Pretty funny, eh? But according to the latest health scare, our bacon-loving lady could be on her way to an early grave. Here’s the headline:
Eating Animal Fat May Lead to Pancreatic Cancer
Oh my gosh! I eat a lot of animal fat … I can feel my pancreas swelling up with tumors as I write. I’ve been issued a death sentence, and I know it’s accurate because – hold onto your seats, now – the article included the magic words study finds right there in the sub-headline.
And what an amazing study this has turned out to be. So far it has indicated that being overweight in middle age will kill you, a lack of physical activity can increase your odds of breast cancer, red meat will give you colon cancer, alcohol can lead to pancreatic cancer and fruits and vegetables may protect against lung cancer … uh, but only in men. The study also achieved the amazing feat of indicating that dietary fat may lead to breast cancer – but red meat doesn’t.
Considering how many headlines this study has already produced – with more sure to follow – I’m going to suggest you memorize the name: The NIH-AARP Diet and Health Study. I’m also going to suggest that when you spot an article that cites this study, you bookmark it, download it, print it, and then use the pages to paper-train a puppy.
NIHARP (my shorthand) is one of those big, expensive studies that enables researchers to analyze data, publish research papers, give speeches, and otherwise pay their mortgages for years without ever seeking another grant. In fact, as the media likes to repeat over and over, this is THE LARGEST STUDY OF ITS KIND.
Wow, that must mean we’re looking at some rock-solid science here, right? Hardly.
Because NIHARP is typical in many ways of the studies that scared people away from fat, it’s worth taking a closer look. I downloaded quite a few study documents, including the original food survey, and I’ll try to explain the weaknesses of studies like this while keeping the statistical geek-speak to a bare minimum.
My girls have recently become huge fans of The Sound of Music. So, as the song says, let’s start from the very beginning …
Throughout 1995 and 1996, the investigators mailed a food-frequency questionnaire to 3.5 million members of the American Association of Retired Persons, all aged 50 to 69, who lived in six states (California, Florida, Pennsylvania, New Jersey, North Carolina, Louisiana), plus two metro areas (Detroit and Atlanta.) The authors said they chose these areas because they have high concentrations of retired people. I’m guessing that if people retired in California or Florida, it was for the weather, whereas if they retired in Detroit, they couldn’t afford to move.
Here’s the first big problem with the study (the largest of its kind!): the survey itself. In order to determine what people eat, the investigators sent them a list of 120 foods and asked them to answer questions like this:
Over the last 12 months, how often did you eat the following foods? (Ignore any recent changes.)
Whole milk (4%), NOT in coffee, NOT on cereal: Never | 1-6 per year | 7-11 per year | 1 per month | 2-3 per month | 1-2 per week | 3-4 per week | 5-6 per week | 1 per day | 2-3 per day | 4-5 per day | 6+ per day. Portion size: less than ½ cup | ½ to 1 cup | more than 1 cup.
Breads or dinner rolls, NOT INCLUDING ON SANDWICHES: Never | 1-6 per year | 7-11 per year | 1 per month | 2-3 per month | 1-2 per week | 3-4 per week | 5-6 per week | 1 per day | 2-3 per day | 4-5 per day | 6+ per day. Portion size: less than 1 slice or roll | 1 or 2 slices or rolls | more than 2 slices or rolls.
Mayonnaise or mayonnaise-like salad dressing on bread: Never | 1-6 per year | 7-11 per year | 1 per month | 2-3 per month | 1-2 per week | 3-4 per week | 5-6 per week | 1 per day | 2-3 per day | 4-5 per day | 6+ per day. Portion size: less than 1 teaspoon | 1 to 3 teaspoons | more than 3 teaspoons.
Ground beef in mixtures such as tacos, burritos, meatballs, casseroles, chili, meatloaf: Never | 1-6 per year | 7-11 per year | 1 per month | 2-3 per month | 1-2 per week | 3-4 per week | 5-6 per week | 1 per day | 2-3 per day | 4-5 per day | 6+ per day. Portion size: less than 3 ounces | 3 to 7 ounces | more than 7 ounces.
Could you answer a survey like that accurately? I couldn’t. In fact, I didn’t. When I was working for the National Safety Council, some genius in management decided everyone in the company should fill out a survey like this one. On a whole lot of the questions, I needed a box labeled “I have no freakin’ idea.” But there wasn’t one. So I did what all my pals at work did: I guessed.
And I was 25 years old, not 65. My memory was sharp then and it still is, but I couldn’t tell you what I ate last Tuesday, never mind last February. Of the nearly 3 million people who received the NIHARP survey but didn’t return it, how many do you suppose looked it and mumbled, “I have no freakin’ idea,” then tossed it in the trash?
But around 600,000 people did return the survey, which leads to the second problem: this is a self-selected group that doesn’t mirror the general population.
In the baseline data, it’s obvious that compared to the general population, the survey group is far more likely to be white (over 90 percent), well educated, and non-smoking. The authors admitted they were concerned about the low response rate (about 17 percent), but managed to discern that “a shifting and widening of the intake distributions among respondents compensated for the less-than-anticipated response rate.”
In other words, they declared this cross-section of the population varied enough for a study and decided to keep going. (Gotta pay that mortgage, you know.)
Here’s the third problem: the self-selected group was winnowed down even further by the investigators. Yes, it’s common practice to try to dump incomplete or suspicious data, but in explaining how they determined if a survey was sufficiently complete, they stated, “In calculating our initial cohort sample size of 350,000 we focused on a single nutrient, dietary fat.”
Hmmm … sounds to me like they already had an opinion about which nutrient would wind up being linked to cancer. If they could determine how much fat you ate, you were in. Why fat? Why not sugar, or white flour, or corn flakes?
Nearly ten years after the first survey, the authors mailed a similar questionnaire, along with others that asked about exercise, smoking and medications. Then they compared the respondents’ diets with their rates of various diseases, focusing primarily on cancer. That’s where they came up with all the crunchable numbers.
So how well do numbers like these crunch? That’s the fourth big problem: they don’t crunch very well. They’re more on the squishy side. In one of their many papers, here’s how the researchers evaluated the accuracy of their own food-intake data:
For the 26 nutrient constituents examined, estimated correlations with true intake (not energy-adjusted) ranged from 0.22 to 0.67 … When adjusted for reported energy intake, performance improved; estimated correlations with true intake ranged from 0.36 to 0.76.
So what does that statement mean? Here’s what a site that explains statistics in plain English has to say about correlation:
Correlations of less than 0.1 are as good as garbage. The correlation shown, 0.9, is very strong. Correlations have to be this good before you can talk about accurately predicting the Y value from the X value.
If you want to think of it visually, a correlation of 1.0 gives you a perfect trendline: if smoking absolutely, positively causes lung cancer and is absolutely, positively dose-dependent, then you could plot the number of cigarettes smoked per day against the incidence of lung cancer, and you’d get one of those lines that starts at zero in the lower left and zooms straight to the upper-right corner.
Correlation examples (courtesy Tony at www.EmotionsForEngineers.com)
But for this study, the estimated correlation (after being adjusted upwards) is between 0.36 and 0.76. In other words, the investigators themselves estimate that the accuracy of their food survey is somewhere between lousy and decent. Well, decent might be stretching it. The same analysis of their own study included this statement:
However, previous biomarker-based studies suggest that, due to correlation of errors in FFQs and self-report reference instruments such as the 24HR, the correlations and attenuation factors observed in most calibration studies, including ours, tend to overestimate FFQ performance.
So the lousy-to-decent estimate might be overestimated. Kudos to them for saying as much. And yet from this data, they’re going to look for correlations between diets and diseases and write a slew of research papers on what they find.
Which brings us to the fifth big problem: the associations you find when looking at data depend largely on the associations you seek. In a study like this, you gather a huge amount of data, then you ask the data some questions. How you ask the question affects the answer.
Some months ago, the researchers asked this data if there was an association between red meat and colon cancer, and wouldn’t you know it, the data answered “yes.” At least that’s the story that made the headlines. But the truth is, the question they asked went more like this: “Do people who eat a lot of steaks, hot dogs, hamburgers, sausage, pizza, cold cuts, bacon and deli sandwiches have a higher rate of colon cancer?”
Grouping all those foods together under the label “red meat” confounds the question – and it wasn’t necessary to confound the question. In the food survey, “steaks” is a separate item. If you really want to know if red meat causes cancer, why not simply ask, “Do people who eat a lot steaks have a higher rate of colon cancer?” Maybe they did ask that question. Maybe they didn’t like the answer, so they asked it again and included pizza and hot dogs.
Here’s another strange grouping: the food survey lumped butter and margarine together as a single food item. I nearly jumped out of my skin when I read that one. Talk about confounding the data! Butter is natural. Margarine is a processed frankenfood. The only similarity is that people spread them on toast. You may as well lump cigarettes and carrot sticks together because they have the same shape.
Even when researchers ask well-designed questions, there’s the “don’t ask, don’t tell” problem: there may be associations lurking in the data that no one is looking for. When Ancel Keys cherry-picked six countries and went looking for an association between fat and heart disease, he found it. But the same overall data showed a much stronger association between sugar and heart disease … and an even stronger association between television ownership and heart disease.
Which brings us to the sixth problem: Associations are only useful for providing clues. They don’t identify the cause. There’s a strong association between obesity and type II diabetes. Does that mean being fat causes diabetes? Nope. It could mean diabetes makes you fat. Or, more likely, it could mean obesity and diabetes are both caused by excess insulin. You get the idea.
Considering that the animal fat will kill you! message has been around for more than 30 years, it’s highly likely that people who eat a lot of pizza, hot dogs, hamburgers, bacon, sausage and deli sandwiches are the “non-adhering” types Dr. Mike Eades wrote about awhile back. (Or, as I call them, “people who don’t give a @#$%.”)
Those same people may also consume more sugar, more white flour, more high-fructose corn syrup, more cough syrup, etc. – which is not much of a stretch, when you consider that pizza, hot dogs, hamburgers and deli sandwiches are all served with a load of starch. But as far as I can tell, the NIHARP investigators aren’t asking questions about sugar and starch. So far, they seem interested in discovering that animal fat is dangerous, while fruits and vegetables will save your life.
The next time you see yet another paper from this study (the largest of its kind!) generate yet another round of alarmist headlines about the possible dangers of animal fats (and you will), keep this in mind about The NIH-AARP Diet and Health Study:
What we’re looking at is 1) a survey study with a low response rate that 2) required old people to accurately recall what they’d eaten in the past year (twice), which then provided data that is 3) almost certainly polluted by self-selection and confounding variables, and is 4) being analyzed by researchers who indicated from the beginning that their main concern is dietary fat, all for the purpose of 5) identifying associations, which don’t tell us very much anyway.
Other than that, it’s a fine piece of work. Now go fry up some bacon, and don’t worry about your pancreas. But try to avoid throwing the pan out the window.
(Hat tip to Mike Eades for Twittering the video. I nearly did a spit-take with my coffee.)
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Yay! Ads frim New Zealand are awesome. My vegetarian mother took umbrage at it, but that’s because her low-fat, high-starch diet has left her with no sense of humour. 🙂
I’ve actually gotten to the point now where I pay ZERO attention to anything that’s screamed from the newspapers or mainstream media. I know how I feel now that I eat plenty of tasty animals. I know how I felt on a vegetarian diet, too and I am never going back to that. Four years in I was considering therapy because I literally thought my ‘eating disorder’ was driving me crazy. I realise now that internally I was just starving and my body was sending out panic signals.
If eating deadly, deadly animal fats means I’m going to die of some horrific disease, so be it. At least I’m dying sane and satiated.
I’m with you. I would just ignore the all the “study finds blah blah blah” articles, but after wading through research for Fat Head, I can’t resist peeking behind the curtain to see whether or not there’s a real scientist standing there.
Go the Kiwi ad. Remember that on TV a while back.
NIHARP… NIJERK?
CSPI made it onto our TVs here today. A study showing how a persons arteries changed in real time when eating fatty foods. The three items? Deep fried macaroni and cheese, a quesedilla and a brownie with whipped cream. Yes, all fatty, but also all starchy/sugary. But no, all about the fat. There was nothing in the article about eating an only fatty (not starchy) meal or visa versa.
It seemed to be streamed from an American station, so I would imagine its been in your news as well. I expected to log on to find yourself or Dr Eades herniating at it…
I haven’t seen it yet. I don’t suppose CSPI is going to mention that heart attacks are far more likely to occur after a high-glycemic meal …
If the associations are qualified by the phrase “when adjusted for”, you can bet they’re less than worthless. As a statistical measure, correlation at least “is what it is”, a number that describes a particular statistical relationship with no assumptions. It just tells you something about your data (similar to the average value), without assuming anything about the underlying causal relationships amongst variables. “Adjustment”, on the other hand, does require some assumptions, probably that the relationship is linear, because that makes the math easier. Any adjusted numbers are thus polluted by the underlying assumptions, which almost certainly are vast oversimplifications, if not just plain wrong.
To put it another way: you can’t squeeze blood from a rock. Data contains a certain amount of information. It doesn’t matter how much you shake it up, the information content isn’t going to change. In other words, you can’t “adjust” the data and get “better” answers without adding information. If that added information isn’t other data, it must be assumptions (more technically, prior knowledge). There’s nothing wrong with including prior knowledge in your analysis; indeed, that’s how science should proceed (start with hypothesis, modify belief based on data). The problems occur when the assumptions are clearly bogus (like that of linear relationships amongst variables) and the existence and form of those assumptions is swept under the rug by use of an “accepted statistical procedure”.
The saddest part is that almost all scientists are clueless on this point. They are taught recipes from the statistics cookbook without ever really understanding the underlying math and questions for which those recipes can provide a mathematically valid answer. The recipes are blindly applied, and the sort of chaos described above ensues. It’s tragic in the sense that even basic common-sense reasoning is supplanted by statistical gobbledygook. And there’s nothing wrong with statistics per se, it’s just used wrong. But since almost everybody does it wrong, they all think they’re doing it right, even though a moment of rational thought would show it must be incorrect, or at least incomplete.
Math is beautiful, but like language, it can be used to create poetry or propaganda. Some scientists are definitely cluess, but I’m afraid some others understand the math quite well and intentionally twist it. Uffe Ravnskov has found some veeerrry interesting “adjustments” in research papers.
The journalists who write about medical issues are often beyond clueless when it comes to statistics. I can’t tell you how many times I read a headline like “Eating meat increases odds of colon cancer.” Most people read that and interpret it to mean eating meat is like adding extra bullets to the chamber before playing Russian roulette; i.e., meat CAUSES colon cancer in the same way cigarettes cause lung cancer, so the more of it you eat, the more you’re stressing your colon into developing tumors. Whereas the “increases odds” only means that in some study sample, there was a statistical assocation between eating meat and colon cancer — which could mean meat-eaters smoke more, drink more sodas, etc.
So since the wrong questions are being asked of the data, can’t we get some fat heads together and ask it the right questions? Build our own association of increased pizza = increased cancer? Or was pizza lumped with cold cuts and grass fed steak in the survey making that question impossible to answer?
Considering how they gathered it, I’m afraid it would be like asking a blind man to describe the local scenery. And I’m not sure they’re sharing the database with anyone before they can squeeze every possible publishable study from it.
Here’s one more from today….Carbs may supress tumor growth. http://www.sciencedaily.com/releases/2009/07/090706181449.htm
I guess that explains the near-total lack of cancer in our high-carb society. Here’s a perfect example of why people end up ignoring all the “study says” headlines: on the same page as “Carbohydrate Acts as Tumor Suppressor” there’s another headline, “High-Carb Diet Linked to Prostate Tumor Growth.”
The goofy thing about the fat/pancreatic cancer “connection” is that it goes against what we know about the associated biochemistry. Fat has little direct effect on the pancreas, though it does cause various hormones to be secreted that modulate insulin. Glucose, on the other hand, directly activate genes in the pancreas. Loads of refined carbs have a dramatic effect on the pancreas.
As for tumor growth, the following is known:
– Cancerous cells generally can only metabolize glucose.
– Said glucose is metabolized anaerobically, so they need LOTS.
– The only way to get that sugar into the cancer cell is via insulin-stimulated glucose transport.
So oodles of glucose and associated insulin sound like the recipe for cancer promotion (isn’t that the Warburg hypothesis?) The pancreas is necessarily exposed to very high levels of both on a refined carbohydrate diet.
The sugar/tumor growth referenced in the other article talks about more complex sugar molecules called glycans. I believe the body makes these, and they’re very different than typical dietary carbohydrate. Remember that “carbohydrate” is any molecule whose chemical formula can be expressed as some number of carbons and water molecules, and it’s a much broader family than the usual fructose/glucose etc. we generally focus on.
That’s why I believe if the researchers 1) had a way of truly measuring food intake accurately, and 2) bothered to look for links to something besides fat, they’d find that most cancers are linked to glucose-producing foods, not fatty foods. The “I don’t give a @#$%” non-adherers probably eat a lot of fat, a lot of sugar, a lot of starch, etc., but fat is getting the blame.
From the questions these researchers asked the study participants, it was clear they thought they already knew what the right answers to the questions were and they were just fishing for respondents to back them up.
The sad thing is that people concerned about their health who get their information from the mainstream media believe all these studies without question. I used to, before I discovered some very excellent bloggers who expose these studies for the junk science they really are. Studies such as this, and the reporting of them, are very useful in reinforcing a set of assimiliated–but wrong–commonplaces about what is healthful to eat. Now I just ignore any headlines that start out: “Study shows….” I can be sure said study either was designed poorly, interpreted incorrectly, or reported inaccurately, or, more likely, all of the above.
And it’s even worse when journalists write headlines such as “Eating Meat Increases Risk of Colon Cancer.” That sounds like a connection has been proved, along the lines of “Skiing increases risk of smashing into large trees,” but of course it’s nothing of the sort.
I loved the bacon video. Thanks for the laugh.
BTW, I started watching your Fat Head dvd; however, I watched it on a day I was off work sick, and fell asleep partway through it. Actually, I think I dozed off right about where the Drs. Eades were talking. Sigh. Anyway, what I saw I found fascinating, and eventually I’ll watch it on a day when I’m not likely to start snoring part way into it!
Good grief, we’re putting people to sleep! I hope that doesn’t happen the second time around.
@Tom,
It’s even stupider, because we know that fat tends to increase insulin secretion. This probably evolved in the context of eating meat, where it’s a good thing (you need insulin to get the fat and amino acids into your cells; amino acid absorption causes glucagon to be released, which helps keep your blood sugar stable in the absence of dietary carbs and presence of insulin). But fat and refined carbs is probably a real mess. The refined carbs trigger large insulin release as it is, and throwing fat on top of that probably just makes the situation worse.
So we might expect to see that correlation between fat consumption and cancer, given the composition of the modern diet. Unfortunately, it seems like the boobs who do these hand-waving observational studies don’t know any of this stuff.
@ethyl d,
Though it certainly seems like these scientists are fishing for ways to get a pre-supposed answer, I think in reality they’re probably just stupid. Well-intentioned, but too dumb to realize that their study design is biased towards a particular answer.
So it’s true that fat mixed with refined carbs is the “killer combination.” Think of all the foods that fall into that category: french fries, potato chips, desserts, take-out Chinese, donuts, a thousand varieties of sandwhiches, pizza, etc. No wonder diabetes is rampant.
I’d like to see someone request access to the database to do their own independent analysis – perhaps someone from the Nutrition and Metabolism Society. I don’t think it would be too difficult to estimate sugars, fructose or intake of carbohydrates in general, if they asked questions at all related to the diet as a whole. I highly doubt that the researchers could only get good estimates of fat intake from the data! If this study was funded by grant funds, they should be obligated to make the data available to the public – after all we paid for it. I’d really like to see what someone without a “fat is evil” bias would make of the data! At least report on ALL the data and not just single out dietary fat!
I’m not sure how people get ahold of research databases like this one, but yes, that would be an interesting study.
@Tom,
I don’t know if it’s true, because I don’t think it’s been directly tested in living people. But it seems a pretty good hypothesis based on the biochem. Can’t think of an instance in our evolution when we would have eaten quantities of carbs and fats simultaneously. Hunter-gatherer groups seem to be either/or, and will take fat if they can get it. The most glycemic naturally available food would be honey. So unless our ancestors made a practice of regularly fighting angry bees and dishing up brains topped with honey, I don’t think our genes would have been exposed much to this stimulus.
Copy of a letter/ email that I have sent to everybody I know….friends, family, colleagues, students, acquaintances, about GCBC and Fat Head.—
Hello Dear Ones and a book recommendation related to my mom’s health . July 2009 . My mother is 82 and losing her memory. She’s physically healthy and as pleasant as ever, which is nice- I guess. My frustration is that this was preventable – her vascular dementia. Hopefully the following information will be helpful to you, or intriguing or tick you off, but I’m aiming for some kind of reaction -and any will do. And, she’d probably be pleased to know her predicament could lead to some greater good.
Gary Taubes’ 2007 book, “Good Calories, Bad Calories” is what I’m hawking. If you have elderly relatives in your life, or if you eat, you want to read this book. Though I have recommended books to some of you before, until now, they’ve all just been fun or interesting ones. But this book literally changed my life and view of the conduct of science. I’m not exaggerating, even though some of you also know that I’m dramatic for effect in conversation!. I first laid hands and eyes on this important tome in June ’08. I sat and read it in two days because I could NOT put it down. In the year since, I have learned and read more and I’ve reached a critical mass…..thus the reason you hold this letter in your hand.. GCBC is a paradigm slayer. By now you might have ‘evil-nutrient’ witch-hunting fatigue, but I implore you to read it. Before Taubes, I had NO clue that there isn’t any research to support the current dogma that we should eat low-calorie and low- fat foods.
Your brain is 70% fat. Each membrane surrounding each one of your 100 trillion cells is composed of cholesterol and lipid and I’ve calculated that the combined surface area of all these membranes is equivalent to two football fields! These membranes regulate all cellular processes and help sustain and maintain you. 50% of the weight of your cerebral cortex is cholesterol. My mom has spent her life trying to ‘eat right’. Instead of eating nourishing, fatty brain fuel, she ate a lot of altered, low-cholesterol, processed vegetable ‘Frankenstein Fats’. These were originally developed for the varnish, paint, putty, and candle industries. When new markets were sought and their addition to animal feed didn’t pan out, they were dumped into human chow – and claims they enhanced health began (and continue).
New neurons were thought to be created only in the developing fetus and newborn. Now we know that isn’t the only time we make them, but it also isn’t the most critical part of this story. It’s the interconnections between brain cells where the greatest potential lies and this seems to be a process that can continue, new connections being forged, throughout life. But high quality saturated animal FAT is a requirement if this is to occur. Prevention of dementia, or its retardation if it’s already begun, is my reason for writing this letter.
“The average brain consists of one hundred billion neurons . . . each neuron is connected to other neurons, usually one thousand to ten thousand others . . . the number of combinations possible exceeds the number of particles in the known universe” (Dr. Daniel Levitin, professor of psychology and neuroscience at McGill University and author of ‘This Is Your Brain on Music’). My opinion is that the brain is ‘plastic’ and can repair and regenerate itself and bypass damaged interconnections when necessary, but only if it’s properly fueled.
I hope I’ve grabbed your attention. Please refer to the following references list and PLEASE contact me if you do. I want to get something started. Wishing you High Fat Food For Thought from My Year of Reading Dangerously!
Talk by Gary Taubes at Grand Rounds, Dartmouth Medical June 2009 (journalists not usually invited to these……) http://www.dhslides.org/mgr/mgr060509f/f.htm
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“FAT HEAD” DVD by Tom Naughton
“My Big Fat Diet”, DVD Dr. Jay Wortman, Bare Bones Productions
FAT HEAD blog http://www.fathead-movie.com/index.php/2009/04/19/can-your-own-bologna-kill-you/
HYPERLIPID blog
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“The Eden Alternative”, Dr. William Thomas http://www.edenalt.org/
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‘Space Doc’, Duane Graveline, http://www.spacedoc.net/
‘Good Calories, Bad Calories’, Gary Taubes/”Trick And Treat”, Barry Groves/”Cereal Killer”, Alan Watson/”The Great Cholesterol Con”, Dr. Malcolm Kendrick/”Pure, White and Deadly”, J.Yudkin PhD/
“Sugar Blues”, William Dufty/”Primal Body- Primal Mind”, Nora Gedgaudas/”Nourishing Traditions”, Sally Fallon/”Know Your Fats”, Dr. Mary Enig/”The Vegetarian Myth”, Lierre Keith
In Science Is Veritas, Laurie
Great letter. I hope you change some minds out there.
This is a clip that was on the news here in Canada. Once again the blame is all on the Fat. http://watch.ctv.ca/news/health/lifetime-with-monica-matys/#clip191036
Would have been interesting to see what their results would be if the carbs had been cut from the meals.
I saw an article about CSPI’s latest bit of nonsense as well. There’s so much that’s ridiculous about this one, it may require a full post.
Hi Tom,
Nice post. Good breakdown on some of the many flaws in this study and approach in general.
I generated some sample corrrelations and put them up on Emotions for Engineers so people can see what they look like.
http://www.emotionsforengineers.com/2009/07/some-sample-correlations.html
It’s interesting to see what those correlation numbers really mean.
Cheers,
Tony
Great work, Tony. I knew the estimated correlations would produce a scattered distribution, but I didn’t know how to create a chart to demonstrate it visually. Would you mind if I insert one of those graphics into the original post for people who stumble on it later? (With credit, of course.)
Thanks. Feel free to use the graphs.
T
Of course the real problem here is red meat that’s been fed GRAINS, antibiotics and growth hormones. Just go for the Antibiotic free, hormone free, grass fed meat and all will be well.
Very good point. But given an either/or, I’ll eat the corn-fed cow before I’ll eat the corn.
Tom – thanks for doing this. These headlines seem to come out daily and while I am confident in the primal diet I’ve migrated to, I still occasionally get doubts from the onslaught. Your break down helps alleviate those (very minor) fears.
When you lump “hamburgers and bacon” in with pizza, deli sandwhiches, and hot dogs, I assume you mean standard processed (feedlot) burgers served on crap buns and drowned in HFCS ketchup and Oscar-Meyer-like-processed bacon…
Definitely. I can’t imagine anyone who goes to the effort to find steaks and burgers from grass-fed cows would also eat pizza and hot dogs.
I think the whole issue is that we are trying to mass produce stuff that should be grown in our own back yards. God didn’t create supermarkets! We weren’t created to live/work/play indoors all day in little cubicles, and eat foods that have traveled the world in boxes, and refrigerated trucks.
As someone who spends most of the day sitting down while programming software or writing, I agree. When I get out and move, my body is happier.