The  SBU (Swedish Council on Health Technology Assessment) is charged by the Swedish government with assessing health care treatments. Their recent acceptance of low-carbohydrate diets as best for weight loss is one of the signs of big changes in nutrition policy.  I am happy to reveal the next bombshell, this time from the American Diabetes Association (ADA) which will finally recognize the importance of reducing carbohydrate as the primary therapy in type 2 diabetes and as an adjunct in type 1.  Long holding to a very reactionary policy — while there were many disclaimers, the ADA has previously held 45 – 60 % carbohydrate as some kind of standard — the agency has been making slow progress. A member of the writing committee who wishes to remain anonymous has given me a copy of the 2014 nutritional guidelines due to be released next year, an excerpt from which, I reproduce below.

Nutrition Therapy Recommendations for the Management of Adults With Diabetes 

This position statement on nutrition therapy for individuals living with diabetes replaces previous position statements, the last of which was published in 2013 [1] and incorporated into the Standards of Medical Care of 2014 [2]. In particular, evidence suggests that the starting point for therapy for type 2 diabetes and adjunct treatment of type 1, should be some form of very low-carbohydrate diet. The amount of carbohydrates is the most important factor influencing glycemic response after eating and should be considered when developing the eating plan. Carbohydrate intake has a direct effect on postprandial glucose levels in people with diabetes and is the primary macronutrient of concern in glycemic management. While it is still recognized that there is not an ideal percentage of calories from carbohydrate for all people with diabetes, carbohydrate intake should be as low as possible for most people. 

There are several good references for implementation [3, 4] although the degree of reduction of dietary carbohydrate should be based on individualized assessment of current eating patterns, preferences, and metabolic goals. Collaborative goals should be developed with the individual with diabetes. For good health, any carbohydrate intake should come from vegetables, fruits, legumes, and dairy products rather than intake from other carbohydrate sources, especially those that contain high starch and sugar.  In recognizing the importance of removing carbohydrates, the current guidelines deviate from, and consider inappropriate, previous recommendations from 2008 [5] that “sucrose-containing foods can be substituted for other carbohydrates in the meal plan or, if added to the meal plan, covered with insulin or other glucose lowering medications.” While substituting sucrose-containing foods for isocaloric amounts of other carbohydrates may have similar blood glucose effects, it is now recommended that consumption should be minimized to avoid displacing nutrient-dense food choices.

Recommendations for low-carbohydrate diets.

The new recommendations emphasizing low-carbohydrate diets follow from the observations noted previously [5] that improvements in serum lipid/lipoprotein measures including improved triglycerides, VLDL triglyceride, and VLDL cholesterol, total cholesterol, and HDL cholesterol levels are now recognized as a reliable feature of lower-carbohydrate diet compared with higher carbohydrate intake levels. Through the collaborative development of individualized nutrition interventions and ongoing support of behavior changes, patients should understand the rationale of carbohydrate restriction and be made aware of its potential value.

Most important for clinicians is understanding results of two independent comparative studies from the laboratories of David Jenkins [6] and of Eric Westman [7] shown in Figure 1.

Fad_Westman_Jenkins_FigFigure 1. Comparison of High Cereal and Low Glycemic Index Diets and of Low Glycemic Index Diets and Low Carbohydrate Diets

The role of body mass in diabetes.  

More than three out of every four adults with diabetes are at least overweight, and nearly half of individuals with diabetes are obese. Because of the relationship between body weight (i.e., adiposity) and insulin resistance, weight loss has long been a recommended strategy for overweight or obese adults with diabetes. Two important experimental results bear on the new recommendations. First, in numerous trials, low-carbohydrate diets of one type or another out-perform other diets to which they are compared. No diet is better than carbohydrate restriction for weight loss. However, it has been shown that the features of both type 1 and type 2 diabetes are improved by low-carbohydrate diets even in the absence of weight loss.

Previous recommendations on nutritional therapy have failed to take account important work of Nuttall and Gannon who have clearly shown that the symptoms of type 2 diabetes can be improved without the requirement for weight loss [8-10].  Even under weight-maintenance conditions, dietary carbohydrate restriction dramatically improves glycemic control as well as HbA1c and lipid markers. This fact is important given the resistance that many individuals show to weight loss.  A series of papers from Nuttal and Gannon [8-10] measured many hormones and parameters in response to various carbohydrate-reduced diets. Although the percentage of carbohydrate differed in many of these studies, the most effective level of carbohydrate in improving the markers was the lowest level of carbohydrate used.  Results from one study from Nuttall and Gannon’s lab [10] are shown in Figure 2.  A low-carbohydrate (20% energy) diet was instituted for five weeks under conditions where weight was maintained. It is clear from the figure 24-hr integrated and postprandial glucose as well as hemoglobin A1c was improved after the five-week diet period (●) compared to performance before (▲).   These results contrast with outcomes from low-fat and calorie-restricted diets, which generally require weight loss for diabetes symptoms to improve. While the results have recently been extended to longer periods [8], it is important to recognize that nothing in the results contradicts the idea that benefit will continue to accrue as long as the diet is adhered to.

EDUC_AHRQ_Gannon_May4 Figure 2. Comparison of blood glucose, endogenous insulin and glycosylated hemoglobin in sixmales with mild untreated type 2 diabetes fed a low-carbohydrate/ high-protein diet (non-ketogenic;20% carbohydrate, 30% protein). Results are shown before (▲) and after (●) the five-week regimen.

It is now recognized that the amount of dietary saturated fat and cholesterol recommended for people with diabetes is the same as that recommended for the general population. Recent studies have confirmed that there is no relation between dietary saturated fat and cholesterol and cardiovascular disease [11-13]. Previous statements that “patients on low-carbohydrate diets, monitor lipid profiles” is no longer considered appropriate although all patients with diabetes should monitor their lipids.

Is this real? Can you believe it? 

Is this real? No. It’s not real. It could be real if the American Diabetes Association adopts it. You believed that it was real because it is reasonable and it follows from both common sense and scientific principles. You believed it because it provided you with the data rather than giving you the opinion of a committee that chose whatever studies it wanted to, and took the conclusions at face value. Most of all, you believed it because we all want to believe it. Previous guidelines from the ADA have been incomprehensible and ultimately embarrassing. Since the principles of low-carbohydrate diets are so reasonable, bloggers and others have continually tried to find signs of their acceptance in each new position statement from the ADA, signs that could be described as “encouraging first steps.” Invariably, the ADA guidelines have been, instead, the camel-like creations of a committee characterized by stultifying clichés — one reason that you might have believed that the version above was real is that I included trivial phrases — the text that is in blue  — from the 2013 guidelines. I wrote this because several bloggers tried to put a positive spin on the 2013 guidelines and I was going to comment on how little it would have taken for them to get it right. So I decided to write it for them.

Imperial Dishabilement. Critique of the 2013 Guidelines

Diabetes Care is the house organ of the ADA. The 2013 guidelines are subject only to internal review. No real peer review is possible and it shows. We are not supposed to be too critical, however. Standards of propriety are expected of the reader. We are supposed to refrain from blunt criticism of style and content, like Robert French’s critique of A companion to Woody Allen in the Times Literary Supplement (October 4, 2013):

“The book is 90% of obfuscation, 10% illumination. Statements of the obvious abound (‘Like many Christians, Jews, Muslims and others, Allen can practice a faith without always believing in it’).”

 We are expected to ignore fatuous remarks stating that one of the goals of nutrition therapy is:

 “To maintain the pleasure of eating by providing positive messages about food choices while limiting food choices only when indicated by scientific evidence.”

I admit that I had to ask an English professor for an explanation as to why this particular line is so annoying. “It implies that there is some agency out there who wants to deny you pleasure or unjustly limit your food choices.” But statements of the obvious do abound. Some examples:

“For overweight or obese adults with type 2 diabetes, reducing energy intake while maintaining a healthful eating pattern is recommended to promote weight loss.” (twice)

“Personal preferences (e.g., tradition, culture, religion, health beliefs and goals, economics) and metabolic goals should be considered when recommending one eating pattern over another.”

“A healthful eating pattern, regular physical activity, and often pharmacotherapy are key components of diabetes management.”

“Effective nutrition therapy interventions may be a component of a comprehensive group diabetes education program or an individualized session achieved.”

“Health professionals should collaborate with individuals with diabetes to integrate lifestyle strategies that prevent weight gain or promote modest, realistic weight loss.”

All such documents have a certain degree of boiler plate but here it is relentless and overpowering and it takes the place of the science. And it protests too much. “Individualized” appears 21 times in the guidelines. But it is disingenuous. Individualized is just what the previous guidelines were not and those recommendations are specifically not retracted. It is not sufficient to say that your paper “replaces previous position statements.” You have to explain what the previous ones were and why they are no longer applicable.

If therapy is individualized, what principles is individualization based on? “Individuals who have diabetes should receive individualized Medical Nutrition Therapy (MNT) as needed to achieve treatment goals, preferably provided by a registered dietitian (RD) familiar with the components of diabetes MNT.” In other words, you’re on your own, or worse, turn it over to the RD’s.  Where do the RD’s get their understanding of diabetes MNT?  Well, probably from the last implementation of the ADA guidelines which were unabashed in what they opposed:

“Low-carbohydrate diets might seem to be a logical approach to lowering postprandial glucose. However, foods that contain carbohydrate are important sources of energy, fiber, vitamins, and minerals and are important in dietary palatability” [5] and…

“For weight loss, either low-carbohydrate or low-fat calorie-restricted diets may be effective in the short term (up to1 year).”


“For patients on low-carbohydrate diets, monitor lipid profiles, renal function,and protein intake (in those with nephropathy), and adjust hypoglycemic therapy as needed.”

In other words, low-carb diets are okay if you don’t mind having a heart attack or kidney failure (oh, of course only if you have nephropathy; it’s not a failure to understand of English usage that puts the disclaimer in the wrong place in the sentence ) and the low-carb diet will lead to hypoglycemic episodes.

Most of all, you have to provide new guidance. But guidance is not available in the 2013 position statement. :

“The optimal macronutrient intake to support reduction in excess body weight has not been established.”

“Evidence suggests that there is not an ideal percentage of calories from carbohydrate, protein, and fat for all people with diabetes; therefore, macronutrient distribution should be based on individualized assessment of current eating patterns, preferences, and metabolic goals.”

“The evidence suggests that several different macronutrient distributions/eating patterns may lead to improvements in glycemic and/or CVD risk factors (88). There is no “ideal” conclusive eating pattern that is expected to benefit all individuals with diabetes (88). ” (Reference 88 is to the same group’s review of low carbohydrate diets).

Evidence does not generally suggest what is not ideal.  This is especially true if you don’t look at all the evidence and this is the ADA guideline’s greatest failing. The two figures above, by themselves, constitute a strong case for low carbohydrate diets. These papers are not cited by the 2013 guidelines although I have personally pointed them out to members of the committee.  Non-scientists ask me: “Can you do that? Can you just leave out relevant papers?”

And “ideal” may not be possible anywhere in medicine. What you want is best practice or, as we describe it, the “default diet,” what you try first, your best bet.

The bottom line is that the 2013 guidelines are weak on science and dreadful in style. The two are closely linked. Obfuscation rather than clarification. The emperor is naked. The document would never survive real peer review. In the end, we have to ask why this is tolerated. The answer is usually that the ADA is a private organization and they may do as they choose. Or are they? They are tax exempt and their officers and editors have federal grants. On publication, Diabetes Care is their journal and the editors can publish whatever they like. Or can they? Is any paper in such a publication to be believed if there is this level of bias among the editors? Are they accountable at all?

The writing committee. 

There are no real credentials in science. We all accept that a major part of our understanding of the physical world comes from a clerk in a patent office. But that’s only true if the science is correct. So who did the ADA get to present their position? The list is below. You can Google them to see their qualifications. There are two PhD’s and, oddly, only one representative of the M in MNT (Medical Nutrition Therapy), Will Yancy, who, in fact, has provided strong evidence supporting low-carbohydrate diets. Yancy is a co-author on the un-cited study in Figure 1 (ref. 4). The first author of the 2013 Guidelines, Allison Evert has two publications: those Guidelines and the review paper on low-carbohydrate diets, a subject with which she appears to have no experience.  Most of the other authors also appear to have no experience with research on the effects of macronutrients. Most have little research experience at all.  As for Yancy, who has made a major contribution to dietary carbohydrate restriction, it is generally assumed that they threatened his life.

Allison B. Evert, MS, RD, CDE

Jackie L. Boucher, MS, RD, LD, CDE

Marjorie Cypress, PhD, C-ANP, CDE

Stephanie A. Dunbar, MPH, RD

Marion J. Franz, MS, RD, CDE

Elizabeth J. Mayer-Davis, PHD, RD

Joshua J. Neumiller, PharmD, CDE, CGP, FASCP

Robin Nwankwo, MPH, RD, CDE

Cassandra L Verdi, MPH, RD

Patti Urbanski, MED, RD, LD, CDE

William S. Yancy, Jr., MD, MHSC


1. American Diabetes Association: Nutrition Recommendations and Interventions for Diabetes–2013. Diabetes Care 2013, 36(Suppl 1):S12-S32.

2. Association AD: Standards of Medical Care in Diabetes — 2014. Diabetes Care 2014, 37, Supplement 1:S15-S80.

3. Bernstein RK: Dr. Bernstein’s diabetes solution : the complete guide to achieving normal blood sugars, 4th edn. New York: Little, Brown and Co.; 2011.

4. Vernon MC, Eberstein JA: Atkins Diabetes Revolution.  The Groundbreaking Approach to Preventing and Controlling Type 2 Diabetes. New York: William Morrow; 2004.

5. American Diabetes Association: Nutrition Recommendations and Interventions for Diabetes–2008. Diabetes Care 2008, 31(Suppl 1):S61-S78.

6. Jenkins DJ, Kendall CW, McKeown-Eyssen G, Josse RG, Silverberg J, Booth GL, Vidgen E, Josse AR, Nguyen TH, Corrigan S et al: Effect of a low-glycemic index or a high-cereal fiber diet on type 2 diabetes: a randomized trial. JAMA 2008, 300(23):2742-2753.

7. Westman EC, Yancy WS, Mavropoulos JC, Marquart M, McDuffie JR: The Effect of a Low-Carbohydrate, Ketogenic Diet Versus a Low-Glycemic Index Diet on Glycemic Control in Type 2 Diabetes Mellitus. Nutr Metab (Lond) 2008, 5(36).

8. Gannon MC, Hoover H, Nuttall FQ: Further decrease in glycated hemoglobin following ingestion of a LoBAG30 diet for 10 weeks compared to 5 weeks in people with untreated type 2 diabetes. Nutr Metab (Lond) 2010, 7:64.

9. Gannon MC, Nuttall FQ: Control of blood glucose in type 2 diabetes without weight loss by modification of diet composition. Nutr Metab (Lond) 2006, 3:16.

10. Gannon MC, Nuttall FQ: Effect of a high-protein, low-carbohydrate diet on blood glucose control in people with type 2 diabetes. Diabetes 2004, 53(9):2375-2382.

11. Forsythe CE, Phinney SD, Feinman RD, Volk BM, Freidenreich D, Quann E, Ballard K, Puglisi MJ, Maresh CM, Kraemer WJ et al: Limited effect of dietary saturated fat on plasma saturated fat in the context of a low carbohydrate diet. Lipids 2010, 45(10):947-962.

12. Jakobsen MU, Overvad K, Dyerberg J, Schroll M, Heitmann BL: Dietary fat and risk of coronary heart disease: possible effect modification by gender and age. Am J Epidemiol 2004, 160(2):141-149.

13. Siri-Tarino PW, Sun Q, Hu FB, Krauss RM: Saturated fat, carbohydrate, and cardiovascular disease. Am J Clin Nutr 2010, 91(3):502-509.

tarnowerhermanThe only person definitely known to have died as a consequence of an association with a low-carbohydrate diet is Dr. Herman Tarnower, author of the Scarsdale diet, although, as they used to say on the old TV detective shows, the immediate cause of death was lead poisoning. His girlfriend shot him. Not that folks haven’t been looking for other victims. The Atkins diet is still the bête noire of physicians, at least those who aren’t on it — a study published a few years ago said that physicians were more likely to follow a low carbohydrate diet when trying to lose weight themselves, while recommending a low fat diets for their patients.

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Paris. The summer of 1848. Mobs filled the streets, building barricades just like in Les Mis. If they’d had cars, they probably would have been set on fire.  In February of that year, the King, Louis-Phillipe, had abdicated in yet another French Revolution.  There was a new government, what is called the Second Republic, but whatever it tried to do, it didn’t make anybody happy and there was more unrest. At the Collège de France, faculty complained that it had “slackened the zeal for research among all of the chemists, and all of their time … is absorbed by politics.”


 Figure 1. The Revolution of 1848. Barricades on the Rue Soufflot (Horace Vernet)

Bernard Read the rest of this entry »

“…789 deaths were reported in Doll and Hill’s original cohort. Thirty-six of these were attributed to lung cancer. When these lung cancer deaths were counted in smokers versus non-smokers, the correlation virtually sprang out: all thirty-six of the deaths had occurred in smokers. The difference between the two groups was so significant that Doll and Hill did not even need to apply complex statistical metrics to discern it. The trial designed to bring the most rigorous statistical analysis to the cause of lung cancer barely required elementary mathematics to prove his point.”

Siddhartha Mukherjee —The Emperor of All Maladies.

 Scientists don’t like philosophy of science. It is not just that pompous phrases like hypothetico-deductive systems are such a turn-off but that we rarely recognize it as what we actually do. In the end, there is no definition of science and it is hard to generalize about actual scientific behavior. It’s a human activity and precisely because it puts a premium on creativity, it defies categorization. As the physicist Steven Weinberg put it, echoing Justice Stewart on pornography:

“There is no logical formula that establishes a sharp dividing line between a beautiful explanatory theory and a mere list of data, but we know the difference when we see it — we demand a simplicity and rigidity in our principles before we are willing to take them seriously [1].”

A frequently stated principle is that “observational studies only generate hypotheses.” The related idea that “association does not imply causality” is also common, usually cited by those authors who want you to believe that the association that they found does imply causality. These ideas are not right or, at least, they insufficiently recognize that scientific experiments are not so easily wedged into categories like “observational studies.”  The principles are also invoked by bloggers and critics to discredit the continuing stream of observational studies that make an association between their favorite targets, eggs, red meat, sugar-sweetened soda and a metabolic disease or cancer. In most cases, the studies are getting what they deserve but the bills of indictment are not quite right.  It is usually not simply that they are observational studies but rather that they are bad observational studies and, in any case, the associations are so weak that it is reasonable to say that they are an argument for a lack of causality. On the assumption that good experimental practice and interpretation can be even roughly defined, let me offer principles that I think are a better representation, insofar as we can make any generalization, of what actually goes on in science:

 Observations generate hypotheses. 

Observational studies test hypotheses.

Associations do not necessarily imply causality.

In some sense, all science is associations. 

Only mathematics is axiomatic.

 If you notice that kids who eat a lot of candy seem to be fat, or even if you notice that candy makes you yourself fat, that is an observation. From this observation, you might come up with the hypothesis that sugar causes obesity. A test of your hypothesis would be to see if there is an association between sugar consumption and incidence of obesity. There are various ways — the simplest epidemiologic approach is simply to compare the history of the eating behavior of individuals (insofar as you can get it) with how fat they are. When you do this comparison you are testing your hypothesis. There are an infinite number of things that you could have measured as an independent variable, meat, TV hours, distance from the French bakery but you have a hypothesis that it was candy. Mike Eades described falling asleep as a child by trying to think of everything in the world. You just can’t test them all. As Einstein put it “your theory determines the measurement you make.”

Associations predict causality. Hypotheses generate observational studies, not the other way around.

In fact, association can be strong evidence for causation and frequently provide support for, if not absolute proof, of the idea to be tested. A correct statement is that association does not necessarily imply causation. In some sense, all science is observation and association. Even thermodynamics, that most mathematical and absolute of sciences, rests on observation. As soon as somebody observes two systems in thermal equilibrium with a third but not with each other (zeroth law), the jig is up. When somebody builds a perpetual motion machine, that’s it. It’s all over.

Biological mechanisms, or perhaps any scientific theory, are never proved. By analogy with a court of law, you cannot be found innocent, only not guilty. That is why excluding a theory is stronger than showing consistency. The grand epidemiological study of macronutrient intake vs diabetes and obesity shows that increasing carbohydrate is associated with increased calories even under conditions where fruits and vegetables also went up and fat, if anything went down. It is an observational study but it is strong because it gives support to a lack of causal effect of increased carbohydrate and decreased fat on outcome. The failure of total or saturated fat to have any benefit is the kicker here. It is now clear that prospective experiments have, in the past, and will continue to show, the same negative outcome. Of course, in a court of law, if you are found not guilty of child abuse, people may still not let you move into their neighborhood. It is that saturated fat should never have been indicted in the first place.

An association will tell you about causality 1) if the association is strong and 2) if there is a plausible underlying mechanism and 3) if there is no more plausible explanation — for example, countries with a lot of TV sets have modern life styles that may predispose to cardiovascular disease; TV does not cause CVD.

Re-inventing the wheel. Bradford Hill and the history of epidemiology.

Everything written above is true enough or, at least, it seemed that way to me. I thought of it as an obvious description of what everybody knows. The change to saying that “association does not necessarily imply causation” is important but not that big a deal. It is common sense or logic and I had made it into a short list of principles. It was a blogpost of reasonable length. I described it to my colleague Gene Fine. His response was “aren’t you re-inventing the wheel?” Bradford Hill, he explained, pretty much the inventor of modern epidemiology, had already established these and a couple of other principles. Gene cited The Emperor of All Maladies, an outstanding book on the history of cancer.  I had read The Emperor of All Maladies on his recommendation and I remembered Bradford Hill and the description of the evolution of the ideas of epidemiology, population studies and random controlled trials. I also had a vague memory, of reading the story in James LeFanu’s The Rise and Fall of Modern Medicine, another captivating history of medicine. However, I had not really absorbed these as principles. Perhaps we’re just used to it, but saying that an association implies causality only if it is a strong association is not exactly a scientific breakthrough. It seems an obvious thing that you might say over coffee or in response to somebody’s blog. It all reminded me of learning, in grade school, that the Earl of Sandwich had invented the sandwich and thinking “this is an invention?”  Woody Allen thought the same thing and wrote the history of the sandwich and the Earl’s early failures — “In 1741, he places bread on bread with turkey on top. This fails. In 1745, he exhibits bread with turkey on either side. Everyone rejects this except David Hume.”

At any moment in history our background knowledge — and accepted methodology —  may be limited. Some problems seem to have simple solutions. But simple ideas are not always accepted. The concept of the random controlled trial (RCT), obvious to us now, was hard won and, proving that any particular environmental factor — diet, smoking, pollution or toxic chemicals was the cause of a disease and that, by reducing that factor, the disease could be prevented, turned out to be a very hard sell, especially to physicians whose view of disease may have been strongly colored by the idea of an infective agent.

Hill_CausationThe Rise and Fall of Modern Medicine describes Bradford Hill’s two demonstrations that streptomycin in combination with PAS (para-aminosalicylic acid) could cure tuberculosis and that tobacco causes lung cancer as one of the Ten Definitive Moments in the history of modern medicine (others shown in the textbox). Hill was Professor of Medical Statistics at the London School of Hygiene and Tropical Medicine but was not formally trained in statistics and, like many of us, thought of proper statistics as common sense. An early near fatal case of tuberculosis also prevented formal medical education. His first monumental accomplishment was, ironically, to demonstrate how tuberculosis could be cured with the combination of streptomycin and PAS.  In 1941, Hill and co-worker Richard Doll undertook a systematic investigation of the risk factors for lung cancer. His eventual success was accompanied by a description of the principles that allow you to say when association can be taken as causation.

 Ten Definitive Moments from Rise and Fall of Modern Medicine.

1941: Penicillin

1949: Cortisone

1950: streptomycin, smoking and Sir Austin Bradford Hill

1952: chlorpromazine and the revolution in psychiatry

1955: open-heart surgery – the last frontier

1963: transplanting kidneys

1964: the triumph of prevention – the case of strokes

1971: curing childhood cancer

1978: the first ‘Test-Tube’ baby

1984: Helicobacter – the cause of peptic ulcer

Wiki says: “in 1965, built  upon the work of Hume and Popper, Hill suggested several aspects of causality in medicine and biology…” but his approach was not formal — he never referred to his principles as criteria — he recognized them as common sense behavior and his 1965 presentation to the Royal Society of Medicine, is a remarkably sober, intelligent document. Although described as an example of an article that, as here, has been read more often in quotations and paraphrases, it is worth reading the original even today.

Note: “Austin Bradford Hill’s surname was Hill and he always used the name Hill, AB in publications. However, he is often referred to as Bradford Hill. To add to the confusion, his friends called him Tony.” (This comment is from Wikipedia, not Woody Allen).

The President’s Address

Bradford Hill’s description of the factors that might make you think an association implied causality:


1. Strength. “First upon my list I would put the strength of the association.” This, of course, is exactly what is missing in the continued epidemiological scare stories. Hill describes

“….prospective inquiries into smoking have shown that the death rate from cancer of the lung in cigarette smokers is nine to ten times the rate in non-smokers and the rate in heavy cigarette smokers is twenty to thirty times as great.”

But further:

“On the other hand the death rate from coronary thrombosis in smokers is no more than twice, possibly less, the death rate in nonsmokers. Though there is good evidence to support causation it is surely much easier in this case to think of some features of life that may go hand-in-hand with smoking – features that might conceivably be the real underlying cause or, at the least, an important contributor, whether it be lack of exercise, nature of diet or other factors.”

Doubts about an odds ratio of two or less. That’s where you really have to wonder about causality. The progression of epidemiologic studies that tell you red meat, HFCS, etc. will cause diabetes, prostatic cancer, or whatever, these rarely hit an odds ratio of 2.  While the published studies may contain disclaimers of the type in Hill’s paper, the PR department of the university where the work is done, and hence the public media, show no such hesitation and will quickly attribute causality to the study as if the odds ratio were 10 instead of 1.2.

2. Consistency: Hill listed the repetition of the results in other studies under different circumstances as a criterion for considering how much an association implied causality. Not mentioned but of great importance, is that this test cannot be made independent of the first criterion. Consistently weak associations do not generally add up to a strong association. If there is a single practice in modern medicine that is completely out of whack with respect to careful consideration of causality, it is the meta-analysis where studies with no strength at all are averaged so as to create a conclusion that is stronger than any of its components.

3. Specificity. Hill was circumspect on this point, recognizing that we should have an open mind on what causes what. On specificity of cancer and cigarettes, Hill noted that the two sites in which he showed a cause and effect relationship were the lungs and the nose.

4. Temporality: Obviously, we expect the cause to precede the effect or, as some wit put it “which got laid first, the chicken or the egg.”  Hill recognized that it was not so clear for diseases that developed slowly. “Does a particular diet lead to disease or do the early stages of the disease lead to those peculiar dietetic habits?” Of current interest are the epidemiologic studies that show a correlation between diet soda and obesity which are quick to see a causal link but, naturally, one should ask “Who drinks diet soda?”

5. Biological gradient:  the association should show a dose response curve. In the case of cigarettes, the death rate from cancer of the lung increases linearly with the number of cigarettes smoked. A subset of the first principle, that the association should be strong, is that the dose-response curve should have a meaningful slope and, I would add, the numbers should be big.

6. Plausibilityy: On the one hand, this seems critical — the association of egg consumption with diabetes is obviously foolish — but the hypothesis to be tested may have come from an intuition that is far from evident. Hill said, “What is biologically plausible depends upon the biological knowledge of the day.”

7. Coherence: “data should not seriously conflict with the generally known facts of the natural history and biology of the disease”

8. Experiment: It was another age. It is hard to believe that it was in my lifetime. “Occasionally it is possible to appeal to experimental, or semi-experimental, evidence. For example, because of an observed association some preventive action is taken. Does it in fact prevent?” The inventor of the random controlled trial would be amazed how many of these are done, how many fail to prevent. And, most of all, he would have been astounded that it doesn’t seem to matter. However, the progression of failures, from Framingham to the Women’s Health Initiative, the lack of association between low fat, low saturated fat and cardiovascular disease, is strong evidence for the absence of causation.

9. Analogy: “In some circumstances it would be fair to judge by analogy. With the effects of thalidomide and rubella before us we would surely be ready to accept slighter but similar evidence with another drug or another viral disease in pregnancy.”

Hill’s final word on what has come to be known as his criteria for deciding about causation:

“Here then are nine different viewpoints from all of which we should study association before we cry causation. What I do not believe — and this has been suggested — is that we can usefully lay down some hard-and-fast rules of evidence that must be obeyed before we accept cause and effect. None of my nine viewpoints can bring indisputable evidence for or against the cause-and-effect hypothesis and none can be required as a sine qua non. What they can do, with greater or less strength, is to help us to make up our minds on the fundamental question – is there any other way of explaining the set of facts before us, is there any other answer equally, or more, likely than cause and effect?” This may be the first critique of the still-to-be-invented Evidence-based Medicine.

Nutritional Epidemiology.

The decision to say that an observational study implies causation is equivalent to an assertion that the results are meaningful, that it is not a random association at all, that it is scientifically sound. Critics of epidemiological studies have relied on their own perceptions and appeal to common sense and when I started this blogpost, I was one of them, and I had not appreciated the importance of Bradford Hill’s principles. The Emperor of All Maladies described Hill’s strategies for dealing with association and causation “which have remained in use by epidemiologists to date.”  But have they? The principles are in the texts. Epidemiology, Biostatistics, and Preventive Medicine has a chapter called “The study of causation in Epidemiologic Investigation and Research” from which the dose-response curve was modified. Are these principles being followed? Previous posts in this blog and others have have voiced criticisms of epidemiology as it’s currently practiced in nutrition but we were lacking a meaningful reference point. Looking back now, what we see is a large number of research groups doing epidemiology in violation of most of Hill’s criteria.

The red meat scare of 2011 was Pan, et al and I described in a previous post, the remarkable blog from Harvard . Their blog explained that the paper was unnecessarily scary because it had described things in terms of “relative risks, comparing death rates in the group eating the least meat with those eating the most. The absolute risks… sometimes help tell the story a bit more clearly. These numbers are somewhat less scary.”  I felt it was appropriate to ask “Why does Dr. Pan not want to tell the story as clearly as possible?  Isn’t that what you’re supposed to do in science? Why would you want to make it scary?” It was, of course, a rhetorical question.

Looking at Pan, et al. in light of Bradford Hill, we can examine some of their data. Figure 2 from their paper shows the risk of diabetes as a function of red meat in the diet. The variable reported is the hazard ratio which can be considered roughly the same as the odds ratio, that is, relative odds of getting diabetes. I have indicated, in pink, those values that are not statistically significant and I grayed out the confidence interval to make it easy to see that these do not even hit the level of 2 that Bradford Hill saw as some kind of cut-off.


The hazard ratios for processed meat are somewhat higher but still less than 2. This is weak data and violates the first and most important of Hill’s criteria. As you go from quartile 2 to 3, there is an increase in risk, but at Q4, the risk goes down and then back up at Q5, in distinction to principle 5 which suggests the importance of dose-response curves. But, stepping back and asking what the whole idea is, asking why you would think that meat has a major — and isolatable role separate from everything else — in a disease of carbohydrate intolerance, you see that this is not rational, this is not science. And Pan is not making random observations. This is a test of the hypothesis that red meat causes diabetes. Most of us would say that it didn’t make any sense to test such a hypothesis but the results do not support the hypothesis.

What is science?

Science is a human activity and what we don’t like about philosophy of science is that it is about the structure and formalism of science rather than what scientists really do and so there aren’t even any real definitions. One description that I like, from a colleague at the NIH: “What you do in science, is you make a hypothesis and then you try to shoot yourself down.” One of the more interesting sidelights on the work of Hill and Doll, as described in Emperor, was that during breaks from the taxing work of analyzing the questionnaires that provided the background on smoking, Doll himself would step out for a smoke. Doll believed that cigarettes were unlikely to be a cause — he favored tar from paved highways as the causative agent — but as the data came in, “in the middle of the survey, sufficiently alarmed, he gave up smoking.” In science, you try to shoot yourself down and, in the end, you go with the data.


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.

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Everybody has their favorite example of how averages don’t really tell you what you want to know or how they are inappropriate for some situations. Most of these are funny because they apply averages to cases where single events are important. I’ll list a couple in the text boxes in this post. From the title:

If Bill Gates walks into a bar, on average, everybody in the bar is a millionaire.

Technically speaking, averages start with the assumption that deviations are due to random error, that is, that there is a kind of “true” value if we could only control things well — if there were no wind resistance and all balls were absolutely uniform, they would always fall in the same place; any spread in values is random rather than systematic.
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The reporter from Men’s Health asked me: “You finish dinner, even a satisfying low-carb dinner,” — he is a low-carb person himself — “you are sure you ate enough but you are still hungry. What do you do?”  I gave him good advice. “Think of a perfectly broiled steak or steamed lobster with butter, some high protein, relatively high fat meal that you usually like.  If that doesn’t sound good, you are not hungry.  You may want to keep eating. You may want something sweet.  You may want to feel something rolling around in your mouth, but you are not hungry.  Find something else to do — push-ups are good.  If the steak does sound good, you may want to eat. Practically speaking, it’s a good idea to keep hard-boiled eggs, cans of tuna fish around (and, of course, not keep cookies in the house).” I think this is good practical advice. It comes from the satiating effects of protein food sources, or perhaps the non-satiating, or reinforcing effect of carbohydrate. But the more general question is: What is hunger? Read the rest of this entry »