Proteinaholic | A Response to Denise Minger – Part 1
Jul 21, The China Study: Fact or Fallacy? by Denise Minger - article found and I can see how she might reach the conclusions she did; this is .. Or was this bias reflecting your personal preference for eating raw meat and avoiding wheat flour ? .. user-pic. From Dr. Campbell's "last post" on the subject (found at. Today we are interviewing Denise Minger who reveals the truth behind what they And now, I'm being super obnoxious about Paleo and grass-fed meat and . this book had done with these numbers to reach the conclusions that he reached. .. this book, I've realized that the picture is actually a lot more nuance than that. About this site Many moons ago, I started this blog to combat some of the myths needs along with cute animal pictures to make my long-winded blog tomes less . no-crap fare with smaller amounts of seafood, eggs, and organ meats. . ago i was having a meeting with my psyciatrist, and i mentioned something about .
Campbell's article -- which includes the revelation that Price himself, the founder, actually recommended a vegetarian diet to his family as the most healthy. Of course, Minger expresses no interest in publicizing any of her work when it shows Campbell is correct.
We see this often; someone trying to build some credibility on their own by taking aim at the biggest target they can find in hope that they can punch a hole, thus showing themselves to be smart enough to take down the big guy. Unqualified to actually do any kind of study of her own, Minger hopes to find flaws in the peer-reviewed work of researchers from Oxford University, Cornell University, and the Chinese Academy of Preventive Medicine.
Except she's not up to the task of taking on professional researchers who have to work to the most rigorous standards in academia. These are slightly higher than standards for kids blogging on the web.
The Low Carb Diabetic: Denise Minger — Meet Your Meat: An Objective at a Controversial Food
A critic's post pointing out some of Minger's errors disappears from her blog, and reappears when the critic starts complaining about it elsewhere on the web. Minger then publicly admits that she could use help understanding Dr.
Campbell's research, because she doesn't have professional expertise to analyze and interpret the data she's pontificating about. Campbell felt he needed to take the time to dignify Minger's musings with a response. Still, this is the internet, and I guess sometimes it doesn't hurt to respond, even if the attacks constitute no more than a mosquito bite.
So just in case there are individuals who might feel there was merit to any of Minger's scientific-sounding speculation, here is Dr. Reply to Denise Minger by Dr.
Denise Minger has published a critique of our book, The China Study, as follows. This is a welcome development because it gives this topic an airing that has long been hidden in the halls and annals of science. It is time that this discussion begin to reach a much larger audience, including both supporters and skeptics. I hope at some point to be able to read all of the discussions and the questions that have been raised, but present deadlines and long-standing commitments have forced me, for now, to focus on the most common concerns and questions, in order to respond in a timely manner here.
Minger for having the interest, and taking the time, to do considerable analysis, and for describing her findings in readily accessible language.
And kudos to her for being clear and admitting, right up front, that she is neither a statistician nor an epidemiologist, but an English major with a love for writing and an interest in nutrition. We need more people with this kind of interest. I am the first to admit that background and academic credentials are certainly not everything, and many interesting discoveries and contributions have been made by "outsiders" or newcomers in various fields.
On the other hand, background, time in the field, and especially peer review, all do give one a kind of perspective and insight that is, in my experience, not attainable in any other way. I will try to make clear in my comments below when this is particularly relevant. My response can be divided into three parts, mostly addressing her argument's lack of proportionality--what's important and what's not.
Misunderstanding our book's objectives and my research findings Excessive reliance on the use of unadjusted correlations in the China database Failure to note the broader implications of choosing the right dietary lifestyle Before proceeding further, however, I would like to make a general comment about my approach in responding to Denise.
I believe Denise is a very intelligent person, and I can see how she might reach the conclusions she did; this is easy to do for someone without extensive scientific research experience. Having said this, there are fundamental flaws in her reasoning, and it is these flaws that I will address in this paper. Some might wonder, "Why didn't he go through her laundry list of claims and address each one in the same order?
I do in fact illustrate this point by addressing one of her claims regarding wheat, and the reader can assume that one could go through a similar exercise with all her claims. Not understanding the book's objectives. The findings described in the book are not solely based on the China survey data, even if this survey was the most comprehensive not the largest human study of its kind.
As explained in the book, I draw my conclusions from several kinds of findings and it is the consistency among these various findings that matter most.
First and foremost, our extensive work on the biochemical fundamentals of the casein effect on experimental cancer in laboratory animals only partly described in our book was prominent because these findings led to my suggestion of fundamental principles and concepts that apply to the broader effects of nutrition on cancer development.
These principles were so compelling that they should apply to different species, many nutrients, many cancers and an almost unlimited list of health and disease responses e.
These principles also collectively and substantially inferred major health benefits of whole plant-based foods. This earlier laboratory work, extensively published in the very best peer-reviewed journals, preceded the survey in China.
These findings established the essence of what can be called biological plausibility, one of the most important pillars establishing the reliability of epidemiological research. The first years of our work was not, as some have speculated, an investigation specifically focused on the carcinogenic effects of casein. It was primarily a series of studies intended to understand the basic biology of cancer and the role of nutrition in this disease.
The protein effect, of course, was remarkable, and for this reason, it was a very useful tool to give us a novel insight into the workings of the cancer process. By 'testing', I mean questioning whether any evidence existed in the China database to support a protective effect characterized by the nutritional composition of a plant-based diet.
I was not sure what might be found but nonetheless became impressed with what was eventually shown. The China project data afforded an opportunity to consider the collective interplay and effects of many potentially causative factors with many disease outcomes--the very definition of nutrition my definition of nutrition is not about the isolated effects of individuals nutrients, or even foods for that matter.
The China project encouraged us not to rely on independent statistical correlations with little or no consideration of biological plausibility. In the book, I drew my conclusions from six prior models of investigation to illustrate this approach: Using this strategy, I first inquired whether a collection of variables in the China survey ranging from univariate correlations to more sophisticated analyses could consistently and internally support each of these biologically plausible models and, second, I determined whether the findings for each of these models were consistent with the overarching hypothesis that a whole food, plant-based diet promotes health--I could not discuss much of this rationale in a page-limited book intended for the public.
Most importantly, I cannot emphasize enough that the findings from the China project, standing alone, do not solely determine my final views expressed in the book. That's why only one chapter of 18 was devoted to the China survey project, which is only one link in a chain of experimental approaches. I was simply asking the question whether there were biologically plausible data in the China database to support the findings gained in our laboratory, among others. Because of the uniqueness of the China database, I believed that the evidence was highly supportive.
One of the unique characteristics of this survey was the traditional dietary practices of this cohort of people.
Mostly, they were already consuming a diet largely comprised of plant-based foods, thus limiting our ability to detect an hypothesized plant-based food effect--thus making our final observations that much more impressive.
Third, in the book, we summarized findings from other research groups for a variety of diseases to determine the consistency of our model with their findings, according to my principles and concepts.
This posed for me the question, why? My participation in extensive reviews of the work of others during my year stint working on or as a member of expert committees gave me a particularly rich opportunity to consider these previously published studies. There still is, and for a long time has been, an intentional effort at various levels of science hierarchy to denigrate studies that speak to the more fundamental biology of plant-based diets.
The fact that there has been resistance, oftentimes hostile and personal in the lay community, speaks volumes to me. Fourth, and most importantly, there is the enormously impressive findings of my physician colleagues, which came to my attention near the end of the China project data collection period and which were showing remarkable health benefits of plant-based nutrition, involving not only disease prevention but also disease treatment alphabetically: I cannot overemphasize the remarkable accomplishments of these primary care physicians.
In effect, their work affirmed my earlier laboratory research. I should add that I knew none of them or their work during my career in the laboratory, thus was not motivated or biased to find ways to affirm their work.
It was the combination of these various lines of inquiry that made so compelling the larger story told in the book, at least for me. Denise mostly ignores these fundamental but highly consistent parts of my story. In that vein, I strongly believe that the findings of no single study in biology or even a group of similar studies should be taken too seriously until context is established. Biology is not for engineers and number crunchers, as important as they may be, because, compared to their systems, biological response is much more complex and dynamic.
The use of 'raw' univariate correlations. In a study like this survey in China ecologic, cross-sectionalunivariate correlations represent one-to-one associations of two variables, one perhaps causal, the other perhaps effect.
Use of these correlations aboutin this database should only be done with caution, that is, being careful not to infer one-to-one causal associations. Even though this project provided impressive and highly unique experimental features, using univariate correlations to identify specific food vs. First, a variable may reflect the effects of other factors that change along with the variable under study.
Therefore, this requires adjustment for confounding factors--mostly, this was not done by Denise. Second, for a variable to have information of value as in making a correlationit must exhibit a sufficient range. If, for example, a variable is measured in 65 counties as in Chinathere must be a distribution of values over a sufficiently broad range for it to be useful.
Third, the variables should represent exposures representative of prior years when the diseases in question are developing. I see little or no indication that Denise systematically considered each of these requirements. I should point out that when we were deciding to publish these data in the original monograph, we decided to do something highly unusual in science--to publish the uninterpreted raw correlations, hoping that future researchers would know how to use or not use them.
We felt that this highly unusual decision was necessary because we were wary of those in the West who might have doubted the validity of data collected in China--we had several experiences to suspect this.
But also, we believe that research should be as transparent as possible, simply for the sake of transparency, thus minimizing suspicion of hidden agendas.
We knew that taking this approach was a risk because there could be those who, knowing little or nothing about experimentation of this type, might wish to use the data for their own questionable purposes.
Nonetheless, we decided to be generous and, in order advise future users of these data, we added our words of caution--written about as part of our page monograph. I also have repeated this caution in other publications of mine. It seems that Denise missed reading this material in the monograph.
As I was writing this, I discovered this comment from a self-described professional epidemiologist PhD, cancer epidemiology on one of the blogs A Cancer Epidemiologist refutes Denise Mingers China Study Claims due to incorrect data analysis - 30 Bananas a Day! I do not know this person but did find her comment interesting.
After reviewing Denise's critique, she wrote the following for her Denise's blog, only then to see it quickly and mysteriously disappear. By running a series of correlations, you've merely pointed out linear, non-directional, and unadjusted relationships between two factors.Denise Minger: Starving On A Raw Vegan Diet?
I suggest you pick up a basic biostatistics book, download a free copy of "R" an open-source statistical software programand learn how to analyze data properly. I'm a PhD cancer epidemiologist, and would be happy to help you do this properly. While I'm impressed by your crude, and - at best - preliminary analyses, it is quite irresponsible of you to draw conclusions based on these results alone.
At the very least, you need to model the data using regression analyses so that you can account for multiple factors at one time. Lest it be forgotten, the main value of the China data set is its descriptive nature, thus providing a baseline against which other data sets can be broadly compared, either over time or over geographic space. Nonetheless, they do offer a rich trove of opportunities to generate interesting hypotheses, relatively few of which have been explored to date.
In contrast, using models representing biological plausibility, which was determined from prior research, I simply wanted to see if they were consistent with the China survey data.
For the sake of understanding the downside risk of using univariate correlations, I'll use this imaginary conversation involving a few correlations that Denise thought were relevant to her personal allergy to wheat, although many other examples from Denise's treatise could serve the same purpose.
Denise makes a point concerning a highly significant but unadjusted univariate correlation between wheat flour consumption and two cardiovascular diseases plus a couple other diseases. In doing so, she infers that wheat flour causes these cardiovascular diseases. She also makes the point that "none of these correlations appear to be tangled with any risk-heightening variables, either.
I use this particular example here because others who very much dislike my views have pointed out on the Internet that this example cited by Denise represents evidence of my lack of integrity. The conversation goes like this, after Denise reminds me of these univariate correlations.
I presume you did because you said that 'none of these correlations appear to be tangled with any risk-heightening variables. That is, these nomadic people migrate for part of the year to valleys, where they consume more vegetables and fruits.
Or was this bias reflecting your personal preference for eating raw meat and avoiding wheat flour? In fact, this would be a proper use of univariate correlations, simply searching for those correlations that might hint of supporting evidence for such an hypothesis.
If sufficiently convincing, then we could design a more analytical type of study. This exercise is called hypothesis generation, which is one of the virtues of the China data set. But Denise is doing something different, coming very close to almost randomly inferring causality without adjusting for confounding factors, without scanning the variables for analytical authenticity and without--to my knowledge--having prior evidence of biological plausibility for such an hypothesis.
Then, she uses this example as evidence of a "sin of omission" and a "distorted fact" on my part. In my case, acknowledging this made it easier to stop thinking of animal food consumption as something inherently wrong. I still love animals, but given the broader context of our food system, my goal now is to support only humane farms that treat their animals well, and encourage others to do the same.
How would you describe your current view toward the ethics of the omnivorous diet? But conscious omnivores are perhaps in an even better position than vegans to help transform the way farm animals are treated. This is at the core of omnivore ethics—working towards a major reform of the way we incorporate animals into our food system.
So why on earth would you willingly dive into something as vicious as food politics? Is this issue just that important to you, or do you simply enjoy being called names? It keeps me sane. Do you have any guidance for people suffering from health problems that might help them avoid falling prey to the many faddish, cultish, or simply unscientific diets out there that promise to relieve everything from gout to diabetes to cancer hello, China Study?
The flag gets even redder if a diet requires you to buy an expensive line of supplements the author happens to sell. But beyond the truly obvious scams, it does get tricky figuring out which claims are legit, because so many diet plans cite just enough science to sound impressive.
My best advice is to avoid short-term fixes—e.
Our grain-and-vegetable-oil-based USDA diet is also a recent invention, and shamelessly caters to the food industry rather than human health. Any diet that relies on meal-replacement shakes or packaged foods is also unlikely to be optimal in the long run. When we look at the diets out there cultish or not that claim a high degree of healing success, they all have a few things in common: This holds true for the paleo diet, the raw food diet, the macrobiotic diet, and even the plant-based diet espoused in The China Study.
Vegetable oils, most grain products, and refined sweeteners. Your book, Death by Food Pyramid will be coming out later this year. Can you give a preview of what food issues it will be covering? Figuring out what to believe and who to trust is a major issue for anyone who wants to be healthy.
Along with ripping apart some of the most influential studies that sculpted our nutrition landscape, the book will teach virtually anybody how to look at a study or health claim and critically evaluate it on their own. Basically, I want to close the chasm between the scientific community and the layperson—and my goal with Death by Food Pyramid is to give people the tools necessary to take charge of their health without needing a nutrition PhD and elaborate understanding of Latin prefixes.
Was writing a book on these issues simply a natural extension of your background as an English major — foisted upon you by fans of your blog and China Study debunkery, or was it something you actively pursued?
An even split between the two, for sure. All English majors secretly or not-so-secretly want to write a book and then be on Oprah because the book was so great. It never goes away. But Death by Food Pyramid is the product of something a lot more important than curing my Writing Flu.
I want to help people. I want to give something of real value back to those people, and to all the health-seekers out there—something they can use to improve their lives, or the lives of their loved ones.
It seems like every week, another book comes out detailing what people should and should not eat.