Cell Phones and Cancer: What’s the Real Risk?
On May 27, 2016 the National Toxicology Program (NTP), a research arm of the Department of Health and Human Services, published a report of partial findings from their cell phone carcinogenesis studies.1 The information contained within the report fanned the flames of a now almost quarter-century old debate over the relationship between cell phone use and cancer.
The NTP data showed that between 2.2-3.3% of rats in the experimental group developed gliomas, a frequently aggressive type of brain tumor.1 Before we dissect this data further, we must first examine some of the foundational details of the cell phone-cancer debate. Also we should add the disclaimer that we will be focusing on gliomas in this article due to their malignant nature, and we will largely ignore other less aggressive forms of CNS tumors with questionable links to cell phone use.
Cell phones use a type of non-ionizing electromagnetic radiation known as radiofrequency radiation to facilitate communication.2 Electromagnetic radiation consists of electric and magnetic energy radiating together through space at the speed of light.3 The various subtypes of electromagnetic radiation are generally categorized by their wavelength and frequency; as frequency increases, wavelength decreases.3 The spectrum of electromagnetic radiation stretches from low frequency radio waves, to infrared, to visible light, to ultraviolet, to high frequency X-rays, and finally to the highest frequency, gamma rays.4
The term, radiation, describes the movement of electromagnetic wave or particle energy through space, and does not imply radioactivity.4 Only very high frequency radiation, specifically, X-ray or gamma ray radiation, can damage human DNA through a process of ionization.2 So-called ionizing radiation can be juxtaposed with lower frequency non-ionizing radiation that stretches from low frequency radiofrequency radiation to higher frequency ultraviolet radiation.4 Non-ionizing radiation generally does not produce a high enough frequency, and thus energy, to damage DNA.2 It is for these reasons that repeated, excessive, and long-term exposure to ionizing radiation has been shown to increase the risk of developing some types of cancer, while non-ionizing radiation has not been shown to increase the risk of cancer.2
To reiterate our earlier point, cell phones use a type of non-ionizing radiation known as radiofrequency radiation (RFR) to facilitate communication. The RFR frequency utilized by cell phones falls towards the bottom end of the microwave radiation subset of the larger RFR spectrum.3 The only consequence of RFR exposure that researchers have found evidence for in biological systems is a transient heating effect.2 However, in the example of cell phone emitted RFR, this change in temperature in human tissue is vanishingly small.5
Large epidemiological studies have tried to answer the question of whether cell phone use is related to an increased risk of cancer despite the associated radiation being non-ionizing in nature. The INTERPHONE case-control study examined the correlation between 5,000 people diagnosed with brain tumors (including gliomas) and cell phone use.6 The INTERPHONE study could not establish a clear relationship between the frequency and duration of cell phone use and the development of brain tumors.6
Another study, the Danish prospective cohort study examined approximately 400,000 people, spanned more than 2 decades, and again did not reveal any increased risk of brain tumors among those who used cell phones.6 And in yet another large-scale study known as the Million Women cohort study, almost 800,000 women were followed for 7 years and this study too did not find a link between cell phone use and the development of gliomas.6
Researchers have estimated that even if cell phone use required a latency of 10 years and possessed a very low relative risk of causing cancer, we should have seen a rise in glioma incidence 40% higher than that which we have observed over the preceding decades.7 In fact, between 1992 and 2008 glioma incidence has remained relatively constant.7
Despite the consistently negative results of the aforementioned studies, there are limitations inherent to their study design that have necessitated further study. As a result of the remaining uncertainty, as well as some contradictory evidence in animals, the International Agency for Research on Cancer (IARC) declared RFR from cell phones as “possibly carcinogenic to humans” in 2013.8 One should note that the IARC also declared coffee to be “possibly carcinogenic to humans” in 1991 before revising this classification in June 2016, stating that there was “inadequate evidence” for carcinogenicity.9 We must remember that knowledge evolves with time, and the current NTP study in rats is one of the latest attempts to clarify the relationship between cell phone use and cancer.
There is a final piece of information we have to review before we return to the NTP study. Scientists use the specific absorption rate (SAR) to estimate the rate at which RFR is absorbed by the human body. The Federal Communications Commission (FCC) has set a SAR of 1.6 W/kg as the limit for consumer electronics.3 There is minimal data to support this limit, but the FCC used the best information available in creating the guideline.3
Now that we have established a foundational understanding of the historical debate over cell phone use and cancer, let’s return to the NTP study.
The 2.2-3.3% prevalence of gliomas noted in the cell phone exposed group has some important caveats. First, the statistically significant increase in prevalence was only found in male rats.1 Second, the control base rate of gliomas in male rats of the variety used in the NTP study is normally 2%.1 The reason that the increased prevalence of gliomas in the NTP study was statistically significant in the experimental group was due to the fact that the control group did not develop any gliomas.1 However, if the control group had developed gliomas at the rate expected of this strain of rat, the finding in the experimental group would not have been statistically significant.1 It also bears repeating that the NTP study found no statistically significant biological effects of RFR exposure in female rats.1 Finally, the rats were first exposed in utero and received 9 hours of exposure per day, 7 days a week, for their entire lives.1
Setting aside the aforementioned caveats, let’s look at the experimental design more closely. Experimenters tested 900 megahertz GSM- and CDMA-modulated RFR at a SAR of 1.5, 3, and 6 W/kg.1 GSM and CDMA stand for Global System for Mobiles and Code Division Multiple Access respectively. GSM and CDMA are 2 different RFR technologies used by different cell phone carriers to transmit information.
The 2.2-3.3% prevalence in male rat gliomas was found in all SAR levels of GSM-modulated RFR exposure, but only in the 6 W/kg CDMA-modulated radiofrequency.1 We should recall that the FCC limits consumer electronics to 1.6 W/kg in the US, and as such, the CDMA-modulated RFR at FCC limits would be highly unlikely to cause any carcinogenic effects based on the NTP findings. As to the GSM-modulated RFR, in the US, only AT&T and T-Mobile use it; Sprint, Verizon, and US Cellular use CDMA technology.10
We must await the completion of the NTP study at the end of 2017 to evaluate the data in full before we draw any definitive conclusions.11 In particular, similar experimental protocols are being conducted in mice and this data is not available yet.11 Another study that may add to our current state of knowledge is known as COSMOS. COSMOS is a prospective cohort study that began in 2010, includes almost 300,000 participants, and plans to follow participants for 20-30 years.2 But until such time that more data becomes available, what are we to do with the information at hand?
The National Institutes of Health, the American Cancer Society, and other major organizations have suggested various strategies to minimize the potential risks associated with cell phone use.2,3,6,8 Although some have argued that SAR is an imperfect system for evaluating the biological risk associated with cell phones,5 it is currently the consensus measurement used to evaluate risk. Numerous potential risk reduction strategies seek to reduce SAR, and thus risk.
One of the editors on the MindfulnessMD staff has an IPhone 6 plus that we used for testing purposes. Information available on Apple.com indicates that the SAR of the IPhone 6 plus model A1522 is 1.16 W/kg (over 1 gram of tissue) when 5mm from the body.12 This value represents the highest RFR output level of the phone and falls well below the 1.6 W/kg SAR limit required by the FCC. However, if the data from the NTP study is accurate, even a level of 1.5 W/kg of GSM-modulated RFR may increase the risk of gliomas (at least in rats… in one study). So, if we choose to believe this data and would like to reduce our risk, what can we do?
The first option would be to use the speaker phone feature or a corded headset when making telephone calls. For reasons that will become clear in a moment, moving a cell phone away from the body, even a short distance, dramatically reduces RFR exposure.2 Both speaker phone and a corded headset will reduce RFR exposure to essentially zero if the cell phone is placed a sufficient distance from the body.6
A second option to reduce SAR exposure would be to use a Bluetooth headset, which generally produces a SAR of about 0.001 W/kg.6 A third option takes advantage of the dynamic RFR use of cell phones. Cell phones use more energy, producing a greater SAR when there is low signal.3 Thus, limiting calls to areas of good signal will reduce RFR exposure.
The fourth and final option for reducing RFR exposure and SAR is revealed by the inverse square law. The inverse square law in physics states that the intensity (I) of electromagnetic radiation (such as RFR) is proportional to the source strength of the radiation (S) divided by the sphere area of radiation dispersal (4πr2).13 The complete equation can be represented as I = S / (4πr2). For our purposes, this equation can be thought of as I = 1 / r2, where r is the radius of the sphere that defines the distance of the intensity (I) measurement from the source of radiation (S). This simplification reveals that if the distance from an RFR source doubles, r (radius) also doubles, and as a result, the intensity of the radiation field is reduced to one-quarter of the original intensity. If we triple the distance from our source (e.g. a cell phone) from ourselves (the measurement point for I), we reduce the intensity of radiation to one-ninth that of the original source strength. One can see the general trend towards an exponential decline in intensity whereby, at 10 times the original distance, we will have reduced the intensity to 1% of the source strength. Let’s try to quantify this further with our IPhone 6 plus example.
The 1.16 W/kg maximum SAR was measured at 5mm from the body. A US nickel is 1.95mm thick,14 thus, the distance from cell phone to body used to arrive at the aforementioned SAR was equivalent to a little more than 2 nickels stacked atop one another.
For the purposes of our ensuing discussion we will assume that SAR is directly proportional to intensity (I) and thus distance; however, in reality SAR tends to decrease at different rates as one moves from near-field to far-field.15 That being said, for the purposes of illustrating the law of inverse squares in cell phones, we will ignore this subtly and provide the disclaimer as well as the source material for those interested in learning more.
Returning to our example, if we were to increase the distance of our IPhone 6 plus from our body to the diameter of a dime (17.91mm),14 we would have reduced the intensity of RFR exposure to almost one-thirteenth of the initial intensity, or a SAR of about 0.08 W/kg.13 Increasing the distance to that of the diameter of a regulation soccer ball (around 230mm),16 we would have reduced the intensity to more than one two-thousandth of the original intensity, or a SAR of a little more than 0.0005 W/kg, about half the SAR of a Bluetooth headset. As noted before, SAR is not so simply calculated, but this illustrates the significant impact of moving a radiation source away from the body.
Now that we have discussed potential risk reduction strategies let’s turn to a more pressing question: how much should we worry about this?
The highest estimated relative risk of glioma development in cell phone users from an adequately powered study, putting aside methodological issues for the moment, is 2.5 times that of a non-cell phone user.17 The lifetime risk of developing a glioma in the general population is approximately 0.16% (the lifetime risk of brain or CNS tumor is 0.6%18 and approximately 27%19 of brain tumors are gliomas). If we use the highest estimate of relative risk to predict the lifetime risk of developing a glioma with cell phone exposure, we arrive at an approximate 0.4% risk (incidentally, this value is close to the approximate 0.46%18 lifetime risk of dying from any brain or CNS tumor). This is a generous estimate for various reasons, not least of which is that the largest and most methodologically sound studies have failed to find any increased risk of glioma with cell phone use.2
As a species, we are terrible at assessing risk. Our previous article, Risk Perception: From Ebola to Airplanes summarizes the various errors that we make when assessing risk. There are numerous reasons why our evaluation of the risk of developing a brain tumor is wrought with errors, but perhaps the most significant contributor to these errors is known as the availability heuristic. The availability heuristic basically says that when we can more easily and vividly imagine a scenario (e.g. when that scenario is awful and scary), we tend to dramatically overestimate risk. The solution? Run the numbers.
Your risk of dying from a fall is almost 200% that of your risk of developing a glioma, even at the inflated rate we estimated for worst-case cell phone use.20 Your risk of dying in a motor vehicle accident or by unintentional poisoning is more than 200% that of your risk of developing a glioma.20 Your risk of dying from intentional self-harm is almost 250% that of your risk of developing a glioma.20 Your risk of dying from a chronic lower respiratory disease is almost 1,000% that of your risk of developing a glioma.20 And finally, your risk of dying from another cancer or heart disease is almost 3,600% that of your risk of developing a glioma.20
In conclusion, is it possible that cell phones increase the risk of gliomas and brain tumors? Yes, it’s possible, but a careful analysis of the degree of risk in the worst-case scenario thus imagined suggests that we have many sources of mortality that are far more likely and occupy far less of our mental time. For now, we will await further evidence and perhaps consider speaker phone options when in private.
- Wyde M, Cesta M, Blystone C, et al. Report of Partial Findings from the National Toxicology Program Carcinogenesis Studies of Cell Phone Radiofrequency Radiation in Hsd: Sprague Dawley® SD Rats (Whole Body Exposure).; 2016. http://biorxiv.org/lookup/doi/10.1101/055699. Accessed June 26, 2016.
- National Institutes of Health. Cell phones and cancer risk. Cancer.gov. http://www.cancer.gov/about-cancer/causes-prevention/risk/radiation/cell-phones-fact-sheet#q2. Accessed June 25, 2016.
- Federal Communications Commission. Radio frequency safety. FCC.gov. https://www.fcc.gov/general/radio-frequency-safety-0. Accessed June 25, 2016.
- UCDavis.edu. Electromagnetic Radiation. http://chemwiki.ucdavis.edu/Core/Physical_Chemistry/Spectroscopy/Fundamentals/Electromagnetic_Radiation. Published October 2, 2013. Accessed June 30, 2016.
- Panagopoulos DJ, Johansson O, Carlo GL. Evaluation of Specific Absorption Rate as a Dosimetric Quantity for Electromagnetic Fields Bioeffects. PLoS ONE. 2013;8(6). doi:10.1371/journal.pone.0062663.
- American Cancer Society. Cellular phones. Cancer.org. http://www.cancer.org/cancer/cancercauses/othercarcinogens/athome/cellular-phones. Accessed June 25, 2016.
- Little MP, Rajaraman P, Curtis RE, et al. Mobile phone use and glioma risk: comparison of epidemiological study results with incidence trends in the United States. BMJ. 2012;344(mar08 1):e1147-e1147. doi:10.1136/bmj.e1147.
- IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, World Health Organization, International Agency for Research on Cancer, eds. Non-Ionizing Radiation. Radiofrequency Electromagnetic Fields. Part 2. Lyon: International Agency for Research on Cancer; 2013.
- International Agency for Research on Cancer. IARC Monographs evaluate drinking coffee, maté, and very hot beverages. https://www.iarc.fr/en/media-centre/pr/2016/pdfs/pr244_E.pdf. Accessed June 28, 2016.
- Sascha Segan. CDMA vs. GSM: What’s the difference? PCMag. http://www.pcmag.com/article2/0,2817,2407896,00.asp. Accessed June 26, 2016.
- National Toxicology Program. Cell phones. http://ntp.niehs.nih.gov/results/areas/cellphones/. Accessed June 29, 2016.
- Apple. RF exposure – iPhone 6 plus. Apple.com. http://www.apple.com/legal/rfexposure/iphone7,1/en/. Accessed June 25, 2016.
- Georgia State University. Inverse square law. Hyperphysics. http://hyperphysics.phy-astr.gsu.edu/hbase/forces/isq.html#c4. Accessed June 25, 2016.
- United States Mint. The United States mint about us. USmint.gov. https://www.usmint.gov/about_the_mint/?action=coin_specifications.
- Zhang M, Alden A. CALCULATION OF WHOLE-BODY SAR FROM A 100 MHZ DIPOLE ANTENNA. Prog Electromagn Res. 2011;119:133-153. doi:10.2528/PIER11052005.
- FIFA. Laws of the game – FIFA quality Programme. http://quality.fifa.com/en/Footballs/Quality-Programme-for-Footballs/Laws-of-the-Game/.
- Benson VS, Pirie K, Schuz J, et al. Mobile phone use and risk of brain neoplasms and other cancers: prospective study. Int J Epidemiol. 2013;42(3):792-802. doi:10.1093/ije/dyt072.
- National Institutes of Health. Cancer of the brain and other nervous system. National Cancer Institute SEER stat fact sheets. http://seer.cancer.gov/statfacts/html/brain.html. Accessed June 26, 2016.
- American Brain Tumor Association. Brain tumor statistics. http://www.abta.org/about-us/news/brain-tumor-statistics/. Accessed June 26, 2016.
- National Safety Council. National Safety Council Injury Facts 2016. S.l.: Natl Safety Council; 2016.