First of all: I recently had the pleasure of doing an interview at “Let Them Eat Meat” about my experience with veganism, thoughts on its healthfulness, my overwhelming adoration for the American Dietetic Association, and—because I’m forever branded as That China Study Girl—some final thoughts on a certain book we all know and love.

In case you haven’t heard, Let Them Eat Meat is the brainchild of Rhys Southan, a non-disgruntled ex-vegan who applies his stellar writing skills to the subject of veganism. If you haven’t already stumbled across this site, please stumble there now—you’ll find some fantastic interviews with former (and current) vegans, discussions of related health and moral topics, and a critical look at the arguments for avoiding animal products—including a recent deconstruction of vegan ethical tenets. Even if you don’t have personal experience with an all-plant diet, you might find the material there fascinating from a psychological perspective. So go peruse.

In other news, it looks like bad science—or at least bad reporting—is still alive and well. Case in point:

Fellas: is saturated fat lowering your sperm count? If you believe the flurry of recent articles, it sure sounds like men who eat more saturated fat have fewer—and less virile—swimmers. A Harvard study presented at a reproductive conference last week spawned some gems like these:

High saturated fat intake ‘damages’ sperm

Diets High in Saturated Fats Can Lower Sperm Count, Researchers Say

Eating saturated fat can damage your sperm

Are the meat and dairy industries actually massive government-funded schemes for population control? Is humankind’s history of meat consumption the reason we’re verging on extinction?

Interestingly, when you actually read the articles above, you’ll see that saturated fat wasn’t the only type of fat the researchers linked with sperm problems. From here:

According to the study, an increased intake of saturated fats and monounsaturated fats—which are commonly found in meats, butter, and dairy products—may result in a lower sperm concentration.

(Isn’t it cute how they don’t list the common sources of monounsaturated fat? No one wants to diss olive oil. That’s what the Mediterraneans eat!)

And from here:

The researchers found that men with the highest intake of saturated fat had 41% fewer sperm than men who ate the lowest amount of saturated fat. And men with the highest intake of monounsaturated fat had 46% fewer sperm compared with men with the lowest intake of monounsaturated fat.

I’d give the ol’ “correlation isn’t causation” reminder, but in this case, it might not even be necessary. It looks like the figures cited are the unadjusted ones, because according to this Medscape article (which has more details about the study than the others):

The association between fat intake and semen quality parameters was made with linear regression while adjusting for total energy intake, age, abstinence time, body mass index, smoking status, and intakes of caffeine and alcohol. The results showed that saturated fatty acid levels in sperm were inversely related to sperm concentration (r = −0.53); however, saturated fat intake was unrelated to sperm levels.

D’oh.

So basically, men with higher levels of saturated fat in their sperm tended to have poorer semen quality—but actual dietary intake of saturated fat wasn’t implicated after adjusting for confounders. At least that’s what I’ve pieced together from the available articles, since a quest for the original study yielded nada. Regardless, this is a prime example of the media skewing headlines to fit conventional nutrition wisdom and assuming an association between variables proves cause-and-effect.

And in case anyone’s wondering what’s going on with “The China Study” Suckypedia Wikipedia article that’s now moderated by a vegan editor: Along with pruning out all mention of my critique, gone also are the criticisms from Science Based Medicine’s Dr. Harriet Hall (here and here) as well as the fabulous critiques from Chris Masterjohn (here and here). The only one still up is a brief mention of Loren Cordain. And in case that’s not enough, the “Criticism” section has now been changed to “Reception and criticism,” so half of it is dedicated to praise.

Go figure.

And at the risk of sounding like The Girl Who Cried Wheat Entry, the wheat entry really is coming next! I promise. In the meantime, here’s a new study that shows we have microorganisms in our mouth that can actually degrade gluten. Might this play a role in how folks at risk for celiac respond to wheat? Seems possible.

Lastly, I’d like to thank everyone who’s contributed to the (oft-informative) discussions unfurling on previous entries. I haven’t had time to jump in myself, but I’m grateful to all of you who’ve taken the time to share your thoughts here and engage in what has generally been civil discourse. You people are awesome.

I just learned from a highly reliable source that I am not a “private blogger,” but rather, “very likely a large scale underground defamation campaign against Dr.Campbell.” As a result, all mention of my critique—AKA the Minger Scam—has been yanked from Wikipedia’s “The China Study” page by a vegan editor there. The rationale is as follows:

Just tell me, which “private fun blogger” is able, aside of her alleged full time work and study of “English literature”, to write 36 pages of scientific responses to a professor?!! And again and again??? Either “she” is some sort of very mighty – and very mad and crazy and hate filled – genius, which in itself would be something extremely rare and highly unlikely (really, why would a pretty young girl have so much reason for such a giant ordeal, fight, all that massive work, all that hate???) … Or “she” is in reality another underground [campaign].

Whoops—my bad! I forgot females aren’t supposed to think or write stuff; we’re here to take Home Ec and vacuum in stilettos and learn how to become Good Wives:

On behalf of Minger Scam, Inc., I apologize for any inconvenience we may have caused.

Now onto business.

I’ve got graphs, graphs, graphs galore, but they aren’t really relevant to the upcoming wheat post, so I’m plopping them here instead. In my first China Study critique, I looked at some mortality differences between the five counties that ate the most animal foods and the five counties that ate the least. Here, I’m doing something similar—except this time I’ll be comparing the counties with the super-highest and ultra-lowest heart disease rates and seeing what they do differently in terms of diet.

One of the incredible things about China is the vast difference in heart disease mortality between regions. One county, Fusui, has only 1.5 per 100,000 deaths attributable to heart disease—whereas another county, Dunhuang, has a whoppin’ 184. That’s even more than the US’s figure of 106.

In case graphs freak you out, here’s a summary of what’s below:

• The healthy-hearted regions almost universally had higher intakes of animal fat, animal protein, dietary cholesterol, and saturated fat than the heart-disease-prone regions.
• The healthier regions generally had lower intakes of fiber, light-colored vegetables, plant protein, vegetable oil, and—big surprise—wheat flour.
• Consumption of green vegetables didn’t differ significantly between the high and low heart disease regions. Neither did smoking rates, total cholesterol, or non-HDL cholesterol, although HDL cholesterol looks slightly higher in the regions with excellent heart health.

Does this “prove” anything about diet and heart disease? Nope—there’s the curse of epidemiology again. But we can make the observation that some regions in China exhibited astonishingly low rates of heart disease while eating more animal foods than the Chinese average. And the county with the absolute lowest consumption of animal foods, Longxian, had the second highest rate of heart disease mortality out of all the counties studied. (For the record, I used the China Study II data for this, all of which is available online.)

Key for the graphs:

Red bars, high heart disease rates—left to right:

1. VB = Dunhuang
2. TD = Longxian
3. WC = Tulufan
4. XA = Yongning
5. CC = Jiangxiang

Blue bars, low heart disease rates—left to right:

1. PD = Fusui
2. NC = Qiyang
3. PA = Cangwu
4. NB = Mayang
5. NA = Linwu

Green bar:

Average value for all counties studied in the China Study II.

The graphs should be pretty easy to understand without me yapping away, so without further ado, here ya go.

News:

1. Killin’ la vida China Study. The fabulous Jimmy Moore recently invited me to be on The Livin’ La Vida Low Carb Show, which—if you’re not yet aware—is a podcast-goldmine not only for low carbers, but for anyone interested in health. You can listen to my interview with him here. Despite recording at 8 AM, it was a blast—thanks, Jimmy!

2. “The China Study” dies another death. Up until recently, my biggest beef with Campbell’s casein research was his attempt to extrapolate casein’s effects to all forms of animal protein, despite demonstrating that plant proteins can behave the same way. But now a bigger, stronger, beefier beef has hoofed its way into the picture. Sherlock Holmes Chris Masterjohn did some sleuthing and made some very interesting discoveries about what the casein research really showed. If you haven’t read this article yet, please do so. Now.

3. Campbell speaketh. If you’re going through Campbell withdrawal, fear not: He just published a new article over on The Huffington Post called “Low Fat Diets are Grossly Misrepresented.” You can probably guess what it’s about from the title.

I actually agree with one of the article’s implications, which is that not all “low fat” diets are actually low fat, especially in the case of clinical studies—kind of like we saw with that recent low-carb flapdoodle. A diet with 30% fat isn’t representative of Ornish any more than a diet with 30% carbohydrates is representative of Atkins, but the “low fat” label is often used by researchers to misleadingly describe a moderate fat intake.

Although my last blog post criticized the inaccurate titling of a not-very-low-carb study, the same could be said of many so-called low-fat studies. No matter what side of the diet fence you’re on, from a scientific standpoint, it’s important to be equally critical of all research and not automatically assume studies are well-designed just because their results sound good.

4. Ned Kock does heart disease. A couple weeks ago, Ned did some number-crunching on the China Study II data in relation to heart disease mortality, cholesterol, wheat, and rice. Check out his posts The China Study II: Cholesterol seems to protect against cardiovascular disease and The China Study II: Wheat flour, rice, and cardiovascular disease.

(Big apologies to those who left comments on the last briefly-existent post! I decided to delete some stuff I wrote about my “suspicious connection” to the Weston A. Price Foundation because it came off sounding snarkier than intended, but then I ended up trashing the whole thing so I could post this with a different URL.)

A more substantial wheat entry is comin’ up next.

A few of you lovely readers emailed me today (thanks!) about the study Low-Carbohydrate Diets and All-Cause and Cause-Specific Mortality just published in the Annals of Internal Medicine. This paper compares mortality rates for folks eating a so-called “animal-based diet” versus a so-called “vegetable-based diet,” both of them so-called “low carbohydrate.” I finally got a chance to look at it, and indeed, a glance at the abstract looks a little spooky for any low-carb omnivores out there:

A low-carbohydrate diet based on animal sources was associated with higher all-cause mortality in both men and women, whereas a vegetable-based low-carbohydrate diet was associated with lower all-cause and cardiovascular disease mortality rates.

Oh noes! This abstract sounds vaguely China-Study-esque, with the conclusion that plant-based diets are healthier than ones featuring more animal foods. Was this study really comparing hardcore meat eaters with plant noshers, like the abstract implies? Is animal protein poison after all? Is it time to ditch the steaks and bow down in phytoestrogenic reverence to the almighty tofu?

I’ve said it before and I’ll say it again: In most cases, abstracts tell you a whole lotta’ nothing—so don’t judge a study until you’ve read the full text.

For right now, I’ll give this study the benefit of the doubt and ignore the fact that A) the researchers used a pretty lame decile-based scoring system* and B) employed the notoriously unreliable food-frequency questionnaire to collect their data.**

*NOTE: The decile method divvies up dieters into ten levels of adherence—with the folks in the first decile adhering the least to a low-carb diet, and the folks in the tenth decile adhering the most. The reason it’s lame is that it uses a scoring system based on misconceptions about what a low-carb cuisine looks like, including the necessity of a high protein intake.

**UPDATE: For a mighty entertaining explanation of the flaws of this study—including why food-frequency questionnaires are terrible—please read Chris Masterjohn’s take on this whole shebang. If possible, bring a scuba suit.

First, let’s take a look at what the low-carbohydrate folks were actually eating. Click the thumbnails for a bigger pic—first one’s women, second one’s men.

Ha ha ha ha.

Oh man.

I’ll sum it up. Some of the participants were eating up to 60% of their diet as carbohydrates (first decile), which—last time I checked—is kind of not low-carb. Even the lowest low-carb eaters were still eating over 37% of their calories from carbohydrates. Whoever decided to call this study “low carbohydrate” is nuttier than a squirrel turd. That doesn’t mean it can’t offer anything useful, though, so let’s look at what else is going on in the highest decile for each group (which is the only decile the researchers really looked at):

• Folks adhering the most to the animal-based diet were more likely to smoke and had higher BMIs than the best adherents of the Vegetable Group. Along with influencing mortality outcomes, this suggests the Animal Food group, in the highest decile, may have been somewhat less health-conscious than the dieters lumped into the highest decile for the vegetable category. And that’s the type of thing that has repercussions for other diet and lifestyle choices that weren’t measured in the study.
• The Vegetable Group was nowhere near plant-based: They derived almost 30% of their daily calories from animal sources (animal fat and animal protein), versus about 45% for the Animal Group. D’oh!
• The Vegetable Group adherents ate more fruits, vegetables, and whole grains than the Animal Group adherents—which begs the question: What kinds of carbohydrates filled this macronutrient void for the animal-food eaters? Could it’ve been refined grains and processed carbs, which the study conveniently forgot to document?
• For the Vegetable Group, cancer and cardiovascular mortality was lower in the tenth decile than the first decile, even though both deciles ate exactly the same amount of red meat and nearly the same amount of total animal foods. This suggests animal products aren’t the driving force behind differences in mortality rates.
• Similarly, at the fifth decile, the Vegetable Group had a lower cardiovascular mortality hazard ratio than the Animal Group (0.99 versus 1.21), even though the Vegetable Group was eating a slightly greater proportion of animal foods (33.3% versus 29.9% of total energy for women; 32.9% versus 31% for men).

Here are the mortality tables:

All Cause

Cardiovascular Disease

Cancer

And for the dieters scored based on Vegetable Diet adherence, the people with the lowest cancer mortality (male) and cardiovascular mortality (both genders) were not the ones eating the most plant foods—they were the folks in the sixth and seventh deciles, respectively:

Unfortunately, the article doesn’t show us the food/macronutrient breakdowns for any deciles besides the first, fifth, and tenth, so we don’t know what the average diet looked like for these people. But since the vegetable low-carbohydrate score was based on “the percentage of energy of carbohydrate, vegetable protein, and vegetable fat” the dieters consumed, it’s pretty safe to say that the folks in the sixth and seventh deciles were eating less plant foods than the tenth-decilers (and consequently, more animal foods).

Bottom line: In this study, when you look closer at the data, differences in mortality appear to be unrelated to animal product consumption. Changes in cancer and cardiovascular risk ratios occur out of sync with changes in animal food intake.

So what is responsible for the Vegetable Group’s lower mortality hazard ratios (and the Animal Group’s higher ones)?

Here’s a clue. Every time the researchers made multivariate adjustments to the data to account for the risk factors they did document (including physical activity, BMI, alcohol consumption, hypertension, and smoking, among other things), the hazard ratio went down for the Animal Group (meaning it got better) and it went up for the Vegetable Group adherents (meaning it got worse). That indicates pretty clearly that the Animal Group adherents had more proclivity to disease right from the get go, regardless of meat consumption, and the Vegetable Group adherents may have been more health-aware than most folks. (To see what I’m talking about, look at the mortality tables under the “10″ column, and compare the “Age- and energy-adjusted HR” with the “Multivariate-adjusted HR” for each group.)

In other words, it looks like what this study really measured was a Standard American Diet group (aka highest Animal Group decile) and a slightly-less Standard American Diet group (aka highest Vegetable Group decile). Both ate sucky diets, but the latter had slightly less suckage. You can bet the farm that neither was anything close to “low carb.” And if you have two farms, you can bet the other one that neither diet group was anything near plant-based, so I’m not sure the vegan crowd has much to gloat about here.

The End.

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:

• Diets containing whey proteins or soy protein isolate protect against 7,12-dimethylbenz(a)anthracene-induced mammary tumors in female rats. ” When 100% of the casein-fed rats had at least one tumor, soy-fed rats had a lower tumor incidence (77%) in experiment B (P < 0.002), but not in experiment A (P < 0.12), and there were no differences in tumor multiplicity. Whey-fed rats had lower mammary tumor incidence (54-62%; P < 0.002) and multiplicity (P < 0.007) than casein-fed rats in both experiments. … Furthermore, whey appears to be at least twice as effective as soy in reducing both tumor incidence and multiplicity.” (So much for plant protein being more protective against cancer!)
• Developmental effects and health aspects of soy protein isolate, casein, and whey in male and female rats. We found that SPI [soy protein isolate] accelerated puberty in female rats (p < .05) and WPH [whey protein hydrolysate] delayed puberty in males and females, as compared with CAS (p < .05). … Female rats fed SPI or WHP or treated with genistein had reduced incidence of chemically induced mammary cancers (p < .05) compared to CAS controls, with WHP reducing tumor incidence by as much as 50%, findings that replicate previous results from our laboratory.
• Tp53-associated growth arrest and DNA damage repair gene expression is attenuated in mammary epithelial cells of rats fed whey proteins. “Results indicate that mammary glands of rats fed a WPH [whey protein hydrolysate] diet are more protected from endogenous DNA damage than are those of CAS [casein]-fed rats.”
• A role for milk proteins and their peptides in cancer prevention. “Animal models, usually for colon and mammary tumorigenesis, nearly always show that whey protein is superior to other dietary proteins for suppression of tumour development.”
• A bovine whey protein extract stimulates human neutrophils to generate bioactive IL-1Ra through a NF-kappaB- and MAPK-dependent mechanism. “Our data suggest that WPE [whey protein extract] … has immunomodulatory properties and the potential to increase host defenses.”
• Whey proteins in cancer prevention.
• Whey protein concentrate (WPC) and glutathione modulation in cancer treatment.

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.

At any rate, I recommend not quoting this post or citing it as “evidence” for anything simply because of the uncertainty surrounding the Tuoli data in the China Study. Please see the following posts for more information on the issue of Tuoli’s accuracy:

http://rawfoodsos.com/2010/08/03/the-china-study-a-formal-analysis-and-response/

http://rawfoodsos.com/2010/07/16/the-china-study-my-response-to-campbell/

As I mentioned in the previous post on dairy consumption and disease in China, there’s a fascinating little county by the name of “Tuoli” situated in northwest China—a place quite worthy of nutritional study, due to their unique diet.

They live here:

Which looks like this:

Where they eat a lot of this:

But not a lot of this:

The Tuoli diet is so abnormal for China, in fact, that T. Colin Campbell et al omitted this county from analysis in several China Study papers—such as “Vitamin A and cartenoid status in rural China,” published in the British Journal of Nutrition:

One county (Tuoli County in Xinjiang Autonomous Region), composed primarily of an ethnic minority population of herdspeople, had disproportionately high values for retinol, lipid and protein intake due to an exceptionally high intake of animal foods. This ‘outlier’ was not included in the analysis, to characterize more accurately the average intakes of the rural Chinese population and to avoid the undue influence of one data point on the results.

Given the prevailing beliefs about nutrition and health—such as saturated fat and cholesterol as a cause of heart disease, the necessity of fiber for colon health, the immunity-boosting properties of fruits and vegetables, and the dangers of a diet high in animal fat—it would seem the Tuoli should showcase the health woes that come from breaking every rule in the diet book.

But is that the case?

Tuoli diet

First, let’s take a closer look at what he China Project data has to say about these Tuoli folks.

In terms of macronutrients, the Tuoli consumed an average of 185.6 grams of fat, 172.5 grams of protein, and 322 grams of carbohydrates per day. Average energy intake was a whoppin’ 3704 calories, and average fiber intake was 17.9 grams per day—only slightly more than your run-of-the-mill American.

The average diet of all counties studied in the China Project is clearly carb-based, low in fat and protein (as a percent of total calories):

In contrast, the Tuoli diet is nearly half fat:

Main items on the Tuoli menu included:

• Dairy: 856.5 grams per day (almost two pounds)
• Wheat flour: 371.6 grams per day (0.82 pounds)
• Meat: 121 grams per day (a bit over a quarter of a pound)

Sparse and non-existent items included:

• Potatoes: five to six times per year
• Green vegetables: twice per year
• Fruit: less than once per year
• Legumes: never
• Sea vegetables: never
• Nuts: never
• Eggs: never
• Fish: never
• Plant oils (rapeseed, soybean, sesame, corn): never
• Soy sauce: never

Basically, these folks live on dairy, meat, and wheat, and refuse to eat their vegetables. Sounds like some Americans I know.

Tuoli blood markers and diseases

If the Tuoli’s meat-and-dairy-heavy diet is the source of disease, we’d expect to see these folks facing more chronic conditions than the regions eating plant-based diets. To test whether this is the case, let’s compare Tuoli with the 13 counties in the China Project that consumed less than 1 gram of animal protein per day—the closest thing we have to Chinese vegans.

I’ll be putting these all in a bar graphs, but to prevent an uber-cluttered x-axis, I’ll just use numbers corresponding to each county:

1. Cixian
2. Jingxing
3. Huguan
4. Jiangxian
5. Jiexiu
6. Linxian
7. Songxian
8. Jianhu
9. Taixing
10. Qingzhen
11. Cangxi
12. Shanyang
13. Longxian
14. Tuoli

The first 13 counties will always be blue bars; Tuoli will always be red.

Before getting to the mortality statistics, let’s look at some basic blood markers for heart disease. Here we have total cholesterol of the above counties, lined up side-by-side for comparison.

As you might expect, Tuolians* have higher total cholesterol than most of the near-vegan counties, although it’s still a healthy number by American standards. However, the difference between a couple of those counties isn’t all that profound: Tuoli’s cholesterol is tied with that of Shanyang and lags a bit behind Taixing, both of which consume only trivial amounts of animal products. Curious, indeed. Obviously, something other than animal product consumption affects blood cholesterol.

*”Tuolian” may or may not be an actual term.

Next, let’s peek at triglycerides—a type of blood fat that, in high amounts, can raise your risk of heart disease.

It seems Tuoli is pretty much neck-and-neck with the plant-eating counties. By American standards, triglyceride levels between 150 and 199 are considered borderline high, and lower numbers are considered normal—so only one county, a near-vegan one, had values outside a healthy range.

Disease rates

First up: Death from all causes (per 1000 people under the age of 65). Remember, Tuoli county is the red bar; the blue bars represent the near-vegan counties in the China Project that consumed less than 1 gram of animal protein per day on average.

Okay, so the Tuoli don’t have a higher death rate than the near-vegans. In fact, Tuoli’s total mortality rate is lower than 11 of the other counties and higher than only two.

But what about cancer? Let’s look at mortality from all cancers for Tuoli and the plant-lovin’ regions. Again, Tuoli is the red bar, and the near-vegan counties are the blue ones.

How ’bout them apples? Tuoli doesn’t appear to have higher cancer rates than the near-vegan areas. Eight counties have higher rates and only five have lower ones, leaving Tuoli hovering near the lower-middle end of the spectrum.

Next we have mortality from myocardial infarction (heart attacks) and coronary heart disease, per 1000 people. Tuoli is red, near-vegan counties are blue… you know the drill.

Surprised? Despite a massive intake of cholesterol, saturated fat, calories, animal protein, and all those other horrors ascribed to declining heart health, the Tuoli have relatively low levels of coronary heart disease and heart attacks. Seven near-vegan counties have higher rates than Tuoli, and six have lower rates.

And now for stroke mortality (per 1000 people).

Again, no significantly higher stroke rates for the Tuolians. Seven near-vegan counties have more incidences of stroke, and six have fewer incidences of stroke.

And since lack of fiber is supposed to harm colon health, here is a comparison of colon cancer and rectal cancer mortality (per 1000 people) between the plant-noshing counties and the vegetable-phobic Tuolians.

Looks like they’re doing pretty dandy without much fiber, right?

But what about leukemia? Let’s check it out:

As you can see, Tuoli isn’t significantly worse off than the near-vegan counties in terms of chronic disease. Total mortality rate is lower, cancer rates are lower or similar, heart attacks aren’t more common than usual, stroke rates are average. From this data alone, we’d have no basis for claiming that eating two pounds of dairy per day (and minimal vegetation, aside from wheat flour) is less healthful than consuming a mostly vegetarian diet. For sure, this data fails to support Campbell’s claim that chronic disease rates climb when animal protein intake rises.

(And as you’ll see in an upcoming post, it’s pretty surprising that the Tuoli had low rates of cardiovascular disease while eating high levels of wheat—but we’ll get to that later.)

Why aren’t these people sick and diseased?

We have plenty of evidence showing hormone-pumped dairy, grain-fed meat, pasteurized and homogenized milk, processed lunch meats, and other monstrosities are bad for the human body. No debate there. But we do have a woeful lack of research on the effects of “clean” animal products—meat from wild or pastured animals fed good diets, milk that hasn’t been heat-zapped, antibiotic-free cheeses and yogurts, and so forth. Perhaps the best data we have is from observational studies of isolated or primitive peoples (such as those studied by Weston A. Price), but those lack detailed documentation about mortality rates and don’t usually meet standards of scientific rigor.

In other words, this is one area where nutritional research is pretty deficient.

Is it possible the diseases we ascribe to animal products aren’t caused by animal products themselves, but by the chemicals, hormones, and treatment processes we expose them to? If the Tuoli are any indication, this may be the case. Hopefully future research will shed more light on the matter.

Mongolian yaks: A source of Chinese dairy.

I’ll admit it: Out of all the variables in the China Project, dairy is the one I’ve been most eager to analyze. Not because I’m a dairy lover myself (I haven’t touched it in years) or because I’m secretly a billionaire milk tycoon with my own thousand-acre Holstein farm (au contraire; I’m strangely phobic of cows). In his book, T. Colin Campbell makes such a compelling case about casein (a milk protein) as a cancer-promoting agent that I’m left wondering: Does the China Study data shows an equally convincing link between dairy and disease?

After all, the counties studied in the China Project weren’t eating the hormone-laden, antibiotic-stuffed, factory-farmed dairy we find in most stores. Their dairy was from pastured animals—typically sheep, goats, or yaks along with cattle—raised on natural diets in rural areas. As best I can deduce, milk products were neither pasteurized nor homogenized. This means that any connections we find between dairy and mortality variables are probably from dairy itself—not the nastiness that accompanies the dairy Westerners are more familiar with. This could be one of our best opportunities for studying dairy consumption in its raw, natural state. Yeehaw!

(Note: If this is your first visit to my site and you’re on a quest for China Study information, you may want to start with the earlier posts in this series:)

• What the China Study says about meat and disease
• What the China Study says about fish and disease
• What the China Study says about eggs and disease

Dairy consumption in rural China

First, the bad news—from a scientific standpoint, at least. Only three out of the 65 counties in the China Project consumed any noteworthy amount of dairy at all. The rest were completely dairy-free or consumed dairy only a handful of times per year. That means our sample size of hardcore dairy eaters is tiny, and drawing any conclusions about dairy consumption is trickier than if we had lots of dairy-eating regions to examine.

But there’s some good news, too. Two of the counties that did eat dairy ate a lot of it—856.5 grams per day for Tuoli (just shy of 2 pounds!) and 147 grams per day for Xianghuang qi (about a third of a pound). In terms of diet, both of these places are proverbial black sheep in China, making them quite interesting as case studies. And because these regions consumed so many milk products in contrast to everyone else, any correlations genuinely tied to dairy should be pretty dramatic.

Baoqing county, the third highest consumer of dairy, ate about 19.1 grams of milk products per day. Not a whole lot, for sure, but we should keep an eye on this county as well when looking for links with disease.

A tad more info on these places for anyone who’s curious:

Tuoli county. Located at the tippy-top of northwest China in the Uyghur region—a straggler county on the map, much farther west than any other area studied in the China Project. The Tuoli get over half of their daily calories from dairy products (holy cow, literally; this is even more than Americans eat) and are quite fond of yogurt. They consume very few vegetables, fruits, or nuts, but do eat a significant amount of wheat flour.

Xianghuang qi county. Located in inner Mongolia. Local cuisine includes mutton and dairy products—especially yogurt, fermented milk, Mongolian milk tea, butter, and cheese—as well as oats and buckwheat. Vegetables haven’t been a big part of their menu until quite recently. You can read more about the diet of this region at China.com.

Baoqing county. Located at the northernmost and easternmost spot out of all the counties studied. These folks are one of our highest egg eaters, eat moderate amounts of meat, and consume wheat as their primary grain.

Dairy consumption in rural China

In China, dairy intake ranged from zero grams per day to 856.5 grams per day, as mentioned earlier. Since so few counties consumed milk products, our correlations are strongly swayed by the habits of the two dairy-eating regions. Those include snuff use (correlation of +98), meat eating (+52) and wheat intake (+35). Dairy-eating people also tended to be heavier and taller than other Chinese citizens (+34 and +23, respectively). Although the additional fat and protein from dairy foods could be responsible for a bigger body size, inhabitants of these regions tend to be ethnic minorities in China, and it’s possible they have larger builds genetically.

Dairy intake correlates positively with HDL or “good” cholesterol (+29), but not with LDL or “bad” cholesterol (-15). And in terms of general diet composition, dairy-eating regions had a low intake of fiber (-28), soluble carbohydrates (-23), and plant protein (-25) but a high intake of total protein (+80), animal protein (+99), total fat (+78), and total calories (+62).

So does all this animal protein and fat equate to more chronic diseases, especially cancer? Let’s take a look-see. Surprisingly, there’s only one statistically significant correlation, so I’ll list even the weak correlations to give the full picture.

NEGATIVE CORRELATIONS (more dairy = fewer of these diseases)

Liver cirrhosis: -21
Peptic ulcer: -19
Lymphoma: -19
Other metabolic diseases: -17
Rectal cancer: -14
Penis cancer: -13
Diabetes: -10
Colorectal cancer: -9
Death from all causes: -9
Other heart disease: -9
Bladder cancer: -8
Diseases of the blood and blood-forming organs: -7
Colon cancer: -6
Leukemia: -6
Liver cancer: -4
Neurological diseases: -2

POSITIVE CORRELATIONS (more dairy = more of these diseases)

Hypertensive heart disease: +30*
Stomach cancer: +10
Breast cancer: +9
Stroke: +9
Oesophageal cancer: +8
Death from all cancers: +7
Myocardial infarction: +6
Brain cancer: +4
Cervix cancer: +2
Rheumatic heart disease: +1

Remember that, for both positive and negative correlations, smaller numbers are essentially insignificant. Zero is perfect neutrality, but we rarely get a statistical zero in the real world—especially when we have a maximum of 65 data points to work with. With the exception of hypertensive heart disease, none of the positive correlations appear meaningful, and perhaps only lymphoma and “other metabolic diseases” warrant further study among the negative correlations. (Liver cirrhosis and peptic ulcers, the other marginally strong inverse trends, most likely have non-nutritional causes.)

Hypertensive heart disease

Unlike atherosclerosis, hypertensive heart disease is not caused by plaque building up on arterial walls. With this condition, chronic high blood pressure (AKA hypertension) forces the heart to work harder, leading to a thickening of the muscle. Does something about dairy consumption raise blood pressure and lead to a big heart (the diseased kind, not the generous kind)?

Looking solely at the “hypertensive heart disease” variable, we can see that a few other factors outshine the dairy correlation. Daily salt intake correlates at +37, salt intake plus urine salt correlates at +50, weight correlates at +33, and wheat flour correlates at +54. The “other foods” category—which includes vinegar, MSG, baking powder, tea, and melon seeds—has a correlation of +51. Negative associations include rice (-45), yearly green vegetable intake (-36), steamed bread and pancakes (-57), and daily alcohol consumption (-27).

Since we really only have three counties that consumed significant levels of dairy, it won’t be easy—and maybe not even possible—to pinpoint the role of dairy itself in hypertensive heart disease. Here’s our untampered graph, charting every county that reported hypertensive heart disease  mortality.

Kinda sparse, huh?

There certainly is an upward trend amongst dairy-eating counties, but let’s face it: We’re basing that on two measly dots. Dots that, more importantly, represent complete dietary rebels in this data set. Along with consuming milk products, our two dairy-eating regions have some other nutritional divergences compared to the rest of China. For instance:

• Both significantly fewer vegetables than any of the other 65 counties in the China Project: Tuoli only consumes green vegetables an average of two times per year (!) and Xianghuang qi consumes them 24 times per year, about twice per month. The average intake for all counties is closer to 200 times per year. Could lack of green vegetables, which we already know correlates with hypertensive heart disease, be raising these county’s rates?
• Tuoli consumes a whoppin’ average of 172.5 grams of protein per day, 134.55 of which come from animal sources. Even a gym-rat bodybuilder might consider that excessive. No other county comes close to that intake; the next highest is 90.8 grams per day. Could an uber-high protein intake contribute to hypertension?
• Tuoli also consumes far more fat than any other county: 185.8 grams per day. Wowza. The average for all of China is 44.2. Is a high fat intake playing a role?
• As you’d expect from a very high-fat diet, the Tuoli eat more calories per day than any other county studied in the China Project: 3704 on average. No, that’s not a typo. They’re also the heaviest county among the 65. Do these folks have higher rates of obesity, which surely is a risk factor for hypertensive heart disease?
• Both dairy-eating counties had a higher levels of dietary and urine sodium than average. This one’s a no-brainer; excess sodium is a well-known cause of high blood pressure and, consequently, hypertensive heart disease.
• Both dairy-eating counties eat significant quantities of wheat flour, which—as you shall soon see—has some really mind-bogglingly crazy associations with cardiovascular disease. Seriously, it’ll knock your socks off. But that’s a few more posts away.

And despite eating almost two pounds of dairy a day, Tuoli’s hypertensive heart disease mortality (far right dot) is still surpassed by two other counties—both of which eat no dairy at all. And the disease rate for Xianghuang qi county is right smack dab in the middle of the data set range, ranking behind six dairy-free counties. Even if dairy is a factor in developing hypertensive heart disease, which we can’t say for certain, it’s clearly not the only contributor.

At any rate, I’m not interested in vilifying nor vindicating dairy here; I’m just exploring alternative possibilities for the correlation between milk products and hypertensive heart disease.

Bottom line:

• China’s dairy eaters don’t have significantly more cancers, myocardial infarction, stroke, and so forth than the dairy-free regions.
• Dairy’s only significant mortality correlation, hypertensive heart disease, may be related to any number of variables we don’t have enough data to tweeze apart. (Lack of vegetables, excess sodium, high body weight, and high caloric intake, to name a few.)
• Despite T. Colin Campbell’s findings with the milk protein casein spurring cancer in lab rats, there does not seem to be a correlation between high dairy consumption and cancer in the China Study data.

Are you as fascinated as I am with the Tuoli’s incredibly high-fat, high-protein, vegetableless diet? Are you wondering what their disease rates are, how long they live, and whether they’re any healthier or sicker than the Chinese eating plant-based diets? I sure am. Up next will be a mini-post about the Tuoli specifically, including answers to the aforementioned questions. This should be pretty interesting!

Ah, eggs: Incredible and edible, as the commercial goes. A quintessential staple of American breakfasts, loaded with protein, packed with cholesterol. Bodybuilders chug ‘em down en masse, and raw foodists sometimes experiment with them—but could they raise your risk of disease, as T. Colin Campbell claims all animal foods do? Let’s take a look at the original China Study data and find out.

Egg consumption in rural China

There’s no doubt about it: Eggs aren’t exactly a staple in China. In the China Project counties, egg consumption ranged from zero grams per day to 14.8 grams per day, which is the equivalent of about two or three chicken eggs per week. Not a lot. Although the data is still relevant, whatever we find here only reflects modest egg consumption—not a daily four-egg-omelet habit, for instance.

Unfortunately, we don’t have much information on what kind of eggs these people were eating. You wouldn’t guess it by strolling through an American supermarket, but chickens are, in fact, not the only birds that lay edible eggs. (Shocking, eh?) In China, meals can include eggs from ducks, quail, geese, pigeons, and other poultry, along with those of chickens. And rather than our familiar omelets and souffles, Chinese cuisine embraces things like salted duck eggs (which are soaked in brine for a month) and century eggs (which are soaked in a mixture of ash, salt, clay, lime, and rice straw for a few months—’til the yolks turn green and the eggs develop a delightful ammonia smell).

Alas, the only variable we have in the China Project data is “egg intake,” so we can’t see if particular types of eggs or preservation methods have different effects than others. An unfortunate limitation indeed. But we’ll work with what we’ve got.

In China, egg consumption tied in with a number of other variables. The folks who ate eggs tended to also have low triglycerides (-42), got a larger portion of their total calories from fat (+37), loved them some sea veggies (+41), indulged in a bit of processed starch and sugar (+33), piled on the soy sauce (+45), used a fair amount of soybean, cottonseed, sesame, and peanut oil (+32), gulped down the beer (+38), and smoked cigarettes (+34). Like fish eaters, eggy folks worked more often in industry than in agriculture (+37 and -49, respectively). Whew! Lots of variables there.

Here’s what egg-related correlations look like without adjusting any variables. Again, I’ll just be discussing the statistically significant ones.

NEGATIVE CORRELATIONS (more eggs = fewer of these diseases)

Liver cirrhosis: -46***
Peptic ulcer: -43**
Diseases of the blood and blood-forming organs: -35*
Death from all causes: -33*
Digestive disease other than peptic ulcer: -30*
Hypertensive heart disease: -28
Oesophageal cancer: -26*
Death from all non-cancer causes: -26

It’s questionable how many of these ailments (apart from heart disease and blood-related woes) are even related to diet, so I won’t gush over these happy correlations too much. Things like liver cirrhosis are probably related more to hepatitis B infection, peptic ulcers are linked to the bacterium Helicobacter pylori, and digestive diseases (whatever those consists of) could be related to infection or parasites. But I will say that eggs, in the modest amounts the Chinese consumed, don’t appear to tarnish heart health in any way. Along with hypertensive heart disease, other cardiovascular problems have inverse or neutral correlations with egg intake (-21 for rheumatoid heart disease, -13 for myocardial infarction, and -8 for stroke).

POSITIVE CORRELATIONS (more eggs = more of these diseases)

Colorectal cancer: +35*
Colon cancer: +34*
Rectal cancer: +30*

Look familiar? It should. If you’ll recall, we saw high rates of colorectal cancers (colon and rectal) with meat in an earlier post—a trend that turned out to be related to schistosomiasis infection, not meat itself. And as it just so happens, egg intake correlates strongly with schistosomiasis as well, at the statistically significant rate of +40. Could that pesky little parasite be causing colorectal cancers in egg eaters?

Yep, that’s right… graph time! You know you love it.

Here we have three charts mapping the correlation between eggs and rectal cancer, colon cancer, and all colorectal cancers—using only the counties free from schistosomiasis infection.

Voila; we no longer have a statistically significant correlation between eggs and any form of colorectal cancer. As you can see, even our counties with the highest egg consumption didn’t have considerably more or less of these cancers than the eggless populations.

In conclusion:

We can’t say too much about eggs one way or another, simply because our data pool is limited and we lack some pertinent info—like what kinds of eggs these people ate and in what form. However, based on what we do know from the China Project, there’s no reason to think eating a couple of eggs per week (hopefully organic and free-range) would have any negative health repercussions. More than that may be fine, too; we just can’t say for sure based on this data alone. In fact, egg consumption may even offer benefits for heart health and “diseases of the blood and blood forming organs,” as the variable is titled.

Next up is the last of our animal products: dairy.

In my last post, I explored what the China Study data says about meat and disease—which turns out to be a far cry from what Campbell reports in his book of the same name. In a nutshell, meat has no statistically significant correlations with any diet-related disease, and actually has a negative correlation with death from all causes and death from all cancers. That means the populations that ate more meat generally had fewer chronic diseases than the populations that ate less of it. While it’s impossible to tell from the China Project alone whether this is because meat was protective of illness or simply corresponded with other helpful factors (like better health care), it does undermine Campbell’s assertion that animal product consumption always went hand-in-hand with disease in the China Project.

(If you’re not sure what the China Study is or why I’ve suddenly made it my life’s purpose to examine every modicum of its data, take a gander at the previous entry for an explanation.)

Of course, the “meat” category doesn’t include fish, eggs, or dairy—so these foods aren’t out of the hot seat yet. In this post, I’ll be looking at fish. Sushi lovers, listen up.

Fish intake in rural China

Among the 65 counties studied in the China Project, fish consumption ranged from zero grams per day to 119 grams per day—a bit over a quarter of a pound. Unfortunately, all forms of seafood (finned fish, shell fish, roe, and so forth) are lumped under the same category, even though these foods tend to have much different nutritional profiles.

Surprisingly, fish had no statistically significant association with mercury intake (correlation of -8).

One thing striking about fish consumption in the China Study is that fish-eating regions have quite a few things in common: These counties tend to have a high population density (correlation +46), citizens overwhelmingly work in industry rather than agriculture (correlation +52 for industry and -53 for agriculture), and folks eat a great deal of processed sugar and starch along with the fish (correlation +58) as well as loads of soybean oil, sesame oil, peanut oil, and cotton seed oil (correlation +61). Infant mortality is low, literacy is high, and beer and liquor are quite popular beverages—especially among men. Although occurrence of heart disease is sparse, the average cholesterol levels are high compared to non fish-eating regions (+45 for total cholesterol, +38 for HDL, and +36 for non-HDL)—which doesn’t exactly support the cholesterol-heart disease connection, but I’ll get to that later.

Unlike meat, fish is quite obviously associated with more industrialized coastal regions—which makes things a little tricky when it comes to untangling variables. Putting nutrition aside for a second, we can see that industry-dominated regions are riddled with chronic diseases that rural regions generally don’t exhibit. According to the China Project data, the variable “Percentage of employed population who are in industry” has the following correlations with disease:

Male lung cancer: +62
Leukemia: +53
Female lung cancer: +47
Liver cancer: +47
Colon cancer: +41
Other heart disease: +40
Death from all cancers: +31
Colorectal cancer: +31
Stomach cancer: +25
Breast cancer: +24
Brain cancer: +21

(On the bright side, they have low rates of infectious diseases, pneumonia, parasites, tuberculosis, and other ailments common in the agricultural regions—indicating better living conditions and perhaps better health care.)

In other words, the folks who eat lots of fish typically work in industry, and the folks who work in industry typically have high disease rates. But is the fish to blame? Or is it one of the other factors associated with industry work, like processed starch and sugar intake or occupational hazards? Let’s find out. Here are the straight-up correlations, not adjusted for the variables that could be skewing the trends.

For the sake of science, I’ll only be focusing on the statistically significant correlations in this post.

NEGATIVE CORRELATIONS (more fish= fewer of these diseases)

Rheumatic heart disease: -43**
Diseases of blood and blood forming organs: -35**
Death from all non-cancer causes: -30*

If we prune away the variables that coincide with fish consumption but that negatively impact health—like processed sugar and starch intake, liquor consumption, soybean oil use, and so forth—I wouldn’t be surprised if some of the other correlations would  reach statistical significance:

Neurological diseases: -23
All diseases: -20
Oesophageal cancer: -19
Cervix cancer: -18
Myocardial infarction and coronary heart disease: -15
Stroke: -15
Hypertensive heart disease: -14

Given the non-China-Project research we have regarding fish, this isn’t too surprising: The omega-3 fats in fish tend to benefit cardiovascular function and work as blood thinners, so it’s no shocker that fish-eating regions have low rates of heart disease. In fact, in 2003, Campbell himself co-authored a paper on the protective effects of fish and DHA as revealed by the China Study data: Fish consumption, blood docosahexaenoic acid and chronic diseases in Chinese rural populations. (Too bad he forgot to include that in his book.)

But that’s only the positive stuff. Now let’s look at the more incriminating side of the fishy coin.

POSITIVE CORRELATIONS (more fish = more of these diseases)

Nasopharyngeal cancer: +56***
Diabetes: +41**
Liver cancer: +34**
Leukemia: +25*

Jeepers! That doesn’t look too good, does it? Positive correlations with several cancers and diabetes, all statistically significant. Could fish be a bona fide health-wrecker, even if it does spare your heart? Let’s take a look at these correlations one by one.

Nasopharyngeal cancer

Nasopharyngeal cancer—or NPC, so I don’t have to keep typing that horrible word—is a type of cancer that occurs at the back of the nose, towards the base of the skull. It’s pretty rare in most of the world: Only about 7 out of every million people get it in the US. The main folks with high rates of NPC are some Chinese populations, the Inuit, and some tribes from North Africa, according to the American Cancer Society.

In the counties studied in the China Project, men generally had between two and twelve times as much NPC as women—indicating that this is gender-biased disease. Since diet didn’t differ severely between the sexes, it’s possible that NPC occurrence is related to a lifestyle practice that Chinese men engaged in more than women (such as drinking or smoking). And indeed, NPC has a correlation of +50 with daily liquor consumption, +40 with daily alcohol consumption, +33 with daily beer consumption, +24 with total tobacco consumption, and +22 with homemade cigarette use.

In looking at NPC factors, something else jumps out at me: The heavy metal cadmium is strongly associated with NPC (correlation of +42). This particular metal is known to contribute to a variety of cancers, including NPC. Although cadmium doesn’t occur naturally in food, eating plants grown in cadmium-contaminated soil—or eating animals that consume said plants—is a surefire way to get it stuck in your body for a few decades. Is it possible the coastal, industry-dominated regions that ate the most fish also had cadmium-contaminated soils? Is it possible certain aquatic regions were also polluted with cadmium, which then accumulated in fish?

First, here’s a graph showcasing the original +56 correlation, using all of the data points for fish intake and NPC.

And here’s a graph using only counties that ate less than 25 micrograms of cadmium per day, as determined by the food composite survey for heavy metals. Some of the now-omitted regions were consuming over 90 micrograms per day, which is considered pretty toxic.

Woosh!

Simply removing cadmium from the equation, we’ve bumped a correlation of +56 down to +14, below the threshold of statistical significance. And get this: That highest data point on the chart, near the “12″ grid line, is for the county with the absolute highest use of homemade cigarettes—which not only correlates independently with NPC, but is likely to be a source of cadmium exposure. Coincidence? Perhaps not.

It’s still not clear if cadmium is actually a factor, though, and we’ll never know for sure based on China Study data alone. The American Cancer Society cites infection with the Epstein-Barr virus, consumption of salt-cured foods, and exposure to formaldehyde and wood dust as potential causes of NPC. The China Project data also shows a strong correlation between NPC and tuberculosis, parasitic infection, and peptic ulcers. How are these things related—if they’re related at all? Beats me. I’m no nasopharyngeal cancer expert. But given the prevalence of this disease only in a smattering of places in the world, it’s probably due more to specific food contaminants, certain disease infections, or simply genetics.

Diabetes

Without peeling away any confounding variables, fish has a correlation of +41 with diabetes. That’s pretty high. But given that fish-eating regions also ate above-average amounts of processed sugar and starch (correlation of +58) and also tended to be heavier than most (correlation of +20), we might have a pretty obvious explanation for this sky-high rate. Here’s what our graph looks like using only counties that escaped the ravages of these nutritionally devoid foods, eating 0.5 grams or less of processed sugar and starch per day.

No positive correlation there. Without the influence of processed sugar and starch, the correlation between fish intake and diabetes nosedives from +41 to -5. We’re still in the wobbly land of epidemiological correlations, so we can’t say anything for sure, but it looks like fish itself doesn’t contribute to diabetes. (Unless your fillet of salmon is encrusted with Twinkies.)

Liver cancer

In China, liver cancer—like NPC—is extremely gender biased. In nearly every county, the mortality rates for liver cancer were between two and seven times higher for men than women. Since diet didn’t differ much—if at all—between the sexes, this is a red flag that liver cancer is something related to gender-specific lifestyle habits rather than diet alone.

Indeed, this is one disease that, in the China Study populations, has very little to do with diet: It’s linked pretty blatantly to hepatitis B infection across all counties. This is nothing revelatory, though. The World Health Organization already figured it out:

Hepatitis B is endemic in China and other parts of Asia. Most people in the region become infected with HBV during childhood. In these regions, 8% to 10% of the adult population are chronically infected. Liver cancer caused by HBV is among the first three causes of death from cancer in men, and a major cause of cancer in women.

Dur. Not surprisingly, fish-eating regions not only exhibited high rates of liver cancer, but also had large chunks of the population testing positive for the hepatitis B virus—a correlation of +35, a smidgen higher than the correlation with liver cancer. In other words, it looks like fish-eating regions had a lot of HPV-induced liver cancer, but diet wasn’t the cause.

Leukemia

According to the raw data, fish had a correlation of +25 with leukemia. Is this one legit?

For starters, let’s look at factors that correlate with leukemia in the China Project data. The most significant variable both fish consumption and leukemia have in common is industry work: +52 for fish and +53 for leukemia. (They both share a inverse correlation of -53 with agricultural work.) Could something about industry labor itself be a factor in leukemia occurrence? My spidey senses are tingling.

And look what we have here:

A retrospective cohort study was carried out in 1982–1983 among 28,460 benzene-exposed workers (15,643 males, 12,817 females) from 233 factories and 28,257 control workers (16,621 males, 12,366 females) from 83 factories in 12 large cities in China. … Risk of leukemia rose as duration to exposure to benzene increased up to 15 years, and then declined with additional years of exposure. Leukemia occurred among some workers with as little as 6 to 10 ppm average exposure and 50 ppm-years (or possibly less) cumulative lifetime exposure (based on all available measurements for the exposed work units).

The years cited for this study, by the way, are right around the time the China Study data was collected. How convenient!

Indeed, it seems benzene exposure was a significant problem for some industrial workers in China—the same industrial workers who ate a lot of fish. So is seafood to blame for higher leukemia rates, or could it be occupational hazards like benzene?

Unfortunately, the China Project doesn’t record benzene exposure. And we’re a few decades too late to go track down that data now (if you have a time machine, please contact me). What we can do is clarify the picture by looking at fish consumption and leukemia in counties with low levels of industrial employment. Here’s a graph showing exactly that—using only regions where less than 10% of the population worked in industry:

So there you have it. With industrial work out of the equation, fish no longer bears a statistically significant correlation with leukemia.

In a nutshell:

• Based on the China Project data, fish may have a protective effect against some forms of heart disease, diseases of the blood, and diseases of blood-forming organs.
• Fish intake has raw correlations with several cancers and diabetes, but these trends appear to be a result of other factors that accompany fish consumption rather than the fish itself (cadmium exposure, processed sugar and starch intake/high body weight, hepatitis B infection, and benzene exposure). When we tease out these confounding factors, fish loses or reverses its positive correlation with these diseases.
• No matter what you eat—vegan, vegetarian, pescetarian, or otherwise—be  cautious about cadmium intake, since this metal does appear to cause some cancers and disease.

That’s all for the fish, folks. Next up: eggs and dairy.

As promised, it’s time to unveil all this China Study business. Grab a raw, nonalcoholic drink and make yourself comfy!

Let me start by saying that this isn’t an attempt at “debunking” the China Study or discrediting T. Colin Campbell. Quite the contrary. “The China Study” book is excellent in many ways, if only to underscore the role of nutrition in health. If I ever met Mr. Campbell in person, I’d give him a jubilant high-five and thank him for fightin’ the good fight—for exposing the reality of Big Pharma, for emphasizing the lack of nutritional education most doctors receive, for censuring the use of scientific reductionism, for underlining the importance of diet in disease prevention. Campbell and I are on the same page in many ways. His scroll of accomplishments is impressive and I sincerely believe his heart is in the right place, even if I don’t agree with all of his conclusions.

My goal here is solely to look at the original China Study data and see what it says. When Campbell’s conclusions seem valid, I’ll point it out. When Campbell’s conclusions seem awry, I’ll point it out.

For anyone who hasn’t read it yet, here’s a brief rundown of Campbell’s book and the main study it’s based on. Skip this if you’re already familiar with it (or just too impatient to sit through my drivel).

What is the China Study?

The original China Project is a ginormous study chronicling the diets, lifestyles, and disease trends in 65 rural regions in China. Its data comes from two major surveys—one conducted in 1983/84 and another in 1989/90—and uses data from diet and lifestyle questionnaires, blood and urine samples, three days of diet observation, and local mortality rates for major chronic diseases.

Intrigued? You can read more about it on the Cornell University website.

The uninterpreted data was published in 1990 in a book called “Diet, Life-Style and Mortality in Rural China.” If you want to read it, you can find it at some university libraries, request it at a public library through an inter-library loan, or shell out $90 for a used copy on Amazon.

Why the China Project design is awesome:

• People in these rural Chinese counties tended to live in the same region for life, eating the same diet from birth until death—making it relatively easy to examine nutritional patterns in relation to disease.
• Different regions often had vastly different diets: Some were nearly vegan, some ate boatloads of sweet potatoes, and one county ate two pounds of dairy foods per day (Tuoli). These wide variations make it easier to see trends than if all the data points were more homogeneous.

Why the China Project design is not awesome:

• All the collected data was aggregated at the county level, so even though many thousands of people were involved in the study, we ultimately only have 65 data points to work with. That’s not a whole lot, especially considering how many variables there are.
• Although diet and some lifestyle factors were covered, the China Project didn’t capture any information on physical activity. We don’t know how exercise habits varied between regions, so we can’t determine how activity influenced the occurrence of disease.
• Most importantly: This is an epidemiological study. There aren’t control variables, and it’s impossible to draw actual conclusions from the data. All it reveals are correlations, which may or may not be influenced by additional factors.

Indeed, a golden rule of statistics is correlation doesn’t equal causation. You might see a lot of umbrellas when it rains, but that doesn’t mean umbrellas cause the rain. You might see a particular food pop up in relation to some disease, but there’s no way to tell—from the China Project alone—whether it’s a cause, a consequence, or simply there because of a third unstudied variable.

“The China Study” book is the only reason most people even realize the China Project exists. In this book, Campbell blends research he conducted on rats, aflatoxin, and casein with the results unveiled by the China Study. His ultimate message is that animal protein unequivocally causes cancer (as well as other chronic conditions like heart disease and diabetes), and he claims in no uncertain terms that the China Project data supports this conviction.

Of course, “The China Study” isn’t airtight. Here’s what I take issue with:

1. Campbell projects the effects of casein onto all forms of animal protein, while ignoring research to the contrary (such as the potential anti-cancer properties of whey).
2. The correlation between all animal protein and disease isn’t supported by the original China Study data.
3. The book focuses myopically on the effects of animal foods, while not even mentioning the (incredibly strong) associations certain vegan foods have with disease.

A quick note on stats

Not a math whiz? No problem. The stuff here should be pretty straightforward, but in case you’re rusty or simply allergic to numbers, here’s a refresher on some of the statistics terminology I’ll be using.

A positive correlation means two variables increase together and decrease together. For example, the more food Garfield scarfs down, the more Garfield weighs; the less food Garfield eats, the less Garfield weighs.

A negative correlation means one variable increases while the other decreases, and vice versa. For example, the more Garfield exercises, the less Garfield weighs; the less Garfield exercises, the more Garfield weighs.

To simplify the numbers, I’m expressing correlations in this entry (and subsequent ones) as percentages rather than decimals. That means a correlation that’s normally 0.5 will appear as 50, for instance.

Positive correlations range from 0 – 1 (or 0 – 100 as percentages), and negative correlations range from -1 – 0 (or -100 to 0 as percentages). Due to the sample size of the China Project, correlations greater than 25 or lower than -25 are the most important to look at, and correlations closer to zero aren’t worth more than a cursory glance. The higher the number is, the stronger the correlation.

A p-value indicates how sure you are that your results are accurate and not just a matter of chance. Most statisticians like to use a p-value of 0.05 or less, which means there’s only a 5 in 100 possibility that your results are merely a fluke.

Correlations marked with asterisks indicate the following p-values:

* = p<0.05 (5 in 100 chance that the correlation is accidental)
** = p<0.01 (1 in 100 chance that the correlation is accidental)
*** = p<0.001 (1 in 1000 chance that the correlation is accidental)

Last but not least…

Even though the China Project data documents them, I won’t be looking at correlations with parasite infection, diseases caused by a specific nutrient deficiency, diseases related to environmental factors (like dust disease), and mortality for people under the age of 15 (since the data is typically too sparse to form anything statistically significant, and less likely to reflect diseases caused by long-term nutrition). Mostly, this will be about various cancers and cardiovascular diseases in relation to food.

Now we’re ready to roll. If animal protein is truly a potent, universal cause of disease in humans, we should expect to see strong correlations with chronic conditions whenever meat, egg, dairy, and fish consumption rises. Luckily for us, the China Project documented each of these food types as separate variables, so we can look at each one individually.

First in line: meat.

Meat intake in rural China

From the China Project data, we can see that meat intake ranged from 0 grams per day in Jingxing to 121.1 grams per day in Tuoli, with an average of 26.4 grams for all counties.

Since epidemiological studies are a tangled mess of correlations, we ought to look at the other factors that accompany meat eating in China so we can see the full picture. Meat consumption corresponds positively with beer consumption (+25) and liquor consumption (+26), as well as milk intake (+52),  intake of refined starch and sugar (+25), egg consumption (+38), and use of snuff (+55). In other words: any diseases we find associated with meat could also be related to drinking habits, snuff usage, or consumption of these other foods.

Negative correlations with meat include intake of plant protein (-36), crude fiber intake (-49), intake of other cereal grains (-38), intake of starchy tubers (-31), pipe smoking (-34), intake of salted vegetables (-26), intake of carrots (-29), and sweet potato consumption (-31). In other words: any diseases we find meat protective against could really be due to avoidance of starchy tubers and salted vegetables, a low level of plant protein intake, and so forth.

So what does the original China Study data reveal about meat and disease?

NEGATIVE CORRELATIONS (more meat = fewer of these diseases)

Liver cirrhosis: -38**
Oesophageal cancer: -29*
Myocardial infarction and coronary heart disease: -28*
Cervix cancer: -23
All cancers: -20
Penis cancer: -18
Diseases of blood and blood forming organs: -17
Neurological diseases: -13
Stroke: -12
Diabetes: -11
Lymphoma: -8
All non-cancer causes: -6
Stomach cancer: -5
Hypertensive heart disease: -4
Rheumatic heart disease: -4
Leukemia: -3

With the exception of the first three, none of these trends are “statistically significant”—meaning the correlation is too loose to mean a whole lot. We can assume everything south of myocardial infarction isn’t terribly important. Even so, meat sure doesn’t look like the cancer-causing villain we might expect from reading “The China Study”: Its intake correlates negatively with the average for all cancers, which is a fairly important indicator. And considering meat intake occurs in conjunction with a few unhealthy factors—like beer intake, snuff usage, and lowered fiber and vegetable consumption—it’s possible that meat would have even lower negative correlations with these diseases in isolation.

Perhaps more surprising, though, is that meat actually seems protective of heart attacks and coronary heart disease—at least based on the China Project data set. A correlation of -28, and statistically significant to boot. No wonder Campbell never cited China Project data in his chapter on heart disease: The trend here favors animal food consumption.

But before diving into the nearest steak for the sake of your cardiac health, remember that confounding factors might be skewing these results. Could the meat-eaters be doing something else—a mysterious, intruding variable—that lowers their incidence of heart disease? Quite possibly. The only thing we can say is that meat isn’t playing a convincing role as a cause of all vascular diseases and most cancers.

POSITIVE CORRELATIONS (more meat = more of these diseases)

Colon cancer: +20
Nasopharyngeal cancer: +19
Breast cancer: +15
Colorectal cancer: +10
Rectal cancer: +10
Brain cancer: +10

None of these correlations are considered “statistically significant,” but  let’s take a look at them anyway for the sake of illustrating variable entanglement. What we have are some diseases of the lower digestive tract, including colon and rectal. The “colorectal cancer” variable, by the way, is just a combination of the colon cancer and rectal cancer incidences in each county, although a few counties didn’t report data on these diseases separately.

The correlation between meat and these diseases isn’t alarmingly high; in fact, colon cancer has a stronger correlation with sea vegetable consumption (+56), working in industry (+41), and consuming rapeseed oil (+34). Still, the numbers are positive, and it’d be easy to take a cursory glance at this data and think, “Hey! Meat mucks up your digestive tract.”

But just for kicks, let’s look at another variable meat goes hand-in-hand with: infection with the schistosomiasis parasite. This is actually most associated with sea vegetable intake (correlation +74), but it also corresponds with meat intake because meat eaters tended to also eat more sea vegetables than average. The reason I want to look at schistosomiasis is simple: It has some crazy-high correlations with colorectal diseases.

POSITIVE CORRELATIONS (more schistosomiasis infection = more of these diseases)

Rectal cancer: +88***
Colorectal cancer: +89***
Colon cancer: +72***
Brain cancer: +36

Holy moly, right? And I came across more than a few articles like this:

Chronic infection with schistosomiasis has been clearly associated with the development of bladder cancer, and infestation is associated with a high incidence of colorectal cancer in endemic populations.

What would happen if we only looked at meat consumption and colorectal cancers in counties that weren’t infected with schistosomiasis? We’d have a clearer picture of what meat’s role in these diseases are. Time to roll up our sleeves and do some correlation-untangling!

Here are three graphs using only counties that had a 0% rate of schistosomiasis infection:

Poof! There goes any semblance of a positive correlation between meat and colorectal cancers. In fact, our new correlations are a surprising -38.5 for rectal cancer, 0.03 for colon cancer, and -24.4 for all colorectal cancers. The trend is pretty much neutral for colon cancer, but for rectal cancer, meat almost looks protective.

At any rate, it seems meat categorically evades the crimes Campbell indicts it for—heart disease, cancer, and the like—within the scope of the China Project data. A little surprising, huh?

Next up, I’ll be looking at non-meat forms of animal products: fish, eggs, and dairy. Do these suckers cause disease? Do they cure all ills? Or are they totally irrelevant in the grand scheme of things? These answers and more, coming up!