The China Study: Fact or Fallacy?

Disclaimer: This blog post covers only a fraction of what’s wrong with “The China Study.” In the years since I wrote it, I’ve added a number of additional articles expanding on this critique and covering a great deal of new material. Please read my Forks Over Knives review for more information on what’s wrong with the conclusions drawn from Campbell’s casein/aflatoxin research, and if you’d rather look at peer-reviewed research than the words of some random internet blogger, see my collection of scientific papers based on the China Study data that contradict the claims in Campbell’s book. I’ve also responded to Campbell’s reply to my critique with a much longer, more formal analysis than the one on this page, which you can read here.

When I first started analyzing the original China Study data, I had no intention of writing up an actual critique of Campbell’s much-lauded book. I’m a data junkie. Numbers, along with strawberries and Audrey Hepburn films, make me a very happy girl. I mainly wanted to see for myself how closely Campbell’s claims aligned with the data he drew from—if only to satisfy my own curiosity.

But after spending a solid month and a half reading, graphing, sticky-noting, and passing out at 3 AM from studious exhaustion upon my copy of the raw China Study data, I’ve decided it’s time to voice all my criticisms. And there are many.

First, let me put out some fires before they have a chance to ignite:

  1. I don’t work for the meat or dairy industry. Nor do I have a fat-walleted roommate, best friend, parent, child, love interest, or highly prodigious cat who works for the meat or dairy industry who paid me off to debunk Campbell.
  2. Due to food sensitivities, I don’t consume dairy myself, nor do I have any personal reason to promote it as a health food.
  3. I was a vegetarian/vegan for over a decade and have nothing but respect for those who choose a plant-based diet, even though I am no longer vegan. My goal, with the “The China Study” analysis and elsewhere, is to figure out the truth about nutrition and health without the interference of biases and dogma. I have no agenda to promote.

As I mentioned, I’m airing my criticisms here; this won’t be a China Study love fest, or even a typical balanced review with pros and cons. Campbell actually raises a  number of points I wholeheartedly agree with—particularly in the “Why Haven’t You Heard This?” section of his book, where he exposes the reality behind Big Pharma and the science industry at large. I admire Campbell’s philosophy towards nutritional research and echo his sentiments about the dangers of scientific reductionism. However, the internet is already flooded with rave reviews of this book, and I’m not interested in adding redundant praise. My intent is to highlight the weaknesses of “The China Study” and the potential errors in Campbell’s interpretation of the original data.

(IMPORTANT NOTE: My response to Campbell’s reply, as well as to some common reader questions, can be found in the following post: My Response to Campbell. Please read this for clarification regarding univariate correlations and flaws in Campbell’s analytical methods.)

(If this is your first time here, feel free to browse the earlier posts in the China Study category to get up to speed.)

On the Cornell University website (the institution that—along with Oxford University—spawned the China Project), I came across an excellent summary of Campbell’s conclusions from the data. Although this article was published a few years before “The China Study,” it distills some of the book’s points in a concise, down-n’-dirty way. In this post, I’ll be looking at these statements along with other overriding claims in “The China Study” and seeing whether they hold up under scrutiny—including an in-depth look at Campbell’s discoveries with casein.

(Disclaimer: This post is long. Very long. If either your time or your attention span is short, you can scroll down to the bottom, where I summarize the 9,000 words that follow in a less formidable manner.)

(Disclaimer 2: All correlations here are presented as the original value multiplied by 100 in order to avoid dealing with excessive decimals. Asterisked correlations indicate statistical significance, with * = p<0.05, ** = p<0.01, and *** = p<0.001. In other words, the more stars you see, the more confident we are that the trend is legit. If you’re rusty on stats, visit the meat and disease in the China Study page for a basic refresher on some math terms.)

(Disclaimer 3: The China Study files on the University of Oxford website include the results of the China Study II, which was conducted after the first China Study. It includes Taiwan and a number of additional counties on top of the original 65–and thus, more data points. The numbers I use in this critique come solely from the first China Study, as recorded in the book “Diet, Life-style and Mortality in China,” and may be different than the numbers on the website.)

From Cornell University’s article:

“Even small increases in the consumption of animal-based foods was associated with increased disease risk,” Campbell told a symposium at the epidemiology congress, pointing to several statistically significant correlations from the China studies.

Alright, Mr. Campbell—I’ll hear ya out. Let’s take a look at these correlations.

Campbell Claim #1

Plasma cholesterol in the 90-170 milligrams per deciliter range is positively associated with most cancer mortality rates. Plasma cholesterol is positively associated with animal protein intake and inversely associated with plant protein intake.

No falsification here. Indeed, cholesterol in the China Project has statistically significant associations with several cancers (though not with heart disease). And indeed, plasma cholesterol correlates positively with animal protein consumption and negatively with plant protein consumption.

But there’s more to the story than that.

Notice Campbell cites a chain of three variables: Cancer associates with cholesterol, cholesterol associates with animal protein, and therefore we infer that animal protein associates with cancer. Or from another angle: Cancer associates with cholesterol, cholesterol negatively associates with plant protein, and therefore we infer plant protein protects against cancer.

But when we actually track down the direct correlation between animal protein and cancer, there is no statistically significant positive trend. None. Looking directly at animal protein intake, we have the following correlations with cancers:

Lymphoma: -18
Penis cancer: -16
Rectal cancer: -12
Bladder cancer: -9
Colorectal cancer: -8
Leukemia: -5
Nasopharyngeal: -4
Cervix cancer: -4
Colon cancer: -3
Liver cancer: -3
Oesophageal cancer: +2
Brain cancer: +5
Breast cancer: +12

Most are negative, but none even reach statistical significance. In other words, the only way Campbell could indict animal protein is by throwing a third variable—cholesterol—into the mix. If animal protein were the real cause of these diseases, Campbell should be able to cite a direct correlation between cancer and animal protein consumption, which would show that people eating more animal protein did in fact get more cancer.

But what about plant protein? Since plant protein correlates negatively with plasma cholesterol, does that mean plant protein correlates with lower cancer risk? Let’s take a look at the cancer correlations with “plant protein intake”:

Nasopharyngeal cancer: -40**
Brain cancer: -15
Liver cancer: -14
Penis cancer: -4
Lymphoma: -4
Bladder cancer: -3
Breast cancer: +1
Stomach cancer: +10
Rectal cancer: +12
Cervix cancer: +12
Colon cancer: +13
Leukemia: +15
Oesophageal cancer +18
Colorectal cancer: +19

We have one statistically significant correlation with a rare cancer not linked to diet (nasopharyngeal cancer), but we also have more positive correlations than we saw with animal protein.

In fact, when we look solely at the variable “death from all cancers,” the association with plant protein is +12. With animal protein, it’s only +3. So why is Campbell linking animal protein to cancer, yet implying plant protein is protective against it?

In addition, Campbell’s statement about cholesterol and cancer leaves out a few significant points. What he doesn’t mention is that plasma cholesterol is also associated with several non-nutritional variables known to raise cancer risk—namely schistosomiasis infection (correlation of +34*) and hepatitis B infection (correlation of +30*).

Not coincidentally, cholesterol’s strongest cancer links are with liver cancer, rectal cancer, colon cancer, and the sum of all colorectal cancers. As we saw in the posts on meat consumption and fish consumption, schistosomiasis and hepatitis B are the two biggest factors in the occurrence of these diseases. So is it higher cholesterol (by way of animal products) that causes these cancers, or is it a misleading association because areas with high cholesterol are riddled with other cancer risk factors? We can’t know for sure, but it does seem odd that Campbell never points out the latter scenario as a possibility.

Campbell Claim #2

Breast cancer is associated with dietary fat (which is associated with animal protein intake) and inversely with age at menarche (women who reach puberty at younger ages have a greater risk of breast cancer).

Campbell is correct that breast cancer negatively relates to the age of first menstruation—a correlation of -20. Not statistically significant, but given what we know about hormone exposure and breast cancer, it certainly makes sense. And there is a correlation between fat intake and breast cancer—a non-statistically-significant +18 for fat as a percentage of total calories and +22 for total lipid intake. But are there any dietary or lifestyle factors with a similar or stronger association than this? Let’s look at the correlation between breast cancer and a few other variables. Asterisked items are statistically significant:

Blood glucose level: +36**
Wine intake: +33*
Alcohol intake: +31*
Yearly fruit consumption: +25
Percentage of population working in industry: +24
Hexachlorocyclohexane in food: +24
Processed starch and sugar intake: +20
Corn intake: +20
Daily beer intake: +19
Legume intake: +17

Looks to me like breast cancer may have links with sugar and alcohol, and perhaps also with hexachlorocyclohexane and occupational hazards associated with industry work. Again, why is Campbell singling out fat from animal products when other—stronger—correlations are present?

Certainly, consuming dairy and meat from hormone-injected livestock may logically raise breast cancer risk due to increased exposure to hormones, but this isn’t grounds for generalizing all animal products as causative for this disease. Nor is a correlation of +18 for fat calories grounds for indicting fat as a breast cancer risk factor, when alcohol, processed sugar, and starch correlate even more strongly. (Animal protein itself, for the record, correlates with breast cancer at +12—which is lower than breast cancer’s correlation with light-colored vegetables, legume intake, fruit, and a number of other purportedly healthy plant foods.)

Campbell Claim #3

For those at risk for liver cancer (for example, because of chronic infection with hepatitis B virus) increasing intakes of animal-based foods and/or increasing concentrations of plasma cholesterol are associated with a higher disease risk.

Ah, here’s one that may be interesting! Even if animal products don’t cause cancer, do they spur its occurrence when other risk factors are present? That would certainly be in line with Campbell’s research on aflatoxin and rats, where the milk protein casein dramatically increased cancer rates.

So, let’s look only at the counties with the highest rates of hepatitis B infection and see what animal food consumption does there. In the China Study, one documented variable is the percentage of each county’s population testing positive for the hepatitis B surface antigen. Population averages ranged from 1% to 29%, with a mean of 13% and median of 14%. If we take only the counties that have, say, 18% or more testing positive, that leaves us with a solid pool of high-risk data points to look at.

Animal product consumption in these places ranges from a meager 6.9 grams per day to a heftier 148.1 grams per day—a wide enough range to give us a good variety of data points. Liver cancer mortality ranges from 5.51 to 59.63 people per thousand.

Let’s crunch these numbers, shall we? Here’s a chart of the data I’m using.

When we map out liver cancer mortality and animal product consumption only in areas with high rates of hepatitis B infection (18% and higher), we should see cancer rates rise as animal product consumption increases—at least, according to Campbell. That would indicate animal-based foods do encourage cancer growth. But here’s what we really get.

In these high-risk areas for liver cancer, total animal food intake has a correlation with liver cancer of… dun dun dun… +1.

That’s it. One. We rarely get a perfect statistical zero in the real world, but this is pretty doggone close to neutral. Broken up into different types of animal food rather than total consumption, we have the following correlations:

  • Meat correlates at -7 with liver cancer in high-risk counties
  • Fish correlates at +11
  • Eggs correlate at -29
  • Dairy correlates at -19

In other words, it looks like animal foods have virtually no effect—whether positive or negative—on the occurrence of liver cancer in hepatitis-B infected areas.

Campbell mentioned plasma cholesterol also associates with liver cancer, which is correct: The raw correlation is a statistically significant +37. If it’s true blood cholesterol is somehow an instigator for liver cancer in hepatitis-B-riddled populations, we’d expect to see this correlation preserved or heightened among our highest-risk counties. So let’s take a look at the same previous 19 counties with high hepatitis B occurrence, and graph their total cholesterol alongside their liver cancer rates.

In the high-risk groups, the correlation between total cholesterol and liver cancer drops from +37 to +8. Still slightly positive, but not exactly damning.

If I were Campbell, I’d look at not only animal protein and cholesterol in relation to liver cancer, but also at the many other variables that correlate positively with the disease. For instance, daily liquor intake correlates at +33*, total alcohol intake correlates at +28*, cigarette use correlates at +27*, intake of the heavy metal cadmium correlates at +38**, rapeseed oil intake correlates at +25*—so on and so forth. All are statistically significant. Why doesn’t Campbell mention these factors as possible causes of increased liver cancer in high-risk areas? And, more importantly, why doesn’t Campbell account for the fact that many of these variables occur alongside increased cholesterol and animal product consumption, making it unclear what’s causing what?

Campbell Claim #4

Cardiovascular diseases are associated with lower intakes of green vegetables and higher concentrations of apo-B (a form of so-called bad blood cholesterol) which is associated with increasing intakes of animal protein and decreasing intakes of plant protein.

Alright, we’ve got a multi-parter here. First, let’s see what the actual correlations are between cardiovascular diseases and green vegetables—an interesting connection, if it holds true. The China Study accounted for this variable in two ways: one through a diet survey that measured how many grams of green vegetables each county averaged per day, and one through a questionnaire that recorded how many times per year citizens ate green vegetables.

From the diet survey, green vegetable intake (average grams per day) has the following correlations:

Myocardial infarction and coronary heart disease: +5
Hypertensive heart disease: -4
Stroke: -8

From the questionnaire, green vegetable intake (times eaten per year) has the following correlations:

Myocardial infarction and coronary heart disease: -43**
Hypertensive heart disease: -36*
Stroke: -35*

A little odd, oui? When we look at total quantity of green vegetables consumed (in terms of weight), we’ve got only weak negative associations for two cardiovascular conditions, and a slightly positive association for heart attacks (myocardial infarction) and coronary heart disease. Nothing to write home about. But when we look at the number of times per year green vegetables are consumed, we have much stronger inverse associations with all cardiovascular diseases. Why the huge difference? Why would frequency be more protective than quantity? What accounts for this mystery?

It could be that the China Study diet survey did a poor job of tracking and estimating greens intake on a long-term basis (indeed, it was only a three-day survey, although when repeated at a later date yielded similar results for each county). But the explanation could also boil down to one word: geography.

Let me explain.

The counties in China that eat greens year-round live in a particular climate and latitude—namely, humid regions to the south.  The “Green vegetable intake, times per year” variable has a correlation of -68*** with aridity (indicating a humid climate) and a correlation of -60*** with latitude (indicating southerly placement on the ol’ map). Folks living in these regions might not eat the most green vegetables quantity-wise, but they do eat them frequently, since their growing season is nearly year-round.

In contrast, the variable “Green vegetable intake, grams per day” has a correlation of only -16 with aridity and +5 with latitude, indicating much looser associations with southern geography. The folks who eat lots of green veggies don’t necessarily live in climates with a year-round growing season, but when green vegetables are available, they eat a lot of them. That bumps up the average intake per day, even if they endure some periods where greens aren’t on the menu at all.

If green vegetables themselves were protective of heart disease, as Campbell seems to be implying, we would expect their anti-heart-disease effects to be present in both quantity of consumption and frequency of consumption. Yet the counties eating the most greens quantity-wise didn’t have any less cardiovascular disease than average. This tells us there’s probably another variable unique to the southern, humid regions in China that confers heart disease protection—but green veggies aren’t it.

Some of the hallmark variables of humid southern regions include high fish intake, low use of salt, high rice consumption (and low consumption of all other grains, especially wheat), higher meat consumption, and smaller body size (shorter height and lower weight). And as you’ll see in an upcoming post on heart disease, these southerly regions also had more intense sunlight exposure and thus more vitamin D—an important player in heart disease prevention.

(And for the record, as a green-veggie lover myself, I’m not trying to negate their health benefits—promise! I just want to offer equal skepticism to all claims, even the ones I’d prefer to be true.)

Basically, Campbell’s implication that green vegetables are associated with less cardiovascular disease is misleading. More accurately, certain geographical regions have strong correlations with cardiovascular disease (or lack thereof), and year-round green vegetable consumption is simply an indicator of geography. Since only frequency and not actual quantity of greens seems protective of heart disease and stroke, it’s safe to say that greens probably aren’t the true protective factor.

So that about covers it for greens. What about the next variable in Campbell’s claim: a “bad” form of cholesterol called apo-B?

Campbell is justified in noting the link between apolipoprotein B (apo-B) and cardiovascular disease in the China Study data, a connection widely recognized by the medical community today. These are its correlations with cardiovascular disease:

Myocardial infarction and coronary heart disease: +37**
Hypertensive heart disease: +35*
Stroke: +35*

And he’s also right about the negative association between apo-B and plant protein, which is -37*, as well as the positive association between apo-B and animal protein, which is +25* for non-fish protein and +16 for fish protein. So from a technical standpoint, Campbell’s statement (aside from the green veggie issue) is legit.

However, it’s the implications of this claim that are misleading. From what Campbell asserts, it would seem that animal products are ultimately linked to cardiovascular diseases and plant protein is ultimately protective of those diseases, and apo-B is merely a secondary indicator of this reality. But does that claim hold water? Here’s the raw data.

Correlations between animal protein and cardiovascular disease:

Myocardial infarction and coronary heart disease: +1
Hypertensive heart disease: +25
Stroke: +5

Correlations between fish protein and cardiovascular disease:

Myocardial infarction and coronary heart disease: -11
Hypertensive heart disease: -9
Stroke: -11

Correlations between plant protein and cardiovascular disease (from the China Study’s “diet survey”):

Myocardial infarction and coronary heart disease: +25
Hypertensive heart disease: -10
Stroke: -3

Correlations between plant protein and cardiovascular disease (from the China Study’s “food composite analysis”):

Myocardial infarction and coronary heart disease: +21
Hypertensive heart disease: 0
Stroke: +12

Check that out! Fish protein looks weakly protective all-around; non-fish animal protein is neutral for coronary heart disease/heart attacks and stroke but associates positively with hypertensive heart disease (related to high blood pressure); and plant protein actually correlates fairly strongly with heart attacks and coronary heart disease. (The China Study documented two variables related to plant protein: one from a lab analysis of foods eaten in each county, and one from a diet survey given to county citizens.) Surely, there is no wide division here between the protective or disease-causing effects of animal-based protein versus plant protein. If anything, fish protein looks the most protective of the bunch. No wonder Campbell had to cite a third variable in order to vilify animal products and praise plant protein: Examined directly, they’re nearly neck-and-neck.

If you’re wondering about the connection between animal protein and hypertensive heart disease, by the way, it’s actually hiked up solely by the dairy variable. Here are the individual correlations between specific animal foods and hypertensive heart disease:

Milk and dairy products intake: +30**
Egg intake: -28
Meat intake: -4
Fish intake: -14

You can read more about the connection between dairy and hypertensive heart disease in the entry on dairy in the China Study.

At any rate, Campbell accurately points out that apo-B correlates positively with cardiovascular diseases. But to imply animal protein is causative of these diseases—and green vegetables or plant protein protective of them—is dubious at best. What factors cause both apo-B and cardiovascular disease risk to increase hand-in-hand? This is the question we should be asking.

Campbell Claim #5

Colorectal cancers are consistently inversely associated with intakes of 14 different dietary fiber fractions (although only one is statistically significant). Stomach cancer is inversely associated with green vegetable intake and plasma concentrations of beta-carotene and vitamin C obtained only from plant-based foods.

This is congruous with conventional beliefs about fiber being helpful for colon health. And as a plant-nosher myself, I hope it’s true—but that’s no reason to omit this claim from critical examination. Here are all of the China Study’s fiber variables as they correlate to colorectal cancer:

Total fiber intake: -3
Total neutral detergent fiber intake: -13
Hemi-cellulose fiber intake: -10
Cellulose fiber intake: -13
Intake of lignins remaining after cutin removed: -9
Cutin intake: -14
Starch intake: -1
Pectin intake: +3
Rhamnose intake: -26*
Fucose intake: +2
Arabinose intake: -18
Xylose intake: -15
Mannose intake: -13
Galactose intake: -24

Surprise, surprise: I agree with Campbell on this one! All but two of the fiber variables have inverse associations with colorectal cancers. The first part of Campbell Claim #5 passes Denise’s BS-o-Meter test. Let us celebrate!

…But before we get too jiggy with it, I do have a nit to pick. Fiber intake also negatively correlates with schistosomiasis infection, a type of parasite. Try Googling “schistosomiasis and colorectal cancer” and you’ll get more relevant hits than you’ll ever have time to read. I’ll elaborate on this in a few paragraphs, so hang tight—but for now, I’ll just point out two things:

  1. Schistosomiasis infection is a very strong predictor for colon and rectal cancers, more so than any of the other hundreds of variables studied in the China Project (it has a correlation of +89 with colorectal cancer).
  2. The only fiber factions that don’t appear protective of colorectal cancer (pectin and fucose) also have the most neutral associations with schistosomiasis infection (+1 and -5, respectively—whereas other fiber factions had correlations ranging from -9 to -27 with schistosomiasis). In all cases, the correlation between each fiber faction and colorectal cancer parallels its correlation with schistosomiasis.

In other words: Is it the fiber itself that’s protective against colorectal cancer, or is it the fact that the counties eating the most fiber happened to also have the lowest rates of schistosomiasis? It would, I think, be wise to prune these variables apart before declaring fiber itself as protective based on the China Study data.

There is research conducted outside of the China Project suggesting fiber benefits colon health, but often that association dissolves when researchers adjust for other dietary risk factors, such as with the this pooled analysis of colorectal cancer studies published in the Journal of the American Medical Association. Bottom line: It’s never a good idea to go looking for a specific trend just because we believe it should be there. Chains of confirmation bias are often what cause nutritional myths to emerge and persist. Fiber may be beneficial, but we shouldn’t approach the data already expecting to find this—lest we overlook other important influences.

Moving on. Now, what about the second part of this claim: Stomach cancer is inversely associated with green vegetable intake and plasma concentrations of beta-carotene and vitamin C obtained only from plant-based foods.

Is this a fair assessment? Let’s find out. Here are the correlations between stomach cancer and each of these variables.

Green vegetables, daily intake: +5
Green vegetables, times eaten per year: -35**
Plasma beta-carotene: -14
Plasma vitamin C: -13

Ah, looks like we’re facing the Green Veggie Paradox once again. The folks with year-round access to green vegetables get less stomach cancer, but the the folks who eat more green vegetables overall aren’t protected. Once again, I’ll suggest that a geographic variable specific to veggie-growing regions could be at play here.

As for beta-carotene and vitamin C concentrations in the blood, Campbell is correct in noting an inverse association with stomach cancer. However, the correlations aren’t statistically significant, nor are they very high: -14 and -13, respectively.

Campbell Claim #6

Western-type diseases, in the aggregate, are highly significantly correlated with increasing concentrations of plasma cholesterol, which are associated in turn with increasing intakes of animal-based foods.

From his book, we know Campbell defines Western-type diseases as including heart disease, diabetes, colorectal cancers, breast cancer, stomach cancer, leukemia, and liver cancer. And indeed, the variable “total cholesterol” correlates positively with many of these diseases:

Myocardial infarction and coronary heart disease: +4
Diabetes: +8
Colon cancer: +44**
Rectal cancer: +30*
Colorectal cancer: +33**
Breast cancer: +19
Stomach cancer: +17
Leukemia: +26*
Liver cancer: +37*

Perhaps surprisingly, total cholesterol has only weak associations with heart disease and diabetes—weaker, in fact, than the correlation between these conditions and plant protein intake (+25 and +12, respectively). But we’ll put that last point aside for the time being. For now, let’s focus on the diseases with statistical significance, which include all forms of colorectal cancer, leukemia, and liver cancer. (Despite classifying stomach cancer as a “Western disease,” by the way, China actually has far higher rates of this disease than any Western nation. In fact, half the people who die each year from stomach cancer live in China.)

First, let’s dive into the dark, murky chambers of the digestive tract and start with colorectal cancers. Off we go!

What Campbell overlooks about colorectal cancers and cholesterol

As I mentioned earlier, a little somethin’ called “schistosomiasis” is a profoundly strong risk factor for developing colon cancer and rectal cancer. In the China Study data, schistosomiasis correlates at +89*** with colorectal cancer mortality. Yes, 89—higher than any of the other 367 variables recorded.

This, ladies and gentlemen, is what we call a positive correlation.

It just so happens that total cholesterol also correlates with schistosomiasis infection, at a statistically significant rate of +34*:

Basically, this means that areas with higher cholesterol levels also had—for whatever reason—a higher incidence of schistosomiasis infection. It’s hard to say for sure why this is, but it’s likely that the high-cholesterol and high-schistosomiasis groups had a third variable in common, such as infected drinking water or other source of schistosomiasis exposure.

From this alone, it shouldn’t be too shocking that higher cholesterol also correlates with higher rates of colorectal cancer (+33*):

Clearly, we have three tangled-up variables to sort through: total cholesterol, colorectal cancer rates, and schistosomiasis infection. Is it really higher cholesterol that increases the risk of developing colon and rectal cancers, or is the influence of schistosomiasis deceiving us?

To figure this out, let’s look at what cholesterol and colorectal cancer rates look like only in regions with zero schistosomiasis infection. If cholesterol is a causative factor for colorectal cancers, then cancer rates should still increase as total cholesterol rises.

The above graph showcases a correlation of +13. Still positive, but not statistically significant, and a major downgrade from the original correlation of +33*. It does seem schistosomiasis inflates the correlation between cholesterol and colorectal cancers—something Campbell never takes into account. Is blood cholesterol still a risk factor? It’s possible, but we would need more data to know whether the +13 correlation persists or whether there are additional confounding variables at work. For instance, beer intake is another factor correlating significantly with both total cholesterol (+32*) and colon cancer (+40**).  If we remove the three counties that drink the most beer from of the data set above, the correlation between cholesterol and and colorectal cancer drops to -9.

See how tricky the interplay of variables can be?

What Campbell overlooks about leukemia and cholesterol

Next in our lineup of “Western diseases” is leukemia, which has a statistically significant correlation of +26* with total cholesterol. (Although the implication here is that animal product consumption raises leukemia risk, it should be noted that animal protein intake itself has a correlation of -5 with leukemia, whereas plant protein actually has a correlation of +15 with this disease. But let’s humor this claim anyway by looking solely at the role of blood cholesterol.)

If you’ll recall from the post on fish and disease in the China Study, leukemia correlates very strongly with working in industry (+53**) and inversely with working in agriculture (-53**). Although it’s possible the cause is nutritional, it’s also quite likely that an occupational hazard is to blame—such as benzene exposure, which is a major and well-known cause of leukemia in Chinese factory and refinery workers.

Lo and behold, cholesterol also correlates strongly with working in industry (+45**) and inversely with working in agriculture (-46**). If an industry-related risk factor raises leukemia rates, it could very well appear as a false correlation with cholesterol. How can we tell if this is the case?

Let’s try looking at the correlation between leukemia and cholesterol only in counties where few members of the population were employed in industry. If cholesterol itself heightens leukemia risk, our positive trend should still be in place. In the China Study data set, the range for percent of the population working in industry is 1.1% to  41.3%, so let’s try looking at the counties where the value is under 10%:

For the low-industry counties, the correlation between leukemia and total cholesterol is close to neutral—a mere +4. As you can see, this is hardly a damning trend. And in case you’re wondering if higher cholesterol could possibly spur the rates of leukemia in folks who are already at risk, this isn’t the case either: Using only counties that had 20% or more of the population working in industry, presumably the folks who had the most exposure to chemicals like benzene, the correlation between cholesterol and leukemia is a slightly protective -3.

What Campbell overlooks about liver cancer and cholesterol

I may not be vegan, but that doesn’t mean I like beating dead horses. Instead of rehashing the earlier analysis of liver cancer under Campbell Claim #3, I’ll just repeat that cholesterol does not have a significant correlation with liver cancer when you divide the data set into separate groups: areas with high hepatitis B rates an areas with low hepatitis B rates.

From page 104 of his book:

Liver cancer rates are very high in rural China, exceptionally high in some areas. Why was this? The primary culprit seemed to be chronic infection with hepatitis B virus (HBV). …

… But there’s more. In addition to the [hepatitis B] virus being a cause of liver cancer in China, it seems that diet also plays a key role. How do we know? The blood cholesterol levels provided the main clue. Liver cancer is strongly associated with increasing blood cholesterol, and we already know that animal-based foods are responsible for increases in cholesterol.

Campbell connects some of the dots, but misses a very important one. Indeed, hepatitis B associates strongly with liver cancer. Indeed, cholesterol associates with liver cancer. But what he doesn’t mention is that cholesterol also associates with hepatitis B infection. In other words, the groups with higher cholesterol are already at greater risk of liver cancer than groups with lower cholesterol—but it’s not because of diet.

In addition to greater rates of hepatitis B infection, higher-cholesterol areas had additional risk factors for liver cancer, such beer consumption, which also inflated the trend. Despite Campbell’s claims, cholesterol itself does not appear to significantly heighten cancer rates in at-risk populations.

Given Campbell’s casein research and earlier observations about the animal-protein consuming children in the Philippines getting more liver cancer, I wonder if Campbell approached the China Study already expecting a particular outcome. In a massive data set with 8,000 statistically significant correlations, even a smidgen of confirmation bias can cause someone to find a trend that isn’t truly there.

An example of bias in “The China Study”

Body weight, associated with animal protein intake, was associated with more cancer and more coronary heart disease. It seems that being bigger, and presumably better, comes with very high costs. (Page 102)

Consuming more protein was associated with greater body size. … However, this effect was primarily attributed to plant protein, because it makes up 90% of the total Chinese protein intake. (Page 103)

Let’s read between the lines. Here we have Campbell claiming two things, a few paragraphs apart: One, that body weight is associated with more cancer and heart disease, and two, that body size in China is linked not only with a greater intake of animal protein, but also with a greater intake of plant protein. In fact, the link between body size is stronger with plant protein than with animal protein.

Yet notice how Campbell only implicates animal protein in the association between body weight, cancer, and heart disease. If he were to describe the data without bias, Campbell’s first statement would be this:

Body weight, associated with animal protein intake and plant protein intake, was associated with more cancer and more coronary heart disease.

Maybe his editor just overlooked that omission, eh? Right afterward, Campbell notes:

But the good news is this: Greater plant protein intake was closely linked to greater height and body weight. Body growth is linked to protein in general and both animal and plant proteins are effective! (Page 102)

Wait a minute. This is good news? Didn’t Campbell just say being bigger “comes with very high costs” and that it’s associated with “more cancer and coronary heart disease?” Why is body size a bad thing when it’s associated with animal protein, but a good thing when it’s associated with plant protein?

Does less animal foods equal better health?

People who ate the most animal-based foods got the most chronic disease. Even relatively small intakes of animal-based food were associated with adverse effects. People who ate the most plant-based foods were the healthiest and tended to avoid chronic disease.

This oft-repeated quote from “The China Study” is compelling, but is it true? Based on the data above, it seems like an unlikely conclusion—but let’s try once more to see if it could be valid.

As an illustrative experiment, let’s look at the top five Chinese counties with the lowest animal protein consumption and compare them against the top five counties with the highest animal protein consumption. A data set of 10 won’t yield any confident conclusions, of course, and I won’t treat this as representative of the collective body of China Study data. But since animal protein consumption among the studied counties ranged from 0 grams* to almost 135 grams per day, we should see a stark contrast between the nearly-vegan regions and the ones eating considerably more animal foods. That is, assuming it’s true that “even relatively small intakes of animal-based food” yield disease.

*The county averaging zero grams per day wasn’t completely vegan, but the yearly consumption of animal foods was low enough so that the daily average appeared less than 0.01 grams.

Here are the counties I’ll be using. The first five are our near-vegans; the second five are our highest animal product consumers. From both groups, I had to exclude a top-five county due to missing data for most mortality variables (illegible documentation, according to the authors of “Diet, Life-style and Mortality in China”) and replaced it with a sixth county where animal protein consumption matched within a few hundredths of a gram.

Below are the names of each county, as well as values for their daily animal protein intake, the percentage of their total caloric intake coming from fat, and their daily intake of fiber (in case the latter two variables are also of interest).

To give you a visual idea of these quantities, 135 grams of animal protein is the equivalent of 22 medium eggs per day, 24 grams of animal protein is the equivalent of four medium eggs per day, 12 grams is two eggs, and 9 grams is one and a half eggs. Obviously, that’s quite a wide range even among the top consumers of animal foods, so the highest animal-food-eating counties (Tuoli and XIanghuang qi) may be the most important to study in contrast with the near-vegan counties.

Animal protein intake by county:

For reference, some other diet variables:

And now, mortality rates for important variables (as per 1000 people). I’ll save you my commentary and just show you the graphs, which should speak for themselves. Remember, the five left-most bars (Jiexiu through Songxian) on each graph are the near-vegan counties, and the five right-most bars (Tuoli through Wenjiang) are the highest consumers of animal products.

As you can see, the mortality rates for both groups (near-vegan and higher-animal-foods) are quite similar, with the animal food group coming out more favorably in some cases (death from all cancers, myocardial infarction, brain and neurological diseases, lymphoma, cervix cancer). This little comparison might not carry a lot of scientific clout due to its small sample size, but it does blatantly undermine Campbell’s assessment:

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.

Sins of omission

Perhaps more troubling than the distorted facts in “The China Study” are the details Campbell leaves out.

Why does Campbell indict animal foods in cardiovascular disease (correlation of +1 for animal protein and -11 for fish protein), yet fail to mention that wheat flour has a correlation of +67 with heart attacks and coronary heart disease, and plant protein correlates at +25 with these conditions?

Speaking of wheat, why doesn’t Campbell also note the astronomical correlations wheat flour has with various diseases: +46 with cervix cancer, +54 with hypertensive heart disease, +47 with stroke, +41 with diseases of the blood and blood-forming organs, and the aforementioned +67 with myocardial infarction and coronary heart disease? (None of these correlations appear to be tangled with any risk-heightening variables, either.)

Why does Campbell overlook the unique Tuoli peoples documented in the China Study, who eat twice as much animal protein as the average American (including two pounds of casein-filled dairy per day)—yet don’t exhibit higher rates of any diseases Campbell ascribes to animal foods?

Why does Campbell point out the relationship between cholesterol and colorectal cancer (+33) but not mention the much higher relationship between sea vegetables and colorectal cancer (+76)? (For any researcher, this alone should be a red flag to look for an underlying variable creating misleading correlations, which—in this case—happens to be schistosomiasis infection.)

Why does Campbell fail to mention that plant protein intake correlates positively with many of the “Western diseases” he blames cholesterol for—including +19 for colorectal cancers, +12 for cervix cancer, +15 for leukemia, +25 for myocardial infarction and coronary heart disease, +12 for diabetes, +1 for breast cancer, and +10 for stomach cancer?

Of course, these questions are largely rhetorical. Only a small segment of “The China Study” even discusses the China Study, and Campbell set out to write a publicly accessible book—not an exhaustive discussion of every correlation his research team uncovered. However, it does seem Campbell overlooked or ignored significant points when discerning the overriding nutritional themes in the China Project data.

What about casein?

Along with trends gleaned from the China Project, Campbell recounts the startling connection he found between casein (a milk protein) and cancer in his research with lab rats. In his own words, casein “proved to be so powerful in its effect that we could turn on and turn off cancer growth simply by changing the level consumed” (page 5 of “The China Study”). Protein from wheat and soy did not have this effect.

This finding is no doubt fascinating. If nothing else, it suggests a strong need for more research regarding the safety of casein supplementation in humans, especially among bodybuilders, athletes, and others who use isolated casein for muscle recovery. Unfortunately, Campbell extrapolates this research beyond its logical scope: He concludes that all forms of animal protein have similar cancer-promoting properties in humans, and we’re therefore better off as vegans. This claim rests on several unproven assumptions:

  1. The casein-cancer mechanism behaves the same way in humans as in lab rats.
  2. Casein promotes cancer not just when isolated, but also when occurring in its natural food form (in a matrix of other milk substances like whey, bioactive peptides, conjugated linoleic acid, minerals, and vitamins, some of which appear to have anti-cancer properties).
  3. There are no differences between casein and other types of animal protein that could impose different effects on cancer growth/tumorigenesis.

Campbell offers no convincing evidence that any of the above are true. We do share some metabolic similarities with rats, so for the sake of being able to entertain the possibility that #2 and #3 are valid, let’s assume that the effect of casein on rats translates cleanly to humans.

How does Campbell justify generalizing the effects of casein to all forms of animal protein? Much of it is based on a study he helped conduct: “Effect of dietary protein quality on development of aflatoxin B[1]-induced hepatic preneoplastic lesions,” published in the August 1989 edition of the Journal of the National Cancer Institute. In this study, he and his research crew discovered that aflatoxin-exposed rats fed wheat gluten exhibited less cancer growth than rats fed the same amount of casein. But get this: When lysine (the limiting amino acid in wheat) was restored to make the gluten a complete protein, the rats had just as much cancer occurrence as the casein group. Jeepers!

Campbell thus deduced that it’s the amino acid profile itself responsible for spurring cancer growth. Because most forms of plant protein are low in one or more amino acids (called “limiting amino acids”) and animal protein is complete, Campbell concluded that animal protein, but not plant protein, must encourage cancer growth. Time to whip out the veggie burgers!

Of course, this conclusion has some gaping logical holes when applied to real life. Unless you consume nothing but animal products, you’ll be ingesting a mixed ratio of amino acids by default, since animal foods combined with plant foods still yield limiting amino acids. The rats in Campbell’s research consumed casein as their only protein source, the equivalent of someone eating zero plant protein for life. An unlikely scenario, to be sure.

Moreover, certain combinations of vegan foods (like grains and legumes) have complementary amino acid profiles, restoring each other’s limiting amino acid and resulting in protein that’s complete or nearly so. Would these food combinations also spur cancer growth? How about folks who pop a daily lysine supplement after eating wheat bread? If Campbell’s conclusions are correct, it would seem vegans could also be subject to the cancer-promoting effects of complete protein, even when eschewing all animal foods.

Also, it seems Campbell never mentions an obvious implication of a casein-cancer connection in humans: breast milk, which contains high levels of casein. Should women stop breastfeeding to reduce their children’s exposure to casein? Did nature really muck it up that much? Are children who are weaned later in life at increased risk for cancer, due to a longer exposure time the casein in their mothers’ milk? It does seem strange that casein, a substance universally consumed by young mammals, is so hazardous for health—especially since it’s designed for a time in life when the immune system is still fragile and developing.

At any rate, Campbell’s theories about plant versus animal protein and cancer are essentially speculation. Despite a single experiment with restoring lysine to wheat gluten, he hasn’t actually offered evidence that all animal protein behaves the same way as casein.

But check this out. After delineating his discovery of the link between casein and cancer, Campbell writes:

We initiated more studies using several different nutrients, including fish protein, dietary fats and the antioxidants known as cartenoids. A couple of excellent graduate students of mine, Tom O’Conner and Youping He, measured the ability of these nutrients to affect liver and pancreatic cancer. (Page 66)

So he did experiment with an animal protein besides casein! Unfortunately, Campbell never mentions what the specific results of this research were. In describing the studies he conducted with his grad students, Campbell says only that a “pattern was beginning to emerge: nutrients from animal-based foods increased tumor development while nutrients from plant-based foods decreased tumor development.” (Page 66)

I don’t know about you, but I’d sure like to see the actual data for some of this.

After a little searching, I found one of the aforementioned experiments conducted by Campbell, his grad student Tom, and two other researchers. It was published in the November 1985 issue of the Journal of the National Cancer Institute: “Effect of dietary intake of fish oil and fish protein on the development of L-azaserine-induced preneoplastic lesions in the rat pancreas.”

(A preneoplastic lesion, by the way, is a fancy term for the growth that occurs before a tumor.)

In this study, Campbell and his team studied three groups of carcinogen-exposed rats: One fed casein plus corn oil, one fed fish protein plus corn oil, and one fed fish protein plus fish oil (from a type of high omega-3 fish called menhaden). All groups received a diet of about 20% protein and 20% fat and ate the same amount of calories.

Providing background for the study, the authors note that previous research has showed fish protein to have anti-cancer properties (emphasis mine):

Gridley et al. [n15,n16] reported on two studies in which intake of fish protein resulted in a reduced tumor yield when compared to other protein sources. Spontaneous mammary tumor development in C3H/HeJ mice was reduced. The incidence of herpes virus type 2-transformed cell-induced tumors in mice was also reduced in animals fed a fish protein diet.

Perhaps this should’ve tipped Campbell off that not all sources of animal protein spur cancer growth like casein does. For reference, the cited studies are “Modification of herpes 2-transformed cell-induced tumors in mice fed different sources of protein, fat and carbohydrate” published in the November-December 1982 issue of Cancer Letters, and “Modification of spontaneous mammary tumors in mice fed different sources of protein, fat and carbohydrate” published in the June 1983 issue of Cancer Letters.

So what were the results of Campbell’s experiment? According to the study, both the casein/corn oil and fish protein/corn oil groups had significant preneoplastic lesions. We don’t know whether to blame this on the protein or the corn oil, since—according to the researchers—intake of corn oil has previously been shown to promote the development of L-azaserine-induced preneoplastic lesions in rats.” However, the group that ate fish protein plus fish oil exhibited something radically different:

It is immediately apparent that menhaden oil had a dramatic effect both on the development in the number and size of preneoplastic lesions. The number of AACN per cubic centimeter and the mean diameter and mean volume were significantly smaller in the F/F [fish protein and fish oil] group compared to the F/C [fish protein and corn oil] group. Furthermore, no carcinomas in situ were observed in the F/F group, whereas the F/C group had an incidence of 3 per 16 with 6 total carcinomas.

There’s some significant stuff here, so let’s break this down point by point.

One: The cancer-inducing properties of fish protein, if there are any to begin with, were neutralized by the presence of fish oil. This means that even if all animal protein behaves like casein under certain circumstances, its effect on cancer depends on what other substances accompany it. Animal protein is therefore not a universal cancer promoter; only a situational one, at best.

Two: What does “fish protein” plus “fish fat” start to resemble? Whole fish. Campbell just demonstrated that animal protein may, indeed, operate differently when consumed with its natural synergistic components.

Since there wasn’t a rat group eating casein plus fish oil, we don’t know what the effect of a dairy protein plus fish fat would have been. However, it would be interesting to have more studies looking at cancer growth in mice fed diets of casein plus milk fat. If casein loses its cancer-promoting abilities under that circumstance, as fish protein did with fish oil, then we’d have good reason to think the various factions of whole animal products might reduce any cancer-promoting properties a single component has in isolation.

And Campbell and his team conclude:

[A] 20% menhaden oil diet, rich in omega 3 fatty acids, produced a significant decrease in the development of both the size and number of preneoplastic lesions when compared to a 20% corn oil diet rich in omega 6 fatty acids. This study provides evidence that fish oils, rich in omega 3 fatty acids, may have potential as inhibitory agents in cancer development.

Remember how Campbell said, summarizing this research, that “nutrients from animal-based foods increased tumor development while nutrients from plant-based foods decreased tumor development”? Last I checked, fish oil ain’t no plant food.

Why does Campbell avoid mentioning anything potentially positive about animal products in “The China Study,” including  evidence unearthed by his own research? For someone who has openly censured the nutritional bias rampant in the scientific community, this seems a tad hypocritical.

But back to casein and milk for a moment. It’s interesting that the only dairy protein Campbell experimented with was casein, since whey—the other major protein in milk products—repeatedly shows cancer-protective and immunity-boosting effects, including when tested side-by-side with casein. Just a sampling of the literature:

Given all this, it seems unlikely that casein’s effects on cancer apply to other forms of milk protein—much less all animal protein at large. Isn’t it possible (maybe even probable) that casein has deleterious effects when isolated, but doesn’t exhibit cancer-spurring qualities when consumed with the other components in milk? Could casein and whey work synergistically, with the anti-cancer properties of whey neutralizing the pro-cancer properties of casein?

I’ll let you be the judge.

In summary and conclusion…

Apart from his cherry-picked references for other studies (some of which don’t back up the claims he cites them for), Campbell’s strongest arguments against animal foods hinge heavily on:

  1. Associations between cholesterol and disease, and
  2. His discoveries regarding casein and cancer.

For #1, it seems Campbell never took the critical step of accounting for other disease-causing variables that tend to cluster with higher-cholesterol counties in the China Study—variables like schistosomiasis infection, industrial work hazards, increased hepatitis B infection, and other non-nutritional factors spurring chronic conditions. Areas with lower cholesterol, by contrast, tended to have fewer non-dietary risk factors, giving them an automatic advantage for preventing most cancers and heart disease. (The health threats in the lower-cholesterol areas were more related to poor living conditions, leading to greater rates of tuberculosis, pneumonia, intestinal obstruction, and so forth.)

Even if the correlations with cholesterol did remain after adjusting for these risk factors, it takes a profound leap in logic to link animal products with disease by way of blood cholesterol when the animal products themselves don’t correlate with those diseases. If all three of these variables rose in unison, then hypotheses about animal foods raising disease risk via cholesterol could be justified. Yet the China Study data speaks for itself: Animal protein doesn’t correspond with more disease, even in the highest animal food-eating counties—such as Tuoli, whose citizens chow down on 134 grams of animal protein per day.

Nor is the link between animal food consumption and cholesterol levels always as strong as Campbell implies. For instance, despite eating such massive amounts of animal foods, Tuoli county had the same average cholesterol level as the near-vegan Shanyang county, and a had a slightly lower cholesterol than another near-vegan county called Taixing. (Both Shanyang and Taixing consumed less than 1 gram of animal protein per day, on average.) Clearly, the relationship between animal food consumption and blood cholesterol isn’t always linear, and other factors play a role in raising or lowering levels.

For #2, Campbell’s discoveries with casein and cancer, his work is no doubt revelatory. I give him props for dedicating so much of his life to a field of disease research that wasn’t always well-received by the scientific community, and for pursuing so ardently the link between nutrition and health. Unfortunately, Campbell projects the results of his casein-cancer research onto all animal protein—a leap he does not justify with evidence or even sound logic.

As ample literature indicates, other forms of animal protein—particularly whey, another component of milk—may have strong anti-cancer properties. Some studies have examined the effect of whey and casein, side-by-side, on tumor growth and cancer, showing in nearly all cases that these two proteins have dramatically different effects on tumorigenesis (with whey being protective). A study Campbell helped conduct with one of his grad students in the 1980s showed that the cancer-promoting abilities of fish protein depended on what type of fat is consumed alongside it. The relationship between animal protein and cancer is obviously complex, situationally dependent, and bound with other substances found in animal foods—making it impossible extrapolate anything universal from a link between isolated casein and cancer.

On page 106 of his book, Campbell makes a statement I wholeheartedly agree with:

Everything in food works together to create health or disease. The more we think that a single chemical characterizes a whole food, the more we stray into idiocy.

It seems ironic that Campbell censures reductionism in nutritional science, yet uses that very reductionism to condemn an entire class of foods (animal products) based on the behavior of one substance in isolation (casein).

In sum, “The China Study” is a compelling collection of carefully chosen data. Unfortunately for both health seekers and the scientific community, Campbell appears to exclude relevant information when it indicts plant foods as causative of disease, or when it shows potential benefits for animal products. This presents readers with a strongly misleading interpretation of the original China Study data, as well as a slanted perspective of nutritional research from other arenas (including some that Campbell himself conducted).

In rebuttals to previous criticism on “The China Study,” Campbell seems to use his curriculum vitae as reason his word should be trusted above that of his critics. His education and experience is no doubt impressive, but the “Trust me, I’m a scientist” argument is a profoundly weak one. It doesn’t require a PhD to be a critical thinker, nor does a laundry list of credentials prevent a person from falling victim to biased thinking. Ultimately, I believe Campbell was influenced by his own expectations about animal protein and disease, leading him to seek out specific correlations in the China Study data (and elsewhere) to confirm his predictions.

It’s no surprise “The China Study” has been so widely embraced within the vegan and vegetarian community: It says point-blank what any vegan wants to hear—that there’s scientific rationale for avoiding all animal foods. That even small amounts of animal protein are harmful. That an ethical ideal can be completely wed with health. These are exciting things to hear for anyone trying to justify a plant-only diet, and it’s for this reason I believe “The China Study” has not received as much critical analysis as it deserves, especially from some of the great thinkers in the vegetarian world. Hopefully this critique has shed some light on the book’s problems and will lead others to examine the data for themselves.


    1. I find this very amusing!!! All of you give this Denise so much credit and really don’t understand the formulas!!!I’ll stick with the experts who have spent years,time and money to prove their facts!!!Also, we will be meeting with Colin Campbell on Feb.26th at Sublime Restaurant in Ft. Lauderdale along with Dr. Neal and other Dr’s and scientist!! I’ll print this out and bring it with me!!I’m sure they will have fun with this!!!
      It is very obvious that we are dealing with denial and reisistance to validate your own choices!!!!
      Those of you who put so much faith into this article, should really do your own research!!

      1. Fun. I am curious as to how the restaurant meeting with the Dr.s went and if they in fact laughed and scorned Minger’s responsive analysis. Science relies upon the constant examination by others to find any and all inconsistencies or errors. To believe all that is said in one book or by one scientist doesn’t make you right. It just means you’ve picked a side. Root on fan!!

      2. Dear dlibby,

        I have not double checked Denise’s math. Have you?

        We get that you believe her conclusion is wrong. Why?

        Prove to us that you assertions are founded in reason instead of in your own bias or blind clinging to authority.

        Her method of analysis is transparent. Yours is not.

        She has point out direct correlations in source data. You replied only by calling her names.

        If her conclusion is wrong, then logical and analysis should prove that it is wrong.

        Calling her more names will not make her analysis more or less true. If she is wrong, show us why.

        Don’t just say you can. Show us. That will change more minds to your way of thinking than anything you have written to date.

        If you cannot, then please tell us why you wrote what your wrote.

        1. This is exactly how CAGW-skeptics are treated by climate threat alarmists.
          The skeptic points out direct correlations in source data. The alarmist replies by calling the skeptic names. Interesting.

          1. That’s because the same pattern exists between the China Study and climate change science. Some people spend many years doing careful analysis of all the data, setting their studies in the wider context of previous knowledge and publishing their results in peer-reviewed journals. This is called science. Then other people, with no training in the subject, think they know better, do some simplistic and superficial analysis, and stick it on a blog. This is called skepticism.

            1. The China Study is not scientific research; it’s a mass-market book with a fervent mission. It doesn’t matter how many scientific studies he cites or who reviewed them – the book consists of his analysis and conclusions, and it has not been peer-reviewed.

              You may have missed the part where Dr. Campbell admitted that he picked through the China data looking for what would confirm his already-developed hypothesis. Whatever work he has done in the past, this is not science.

              What Denise has done is point out some of what he ignored and disregarded in the process that calls his conclusions into question.

              The way to rebut her would be point by point. Where is that rebuttal? I cannot find one, by Campbell or anyone else.

                  1. Jack, you are a bit ignorant also. He names himself ‘el jefe’ which is Spanish for ‘the boss’ , suggesting that he might be a Spanish speaker and so far,Jesus is a completely normal name in Spain and in all the Spanish-speaking American countries.

      3. I find you amusing (pardon my lack of exclamatory punctuation, but I harbor the however inane notion that the words I select will suffice to
        augur what opinions I reserve)…and–pardon my lack of restraint for that which follows–somewhat deficient in the realms of literary abilities, general science research, & understanding, and anger

        Admittedly, to draw so much conclusion from so few words might be
        suspect here, but I’ve already sought pardon, and I yet think you to be
        quite immature and, in this specific arena of diet-and-health, overtly
        unqualified so as to be, in any relevant manner, a serious consideration to the issues in review here.

      4. I understand the formulas. I’m a statistician. And I know that by doing only univariate correlations, Campbell is making a first-year undergrad-level error. Statistical modeling involves multiple statistics, not one or two variables taken in isolation. The fact that when we run multivariate analysis on several factors the claimed association between animal products and disease vanishes or reverses tells us that what we were measuring in the univariate analysis was not the effect of ‘animal products’, but the effects of additional confounding variables.

        Minger, fresh from University, no doubt has the rules of good statistics still strong in her mind. Campbell has been in the field for years and may have let his statistical practice slip or not kept up with modern techniques. Skills need to be kept sharp and practiced constantly to be useful, and statistics is no exception. I would put more faith in someone with recent statistical training or refresher training than in someone who has been practicing the same stodgy, ineffective techniques for decades without learning anything new, and who is approaching the data with a clear bias.

        1. Er, I think you should try reading the posts in more detail. It is Campbell who did the multivariate analyses in The China Study, and Denise Minger who has made the first-year undergrad-level error by doing univariate analysis. Trying reading the book before commenting.

            1. You are agreeing that Campbell did the multivariate analyses, because you read the book? or just that Denise did not?

            1. She did a univariate to show that he did not do a true multivariate analysis, by hypothesizing different possible dependencies. Instead of zeroing in on the technique, try reading it from the perspective of trying to understand the data.

          1. Spot on. Its amazing how the internet works… we give so much attention to an uneducated blogger and then praise her for it…. the world we live in

        2. This is absurd. It suggests that experts in fields of study are less qualified than college graduates because college graduates have the most up to date science. College graduates are educated by leaders in their respective fields. In addition fat and protein apologists never seem to be able to address the fact that people recover from a myriad of diseases when they go on a low fat plant based diet. If Denise was right, Dr. McDougall, Dr. Esselstyn & Dr. Barnard would not have the success they do in addressing cancer, heart disease and diabetes.

          1. Even an expert needs evidence to prove an argument. People recover from a myriad of diseases when they lay off the junk food. Most junk-food/processed-food is low fat plant based. You can recover from a myriad of diseases by switch to raw milk or raw fish. Man does not live by sugar and plant protein alone.

      5. dlibby. This is the first most unintelligent post I read yet. Your response is unscientific, immature and meant to inflame. So I’ll respond with your tone. You brag about meeting Colin, which is irrelevant. He could care less what you say or his critics say. I bet you didn’t print this and didn’t show him. I bet your “dinner meeting” consisted if you paying $100’s to sit a 100 ft away while he gave a speech and signed a few books. You then say “do your own research” but you say “stick with the experts”. I guess you’re the expert to determine who are the experts. The fact that you cannot undersatnd the formulas indicates you are just a cow eating the “grass” and you have no mind or no brains to study nutrition. Faith in science is not faith, it’s fact. Colin attempted science and failed. The writer here responds with more science than Colin ever considered and he’s the one selling books to millions. So, continue being a Campbell groupie and keep on living in denial yourself.

        1. You obviously have no idea what you’re talking about but i must admit that as lame as your you’re reply to Dlibby was, it was also quite comical.

          1. Nice try dlibby in disguise. Ad hominems are not great arguments. Neither is supporting yourself with a different name.

      6. True experts do not (or SHOULD not) spend time and money to ‘prove facts’.
        True scientists explore hypotheses. It is virtually impossible to prove most of them; all one can do is find evidence to support or contradict them.
        I suspect that as you can’t even pluralize formula that you probably don’t understand the formulae either.

        1. if something is considered proven, then it is considered a fact; that’s why experts don’t try to prove facts, they understand the grammar/logic of the language. however, if you think they should not try to prove to others what they claim because it’s beneath them, you’re talking from a pre-enlightenment religious dogma framework.

          1. That’s actually incorrect.

            For something to be a ‘fact’, it must be proven and re-proven a great number of times. Just proving it once doesn’t make it a fact.

            Experts do need to prove facts – more importantly, to continuously tweak variables and test if the facts continue to hold up ever under completely different circumstances.

    2. Thank you for this work Denise. What a thoughtful and critical (in the very good sense of that word) piece of work. Your approach is direct and compelling.
      For some time now I’ve been discouraged that so many people who don’t know statistical analysis misuse it dreadfully – but people who SHOULD know their statistical analysis and are able to use it responsibly and yet STILL misuse it dreadfully…well that’s another ball of wax!
      Again, thank you.

      1. How ironic you make this statement about people misusing statistical analysis – Denise clearly is out of her depths and you are thanking her???

        1. Denise spent a lot of time and concentrated effort to show the errors of Campbell. Instead of saying she’s wrong, show us where she is wrong through your efforts. Anybody can make an unsupported claim.

        2. I’m an ex-honours student in stats .. Denise is spot on.

          The key to understanding results like those produced by Campbell, is that you should never confuse correlation with causation. None of the correlations produced by Campbell prove any causal relationships. Showing a ‘statistically significant correlation’ only indicates a relationship that is ’caused’ by a number of other underlying or associated factors.

          For example, lightening is strongly correlated with rain. Does that mean that lightening causes the rain? Of course not!.. Once you find a strong correlation you need to understand the actual causes. Lightening and rain are strongly correlated because of clouds – clouds are what cause both lightening and rain. But if you used Campbell’s logic, you’d get wet every time you got some static electricity from rubbing your shoes on carpet.

          Campbell’s study has not provided any evidence for any of his conclusions. His study is a great accumulation of ideas to test with the correct hypothesis (ie. proving the null hypothesis), but his conclusions are genuinely unsupported.

    3. Let’s see if I understand this. Preferred sources of protein are fish, eggs, and whey. Don’t eat Elmer’s Glue. Get some sun each day. Get tested regularly for schistosomiasis. Does that sum it up in a nutshell?

    4. The only amusing and ironic thing here is the fact that no matter what subject on Earth there is , people fight about it. Football, electronics, religions, politics and now some study.
      I wonder: what is worse to health? Meat, processed foods or all the frustration and unhappiness that leads to disputes everywhere for every possible subject?

      So great I gave up meat because of respect for life and I don’t even care if it was unhealthy or not.
      Best wishes everyone!

      1. I do soooo agree with you! What could ever be wrong with health? Less money in the pockets of men, torturing animals? It’s all about the money….always!
        I think it’s best for all to eat a plant-based diet: for humans because of their (mental) health, for animals because otherwise they are being tortured to feed humans.

        1. Plants aren’t sentinent beings.

          “And God said, Behold, I have given you every herb-bearing seed which is upon the face of all the earth, and every tree in which is the fruit of a tree yielding seed: to you it shall be for meat.”
          -Genesis 1:29

      2. I’m guessing your respect for life doesn’t extend to the little insects that meet their doom in the form of your shoe (or car tire) crashing down upon their existence, fast tracking them to oblivion. Selective reasoning is bliss.

        1. not “selective” reasoning when you account for intention. you might want to do more reading on this subject (and on “reasoning” for that matter) before you comment. thank you.

    5. Denise,

      I just read this post, and I am amazed at your excellent analysis.

      A few days ago, a friend loaned me a copy of “The China Study”, and my initial reaction was disappointment that Campbell’s graphs and charts provided so little evidence for his major conclusions. Then I found your critique, which articulated my own suspicions… and raised several more that I did not even consider.

      Your criticism was very courteous and deferential to Campbell, and I commend you for it. Not everyone would be as tolerant, especially to a famous researcher who uses an “intervening variable” like cholesterol when the raw data provide little or no direct correlation between animals products and various diseases. Most veterans of statistical analysis would have no patience for this slipshod…or slippery… presentation.

      Thanks again for your significant contribution.

      Bob Flood

    6. Congratulations on being a nutritionally semi-educated, statistically-illiterate, but well spoken blogger. As much as you dismiss Bill Gates’ educational failure vs. his business success in computers as evidence that education makes no difference in scientific endeavour; you might consider this: Bill Gates has been farting around with computers since he was a kid – long before most people knew that they even existed. He learned a lot by creating. The big difference between science and creation using applied science is that there is no truth. It just progresses. Bill Gates NEVER argued against the underlying science. He NEVER claimed that silcon was not a good medium for chips. He NEVER said that software was just a fad. (he did muse that “why would anyone need more than 640K – but that is just more of the same). Bill gates was a fly compared to IBM when he started. He did not refute everything they did or said or discovered. He made a way to progress it. He wrote their operating system. If YOU want to be Bill Gates – or have any credibility in your conceit to compare yourself to him, you might want to adapt your approach, You would stop attacking IBM (Dr. Campbell) and his thesis (silicon chips make good processors). Were you to wear his pedigree, you would have been doing research into nutrition since the age of 8 in your bedroom at night with Mom yelling “GO TO BED”. You wear your lack of education like a badge. I have a degree in statistics and engineering. Undergraduate only. So I am also not that well educated. However, I did focus on the statistics. Your analysis is deeply flawed in its critique.

      1. What many of you fail to realize is that owning a television and actually watching it from time to time causes heart attacks, especially in the USA where every heart attack is associated with a television in the home. Therefore, if you throw your television away, you will avoid heart attacks and certainly will have less stress in your life. I think I am correct, therefore I am. (I have a 50% shot at being right at least. If I am right, I am right and if I am wrong, I am wrong. See, 50/50

        1. I’ve also heard that at some point in their lives every heart attack victim ate a banana. Coincidence? I think not.

      2. By the way, my favourite univariate analysis is this: ïce cream causes drowning”. It is hard to find a stronger correlation coefficient than that between the consumption of ice cream the incidence of drowning. Try to figure that one out.

        1. Yep, univariate correlations are pretty much crap in observational studies.

          Were you also aware that larger shoe size in schoolchildren causes better spelling ability?

      3. To go on and on about Bill Gates and then end with a conclusion that the analysis on a separate topic is deeply flawed without explaining how doesn’t really set you up as a credible critic.

        1. It is flawed because it is limited to bivariate analyses (two variables at a time, ignoring everything else—which is pretty much Campbell’s thesis as being a problem with prior research–you can’t look at it so simply) and also because it tries to infer conclusions from non-statistically significant correlations. The data requires much more complex statistical analysis.

          Denise has found absolutely nothing here of interest. Her methods are unsophisticated and meaningless in this context.

          —A statistician

      4. Uh, uhm, Bill Gates is the world’s largest supplier of death-meds to stop live births to third world mothers and deliver infertility to involuntary male victims in his prey-sights. So, he’s a great man, eh?

        Actually you are like the vegans who refuse to allow factful comments on their blogs, who go around spreading hate on open blogs where facts about the vegan death diet are posted.

        Ever consider getting honesty in your mind?

      5. I agree with John. It EASY To Criticized so you can DRAG the other person down. I have learned after 55 years of being adult that it the one that “demeaned” is the one to DON’T TRUST.You can take Dr. Campbell’s 2 cents worth and do whatever you please with it for yourself.
        Years of medical education ?
        Years of Biochemistry education?
        Years of clinical practice ?
        Years of research? ETC??????

    7. Very interesting. As far as the cholesterol link is concerned, it depends whether you see high cholesterol as a cause, or as a symptom of disease. Whilst much of the scientific community out there assumes it is causative, if you contemplate cholesterol’s role within the body as a substance the body uses in repair and restoration, then any kind of disease is almost certainly going to result in higher levels as it scoots around the body doing its job.

      Seeing it as a symptom rather than a cause would throw the whole caboosh out of the window.

      As far as the study is concerned, it’s called the China Study because it studied people in China. Generally, the chinese – especially in rural areas – eat a far more natural diet, whether predominantly plant-based, or meat-based, so how can it possibly have any real bearing on the effects of diet on people eating the ‘Western’ diet, full of sugar, processed carbs, chemicals and food that is generally mucked-about-with?

      Dairy is also not a good comparison – whilst many groups in the World consume dairy and are healthy on it, it is raw and unpasteurised – complete. As the pasteurisation process destroys some of the elements within the milk, it becomes denatured and doesn’t react in the body in the same way as raw milk. The elements within the food communicate with the body – give it instructions on what to do with it. Once they are damaged, the body cannot process it as it should, and it then has the potential to become toxic. A small amount now and again may be tolerable, but when that is the only source of dairy consumed continuously, there has to be a fall-out at some point. Is it the cows milk Casein that is the problem, or the fact that some of the other elements that are needed for its digestion and processing in the body have been destroyed prior to its consumption?

      Statistics cannot ever be true when there are so many different variables to take into consideration – and even missing just one can, and frequently does, throw concepts off into a whole different – and sometimes downright dangerous – direction. How can anyone ever make assumptions based on statistics if they don’t even understand (or only THINK they understand) why certain things act in certain ways or what they do?

      1. Alison, thank you sooooo much for saying EVERYTHING I’d been thinking while reading this critique and the subsequent responses. I wholeheartedly agree, and I would’ve considered the entire critiqu an even more successful effort–I still give Denise prod for the analysis and willingness to question a lot of things I’d started to question myself–if any mention had been made of the differences between “western” and Chinese rural diets or the raw milk/dairy intake, and especially of cholesterol as a symptom of disease. BRAVO

    8. The u.S.A. is filled with unbelievable numbers of STUPID people! I cannot get over how many closed-mind “liberals” there are! But, it’s logical, since the Source of America’s greatness, Creator, was chased away along with His human health guide!

      What’s left is stupid, willy-nilly nutcakes running around electing the likes of Bush and nobama, who are NOT actually presidents, but in reality mere stooges acting out their orders given by banksters running the world.

      Really, it’s “good bye, America.”

      Just study end-time records given humans by Creator in Hebrew Scripture to see why America disappears . . .

    9. Thanks to Denise, we have a proper interpretation of the study he conducted.
      Thanks Dr. Campbell for providing data that supports an omnivoric diet and disproving any information that vegetarianism is healthier.

    10. Dear Denise,

      this indeed is a smart analysis, thank you very much!
      In the whole debate one important fact usually is missed: we all have to die one day. And we will have one weakest organ which will make the body stop working in the end. Thus, everyone will have a final diagnosis. As we are built on a carbo basis and as we are using oxygen as the fuel for the cells, we will all develop cancer, if only living long enough. This is derived from the little mistake in construction (carbo based + oxygen fueled leads to cancerogenic changes of tissue – blame God, but think of the alternatives first…). It therefore is of no interest wether somenone get’s cancer or not, but it is of utmost interest wether he will die from cancer prematurely! Prematurely is not defined in this context. One might agree that 30somethings should not die from cancer, might silver liners? Is it okay to die by 90? There is no real answer to that, I suppose. Data should better be analysed not only by cause of death, but also by years reached and furthermore by quality adjusted lifeyears. I’d prefer for myself to die at 80 by cancer rather than dying at 60 from a heart attack. The war against cancer is a dumb idea, misleading people and filling them with false hope – and a great waste of money.

      With kindest regards,

    11. The volume of snarky comments on this thread is nauseating. Nutrition debates seem to be more often a game of pride and personal attacks. “I know more than you do!! Maybe you should actually do your research!!!” Pathetic. I’m going outside.

    12. Good work, Denise. I have a question about claim #1: in the original study, were the people followed-up to see if they develop cancer or other diseases or were the diagnoses recorded at one time point only at the same time with information on diet, blood-work etc? If so, did they look into how soon cancers developed after detection of high cholesterol levels? What I’m aiming at is that due to altered energy metabolism, cancer may increase triglyceride and total cholesterol levels before it’s even diagnosed. Of course, this would only explain a very small proportion of the associations.

    13. Maybe it’s time for this Denis to take off her/his blog, or at least some of the fallacies he/she wrote! 1. he/she has no qualifications to dare try debunking a scientific study, that was made in vitro, in vivo, on clinical subjects compared with statistic data amounting to the population of China! This would mean that whatever she wrote there, was proofread by a statistician, chemist, biologist (micro-biologist), doctor… well, a whole team of people of different specialisation. Dr Campbell did the study with a team of scientists, not alone in a lab or in a bedroom like this Denis and her blog 2. Meanwhile also other (and not few) studies have checked if the high protein intake is the dominator of degenerative diseases, and surprised.. they seconded Campbell. These are FELLOW SCIENTISTS, NOT A NO-ONE FROM INTERNET 3. to keep a normal intake of protein is automatically forcing u to be a vegan as diet 4. meanwhile other studies (and not few) have proved that protein of animal provenance is actually, even worse. 5. China study was never debunked, scientifically for real I mean! And the pro paleo diet, damn they tried so hard (some even on the field, doctors). China Study was not debunked! So luckily, it is not false even if some (for what ever mental reasons they have) are trying so deeply to reject the news! 6. An idiot claimed that China Study was proved false, and referenced back to this stupid blog, wrote by who the heck is Denis! This is disturbing! The disclaim this Denis used, should sound more like: I AM NOT A DOCTOR, NOR A BIOLOGIST, NOR A SCIENTIST, THIS BLOG IS MY PERSONAL OPINION AND PERCEPTION AND IT COULD BE, SCIENTIFICALLY, INCORRECT! 7. I am sorry to break this to some, but it appears that indeed the dominator for the degenerative diseases, is the high protein intake (with reference to animal source protein).

    14. If Denise ever feels the need to earn a living in an alternative profession then I can tell her she is well suited to modern horse racing betting. Her love of data analysis would make her a formidable player. On a more serious note, what can we run with from all this. Well no one seems to be arguing with the removal of sugar and wheat from our diets. Dump the sugar and simple carbs and all the dwarf wheat we have been poisoned with over the years.

    1. I agree. Not much else can we assume from this. Oh!!!! the natural and pure food. And also, great post Mircea C. Really, loved it.

  1. This. is. Awesome.

    GREAT job, Denise! I don’t know what to make of all this- it’s crazy. Campbell’s crazy.
    I know you’re always nice to everyone, so I’ll say it for you; Campbell’s a freakin’ LIAR. I can’t believe this! Wow, I’m totally NOT referencing China Study again.

    Well at least now we know the truth. Let’s spread it, people!

    Once again, thank you and congratulations. This is amazing.

    1. Apple-man,

      Not sure if you’ll get this, but I just wanted to say you have an admirer. I’ll admit I’ve been lurking around the 30bad forum out of a mix of curiosity and amazement–I’ve never seen passive-aggressive played out in typed words like that in my life, and I’m in awe. Anyhoo, I appreciate your ability to keep your head up and speak your mind as an individual. Kudos to you and your ability to think critically. Keep it real, man.

  2. Fantastic. I’m particularly interested in the correlation between wheat and disease. I’ve been writing about this for a while– mostly on the basis of fairly weak indirect evidence because there’s very little research on the health effects of wheat vs. other grains except in celiac patients. This is probably the best support I’ve seen for the hypothesis. And to think it came from the China study!

    Here’s a study supporting wheat’s association with obesity in China (compared to rice; see table 3):

    And my interpretation:

    1. Once again – correlation is NOT causation. A correlation between wheat and disease only means there are things usually happen at the same time. Maybe wheat has a high correlation with heart disease because people who eat more wheat:

      a) come from lower income families
      b) generally eat more fast food
      c) generally eat more butter or spreads
      d) do not eat a balanced diet
      e) are older
      f) are younger
      g) are male
      h) are female
      i) come from cultural background more genetically predisposed to the diseases in the study
      j) share similar environmental factors which were responsible for disease

      There are lots of different underlying factors which must be understood and controlled for, and once a specific relationship is identified using correlation, it must be separately studied using causal studies – not correlations.

  3. By the way, I would be super grateful if you could work your magic on the wheat data to see if it’s likely to be spurious or not. e.g., is it due to wheat’s association with heavy metals, infectious disease, latitude, etc. I suspect controlling for latitude will attenuate the association, since as I understand it wheat is mostly eaten in Northern China.

    I’m going to link to this post in the next few days, after Richard Nikoley does, since he passed it on to me.

  4. As I read this, Denise, I can’t help but wonder: will your findings have any ramifications on your own approach to diet and health?

  5. Wow. Just wow.

    I am reminded of the confirmation bias when it comes to The China Study, a well-known cognitive bias which means that people only see what they want to see, ignoring any and all evidence to the contrary. So when a longtime veg*n comes out with an exhaustive study “proving” food from animal sources to be unhealthy once and for all, it’s definitely time to go back over his data with a skeptical eye.

    A big kudos to you, Denise, for putting this together. Truly a page to keep as a reference for a long time to come.

    1. so similarly, when a meat-eater comes out with a “repudiation” of a study that “proves” food from animal sources to be unhealthy once and for all, is it time to go over his/her/their data with a skeptical eye?

      I think your comment exposes your bias.

      also, I think both of these studies miss the point.

      1. Meat eating is not an ideology, it´s just a baseline human activity. Veganism, on the other hand, is.

        Also, the raw facts on display here are just devastating, regardless of what one´s dietary inclination is.

        1. I get sick just reading some comments. Bushrat got it right. When all agree, well.. thats impossible, U all have missed a valid point CONTAMINATION. Yes, it will raise your immune responses, but there is such a thing as viral overload – and we are there. I am so busy my website has not updated since 2008 , unlike the rest of the cutting edge world …

          I spend time washing everything , and if I kept animals I would Neem ’em

          Alex @ amoderate life tells it plainly , not one longevity culture were vegan – but missed my point of Contamination – they were in isolated areas , no huge cash transactions – no dirty money, their animals were clean , their soil was clean … and they did not have synthetic Creatine or Carnitine or Acetyl Cystein and dont mix their food with poison (alcohol, to name just 1)

        2. Obviously coming from someone who eats meat. Of course you’d only see it your way. Veganism is not an ideology. Why is it that people who eat meat and vegans can’t just accept each other and not criticize?

          1. Melissa…you’ve confused the question. Asking the greater philosophical question of why people don’t accept everyone’s lifestyle without comment has nothing to do with your conclusive statement that “veganism” is not an ideology. You provided no support for your claim and a very small amount of effort would tell you that being a “vegan” comes with a host of ideological prerequisites and rules.

          2. Almost all attacks come from vegans and vegetarians. When I post that I really like foie gras you,d think from the vegan reaction I eat human babies on a skewer . You won’t find any complaints from meat eaters when a vegan eats a toadstool.

      2. “so similarly, when a meat-eater comes out with a “repudiation” of a study that “proves” food from animal sources to be unhealthy once and for all, is it time to go over his/her/their data with a skeptical eye?”

        The data isn’t the issue here – it’s the interpretation. Campbell clearly took some serious leaps in the conclusions he made from the data, which is thankfully laid bare here.

        But yes, if a monumental study a la The China Study came out showing vast nutritional benefits from meat compared with vegetables, I would certainly hope the skeptics would come after it from every angle, especially if it came from someone like Dr. Cordain, who has an established history of being pro-meat.

        That’s how science progresses, Monica. Not by deleting, distorting, and generalizing, hoping the public will swallow it without question, but by making bold conjectures that you test rigorously and let others try to falsify. That’s why we no longer believe that the Earth is the center of the universe, rather that the sun is the center of the solar system.

        “I think your comment exposes your bias.”

        Yup. I am just full of biases. (I’m only human after all.) However I am one of the few people who will own up to them being biases and not facts. Half of what everyone knows is wrong. The hard part is trying to figure out what half that is.

        1. Yes, everyone makes their assertions based on bias. For one to say they are completely neutral and have zero bias is a lie.

      3. Hey monica; apparently your reading comprehension is not very high (an effect of the all vegan diet??) BUT Denise DOES say she LIKES lots of veggies !! So, that kinda shoots you in the posterior.

    2. Badly done. Did you know that the first studies on car safety were done by the US Air Force? They wanted to know why so many pilots were dying. Turns out they were mostly dying in cars. People like Denise would have poo-pooed this.

      1. AN you have now proven that you are a complete idiot and moron making a giant leap into nothing. It would depend on the parameters of the AF study and if they were separating Auto Deaths from Aircraft Deaths and researching the various related factors. Your statement is pure idiocy.

        1. Is anyone on here capable of holding a rational debate without resorting to abuse in the misguided hope that a barrage of name calling somehow adds weight to the points they want to make. This is probably the worse behaved forum I have come across especially on a such a gentile topic as health and wellbeing

    3. Darrin, Campbell was not a vegetarian until after the study and not a vegan until a long time after the study. I don’t think your observation about the confirmation bias is applicable here.

    4. With all due respect, you were never a vegan. Veganism is NOT about diet. It is a commitment to living a compassionate lifestyle, respecting all sentient Beings and choosing not to exploit them in any way, shape or form. You may have followed a plant based diet, but vegan- NO! There is no such thing as an ex-vegan. That would be the same as saying “Well I used to think it was wrong to kick puppies, but now, what they heck, kicking puppies is just fine as long as I enjoy it.”

      1. I think the expression veganism as an idealogy was used.

        You are wrong when you say “there is no such thing as an ex-vegan”. Can a person not change ones mind? Or one’s philosophy? Many great artistic and scientific advances occurred through such a shift or change in an individuals philosophy – of suddenly seeing something another way, from a different point of view.

        So, if it is not possible to be an ex-vegan, does that mean that I can never become an vegan? That I cannot one day, or over time, adopt your philosophy?

        Are you saying that people cannot change (or leave/join religions for example?)

      2. Hey please chill a bit Tumeria. I think I’ve become a vegan over the last couple of months, consumming only plant based nutrition – that seems to fit the definitions I’ve seen of vegan. I like animals, love my three cats, they seem to like their human too. I don’t much care for house flys though. Living in an older log cabin in Montana, I seem to have plenty of house flies. And I swat them daily – otherwise my cats and I wouldn’t like our existence so much. I think I’m still a vegan.

        And this overall blog post is very interesting and seems worth serious consideration.

  6. Great post! You explain things precisely and concisely.

    A couple of typos:

    “In these high-risk areas for liver cancer, total animal food intake has a correlation with liver cancer of… dun dun dun… +1.”

    Should be 0.

    “so for the sake of being able to entertain the possibility that #2 and #3 are valid”

    Should be #1 and #2.

  7. Hi Denise, as a biologist, I commend you for your detailed research and fact finding in this premiere article debunking a very dangerous compilation of hand picked misinformation. As a reformed raw vegan who now follows a real foods lifestyle according to the Weston Price tradition, I can tell you unequivocably that eating animal products and preparing foods in a traditional manner has indeed increased my health. Weston Price and other traditional foods enthusiasts were discussing these issues in the 1930’s and purporting a healthy balance of all foods and a removal of processed foods, but to no avail.

    It is of interest as well to note that Jon Robbins of vegan fame also wrote a book called healthy at 100 where he revisits all the long lived cultures in the world to determine what each one ate and he NEVER found a vegan culture. All ate some form of dairy/meat, all ate fermented foods and all had limited processed sugars or grain products. All prepared their food in traditional ways and when their youth began eating the SAD diet, they all developed the same degenerative diseases seen accross the country, but they developed them much more quickly. Robbins does NOT promote this book because it obviously goes against his vegan agenda.

    I will be sharing your study on my Thoughts on Friday Link love post and getting it out there to the Real Food community! Thanks so much for your hard work!

    1. Alex: I can’t thank you enough for mentioning the work of Weston A. Price!!!! After Googling his name and reading about his work, I am now ordering the Nourishing Traditions Cookbook by Sally Fallon. Please let me know if there is more information supporting this lifestyle. THANK YOU!

    2. Alex….key words “SOME form of meat or dairy” the China Study promotes 10% or less of animal protein which would account in my opinion as “some”. I wasn’t aware that there was a “vegan agenda” and he probably doesn’t promote it because he believes in animal rights. People can and do live healthy as vegans but just because you are vegan does not make you healthy….potato chips and beer is vegan…but not so healthy. I do agree that processed foods should be kept to a minimum and the body does need raw fruits ad vegetables but raw meat??? I think Denise is a little off on this one.

      1. For the record, the only raw meat I eat is fish (sushi/sashimi). We have Vegsource to thank for the “raw meat advocate” title.

      2. Lily, part of the few (if only??) who dares tread on the steps of St. Denise!

        I don’t see this as “first class” nor worthy of publication in the New England Journal. Healthy people for years have known moderation. I love The China Study because it challenges Americans to change their diet. The US spends more than any other society on Healthcare, yet we have some of the most unhealthy people. Why?

        You make a fantastic point that all of his research is based on a “10% or less” animal protein consumption plan.

        I agree, Denise is a little off on her “un-biased” review. Nothing wrong with telling people to eat more healthy.

          1. I like the enthusiasm you state with your exclamation marks. Don’t change because of the negative view of someone with anger issues :o)

          2. dl, you really oughta try and stop the punctuation…people might think you’re incapable of a confrontation without tossin them the bird, when their perspectives differ from yours–or your heroes. hopefully, we all contain passion about our existences, but the excess of hubris and anger, nee arrogance, can easily
            consume our prospects for sensitivity and reason….tools without which we are unable to do more than dribble and sputter about, such as you seem to immerse yourself in the processes of. You are passionate. Good, Why not get busy with the objective education you are in need of? Or you could remain an ignorant cheerleader for anyone whom your whims attract you to. And even if you do, still watch the exclamation marks…it has been said that the next syndrome is writing in
            all caps…and then…the possibilities of either utter madness, or a life in politics…perhaps both.

        1. Mingers blog reads more like a science paper than many science papers. Unlike Campbell Minger follows all the rules of logic.
          And your comment, “love The China Study because it challenges Americans to change their diet.” is laugh out loud dumb.

      3. Actually there is a girl on Youtube …come to think of it there are two people I know of on Youtube who were previous vegans and had to include meat in their diet because of deficiencies. The girl had a B12 deficiency that could NOT be helped with B12 shots or taking supplements. She decided to eat fish and is healthy now. Her symptoms IIRC were pretty severe.

        I probably have her video in my favorites so I’ll look for it. I’m sure some people already know of her. She got a lot of shit for going back to meat, especially from raw food vegans.

      4. Exactly. Key word here, “some.” I eat a mostly whole, plant-based diet, but I still eat “some” animal products, but less than 10%. I will never be 100% vegan. After adopting this diet, I got down to the size I was in high school. I love my food, and I imagine maintaining my diet and preventing disease will be effortless because of plant-foods. I’m very thankful!

  8. Great work! It’s really nice to see that critical thinking is far more important than just having a great academic pedigree.

  9. Although not explicit, there seemed to be an inference that cholesterol could be a cause of some diseases, when there was positive correlation. Since the body produces cholesterol, it is very possible that the disease (especially involving the liver) modifies cholesterol levels.

    Great work!

  10. This is truly a monumental work, Denise.

    It vividly illustrates the danger of “science with an agenda”, as practiced by Campbell and others of his ilk.

    Thank you.

  11. LOVE this summary! I’ve long passed out Chris Masterjohn’s critique and subsequent dialog with Campbell as an online resource for those wondering about any holes in The China Study. But this summary, along with your prior posts over the past month, are the most thorough I’ve ever seen. You can bet I’ll be passing this along to others from now on! KUDOS to you and your hard work.

    And THANK YOU so much for doing this research for yourself. I know I certainly wouldn’t have done it, although I’m glad to see it done!

    Oh, and I second Stephan’s desire to see you put your skills to work analyzing the wheat connection. I’m VERY curious about that, mostly because I’ve been following Stephan’s own analysis of whatever relevant studies are out there.

  12. Great work, thank you for providing your research.

    I am somewhat depressed after your skillful demonstration of how other variables like parasite infections and other unknown variables can affect the data. This leads me to believe nutrition science will forever be based on beliefs rather than reasoned science, leaving opportunities for egotistic scientists to lead themselves and the rest of us down paths of good intention but harmful destination.

    1. Actually, her demonstration proves how important a thorough understanding of statistics is for any scientific venture. There is a great deal of bad science in all areas that boils down to the researchers basic statistical illiteracy.

  13. I assume your correlation coefficients R^2 are in the range of [-100,100] instead of the typical [-1.0,1.0]?

    Very interesting to see the tight correlations between infectious vectors and cancers. There’s evidence for similar correlations between bacterial infection of the arterial wall and heart disease.

    Also the anti-dairy protein angle is interesting as well. From what I recall, the Lyon heart trial also had some evidence for dairy intake as being a major difference between the trial and control groups, with the trial group ingesting about half the dairy products and having lower incidence of heart disease.

    1. Robert, her correlation coefficients (r) range from -100 to +100 but her r-squared values range from 0 to 100. You can derived them simply by squaring the r values she reported. Squared numbers can’t be negative. :)


  14. Denise:

    I’m so glad you contacted me and I hope my post and efforts to get the word out does your marvelous, high quality, honest and integrated work justice. By the look of comments you’re getting some ver well deserved recognition.

    Nothing short of your collection being the go-to critique of The China Study is acceptable. Right now I’m using Google to source other likely interested parties to make them aware of your work and I challenge and encourage others to do likewise.

    1. I have looked at your website and found you to do a great injustice to good health and twist the truth to your own beliefs!!!!
      Remember there are more people who look into theories of long time study and the long term benefit,s as to those who have little knowledge and pick it apart for their own agenda!!!

  15. Congratulations on a wonderful bit of analysis. First-rate. Extraordinary. Add superlative of choice. K

  16. That was a really good read. As a non-academic/statistician, you clearly described the data in a way that everyone can understand. Thanks, Julie

  17. Simply superb.

    This really belongs in a peer-reviewed journal. This piece is far better and certainly more important than the average dross I read in medical journals.

    Like Stephan, I have been trying to put the hurt on wheat as one of the three “neolithic agents of disease” that are responsible for the diseases of civilization.

    To find that the actual data on which the China Study was based has a stronger relative risk associated with wheat than almost any other food variable is simlutaneously shocking and gratifying.

    I second Dr. Guyenet in asking you to dig deeper into the wheat issue.

    Nice work.

  18. Fantastic work! Mad respect for someone to dedicate the time to robust scientific rigor. Pity Powell couldn’t do the same himself!

  19. Wow, that was a lot of work just for me to READ it! Most impressive. It’s amazing what intelligence, objectivity, and hard work can accomplish. I would REALLY love to see you eventually tackle other similar projects. It’s so wonderful and so sadly rare to find someone who can root out basic unvarnished truths from piles of numbers. What I want is to understand what is healthy, but that has been amazingly hard info to find! You obviously have a wonderful natural talent for pushing aside the bull and getting to the meat of the matter (excuse the pun).

  20. Outstanding, and one of the few examples to be found (including amongst “real” scientists like, ahem, T. Colin Campbell) of the proper use of classical statistics. Nice job not extrapolating correlations beyond what they are, which are numbers derived from data, as opposed to hypothesis tests.

  21. Really solid, and a great reminder at just how twisted, knotted, confusing, and convoluted epidemiological research can be – hence why I never cite epidemiological study as evidence of any pre-asserted hypothesis.

  22. “Apart from his cherry-picked references for other studies (some of which don’t back up the claims he cites them for)”

    I’ve long believed this of many authors who promote a vegan diet.

    I followed a vegan diet for about 5 years. While all my numbers were great, I didn’t feel well. When I added animal products back into my diet, I felt much better and the numbers all improved.

  23. Great post, I found it through the blog, which I follow regularly.

    I’ll be checking your blog from now on also, even though my diet is pretty different from yours (see my blog for more info).

    – JLL

  24. I can’t thank you enough for this!! I agree with Dr. Harris’s review that you approached the data in a tone as close to neutral as possible, which I am especially thankful for (b/c it shows how careful of a thinker you are and that you are not pushing an agenda). You tore apart everything that deserved tearing apart, and you left us with some real gems hidden in the data that Campbell buried. Thanks to Richard for pointing so many of us toward this, too. =)

  25. Amazing work. Thank you so much. I shudder to think that much of the 2010 USDA guidelines are based on similarly derived association data. This is why I believe the safest way to eat is as close as we can muster to how our ancestors ate, using as much scientific knowledge as we can glean from controlled prospective trials to figure out which Neolithic foods are also safe (and which paleo foods are best left out too).

    I’m also intrigued by the possibilities of real health policy implications that could literally help hundreds of millions of people in China. Implementing hepatitis B and parasite infection control throughout the countryside, for example.

  26. Very nice, rigorous critique of Campbell’s methodology!
    Simply, the vegan crowd’s premise that humans supposedly evolved eating only plants is absurd to anyone with the slightest knowledge of evolutionary biology or paleontology. Anyone promoting such as agenda, even with a string of credentials after their name, is pretty much doomed before they begin :-).

    BTW, some of us are currently having a discussion on Campbell’s (negative, of course) review of the “New Atkins Diet” book, if anyone is interested. I enjoy it, not because any great scientific revelations are there, but several vegans are active and I get some sort of perverse pleasure in taking aim at. Sorry, it’s a personality defect I’ve got to get over someday… not today, however.

  27. really excellent. the china study has been hanging around in the back of my mind while my reading and eating have carried me in other directions entirely. i feel reassured by your logic and analysis. thank you.

  28. Thank you so much for all of your hard work and dedication to finding the truth. I found this critique through Robb Wolf’s website and couldn’t be more pleased with it. I’ve had vegans/vegetarians throwing The China Study at me as if it were gospel for far too long. Even The Protein Debate between Campbell and Cordain seems to have no effect on the illusions. This is something that always scares me in the realm of science and health, when a person’s own opinions clouds their judgment and causes them to form a theory and only ask the questions that will give them the answers they seek. Bravo to you for such a well crafted critique.

  29. awesome work denise, the analysis and time spent by you in this is awesome, especially eye opening is the role of wheat in this. i wonder if you could do one article on wheat itself and perhaps homogenised/pasteurised/UHT milk as well. :)

  30. you should publish this, or at the very least, you should post a version of this to as a book review…

  31. HI Denise,

    Thank you for putting this together, I know how much time and work went into it. I will definitely link to this from my blog and also refer my students to it. This is by far the most thorough critique of Campbell’s work that I have seen so far. Kudos!

    Like Stephan, I would like to see the data on wheat parsed a bit more. I hope you can get around to that.


  32. What everyone else said.

    Excellent work.

    You have a very bright future in whatever field you choose to pursue.

  33. Thank you, thank you, thank you. I receive frequent emails and blog comments from vegetarians who believe the China Study was handed down by The Almighty. Now I know where to send them.

    I’ve read other articles on Campbell’s selection bias, but this one is the most comprehensive by far.

  34. To all who have responded, e-mailed, or simply read in silence so far: a sincere and enormous “thank you.” I wasn’t expecting this analysis to generate so much interest, especially given its daunting length, and I’m thrilled so many people have found the information useful.

    A number of you expressed interest in the wheat/heart disease correlation. My next post will be delving into this issue (based on China Study data) in great depth, although the post might not be up for a week or so. In the meantime, a blogger named Brad Marshall wrote a fantastic post on this exact subject in 2005 — so mosey on over there if you haven’t already, and take a gander:

    I’ll be testing whether the wheat/heart disease connection holds true when adjusting for other factors (like latitude). Campbell actually published a paper mentioning this correlation in 1998, so he was definitely aware of it, although obviously chose not to include it “The China Study.”

    To those of you who’ve asked questions, I’ll be getting back to you individually (probably not very promptly, though — sorry in advance!).

    Thanks again, everyone!

    1. Thanks for doing what the authors should have done with this data. I hope you tease out more information from the study.

      I would be waiting for your Wheat results. I have also gone nearly wheat free, after reading so much about it. It was interesting to note that it does cause such wide ranging damage and not just to gluten sensitive people. Now I will try to be more strict.

      Thanks for pointing to the excellent article by Brad Marshall. It actually contains more gems than just the wheat. It shows that Rice is more beneficial than potatoes (Tubers). This to me totally doesn’t make sense. I have been reading about the Paleolithic diet, and it makes sense that Tubers would have been in our diet since ages, but to think that Rice which is a neolithic food, is more beneficial than potatoes, just doesn’t compute for me.

      I hope that you will also work your magic on the rice and tuber data from the study. It will be interesting if the data shows a negative (or at least insignificant) correlation for rice with the various diseases.

      It will allow me to eat rice more guilt free. I will help me relish biryani guilt free ;-).

      Thanks again, and hope that you get into nutrition field.

    2. Denise, if you haven’t already noted it, you might keep an eye out for potential confounders (high omega-6) vegetable oil, and sugar, when looking at the wheat data.

      1. In line with ed’s comment you should also look at trying to break down cholesterol into HDL, LDL and trigs and see what affect this has on the data. The current theory that I believe holds the most water is that the ratio of HDL to LDL is the best indicator of coronary heart disease and cardiovascular disease.
        Further, the type of LDL matters (i.e. small and dense or big and fluffy).

        I’m not sure whether this distinction is made in the data you have, but if it is then it would be interesting to see how closely the different types of cholesterol correlate with various heart problems.

  35. This work is amazing. Nobels have been awarded for much less. To my thinking, you have persuasively established wheat as the #1 threat to modern human health. (“Staff of life” indeed!)

    That Campbell has finally been put to rest pales beside this accomplishment.

    (Though I do have to wonder about what kind of man can discover the slow yet extraordinary danger wheat posed to billions of his fellow man — and then consciously attempt to hide that fact from them!

    The mind reels.

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  37. Anon:

    Let’s not fall into the same trap Campbell did and which Denise worked so hard to show.

    What she did was to demonstrate that other associations were much stronger than animal products and pointed out that Campbell failed to mention those.

    At best, she falsified Campbell’s conclusions as laid out in his book. Let me be clear: she falsified his conclusions, not the hypothesis that animal products are bad, because you simply can’t do that either way with epidemiology.

    On the other hand, Denise has created a ripe field for new hypotheses to be tested in rigeur.

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  39. Oh, woman!
    You are amazing! You really took the bullet for those of us who have recently thought to commit to the same thing…with so much more grace and accuracy than I ever could have. Well done! Thanks for the number crunching, research, analysys and balanced presentation. Thanks for avoiding an alarmist perspective (present too frequently on BOTH sides of the fence when it comes to the China Study.) and making the fruits of your labors public information. Thank you, thank you, sincerely…1,000,000 thanks!

  40. Unbelievable amount and quality of work. I knew Collin T. was full of it when I learned he was part of that group for responsible medicine that somehow omit to mention they are all vegetarians on a mission. A case of diluted personal integrity you could call it. I read the earlier critic but yours is by far the most comprehensive and comprehensible.
    I am going to translate as much of it as I can to Hebrew (the language of my blog) and if the review I wrote of The Vegetarian Myth is any indication we are going to have a lively debate here.
    Looking forward to the piece on gluten. It should be noted however that recent research shows that not all wheat varieties are equal in terms of damage they can inflict, with most recent verities been more potent.

  41. Wonderful analysis! I too were stuck by the associations between wheat and the many diseases listed. Kudos to you for the detailed analysis and concise writing.

  42. well done! the number crunching you did is a amazing (interesting hobby!!)..thanks for giving me a concise argument with “sciency” numbers that I can present to others!!

  43. Wow! This is a new subject for me, and I am speechless. What a great, great, analysis you did. I just added you to my blogroll. I don’t want to miss a single post you write from now on. I love your reasoning, all your hard work involved, and care you’ve taken in making this one great well researched article. Thank you.

  44. Good job doing plots. That’s really important to see data trends, as it really is true that a picture is a better summary than numbers. And as a long time teacher of statistics and researcher myself, I’m absolutely thrilled to see people analyzing data themselves. Seriously, it’s really wonderful to see that whatever I’ve taught in intro stats class that no one wanted to take gets used by some people. Your analysis is a good start, but like all nutrition data, this data is tough, and correlations aren’t enough to analyze it properly. If you continue in this vein, you may want to learn more statistics. Here are some issues you need to deal with:

    1) Outliers. In the plot of that disease that starts with s versus a cancer (colorectal?), you have most of the data clustered around zero prevalence of the S disease, with little evident trend and then you have one outlier from a place with high S disease, and then two points in the middle. That one outlier may be enough to give you the high correlation, and if you took it out, you might have insignificant correlation, and certainly if you took both that point and the 2 middle points out, you would.

    2) Confounding between meat and income. Places with highest grain intake are likely the poorest, and places with the highest meat intake are the wealthiest. See the study discussed here about grain/meat intake in China:
    Obviously income has enormous health impact that go beyond meat intake.

    3) Simpson’s paradox: When you have confounders that might make an enormous difference in the outcome, you have to stratify by them, which you did in some places, when you looked separately at cancer risk of people people with Hep B (if I remember correctly) and without. In some cases, once you stratify, you see that a correlation actually reverses. Here’s one example of that in some sex discrimination data:

    4) Ecological fallacy. Ecological data is a good place to start, but it’s the most crude type of data because obviously there are lots of reasons why, say, Mississippi and Colorado and Massachusetts are different, and a pattern seen across states (or in this case, Chinese provinces) might not hold for each individual within them. In fact, it might be the opposite. When you break down and look within each state, the data might look different. Here’s one example: blue states (Democratic majority states) are richer, but once you look within each state, richer people are more likely to vote Republican. At the same time, some states have stronger association between income and party affiliation than others.

    These are just a few issues that I saw off the top of my head. I don’t mean to be discouraging. Nutrition data is just really really hard. And obviously all these issues apply to the original published analysis that you are reanalyzing their data.

    I hope that you go on to improve the analysis beyond this, or find individual data to work with. Or ways to improve ecological data (which is hard to work with, and I am not so familiar with the methods people use with ecological data.) Some nutrition data that is publicly available is public release NHANES, the main US federal survey of nutrition. I think anyone can get that, and they are very thorough in documenting things like serving size (though obviously as soon as you have people measure their food, they are going to change their eating habits to some extent, and people also lie about which food they eat.)

    Good job with this analysis. I haven’t seen the original book, but if it really is as you say, it’s great to see challenges to claims resulting from substandard data analysis. Nutrition is really hard to study, though.

    1. Janet,

      I’m glad I checked my spam queue, because your fantastic post was snagged there. Thank you so much for sharing your thoughts on this — you bring up so many excellent points and obviously have a wealth of experience with stats!

      1) When writing this critique, I considered posting graphs adjusted for outliers (and played around with this while to see how the correlations were affected), but ultimately chose to just plot the data as recorded in the original monograph. My reasoning: The only correlations supporting Campbell’s claims were the uncorrected ones, and since I was analyzing his claims (not necessarily the validity of the correlations), I figured it’d be best to post the graphs reflecting that.

      In most cases, the outliers vanished naturally once I removed confounding variables. For instance — the outlier you pointed out, in the graph plotting schistosomiasis and total cholesterol, is the same county represented by the outlier in the graph immediately after it (total cholesterol and colorectal cancer). Once the data is adjusted for schistosomiasis infection, that county and its misleading placement disappears.

      EDIT: I just realized you were talking about schistosomiasis and colorectal cancer, not schistosomiasis and cholesterol. My bad! Without the farthest outlier, the correlation remains very high (+74). Without the farther three outliers, including the two in the middle you mentioned, the correlation also remains high (+55).

      2) Great point regarding meat and wealth. Thanks for the link — I’ll check it out. It’s unfortunate the China Study didn’t document income/financial variables, but it may be something that could be approximated indirectly (for instance: Wealthier areas may have less diseases related to poor living conditions, like pneumonia and tuberculosis, so we could divide regions based on indicators of substandard living and see what that does). This is something I’ll be looking into further. Thanks for bringing it up.

      3) Stratifying data did seem to portray the correlations in a new light. Very interesting link; thank you!

      4) Ecological fallacy — in my opinion, this is one of the biggest design limitations of the China Study. Despite the large number of people initially involved, all data was aggregated at the county level, resulting in only 65 data points — none of which preserved the intricacies of individual diet and disease rates; only the averages of a population. Since regions tended to be somewhat isolated and reliant on the same foods (usually what grew locally), this may be less of a problem with the China Project than with other studies of its kind, since regional diets tended to be homogeneous (according to the project’s research team).

      As you’re aware, this sort of study can never yield proof — only clues and hypotheses — so even the most rigorous analysis will have limitations. It could definitely be worthwhile to integrate the ecological data with individual/controlled studies to create something even more definitive.

      Thanks again for your thorough comments. Given your background on this subject, I’d be particularly interested if you see anything I can fine-tune in the analysis above (especially because my lack of credentials will, to some people, be reason enough to dismiss everything I’ve written). I want this to be as accurate as possible, even working within the study’s obvious limitations.


      1. Where did you study nutritional science? Have you been at it for 50 some years?? Wow….I haven’t seen your name or your credentials to match that of T.Colin Campbell…amazing but I guess you don’t need it on this blog because you have obviously convinced some of these readers and certainly not the majority thankfully, of your misleading data, But then I don’t believe that anyone here really knows science or has any real education that is pertnet to this subject!!!You may have a small following but Campbells book has sold millions and has reached those who do know what he is talking about!!!Some of you should go to” Lona Linda” and research what scientist all over the world have found!!They come together ever year for seminars to educate those on vegetarian/vegan diets!!That is something you can not argue with!!I’ll be taking your data to Sublime in Ft. Lauderdale on the 26th to share with Campbell and other educated experts, who have spent most of their lives promoting good health!!!

        1. Compare the digestive systems of herbivores, omnivores, and us…..which do our most resemble? Your agenda is showing, dlibby. She used Campbell’s own information, anyone with the insight, patience, and understanding of statistics could have done that…and she did. Study anatomy, and you’ll have your answers as to how we need to eat.

        2. Your comment is full of… well I can’t say on here. :) – Let’s just say your conditioning is obvious. Credentials mean NOTHING in relation to the validity of the scientific data. Stop trying to shoot the messenger and look at the actual science. That’s critical thinking 101.

          As far as “good health,” that’s subjective.

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  46. This is amazing, congratulations on what you’ve achieved here it’s seriously impressive. You are such an inspiration to me as a fledgling nerd of nutritional science (I just finished a 4 year degree). Maybe if I try really hard I can be as smart as you and blog as well as you do about these things one day *sigh….* Only problem is I can’t handle numbers so statistics is a disaster area for me lol :)

  47. This is absolutely brilliant!

    Like Stephan (above), I’d also love to hear more about the data surrounding wheat. I’ve suspected such correlations before, but I wasn’t aware they were embedded in Campbell’s data.

  48. Thanks for making your exaustive analysis available to the public for free. Since I used to live in China, I can put a lot of the dietary data into context. I didn’t notice any data about plant versus animal fat. Eastern city-dwelling Chinese use a lot of refined vegetable cooking oils, specifically soy and corn, to stirfry vegetables on high heat for a short period. Since Campbell is anti-fat, an examination of plant versus animal fat is not relevant to debunking his claims, but I would be interested in any data, if available.

  49. interesting responses on the 30 bananas a day forum, some are touting Campbell’s previous retort to his previous critics (Colpo and Masterjohn), which I can paraphrase as “they are misinterpreting uncorrected raw data”… what the hell does that mean? Seems to me you worked very hard to correctly interpret the raw data. And Campbell worked very hard to torture the raw data to conform to his own biases. I guess by corrected data, he means “only that data that confirms what I already know”

    That guy’s legacy, hopefully, will be as the text book example of how not to do science. If you are a young, or even experienced scientist, you should constantly be asking yourself, “what would TC Campbell do?” And then you should probably do the opposite!

    others are taking the “how could she, she is killing more animals…” Doesn’t matter to them one bit that Campbell’s conclusions appear to be very seriously in error.

    1. Hi Mr. Freddy,

      I’ve parted ways from 30BAD and won’t be posting there again, but you’re free to pass this along if folks there are confused.

      I’ve seen Campbell’s responses to previous critics and have been perplexed by the “misinterpreting uncorrected raw data” accusation. My best guess is that he’s referring to the “Death from all causes” or “Death from all cancers” variable, which several critics cite in their reviews in order to vindicate animal foods. Both of these variables can be misleading taken out of context: In the raw data, correlations between animal food consumption are inverse for death from all causes (meaning the meat eaters tend to live longer) and also inverse for death from all cancers (meaning the meat eaters tend to have lower rates of cancer, in totality). These are easy things to cite for anyone looking to discredit “The China Study.”

      But what the uncorrected data here overlooks are the many, many confounding variables at play. Do the meat eaters also live in areas with better health care and living conditions (leading to fewer instances of non-diet-related disease)? Do the meat eaters experience less “death from external causes,” another variable that contributes to all-cause mortality? Any number of entangled variables could sway the “Death from all causes” variable, rendering it fairly useless uncorrected.

      Similarly, the “Death from all cancers” variable can be misleading without looking at individual rates of specific cancers. Some are obviously related to lifestyle habits (like smoking and lung cancer), exposure to external hazards (like toxins in the workplace), infections (like hepatitis B or schistosomiasis)–so on and so forth. If, for instance, plant-eaters tended to be heavier smokers than the meat-eaters and exhibited much higher rates of lung cancer, then the “Death from all cancers” variable would lean in favor of meat consumption for reasons unrelated to diet.

      In these cases, I’d certainly agree with Campbell that using the uncorrected data is unwise and potentially misleading. That said, it appears Campbell himself relies on the raw data, since the correlations he cites are only valid before correcting for confounding variables.

      The analysis on this page avoids those traps by looking at individual cancers instead of cancer in the aggregate, dividing populations into high-risk and low-risk groups, and adjusting for variables known to influence disease rates.

      I hope that clarifies some things.


      1. Don’t be fooled people, Denise has misinterpreted raw data, just as many inexperienced “researchers” do. Denise is not qualified to read such data correctly.
        Please refer to the use and misuse on pp. 54-82 of the China Project monograph.

        The following is Dr Campbell’s rebuttal. The rest can be found

        ” China Project results are no exception to these limitations of single experiments. It was very large, unique and comprehensive but it was observational (i.e., not interventional), simply observing things as they were at a single point in time. It provided an exceptionally large number of hypothetical associations (shown as statistically assessed correlations) that may indicate but does not prove cause and effect relationships. These unanalyzed correlations are considered raw or crude. It is highly unusual to find such ‘raw’ data in a scientific report because, in part, untrained observers may misunderstand such raw data.

        For the monograph, we were somewhat uncertain whether to publish such raw data but decided to do so for two principle reasons. First, we wanted to make these data available to other researchers, while hoping that data misuse would not be a significant problem. Second, because these data were collected in rural China at a time when data reliability might have been questioned, we chose to be as transparent as possible. We discussed data use and misuse on pp. 54-82 of the China Project monograph that curiously was overlooked by Masterjohn and Jay’Y’.

        1. Hey John, it’s probably sufficient to post this on one entry instead of three of them.

          I agree wholeheartedly with what Campbell says about the limitations of the China Project data (and for the record, I read the warning chapter in the China Study monograph before diving into the data). If you read my critique, you’ll see that I don’t slap down the raw correlations for this very reason: They’re misleading and can easily imply trends that aren’t actually there. This is why I focus on untangling variables and adjusting for confounding factors, thus rendering the data no longer ‘raw’.

          Campbell’s claims, on the other hand, only appear to be valid before those adjustments are made. In every instance I analyzed, his claims matched with the raw correlations but not with the corrected ones.

          If you feel you or someone you know would be better qualified to handle the statistics, by all means, track down a copy of “Diet, Life-style and Mortality in China” and analyze it for yourself. I’ve tried to be very transparent with my process here so that others may replicate my methods or identify any logical errors, should there be any. If you have suggestions for how I can improve upon this analysis, I’d be glad to hear them. Apart from that, RE: your quote from Campbell — you’re preachin’ to the choir. :)


      2. And who do you think you’re trying to fool, “John?”

        That poor excuse for a “rebuttal” (filled with ad hominem and hand waving — pretty much all Campbell ever does) has been around since 2006 and was in response to Masterjohn and Colpo. It does not in the least address the brunt of Denise’s critique.

        “Denise is not qualified to read such data correctly.”

        You fools crack me up.

      3. Also saw your goodbye post on the 30bad site, also well done. You have a fun to read writing style.

        I don’t think I’ll ever be posting there, haha… I’d be an even bigger and more square-er peg than you in that environment. I was just over there having a look around cuz I was curious about how the vegan true believers would react to your astounding analysis.

        I expected to see some head in the sand reactions, but wow, I was suprised at what I found… some interesting characters over there…

  50. Hello Denise,

    I found this via Dr. Harris as well. One word. Masterful.
    Also urge you to explore the wheat correlation.


  51. Two things that can’t be vilified too much…wheat and The China Study.

    Great job Denise.

    “Campbell actually raises a number of points I wholeheartedly agree with—particularly in the “Why Haven’t You Heard This?” section of his book, where he exposes the reality behind Big Pharma and the science industry at large.”

    The best way to sell a lie? Shove it in with some truths.

  52. Your analysis is completely OVER-SIMPLIFIED. Every good epidemiologist/statistician will tell you that a correlation does NOT equal an association. By running a series of correlations, you’ve merely pointed out linear, non-directional, and unadjusted relationships between two factors. I suggest you pick up a basic biostatistics book, download a free copy of “R” (an open-source statistical software program), and 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.

    1. Hi Rayna,

      Given that this is the first ‘critical’ comment posted so far, you’ll probably get flamed pretty soon — but I’m very grateful for your suggestions, and particularly for your offer to help me get this information publicized even further once it passes your standards. For that, a giant thanks!

      For the sake of making this critique more accessible to readers, I only included the simplest/linear graphs to illustrate some relationships between mortality rates and confounding variables. However, while analyzing the data I did run multiple variable regression analysis on (nearly) all the mortality statistics you see here. I found the results were similar to what I achieved by stratifying the data/eliminating variables by hand (ie, combing through the data in the monograph and using only counties without a certain risk factor — maybe a more crude method than is typically used by statisticians, but again, it produced similar results to running multiple regressions, and I was more interested in seeing whether generally positive or negative associations were in place rather than determining exact numbers). In fact, when running MRA the protective trends for animal foods were even more accentuated in most cases (I recall a -70 between animal protein and cardiovascular diseases).

      For what it’s worth, Campbell’s claims all align with the raw correlations but not with adjusted ones, as far as I can tell, which makes me very curious about his own methods for analyzing the data.

      I didn’t venture beyond linear regressions because I didn’t visually identify curvature in my scatterplots, but if you think this was an error on my part, please let me know. I realize there are probably more sophisticated methods that you PhD-ed epidemiologists use, and I would be much indebted if you let me in on your secrets. :)

      At any rate, I want to make it clear that I’m not trying to draw conclusive statements from the China Study data or prove anything beyond my original point: that Campbell’s analysis of the data overlooks important variables influencing disease rates. That’s the intent of this critique. Nothing more. I don’t see how, in any conceivable way, he could reach the conclusions he did after taking obvious risk factors into account. Campbell is the one insisting this mammoth collection of ecological data shows that meat-eaters are less healthy than plant-eaters and I am simply testing whether this is supported by the data.

      Again, thanks for your generous offer to help. When you get a chance, please shoot me an email at and we can discuss this more. I’m going to dedicate all of next weekend (translation: I will probably work for 48 hours straight and not sleep) to recording the results from multiple regressions and any other analytical methods you recommend. As it stands, I’m confident in the critique on this page, but I’m certainly willing to perform additional analyses if that would make this more readily accepted in the medical field.



    2. Rayna, I think you miss the point. The only conclusion Denise draws is that Campbells presentation of correlations from the data is misleading and inaccurate at best. You are over-interpresting Denise’s post. Defensive much?

      Also, here is something I don’t know. How do you perform multiple regression on 300 variables with 65 data points? And if that’s really the right way to do it, why didn’t Campbell do it that way? Would this only further damn his analysis?

    3. Rayna is right: This analysis, while impressive and very well done, is indeed over-simplified.

      However, Ed is also right: Denise is not attempting to draw any conclusions as such; rather, she is pointing out the inaccuracies of Campbell’s interpretation of the data.

      The irresponsibility lies with the paleo quacks who are now declaring that this “proves” that wheat is indeed the cause of disease. Maybe, maybe not; at best this analysis generates a possible hypothesis that there is a possible link between wheat consumption and disease. Nothing more.

      1. can someone cite for me the study/analysis that shows how rheumatoid arthritis follows wheat consumption in populations as wheat expanded outward from the fertile crescent? i have seen it referred to but have not the actual analysis. i have a family member that i am trying to make aware of this nasty.

        (yes DLM, Denise is not the only bright light to find something sinister about our opioid-stimulating wheat consumption)…

    1. for the record, i did NOT say that the china study *isn’t* bunk – i simply pointed out the errors in denise’s analysis and conclusions. and my offer still stands – i am happy to assist denise with a more appropriate analysis. and if the results still show that dr. campbell’s claims are untrue, then i am happy to share this publicly. but i think if one is going to undertake a scientific stab at something, one should do so responsibly. that’s all i’m saying.

      1. But your critique of Denise applies even more to Campbell himself. Are you not grasping the point that “Campbell’s claims, on the other hand, only appear to be valid before those adjustments are made. In every instance I analyzed, his claims matched with the raw correlations but not with the corrected ones.”?

  53. i don’t think my being vegan invalidates my intellectual capacity for critiquing denise’s analysis. i’m an epidemiologist. i critique my OWN studies with far greater detail than i’ve done here, trust me.

    1. rayna wrote this on another forum here

      “2) Much of her conclusions are drawn from purely ecologic data –
      that is, data that is in aggregate – such as comparing the average
      fat consumption in Japan and the U.S. and the corresponding
      breast cancer rates. Sure, it can be informative, but it doesn’t tell us
      anything about some of the other factors that might be related to
      fat consumption and breast cancer. Ecologic studies are considered
      to be at the bottom of the “epidemiologic study totem pole.” And
      we can NOT draw individual-level conclusions from them, i.e. we
      cannot say that an individual who consumes less fat will, on
      average, be protected from breast cancer (even if that’s true, we
      cannot draw this conclusion from an ecologic study – there’s even a
      term for it: “ecologic fallacy”).”

      (so she says the conclusions are faulty b/c they’re drawn from purely ecological data……hmm…. that’s what the China Study IS, ecological data….so apparently this book was bunk from the start?? looks like campbell is guilty of the ecological fallacy then)

      “OK, my disclaimer: I’m an epidemiologist, and yes, scientists are
      NOT objective (I’ll say it: I’m an ardent veggie with a happy veggie
      family). Hell, science is not objective. I mean, you could be given a
      blob of numbers that mean nothing. It takes some context,
      interpretation, and data processing to make anything meaningful
      out of those numbers. Yes, scientists can be biased, and so can the
      studies they conduct, and the analysis of those studies. But good
      scientists do the best they can, are open about their methods, and
      fair when discussing their results. I applaud Dr. Campbell for
      making his raw data available – very few scientists do this. I will be
      totally honest and say I have not read “The China Study” (I guess I
      feel it’d just be preaching to the choir, but I think I will read it
      now…). “

  54. Dear vegans,

    Please actually rebut these criticisms instead of just appealing to the authority of your credentials.

    Thank you

    1. You have a cat as an avatar and you’re not a vegan? An animal lover that eats animals, now there’s a contradiction if I ever saw one.

      1. I love animals, but I am not in bondage to a newage hippy ideology that prevents me from being at peace with the natural world as it is, carnivores, omnivores, herbivores and all.

      2. gawd i am so tired of this inane veg-head reply – i read “the secret life of plants” waaaay back –

        veg-heads: that salad you are munching is screaming all the way down–

        that i enjoy my ancestral evolutionary diet that includes meat hardly means i am a heartless animal hater – duhhhh…

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