raised risk estimates have been reported in some studies with a case-control design, while the few cohort studies found no increased risks. Case-control studies with retrospectively collected exposure information are subject to several sources of bias which may have influenced their findings, such as differential recall bias and selection bias from non-participation. These biases are especially problematic for case-control studies of brain tumours, as the disease often affects memory, progress rapidly and has a poor prognosis. Cohort studies with prospectively collected exposure information are not affected by differential recall or selection bias but may instead be subject to non-differential exposure misclassification, especially if they lack quantitative exposure data. The COSMOS cohort study was initiated to address these limitations, through prospective collection of exposure information to achieve the same level of detail in exposure data as the case-control studies, but without differential recall bias because all participants are blind to their disease status when the information is collected (brain tumours will occur in the future), and with no selection bias as all participants can be followed in nationwide well-established cancer registers and population registers. This presentation will discuss the theoretical principles of epidemiological case-control and cohort designs and highlight similarities and differences, particularly with regard to exposure misclassification and selection bias, and implications for the interpretation of findings and future prospects.