Wednesday, August 3, 2022

AirPods: Are Apple’s New Wireless Earbuds Safe?

Third-Generation AirPods

The third generation of Apple's AirPods (aka AirPods 3) was introduced in 2021. 

The Specific Absorption Rate (or SAR) for the right AirPod is 0.626 watts per kilogram (assessed via the flat phantom & averaged over 1 gram of tissue) (1). The SAR for the left AirPod is 0.614 watts per kilogram (2). 


April 2, 2019

Second-Generation AirPods

The newly-released second generation of Apple's AirPods (aka AirPods 2) emits Bluetooth microwave radiation in the 2.402 – 2.480 GHz frequency range to communicate with a smart phone or other wireless device.

The Specific Absorption Rate (or SAR) for the right AirPod is 0.581 watts per kilogram (averaged over 1 gram). (1) The SAR for the left AirPod is 0.501 watts per kilogram. (2)

News about the potential health risks from use of wireless headsets first went viral in 2016 (see posts below). This story has gone viral again at this time for the following reasons:
  • Apple announced that it is taking orders for a new version of its wireless headset, AirPods (aka AirPods 2).
  • In the past year, two major studies found conclusive evidence that microwave radiation caused cancer in rats. These studies conducted by the National Toxicology Program in the U.S. and the Ramazzini Institute in Italy received worldwide media coverage.
  • The proliferation of new cell towers and antennas in preparation for the deployment of 5G,fifth generation cellular technology, has stimulated many people to seek out information about the health effects from exposure to the radiation these antennas emit on a 24-7 basis in their neighborhoods.
  • More people now realize we cannot trust governments to protect us from environmental toxins. Industry has too much influence over government regulatory agencies, and governments have conflicts of interest because the telecom industry pays governments substantial taxes and fees.
For some Bluetooth devices like Apple’s AirPods, the Specific Absorption Rate (SAR), a measure of the body’s maximum exposure to microwave radiation, exceeds that of many smart phones. Moreover, the cumulative exposure to radiation from wireless headsets may be substantial since many users keep these devices on their head for hours at a time and use them to listen to music or podcasts.

I have found only two small studies that examined the short-term effects on hearing from exposure to Bluetooth, the communications standard use in AirPods and other wireless headsets (see below). The health effects from long-term exposure to this type of microwave radiation have not been studied.

The FCC minimum exposure levels were adopted in 1996 based largely upon recommendations from industry-funded scientists and engineers. The guidelines were designed only to protect us from short-term heating risks. We now have hundreds of studies that show harmful biologic and health effects from long-term exposure to low levels of microwave radiation that do not involve heating. The guidelines need to be updated to protect us from these effects.

Although there is no consensus regarding a safe level of exposure to microwave radiation, most scientists who have published research on the effects of this radiation agree that the current exposure limits are much too permissive. In fact, more than 240 scientists from 42 nations who have published peer-reviewed research on electromagnetic fields and biology or health totaling over 2,000 papers in professional journals have signed the International EMF Scientist Appeal which calls for stronger exposure limits and health warnings. 

Most wireless safety tips recommend the use of wired headsets or hands-free use of smart phones and other electronic devices instead of wireless headsets.

News Stories

Are AirPods and Other Bluetooth Headphones Safe?
Markham Heid, Medium, March 7, 2019

Are wireless earbuds dangerous? Experts warn that Apple’s AirPods could send an electromagnetic field through your brain
Natalie Rahhal, Daily Mail, March 11, 2019 Revised March 12

Scientists warn wireless, Bluetooth devices may carry cancer risk

Healio: Hematology/Oncology Today, March 13, 2019

Earpods for Cell Phones — Are There Health Risks?

Roxanne Nelson, RN, BSN, Medscape Medical News, March 15, 2019

Are Bluetooth Headphones Dangerous? Here’s What Experts Think
Julia Ries, Healthline, March 24, 2019 

Controversy surrounding safety of wireless earphones: News Focus 2 with Prof. Joel Moskowitz
This Morning, tbs eFM (Seoul, Korea), March 25, 2019 (10 minute audio)

Did 250 Scientists Warn that Apple Airpods Pose a Cancer Risk?
Bethania Palma, Snopes, March 28, 2019

(1) UL Verification Services, Inc. SAR Evaluation Report for Bluetooth Earbud. FCC ID: BCG-A2032. Model Name: A2032. Report Number: 12458150-S2V1. Issue Date: 3/15/2019. Fremont, CA.

(2) UL Verification Services, Inc. SAR Evaluation Report for Bluetooth Earbud. FCC ID: BCG-A2031. Model Name: A2031. Report Number: 12458150-S1V1. Issue Date: 3/15/2019. Fremont, CA.

December 13, 2016

Apple announced today that AirPods can be ordered online and will be available in stores next week. The wireless earbuds will be available in limited quantities in more than 100 countries and territories.

Apple originally planned to ship AirPods in October and has not explained the reason for the delay. The Wall Street Journal reported that the delay was due to problems with the Bluetooth wireless technology employed by this device.

September 12, 2016

Apple’s new AirPods are wireless earbuds that employ Bluetooth technology to communicate with your smart phone, laptop, or smart watch. 

According to Apple, “After a simple one-tap setup, AirPods are automatically on and always connected.”

The Specific Absorption Rate (SAR) for the AirPods

The right AirPod emits Bluetooth microwave radiation in the 2.402 – 2.480 GHz frequency range to communicate with a smart phone or other wireless device. The Specific Absorption Rate (or SAR) for the right AirPod is 0.466 watts per kilogram (averaged over 1 gram). (1) The SAR  for the left AirPod is 0.510 watts per kilogram. (2)

For more information about the SAR see my post on the iPhone 7.

If one uses the AirPods many hours a day, the cumulative exposure to the brain from this microwave radiation could be substantial. 

According to EE Times, the left AirPod communicates with the right AirPod using a different technology, "near field magnetic induction (NFMI)."

Although there is a substantial research literature on the health risks of exposure to magnetic fields, I am not aware of any biologic research that examines NFMI. Hence, this post focuses on the risks to the brain from exposure to Bluetooth radiation. 

Is Bluetooth safe?

The wireless industry argues that devices that use Bluetooth are safe because the microwave radiation emitted by such devices is low compared to FCC guidelines. The FCC requires the SAR to be 1.6 watts per kilogram or less.

More than 240 scientists who have published research on electromagnetic radiation safety believe that current national and international guidelines for exposure to radio frequency radiation are inadequate to protect human health (see the International EMF Scientist Appeal).

I could find only two peer-reviewed studies that have examined the effects of exposure to Bluetooth radiation. The studies which employed small samples evaluated the effects of brief exposure to Bluetooth radiation on the auditory system. (2) Given the study limitations, the absence of significant effects is not surprising. These studies do not provide the basis to argue that long-term exposure to Bluetooth radiation is safe.

Low-intensity microwave radiation can open the blood-brain barrier

In 1975, Allan Frey published a paper in the Annals of the New York Academy of Sciences which reported that exposure to low intensity microwave radiation could open the blood-brain barrier in rats. Moreover, pulsed radio frequency waves (like Bluetooth) were more likely to produce this effect than continuous waves. (3)

The blood-brain barrier is a special layer of cells in the brain that prevents chemical toxins in the blood system from reaching the brain. Breaching this barrier could potentially lead to neurodevelopmental and neurodegenerative diseases and brain cancer.

More than a dozen peer-reviewed studies have replicated Frey's findingsexposure to low intensity microwave radiation can open the blood-brain barrier (see links below). (3)  

The effect of microwave radiation on the blood-brain barrier is nonlinear—it occurs with low intensity exposures but not at higher intensity exposures.

Although other published studies have failed to find the blood-brain barrier effect, these studies tended to use higher intensity exposures or employed small samples.


We may not be certain of the long-term risks of using Bluetooth devices, but why would anyone insert microwave-emitting devices in their ears near their brain when there are safer ways to use a cell phone?

I recommend the use of corded headsets or hands-free use of cell phones, not wireless earbuds. Moreover, one should never keep a cell phone next to your body, especially during a phone call, but also whenever the phone is powered on. For additional tips on how to reduce your exposure to wireless radiation see

News coverage

In the past few days, numerous news stories have appeared citing industry-affiliated scientists who claim that AirPods are safe. Nonetheless, a few news reports have addressed the potential health risks from using AirPods:

·         CBS San Francisco"Apple Unveils iPhone 7 Without Headphone Jack"
·         Daily Mail“Could wireless headphones harm your health?”

Since the stories in the Daily Mail and CNN were posted on September 8, over two dozen online news stories have appeared that discuss the potential health risks from the microwave radiation emitted by AirPods.


(1) UL Verification Services, Inc. SAR Evaluation Report for Wireless Headset. FCC ID: BCG-A1523. Model Name: A1523. Report Number: 16U23784-S6V1. Issue Date: 8/30/2016. Fremont, CA.

(2) UL Verification Services, Inc. SAR Evaluation Report for Wireless Headset. FCC ID: BCG-A1722. Model Name: A1722. Report Number: 16U23784-S1V1. Issue Date: 8/30/2016. Fremont, CA.

(3) Peer-reviewed studies which reported on the effects of brief exposure to Bluetooth radiation:

Mandalà M, Colletti V, Sacchetto L, Manganotti P, Ramat S, Marcocci A, Colletti L. Effect of Bluetooth headset and mobile phone electromagnetic fields on the human auditory nerve. Laryngoscope. 2014 Jan;124(1):255-9.

Balachandran R, Prepageran N, Rahmat O, Zulkiflee AB, Hufaida KS. Effects of Bluetooth device electromagnetic field on hearing: pilot study. J Laryngol Otol. 2012 Apr;126(4):345-8.

(4) Peer-reviewed studies which reported opening of the blood-brain barrier from exposure to low-intensity microwave radiation:

Sırav B, Seyhan N. Effects of GSM modulated radio-frequency electromagnetic radiation on permeability of blood-brain barrier in male & female rats. J Chem Neuroanat. 2016 Sep;75(Pt B):123-7  23.

Tang J, Zhang Y, Yang L, Chen Q, Tan L, Zuo S, Feng H, Chen Z, Zhu G. Exposure to 900MHz electromagnetic fields activates the mkp-1/ERK pathway and causes blood-brain barrier damage and cognitive impairment in rats. Brain Res. 2015 Jan 15.

Sirav B, Seyhan N. Effects of radiofrequency radiation exposure on blood-brain barrier permeability in male and female rats. Electromagn Biol Med. 2011 Dec;30(4):253-60.

Sirav B, Seyhan N. Blood-brain barrier disruption by continuous-wave radio frequency radiation. Electromagn Biol Med. 2009;28(2):215-22.

Nittby H, Brun A, Eberhardt J, Malmgren L, Persson BR, Salford LG. Increased blood-brain barrier permeability in mammalian brain 7 days after exposure to the radiation from a GSM-900 mobile phone. Pathophysiology. 2009 Aug;16(2-3):103-12.

Söderqvist F, Carlberg M, Hansson Mild K, Hardell L. Exposure to an 890-MHz mobile phone-like signal and serum levels of S100B and transthyretin in volunteers. Toxicol Lett. 2009 Aug 25;189(1):63-6.

Eberhardt JL, Persson BR, Brun AE, Salford LG, Malmgren LO. Blood-brain barrier permeability and nerve cell damage in rat brain 14 and 28 days after exposure to microwaves from GSM mobile phones. Electromagn Biol Med. 2008;27(3):215-29.

Belyaev IY,  Koch CB, Terenius O, Roxström-Lindquist K, Malmgren LO, H Sommer W, Salford LG, Persson BR. Exposure of rat brain to 915 MHz GSM microwaves induces changes in gene expression but not double stranded DNA breaks or effects on chromatin conformation. Bioelectromagnetics. 2006 May;27(4):295-306.

Salford LG, Brun AE,  Eberhardt JL,  Malmgren L,  Persson BR. Nerve cell damage in mammalian brain after exposure to microwaves from GSM mobile phones. Environ Health Perspect. 2003 Jun;111(7):881-3; discussion A408.

Leszczynski D, Joenväärä S, Reivinen J, Kuokka R. Non-thermal activation of the hsp27/p38MAPK stress pathway by mobile phone radiation in human endothelial cells: molecular mechanism for cancer- and blood-brain barrier-related effects. Differentiation. 2002 May;70(2-3):120-9.

Schirmacher A, Winters S, Fischer S, Goeke J, Galla HJ, Kullnick U, Ringelstein EB, Stögbauer F. Electromagnetic fields (1.8 GHz) increase the permeability to sucrose of the blood-brain barrier in vitro. Bioelectromagnetics. 2000 Jul;21(5):338-45.

Fritze K, Sommer C, Schmitz B, Mies G, Hossmann KA, Kiessling M, Wiessner C. Effect of global system for mobile communication (GSM) microwave exposure on blood-brain barrier permeability in rat. Acta Neuropathol. 1997 Nov;94(5):465-70.

Salford LG, Brun A, Sturesson K, Eberhardt JL, Persson BR. Permeability of the blood-brain barrier induced by 915 MHz electromagnetic radiation, continuous wave and modulated at 8, 16, 50, and 200 Hz. Microsc Res Tech. 1994 Apr 15;27(6):535-42.

Persson BR, Salford LG, Brun A, Eberhardt JL, Malmgren L. Increased permeability of the blood-brain barrier induced by magnetic and electromagnetic fields. Ann N Y Acad Sci. 1992 Mar 31;649:356-8.

Frey AH, Feld SR, Frey B. Neural function and behavior: Defining the relationship. Annals of the New York Academy of Sciences, 247: 433–439. 1975. 

Tuesday, August 2, 2022

Trends in Brain Tumor Incidence Outside the U.S.

Use of mobile phones and progression of glioma incidence in four Nordic countries since 1979

My notes: 

Although the title of the following report from the WHO International Agency for Research on Cancer is in German, the report is available in English. 

The report's summary, "no indications of a detectable effect of mobile phones have been found," seems misleading because it is inconsistent with the report's final conclusion, namely, "An increased risk in the 10% heaviest mobile phone users was an exception to this general situation, as it remained plausible."

[The 10% "heaviest mobile users" in the Interphone study had 1,640 or more hours of lifetime call time. That would amount to approximately 30 minutes per day over a 10-year period.]

The report's bottom line: 

"This ecological data is not sufficient to dismiss every potential mobile phone related risk scenario, but suggests that the risk – if it exists - would be very small, only occur after very long latency periods of several decades, or only affect small subgroups within glioma patients." 

If only a portion of the population has a genetic susceptibility to brain cancer in the presence of microwave radiation as appears to be the case with thyroid cancer (Luo et al., 2020), that could explain why the odds ratios obtained for brain cancer risk from case-control studies of heavy, long-term mobile phone users over-predict glioma incidence in the overall population based upon tumor registry data.
* Luo J, Li H, Deziel NC, Huang H, Zhao N, Ma S, Nie X, Udelsman R, Zhang Y. Genetic susceptibility may modify the association between cell phone use and thyroid cancer: A population-based case-control study in Connecticut. Environmental Research. 2020 Mar;182:109013. doi: 10.1016/j.envres.2019.109013. (see also Thyroid Cancer and Mobile Phone Use)


Deltour I, Schuz J. Nutzung von Mobiltelefonen und Verlauf der Gliom-Inzidenz seit 1979: Vorhaben 3618S00000 (FM 8867). International Agency for Research on Cancer. Jun 2022. Open access report:


1.1 Introduction

In the Nordic countries, the sharp increase in the use of mobile phone occurred in the mid-1990s among adults; thus, time trends in glioma incidence rates (IR) may provide information about possible risks associated with mobile phone use. We investigated time trends in IR of glioma, and compared IR and observed number of cases to those that would be expected under a range of hypothetical mobile phone risk scenarios, encompassing risk levels reported in published case-control studies.

1.2 Methods

We analyzed age standardised IR of glioma in Denmark, Finland, Norway, and Sweden among adults 20-84 years old, using data from national cancer registries and population data covering the period 1979-2016, using a log linear joinpoint analysis. Exposure distribution of use and of high level of use were obtained from self-reported information in the Nordic Interphone, the Cosmos-Denmark and the Cosmos-France datasets. Based on analytical epidemiological studies, we considered various scenarios according to which mobile phone use would hypothetically increase the glioma risk. We quantified compatibility, or absence of compatibility between the observed data and the risk scenarios by projecting incidence rates of glioma of men aged 40-69 years old under these scenarios and comparing them with the observed incidence rates in the Nordic countries.

1.3 Results

Glioma IR increased regularly with annual percent change (APC) of 0.6 (95% confidence interval (CI) 0.4-0.7) in men and 0.3 (95%CI 0.2-0.5) in women in the period 1979-2016. There were hardly any changes in IR among men and women below age 59. In men and women in their sixties, IR increased by 0.6 (95%CI 0.4-0.9) in men and 0.4 (95%CI 0.2-0.7) in women, regularly for the whole period of observation, while IR among 70-84 years old increased very markedly, with APC of 3.1 (95%CI 2.6-3.5) among men and 2.8 (95%CI 2.3-3.3) among women over at least the last 2 decades of observation. Very few risk scenarios appeared compatible with the observed data using standardised incidence ratios analyses. The risk scenarios that appeared compatible involved either long latencies (20 years), or very low risks (RR = 1.08); in these projections, risks that would be limited to mobile phone heavy users were not compatible with the observed number of cases.

1.4 Discussion

IR time trends did not demonstrate breakpoints in their secular evolution in the last 20 years. Virtually all the reported results from the case-control studies with a positive association between mobile phone use and glioma risk were shown to be implausible in our simulations comparing them with the observed incidence rates, implying that biases and errors have likely distorted their findings; very low risks at the population level, and risks after very long latencies remained plausible. Simulations were based on high quality case registration, which is a strength, while the uncertainties in the exposure information and the limited information about some of the model’s assumptions were limitations. Altogether, this study confirms and reinforces conclusions made previously, that no indications of a detectable effect of mobile phones have been found.


... We analyzed the time trends in the incidence rates of glioma among adults aged 20 to 84 years of the Nordic countries from 1979 to 2016 (step 1 of the work description). Then, we addressed the question whether the observed time trends and observed number of cases were statistically different from the one we would observe if we assumed that the use of mobile phones caused glioma, so if we assumed that there was a true causal association (step 2 and step 3 of the work description). Within this, we delineated the levels of risks and the duration of induction periods that would not be compatible with the observed time trends and numbers of cases in this population (step 3 of the work description). We also discussed these findings in light of some of the elevated OR found in the literature. The study tested the consistency between risks that have been reported and the effect they would have had at the level of the population, had they been true. Noteworthy, the study was not meant to dismiss every single hypothetical association, as it would most likely always be possible to devise a pattern of risk that would fit the data....

This study was based on 28,015 male and 20,630 female glioma cases diagnosed from 1979 to 2016 in Denmark, Finland, Norway and Sweden (called “the Nordic countries” in the following). In 2016, the number of glioma cases was 1,724 in a population of 19.7 million adults aged 20–84 years. Over the last 10 years of data, Sweden accounted for 38% of the population and of the cases; of the remainder, Denmark, Finland, and Norway had populations of similar size. The age-standardized incidence rates were higher in men (9.1 per 100000 person years) than in women (6.1 per 100 000 person years), and higher with increasing age. All countries had comparable rates; Norway had slightly higher rates, while Finland had slightly lower rates in both sexes (Table 2 and Table 3).

Joinpoint analyses described in paragraph 6.1 showed that overall, the trends were smooth: glioma rates increased by 0.6% (95% CI 0.4%-0.7%) per year in men and 0.3% (95% CI 0.2%-0.5%) per year in women over the period 1979-2016 in the Nordic countries combined (Table 4 and Table 5), and in each country separately except for a marked increase in 1979-1984 in Swedish men (APC about 6%). For the younger age groups (20-39 and 40-59 years old), the time trends were smooth and did not demonstrate strong increases at any point in time during the period 1979 to 2016 in any country among men (Table 6), and women (Table 7). Below the age of 60, incidence rates were generally stable over the whole period (Figure 1, Table 6 and Table 7). Among people aged 60-69 years old, incidence rates increased gradually by 0.6% in men and 0.4% in women per year, and these regular increases with no joinpoint were observed in every country and at a very similar rate in both sexes, except among Swedish women, whose rates showed a slight decrease. Irregular patterns were observed among the persons aged 70-84 years old at the beginning of the observation period, while for at least the last 12 years of observation, all countries showed highly increasing rates. Exceptions to this general pattern were noted among the Finnish males and the Norwegian females, in which an increase was seen at the beginning of the observation period that lasted at least 21 years.

The analysis by subgroups of tumour types could be performed only for the period 1990-2016 for reasons of data availability: in Sweden, a separate code for glioblastoma did not exist prior to 1993, and very few of the tumours which had been diagnosed during the period 1990-1992 were retrospectively coded into this code. Indeed, cancer registries are continuously updated when additional information becomes available on an earlier diagnosis, for example.

Among men and women, the rates of glioblastomas increased in the last years of observations, while the rate of other high-grade gliomas decreased (Table 8 and Table 9). Rates of low grade gliomas were relatively stable in all countries since the mid 1990’s except in Denmark, where substantial increases were noted towards the end of the period of observation, albeit non-significant....

When examining the trends by subtypes, glioblastoma generally increased while other high grade gliomas decreased, and low grade glioma were stable in the most recent period, except in Denmark where low grade glioma rates increased among men and women in the last 3 years of observation. In Sweden, the rates of glioblastoma underwent most changes, namely the increase in glioblastoma rates in Sweden in the years after the introduction of that code by the cancer registry, since a new code is not mandatorily fully used immediately after it is introduced....

To sum up, our simplified and more sophisticated analyses appeared to indicate that the small increase in IR of men age 40-59 and the marked increase in RR of men aged 60-69 were generally not compatible with the same mobile phone related risks increases. When models in which the totality of the IR increases were assumed to be associated with mobile phone effects, a RR of 1.31 that would start 20 years after first using a mobile phone was borderline compatible between these 2 age groups, while all other induction periods (0, 5, 10, 15 years) or heavy users risk scenarios produced RR estimates and CI which did not overlap between the 2 age groups when the same exposure distribution was considered. When half of the IR increases were attributed to other factors, none of the mobile phone related risks scenarios were compatible with the data, in the SIR analyses (assuming the same risk in both age groups). When most (75%) of the IR increases were attributed to other factors, then small excess risks (RR= 1.08 applying to all users after 10 years) or risks after long latencies (RR = 1.3 applying to all users after 20 years) were compatible with the observed incidence rates and exposure distributions that we assumed. Further work on these scenarios could shed more light on the remaining uncertainties. Of note, scenarios of risks limited to heavy users groups did not appear compatible with the observed number of cases in these analyses....

Our simulation study is not free of assumptions. The induction period relating mobile phone use and glioma risk, if such an association exists, is unknown, so is the magnitude of the risk, and the real patterns may be more complex than the scenarios that we simulated. In addition, there are several factors that we did not account for. The coverage of the Nordic cancer registries was not complete, but some 1.5% to 10% of the malignant tumours were missed in this age group. In Sweden, it has been estimated that completeness would not have changed over the period 1998-2014, while completeness might have improved in other countries. We modelled that other, yet to be discovered, risk factors of the disease as well as improvement in its detection and reporting had a smooth, gradual impact, over the period 1979-2016, which is consistent with the gradually increasing IR. We used 3 sources of information on the use of mobile phones, all self-reported, to evaluate the prevalence of use and heavy use up to 2002, 2008 or 2016 and extrapolated the prevalences for the periods and age groups for which no data was available, based on the trends observed in the other age groups. The use of hands-free devices was not accounted for, although this was not frequent in these populations (data not shown).

In conclusion, it is difficult to demonstrate the absence of risk, in real life condition, and assumptions about the impact of the improvement of diagnosis tools, treatment and registration changes over time were used in our simulations. However, based both on the observed IR and the simulations, we reiterate and strengthen our previous conclusion that, the risk, should one exist, ought to be lower or occur after a longer induction period or act on a smaller population, or a combination of these, than most of the level of risk that have been reported in previously published case-control studies.


In this project we projected incidence rates of glioma under various scenarios of mobile phone-associated increased glioma risks, and compared them with the observed incidence rates in the Nordic countries. The comparison was carried out on the data of men aged 40 to 69 years. The modelled scenarios included risk increases reported from analytical epidemiological studies, which were all of case-control design. Most of those results were shown to be implausible in our simulations, implying that biases and errors in the self-reported use of mobile phones have likely distorted their findings. An increased risk in the 10% heaviest mobile phone users was an exception to this general situation, as it remained plausible. Results of cohort studies showing no association were compatible with observed incidence rates. We also studied what hypothetical mobile phone-related risks were conceivable if the changes in incidence rates in 40-59 year old and 60-69 year old men were fully attributable to mobile phone use. The fact that we observed different hypothetical risks in these two age groups while research at present has not suggested that older men should have higher risk related to mobile phone use than younger men, does not align with the assumption that mobile phone exposures caused the incidence rate trends. This ecological data is not sufficient to dismiss every potential mobile phone related risk scenario, but suggests that the risk – if it exists - would be very small, only occur after very long latency periods of several decades, or only affect small subgroups within glioma patients.

Open access report:


Incidence trends of adult malignant brain tumors in Finland, 1990-2016

Natukka T, Raitanen J, Haapasalo H, Auvinen A. Incidence trends of adult malignant brain tumors in Finland, 1990-2016. Acta Oncol. 2019 Apr 15:1-7. doi: 10.1080/0284186X.2019.1603396.


BACKGROUND: Several studies have reported increased incidence trends of malignant gliomas in the late 1900s with a plateau in the 2000s, but also some  recent increases have been reported. The purpose of our study was to analyze incidence trends of malignant gliomas in Finland by morphology and tumor location.

MATERIAL AND METHODS: Data on 4730 malignant glioma patients were obtained from case notifications to the nationwide, population-based Finnish Cancer Registry (FCR), and less detailed data on 3590 patients up to 2016. Age-standardized incidence rates (ASR) and average annual percent changes (APCs) in the incidence rates were calculated by histological subtype and tumor location.

RESULTS: The incidence rate of gliomas was 7.7/100,000 in 1990-2006 and 7.3 in 2007-2016. The incidence of all gliomas combined was stable during both study periods, with no departure from linearity. In an analysis by age group, increasing incidence was found only for ages 80 years and older (1990-2006). During both study periods, incidence rates were increasing in glioblastoma and decreasing in unspecified brain tumors. In 1990-2006, rates were also increasing for anaplastic oligodendroglioma, oligoastrocytoma and unspecified malignant glioma, while decreasing for astrocytoma. As for tumor location, incidence in 1990-2006 was increasing for frontal lobe and brainstem tumors, as well as those with an unspecified location, but decreasing for the parietal lobes, cerebrum and ventricles.

CONCLUSIONS: No increasing incidence trend was observed for malignant gliomas overall. An increasing incidence trend of malignant gliomas was found in the oldest age group during 1990-2006.


The incidence trend of glioblastoma was slightly increasing (APC: +0.8%; 95% CI: 0.0, +1.7 for 1990–2006 and +1.9%; 95% CI: +0.2, +3.5 for 2007–2016; Tables 2 and 3).

Incidence of glioblastoma increased slightly throughout the study period, while unspecified tumors of the brain showed a decreasing incidence trend.

We also found a slightly increasing incidence trend for the most common histological subtype, glioblastoma, which is consistent with several other studies [1,5,7–9,11,17,18]. A study from United States showed an increasing incidence trend for gliomas in the frontal lobe and decreasing trends for the cerebrum, ventricles and overlapping subtypes [17].


[1] Ostrom QT, Gittleman H, Liao P, et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2010–2014. Neuro Oncol. 2017;19: v1–v88.
[5] Ho VKY, Reijneveld JC, Enting RH, et al. Changing incidence and improved survival of gliomas. Eur J Cancer. 2014;50:2309–2318.
[7] Arora RS, Alston RD, Eden TOB, et al. Are reported increases in incidence of primary CNS tumours real? An analysis of longitudinal trends in England, 1979–2003. Eur J Cancer. 2010;46: 1607–1616.
[8] Deorah S, Lynch CF, Sibenaller ZA, et al. Trends in brain cancer incidence and survival in the United States: surveillance, epidemiology, and end results program, 1973 to 2001. Neurosurg Focus. 2006;20:E1.
[9] Hess KR, Broglio KR, Bondy ML. Adult glioma incidence trends in the United States, 1977–2000. Cancer. 2004;101:2293–2299.
[11] Lonn S, Klaeboe L, Hall P, et al. Incidence trends of adult primary intracerebral tumors in four Nordic countries. Int J Cancer. 2004; 108:450–455.
[17] Zada G, Bond AE, Wang YP, et al. Incidence trends in the anatomic location of primary malignant brain tumors in the United States: 1992–2006. World Neurosurg. 2012;77:518–524.
[18] Dubrow R, Darefsky AS. Demographic variation in incidence of adult glioma by subtype, United States, 1992–2007. BMC Cancer. 2011;11:325.


Trends in the incidence of primary brain, central nervous system and intracranial tumors in Israel, 1990-2015

Keinan-Boker L, Friedman E, Silverman BG. Trends in the incidence of primary brain, central nervous system and intracranial tumors in Israel, 1990-2015. Cancer Epidemiol. 2018 Oct;56:6-13. doi: 10.1016/j.canep.2018.07.003.


• Exponential growth in cellphone use fueled concerns regarding brain and CNS tumors.
• Results so far are inconsistent. Studying cancer incidence trends may thus be informative.
• We studied brain tumor trends from 1990 to 2015 in Israel, when cellphone use dramatically increased.
• Results do not support a substantial role for cellphone use; smaller risks in special subgroups may exist.
• Future research is needed; implementation of the precautionary principle is prudent.


BACKGROUND: The association between cellphone technology and brain, central nervous system (CNS) and intracranial tumors is unclear. Analysis of trends in incidence of such tumors for periods during which cellphone use increased dramatically may add relevant information. Herein we describe secular trends in the incidence of primary tumors of the brain and CNS from 1990 to 2015 in Israel, a period during which cellphone technology became extremely prevalent in Israel.

METHODS: All cases of primary brain, CNS and intracranial tumors (excluding lymphomas) diagnosed in Israel from 1990 to 2015 were identified in the Israel National Cancer Registry database and categorized by behavior (malignant; benign/uncertain behavior) and histologic type. Annual age-standardized incidence rates by sex and population group (Jews; Arabs) were computed, and the annual percent changes and 95% confidence intervals per category were calculated using Joinpoint software.

RESULTS: Over 26 years (1990-2015) no significant changes in the incidence of malignant brain, CNS and intracranial tumors were observed, except for an increase in malignant glioma incidence in Jewish women up to 2008 and Arab men up to 2001, which levelled off in both subgroups thereafter. The incidence of benign/uncertain behavior brain, CNS and intracranial tumors increased in most population groups up to the mid-2000s, a trend mostly driven by changes in the incidence of meningioma, but either significantly decreased (Jews) or stabilized (Arabs) thereafter.

CONCLUSIONS: Our findings are not consistent with a discernable effect of cellphone use patterns in Israel on incidence trends of brain, CNS and intracranial tumors.


"When cancer occurrence rates referred to glioblastomas only, Joinpoint analysis of incidence trends was restricted to the period from 1995 to 2015 due to small numbers of cases in the Arab population prior to 1995. Stable incidence trends were noted, with non-significant APCs, in all population subgroups: APC1995–2015 for Jewish men was +0.6% (95%CI -0.4%,+1.6%); APC1995–2015 for Jewish women was +0.6% (95%CI -0.1%,+1.6%); APC1995–2015 for Arab men was -1.6% (95%CI -3.9%,+0.8%); APC1995–2015 for Arab women was +0.4% (95%CI -2.9%,+3.8%).

Analysis of time trends by age groups disclosed stable trends in most population- age- and sex groups, except for a mild increase in Jewish males aged 65 and over (APC1990–2015 +1.2%, p < 0.05) and in Arab males aged 20–64 (APC1990–2015 +1.5%, p < 0.05). In the population of Arab females, lack of cases in the age groups of 20–64 and 65+ in certain years prevented an analysis of trends."

"However, ecologic studies, of which ours is an example, may be insensitive to excess in risk which is restricted to certain groups (for example, heavy users or subjects exposed from very young ages) or to certain tumor types (e.g., tumors that are very rare, that involve specific anatomical sites, or that have unusually long latency periods) [34]. Little et al. [35] also commented that the predicted rates of glioma based on data derived from the small proportion of highly exposed people in the Interphone study, could be consistent with the observed rates in their study [35]. Therefore, although a substantial risk is not very plausible, smaller risks cannot be ruled out and future research should address specific exposure groups, and tumor types and sites, and should allow for longer follow up periods."


England: Brain Cancer Incidence Increased in Temporal and Frontal Lobes of Brain since 1995

A new study of cancer data in England essentially replicated the results of the Philips et al study (see below). The study found that the two age groups most vulnerable to carcinogenic effects from cell phone use -- young and elderly adults -- showed increased incidence over time in brain cancer in the frontal and temporal lobes of the brain -- the two lobes that receive the greatest dose of microwave radiation when cell phones are used near the head during phone calls.

However, Frank de Vocht, the author of this paper, rejected the explanation that cell phone use caused the increased cancer risk. He attributed the increased incidence to better diagnosis of brain tumors, especially in the elderly. Of course, this does not explain why the increase was only observed in the frontal and temporal lobes. He did not rule out the possibility that cell phone radiation may be a contributing factor to the observed increase.

Microwave News reported on this study and published the following graph obtained from Alasdair Philips (Microwave News, "Location, Location, Location: Aggressive Brain Tumors Tell a Story; GBM Rise Only in Frontal and Temporal Lobes, Oct 26, 2018.)

de Vocht F. Analyses of temporal and spatial patterns of Glioblastoma Multiforme and other brain cancers subtypes in relation to mobile phones using synthetic counterfactuals. Environmental Research. Available online 17 October 2018.


• English 1985–2005 brain cancer subtype rates were compared to counterfactual trends
• Excess GBM increases were found in the frontal and temporal lobes, and cerebellum
• Mobile phone use was unlikely to have been an important putative factor
• No evidence of an effect of mobile phone use on acoustic neuroma and meningioma


This study assesses whether temporal trends in glioblastoma multiforme (GBM) in different brain regions, and of different malignant and benign (including acoustic neuroma and meningioma) subtypes in the temporal lobe, could be associated with mobile phone use.

Annual 1985–2005 incidence of brain cancer subtypes for England were linked to population-level covariates. Bayesian structural timeseries were used to create 2006–2014 counterfactual trends, and differences with measured newly diagnosed cases were interpreted as causal effects.

Increases in excess of the counterfactuals for GBM were found in the temporal (+38% [95% Credible Interval -7%,78%]) and frontal (+36% [-8%,77%]) lobes, which were in agreement with hypothesised temporal and spatial mechanisms of mobile phone usage, and cerebellum (+59% [-0%,120%]). However, effects were primarily present in older age groups, with largest effects in 75+ and 85+ groups, indicating mobile phone use is unlikely to have been an important putative factor. There was no evidence of an effect of mobile phone use on incidence of acoustic neuroma and meningioma.

Although 1985–2014 trends in GBM in the temporal and frontal lobes, and probably cerebellum, seem consistent with mobile phone use as an important putative factor, age-group specific analyses indicate that it is unlikely that this correlation is causal.


Assessment of specific cancer subtypes in the temporal lobe indicated that the excess incidence was mainly found for GBM, with similar trends observed in the frontal lobe and cerebellum....  The increased rates of specific brain cancer subtypes in excess of the counterfactuals correspond to the spatial and temporal patterns that would be expected if exposure to RF from mobile phones were an important putative factor (Cardis et al., 2008, Morgan et al., 2016) ... However, age group-specific analyses indicate that the excess relative impacts increased with age over 65 years and were primarily found in the very old (75/85+ years of age) for whom it is unlikely that mobile phone use had been an important causal factor. In addition, excess numbers of newly diagnosed cases were also observed in the young (<24 years of age) for whom mobile phone use is also an unlikely causal factor....

The assumption that a 10-year lag was the most plausible period between first exposure and when increased risk could be observed in registry data was based on the previous analyses (De Vocht (2016)). Although sensitivity analysis using a 15-year lag showed no evidence of excesses relative to counterfactuals, this may still have been too short....
This study, in agreement with other data from the UK and elsewhere, shows that the incidence of glioblastoma multiforme (astrocytoma grade IV) has increased significantly since the 1980s, especially in the frontal and temporal lobes and cerebellum. However, it further provides evidence that the trend of increasing numbers of newly diagnosed cases of glioblastoma multiforme in the temporal lobe (but likely in the frontal lobe and cerebellum as well) since the mid-1980s, although seemingly consistent with the hypothesis of exposure to radiofrequency radiation from mobile phones being an important putative factor, should to a large extent (if not exclusively) be attributed to another factor or factors; of which improvements in diagnostic techniques, especially in the elderly, seems the most plausible. Although these analyses indicate that it is unlikely that exposure to RF from mobile phones is an important putative factor, they also cannot exclude it as a contributing factor completely. It is therefore important to keep monitoring incidence trend data.

Competing financial interests declaration: The author has previously done consulting for EPRI [Electric Power Research Institute], not related to this work. 

Financial support: No external funding was obtained for this study.

Mar 25, 2018

England: Rates of Aggressive Brain Cancer Increased from 1995 to 2014

A newly-published study of brain tumor incidence trends in England from 1995 to 2014 found that the trends over time varied by type of cancer, especially in the frontal and temporal lobes.

The study found “a sustained and highly statistically significant” increase in glioblastoma multiforme (GBM), the most common brain cancer, across all ages. The rate of GBM more than doubled from 2.4 to 5.0 per 100,000 people. However, this increase was mostly hidden because the overall malignant brain tumor trend was relatively flat due to a reduced incidence of lower grade brain tumors.

In England in 1995, when the tumor site was specified at the time of diagnosis, the frontal or temporal lobes of the brain accounted for 41% of malignant brain tumors. By 2015, these two sites accounted for 60% of the tumors.

One cannot know from tumor registry data alone what caused these differential trends in brain cancer. Based upon epidemiologic research, the most compelling explanation for the increased incidence in these deadly brain tumors, especially in the frontal and temporal lobes, may be exposure to microwave radiation due to widespread adoption of cell phones. However, the increased use of CT imaging scans is an alternative, but less compelling, explanation because far fewer people would have been exposed to this form of ionizing radiation.

In the U.S., Zada and his colleagues (2012) obtained similar results in an analysis of national tumor registry data from 1992 to 2006.

Those who cite statistics which appear to show a flat-line trend in overall brain tumor incidence and argue that cell phone use doesn’t cause brain cancer need to examine data on the location and type of brain tumors over time.

Also see:

Microwave News. “Aggressive Brain Tumors on the Rise in England.” March 25, 2018.

Source: Alasdair Philips via Microwave News.


Brain tumours: rise in Glioblastoma Multiforme incidence in England 1995–2015 suggests an adverse environmental or lifestyle factor

Alasdair Philips, Denis L. Henshaw, Graham Lamburn, and Michael O'Carroll. Brain tumours: rise in Glioblastoma Multiforme incidence in England 1995–2015 suggests an adverse environmental or lifestyle factor. Journal of Environmental and Public HealthArticle ID 7910754, 2018.


• A clear description of the changing pattern in incidence of brain tumour types
• The study used extensive data from an official and recognised quality source
• The study included histological and morphological information
• The study identified a significant and concerning incidence time trend
• Some evidence is provided to help guide future research into causal mechanisms


Objective To investigate detailed trends in malignant brain tumour incidence over a recent time period.

Methods UK Office of National Statistics (ONS) data covering 81,135 ICD10 C71 brain tumours diagnosed in England (1995–2015) were used to calculate incidence rates (ASR) per 100k person–years, age–standardised to the European Standard Population (ESP–2013).

Results We report a sustained and highly statistically significant ASR rise in glioblastoma multiforme (GBM) across all ages. The ASR for GBM more than doubled from 2.4 to 5.0, with annual case numbers rising from 983 to 2531. Overall, this rise is mostly hidden in the overall data by a reduced incidence of lower grade tumours.

Conclusions The rise is of importance for clinical resources and brain tumour aetiology. The rise cannot be fully accounted for by promotion of lower–grade tumours, random chance or improvement in diagnostic techniques as it affects specific areas of the brain and only one type of brain tumour. Despite the large variation in case numbers by age, the percentage rise is similar across the age groups which suggests widespread environmental or lifestyle factors may be responsible.


1/. We show a linear, large and highly statistically significant increase in primary GBM tumours over 21 years from 1995–2015, especially in frontal and temporal lobes of the brain. This has aetiological and resource implications.
2/. Although most of the cases are in the group over 54 years of age, the age–standardised AAPC rise is strongly statistically significant in all our three main analysis age groups.

3/. The rise in age–standardised incidence cannot be fully accounted for by improved diagnosis as it affects specific areas of the brain and just one type of brain tumour which is generally fatal. We suggest that widespread environmental or lifestyle factors may be responsible.

4/. Our results highlight an urgent need for funding more research into the initiation and promotion of GBM tumours. This should include the use of CT imaging for diagnosis and also modern lifestyle factors that may affect tumour metabolism.