Friday, April 16, 2010

The Study Everyone Talks About Part 1: Correlation is NOT Causation

The China Study

Whenever I get to talking paleo with people, it comes up.  Inevitably.

"Have you heard of The China Study?"

"But what about The China Study?"

"The China Study is based on tons of RESEARCH, where is yours?" and

"My friend/cousin/neighbor/sibling/pet became a vegan/vegetarian after reading The China Study--it was THAT convincing!"


Okay, so let's compile those reviews and research on why The China Study is NOT an insta-kill to the paleo/primal diet or low-carb approach.  I am breaking this topic into bite-sized portions since it is GINORMOUS (yes, that's a word)!  So today we'll tackle what the study said and the limitations of a study that large.

*crackles knuckles*  *takes a deep breath*

The China Study: What Is It?

From The China Study website (my emphasis in bold):
"The research project culminated in a 20-year partnership of Cornell University, Oxford University, and the Chinese Academy of Preventive Medicine, a survey of diseases and lifestyle factors in rural China and Taiwan. More commonly known as the China Study, “this project eventually produced more than 8000 statistically significant associations between various dietary factors and disease.” 
The findings? “People who ate the most animal-based foods got the most chronic disease … People who ate the most plant-based foods were the healthiest and tended to avoid chronic disease. These results could not be ignored,” said Dr. Campbell.
Wikipedia further elaborates on study size:
"The China Study," referred to in the title is the China Project, a "survey of death rates for twelve different kinds of cancer for more than 2,400 counties and 880 million (96%) of their citizens" conducted jointly by Cornell University, Oxford University, and the Chinese Academy of Preventive Medicine over the course of twenty years.
and provides the authors' recommendations:
The authors recommend that people eat a whole food, plant-based diet and avoid consuming beef, poultry, eggs, fish and milk as a means to minimize and/or reverse the development of chronic disease. The authors also recommend that people take in adequate amounts of sunshine in order to maintain sufficient levels of Vitamin D and consider taking dietary supplements of vitamin B12 in case of complete avoidance of animal products. The authors criticize "low carb" diets (such as the Atkins diet), which include restrictions on the percentage of calories derived from complex carbohydrates.
Bottom line: Dr. T. Colin Campbell and his team found that animal protein in the diet correlated with increased risk of disease through observational or epidemiological studies and meta-analysis.  His recommendation?  Go vegan.

The Limitation of Epidemiological Studies: Correlation Is NOT Causation, Peoples!

One of the major limitations of this kind of research is its breadth.  You can pull so much data together that it becomes muddied with confounding factors and the linkages you make are tenable at best.  Dr. Eades, author of Protein Power, has gotten so tired of arguing against these studies that he posted a reference about them:
Observational studies – also called prospective or cohort studies and sometimes even epidemiological studies – are the kind most often reported in the media simply because there are so many of them.  These are the studies in which researchers look for disease disparities between large populations of people with different diets, lifestyles, medications, incomes, etc.  If disease disparities are found to exist between groups, then researchers try to make the case that the difference in diet, lifestyle, medication, etc. is the driving force behind the disparity.
And meta-analyses:
For those who don’t know, meta-analyses are compilation studies in which researchers comb the medical literature for papers on a particular subject and then combine all the data  from the individual studies together into one large study.  This combining is often done to bring together a collection of studies, none of which contain data that has reached statistical significance, to see if the aggregate of all the data in the studies reaches statistical significance.  I think these types of meta-analyses are highly suspect, because they can lead to conclusions not warranted by the actual data. 
and the problem:
Researchers using meta-analyses set up selection criteria to pick which studies will be included in their final product, which leaves the door open for all kinds of mischief.   
Dr. Eades has a great analogy to share, so read the original reference, but it boils down to:
Problem is they can never possibly think of all the differences between the groups.  As a consequence, they never have a perfect study with exactly the same number, sex, age, lifestyle, etc. on both sides with the only difference being the study parameter. And so they don’t really ever prove anything.  
Observational studies only show correlation, not causation, a fact that everyone doing research and reading about research should have tattooed on their foreheads. 
Correlation can create a hypothesis for further testing.  That's it.  No light-bulb-over-the-head, ah-HA! moment of realization.  Sorry.

So where does The China Study come in?  The problem is that although The China Study definitely covers the Correlation is not Causation topic, it doesn't heed its own warnings.  It still slips down the rabbit hole when it says:
This does not mean that correlations are useless.  When they are properly interpreted, correlations can be effectively used to study nutrition and health relationships.  The China Study, for example, has over 8,000 statistically significant correlations, and this is of immense value.  When so many correlations like this are available, researchers can begin to identify patterns of relationships between diet, lifestyle and disease.  These patterns, in turn, are representative of how diet and health processes, which are usually complex, truly operate.  However, if someone wants proof that a single factor causes a single outcome, a correlation is not good enough.
Okay, I am getting a little nervous.  Correlations are now "patterns." Are they trying to make correlations sound more concrete?  Patterns are usually obvious and if obvious, does that mean they are real?Continuing down that hole:
After obtaining the results from a variety of studies, we can then begin to use these tools and concepts to assess the weight of the evidence.  Through this effort, we can begin to understand what is most likely to be true, and we can behave accordingly.  Alternative hypotheses no longer seem plausible, and we can be very confident in the result.  Absolute proof, in the technical sense, is unattainable and unimportant.  But common sense proof (99% certainty) is attainable and critical.  
Now my fears are realized.  The China Study authors have leapt from correlation to 'truth,' and "behave accordingly" sounds a whole lot like a prescription to me.  In one fell swoop, they've eliminated other hypotheses and don't even have to test their own due to their 'confidence in the result.'  Heck, why even bother seeking proof since it's "unattainable" and "unimportant."  "Common sense" is enough.  Well, maybe for them, but NOT for me.  And throwing out the animal-based diet that we evolved upon and that may even have been the impetus for our evolutionary path is NOT common sense to me!  

Okay, take a deep breath, Kristy...  Watch those cortisol levels.  I am just flustered at how well they can parlay the Correlation is not Causation topic and then with a final jab leave the average reader feeling satisfied that their breadth of research is enough to provide 'truth' and prescription.  Who the hell needs causation when you have those?

Think I am just crazy?  Think The China Study makes perfect sense?  Read Gary Taubes's (author of Good Calories, Bad Calories) thorough article for the New York Times.  He describes the leap from epidemiological study to preventative medicine as skipping vital experimental testing of the hypotheses epidemiological studies produce.  Why is this leap so often made?  Well, it's complicated:
The randomized-controlled trials needed to ascertain reliable knowledge about long-term risks and benefits of a drug, lifestyle factor or aspect of our diet are inordinately expensive and time consuming. By randomly assigning research subjects into an intervention group (who take a particular pill or eat a particular diet) or a placebo group, these trials “control” for all other possible variables, both known and unknown, that might effect the outcome: the relative health or wealth of the subjects, for instance. This is why randomized trials, particularly those known as placebo-controlled, double-blind trials, are typically considered the gold standard for establishing reliable knowledge about whether a drug, surgical intervention or diet is really safe and effective.
But clinical trials also have limitations beyond their exorbitant costs and the years or decades it takes them to provide meaningful results. They can rarely be used, for instance, to study suspected harmful effects. Randomly subjecting thousands of individuals to secondhand tobacco smoke, pollutants or potentially noxious trans fats presents obvious ethical dilemmas. And even when these trials are done to study the benefits of a particular intervention, it’s rarely clear how the results apply to the public at large or to any specific patient. Clinical trials invariably enroll subjects who are relatively healthy, who are motivated to volunteer and will show up regularly for treatments and checkups. As a result, randomized trials “are very good for showing that a drug does what the pharmaceutical company says it does,” David Atkins, a preventive-medicine specialist at the Agency for Healthcare Research and Quality, says, “but not very good for telling you how big the benefit really is and what are the harms in typical people. Because they don’t enroll typical people.”
These limitations mean that the job of establishing the long-term and relatively rare risks of drug therapies has fallen to observational studies, as has the job of determining the risks and benefits of virtually all factors of diet and lifestyle that might be related to chronic diseases. The former has been a fruitful field of research; many side effects of drugs have been discovered by these observational studies. The latter is the primary point of contention.
That latter is the basis for The China Study.  Still not convinced?  Read Lierre Keith's scour of epidemiological studies in The Vegetarian Myth, and her warning:
...until all the variables are controlled and the results reproducible, no conclusions can be drawn.  
Can you even begin to imagine the variables in a study as large as the China Study happily professes?  Remember it is based upon a "survey of death rates for twelve different kinds of cancer for more than 2,400 counties and 880 million (96%) of their citizens."  Even just small studies have nearly unlimited variables like diet, sleep, exercise, family, work, stress, transportation, socioeconomic status, environmental differences, genetic endowment, life history, having an ingrown toenail, etc.  How is anything meaningful ever said?  Well, researchers find correlations that create testable hypotheses and test them.  Over and over again.  Once they get the same results over and over again, THEN they can say something meaningful like X leads to greater risk of Y.  One study of 20 people and one study compiling the results of 300 different studies are just as meaningless when it comes to predictive power.

Gary Taubes (in the same New York Times article) provides a suggestion for critically evaluating scientific research:
So how should we respond the next time we’re asked to believe that an association implies a cause and effect, that some medication or some facet of our diet or lifestyle is either killing us or making us healthier? We can fall back on several guiding principles, these skeptical epidemiologists say. One is to assume that the first report of an association is incorrect or meaningless, no matter how big that association might be. After all, it’s the first claim in any scientific endeavor that is most likely to be wrong. Only after that report is made public will the authors have the opportunity to be informed by their peers of all the many ways that they might have simply misinterpreted what they saw. The regrettable reality, of course, is that it’s this first report that is most newsworthy. So be skeptical.
If the association appears consistently in study after study, population after population, but is small — in the range of tens of percent — then doubt it. For the individual, such small associations, even if real, will have only minor effects or no effect on overall health or risk of disease. They can have enormous public-health implications, but they’re also small enough to be treated with suspicion until a clinical trial demonstrates their validity.
If the association involves some aspect of human behavior, which is, of course, the case with the great majority of the epidemiology that attracts our attention, then question its validity. If taking a pill, eating a diet or living in proximity to some potentially noxious aspect of the environment is associated with a particular risk of disease, then other factors of socioeconomic status, education, medical care and the whole gamut of healthy-user effects are as well. These will make the association, for all practical purposes, impossible to interpret reliably.
The exception to this rule is unexpected harm, what Avorn calls “bolt from the blue events,” that no one, not the epidemiologists, the subjects or their physicians, could possibly have seen coming — higher rates of vaginal cancer, for example, among the children of women taking the drug DES to prevent miscarriage, or mesothelioma among workers exposed to asbestos. If the subjects are exposing themselves to a particular pill or a vitamin or eating a diet with the goal of promoting health, and, lo and behold, it has no effect or a negative effect — it’s associated with an increased risk of some disorder, rather than a decreased risk — then that’s a bad sign and worthy of our consideration, if not some anxiety. Since healthy-user effects in these cases work toward reducing the association with disease, their failure to do so implies something unexpected is at work.
All of this suggests that the best advice is to keep in mind the law of unintended consequences. The reason clinicians test drugs with randomized trials is to establish whether the hoped-for benefits are real and, if so, whether there are unforeseen side effects that may outweigh the benefits. If the implication of an epidemiologist’s study is that some drug or diet will bring us improved prosperity and health, then wonder about the unforeseen consequences. In these cases, it’s never a bad idea to remain skeptical until somebody spends the time and the money to do a randomized trial and, contrary to much of the history of the endeavor to date, fails to refute it.

I think I have given your brain enough food for thought for today.  At least now your first line of defense against The China Study question is that it can provide correlation but NOT causation.  There is NO predictive value through The China Study that an animal-based diet causes chronic disease or that a plant-based one does not.  There are no X leads to Y conclusions possible.  Period.

Feast upon it and we'll come back to discuss the reviews and research.  Enjoy your weekend!

Here is the next part: The Study Everyone Talks About Part 2: The Ravaging Reviews


  1. Thanks for this Kirsty! Very timely... I spotted 'The China Study' in the library today and nearly picked it up, but decided not to: I decided my understanding of the scientific method is not good enough to make an objective analysis of the information within.

    Some days I wish I had another lifetime to study statistics, epidemiology and sociology. I was thinking about studying nutrition, but it would be an exercise in frustration with the whole field so entrenched in flawed science.

    I'm thoroughly convinced by the arguments of Taubes et al in favor of a low-carb diet.

  2. Colin Campbell is a vegetarian. He designed the study to prove that vegetarian is best. When you know the results you want to get, you can select the participants and design it to get those results. The study is worthless, but the book on it is unfortunately selling well.

    Humans have never been vegan. Until we developed tools 2.5 million years ago (allowing us to kill and eat animals) we ate insects. The high protein and nutrition that they provide would have been needed for us to have developed into such brainy creatures. Now one could argue that 2.5 million years isn’t a long enough time for our bodies to have adapted to meat eating. But if you take that position you had better completely avoid Neolithic foods, even more so than the paleo eater avoids them.

    Now, of course, veganism is really a choice to not exploit animals. You shouldn’t argue with someone’s ethics choice. But a vegan cannot argue that his diet is the optimum diet for the human body.

    More on paleo eating is here:

  3. Thanks Helen! Glad I could help! I know the topic is daunting, but I am trying to cover all the bases and gather together reputable resources. Mostly, I need the answers myself for my response to that inevitable question!

    Don, what a well-thought out comment! I agree with your evolutionary history, but I think we would have killed and eaten animals long before we had tools. Chimps hunt and I think our hands would have sufficed to grab what we could when the opportunity presented itself. Tools definitely allowed us to exploit that meat-eating niche, though!

    The argument against animal exploitation is emotionally charged, but I believe it was respectfully, thoughtfully, and carefully presented by Lierre Keith in The Vegetarian Myth. Really, we can't live in a bubble--our lives depend upon animals. It is up to us to acknowledge all creatures, big and small, that contribute to our lives and to treat them respectfully, even as our food. And like you said, if someone wishes to refrain from eating this creature or that, it's that person's choice, but it is not the optimum diet for the human body to leave out meat.

  4. I'm currently on page 148 of The China Study. I find the author's style of writing easy to comprehend but very irritating. My complaint? Excessive use of superlative. Here are a few examples (chosen at random) from pages 106 and 107:
    ...incredible complexities and subtleties...impressive and informative web of information...this mammoth study fit perfectly...At the end of the day, the strength and consistency if the majority if the evidence is enough to draw valid conclusions ...incredible benefits...evidence is so overwhelming that...mountain of supporting research...convinced me to turn my own dietary lifestyle around.

    I've read enough nutrition literature over the years to recognize that the hallmark of a weak argument is the hard sell approach, an unwarranted sense of confidence in one's conclusions bolstered by repetition and excessive use of superlative. I find this sort of thing extremely tedious. Want to read some good authors? Try "Nutrition Against Disease" by Roger J.Williams, PhD, "Nutrition and your Mind" by George Watson, PhD, and "Sweet and Dangerous" by John Yudkin, MD.

  5. David, that's in interesting list.

    Don, I agree w Kristy - the argument that vegan/vegetarian eating is somehow merciful to animals or to the environment has been dismantled by Ms. Kieth; the Vegetarian Myth is a 'can't put it down' masterpiece ... until she shifts into politics at the end. That part is still informative, but not gripping.

    What a post, Kristy, thank you. Love the Taubes link. In the end, we get to test ourselves. Measure the inputs and outputs and you can get an imperfect but powerful testament to what works for you. Very low fat got me 15 pounds fatter, with massive blood sugar crashes, even though I was working out many hours/week doing cardio, resistance work and martial arts. It also got me motivated to take a lot of ibuprofen due to high inflammation, poor sleep quality and virtually nothing I liked. Meat vegetables nuts and seeds, with LOTS of fat, has me feeling well, looking fair to middlin' for a 46 year old, sleeping well, and drawing rave reviews on my flight physicals - low TG, good HDL, low fasting glucose. I'm sold. And if per chance living like this kills me, it's a fair trade.

  6. David, I agree with the overuse of superlatives being a thinly veiled disguise of unfounded conclusions. You don't have to overemphasize when the facts are plainly visible. Great choices for future reading; I will put them on my list! Thank you!

    Paul, thank you for the feedback! I love that Taubes article too. The more I read from him, the more I respect that man. And you are right, the best argument is N=1: Does it work for you? For Lierre Smith author of The Vegetarian Myth, the answer became unavoidable as her health severely deteriorated on a vegan diet. Her experience is not an isolated case. Just like you, I am healthiest by how I feel, perform at the gym, and by my blood work now on a paleo-style approach than on a low-fat, high carb diet, vegetarian trial as a teen, or zoning without paleo foods. That is all the fact I need to continue to eat paleo-style and try to refine my choices to be more local, seasonal, unprocessed, wild-caught, pasture-raised, etc.

  7. Thanks for the great post. I read The China Study back in my vegan days and couldn't help but wonder how all those people survived this long eating a vegan diet. It was a nagging question of common sense. Suddenly this guy comes along and says that animal products cause cancer? Too many questions.....I wasn't vegan for long.

    Could you consider taking a look at "Skinny Bitch"?Another book out there telling people how bad it is to eat meat (I don't recall differentiating between grass fed vs. grain fed beef. )

  8. I know I'm a bit late to this discussion, but I'll just add two points (wearing my professional statistician hat) - There are legitimate issues about food quality in China, it doesn't seem unreasonable to assume that those eating more meat have higher exposure to toxins than those eating only vegetables/grains (ok, so this isn't a statistician observation, but the whole toxins concentrate up the food chain thing... which I think is still valid). The point I'm making is that the results may be valid (ie plant eaters had less cancer) but the division incorrect. This leads to a comment about your treatment of correlations.

    I have a small objection to the wording you used "Correlations are now "patterns." Are they trying to make correlations sound more concrete? Patterns are usually obvious and if obvious, does that mean they are real?". Looking at correlations in large data sets, with many explanatory variables, as patterns is actually a very useful and practical way of visualizing relationships between variables. This doesn't mean the relationships are not spurious and *great* care must be taken in the interpretation of such patterns, which obviously wasn't done. Additionally, despite our wishes, patterns are not easy to spot in messy, high dimensional data such as this. They just aren't. That is a reality of trying to analyze large, comprehensive studies, patterns are bloody hard to find - even if they actually exist! Finally, epidemiological studies do have value, it's just that great care must be taken in the interpretation of results, and that is not often the case.

    As a caveat, I haven't read the book, nor do I plan to, it seems quite clear that the book is an utter waste of time and the study itself was, misguided, with far reaching conclusions made that just can't be justified. I generally agree with your comments, it's just that it feels a bit like you are throwing all epidemiological studies, correlations and patterns out as well, despite the fact that they all have real value. We just have to be careful! (very, very careful...)

    As an aside to this entire comment, I enjoy your blog.

  9. Thank you, Kat, for contributing another book to my list of "Must Reads"! I appreciate your feedback, and that it is coming from the unique experience of having been a vegan. Thanks!

    Anonymous, thank you for your feedback! I totally understand your point of view with the statistics. I was trying to express that Campbell uses word choice to make his argument more convincing by evolving the correlations into patterns and then cause-effect relationships. I understand that epidemiological studies and even meta-analyses ARE useful, but not at drawing cause-effect relationships or dietary prescriptions without further testing. Thank you for emphasizing the caution I had intended to express in my post.

  10. Here's a debate between Campbell and Cordain . A very poor showing by Campbell, with almost no references to any studies in his statement paper and rebuttal. His 1st sentence of his rebuttal says it all, "My critique of Professor Loren Cordain’s proposition
    almost entirely depends on my philosophy of nutrition." Cordain's 160ish paper references don't fit Campbell's mental model, so they *must* be wrong.

  11. I remember a study that was presented at my university when I was a first-year graduate student. The study had something like 25,000 subjects. The presenter was enthusiastic about his results... right up until an older graduate student who was also attending the presentation challenged them on exactly this point. Later on, the older graduate student said to me "With the amount of data he had, my big toe would be statistically significant. It doesn't mean anything in the real world, though."

    Epidemiological studies are not useful for talking about causation. That's the meat of it, and we need to make that message viral so people will actually Get It. But that's a pipe dream on my part, I suppose.

  12. Outstanding summary Kristy - awesome job.

    One thing I have read regarding research is that the hallmark of a great scientist is that they will dedicate their life to proving they are wrong. For example, if I believe that red cars are always faster, I would dedicate my time to trying to show they are not... to trying to prove the null hypothesis.

    As someone has already mentioned, Campbell is a vegetarian. And one must smell a large rodent when a vegetarian produces 'evidence' that following a vegetarian diet is optimal. It would seem that Campbell has constructed a study to prove his own bias. When in actual fact, he should have spent his time trying to prove the opposite. Had he, despite his efforts to prove that eating meat was optimal to human health, found that vegetarianism/veganism was a superior way to eat, then he would have had more credibility me thinks!

  13. is it just me, or is crux of your argument that there is no possible way to use science to study nutrition?

  14. You guys crack me up for your sheer LACK of independent, unique, original, or introspective thought or debate... You talk about qualitative factors of vegetarians/vegans, such as the stereotypical assumption that they are starch-aholoics and eat tons of grains... same as you double standard the argument of vegetarians/vegans wrongfully assuming all meat is bad, but then they don't qualify conventional crap meat vs. organic/pasture/grass fed...

    BTW, even in double-blind, placebo controlled, peer reviewed clinical studies looking to test certain nutritional/dietary/supplemental/drug hypotheses, there are ALWAYS too many outside variables unaccounted for that will ALWAYS invalidate and skew the outcome to a moderate to large extent... therefore, quantitative EPIDEMIOLOGICAL STUDIES OF LARGE SCALE, BREADTH, CROSS REFERENCE, PARAMETERS, ETC (such as China Study, Framington's various studies, etc etc), DO IN MANY CASES PROVE TO A LARGE DEGREE THAT ---_YES-----,

    If I drop the hammer on my toe 10 times and my toe aches and is sore for days or weeks afterward 10 times out of 10, it doesn't take a fancy study to realize and acknowledge, to everyone's chagrin, THAT YET CORRELATION DOES EQUAL CAUSALITY!!!

    Use a bit of higher level thinking people... stop parroting your mentor and talking heads' talking points ad infinitum! PLEASE!

  15. Hi Anonymous,
    Did you even read my articles? This is a literature review--intended to present the arguments against The China Study. The point is to gather information and present it as concisely as possible. So I think you missed that.

    I agree with you that group characteristics, even stereotypes, aren't always definitive for the individual--which is somewhat funny given that is one of the pitfalls of The China Study: using pooled data to make individual dietary recommendations. I LOLed.

    I disagree with your argument that there are always too many variables to test so let's just say "screw it" and allow correlations to lead us to causations. And Mandy, many researchers do in fact try to study nutrition in a scientific manner with success. I find value in the controlled, randomized, placebo-utilizing trials. Nutrition research is challenging, but I think it is worth the pursuit even if we are never 100% sure of anything. And, like Jamie commented above, if time and time again testing AGAINST one's preferred diet came up in SUPPORT of it, then that is pretty good data for that diet, as opposed to trying to find preconceived proof by finagling and misrepresenting data to get the desired outcome. This is too often the case. There is value in epidemiological studies and meta-analysis, but one has to TEST the hypotheses they generate to realize that value and determine causation.

    Thank you for your feedback, Miles (I cited that debate in my second installment in the series--great reference!), Adam (here, here!), Jamie (thank you for adding a great suggestion for researchers to strive to DISPROVE what they personally/professionally seek to prove), Mandy (for a valid question), and Anonymous (for adding a nibble for thought). I appreciate your contribution to this discussion, each of you!

  16. I'm not surprised that the many people commenting against the China Study, didn't actually READ it. If you had you would have learned that Campbell was initially seeking to prove that animal protein is necessary for optimum health. When he realized that the healthiest people ate a plant-based diet, his research took a drastic turn. He was raised on a dairy farm and didn't become a vegan until AFTER his findings. There are lots of athletes who eat a whole food plant-based diet...

  17. Anonymous, I not only read it, I practiced it for 3 months. I was never so sick or felt so bad in my entire life. My doctor told me to "GET OFF THE STRICT VEGETARIAN DIET NOW!!"

  18. I have yet to see quality, scientific evidence against the China Study. This article doesn't attack a single SPECIFIC conclusion (there's far more than just one study) that Dr. Campbell makes. Rather, it says "correlation is not causation, I've seen vegan people and they look unhealthy," and moves on. Dismissing a 300+ page book based on Campbell's entire academic career.

    And like Anonymous said, those of you who are claiming he went out and did this research with the intent of proving "plants good, animals bad," you haven't even read the introduction to the book. You seriously think that at a time when EVERYONE else in academia, including Campbell's own research advisors, were promoting high-protein diets that it was somehow professionally beneficial for him to begin writing papers contradicting that? Give me a break. He had to get all of this research, contradicting almost all other research in that field (at the time), peer-reviewed by people who disagreed with him. Hundreds of papers. It seems rather ridiculous you guys think you can just write some little snippet on "correlation vs. causation" and dismiss it.

  19. Hi Anonymous,
    Thank you for reading my blog. I guess we agree to disagree because I don't think that Campbell made solid conclusions based on the data. With nutrition research, there seems to be a study to support any diet and any side of an argument. I suggest you go with your gut: if you feel good eating what you eat, awesome, if you don't, try changing it up and trying something new. I feel great on my paleo-style approach. I know when I eat too much carbohydrate, refined ones, or grain-based ones, I get sick. From my own personal experience, that is the data I need to keep on track. Hope you are happy and healthy too!
    Best wishes,

  20. It's hard to add to all the great posts, but here goes: excavations of northern raw fat and raw meat eating people's skulls showed that they had very impressive healthy teeth. Not so of the very same people today who have added significant amounts of bread, hydrogenated fat, get the point.