Guest blog from Martin Röösli: Epidemiology, I like!

This is the next in a series of guest blogs on BRHP. The opinions expressed in it are of Martin Röösli himself. Publication of these opinions in BRHP does not mean that BRHP automatically agrees or endorses these opinions. Publication of this, and other guest blogs, is an attempt to start an open debate and free exchange of opinions on RF and health.

Over the years I had interesting and exciting discussions with Martin about epidemiology and especially the Danish Cohort. Clearly, our ideas about the scientific value of Danish Cohort differ. Those interested in my opinions can find them in several posts here, on BRHP, and in my column in The Washington Times Communities and, finally, in my opinion piece in The Scientist Magazine.

Here, below, is what is Martin’s opinion on the Danish Cohort.


Martin Röösli: Epidemiology, I like!

I love epidemiology because it is about numbers. It is rarely black and white; it is about shades, it is about magnitude and about likelihoods. I love epidemiology because it is complex. It deals with the whole heterogeneity that life offers us. For real life questions such as long term health risks, conclusions can be rarely drawn in a simple way. One has to find and put together all relevant puzzle pieces from different sources in a clever way to obtain the full picture.

That is, why I love the “infamous” Danish Mobile Phone Subscriber Cohort Study. I would not claim that the study is superior to all other mobile phone brain tumour studies. Admittedly, it has weaknesses, adequately discussed in the paper by the authors. Most importantly, however, the study has strengths and offers a different perspective on the relevant question whether long term mobile phone use causes brain tumours.

The strengths of the Danish cohort studies are minimal selection bias and objective exposure data, which cannot be offered by case-control studies to date. The used exposure surrogate – duration of a mobile phone subscription in years – is crude. But is it really useless as often claimed?

Let us first look at an eye-striking finding in the Schüz et al, 2006 paper (JNCI). Male mobile phone subscribers had a decreased risk for smoking related cancers whereas female mobile phone subscribers had an increased risk for these sites and in addition an increased risk for Cervix uteri cancer. Is this due to mobile phone radiation? This is very unlikely but plausibly explained by different social behaviour and gender different smoking patterns of early mobile phone subscribers compared to the general population. This is an illustrative example of confounding for a textbook in epidemiology, which also convincingly demonstrates that the Danish subscriber cohort study is sensitive enough to detect cancer relevant exposure differences between the two study groups. In the most recent paper from Frei et al. (2011) the analysis could be adjusted for educational level and income and these confounding effects were somewhat reduced.

The most important question is thus, whether to be an early mobile phone subscriber is a representative exposure proxy for long term mobile phone use. It has been argued that this is not the case, because more than 300,000 business users could not be identified and were included in the comparison group, and this has downward biased the risk estimates. This is true but as an epidemiologist I have to think in numbers! Let us assume for glioma a true relative risk of 1.5 for an average long term mobile phone user and that 300,000 subscribers are erroneously included in the unexposed Danish population (4,100,000). Let us further be conservative and assume that these business users were heavy users and had actually a higher relative risk of 2.0. Thus the relative reference risk of 1.0 of the non-subscribers would increase to 1.07 [=(4,100,000*1+300,000*2)/4,400,000]. The resulting observed risk in the study would then be 1.40 (=1.5/1.07). As you can see, there is some underestimation but is completely unlikely to explain the actually observed relative risk for glioma of 0.98 for female subscribers and 1.08 for male subscribers. As for alcohol in the blood, the extent of dilution matters. This is an illustrative example on the impact of sensitivity and specificity of epidemiological exposure assessment on the study result; a quite complex issue for students in epidemiology.

Obviously the exposure surrogate used in the Danish Cohort Study is a very valid and discriminant long-term exposure surrogate if glioma risk starts to increase exactly after an induction period of 12 years. Under this assumption mobile phone subscription after 1995 would be irrelevant for the follow-up period until end of 2007. However, if the induction period is much longer, has a large between subject variability, or if the glioma risk is rather related to the amount of use than the duration since start of regular use, the used exposure proxy may not be informative. Nevertheless, indications were found that early subscribers still use the phones more often than other subscribers (Frei, et al, 2011), and that early subscribers were four times more likely to be regular mobile phone users than non-subscribers in an Interphone validation study (Schüz et al, 2007). In addition, early mobile phone users were more likely to having used analogue phones with higher output power than later subscribers. Altogether, it seems very likely that early subscribers received a higher lifetime microwave dose compared to the rest of the population.

In summary, the Danish Subscriber Cohort Study allows to reject some of the hypotheses about mobile phone use and cancers. It cannot solve everything and needs to be considered in the context of all available research, which includes case-control studies and ecological time trends analyses. All these epidemiological study designs have their limitations and strengths and only a balanced and comprehensive evaluation of all aspects will produce adequate conclusions. Most importantly, epidemiology provides data from real populations consisting of numerous genetic variations and susceptibilities and not only for one single genetic variation. That is what eventually matters for the population! It has been demonstrated all over again, if an exposure is relevant for the population’s health, epidemiology will reveal it. More difficult is to detect small risks or risk related to rare events (e.g. histological subtypes or genetic variants). Needless to say that epidemiology cannot predict the future. If induction period of mobile phone effects lasts several decades, the impact on population level is not (yet) noticeable. This uncertainty remains and can be addressed with other research disciplines. But as I said, epidemiology is about likelihoods, it is about quantities, it is complex, it is about real life and it is about the population’s health. That is why I became an epidemiologist.



26 thoughts on “Guest blog from Martin Röösli: Epidemiology, I like!

  1. Professor:

    First, I agree with the other posters that the new color scheme is a huge improvement. Second I want to step back from insults (I’m as guilty as anyone) and get back to science. I just don’t see your argument about exposure data.

    While I am not into marketing I have seen many surveys that include ternary responses such as “Very important, somewhat important, not important.” These are part of a Likert Scale, about which I know little.

    There is no way to measure “importance.” These surveys assume however, that there is correlation between the response and importance. Companies pay major fees for these surveys and they do not like to waste money.

    It seems to me that Million Women study is doing something analogous. We do not know what the exposure is, but we are assuming that it’s correlated to frequency which is similarly based on a Likert scale. The only way to show that it’s meaningless and unethical is to demonstrate that this correlation does not exist. You can argue the relative strength of the association but to call it unethical requires that you substantiate your claim.

  2. Biron,
    Read carefully the text concerning how exposure to cell phones was done in this study. Anyone, able to think logically, can understand that it is inadequate information. Epidemiologists planning this study should know it. If they did not know it then it is a flaw in planning, if they knew it then it is somethiung else… And, I first analyze science and then, if necessary, I criticize it… Nothing else, simple logic and rules of gathering of scientific data…

  3. Professor:

    You spend more time hurling insults than you do analyzing science.

    If you are to claim that the Million Women and Danish Cohort are bad science and unethical, then you need to show that actual exposure and the participants estimates are uncorrelated. While individual responses may have large error, the collective response should be correlated and meaningful by the large number of participants.

    You have not given any suggestion that they are uncorrelated — it is extremely improbable that no correlation exists. Show the bias or confounding. The insults and accusations of fraud are good theatre for activists but I will not be fooled by your unscientific response and disregard for statistics.

  4. Biron, you are absolutely wrong and you show complete lack of the understandidn on what scientific research is based. It is based on evidence coming from solid data not on assumptions. Danish Cohort and The Million Women Study are both bad science because they compare cancer prevalence with false exposure data. Logically, out of such comparison can not come out anything else but false conclusion.

  5. Thanks Deborah. With this simple change I, apparently, made many persons happy. Nice…

  6. One clarification on this question I put out there: “Is it necessary or possible to “prove” a dose-response relationship in this case when the effects of microwave exposure have been demonstrated to be nonlinearly induced and when, in the real world, they are impossible to quantify?”

    I don’t mean this to the extreme that it isn’t necessary to properly identify those exposed to microwave/rf and those not exposed. I do believe it is necessary to include those exposed to DECT/cordless phone microwaves in the exposed group. The exposure is to the microwaves, not the device, necessarily, right?

  7. Professor:

    “Martin, the problem is that you do not know what is the average exposure in group.”

    It’s not necessary to know the average exposure. What is critical is to know whether in aggregate one million subjects can collectively classify their usage such that the law of large numbers takes effect. Exposure is a function several random variables including time. If:

    1) the variables other than expsosure time are uncorrelated with exposure time
    2) there is positive correlation between the subject’s response and exposure time

    then we should have a dose relationship.

    Professor Röösli:

    Your explanation of direction risk of DECT phones and the misclassification of business users in the Danish cohort are an epiphany for those who understand basic probability and statistics. While there may be some questions about the level of exposure, you have poured cold water on the assertions by the Professor and others like Moskowitz (who seeks wants 5$ / year from me for my family subscription) and Davis who claim the study is misleading. It has flaws and limitations, but these are stated.

    We can now reject the Professor’s claim that the Danish Cohort is unethical and a scandal. Thank you for your insight.

  8. Dariusz, I am really glad you changed to a white background. The white letters on the black background was very difficult for me to read. This is much better.

  9. As far as the studies go, why don’t the researchers just ask about cordless phone use, the same as they have done regarding cell phone usage.

    Every home I have been in in the last 10 years or more has had a cordless phone. It’s hard to even find a land line phone at the store. Almost every home for the last 5 years or more has also had wifi. Every store, office, street light, city has WiFi or WiMax.

    And what of all the far field exposures? Is it necessary or possible to “prove” a dose-response relationship in this case when the effects of microwave exposure have been demonstrated to be nonlinearly induced and when, in the real world, they are impossible to quantify? Moreover, the exposures are unqualifiable, different complex wave forms and harmonics in every space, acting on different people differently.

  10. Biron,

    There is no doubt that microwaves are biologically active. If you now want to quibble about whether or not uncontrolled, indiscriminate cell membrane disruption is an adverse effect or not, I will leave you to argue with your own straw man. I didn’t sign up for the debate team; this is more than an exercise polemics to me.

    PS Children absorb more radiation than most adults for more reasons than their size, but I like your cooking analogy. It’s a useful visual.

  11. “Even if children are more susceptible to environmental hazards tells us nothing about whether RF is a hazard. Before one commences the “save-our-children” rhetoric, there must be something from which they need to be saved”

    @ Biron

    a very good point and isn’t this exactly that, what Dr. Lesczcynski always claimed?

    We first must examine whether the person ever responds to EMF.

    It seems to me, we make the second step before the first.
    For me, epi studies are wasting money as long as we don’t know more about whether EMF are harmful for humans.

    and @ Biron: I don’t remember, that I ever posted a link about Dr. Eger and his activism as you asked me. For me, it makes no sense to discuss about Dr. Eger and his diverse “studies”.

  12. The crucial question is, how is DECT phone use correlated to mobile phone use. If it is not correlated, the risk estimates will be completely unbiased bunless exposure from mobile phone use is negligible compared to exposure from DECT phones. If it is positively correlated, i.e. persons who use more mobile phones also use more DECT phones, the direction of the risk will be correct but not the magnitude attributed to mobile phone exposure. If it is negatively correlated, i.e. persons who use mobile phones use less DECT phones, direction of risk can be biased. In this case almost the whole population became exposed within a relatively short time and one may give more weight to incidence time trends analysis. Although this type of studies has other limitations…

  13. Martin, the problem is that you do not know what is the average exposure in group. Groups are mix of differently exposed persons and you do not know how many got high and how many got low exposure. You cannot calculate average exposure in group.

  14. Dariusz, the crucial question is whether the average per exposure group differs. If so, you can address dose-response.

  15. “Is it not true that children are more vulnerable than adults to environmental hazards and in fact, are physiologically different from adults, their cells are still differentiating and proliferating at a faster rate?”

    Even if children are more susceptible to environmental hazards tells us nothing about whether RF is a hazard. Before one commences the “save-our-children” rhetoric, there must be something from which they need to be saved.

    “That children absorb more microwave radiation than adults?”

    This is probably true. Children are smaller, and if growth is linear in all directions, volume grows by the cube and surface area by the square. Thus there is more surface area per unit volume in children. There is less exposure in total in children, but more per unit volume (or mass). When you cook food, it cooks faster when it’s in smaller pieces because you increase the surface area.

    All this is moot unless one proves that wireless technology is harmful.

    So yes, your argument about children is non-sequitur.

  16. Martin, you are mixing different things by referring to Snow’s work. Dose of RF received by a person is different from the mechanism how it works. It is very common to hear that epidemiological studies show no RF effect and do not show any dose response. How these studies could show dose when in the same exposure group are analyzed hightly exposed persons and low exposed persons. This error is present in both cohort studies on RF: Danish Cohort and The Million Women Study.

  17. A good point, better exposure data is always an asset. However, in epidemiological research an adequate exposure surrogate can be good enough for hazard identification, without knowing the exact dose. That is how the field of environmental epidemiology has started in the 19th century with John Snow’s famous study on cholera at a time when little was known about the underlying disease mechanism.

  18. @Deborah Rubin: I get the impression that you thought your comment had been responded to by the author of the blogpost (Martin). Unless I’m mistaken, the response was actually written by @BironEMF.

  19. One more point re “Finally, your statement “but even our children are becoming ill at alarming rates” is non-sequitur and alarmist, suggesting that RF technology targets children.”

    Is it not true that children are more vulnerable than adults to environmental hazards and in fact, are physiologically different from adults, their cells are still differentiating and proliferating at a faster rate? That children absorb more microwave radiation than adults?

  20. Martin, I think you may have misunderstood my comment. And I thought you, an avid epidemiologist, might already be familiar with the correlations between the increases in some diseases and conditions as they relate to the large scale adoption of wireless devices, starting with the DECT cordless home phones.
    ex Pritchard, 2013.
    You may have noted, in my comment, I acknowledged that there are many possible interrelated causes for these increases. Unlike you, perhaps, I would suggest the time for alarm is long overdue–along with the time to properly inform the public about the possible adverse effects of microwave exposure as demonstrated in the peer-reviewed literature. It is long past time time to label wireless devices with a warning and long past time to inform the public so they can make an informed decision to consent. It is unethical to do otherwise, in my opinion, as with other health hazards.

    However, in my comment I was trying to make the point that we won’t find what we aren’t looking for in the first place.

    FCC tells us there is no evidence that wireless microwave exposure is causing any illness in our society. They and the schools and the health dept, etc, almost always focus on brain tumors–and even there we see the interpretation and adequacy of the studies is always debatable. But there is only one truth regarding whether or not the exposure is increasing the incidences and/or growth rate of brain cancers. And it must be determined and communicated as soon as possible.

    In the meantime…

    My real point is that since the wide scale adoption of wireless microwave emitting devices–starting with DECT cordless phones–and the infrastructure, we are seeing an increase in many diseases and conditions that correspond more immediately than brain tumors may to that exposure. I gave you only a few examples. And of course, these increases may not be caused by this exposure, or they may be caused by it, and/or they may be caused by the exposure and other exposures and/or individual variations. I don’t know. But I think we need to find out.

    It seems reasonable to me that we should examine these associations because the increases in disease and exposure to microwaves exist in the same time line and because peer-reviewed studies demonstrate that similar levels of microwave radiation can cause the biological effects associated with the etiology of these diseases. For my neurological examples to you, I will offer that the literature shows cell membrane disruption, blood brain barrier disruption, brain wave pattern changes and hormonal/neurotransmitter disruption, etc. I would add that we also have the anecdotal evidence of people who are more immediately and severely affected by the exposures. I believe it is irrational and unethical to not act on all of this information–especially considering the mass proliferation of microwave emitting devices around the globe used by infants, children, the infirm, etc.– most of whom are completely oblivious to the fact that there is ample evidence of harm.

  21. ALL exposures should be considered, not just cellphones and DECT phones. And I agree with your observation, some DECT phone exposures can exceed some cellphones some of the time, particularly GSM phones . But UMTS devices will well below DECT exposure most of the time.

    Epidemiological studies without complete exposure assessment have limited value and should not be taken too seriously. But can’t be dismissed totally.

  22. Martin,

    You acknowledge that your study used a crude exposure assessment, and that is a limitation of the study. But, it is also true that other epidemiology studies looking at the same or similar questions used imperfect exposure assessments – like distance from source or mailed questionnaires asking about number of calls and/or minutes of use. Without proper dosimetry, it seems very unlikely to me that resulting data could be very reliable. Do you have any comment on this? Or do you have any thoughts on how dosimetry could be improved on future studies?

  23. Deborah:

    I do not know the validity of the correlation of the illnesses you list above to the growth of cordless and mobile phone use, but it is irresponsible to suggest that wireless technologies are the prime mover.

    There are many things that civilization introduces that would correlate with the reported increase in cancer. Yes, we use more wireless technology but we also eat more sushi and drink more diet soda. We have indoor plumbing. We drive more than we did fifty years ago and our bodies are subject to more acceleration and deceleration. We have nail salons and drink bottled water.

    The claims that use of wireless technologies may be causal for autism are equally specious. The converse is certainly plausible. Furthermore, autism, ADHD and other cognitive disorders are highly subjective and may be influenced by any number of social or educational trends.

    Early onset dementia, if indeed it is rising, may be the result of many other agents or phenomena. One could speculate that medicine is saving unhealthy people who would otherwise die at a very early age and who instead live only to succumb to early dementia.

    Finally, your statement “but even our children are becoming ill at alarming rates” is non-sequitur and alarmist, suggesting that RF technology targets children.

    In summary we know very little about our prospects for health and even less about what influences it.

  24. I have found it hard to take any cell phone epidemiological study seriously when exposure to DECT cordless phones is not considered. I have personally seen various DECT phones measured and would say that the radiation from DECT phones is comparable to, and in some cases, higher than cell phones.

  25. “If induction period of mobile phone effects lasts several decades, the impact on population level is not (yet) noticeable”

    I wonder–there are so many diseases on the rise that correlate to cordless and cell phone adoption. Granted, we are exposed to so many uncontrolled variables in our day to day lives, but even our children are becoming ill or impaired at alarming rates. Autism, ADD, ADHD, anxiety and depression, etc, rates are all increasing.

    Also, early onset dementia rates are rising.

    Several cancer rates are increasing, for example salivary gland and thyroid.

    And what of Hardell’s recent study, Case-control study of the association between malignant brain tumours diagnosed between 2007 and 2009 and mobile and cordless phone use?

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