Archive for the ‘Uncategorized’ Category

Ferdinand I. Charm, Piltdown, UK

The bizarre behavior of the medical nutritional establishment in recent years has caused critics to see an analogy with the Federal government. The continued influx of low-carb researchers across the borders of traditional medicine has caused a strong backlash which, in turn, has led to  accusations of a breakdown of style and even financial misdeeds. A key issue was a paper by Sarah Seidelmann, MD, a cardiologist with no experience in nutrition and her coworkers at Harvard School of Public Health and the associated Brigham and Women’s hospital.  The article claimed that the increasingly popular low-carbohydrate diets were actually life-threatening. Apparent communication between the authors and a Norwegian-based vegetarian pressure group called EAT-Lancet led to investigation by the so-called Moola Committee. The committee was concerned that Dr. Walter Willett of Harvard, one of the authors on Seidelmann, et al., was also a co-chairman of a recent EAT-Lancet commission and had been present at various meetings with foreign nutritional powers. It was revealed today, however, that the Moola Investigation did not find evidence of collusion with Norway or other nations.

Willett is a widely respected nutritionist and co-developer of the Hu-Willett  theorem: for any meat-containing diet and any disease state. there exists at least one finite set of confounders such that the diet can be shown to cause the disease. 

Seidelmann, et al. was generally considered to be a reflection of the long-standing attempts of the medical establishment to build a wall to keep low-carbohydrate diets from patients with diabetes and obesity. The authors denied such hostile intent and emphasized the fundamental scientific importance of their publication. “This work provides the most comprehensive study of carbohydrate intake that has been done to date,” was the description by the principle author, another cardiologist, Scott Solomon, MD, in social media in a style that has come to be called Presidential.“It’s a really terrific study. You’re gonna’ love it. It’s really terrific.” The Moola committee considered that this was not accurate and the study was really obstructing investigation into the real science. 

Scott Solomon, MD. Nobody has ever done a more comprehensive study.

The issue was not carbohydrate intake — none was measured. In fact, no low-carbohydrate diets were studied at all. The data were extracted from a different study about atherosclerosis. There was, however, a comprehensive questionnaire about what subjects had been eating at two time points many years apart. The results were quite surprising in that low-carbohydrate diets and high-carbohydrate diets were a risk. Only the 50 %. level characteristic of the US population diet during the obesity epidemic was beneficial. This paradoxical recommendation to do nothing, in combination with the failure to cite major benefits of carbohydrate restriction in the literature, was further evidence of obstruction, however passive.

The website says that “EAT is a bite-sized organization with an outsized appetite for impact,” reflecting the sense of humor for which Norway is famous. Among the insights: “Packing leftovers into lunch boxes, using them in new creative recipes or keeping them for future consumption is good for the planet.” The EAT-Lancet commission explains that it is flexible in its recommendations “There is something for everyone across price ranges, cultures, age groups and individual preferences” although it is important “to consume no more than 98 grams of red meat (pork, beef or lamb), 203 grams of poultry and 196 grams of fish per week.”

The highlighted section is about 98 grams.

The Moola investigators were concerned that Willett’s presence on the EAT-Lancet governing board might be a conflict of interest. That authors are charged $ 5,000 to publish in Lancet Public Health also raised questions about financial impropriety. Because the study was funded by the NIH, it seemed that American tax payers were giving money to a pressure group whose roots appear to be in foreign countries.

Walter Willett, MD. Looks like Wyatt Earp but not a straight-shooter.

In the end, the Investigation knew some bucks were involved but couldn’t figure out what had happened at all but decided it wasn’t collusion. They couldn’t understand, though, how the Lancet, supposedly an independent medical journal could be tied to a political lobby group and worried that this might represent obstruction of science. This was the general reaction in the scientific community and wits on the internet suggested the journal change its name to Slants-it

Dr. Richard Feinman of SUNY Downstate Medical Center, author of the expose Nutrition in Metabolism, was one of many critics who claimed that the Seidelmann paper could not have received peer review. He was told by Dr. Audrey Ceschia, editor of Lancet Public Health that he simply did not understand the contemporary concept of Editor-Based-Medicine. 

“These kinds of epidemiological studies with such low relative risk are, of course, meaningless,” Feinman said. The relative risk for “low-carb” vs. control was so close to 50-50 that, as he further explained: “it means just what fifty per cent chance of rain, means. It means you know just what you knew before you turned on the radio.” Oddly, Feinman took a positive point of view of things: “overall the low-carb-deniers have done a good job. Science is a human activity and so there are no precise definitions, but a good start: ‘What you do in science is you make a hypothesis and then try to shoot yourself down.’ Som the obsessive compulsive mission of the medical establishment to find something, anything, wrong with low-carb diets and their failure to come up with any risk, anything at all, means that low-carb diets are about the healthiest change you can make in your life-style.” Of course, there are always individual exceptions. Recently, after fifty years of scientific studies of low-carb diets without significant side-effects, a couple of unnamed, unidentified women were reported to have said — not a scientific study — that their low-carb diet gave them vaginal odor. The low-carb-deniers grabbed their story and it was blown all over the media including serious outlets like Forbes. (No women were identified and the story appears to have been invented by Edelman, a public relations firm although their client remains unknown).

The Moola Investigation is reportedly considering other potential obstruction of science cases. There is a consistent pattern, according to the investigators. to bring back “concerns” about health which have been widely discredited. Most recently, and most charming for its retro style, eggs and cholesterol, have come out of retirement following reports from yet another 50 % chance of rain study. Other likely attempts are to bring back the food pyramid which will now be used to store ever more grain. 

In a story in The Guardian, Seidelmann said “the team had published a substantial body of work ‘to thoroughly answer a question and not simply provide just one piece of the picture.’” Feinman admitted that it was the most substantial body of work on low-carbohydrate diets that did not study any low-carbohydrate diets.

All are eager to see the final Moola report.

We have a good deal of enthusiasm in the keto/paleo/low-carb community. We have the real sense that we can we use carbohydrate restriction to take advantage of the characteristic metabolic features of cancer — inflexible reliance on glucose. Enthusiasm may have outstripped the data, however, and several groups are trying to fill the gap. The barrier rests with the difficulty for anybody to obtain funding from NIH or other major government or private agencies. On top of this looms the long-standing resistance to low-carbohydrate diets making things particularly difficult. Our group is carrying out some good experiments and we employ a dedicated technician and we can efficiently use limited funds. Your backing can help.  A $ 15 donation gets us several days of supplies for the in vitro experiments that provide the biochemical underpinnings for attacking cancer in the clinic. Our project at experiment.com provides background, a place for discussion and reports from the lab.

The current metabolic point of view in cancer — emphasizing flexibility of fuel choices —  derives from renewed interest in the Warburg effect. Warburg saw that many cancer cells were producing lactic acid, the product of glycolysis. In other words, the tumors were not using the more efficient aerobic metabolism even when oxygen was present in the environment. The tumor cell’s requirement for glucose suggests the possibility of giving the host an advantage by restricting carbohydrate and offering ketone bodies as an alternative fuel.constant_ATP_UCP2

We showed previously that we could inhibit the growth of 7 different cancer cell lines and repress the production of ATP (the”‘energy molecule” in cell culture by adding acetoacetate (one of the ketone bodies) to the medium.  Control normal cell lines were not affected. In addition, we showed that ATP reduction was associated with the level of a molecule called uncoupling protein-2 (UCP-2).  I explain in other posts what “uncoupling” means and how it figures into energy efficiency. First, the big picture..

What is the context of inhibition by ketone bodies ?
The real context, of course, is human cancer. Our 28 day pilot human trial of 10 subjects with advanced cancers on a very low carbohydrate ketogenic diet (KD) was published in Nutrition (Elsevier) in 2012.  A small study — nominally just to show safety and feasibility, it was nonetheless well received. Of note, is that we found that those patients with the greatest extent of ketosis had stable cancers or partial remission, while those with the least ketosis showed continued progressive cancer. Despite a favorable editorial and the Metabolism Award from the journal. Unfortunately, our proposal to scale up to 65 patients was rejected by the NIH/NCI which we find very discouraging perhaps related to a commitment to drug therapy. In any case, we appeal now for help in supporting dietary cancer research.
You can help. To donate:  Our project ia at experiment.com

Following up from chapters in The World Turned Upside Down, I will try to provide a guide to getting through the medical literature. I will talk about relative risk first with an excerpt from the book and a quick way to get a feel for what relative risk really is.

It has been frequently pointed out that to succeed at major league baseball all you have to do is screw up no more than 70 % of the time. In fact ,it is almost 75 years since someone was able to come up with a failure rate as low as 60 %. (Ted Williams hit .406 in 1941). The point is that statistics is about interpretation. It is how you describe things. As in Paulos’s Once Upon a Number, mathematics and especially statistics is a story, and how you tell it.  The potential for being misled is obviously great. The idea that statistics is a cut-and-dried standard set of manipulations into which you pour your data and from which you are automatically given significance, importance and truth, is one of the major components in the failure of the medical nutrition literature. (more…)

Mayor-Bloomberg-The-Littlest-Dictator--99309

My comments in answer to Jonny Bowden’s Huffington Post take on the sugar tax where he suggested that despite it’s flaws, “it’s all we’ve got.” I insisted that It’s not all we’ve got. We have the science and, in one afternoon, Bloomberg could convene a panel of scientists to evaluate presentations by all the players including me who believe that sugar is a smokescreen for not facing the importance of total carbohydrate restriction which you [Jonny Bowden], among others, have explained. Everybody should be heard. What I see is another rush to judgement like the low fat fiasco which we still have with us.

That you “have to do something” comes right out of Senator McGovern’s mouth as in Fat Head. And “deadly white substance that literally creates hormonal havoc and appetite dysregulation … promoting metabolic syndrome, diabetes, obesity and heart disease” is way outside of the bounds of science. I am not the only one to point out that Lustig’s population study represented the return of Ancel Keys.

We go with science or we don’t.

(more…)

First published in October of 2011, this post announced a Q&A on line with Harvard’s Eric Rimm to answer question about the School of Public Health’s new  “Healthy Eating Plate,” its own version of nutritional recommendations to compete with the USDA’s MyPlate. A rather  limited window of one hour  was allotted for the entire country to phone in our questions.  Unfortunately HSPH was not as good at telecommunications as it is at epidemiology and the connection did not start working for a while.  The questions that I wanted to ask, however, still stand and this post is a duplicate of the original with the notice about the Q&A removed.  Harvard has been invited to participate in a panel discussion at the Ancestral Health Symposium, and we will see how these questions can be answered.

— adopted from Pops (at Louder and Smarter), the anonymous brilliant artist and admitted ne’er do well.

One of the questions surrounding USDA Nutrition Guidelines for Americans was whether so-called “sunshine laws,” like the Freedom of Information Act, were adhered to. Whereas hearings were recorded, and input from the public was solicited, there is the sense that if the letter of the law was followed, the spirit was weak.  When I and colleagues testified at the USDA hearings, there was little evidence that their representatives were listening; there was no discussion. We said our piece and then were heard no more.  In fact, at the break, when I tried to speak to one of the panel, somebody came out from backstage, I believe unarmed, to tell me that I could not discuss anything with the committee.

Harvard School of Public Health, home of  “odds ratio = 1.22,” last month published their own implementation of the one size-fits-all approach to public nutrition, the”Healthy Eating Plate.”  Their advice is full of  “healthy,” “packed with” and other self-praise that makes this mostly an infomercial for HSPH’s point of view. Supposedly a correction of the errors in MyPlate from the USDA, it seems to be more similar than different. The major similarity is the disdain for the intelligence of the American public. Comparing the two plates (below), they have exchanged the positions of fruits and vegetables.  “Grains” on MyPlate is now called “Whole Grains,” and “Protein” has been brilliantly changed to “Healthy Proteins.”  How many NIH grants were required to think of this is unknown.  Harvard will, of course, tell you what “healthy” is:, no red meat and, of course watch out for the Seventh Egg.

 

 

 

 

 

 

 

So here are the  questions that I wanted to ask:

  1. Dr. Rimm, you are recommending a diet for all Americans but even within the pattern of general recommendations, I don’t know of any experimental trial that has tested it.  Aren’t you just recommending another grand experiment like the original USDA recommendations which you are supposedly improving on?
  2. Dr. Rimm, given that half the population is overweight or obese shouldn’t there be at least two plates?
  3. Dr. Rimm, I think the American public expects a scientific document.  Don’t you think continued use of the words “healthy,” “packed with nutrients,” makes the Plate more of  an informercial for your point of view?
  4. Dr. Rimm, the Plate site says “The contents of this Web site are not intended to offer personal medical advice,” but it seems that is exactly what it is doing. If you say that you are recommending a diet that will “Lower blood pressure; reduced risk of heart disease, stroke, and probably some cancers; lower risk of eye and digestive problems,” how is that not medical advice?  Are you disowning responsibility for the outcome in advance?
  5. Dr. Rimm, more generally, how will you judge if these recommendations are successful? Is there a null hypothesis? The USDA recommendations continue from year to year without any considerations of past successes or failures.
  6. Dr. Rimm, “healthy” implies general consensus but there are many scientists and physicians with good credentials and experience who hold to different opinions. Have you considered these opinions in formulating the plate? Is there any room for dissent or alternatives?
  7. Dr. Rimm, the major alternative point of view is that low-carbohydrate diets offer benefits for weight loss and maintenance and, obviously, for diabetes and metabolic syndrome. Although your recommendations continually refer to regulation of blood sugar, it is not incorporated in the Plate.
  8. Dr. Rimm, nutritionally, fruits have more sugar, more calories, less potassium, fewer antioxidants than vegetables.  Why are they lumped together? And how can you equate beans, nuts and meat as a source of protein?
  9. Dr. Rimm, looking at the comparison of MyPlate and your Plate, it seems that all that is changed is that “healthy” has been added to proteins and “whole” has been added to grains.  If people know what “healthy” is, why is there an obesity epidemic? Or are you blaming the patient?
  10. Dr. Rimm, you are famous for disagreeing on lipids with the DGAC committee yet your name is on their report as well as on this document is supposed to be an alternative.  Do we know where you stand?
  11. Dr. Rimm, the Healthy Plate “differences” page says “The Healthy Eating Plate is based exclusively on the best available science and was not subjected to political and commercial pressures from food industry lobbyists.” This implies that the USDA recommendations are subject to such pressures.  What is the evidence for this? You were a member of the USDA panel. What pressures were brought to bear on you and how did you deal with them
  12. Dr. Rimm, the Healthy Plate still limits saturated fat even though a study from your department showed that there was, in fact, no effect of dietary saturated fat on cardiovascular disease.  That study, moreover, was an analysis of numerous previous trials, the great majority of which individually showed no risk from saturated fat. What was wrong with that study that allows you to ignore it?

*Medicineball, (colloq) a game that derives from Moneyball, in which an “unscientific culture responds, or fails to respond, to the scientific method ” in order  to stay funded.

A guide for consumers and the media

For Mark Twain’s hierarchy of lies, damned lies and statistics, we should really add epidemiological lies, those reports showing that brown rice or trans-palmitoleic acid will prevent diabetes and diet soda will make you fat, which appear every week or so in ABCNews.  (I mean the generic media, but ABCNews and I have a close relationship: sometimes they even print what I tell them).  If you’ve been eating white rice instead of brown rice and you develop diabetes ten years later, it is the fault of your choice of rice. Everybody knows that this is ridiculous but the data are there showing an almost 4-fold increased risk, so how can you argue with the numbers.

These kinds of studies are always based on associations and the authors are usually quick to tell you that association doesn’t mean causality even as they interpret the data as a clear guide to action (“Substitution of whole grains, including brown rice, for white rice may lower risk of type 2 diabetes.”)   In fact, to most scientists, association can be a strong argument for causality.  That is not what’s wrong with them. Philosophically speaking, there are only associations.  All we really know is that there is a stream of particles and there is an association between the presence of a magnet and the appearance of a spot on a piece of photographic paper (anybody remember photographic paper?).  God does not whisper in your ear that the particle has a magnetic moment.  It is the strength of the idea behind the association and the presentation of the idea that determines whether the association implies causality.  What most people really mean is that “association does not necessarily imply causality.  You may need more information.” What’s wrong with the rice story is that the idea is lacking in common sense.  The idea that the type of rice you eat has any meaningful impact by itself, or even whether one can guess whether it has a positive or negative impact on a general lifestyle, is absurd.  But what about the statistics? Here the problem is really presentation of the data.  The number of papers in the literature pointing out the errors in interpretation of statistics is very large although it is still less than the number of papers making those errors.  There are numerous problems and many examples but let’s look at the simplest case: limitations of reporting relative risk and alternatives.

images-1Here’s a good example cited in a highly recommended popular statistics books, Gerd Gigerenzer’s “Calculated Risks.” He discusses a real case, the West of Scotland Coronary Prevention Study (WOSCOPS) comparing the statin drug, pravastatin to placebo in people with high cholesterol.  The study was started in 1989 and went on for about 5 years.  (These days, I think you can only compare different statins; everybody is so convinced that they are good that a placebo would be considered unethical):

1. First, the press release: “People with high cholesterol can rapidly reduce… their risk of death by 22 per cent by taking…pravastatin.”

2. Now, ask yourself what this means? If 1000 people with high cholesterol take pravastatin, how many people will be saved from a heart attack that might have otherwise killed them?  Think about this, then look at the data, the data that should have  been reported in the media.

3. The data:

Treatment        deaths during 5 years (per 1000 people with high cholesterol)

pravastatin             32

placebo                  41

Right off, it doesn’t look as good as you might have thought.  Overall, death from a heart attack is a major killer, but if you take a thousand people and watch them for five years, not that many people die from a heart attack. Now there are three standard ways of representing the data.

4. Data presentation – Relative risk reduction.

Risk is the number of cases divided by total number of people in the trial (or risk per total number). So you calculate a risk for 1000 people on the drug = 32/1000 = 03.2 % and similarly for people on the statin. Risk reduction for comparing treatments is\ the difference between the two risks.  The relative risk reduction here  is just the reduction in risk divided by the risk for the placebo:

Risk reduction (number of people saved per thousand)  = 41-32 = 9. Saving 9 lives doesn’t sound that great but lets get the per cent as reported.

Relative risk reduction = 9/41 = 22 % as indicated, and it does sound like a big deal but there are other ways to look at the data.

5.  Data presentation – Absolute risk reduction.  Again, you start with risk, the number of cases divided by total number but you calculate the actual fraction.  The absolute risk reduction is the difference between these two fractions.

For pravastatin, risk = 32/1000

For placebo, risk = 41/1000

Absolute risk reduction = (41/1000) – (32/1000) = 9/1000 = 0.9 % (less than 1 %)

6.  Data presentation – Number needed to treat (NNT): This is a good indicator of outcomes.  If you treat 1000 people, 9 will survive who might have otherwise died. So,

number that you have to treat  to save one life = NNT  =  1000/9 = 111 people .

7. Conclusion: 22 % risk reduction is true enough but it seems like it didn’t really tell you what you want to know.  Cutting to the chase, would you take a statin if you had high cholesterol (more than about 250 mg/dl) and, as in WOSCOPS, no history of heart attacks. On the basis of this study alone, it’s not clear.  First, the risk is low.  There is clearly a benefit but how predictable is that benefit?  In the study, 99 % of the people had no benefit.  Of course, if you are the one out of a hundred, the drug would be a good thing.  The question is not easy to answer but the point of what’s written here is that the statistics as reported in the media might have led you to jump to conclusions.  Before you jump, though, you might ask about side-effects.  This is a complicated subject because although the side-effects are rare, their incidence is not zero and they can be severe but this post is only about the statistics.


Stepping back and looking at the recent scientific literature, I am struck with how life is a miracle.  How could humans have evolved in the face of threats from red meat, from eggs, even from the dangers of shaving?  (If you write about nutrition you have to create a macro that types out “I’m not making this up:” the Caerphilly Study [1] shows you the dangers of shaving… or is it the dangers of not shaving?).  With 28% greater risk of diabetes here, 57 % greater risk of heart disease there how could our ancestors have ever come of child-bearing age?  With daily revelations from the Harvard School of Public Health showing the Scylla of saturated fat and the Carybdis of sugar between which our forefathers sailed, it is amazing that we are here.

These studies that the media writes about, are they real?  They are certainly based on scientific papers.  If the media is not always able to decipher them, reporters do generally talk to the researchers. And the papers must have gone through peer review and yet many actually defy common sense.   Can the medical literature have such a high degree of error?  Could there be a significant number of medical researchers who are not doing credible science?  How can the consumer decide?  I am going to try to answer these questions.  When people ask questions like “could the literature be wrong?,” the answer is usually “yes” and I will try to explain what’s wrong and how to read the nutritional literature in a practical way. I am going to try to make it simple.  It is science, but it is pretty simple science.  I am going to illustrate the problem with the example of a paper by Djoussé [2].  But first, a joke.

It was a dumb joke. In my childhood, there was the idea, probably politically incorrect, that Indians, that is, Native Americans, always said “how” as a greeting.  The joke was about an Indian with a great memory who is asked what he had for breakfast on New Years day the previous year.  He says “eggs.”  They are then interrupted by an earthquake or some natural disaster and the interviewer and the Indian don’t meet again for ten years.  When they meet, the interviewer says “how.”  The Indian answers “scrambled.”

If the interviewer had been an epidemiologist he might have asked if he had developed diabetes.   Djoussé, et al. [2] asked participants about how many eggs they ate and then ten years later, if they developed diabetes it was assumed to be because of the eggs.  Is this for real?  Do eggs cause changes in your body that accumulate until you develop a disease, a disease that is, after all, primarily one of carbohydrate intolerance?  The condition is due either to the inability of the pancreas to produce insulin in response to carbohydrate (type 1) or to impaired response of the body to the insulin produced and a deterioration of the insulin-producing cells of the pancreas (type 2).  Common sense says that there is something suspicious about the idea that eggs would play a major role.  It is worth trying to understand the methodology and see if there is a something beyond common sense, and whether this is a problem in other studies besides   Djoussé’s.

What did the experimenters actually do.  First, people were specifically asked “to report how often, on average, they had eaten one egg during the past year,” and “classified each subject into one the following categories of egg consumption: 0, < 1 per week, 1 per week, 2-4 per week, 5-6 per week, and 7+ eggs per week.”  They collected this data every two years for ten years.  With this baseline data in hand they then followed subjects “from baseline until the first occurrence of a) type 2 diabetes, b) death, or c) censoring date, the date of receipt of the last follow-up questionnaire” which for men was up to 20 years.  Thinking back over a year: is there any likelihood that you might not be able to remember whether you had 1 vs. 2 eggs on average during the year?  Is there any possibility that some of the men who were diagnosed with diabetes ten years after their report on eggs changed their eating pattern in the course of ten years?  Are you eating the same food you ate ten years ago?  Quick, how many eggs/week did you eat last year?

Reading a scientific paper: the Golden Rule.

Right off, there is a problem in people reporting what they ate but this is a limitation of many nutritional studies and, while a source of error, it is depends on how you interpret the data.  All scientific measurements have error.  It is not a matter of ignoring the data but rather not interpreting results beyond measurement.  So, here’s how I read a scientific paper.   First, I look for the pictures.  What? A professor of biochemistry looks for the pictures first?  In a scientific paper, of course, they are called figures but it’s not just saving a thousand words.  (I get a thousand emails every couple of weeks). It’s about presentation of the data.

The principle is that a scientific paper is supposed to explain. The principle is laid out in what I call the golden rule of scientific papers.  It comes from the Book PDQ Statistics by Geoffrery Norman and David Streiner.  PDQ stands for Pretty Darned Quick and some of the humor is pretty sophomoric (e.g. it has Convoluted Reasoning or Anti-intellectual Pomposity detectors) but it is an excellent introductory statistics book.  Here’s the Golden Rule:

“The important point…is that the onus is on the author to convey to the reader an accurate impression of what the data look like, using graphs or standard measures, before beginning the statistical shenanigans.  Any paper that doesn’t do this should be viewed from the outset with considerable suspicion.”

— Norman & Streiner, PDQ Statistics [3]

In other words: teach.  Make it clear.  Eye-balling Djoussé, et al., we see that there are no figures.     A graph of number of eggs consumed vs number of cases of diabetes is what would be expected of the golden rule.  The results, instead are stated in the Abstract of the paper as the following mind-numbing statistics. (You don’t really have to read this)::

“Compared with no egg consumption, multivariable adjusted hazard ratios (95% CI) for type 2 diabetes were 1.09 (0.87-1.37), 1.09 (0.88-1.34), 1.18 (0.95-1.45), 1.46 (1.14-1.86), and 1.58 (1.25-2.01) for consumption of <1, 1, 2-4, 5-6, and 7+ eggs/week, respectively, in men (p for trend <0.0001). Corresponding multivariable hazard ratios (95% CI) for women were 1.06 (0.92-1.22), 0.97 (0.83-1.12), 1.19 (1.03-1.38), 1.18 (0.88-1.58), and 1.77 (1.28-2.43), respectively (p for trend <0.0001).”

What does all this mean? I will just state what the statistics mean because it is worth considering the conclusion as stated by the authors.

The meaning of the statistics is that there was no risk of consuming 1 egg/week compared to eating none.  Similarly, there was no risk in eating 2-4 eggs/week or 5-6 eggs/week.  But when you up your intake to 7 eggs or more per week, that’s it.  Now, you are at risk for diabetes.  The relative risk is small but there it is. You are now at greater risk.

Since I like pictures, I will try to illustrate this with a modified still from the movie, The Seventh Seal directed by Ingemar Bergman.  Very popular in the fifties and sixties, these movies had a captivating if pretentious style: they sometimes seemed to be designed for Woody Allen’s parodies.  One of the famous scenes in The Seventh Seal is the protagonist’s chess game with Death.  A little PhotoShop and we have a good feel for what happens if you go beyond 5-6 eggs/week.

 

1. Ebrahim S, Smith GD, May M, Yarnell J: Shaving, coronary heart disease, and stroke: the Caerphilly Study. Am J Epidemiol 2003, 157(3):234-238.

2. Djoussé L, Gaziano JM, Buring JE, Lee IM: Egg consumption and risk of type 2 diabetes in men and women. Diabetes Care 2009, 32(2):295-300.

3. Norman GR, Streiner DL: PDQ statistics. 3rd edition. Hamilton, Ont.: B.C. Decker; 2003.