Why the Energy Balance Theory is pseudoscience

Why the Energy Balance Theory is pseudoscience

First of all, its basis is a mere tautology (i.e. needless repetition of an idea) referred to the adipose tissue:

if the adipose tissue accumulates energy, in that tissue more energy comes in than gets out

This is just a truism, because that is what “accumulation” means, since energy can’t come out of nothing nor can it disappear, but this tautology tells us nothing about why the accumulation of triglycerides is happening. The tautology (in its correct form) is useless. The false sense of utility provided by the Energy Balance Theory comes from a deceitful transformation of the useless tautology: the trick is that the boundary for the application of the First Law of Thermodynamics is unjustifiably considered to be the whole body’s boundary, instead of the correct boundary, which is the adipose tissue’s boundary. Understanding this deception is crucial: if you want to apply the First Law of Thermodynamics, you must have a clearly defined physical boundary in its use. The Energy Balance Theory violates that principle and that fact makes this theory a hoax.

A thermodynamic system is that part of the world to which we are directing our attention. Everything that is not a part of the system constitutes the surroundings. The system and surroundings are separated by a boundary.

Internal energy is the totality of all forms of kinetic and potential energy of the system

When the “Calories In” and “Calories Out” terms are used, the physical boundary is the whole body’s boundary. This is mandatory. And, therefore, the totality of all forms of energy in the body have always to be taken into account. It is unjustifiable and deceitful to only consider the energy stored in a specific tissue (e.g. the accumulation of triglycerides in the adipocytes).

Calories In = Calories Out + Change in FAT DEPOSITS

Calories In = Calories Out + Change in ALL ENERGY STORES

Any energy that’s left over after the body has used what it needs is stored as body fat (source)

That is a theory that doesn’t derive from physics’ laws.

The faux causality problem

Moreover, the Energy Balance Theory relies on an unfounded attribution of causality. It is easy to understand this point, just by comparison with any other growth in a biological system. What does the Energy Balance Theory tell us about conditions such as fatty liver, muscle hypertrophy, giantism or a tumor’s growth? What does it tell us about how anabolic steroids work? All of those situations represent the growth of tissues inside of the body, and therefore they represent energy accumulation in one or several tissues, just as obesity does.

Fatty Liver

Fat accumulates in the liver, therefore

it is an incontrovertible fact of physics that fatty liver happens when calorie intake exceeds expenditure […] the laws of physics ensure that any person will reverse its fatty liver if calorie intake is reduced sufficiently

it is an incontrovertible fact of physics that weight increases when calorie intake exceeds expenditure […] the laws of physics ensure that any obese person will lose weight if calorie intake is reduced sufficiently


Your body can’t grow unless you eat more than you expend:

An imbalance between energy intake and energy expenditure is the primary etiology for giantism.

An imbalance between energy intake and energy expenditure is the primary etiology for excess weight gain.

Muscle mass

Muscle tissue can’t grow unless there is a caloric inbalance:

Muscle hypertrophy is defined as a state of increased muscle mass resulting from chronic nutrient excess, where energy intake significantly exceeds energy expenditure

Obesity is defined as a state of increased adiposity resulting from chronic nutrient excess, where energy intake significantly exceeds energy expenditure


A tumor can’t grow unless more energy comes in than gets out:

A key determinant of a tumor’s growth is the balance between ingested calories and the body’s basal energy expenditure. The tumor’s growth therefore results when small positive energy balances accumulate over a long period of time

A key determinant of obesity is the balance between ingested calories and the body’s basal energy expenditure. Obesity therefore results when small positive energy balances accumulate over a long period of time

Anabolic steroids

Do anabolic steroids increase your muscle mass by making you hungry or sedentary?

if anabolic steroids don’t increase energy intake […], and don’t decrease energy expenditure, then how exactly are they supposed to cause energy accumulation in the body as fat? There is no energy fairy

if insulin doesn’t increase energy intake [… ], and doesn’t decrease energy expenditure, then how exactly is it supposed to cause energy accumulation in the body as fat? There is no energy fairy

Your energy expenditure is not a controllable input of the system

The Energy Balance Theory hoax is supported with rethorical fallacies where the energy expenditure is alluded as if it were a controllable input of the equation. It is not. If both energy intake and energy expenditure are considered inputs of the system, and if the decepcion explained above is used (i.e. considering only the energy stored in a specific tissue), a false impression of causality is created:

When calorie expenditure decreases and calorie intake increases, the energy balance equation leaves only one possible outcome: fat gain (source)

When calorie expenditure decreases and calorie intake increases, the energy balance equation leaves only one possible outcome: fatty liver or muscle hypertrophy or giantism or a tumor’s growth or you are pregnant and the fetus grows

As explained above, to assume a result for an output (“calorie expenditure decreases”) is cheating. It is not an input we can control.

When calorie intake increases, in the case where the calorie expenditure decreases the energy balance equation leaves only one possible outcome: fatty liver or muscle hypertrophy or giantism or a tumor’s growth

The energy balance equation can NEVER be used to predict the response from a living tissue to a stimulus, because that law has nothing to do with biology. Its use related to the study of obesity is based on rethorical fallacies and it is, therefore, unwarranted.

Does this mean that the First Law of Thermodynamics is not valid in a biological system?

That idea is not correct: the First Law of Thermodynamics is always fulfilled, and, therefore, it is also fulfilled in biological systems. It is the Energy Balance Theory what is a fraud, because it is both a misapplication and a misinterpretation of what the First Law of Thermodynamics says.

The pseudoscience is the pretension that the Energy Balance Theory is rightfully derived from the First Law of Thermodynamics and that, therefore, it must be used to deduce causes and solutions for obesity. The Energy Balance Theory is a hoax and it can’t be used for that purpose, just as it is clearly inappropriate to deduce how to cure your fatty liver, how to increase your muscle mass or how to treat a kid that suffers from giantism. Obesity is not a special condition.

Ultimately, obesity reflects energy imbalance, so the major areas for intervention relate to dietary intake and energy expenditure, for which the main modifiable component is physical activity (source)

Giantism also reflects energy imbalance, right? What are the major areas for intervention in that case? A tumor’s growth also reflects energy imbalance, right? What are the major areas for intervention in that case?

Further reading:

Are we obese because of a hungry brain or are we because of the pseudoscience that the “experts” spread?

The energy balance theory

Stephan Guyenet, PhD has written a book titled “The Hungry Brain: Outsmarting the Instincts That Make Us Overeat “. Just having a look at its cover makes it clear that nothing interesting can be expected from inside the book, as this guy is trying to answer a wrong question: he assumes that the cause of obesity is that we overeat.

A couple of excerpts from the book:

Three independent methods suggest that our calorie intake increased substantially over the course of the obesity epidemic, and this increase is sufficient to account for the weight we gained. Simply stated, we gained weight because we ate more.

When you eat more calories than you burn, the excess calories are primarily shunted into your adipose tissue. Your adiposity, or body fatness, increases. It really is as simple as that

Any energy that’s left over after the body has used what it needs is stored as body fat

When calorie expenditure decreases and calorie intake increases, the energy balance equation leaves only one possible outcome: fat gain. We gained fat as we ate more calories than we needed to remain lean, given our physical activity level. In other words, we overate.

Quackery and pseudoscience

Two sentences from Guyenet’s book are perfect as an illustration of how the energy balance pseudoscience is built:

When you eat more calories than you burn, the excess calories are primarily shunted into your adipose tissue. Your adiposity, or body fatness, increases. It really is as simple as that

Any energy that’s left over after the body has used what it needs is stored as body fat

Is actually that the way our body works? First our body uses the energy it needs, and then what’s left is stored as body fat? Is that what our knowledge of the human body’s physiology says that happens? I’d like to see the scientific evidence that supports Guyenet’s claims, because I think it is absolutely UNTRUE that our body works the way he declares. Guyenet’s ideas are not science, they are quackery.

What are the tricks here?

    1. the sophistry makes energy expenditure seem like an input in the “human body” system. And once two terms of the energy balance (i.e. expenditure and intake) are fraudulently presented as inputs, then the energy balance equation is used to deduce that the the third one (energy stored as body fat) is forced to change. But the caloric intake is, actually, the only input in the “energy balance” model: energy expenditure and energy accumulation are outputs/results/consequences, not inputs/variables under our control. They deduct what is cause and what is effect from a mathematical equation when causality can only be inferred from the knowledge of how this particular system works.
    2. without any possible justification, they use the term “body fat” in the energy balance equation, instead of “energy accumulation”. The result of this is that two terms of the energy balance equation are related to the human body as a whole, but the third one (and also the conclusions) are related to a specific tissue. As I said before: unjustifiable.
    3. they perform a one-dimensional problem analysis, one that misleadingly only takes into account the “energy” variable and, logically, this approach is a blind alley in which the only conclusion that can be reached is to identify the calories as cause or solution for our obesity problem.

Moreover, the data that Guyenet is using is epidemiological, i.e. statistical data from a population. These data aren’t from a controlled experiment’s output. In this case, not even the caloric intake is necessarily an input, a cause: a priori it is only an effect, an observed symptom. Nobody here has carried out a controlled experiment in which the caloric intake has been increased: we are observing that the caloric intake has increased in the last decades, because of an unknown cause. There is no rational basis supporting Guyenet’s claims, which are the idea that two of the terms of the energy balance equation have changed and then, as a consequence, the third one has been forced to change.

An inappropriate food composition (i.e. the presence of sugars, grain flours, added chemicals, etc.) could have simultaneously induced fat accumulation —-per se, independently of the calories consumed—, an increase in the caloric intake (which in turn aggravates the body fat accumulation) and a reduction of the physical activity levels. The laws of thermodynamics can’t say what is cause and what is effect, nor do they impose a relevant role for energy, neither as a cause nor as a solution to the problem of obesity. The idea that “calories count” is not derived from the thermodynamics laws, and therefore it needs to be proved. I believe it is really significative that when evidence is presented to defend this theory, it is always false.

Although I have written repeatedly about all these sophisms, there is one of them that I consider critical:

from a tautology (i.e. saying the same in a different way) it is inferred that gaining or losing weight are energy balance issues, and that talking about calories is unavoidable.

“If you eat more calories than you burn, you will gain weight”


The best way to explain the deception is, probably, to apply the same reasoning to a different tissue, e.g. muscle mass:

the laws of physics tell us that muscle mass can’t get bigger unless you eat more than you spend, so the increase in muscle mass happens as a result of a caloric intake that is excessive for your energy needs

You know it is wrong. You know that there is a “trick” in the reasoning. You know that the laws of physics don’t say that the muscle mass increases because you eat too much and move too little, and nobody can convince you of that, no matter how skilled they are playing with words. You understand that, when talking about the muscle tissue, it is absolutely stupid to use the energy balance theory to infer the cause of the growth. Once you realize that facts, nobody will ever convince you that using the laws of physics is a must when talking about the adipose tissue.

If you consume more calories than you burn, will your muscles grow?

What is wrong with the above sentence? This is not a rhetorical question: it is an important one. Can you explain the fallacy?

The carrot, the stick and the string

In one of my favourite blog posts, ““, I use the analogy of a man attached to a carrot by means of a stick and a string (see image below). What I try to to illustrate with the analogy is how solutions for a problem derived from inviolable laws of physics, can be undeniably stupid. As we will see next, a key in the fallacy is assuming a value for a parameter that is not actually under our control.


Referred to the picture above, are the following statements true or false?

If you run faster than the carrot, you’ll reach it.

If you run slower than the carrot, it will eventually disappear from your sight.

Reaching the carrot is about managing your speed relative to the carrot’s speed. Creating a speed surplus is the way to reach it, while a speed deficit will make it move away from you.

Disassembling the stick that links you to the carrot is useless, because unless your speed is greater that the carrot’s you won’t reach it.

Are you still not persuaded that speed is the key to solve the problem?

all you need is to know is the carrot’s speed and then move faster than it. Let’s say that the carrot is moving at 1 km/h. In this case, you only need to move a little faster, for example at 2 km/h, and I can guarantee that you’ll reach the carrot. It really is as simple as that.

Do you disagree with this? May be you think that it is possible to reach the carrot without being faster than it is? I’m sorry to break this to you, but that would violate the laws of physics and you can’t do that.

Is it true that if you run faster than the carrot you’re going to catch it? Yes, it is, but it is a sophism , because this solution is only correct in appearance, since it is unrelated to the specifics of the problem. Any reference made to the carrot’s speed should be making clear that this magnitude is an observed output, instead of giving the impression that it is an input with a specific value or that we can force a positive or negative difference relative to another parameter.

According to logic, what is the relationship between the man’s speed and his distance to the carrot? Does logic say that managing his speed is the way to reduce that distance? Do the laws of physics tell us that any solution that works does so simply because it helps us increase our speed?

If the laws of physics say always exactly the same thing, whether there is or there isn’t a stick that links you to the carrot, can these laws be useful in any way to solve the problem?

The laws of thermodynamics are exactly the same regardless of the physiological mechanism used by an adipocyte to grow! What on earth made us believe that these laws can be useful for understanding or curing obesity? Nobody uses them with any other growth of a tissue. Isn’t that fishy?


We are nothing else than arrogant morons. If we ask a child for help on how to reach the carrot, he/she will not say that you have to create a speed surplus. Moreover, the “speed” concept won’t even cross his/her mind. And he/she will solve the problem. The fact that a law of physics is inviolable, doesn’t mean that that law is necessary, nor useful nor relevant to solve a problem. In my opinion, the people that defend the use of the laws of thermodynamics in nutrition are themselves the problem and will never be the part of the solution.

If you consume 2000 kcal/day and your expenditure is 1950 kcal/day, you will gain weight. If you have that same energy expenditure and you consume only 1900 kcal/day, you will lose weight.

Did we gain weight because we consumed more calories than we expended? Can you tell now how, from a tautology that tells us nothing useful, has the energy balance pseudoscience been built?

Further reading:

Sugar-sweetened beverages and obesity

DAILY calories from sugar-sweetened beverages among U.S. adults (1980-2010):

imagen_0462 (source,source)

CUMULATIVE TOTAL increment in the percentage of obese adults (orange stars) versus CUMULATIVE TOTAL calories from sugar-sweetened beverages (blue line; numerical data not shown in the figure):

Are these data consistent with an important effect of sugar-sweetened beverages on body weight? Do they suggest, on the contrary, that sugar-sweetened beverages are highly unlikely to be an important cause of obesity?

Further reading:

Guyenet refutes the idea that sugar causes obesity

Assume that each year you gain an amount of body weight that is directly proportional to the amount of sugar you eat. Or, in other words, if you consume 100 g/d of sugar and you fatten a few kilos, if you eat 50 g/d of sugar, you fatten half that amount.

Suppose you’ve been consuming more and more sugar and you were getting fatter. Your consumption peaked at 110 g/d. Nevertheless, in the last 15 years your consumption has gone down progressively, and today you are eating a little less than you used to: 95 g/d. What is the expected evolution for your body weight? Under the assumption that sugar is making you fatten, your body weight is expected to go on rising, but at a slightly lower rate.

That is what I show in the graph below, created assuming that fattening is directly proportional to sugar intake. The blue curve represents sugar consumption (grams/day); the stars show what the body weight would have been in case we hadn’t changed the sugar consumption trend 15 years ago; the orange curve shows the actual body weight evolution (assuming that instead of consuming more and more sugar, we have progressively and slightly reduced our consumption in the last 15 years, as indicated by the blue curve):


Again, if sugar is fattening, what effect would be expected if our consumption were reduced? We would keep getting fatter, but at a slightly lower rate. That is what the orange curve in the graph above confirmed.

A few days ago (see) Stephan Guyenet, PhD wrote an article trying to refute the idea that sugar is fattening us. In his view, the explanation is simpler than that: we eat too much unhealthy food because we like it. His is just another version of the pseudoscientific energy balance theory.

One of the arguments presented by Guyenet is that added sugar intake has declined between 1999 and 2013, but the percentage of adult obese has not. He says, those facts make “highly unlikely” that sugar is the primary cause of obesity. This is the graph he uses as proof:

His reasoning is that if consuming 110 g/d of sugar makes us fatten, consuming between 95 and 110 g/d should make us lose weight! Since epidemiological data says we kept getting fatter and fatter, he concludes that  sugar is “highly unlikely to be the primary cause of obesity”.

Americans have been reining in our sugar intake for more than fourteen years, and not only has it failed to slim us down, it hasn’t even stopped us from gaining additional weight. This suggests that sugar is highly unlikely to be the primary cause of obesity or diabetes in the United States, although again it doesn’t exonerate sugar.

What he is saying is that if hitting your head against the wall ten times produces pain, hitting your head against the wall only nine times shouldn’t be less painful, it should be pleasant. If you realise it is not pleasant, if you realise nine times is still painful, albeit to a lesser extent than doing the same ten times, this suggests that there is no relationship between the hitting against the wall and the pain you suffer. Extremely stupid reasoning.

Moreover: between 1980 and 1999, sugar consumption was in the 85 to 110g/d range and people gained weight. Guyenet says that between 2000 and 2013, when sugar consumption was between 95 and 110 g/d, body weight should have decreased.

On the other hand, note that Guyenet interprets data from the graph as if it were a controlled experiment, when it is just observational data. No controlled experiment was carried out.

Note also that the y-axis for the blue curve in Guyenet’s graph doesn’t begin with zero g/d, and this makes the decrease in sugar intake seem greater than it actually is.

Edit (1/18/2017): there is a second part of this article, providing a more thorough explanation:
If your today’s sugar intake is lower than yesterday’s, do you slim down?


Further reading:

Bad nutritional science (II)

Some time ago I wrote a critique (“Bad science“) of a meta-analysis that analyzed the effectiveness of low-carb diets, entitled “Low Carbohydrate versus Isoenergetic Balanced Diets for Reducing Weight and Cardiovascular Risk: A Systematic Review and Meta-Analysis“. That blog entry was one of the most visited pages of this blog in year 2014.

At the time I checked a few, not all, of the original data sources used in the meta-analysis, finding several blatant “mistakes” (were they really “mistakes”?). We found mistakes in Figure 3 and we found that the most influential data of Figure 4, from Sacks 2009, was reversed: it should favor low-carb diets, and not the opposite. An important “mistake”.

I would like to add a few comments on the meta-analysis and the data it uses.

Lim 2010

Out of curiosity I checked another article used in Figure 4 of the meta-analysis, which is denoted as Lim 2010. Apparently in that study a “balanced” diet was better for weight loss than a “low-carb” diet.


Was it really so? I have my doubts about that.

The study is from year 2010, entitled “Long-term effects of a low carbohydrate, low fat or high unsaturated fat diet compared to a no-intervention control

Three diets are compared with a control group. One of those diets is supposedly low in carbohydrates, the one they call VLC. The following graph shows the body weight evolution in the different groups (for the control group only only baseline and final values are shown, with a hollow circle):

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The text at the bottom of figure 2 says one of the diets is identified with dark circles, but there are no dark circles in the graph. That makes me doubt about what curve corresponds to each diet. Fortunately, the baseline body weights for the different groups are given to us in Table 1, and they are different for each group, allowing us to identify the curves:


  • The curve with the lowest baseline value corresponds to the VLC diet,
  • The curve with the highest baseline value corresponds to the HUF diet, and
  • The curve  with a baseline value similar to that of the control group is the VLF diet.

Therefore, in the figure, the total change in body weight experienced with the VLC diet (the one supposedly low-carb) corresponds to the red straight line. The other two diets correspond to the blue (HUF) and green (VLF) straight lines.

What diet produced a bigger weight loss? Apparently that was the VLC diet, the one with a more negative slope. That doesn’t match the data included in the meta-analysis:


The origin of the discrepancy is that Lim et al. gave three different versions of the results: a) the one we have seen in Figure 2, b) what they say in the text of the article and c) data from Table 3.

In Table 3 we are told is the HUF diet the one that resulted in more weight loss after 15 months.


And the values in the text are also different and clearly wrong, at least in the error values (0.1 and 0.01 kg?):

The estimated weight change from baseline to 15 months was 3.0 ±0.2 kg for VLC, 2.0 ±0.1 kg for VLF, 3.7 ±0.01 kg for HUF.

These standard deviations values of 0.1, 0.2 and 0.01 kg can also be found in the abstract of the article. They are clearly wrong.

What data do we believe? data from the graph, from the table or from the text? At least two of these three sources are wrong. Perhaps all of them are wrong. The authors of the meta-analysis chose the data from table 3, but in my opinion, in the absence of an explanation, Lim 2010 data is useless.

I don’t understand why only data from the HUF diet, the one supposedly better than the VLC diet (according to table 3), was included in the meta-analysis, but not data from the VLF diet, the one supposedly worse than the VLC diet (according to all the sources), although the percentages of macronutrients of the VLF and HUF diets are very similar. Even if we believe data from table 3 is the data without errors and data from Figure 2 and from the text are wrong, the VLC diet would be as good as the other two diets, if both of them are considered. But, I insist, the VLC diet is the best if we use data from Figure 2.

Moreover, the VLC diet was hardly a low-carb diet, with a percentage of kcal from carbohydrates that increased as time went by. It was only really low-carb at the beginning of the study:



For example, at 15 months 0.365 * 1635 kcal = 597 kcal, what gives us 149 g of carbohydrates. Too many carbs for a low-carb diet.

Do we link the result of this study to a low-carb diet, when in fact the participants didn’t follow a low-carb diet? That is actually the main flaw of the meta-analysis (apart from all the errors we found in the data, which coincidentally always make low-carb diets’ results seem worse), that the authors consider as “low-carb diet” a diet that people who follow low-carb diets wouldn’t say are low-carb. That mistake creates misinformation.

On the other hand, the diets were supposedly isocaloric, but the reality is that the VLC group (red curve) had a caloric intake bigger than the HUF group (blue curve). The diets were NOT isocaloric. Values shown in kcal/day for 3, 6, 9, 12 and 15 months.

In short,

  • there are three different versions of weight loss results. At least two of these sources, or may be all of them, are wrong.
  • the VLC diet  was not low-carb, except for the first months
  • the diets were not isocaloric, with differences in kcal/day with an order of magnitude that may have consequences in the long term. The meta-analysis is supposed to use only data from isocaloric diets.
  • the authors of the meta-analysis only used data from the HUF diet, the one that they believed was better than the VLC diet. They didn’t include data in the meta-analysis from the diet that supposedly was worse than  the VLC.

As a final comment on this article, if the authors of the meta-analysis had to choose between the data from table 3 , from figure 2 or from the text, among those three possibilities they chose the option more unfavorable for the low-carb diets, data from table 3. May be we can’t be blame them for not realizing the absolute disaster that Lim 2010 data was. But when processing data from table 3, without a clear reason, they only used data from the diet they thought was better than the VLC diet, ignoring data from the diet they thought was worse than the VLC diet. May be they didn’t see the inconsistencies between figure 2, text and table 3, but for sure they saw there was another diet in table 3. And they made the decision to ignore that diet.

Keogh 2007

I have doubts about another article used in figure 4 of the meta-analysis. The study has only 13 participants, Keogh 2007, but there is another one from the same authors with many more participants.


About 130 g/day of protein in the study not included in the meta-analysis, 134 g/day in the study included. Both with the same duration, 52 weeks.

The article to which I am referring is “Long-term effects of a very-low-carbohydrate weight loss diet compared with an isocaloric low-fat diet after 12 mo” (Brinkworth 2009), and there are 69 participants that completed the study, not 13. 1.9 kg of body fat were lost with a low-carb diet (LC), a real low-carb diet, with roughly the same calories than the low-fat diet (LF). More body fat loss, with basically the same calories. This article, with a mean difference between diets of 2.9 Kg in body weight and 69 participants would have had a big weight in the final result of the meta-analysis.

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Diets were isocaloric, although it was not pretended. As a matter of fact caloric intake differences between diets were lower than in the study of Lim et al 2010 we analyzed before (and that study was included in the meta-analysis). In any case Brinkworth 2009 was not discarded for that reason: according to table 7 of the meta-analysis, Brinkworth 2009 is excluded because it is “Duplicate and/or complimentary”, but this study has nothing to do with the studies used in figure 4. All the trials have a different registration number: therefore Brinkworth 2009 is not a duplicate nor complementary of any of them:

  • Brinkworth 2009. Trial ACTRN12606000203550. E.g. 391 people responded to the announcement, 69 participants completed the study
  • Wycherley 2012. Trial ACTRN12606000002583. E.g. 1150  people responded to the announcement, 68 participants completed the study
  • Keogh 2007. Trial ACTRN012605000614695 (this one is the study with 13 participants)

I didn’t include Layman 2009 in the list above this line because it is an article from a different set of authors. Since the results found in Brinkworth 2009 are clearly favourable to the low-carb diet, it is impossible that the authors of the meta-analysis could think it is a duplicate/complementary of Keogh 2007. The only possibility then, is that they believe that there is a conflict with Wycherley 2012, a study with a different registration number, different number of participants and published three years later. If, for some reason I can’t see, they decided to choose between those two studies, they chose the one with a less favorable outcome for low-carb diets.

Layman 2009

Although it has no relevance, because it doesn’t affect the mean result of the meta-analysis, there is another study included in figure 4, Layman 2009, from which “intention-to-treat” (ITT) data is used, i.e. made-up data. By chance, that fact doesn’t change the difference between diets, 2 kg, but it gives a weight to this study in the computations that it doesn’t deserve, because instead of 71 participants, which is the actual data, they suppose there are 103, that are the total participants once made-up data is added. And the ITT data have a lower standard deviation than the actual data, making made-up data seem more reliable than actual data. That is outrageous!


The “intention-to-treat” philosophy, where data is made-up for non-completers, may be seen as acceptable by “scientists”, but we, “normal” people, can only think of it as a joke (see).

I insist that using ITT data probably didn’t affect that much the meta-analysis result, but I want to make the point that false information is shown to us as actual data from a scientific experiment. “Intention-to-treat” data are not results from an experiment, they are a product of the authors’ imagination. It is unacceptable to use them as results from a scientific experiment.

Finally, I want to thank Andrés for his insightful suggestions.

Further reading: