21 June 2024.
Joel M. Moskowitz, John W. Frank, Ronald L. Melnick, Lennart Hardell, Igor Belyaev, Paul Héroux, Elizabeth Kelley, Henry Lai, Don Maisch, Erica Mallery-Blythe, Alasdair Philips.
Joel M. Moskowitz, John W. Frank, Ronald L. Melnick, Lennart Hardell, Igor Belyaev, Paul Héroux, Elizabeth Kelley, Henry Lai, Don Maisch, Erica Mallery-Blythe, Alasdair Philips.
On Behalf of the International Commission on the Biological Effects of Electromagnetic Fields
To the Editors, Environment International
We write to point out serious methodological problems with the Cohort Study on Mobile Phones and Health (COSMOS) brain tumor risk paper (Feychting et al., 2024). Because of these flaws, the study does not provide reliable estimates of the risks of tumors associated with exposure to mobile phone radio frequency radiation (RFR). This paper which summarizes interim results from this 25-plus year cohort study (Schüz et al., 2011) demonstrates many of the overall study’s shortcomings.
1. Problems with exposure assessment
At baseline, COSMOS collected data on the frequency and duration of mobile phone calls based on self-reports, partially supplemented with data from operator records from telecommunications providers. This is a poor proxy for the amount of RFR exposure from a mobile phone. Misclassification of RFR exposure was substantial because the amount of exposure from a mobile phone varies by up to four orders of magnitude depending on the cellular network technology and the strength of the signal from the cell tower (Wall et al., 2019). COSMOS did not account for this variability. The study also did not control for other sources of RFR exposure, including cordless phones, personal wireless devices, Wi-Fi routers, and cell towers.
The study used mobile phone use data at baseline to predict brain tumor incidence about seven years later (median = 7.12 years). During this time interval the cellular technology, types of mobile phones and patterns of mobile phone usage changed, and the density of cell towers or masts increased. All of these factors would alter the RFR exposure over time and reduce the ability of the baseline data to predict any health outcomes. The multiple sources of random and systematic measurement error discussed above contributed to substantial misclassification of the three comparison groups in terms of RFR exposure and biased the study results, because of its cohort design, towards the null (Setia, 2016).
Since almost everyone in this cohort study regularly used mobile phones at baseline (including two-thirds who used mobile phones for 10 or more years) and many were exposed to others sources of RFR (e.g., cordless DECT phones, cell towers, Wi-Fi), there was no unexposed group. That the authors chose to use the bottom 50 % of the mobile phone use distribution as the reference group instead of a more extreme percentile cutoff (e.g., the bottom decile of mobile phone use) does not seem defensible. Comparing the top quartile or decile of mobile phone use to the bottom 50 % (which averaged up to 10.6 min per day of call time) when there is considerable measurement error as in the present study reduces the likelihood of finding a difference in tumor risk across exposure strata. Thus, this choice of a reference group further biased the results towards the null.
Continue reading:
https://www.sciencedirect.com/science/article/pii/S0160412024003933
To the Editors, Environment International
We write to point out serious methodological problems with the Cohort Study on Mobile Phones and Health (COSMOS) brain tumor risk paper (Feychting et al., 2024). Because of these flaws, the study does not provide reliable estimates of the risks of tumors associated with exposure to mobile phone radio frequency radiation (RFR). This paper which summarizes interim results from this 25-plus year cohort study (Schüz et al., 2011) demonstrates many of the overall study’s shortcomings.
1. Problems with exposure assessment
At baseline, COSMOS collected data on the frequency and duration of mobile phone calls based on self-reports, partially supplemented with data from operator records from telecommunications providers. This is a poor proxy for the amount of RFR exposure from a mobile phone. Misclassification of RFR exposure was substantial because the amount of exposure from a mobile phone varies by up to four orders of magnitude depending on the cellular network technology and the strength of the signal from the cell tower (Wall et al., 2019). COSMOS did not account for this variability. The study also did not control for other sources of RFR exposure, including cordless phones, personal wireless devices, Wi-Fi routers, and cell towers.
The study used mobile phone use data at baseline to predict brain tumor incidence about seven years later (median = 7.12 years). During this time interval the cellular technology, types of mobile phones and patterns of mobile phone usage changed, and the density of cell towers or masts increased. All of these factors would alter the RFR exposure over time and reduce the ability of the baseline data to predict any health outcomes. The multiple sources of random and systematic measurement error discussed above contributed to substantial misclassification of the three comparison groups in terms of RFR exposure and biased the study results, because of its cohort design, towards the null (Setia, 2016).
Since almost everyone in this cohort study regularly used mobile phones at baseline (including two-thirds who used mobile phones for 10 or more years) and many were exposed to others sources of RFR (e.g., cordless DECT phones, cell towers, Wi-Fi), there was no unexposed group. That the authors chose to use the bottom 50 % of the mobile phone use distribution as the reference group instead of a more extreme percentile cutoff (e.g., the bottom decile of mobile phone use) does not seem defensible. Comparing the top quartile or decile of mobile phone use to the bottom 50 % (which averaged up to 10.6 min per day of call time) when there is considerable measurement error as in the present study reduces the likelihood of finding a difference in tumor risk across exposure strata. Thus, this choice of a reference group further biased the results towards the null.
Continue reading:
https://www.sciencedirect.com/science/article/pii/S0160412024003933
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