Relationship between radiofrequency-electromagnetic radiation from cellular phones and brain tumor: Meta-analyses using various proxies for RF-EMR exposure-outcome assessment

Relationship between radiofrequency-electromagnetic radiation from cellular phones and brain tumor:  Meta-analyses using various proxies for RF-EMR exposure-outcome assessment
saferemr.com, 10 October 2024

On 10 October 2024, the journal Environmental Health published a systematic review and meta-analytic study on cell phone use and brain tumor risk by Moon et al. (2024). The study found significantly elevated risks for three types of brain tumors when examining tumors on the side of the head where cell phones were held and for heavy, long-term cell phone use.

Six other systematic reviews and meta-analyses of case-control studies published in peer-reviewed journals since 2016 have also also found significant associations between heavy, long-term cellphone use and brain tumor risk (Wang & Guo, 2016; Bortkiewicz et al., 2017; Carlberg & Hardell, 2017; Prasad et al., 2017, Yang et al., 2017; Choi et al., 2020).

These seven peer-reviewed meta-analytic studies contradict the conclusion of the recent WHO systematic review conducted by Karipidis et al. (2024) that there is no evidence cell phone use causes brain cancer. To learn about serious problems with the WHO systematic reviews on the health effects of radiofrequency radiation see:

WHO Radiofrequency EMF Health Risk Assessment Monograph (EHC series)

Wang & Guo (2016). Meta-analysis of association between mobile phone use and glioma risk. J Cancer Research Therapy http://bit.ly/2o1dVcn

Bortkiewicz et al (2017). Mobile phone use and risk of intracranial tumors and salivary gland tumors - A meta-analysis. Int J Occ Med Envir Health. http://bit.ly/2nVJC5d

Carlberg & Hardell (2017). Evaluation of mobile phone and cordless phone use and glioma risk using the Bradford Hill viewpoints from 1965 on association or causation. Biomed Res Int. http://bit.ly/2WwBX1K

Prasad et al (2017). Mobile phone use and risk of brain tumours: a systematic review of association between study quality, source of funding, and research outcomes. Neurol Sci. http://bit.ly/2Xxp83P

Yang et al (2017). Mobile phone use and glioma risk: A systematic review and meta-analysis. PLOS One. https://bit.ly/3U0kafd

Choi, Moskowitz, et al (2020). Cellular phone use and risk of tumors: Systematic review and meta-analysis. Int J Envir Res Public Health. https://doi.org/10.3390/ijerph17218079.

Moon et al. (2020). Relationship between radiofrequency-electromagnetic radiation from cellular phones and brain tumor: meta-analyses using various proxies for RF-EMR exposure-outcome assessment. Environ Health. https://doi.org/10.1186/s12940-024-01117-8.

Karipidis et al. (2020). The effect of exposure to radiofrequency fields on cancer risk in the general and working population: A systematic review of human observational studies - Part I: Most researched outcomes. Environ Int. https://doi.org/10.1016/j.envint.2024.108983

Moon J, Kwon J, Mun Y. Relationship between radiofrequency-electromagnetic radiation from cellular phones and brain tumor: meta-analyses using various proxies for RF-EMR exposure-outcome assessment. Environ Health 23, 82 (2024). https://doi.org/10.1186/s12940-024-01117-8.

Abstract

Introduction The authors conducted meta-analyses regarding the association between cellular and mobile phone use and brain tumor development by applying various radiofrequency-electromagnetic radiation (RF-EMR) exposure subcategories. With changing patterns of mobile phone use and rapidly developing Wireless Personal Area Network (WPAN) technology (such as Bluetooth), this study will provide insight into the importance of more precise exposure subcategories for RF-EMR.

Methods The medical librarian searched MEDLINE (PubMed), EMBASE, and the Cochrane Library until 16 December 2020.

Results In these meta-analyses, 19 case-control studies and five cohort studies were included. Ipsilateral users reported a pooled odds ratio (OR) of 1.40 (95% CI 1.21–1.62) compared to non-regular users. Users with years of use over 10 years reported a pooled OR of 1.27 (95% CI 1.08–1.48). When stratified by each type of brain tumor, only meningioma (OR 1.20 (95% CI 1.04–1.39)), glioma (OR 1.45 (95% CI 1.16–1.82)), and malignant brain tumors (OR 1.93 (95% CI 1.55–2.39)) showed an increased OR with statistical significance for ipsilateral users. For users with years of use over 10 years, only glioma (OR 1.32 (95% CI 1.01–1.71)) showed an increased OR with statistical significance. When 11 studies with an OR with cumulative hours of use over 896 h were synthesized, the pooled OR was 1.59 (95% CI 1.25–2.02). When stratified by each type of brain tumor, glioma, meningioma, and acoustic neuroma reported the pooled OR of 1.66 (95% CI 1.13–2.44), 1.29 (95% CI 1.08–1.54), and 1.84 (95% CI 0.78–4.37), respectively. For each individual study that considered cumulative hours of use, the highest OR for glioma, meningioma, and acoustic neuroma was 2.89 (1.41–5.93) (both side use, > 896 h), 2.57 (1.02–6.44) (both side use, > 896 h), and 3.53 (1.59–7.82) (ipsilateral use, > 1640 h), respectively. For five cohort studies, the pooled risk ratios (RRs) for all CNS tumors, glioma, meningioma, and acoustic neuroma, were statistically equivocal, respectively. However, the point estimates for acoustic neuroma showed a rather increased pooled RR for ever-use (1.26) and over 10 years of use (1.61) compared to never-use, respectively.

Excerpts:

“In consideration of these rapidly changing mobile phone technologies, the currently used proxies for RF-EMR exposure assessment are crude and insufficient to clarify the relationship between RF-EMR exposure from cell phones and brain tumor incidence.... The usual exposure measures, such as the years of mobile phone use, the cumulative duration of calls, and the number of calls per week, are rough indicators of mobile phone use.... the authors conducted a series of meta-analyses and subgroup analyses using various exposure measuring categories, from crude to more precise ones. In consideration of crude exposure classifications used in previous meta-analyses, this study will give insight into the importance of more precise exposure subcategories in investigating this topic."

"... the authors analyzed the risk of bias regarding selection and recall bias for the amount of cell phone use and misclassification and recall bias for ipsilateral/contralateral use. A major reason was that typical risk of bias rating tools such as the National Toxicology Program Office of Health Assessment and Translation Risk of Bias rating tool (NTP OHAT RoB rating tool, Supplementary material B) were not appropriate for assessing individual studies regarding this topic." [Note: Karipidis et al. (2024) relied on this rating tool.]

"With the conversion from 2G cellular phones through 3G and 4G mobile phones to current 5G mobile phones, transmission of large data became possible. With the introduction of 3G technology, all aspects of our society and daily lives have changed drastically. Currently, we are using mobile phones nearly continuously and putting mobile phones near our bodies even when we are not using them. For example, if people use their mobile phone for morning-alarming purposes, they might put their mobile phone near the bed, sometimes even beside their head, all night. These changed patterns of mobile phone use could increase exposure to RF-EMR from cellular and mobile phones. Therefore, precise exposure assessment for RF-EMR from mobile phones would become more complex in future studies."

"The results of cumulative meta-analyses according to precision indicated that the pooled OR was biased downwards with the addition of studies with lower precision. This indicates that the results of studies with a lower precision should be interpreted cautiously."

"Because brain tumors require a latency period to develop [29], an accurate assessment of brain tumor risk associated with RF-EMR exposure requires a long observation span. However, each included study did not consider a sufficient latency period in their study design. This could have led to a possible underestimation of brain tumor risk. Future studies with long observation spans might resolve this problem.”

"In this meta-analysis, as the applied exposure subcategories became more concrete, the pooled ORs showed more increased values with statistical significance. Even though the meta-analysis of cohort studies showed statistically equivocal pooled effect estimates, (i) as the number of included studies increases and (ii) as the applied exposure subcategory becomes more concrete, the pooled RRs could show a different aspect in future studies. Furthermore, changing patterns of mobile phone use and increasing use of earphones or headphones with WPAN technology should be sufficiently considered in future studies. Relatively short observation spans for brain tumor incidence and age of starting exposure and brain tumor diagnosis should also be considered in future studies. Previous studies that adjusted for selection and recall bias for the amount of cellphone use and misclassification and recall bias for ipsilateral/contralateral use showed possible underestimations of previous risk estimates. Future studies should try to adjust for these biases in their study design."

Open access paper: https://ehjournal.biomedcentral.com/articles/10.1186/s12940-024-01117-8
Supplementary material: https://static-content.springer.com/esm/art%3A10.1186%2Fs12940-024-01117-8/MediaObjects/12940_2024_1117_MOESM1_ESM.docx

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