Guest post: Denialism as Pseudoscientific Thinking.

In pseudoscience there’s a subtype called Denialism. Denialism seeks to deny an established science and violate multiple principles of logic, and scientific methodology, this is mostly because of a priori beliefs and preconceptions. Typically the same cognitive and logical errors are committed in denialism reasoning.

The whole process starts with a desired conclusion, that a generally accepted scientific or historical claim is not true. Denialists have ideological reasons, and engage in motivated reasoning, rationalizing away the undesired claim.

In essence and practical terms, they work backward from their desired conclusion, filling in justifications.

1. Moving the goalposts

In moving the goalposts, they always demand more evidence for a claim, even if currently available. However when that burden of evidence is met, the goalposts are moved and more evidence is demanded.

They may use vagueness in defining a certain term to move the goalpost away from any possible dis-confirming evidence.

2. Unreasonable demand for evidence

Because science has gaps, they explore them as if it the specific scientific theory being discussed is invalid or not well established.

Let’s take the example of HIV denial. Deniers often demand a single study or scientific paper establishing HIV as the cause of AIDS. However, it is not established by a single study but rather by a large body of evidence.

In scientific reasoning we must see if the gaps are slowly being filled, and if predictions are met, and if it fits together with other lines of evidence, observational or experimental.

If a theory has been going around in circles and not progressing, that is a strong indication of pseudoscience.

3. Pointing out disagreements

Disagreements within a discipline are explored, often small details, as if the science in question is not solid.

4. Denying entire categories of evidence

Another strategy the narrowing of evidence that may count as “scientific”. The most common is using the logical fallacy of confusing correlation with causation.

Correlation is not the same as causation, not necessarily anyway. Correlations need to be used properly, and multiple correlations can triangulate a specific causal relationship observed in a correlation. Epidemiology is based on correlations and observational evidence, if they were invalid the entire field simply would vanish.

They can even deny all historical sciences such as astronomy, geology, or even forensics.

5. False dichotomy

This is an argument from ignorance. If a version of events is not true then the alternate claim or version must be. However, they rarely provide positive evidence for their alternate claim.

6. Campaign of Doubt

Little factoids can be gathered and taken out of context. The goal is to sow doubt, uncertainty, and distrust, focusing on apparent inconsistencies, or gaps. However in healthy skepticism we consider all the evidence in the proper perspective, and even though knowledge is incomplete, reliable conclusions can be achieved.

7. Conspiracy theory

As a last resort comes the conspiracy theory, claiming that the scientific evidence itself is fraudulent, a grand conspiracy. This tactic allows them to dismiss all the evidence and rationalize it away.



Grant, John. Denying Science. Amherst: Prometheus Books, 2011.

Novella, Steven. “More on God of the Gaps.” NeuroLogica Blog. http://theness.com/neurologicablog/index.php/more-on-god-of-the-gaps

Novella, Steven. “Skepticism and Denial.” The NESS. http://www.theness.com/index.php/skepticism-and-denial

Specter, Michael. Denialism: How Irrational Thinking Hinders Scientific Progress, Harms the Planet, and Threatens Our Lives. London: Penguin Press, 2009

Tokuno, Hajime. “Holocaust Denial.” The NESS. http://www.theness.com/index.php/holocaust-denial


For more information on Sérgio Fontinhas, see Big Fitness Project.

Guest post: Science versus Pseudoscience.

Pseudoscience is so flawed that it cannot be considered legitimate science. Of course it is common to claim that one’s beliefs are scientific, but mostly they are not.

Pseudoscience lacks the true method of science and goes way beyond just a few errors, the methods themselves are so flawed that makes the theory suspicious.

Between the two extremes of science and pseudoscience there is a gray zone, but legitimate science and pseudosciences can still be identified. The denial of this two extremes in the continuum, is a false continuum logical fallacy, or philosophically called the demarcation problem.

Features of Pseudoscience

1. Motivated reasoning

The most prominent feature of this pathological science is working backward from desired results, or motivated reasoning. The result is that they make evidence fit into preconceived notions. They use biased logic and cherry-picked evidence in order to defend a desired conclusion. There’s no concern and effort to prove their own theories wrong.

This relates to the congruence bias, testing one’s own theory by looking for positive evidence and cherry-picked evidence.

2. Burden of proof and confirmation bias

They will only look for confirming evidence, avoid dis-confirming evidence, and may engage in special pleading and shifting the burden of proof.

In confirmation bias, they look for supportive evidence for their own desired conclusions, choosing only the evidence that supports their own theory, irrespective of quality, negative evidence.

3. Anecdotal evidence

Anecdotes are uncontrolled, or ad-hoc observations, and they are not systematic. They rely on confirmation bias and recall bias.

Low-grade evidence is often favored no matter how implausible it may be.

Emotional appeal is another typical tactic among pseudoscientists who try to defend their statements, claiming what people say is more important than actual numbers on paper.

Pseudoscientific belief may even be based upon a single case or observation, preliminary evidence, or even a single anecdote. This is the hasty generalization logical fallacy.

Pseudoscientific principles may also be based upon a philosophical idea, not been empirically tested or developed as a scientific theory.

4. Grandiose claims (Galileo syndrome)

This involves grandiose claims based upon preliminary evidence. Far-reaching claims overturn entire portions of well-established science, using very little research or tiny bits of evidence.

5. Alternative science

In extreme cases, pseudoscience leads to alternative science, all of science is replaced with an alternative version.

6. Absolute claims

Pseudoscientists make bold claims that are often absolute and go way beyond the evidence. Pseudoscientists offer simple answers to complex questions, a theory of everything where one tiny casual source is used to explain the entire universe, if it comes to that.

7. Hostility

Pseudoscientists generally cannot accept criticism and avoid the scientific community. They claim being victim of a conspiracy and stay away from mainstream science and community.

8. Vagueness

Pseudoscientists use vague terms and words to obfuscate, so they can shift the definition around, use it in different ways at different times when it suits them, to confuse others and avoid explaining their point. Vague terms such as “information” or “energy” are often used with no specificity as in a scientific discussion.

9. Stagnation

Pseudosciences fail to progress, and tend to be stagnant. They are ad nauseam trying to establish their theory rather than build a body of evidence for it.

10. Anomaly hunting

Anomaly hunting is yet another common feature in which they search for anomalies trying to establish a conclusion, which does not seek to refute or explore other alternatives.



Nickerson, Raymond. “Confirmation Bias: A Ubiquitous Phenomenon in Many Guises.” Review of General Psychology 2, no. 2 (1998): 175–220.

Novella, Steven. “Anomaly Hunting.” NeuroLogica Blog. http://theness.com/neurologicablog/index.php/anomaly-hunting

Pigliucci, Massimo. Nonsense on Stilts: How to Tell Science from Bunk. Chicago: University of Chicago Press, 2010

Shermer, Michael, The Borderlands of Science: Where Sense Meets Nonsense. New York: Oxford University Press, 2001.

Gardner, Martin. Fads and Fallacies in the Name of Science. Mineola: Dover Publications, 1957
Shermer, Michael. Why People Believe Weird Things. New York: Henry Holt/Times Books, 1997.


For more information on Sérgio Fontinhas, see Big Fitness Project. 

Another tasty analogy.

Here's a tasty analogy.

From http://grannychoe.com/recipe3_Soup.php

In Ultra-high-fat (~80%) diets: Fat storage, and a delicious analogy, I analogised the effect of carbohydrate consumption on mean serum glucose level with the effect of fat consumption on mean serum triglyceride level. Here's another one.

Chronic excessive consumption of carbohydrates relative to what are being burned results in excessive fat synthesis in the liver, resulting in excessively-high fasting serum triglyceride level, which is harmful.

Chronic excessive consumption of fats relative to what are being burned results in excessive cholesterol synthesis in the liver, resulting in excessively-high fasting VLDL, LDL & IDL level, which is harmful.

Seems legit.

Siri-Tarino et al, Forests & Trees and "Eureka!" moments.

Here's Fig. 2 from Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease:-

Risk ratios and 95% CIs for fully adjusted random-effects models examining associations between saturated fat intake in relation to coronary heart disease and stroke.

The above "Forest" plot has a subtotal RR of 1.07 (95% CI 0.96 1.19). The overall conclusion is that there's no association between saturated fat intake and the RR for CHD. Hmmm.

I looked at the data in Table 3. Of the 16 studies contributing to the CHD results, only 3 of them specify high sat fat intakes over a wide range. The results from these 3 studies are as follows:-

Pietinen et al: RR=0.93 (95% CI 0.6, 1.44).
Mann et al: RR=2.77 (95% CI 1.25, 6.13).
Boniface et al: Pooled RR = 1.37 (95% CI 1.17, 1.65).

The results from Pietinen et al are statistically-insignificant (95% CI values are way above & below 1) with an overall slight protective effect. The results from Mann et al have a RR >> 1 with both 95% CI's >1 and the results from Boniface et al have a RR >1 with both 95% CI's >1.

Other studies either have sat fat intakes varying from very low to low, or specify mean/median sat fat intakes without values for highest & lowest tertiles/quartiles/quintiles etc. Other studies have results that are statistically-insignificant.

However, there are some studies that show a slight protective effect of small amounts of sat fats. How come?

Thanks to George Henderson, I had a "Eureka!" moment. He posted a link to Dietary intake of saturated fat by food source and incident cardiovascular disease: the Multi-Ethnic Study of Atherosclerosis.

Here's Fig. 1 from that study.

HRs and 95% CI's of CVD risk according to quintiles of energy-adjusted SF from different sources (n = 5209).

The Meat SF plot has a net positive slope (bad news, but the range of intake is very small), the Butter & Plant SF plots are random, but the Dairy SF plot has a net negative slope (good news). Dairy saturated fats in amounts of up to 10g/day are protective against CHD. As the Dairy sat fat intake is too small to have a significant effect on lipids, what's the mechanism? I think that it's Vitamin K2. See Chowdhury et al, More forests & more trees and more "Eureka!" moments with cheese.

When you average out the results from all studies, the result is null. This is data dilution statistics.

EDIT: See also Study: Saturated Fat as Bad as Sugar!

I'm NOT a lipophobe, I'm a very naughty boy!

First, postprandial triglycerides again. From Fasting Compared With Nonfasting Triglycerides and Risk of Cardiovascular Events in Women, here's a plot of HR for future CHD vs TG's at various times after eating.

Hazard ratio (HR) and 95% confidence interval (CI) for highest vs lowest tertiles of triglyceride level (see Table 3 for values), adjusted for age, blood pressure, smoking, hormone use, levels of total and high-density lipoprotein cholesterol, diabetes mellitus, body mass index, and high-sensitivity C-reactive protein level.

Notice how the HR falls with increasing time from last meal. As TG's ≥12 hours after eating are a surrogate for Insulin Resistance (IR) and the HR is only 1.04 (95% CI 0.79 - 1.38), this strongly suggests that IR is not a significant factor.

It's been suggested that IR might increase PP TG's in the 2 - 4 hour period due to impaired clearance. According to Fig. 3B in Extended effects of evening meal carbohydrate-to-fat ratio on fasting and postprandial substrate metabolism, TG clearance in healthy men doesn't significantly start until after 4 hours has elapsed. Therefore, an impairment in TG clearance isn't going to make a significant difference to TG level in the 2 - 4 hour period.

Second, the reason why I'm having to repeat myself is due to Cholesterol: Do chylomicrons clog your arteries? (2), where I've been called "my resident lipophobe". As I drink Gold Top milk (5.2g of fat/100mL) and eat pork including belly slices (you know, those strips of pork with a lot of fat on them), I'm being attacked for something that I'm not.

What I'm criticising is dietary extremism. Eating fats in foods is fine by me, but eating sticks of Kerrygold butter and/or dumping loads of butter and/or MCT oil into coffee to achieve "Nutritional Ketosis" is not a good idea. Anyway, here's an amusing spoof on Bulletproof coffee.

Reversing type 2 diabetes, the lecture explaining T2D progression, and how to treat it.

Julianne Taylor of Paleo & Zone Nutrition posted the following excellent lecture on Facebook:-

Eating Through The Myths: Food, Health and Happiness - Taylor, Prof. R., Berlin, 28-Sep-12

Salient points:

1) It's a chronic calorie excess (of carbohydrates and/or fats) that causes problems.
2) Motivation, motivation, motivation!
3) Both diet and exercise are important. See Move More: Solutions to problems.
4) You can't outrun your fork. See The 5th Myth of Modern Day Dieting: You Can Outrun Your Fork.
5) Underlying Insulin Resistance needs to be addressed. See Insulin Resistance: Solutions to problems.

See also Reversal of type 2 diabetes: normalisation of beta cell function in association with decreased pancreas and liver triacylglycerol, and Pathogenesis of type 2 diabetes: tracing the reverse route from cure to cause.

For more information on Prof. Taylor's work, see Reversing Type 2 Diabetes.

Carbs, Carbs, Carbs, Carbs and Carbs.

Carbohydrates seem to get the blame for everything nowadays. "Carbohydrates made me fat". "Carbohydrates burned-out my pancreas". "Carbohydrates raised my blood glucose". "Carbohydrates raised my blood triglycerides". "Carbohydrates stole mer jerb!". O.K, I made the last one up!
If carbohydrates are responsible for all of these bad things, then how come a diet of only potatoes had the opposite effect? See 20 Potatoes a day.

Also, Blue Zone populations eat a diet with a high percentage of total energy (%E) from carbohydrates. See Low serum insulin in traditional Pacific Islanders--the Kitava Study and The Kitava Study. The Kitavans eat ~70%E from carbohydrates, ~20%E from fats and ~10%E from proteins. They don't eat a significant amount of Western crap-in-a-bag/box/bottle.

Maybe it has something to do with the type of carbohydrates and with what they're eaten. In A very-low-fat diet is not associated with improved lipoprotein profiles in men with a predominance of large, low-density lipoproteins , (emphasis, mine) "The very-low-fat, high-carbohydrate experimental diet was designed to supply less than 10% of energy from fat (2.7% saturated, 3.7% monounsaturated, and 2.6% polyunsaturated), with 75% from carbohydrate (with equal amounts of naturally occurring and added simple and complex carbohydrate) and 15% from protein." Simple carbohydrates are sugars.

The experimental diet which did bad things contained 37.5%E from sugars. I declare shenanigans!

1. There are simple carbs, there are simple carbs and there are simple carbs. In the previous post, the graph of plasma triglycerides after an OGTT showed that 100g of glucose had no significant effect on plasma triglycerides over a 6 hour period. If it had been 100g of fructose, there would have been a significant increase in plasma triglycerides. Galactose is taken-up by the liver and has minimal effect on blood glucose, but I don't know its effect on plasma triglycerides.

2. There are complex carbs, there are complex carbs and there are complex carbs. Overcooked starch is high in amylopectin which is highly-branched, which means that it hydrolyses rapidly into glucose which gives it a very high glycaemic index. Raw & refrigerated potato starches have very low glycaemic indices, due to the presence of amylose, or other resistant starches. Rice contains a mixture of starches which varies with rice type, cooking time and subsequent refrigeration.

3. There are oligosachharides e.g. FOS.

4. There are polysaccharides e.g. inulin.

5. There is soluble fibre/fiber e.g. cellulose.

Although overeating sugars containing fructose & starches that rapidly hydrolyse into glucose makes the liver fatty, overeating fats also makes the liver fatty. See Pathogenesis of type 2 diabetes: tracing the reverse route from cure to cause.

It's the chronic over-consumption of crap-in-a-bag/box/bottle (high in sugars and/or starches and/or fats), not just carbohydrates, that causes over-fatness and other health problems.