One goal of Intermediate Physics for Medicine and Biology is to provide readers with an understanding of the physics underlying biomedicine, so they can recognize and refute pseudoscientific ideas. For instance, in Chapter 9 of IPMBRuss Hobbie and I discuss the physics behind the discredited claim that weak, low frequency electromagnetic fields (ranging in frequency from 60 Hz powerline fields to cell phone radiowaves) are dangerous.
These days, with so much pseudoscience parading as fact, and with the United State’s Secretary of the Department of Health and Human Services being a leading proponent of anti-science nonsense, what we need is something to point out and refute all this quackery. What we need is Quackwatch.org. According Quackwatch’s mission statement,
Quackwatch is a network of Web sites and mailing lists developed by Stephen Barrett, M.D. and maintained by the Center for Inquiry (CFI). Their primary focus is on quackery-related information that is difficult or impossible to get elsewhere. Dr. Barrett’s activities include:
Investigating questionable claims
Answering inquiries about products and services
Advising quackery victims
Distributing reliable publications
Debunking pseudoscientific claims
Reporting illegal marketing
Improving the quality of health information on the Internet
Attacking misleading advertising on the Internet
For those of you who prefer social media, you can follow Quackwatch on Facebook and Twitter.
Quackwatch was established by Stephen Barrett, a retired medical doctor. These days he’s in his 90’s and deserves a rest after a lifetime of defending science. Unfortunately, there’s no rest for the weary; we need him now more than ever.
Hotez’s book provides insight into the challenges faced by parents with autistic children (by the way, Peter Hotez is not the hero of this book; the hero is his wife Ann). Moreover, the book makes a compelling argument that vaccines do not cause autism. Hotez reviews much of the scientific literature relevant to the relationship of vaccines to autism. In particular, he mentions a meta-analysis of clinical studies published by a group from Australia. As much as I enjoyed and admired Hotez’s book, I probably would have led off by discussing that publication, rather than waiting until late in the book to bring it up.
There has been enormous debate regarding the possibility of a link between childhood vaccinations and the subsequent development of autism. This has in recent times become a major public health issue with vaccine preventable diseases increasing in the community due to the fear of a ‘link’ between vaccinations and autism. We performed a meta-analysis to summarise available evidence from case-control and cohort studies on this topic (MEDLINE, PubMed, EMBASE, Google Scholar up to April, 2014). Eligible studies assessed the relationship between vaccine administration and the subsequent development of autism or autism spectrum disorders (ASD). Two reviewers extracted data on study characteristics, methods, and outcomes. Disagreement was resolved by consensus with another author. Five cohort studies involving 1,256,407 children, and five case-control studies involving 9,920 children were included in this analysis. The cohort data revealed no relationship between vaccination and autism (OR: 0.99; 95% CI: 0.92 to 1.06) or ASD (OR: 0.91; 95% CI: 0.68 to 1.20), nor was there a relationship between autism and MMR (OR: 0.84; 95% CI: 0.70 to 1.01), or thimerosal (OR: 1.00; 95% CI: 0.77 to 1.31), or mercury (Hg) (OR: 1.00; 95% CI: 0.93 to 1.07). Similarly the case-control data found no evidence for increased risk of developing autism or ASD following MMR, Hg, or thimersal exposure when grouped by condition (OR: 0.90, 95% CI: 0.83 to 0.98; p = 0.02) or grouped by exposure type (OR: 0.85, 95% CI: 0.76 to 0.95; p = 0.01). Findings of this meta-analysis suggest that vaccinations are not associated with the development of autism or autism spectrum disorder. Furthermore, the components of the vaccines (thimersal or mercury) or multiple vaccines (MMR) are not associated with the development of autism or autism spectrum disorder.
Some of the terms and concepts mentioned in the abstract may be unfamiliar, so let me explain them.
Autism and Autism Spectrum Disorders. Autism is a disorder of the nervous system that begins during the development of a fetus. An autistic person may engage in repetitive, inflexible behaviors or have problems interacting with people. The disorder can vary in its severity and symptoms, so people with different degrees of severity are said to be on the autism spectrum.
Vaccine. A vaccine is a biological agent that stimulates a person’s immune system to recognize and destroy a microorganism causing an infectious disease. Vaccines are often made from a weakened form of the microbe.
The MMR Vaccine. The MMR vaccine protects children against three diseases: measles, mumps, and rubella (German measles). An initial dose of the MMR vaccine is typically given around a child’s first birthday and a second dose before entering school. It’s usually given by injection.
Thimersal-Containing Vaccine. Thimersal is a molecule containing mercury. The element mercury, whose chemical symbol is Hg, is a known toxin. However, not all molecules containing mercury are as toxic as is mercury metal itself. Mercury compounds like thimersal are used in low doses as a preservative in some vaccines. Before 1991, thimersal was included in the childhood vaccine DPT which protects against diphtheria, tetanus (lockjaw), and pertussis (whopping cough). Now no childhood vaccines contain thimersal, although it’s still used in some flu vaccines.
Meta-Analysis. Meta-analysis is a statistical method of analyzing and summarizing several clinical trials. A meta-analysis can increase the number of patients being analyzed, resulting a more statistical power. It can also help in resolving studies with inconsistent results.
Case-Control Study. A case-control study is a clinical study that compares two groups: one having a disease and one not (the control). It is often retrospective, meaning it uses existing data from people known to have a disease, and therefore can be conducted quickly.
Cohort Study. A cohort study is a clinical trial that takes a group of people and follows them through time to determine what fraction develop some disease. It is prospective, collecting data on exposure to some suspected cause. A cohort study can take a long time to complete and, for a rare disease, requires studying a large population, but it’s less susceptible to bias than a case-control study.
Odds Ratio. The odds ratio (OR) is a statistical measure to determine if some factor has an effect. For example, suppose in a case-control study you examined the medical records of 600 people who had the MMR vaccine; 570 were healthy but 30 had autism (the odds of being healthy are 570:30, or 19:1). As a control, you examined the medical records of 400 people who did not have the MMR vaccine; 380 were healthy but 20 had autism (the odds of being healthy are 380:20, or 19:1). In that case, the odds ratio would be
When the odds ratio is one, you conclude the MMR vaccine had no effect (the odds of having autism are the same whether or not you had the vaccine). If, however, among the 600 people who had the MMR vaccine 510 were healthy and 90 had autism (with the control group being unchanged from that given above) then the odds ratio would be
In this case, the MMR vaccine would have a clear effect. For smoking and lung cancer, the odds ratio is quite large, about 10.
95% Confidence Interval. How large must the odds ratio be in order to
conclude there is some effect? That depends on how much uncertainty
there is. For instance, if you flip a coin four
times, the most likely result is two heads and two tails. However, there
is still one chance out of sixteen, about 6%, that you’ll get four
heads. If you want to be more certain that a coin is fair and not
biased, you would need to flip the coin more than four times. In the
same spirit, to completely characterize how much confidence you have in
the result of a clinical trial, you must indicate how large the
uncertainty is in the result. Most clinical studies will give the odds
ratio and a range of values for which—based on a statistical
analysis—there is a 95% chance that the odds ratio is within that
interval. The convention is that if the 95% confidence interval does not
contain the value of one, then there is a statistically significant effect. If it does contain one, any effect is not statistically
significant. Using a value of 95%, rather than say 98%, is arbitrary,
but you have to draw the line somewhere, and 95% confidence is the usual
medical criteria for significance. For example, if in one of these autism studies the odds ratio was 1.05 and the 95% confidence interval
was 0.8 to 1.3, you would conclude that there is not a statistically
significant effect of the vaccine. If, on the other hand, the odds
ratio were 1.05 and the 95% confidence interval was 1.02 to 1.08, you
would conclude there is a small but statistically significant effect of the vaccine on
autism. Note that in statistics the word “significance” does not mean
“important.” It means “unlikely to be due to chance.” One
virtue of a meta-analysis is that by combining several studies the
number of people analyzed increases, which can shrink the 95% confidence
range, which provides better statistical power to say if the odds
ratio is significantly different than one.
p-value. Whenever you have an arbitrary threshold, like saying a result is or is not statistically significant, you worry about cases that are near the threshold. To provide additional information, researchers sometimes give the p-value. It is the probability that a result at least this extreme could happen by chance. In medicine, usually p = 0.05 is the cutoff between a result being considered significant or not significant. But if the result has p = 0.03, you might say it is significant (less than 0.05) but you might think that it is still questionable and maybe you should repeat that study with a larger number of people. On the other hand, if p = 0.0002 you would say that the result almost certainly didn’t happen by chance and you would therefore have a lot of confidence in it. In this meta-analysis, the p-value is sometimes given, especially for borderline cases, to help the reader estimate the true significance of the result.
MEDLINE, PubMed, EMBASE, Google Scholar. These databases contain information about scientific publications, including articles describing clinical trials. They can be searched using various keywords to find publications about a particular subject. MEDLINE is a database compiled by the National Library of Medicine, and covers all biomedical research. It can be searched online using a tool called PubMed, which includes MEDLINE plus a few other databases. EMBASE is an international database that focuses on the pharmaceutical industry. Google Scholar is a free web search engine that covers all scholarly publications.
Now that we understand the vocabulary, what does this meta-analysis show? It indicates that there is no evidence supporting a connection between vaccines and the development of autism. It also shows there is no risk that thimersal or mercury causes autism. In fact, some of the results suggest a weak protective effect caused by thimersal. For example, an odds ratio of 0.85 with a 95% confidence interval of 0.76 to 0.95 suggests that the odds ratio may be slightly less than one, which means the vaccine prevents people from getting autism. However, the p-value for this result was 0.01 which is small but not that small, and I wouldn’t put too much confidence in the claim that the vaccine is protective. But the results sure don’t suggest there is a health risk.
What I’ve analyzed today is one paper, albeit a meta-analysis. It’s over ten years old. There are lots of other data out there now, and Hotez describes some of it in Vaccines Did Not Cause Rachel’s Autism. He also emphasizes that autism is thought to arise from problems during the development of a fetus, long before the child receives any vaccines, so there’s no reason to suspect vaccines as a cause of autism. All this evidence, taken together, implies the probability of vaccines causing autism is extremely low.
Why do people still claim vaccines cause autism? There will certainly be cases where a child will receive a vaccine and then start showing symptoms of being on the autism spectrum. Some might point to such cases and say “see, I told you so!” The question is, how many of those children would have started showing symptoms of autism even if they didn’t get the vaccine? Homework problem 9 in Chapter 3 of Intermediate Physics for Medicine and Biology explores this type of question quantitatively. The reason you need a large, controlled statistical study is so you’re not fooled by a few such coincidences.
One thing clinical studies, such as the one that I discussed today, cannot give you is certainty. You can’t say with absolute certainty (p = 0) that vaccines don’t cause autism. Science doesn’t deal in certainties, just probabilities. All you can say is that the evidence suggests there is no connection between vaccines and autism. The best you can do is to collect enough evidence so that the probability of a relationship is very small. That is where we are today. The probability of vaccines causing autism is extremely low. That’s the best conclusion science can offer. And when the probability is vanishingly small, we often feel confident in summarizing the situation with a simple (if somewhat too simple) declarative sentence, such as Vaccines Did Not Cause Rachel’s Autism.
Outbreak News TV: Vaccines Did Not Cause Rachel's Autism.
Want a sneak peek at one of the new homework problems tentatively included in the 6th edition of Intermediate Physics for Medicine and Biology? Today I present a problem related to the flawed “cyclotron resonance hypothesis.” A lot of nonsense has been written about the idea of extremely low frequency electromagnetic fields influencing biology and medicine, and one of the proposed mechanisms for such effects is cyclotron resonance.
One important application of magnetic forces in medicine
is the cyclotron. Many hospitals have a cyclotron for the
production of radiopharmaceuticals, especially for generating
positron-emitting nuclei for use in Positron EmissionTomography (PET) imaging (see Chap. 17).
Consider a particle of charge q and mass m, moving with
speed v in a direction perpendicular to a magnetic field B.
The magnetic force will bend the path of the particle into a
circle. Newton’s second law states that the mass times the
centripetal acceleration, v2/r, is equal to the magnetic force
mv2/r = qvB. (8.5)
The speed is equal to [the] circumference of the circle, 2πr,
divided by the period of the orbit, T. Substituting this
expression for v into Eq. (8.5) and simplifying, we find
T = 2π m/(qB). (8.6)
In a cyclotron particles orbit at the cyclotron frequency,
f = 1/T. Because the magnetic force is perpendicular to the
motion, it does not increase the particles’ speed or energy. To
do that, the particles are subjected periodically to an electric
field that changes direction with the cyclotron frequency so
that it is always accelerating, not decelerating, the particles.
This would be difficult if not for the fortuitous disappearance
of both v and r from Eq. (8.6), so that the cyclotron frequency
only depends on the charge-to-mass ratio of the particles and
the magnetic field, but not on their energy.
This analysis of cyclotron motion works great in a vacuum. The trouble begins when you apply the cyclotron concept to ions in the conducting fluids of the body. The proposed hypothesis says that when an ion is moving about in the presence of the earth’s magnetic field, the resulting magnetic force causes it to orbit about the magnetic field lines, with an orbital period equal to the reciprocal of the cyclotron frequency. If any electric field is present at that same frequency, it could interact with the ion, increasing its energy or causing it to cross the cell membrane.
Below is a draft of the new homework problem, which I hope debunks this erroneous hypothesis.
Section 9.1
Problem 7. One mechanism for how organisms are influenced by extremely low frequency electric fields is the cyclotron resonance hypothesis.
(a) The strength of the earth's magnetic field is about 5 × 10–5T. A calcium ion has a mass of 6.7 × 10–26kg and a charge of 3.2 × 10–19C. Calculate the cyclotron frequency of the calcium ion. If an electric field exists in the tissue at that frequency, the calcium ion will be in resonance with the cyclotron frequency, which could magnify any biological effect.
(b) This mechanism seems to provide a way for an extremely low frequency electric field to interact with calcium ions, and calcium influences many cellular processes. But consider this hypothesis in more detail. Use Eq. 4.12 to calculate the root-mean-square speed of a calcium ion at body temperature. Use this speed in Eq. 8.5 to calculate the radius of the orbit. Compare this to the size of a typical cell.
(c) Now make a similar analysis, but assume the radius of the calcium ion orbit is about the size of a cell (since it would have difficulty crossing the cell membrane). Then use this radius in Eq. 8.5 to determine the speed of the calcium ion. If this is the root-mean-square speed, what is the body temperature?
(d) Finally, compare the period of the orbit to the time between collisions of the calcium ion with a water molecule. What does this imply for the orbit?
This analysis should convince you that the cyclotron resonance hypothesis is unlikely to be correct. Although the frequency is reasonable, the orbital radius will be huge unless
the ions are traveling extraordinarily slowly. Collisions with water molecules will completely disrupt the orbit.
For those who don't have the 5th edition of IPMB handy, Eq. 4.12 says the root-mean-square speed is equal to the square root of 3 times Boltzmann's constant times the absolute temperature divided by the mass of the particle.
I won’t give away the solution to this problem (once the 6th edition of IPMB is out, instructors can get the solution manual for free by emailing me at roth@oakland.edu). But here are some order-of-magnitude results. The cyclotron frequency is tens of hertz. The root-mean-square (thermal) speed of calcium at body temperature is hundreds of meters per second. The resulting orbital radius is about a meter. That is bigger than the body, and vastly bigger than a cell. To fit the orbit inside a cell, the speed would have to be much slower, on the order of a thousandth of a meter per second, which corresponds to a temperature of about a few nanokelvins. The orbital period is a couple hundredths of a second, but the time between collisions of the ion with a water molecule is one the order of 10–13 seconds, so there are many billions of collisions per orbit. Any circular motion will be destroyed by collisions long before anything like an orbit is established. I’m sorry, but the hypothesis is rubbish.
Finally, for you folks who are really on the ball, you may be wondering why this homework problem is listed as being in Chapter 9 when the discussion of the cyclotron is in Chapter 8 of the 5th edition of IPMB. (In this post I changed the equation numbers in the homework problem to match the 5th edition, so you would have them.) Hmm.. is there a new chapter in the 6th edition? More on that later…
To be fair, I should let my late friend Abraham Liboff tell you his side of the story. In this video, Abe explains how he proposed the cyclotron resonance hypothesis. I liked Abe, but I didn’t like his hypothesis.
What is electromagnetic hypersensitivity? It’s an alleged condition in which a person is especially sensitive to weak radiofrequency electromagnetic fields, such as those emitted by a cell phone or other wireless technology. All sorts of symptoms are claimed to be associated with electromagnetic hypersensitivity, such as headaches, fatigue, anxiety, and sleep disturbances. An example of a person who says he has electromagnetic hypersensitivity is Arthur Firstenberg, author of The Invisible Rainbow, a book about his trials and tribulations. Many people purportedly suffering from electromagnetic hypersensitivity flock to Green Bank, West Virginia, because a radiotelescope there requires that the surrounding area being a “radio quiet zone.”
Is electromagnetic hypersensitivity real? Answering this question should be easy. Take people who claim such hypersensitivity, sit them down in a lab, turn a radiofrequency device on (or just pretend to), and ask them if they can sense it. Ask them about their symptoms. Of course, you must do this carefully, avoiding any subtle cues that might signal if the radiation is present. (For a cautionary tale about why such care is important, read this post.) You should do the study double blind (neither the patient nor the doctor who asks the questions should be told if the radiation is or is not on) and compare the patients to control subjects.
The
effects of radiofrequency electromagnetic fields exposure on human
self-reported symptoms.
Many such experiments have been done, and recently a systematic review of the results was published.
This review is part of an ongoing project by the World Health Organization to assess potential health effects from exposure to radiofrequency electromagnetic fields. The authors come from a variety of countries, but several work at the respected Swiss Tropical and Public Health Institute.
I’m particularly familiar with the fine research of Martin Röösli, a renowned leader in this field.
The authors surveyed all publications on this topic and established stringent eligibility criteria so only the highest quality papers were included in their review. A total of 41 studies met the criteria. What did they find? Here’s the key conclusion from the author’s abstract.
The available evidence suggested that study volunteers could not perceive the EMF [electromagnetic field] exposure status better than what is expected by chance and that IEI-EMF [Idiopathic environmental intolerance attributed to electromagnetic fields, their fancy name for electromagnetic hypersensitivity] individuals could not determine EMF conditions better than the general population.
The patients couldn’t determine if the fields were on or off better than chance. In other words, they were right about the field being on or off about as often as if they had decided the question by flipping a coin. The authors added
Available evidence suggests that [an] acute RF-EMF [radiofrequency electromagnetic field] below regulatory limits does not cause symptoms and corresponding claims in... everyday life are related to perceived and not to real EMF exposure status.
Let me repeat, the claims are related “to perceived and not to real EMF exposure.” This means that electromagnetic hypersensitivity is not caused by an electromagnetic field being present, but is caused by thinking that an electromagnetic field is present.
Yes, there are some limitations to this study, which are discussed and analyzed by the authors. The experimental conditions might differ from real-life exposures in the duration, frequency, and location of the field source. Most of the subjects were young, healthy volunteers, so the authors could not make conclusions about the elderly or chronically ill. The authors could not rule out the possibility that a few super-sensitive people are mixed in with a vast majority who can’t sense the fields (although they do offer some evidence suggesting that this is not the case).
Their results do not prove that a condition like electromagnetic
hypersensitivity is impossible. Impossibility proofs are always
difficult in science, and especially in medicine and biology. But the
evidence suggests that the patients’ symptoms are related “to perceived
and not to real EMF exposure.” While I don’t doubt that these patients are
suffering, I’m skeptical that their distress is caused by
electromagnetic fields.
Why read a 35-year old book about a rapidly changing technology like energy? I admit, the book is in some ways obsolete. Cohen insists on using rems as his unit of radiation effective dose, rather than the more modern Sievert (Sv). He discusses the problem of greenhouse gases and global warming, although in a rather hypothetical way as just one of the many problems with burning fossil fuels. He was optimistic about the future of nuclear energy, but we know now that in the decades following the book’s publication nuclear power in the United States did not do well (the average age of our nuclear power plants is over 40 years). Yet other features of the book have withstood the test of time. As our world now faces the dire consequences of climate change, the option of nuclear energy is an urgent consideration. Should we reconsider nuclear power as an alternative to coal/oil/natural gas? I suspect Cohen would say yes.
In Chapter 4 of The Nuclear Energy Option Cohen writes
We have seen that we will need more power plants in the near future, and that fueling them with coal, oil, or gas leads to many serious health, environmental, economic, and political problems. From the technological points of view, the obvious way to avoid these problems is to use nuclear fuels. They cause no greenhouse effect, no acid rain, no pollution of the air with sulfur dioxide, nitrogen oxides, or other dangerous chemicals, no oil spills, no strain on our economy from excessive imports, no dependence on unreliable foreign sources, no risk of military ventures. Nuclear power almost completely avoids all the problems associated with fossil fuels. It does have other impacts on our health and environment, which we will discuss in later chapters, but you will see that they are relatively minor.
He then compares the safety and economics of nuclear energy with other options, including solar and coal-powered plants for generating electricity. Some of the conclusions are surprising. For instance, you might think that energy conservation is always good (who roots for waste?). But Cohen writes
Another energy conservation strategy is to seal buildings more tightly to reduce the escape of heat, but this traps unhealthy materials like radon inside. Tightening buildings to reduce air leakage in accordance with government recommendations would give the average American an LLE [loss of life expectancy] of 20 days due to increased radon exposure, making conservation by far the most dangerous energy strategy from the standpoint of radiation exposure!
His Chapter 8 on Understanding Risk is a classic. He begins
One of the worst stumbling blocks in gaining widespread public acceptance of nuclear power is that the great majority of people do not understand and quantify the risks we face. Most of us think and act as though life is largely free of risk. We view taking risks as foolhardy, irrational, and assiduously to be avoided….
Unfortunately, life is not like that. Everything we do involves risk.
He then makes a catalog of risks, in which he converts risk to the average expected loss of life expectancy for each case. This LLE is really just a measure of probability. For instance, if getting a certain disease shortens your life by ten years, but there is only one chance out of a hundred of contracting that disease, it would correspond to an LLE of 0.1 years, or 36 days. In his catalog, the riskiest activity is living in poverty, which has an LLE of 3500 days (almost ten years). Smoking cigarettes results in an LLE of 2300 days. Being 30 pounds overweight is 900 days. Reducing the speed limit on our highways from 65 to 55 miles per hour would reduce traffic accidents and give us an extra 40 days. At the bottom of his list is living near a nuclear reactor, with a risk of only 0.4 days (less than ten hours). He makes a compelling case that nuclear power is extraordinarily safe.
Cohen summarizes these risks in a classic figure, shown below.
Figure 1 from Chapter 8 of The Nuclear Energy Option.
Our poor risk perception causes us (and our government) to spend money foolishly. He translates societies efforts to reduce risk into the cost in dollars to save one life.
The $2.5 billion we spend to save a single life in making nuclear power safer could save many thousands of lives if spent on radon programs, cancer screening, or transportation safety. This means that many thousands of people are dying unnecessarily every year because we are spending this money in the wrong way.
He concludes
The failure of the American public to understand and quantify risk must rate as one of the most serious and tragic problems for our nation.
I agree.
Cohen believes that Americans have a warped view of the risk of nuclear energy.
The public has become irrational over fear of radiation. Its understanding of radiation dangers has virtually lost all contact with the actual dangers as understood by scientists.
Apparently conspiracy theories are a problem we face not only today but also decades ago, when the scientific establishment was accused of hiding the “truth” about radiation risks. Cohen counters
To believe that such highly reputable scientists conspired to practice deceit seems absurd, if for no other reason than that it would be easy to prove that they had done so and the consequences to their scientific careers would be devastating. All of them had such reputations that they could easily obtain a variety of excellent and well-paying academic positions independent of government or industry financing, so they were to vulnerable to economic pressures.
But above all, they are human beings who have chosen careers in a field dedicated to protection of the health of their fellow human beings; in fact, many of them are M.D.’s who have foregone financially lucrative careers in medical practice to become research scientists. To believe that nearly all of these scientists were somehow involved in a sinister plot to deceive the public indeed challenges the imagination.
What do I think? I would love to have solar and wind supply all our energy needs. But until they can, I vote for increasing our use of nuclear energy over continuing to burn fossil fuels (especially coal). Global warming is already bad and getting worse. It is a dire threat to us all and to our future generations. We should not rule out nuclear energy as one way to address climate change.
Happy birthday, Bernard Cohen! I think if you had lived to be 100 years old, you would have found so many topics to write about today. How we need your rational approach to risk assessment.
Firing Line with William F. Buckley Jr.: The Crisis of Nuclear Energy.
One of the key ideas in my book is the clinical trial. Critical thinking lies at the heart of such trials. In the chapter about the health effects of magnets, I discuss the importance of clinical trials being double blind, randomized, and placebo controlled. Why are these features crucial? They keep you from fooling yourself. In particular, a study being double blind (meaning that “not only the patient, but also the physician, does not know who is in the placebo or treatment group”) is vital to prevent a doctor from inadvertently signalling to the patient which group they are in. One of Trecek-King’s favorite sayings is the quote by Richard Feynman that “you must not fool yourself—and you are the easiest person to fool.” That sums up why double blinding is so important.
Placebos are discussed several times in my book. My favorite example of a placebo comes from a clinical trial to evaluate a new drug. “If a medication is being tested, the placebo is a sugar pill with the same size, shape, color, and taste as that of the drug.” One reason I dwell on placebos is that sometimes they are difficult to design. When testing if permanent magnets can reduce pain, “this means that some patients received treatment with real magnets, and others were treated with objects that resembled magnets but produced a much weaker magnetic field or no magnetic field at all.” It is hard to make a “fake magnet” or a “mock transcranial direct current stimulator.” Yet, designing the placebo is exactly a situation where critical thinking skills are essential.
Critical thinking overlaps with the scientific method, with its emphasis on examining the evidence. In Are Electromagnetic Fields Making Me Ill?, my goal was to present the evidence and then let the reader decide what to believe. But that’s hard. For instance, the experimental laboratory studies about the biological effects of cell phone radiation are a mixed bag. Some studies see effects, and some don’t. You can argue either way depending on what studies you emphasize. I tried to rely on critical reviews to sort all this out (after all, where better to find critical thinking than in a critical review). But even the critical reviews are not unanimous. I probably should’ve examined each article individually and weighed its pros and cons, but that would have taken years (the literature on this topic is vast).
Trecek-King often discusses the importance of finding reliable sources of information. I agree, but this too is not always easy. For instance, what could be more authoritative than a report produced by the National Academy of Sciences? In Are Electromagnetic Fields Making Me Ill? I laud the Stevens report published in the 1990s about the health hazards (or should I say lack of hazards) from powerline magnetic fields. Yet, I’m skeptical about the National Academies report published in 2020 regarding microwave weapons being responsible for the Havana Syndrome. What do I conclude? Sometimes deferring to authority is useful, but not always. You can’t delegate critical thinking.
I have found that one useful tool for teaching and illustrating critical thinking are the Point/Counterpoint articles published in the journal Medical Physics. In Are Electromagnetic Fields Making Me Ill? I cite three such articles, on magnets reducing pain, on cell phone radiation causing cancer, and on the safety of airport backscatter radiation scanners. Each of these articles are in the form of a debate, and any lack of critical thinking will be exposed and debunked in the rebuttals. I wrote
When I taught medical physics to college students, we spent 20 minutes each Friday afternoon discussing a point/counterpoint article. One feature of these articles that makes them such an outstanding teaching tool is that there exists no right answer, only weak or strong arguments. Science does not proceed by proclaiming
universal truths, but by accumulating evidence that allows us to be more or less confident in our hypotheses. Conclusions beginning with “the evidence suggests…” are the best science has to offer.
One skill I emphasized in my teaching using IPMB, but which I don’t see mentioned by Trecek-King, is estimation. For instance, when discussing the potential health benefits or hazards of static magnetic fields, I calculated the energy of an electron in a magnetic field and compared it to its thermal energy. Such a simple order-of-magnitude estimate shows that thermal energy is vastly greater than magnetic energy, implying that static magnetic fields should have no effect on chemical reactions. Similarly, in my chapter about powerline magnetic fields, I estimated the electric field induced in the body by a 60 Hz magnetic field and compare it to endogenous electric fields due mainly to the heart’s electrical activity. Finally, in my discussion about cell phone radiation I compared the energy of a single radio-frequencyphoton to the energy of a chemical bond to prove that cell phones cannot cause cancer by directly disrupting DNA. This ability to estimate is crucial, and I believe it should be included under the umbrella of critical thinking skills.
In the video I watched, Trecek-King discussed the idea of consensus, and the different use of this term among scientists and nonscientists. When I analyzed transcranial direct current stimulation, I bemoaned the difficulty in finding a consensus among different research groups.
Finding the truth does not come from a eureka moment, but instead from a slow slog ultimately leading to a consensus among scientists.
I probably get closest to what scientists mean by consensus at the close of my chapter on the relationship (actually, the lack of relationship) between 5G cell phone radiation and COVID-19:
Scientific consensus arises when a diverse group of scientists openly scrutinizes claims and critically evaluates evidence.
Consensus is only valuable if it arises from individuals independently examining a body of evidence, debating an issue with others, and coming to their own conclusion. Peer review, so important in science, is one way scientists thrash out a consensus. I wrote
The reason for peer review is to force scientists to convince other scientists that their ideas and data are sound.
Perhaps the biggest issue in critical thinking is bias. One difficulty is that bias comes in many forms. One example is publication bias: “the tendency for only positive results to be published.” Another is recall bias that can infect a case-controlepidemiological study. But the really thorny type of bias arises from prior beliefs that scientists may be reluctant to abandon. In Are Electromagnetic Fields Making Me Ill? I tell the story of how Robert Tucker and Otto Schmidt performed an experiment to determine if people could detect 60 Hz magnetic fields. They spent five years examining their experiment for possible systematic errors, and eventually concluded that 60 Hz fields are not detectable. I wrote “One reason the bioelectric literature is filled with inconsistent results may be that not all experimenters are as diligent as Robert Tucker and Otto Schmitt.”
After listening to Trecek-King’s video, I began to wonder if the Tucker and Schmidt experiment might alternatively be viewed be a cautionary tale about bias. Was their long effort a heroic example of detecting and eliminating systematic error, or was it a bias marathon where they slaved away until they finally came to the conclusion they wanted? I side with the heroic interpretation, but it does make me wonder about the connection between bias and experimental design. The hallmark of a good experimental scientist is the ability to identify and remove systematic errors from an experiment. Yet one must be careful to root out all systematic errors, not just those that affect the results in one direction. The conclusion: science is difficult, and you must be constantly on guard about fooling yourself.
I reexamined Are Electromagnetic Fields Making Me Ill? to search for signs of my own biases, and came away a little worried. For instance, when talking about 5G cell phone radiation risks, I wrote
The 5G cell phone debate strikes me as déjà vu. First Mesmer’s “animal magnetism” treatments ascended in popularity and then declined. Next the use of magnets for therapy rose and fell. Then came the power line debate; a crescendo followed by a diminuendo. Later the dispute over traditional cell phones came and went. Now, we are doing it all over again for 5G.
After listening to Trecek-King’s video, I am nervous that this was an inadvertent confession of bias. Do my past experiences predispose me to reject claims about electromagnetic fields being dangerous? Or am I merely stating a hard-earned opinion based on experience? Or are those the same thing? Is it bias to believe that Lucy will pull that football away from Charlie Brown at the last second?
I tried to focus my book on the evidence and not on personal opinions, but can we ever be sure? If I was a proponent of the idea that cell phones cause cancer, I might point to the above déjà vu quote as evidence that the author of Are Electromagnetic Fields Making Me Ill? was biased. Yet, if you asked me now if I still believed what I wrote in that quote, I would say “you betcha I do.” Does my statement have relevance to the 5G cell phone debate? I think it does, although it’s no substitute for hard evidence. Can we ever truly free ourselves from our biases? Perhaps not, but at least we can be aware of them, so as to be on guard.
All this discussion about critical thinking and bias is related to the claims of pseudoscience and alternative medicine. At the end of Are Electromagnetic Fields Making Me Ill? I ponder the difficulty of debunking false claims.
The study of biological effects of weak electric and magnetic fields attracts pseudoscientists
and cranks. Sometimes I have a difficult time separating the charlatans
from the mavericks. The mavericks—those holding nonconformist views based on
evidence (sometimes a cherry-picked selection of the evidence)—can be useful to
science, even if they are wrong. The charlatans—those snake-oil salesmen out to
make a quick buck—either fool themselves or fool others into believing silly ideas
or conspiracy theories. We should treat the mavericks with respect and let peer
review correct their errors. We should treat the charlatans with disdain. I wish for
the wisdom to tell them apart.
I’ll give Trecek-King’s the last word. Another of her mantras, which to me sums up why we care about critical thinking, is:
I am not saying that all of our problems can be solved with critical thinking. I’m saying that it is our best chance.
Critical Thinking in Education, featuring Melanie Trecek-King, Bertha Vazquez, and Daniel Reed
Every year the Kresge Library at Oakland University hosts an event called “Authors at Oakland” where they honor publications by Oakland University faculty. This year was “a celebration of the book.” Intermediate Physics for Medicine and Biology was featured at a previous Authors at Oakland event, and this year I submitted Are Electromagnetic Fields Making Me Ill? Two authors were selected to give a short talk about their book, and I was one of them. So on Wednesday, March 20 I spoke to an audience of OU librarians, members of the faculty senate library committee, and other interested professors and students.
The talk was not recorded but below is a transcript, as best as I can remember it.
Thank you for selecting my book Are Electromagnetic Fields Making Me Ill? to be featured here at Authors at Oakland. My friend David Garfinkle once told me that any time a book has a title in the form of a question, the answer’s always “no.” That’s true for my book, and sums it up in a nutshell.
How did I come to write this book? In November of 2019, just before Covid arrived, I was asked to participate in a town hall meeting in Rochester, Michigan about the then-new 5G cell phones. I was to be the health effects expert. I thought I was going to give a short talk to a quiet and respectful audience. Little did I know what was in store. [At this point I showed about the first one and a half minutes of the video below.]
I discussed the hazards of 5G cell phone radiation at a town hall meeting in Rochester, Michigan in 2019. The audience was not convinced by my claim that the risks are small. https://www.youtube.com/watch?v=smQ0Nnz7lLk
This experience got me to wondering why people believe things that aren’t supported by the evidence and what could I do about it? In response to the second question, I wrote this book.
The book covers several topics, but today I’ll focus on the issue that started it all: cell phones and cancer.
Not everyone agrees with me that 5G cell phone radiation is harmless. Devra Davis has written a book titled Disconnect, in which she claims to tell “the TRUTH about cell phone RADIATION, what the INDUSTRY has done to HIDE it, and how to PROTECT your FAMILY.” I disagree with her conclusions, but the issue shouldn’t be viewed as my word against hers. Let’s look at the evidence.
That’s how science works.
Quantum mechanics tells us that electromagnetic radiation is not continuous but comes in lumps called photons.
The energy of a photon is proportional to its frequency. Very high frequency photons like for x-rays have enough energy that they can disrupt DNA, causing mutations leading to cancer. However, cell phones operate at a much lower frequency, on the order of a gigahertz (one billion oscillations per second), in the realm of microwaves. These photons have an energy of about 0.000004 eV (an eV or “electron volt” is a unit of energy appropriate when discussing single atoms or molecules). What should we compare that energy to? All molecules are bouncing around randomly, called thermal motion. The thermal energy at our body temperature is about 0.02 eV. A cell phone photon would be swamped by the thermal noise. Chemical bonds have strengths of several electron volts. A cell phone photon is far too weak to break bonds, so they can’t directly disrupt DNA and cause cancer like x-ray photons can. If they have any effect it must be an indirect one, such as affecting our immune system or suppressing our body’s ability to repair DNA damage.
A microwave oven. (Consumer Reports, CC BY-SA 4.0, https://creativecommons.org/ licenses/by-sa/4.0, via Wikimedia Commons)
Even though one photon can’t damage our tissue, you might be wondering what would happen if we deposited many, many photons into our body? Physicists have a word for that: “heat.” We know microwaves can heat tissue. You prove that every time you warm up your leftovers in your microwave oven. However, physicists understand how microwaves heat tissue very well, and can predict how hot tissue will get when exposed to microwaves. Cell phones don’t emit enough microwave radiation to significantly heat tissue. The Federal Communications Commission limits the amount of radiation a cell phone can emit to levels that don’t cause significant heating. Your cell phone doesn’t cook your brain. If microwave radiation represents a hazard to our tissue, it’s not only through an indirect effect but also a nonthermal effect.
Let’s now look at four types of evidence about the risk of cell phone radiation: 1) theoretical analysis, 2) cancer rates, 3) epidemiological evidence, and 4) laboratory experiments.
Asher Sheppard and his colleagues have analyzed every theoretical mechanism they could think of to determine if microwaves have a significant affect on our tissue. After an exhaustive search, they concluded that
In the frequency range from several megahertz to a few hundred gigahertz, the focus of this paper, the principal mechanism for biological effects, and the only well-established mechanism, is the heating of tissues.
I can imagine that you’re thinking “well, maybe those armchair theorists just weren’t smart enough to dream up the correct mechanism.” Perhaps, but the point I want to make is that the concern about cell phone radiation isn’t being driven by a theoretical prediction. Theory does not predict there should be an effect.
Cell phone use and brain cancer trends between 1976 and 2006. (Data from Inskip et al.)
Now look at this plot of brain cancer trends. Back in the 1980s, when I was a graduate student, no one had cell phones. The use of cell phones has exploded since then. The data shown only goes out to about 2010, but if you extend the data to today essentially everyone has a cell phone. However, the cancer rate has been flat over those decades. And the brain cancer rate, in particular, has been nearly flat. If cell phones are causing brain cancer, it’s not a strong enough signal to show up in the cancer rate data.
Epidemiology studies examine large groups of people, some exposed to a hazard and some not, to compare their health. One of the first epidemiological studies is called the INTERPHONE study, and it did suggest a weak association of heavy cell phone use with cancer. INTERPHONE was a case control study; the researchers interviewed many people with brain cancer to determine their prior cell phone use, and compared these people to a control group without cancer. These studies are useful for getting data on rare hazards quickly, but they’re susceptible to biases, such as “recall bias” where a person with cancer who used their cell phone a lot will remember that clearly and perhaps regretfully while a member of the control group might not remember whether or not they even used a cell phone at all. A cohort study is a better type of epidemiological analysis. A large number of people, some cell phone users and some not, are followed for many years to see who gets cancer. Two large cohort studies—the Million Women Study in Europe and another study that involved essentially the entire population of Denmark—didn’t indicate a signal for an increased rate of cancer caused by cell phone use. A meta-analysis of many epidemiological studies by Martin Röösli and his coworkers concluded that
Epidemiological studies do not suggest increased brain or salivary gland tumor risk with [mobile phone] use, although some uncertainty remains regarding long latency periods (>15 years), rare brain tumor subtypes, and [mobile phone] usage during childhood.
Another large cohort study, called COSMOS, is now being carried out in Europe. When I was preparing this Powerpoint presentation, I thought I’d have to tell you that we’ll need to wait a few years until the results are published. Then, just this week, a preliminary report found that there’s no evidence that cell phone use is associated with higher rates of brain cancer. Some people might claim that there’s a long latency period between the exposure to cell phone radiation and the occurrence of cancer, and that a large uptick in the cancer rate will happen soon. Maybe, but as each year goes by that scenario becomes less and less likely.
The final type of evidence is laboratory experiments, such as studies using rats, mice, or cells in a dish. The evidence here is mixed; many experiments see effects and many do not. In fact, you could make a compelling case for or against cell phone health effects, depending on which articles you read. Unfortunately, the quality of these studies is also mixed.
Often scientists sometimes conduct a systematic review, weighing the pros and cons of the many experiments. For example, Anne Perrin and her collaborators reviewed the effects of radiofrequency electromagnetic fields on the blood brain barrier, and found that
recent studies provide no convincing proof of deleterious effects of [radiofrequency radiation] on the integrity of the [blood brain barrier].
But other systematic reviews have come to different conclusions, and I fear it’s difficult to draw definite conclusions from the experimental investigations.
Federal agencies—such as the Food and Drug Administration, the Center for Disease Control, and the National Cancer Institute (part of the National Institutes of Health)—often conduct their own reviews of the evidence. My favorite is the National Cancer Institute, which was the agency that got the round of boos during that 5G town hall meeting I participated in. These aren’t bureaucrats conducting the review, but instead are our nation’s top cancer scientists. They concluded that
The human body does absorb energy from devices that emit radiofrequency radiation. The only consistently recognized biological effect of radiofrequency radiation absorption in humans that the general public might encounter is heating to the area of the body where a cell phone is held (e.g., the ear and head). However, that heating is not sufficient to measurably increase core body temperature. There are no other clearly established dangerous health effects on the human body from radiofrequency radiation.
So, the evidence from theoretical analysis, cancer trends, epidemiology, and experiments makes a strong case that there are no health risks from cell phone radiation. Impossibility proofs are difficult in biology and medicine, but to me the evidence is compelling that the electromagnetic waves emitted by cell phones are safe.
A final question is if we should believe the scientists. Should we trust the National Cancer Institute to provide a unbiased review, or are they trying to hide hazardous effects. I believe a conspiracy secretly carried out by hundreds if not thousands of scientists and medical doctors is absurd. In my book I wrote
Dangers arising from cell phone radiation strike me as unlikely, but not inconceivable. However, the claims that there exists a vast plot, with scientists colluding to conceal the facts, are ridiculous.
Finally, in the acknowledgments section of my book I thank the Kresge Library for “assisting me with obtaining books and articles related to this research.” In particular, the interlibrary loan office here at Kresge Library has been essential to my research. I worked them pretty hard. You can’t write a book like this without a good interlibrary loan department.
Thank you. Does anyone have questions?
I must admit the biggest applause arose from my comment about the interlibrary loan office, but then the crowd was largely librarians. Overall Authors at Oakland was a wonderful event, and I deeply appreciate being invited to speak at it.
I am an emeritus professor of physics at Oakland University, and coauthor of the textbook Intermediate Physics for Medicine and Biology. The purpose of this blog is specifically to support and promote my textbook, and in general to illustrate applications of physics to medicine and biology.
