I make mistakes, and acknowledging and correcting them is an important part of how I grow. On this page, I list every mistake I know of in my book The Hungry Brain, and whether they have been corrected in the paperback edition. Thanks to everyone who has pointed out mistakes!

I’m certain there are more I haven’t caught yet. If you spot one, please let me know and I’ll add it to the list.

1. P. 44. The book refers to the psychological concept of punishment as “negative reinforcement”. Negative reinforcement is a psychological concept as well, but not the one I intended to refer to in that passage. This has been corrected in the paperback version. Pointed out by Rebecca Strickland.
2. P. 51. The book states that “Humans have a strong preference for salt (sodium chloride)– one inclination we don’t share with rats.” I discuss this further in the associated footnote. I don’t think this is a mistake exactly because rats don’t enjoy salty food like humans, but Anthony Sclafani pointed out to me that rats do prefer to drink a dilute salt solution to plain water. I removed the statement in the paperback.
3. P. 54. In a footnote, the book states that the Diagnostic and Statistical Manual of Mental Disorders is published by the American Psychological Association. It’s actually published by the American Psychiatric Association. This has been corrected in the paperback version. Pointed out by Sylvia Karasu.
4. P. 136-7. While discussing a rat study by Barry Levin and Ambrose Dunn-Meynell, I made two errors in describing the experimental diets. First, I stated that the researchers “restricted their food intake while keeping them on the palatable diet”. In fact, the rats were switched back to unrefined rodent chow during the restriction period. Second, I stated that “they quickly bounced back up to the weight of rats that had been eating an unrestricted palatable diet and gaining weight the entire time”. In fact, the latter group was placed on an unrestricted palatable diet for 12 weeks, then unrestricted unrefined rodent chow for an additional 16 weeks, and were on chow when the other group was switched and the two groups converged in weight. Neither error impacts the substance of the passage. Pointed out by a friend of Gary Taubes, via Gary.
5. P. 171-2. I discuss a twin study of the genetic contribution to obesity conducted by Mats Borjeson and published in 1976, and the passage could be read as implying that he was the first to perform such a study. Twin studies on obesity were published prior to Borjeson’s study, as reviewed in the 1966 paper “A review of genetic and constitutional factors in human obesity“, by Carl Seltzer and Jean Mayer. I don’t recall who pointed this one out to me, but thanks, whoever you are.
6. P. 175. I attribute the quote “genetics loads the gun, and environment pulls the trigger” to Francis Collins. Although Collins said it, the quote is typically attributed to obesity researcher George Bray. This has been updated in the paperback version. Pointed out by Sylvia Karasu.

Gary Taubes argues that energy imbalance (calories in > out) does not cause obesity; rather, energy imbalance is a result of the fattening process. In this post, I evaluate this claim, which boils down to the question of which side of the energy balance equation is driving the other. A version of this debate has been happening within the obesity research community, including my corner of it, for decades. The truth is that while fat mass can clearly be changed by altering energy balance, and energy imbalance is required for obesity to occur, we don’t know for sure which side of the equation drives the development of common obesity. Current evidence suggests that energy imbalance probably drives obesity development, but the body fat regulatory system may drive energy imbalance and contribute to obesity development as well. Regardless of this, the evidence suggests that the primary body system in charge of the energy balance equation as a whole is probably the brain, not insulin or fat tissue.

I recently had a spirited debate on Twitter with journalist and low-carb diet advocate Gary Taubes about the energy balance equation. The debate relates to a long-standing difference of opinion about the implications and usefulness of the equation. Taubes’s arguments about energy balance have been persuasive to the general public, and a few researchers, so I think it’s worthwhile to address them. This was also an opportunity for me to clarify my own thinking.

What is the energy balance equation, and what is the claim about it?

The energy balance equation states that changes in the amount of energy in the body are equal to the amount of energy entering the body, minus the amount leaving:

Change in body energy = Energy in – Energy out

This equation is an expression of the first law of thermodynamics, it’s simple arithmetic, and it’s not in question. Since fat tissue is by far the most capacious and most modifiable energy storage site in the body, substantial changes in the energy content of the body are represented by changes in body fat mass.

The body of a person with mild obesity contains about twice as much energy as the body of a lean person of the same sex and height, and this difference in body energy content is accounted for almost exclusively (~92%) by differences in fat mass.* It is of obvious interest to understand how this extra energy arrived in the body.

On many occasions, including in his new book The Case for Keto, Taubes has expressed a dim view of how he believes the energy balance equation is interpreted by researchers:

As sceptics pointed out at the time, though, the energy balance notion has an obvious flaw: it is tautological. If we get fatter (more massive), we have to take in more calories than we expend— that’s what the laws of thermodynamics dictate—and so we must be overeating during this fattening process. But this tells us nothing about cause. Here’s the circular logic:

Why do we get fat? Because we overeat.

How do we know we’re overeating? Because we’re getting fatter.

And why are we getting fatter? Because we’re overeating.

And so it goes, round and round

Gary Taubes. BMJ 346:16-17. 2013.

The key claims in this passage are that the energy balance equation tells us nothing about what causes obesity (“this tells us nothing about cause”), and assuming that energy imbalance causes obesity because of the energy balance equation is illogical circular reasoning (“here’s the circular logic”).

The first thing that stands out to me is that I can’t recall having encountered in the scientific literature a circular argument like the one Taubes makes. I certainly don’t recognize it as a pervasive or fundamental way of thinking in my field. The common argument is that the energy balance equation implies that energy in > out causes obesity. That may be debatable but it isn’t circular. Taubes’s version is circular because he tacks on a series of self-referencing assertions that aren’t part of the original argument. In his telling, researchers answer questions about obesity by making assumptions that are based on one another.

Fortunately, researchers have a better way of answering questions than making circular assumptions: experimental evidence. For example, we don’t have to assume anything about energy intake– we can measure it. That’s how we know it’s typically higher in people with obesity. See this graph of accurately measured energy intake graphed against body mass index of 15 men of widely varying body fat levels.**

Likewise, we don’t have to assume anything about the impact of increasing energy intake on body fatness– we can measure it. That’s how we know increasing energy intake increases body fatness, regardless of whether the excess energy comes from carbohydrate or fat.

In the end, I don’t know what to make of Taubes’s circular argument. It’s obviously illogical but I don’t recognize it from the scientific literature, and it ignores quite a bit of relevant scientific evidence. I’m not sure who it’s arguing against. Maybe I’m missing something?

Nevertheless, I think there’s a logical idea in the passage that gets at an interesting question. So I’m going to steel-man it, which means to present the strongest, most charitable version of it that I can. Here goes:

• People often focus on the right side of the energy balance equation (energy in/out) as driving the left side (change in body energy). “She ate more, therefore she gained fat”.
• However, the equation itself doesn’t imply directionality.
• It’s possible that this is causally flipped in the development of common obesity, where the original cause is a biological process that drives fat gain, and energy imbalance is simply a tool serving that process. “Her body was ‘trying’ to gain fat, and this process caused her to eat more and/or reduced her metabolic rate”.
• If the latter scenario is true, it would be more appropriate to apply the word “cause” to the biological process rather than energy imbalance, since the former is ultimately driving the latter.

An analogy Taubes uses frequently is that of growth. In the case of a child becoming an adult, wouldn’t we say that the growth process is causing the child to eat more, rather than eating more causing the child to grow?

The argument is logical, but that doesn’t necessarily mean it’s correct in the context of common obesity. Let’s evaluate it.

Energy imbalance is causal, but that doesn’t necessarily mean it’s in charge

As mentioned previously, the body of a person with mild obesity contains about twice as much energy as the body of a lean person, and nearly all (~92%) of the excess energy is in fat tissue.*

According to physics and simple arithmetic, as expressed by the energy balance equation, this energy accumulation must result from energy imbalance (energy in > out). There is no other possible way for the extra energy to arrive in the body. Energy imbalance is required for the state of common obesity to develop. It is therefore causal, as opposed to just being an innocent bystander. That said, I acknowledge that there is an important semantic issue around how we use the word “cause”. I’ll come back to that.

Energy imbalance is also causal in the case of a child growing, because an adult’s body contains more energy than a child’s body. The normal transition from child to adult cannot occur without energy imbalance. But growth isn’t a very good analogy for obesity. One reason is that in obesity, excess energy in the body is the condition. The difference in the energy content of a lean body vs. an obese body is nearly all accounted for by the difference in fat tissue mass, which is the definition of obesity. That isn’t the case in development. A second reason the analogy fails is that increasing a well-nourished person’s calorie intake causes them to gain body fat, while increasing a well-nourished child’s calorie intake does not cause them to develop into an adult. Similarly, reducing calorie intake causes body fat loss but doesn’t cause an adult to regress back to a child. I won’t consider this analogy further.

I think the best way to think about obesity, and everything else, is as a causal chain (or causal web if you want to be fancy). Everything is caused by something, so whatever our variable of interest (e.g., body fatness), it was caused by one or more upstream factors, which in turn were caused by something else, ad infinitum. Each cause is a link in the chain. No matter what your model of obesity is, in order to explain the development of an obese body, energy imbalance has to be a link in the model’s causal chain. If it isn’t, you’ve run afoul of physics and arithmetic.

That said, I do think Taubes’s argument has some logic, and it comes down to the question of what is ultimately controlling the system. In a typical causal chain, there are some links that actively determine the system’s output, and other links that just transmit the signal. Another way of thinking about this is that some links “give orders” and other links just “take orders”. The logical piece of Taubes’s argument is that the energy balance equation itself doesn’t imply which side is giving orders, and which is taking orders.

Consider this example. The speed of a car is determined (in large part) by the amount of force its tires exert on the road. Tires cause a car to move forward. Yet if we want to understand why some cars tend to drive faster than others on a local highway, studying their tires won’t provide any insight into that: the tires are just taking orders from upstream links in the causal chain (axle, transmission, engine, accelerator, etc.). To understand why some cars drive faster than others, we have to focus on the part of the system that’s giving orders, which is the person behind the wheel.

But what do we apply the word “cause” to? This might seem like splitting semantic hairs, but I think it’s actually at the heart of this debate. Is every link in the causal chain a “cause”? Or does a link have to give orders to be a “cause”? Taubes appears to use the latter definition, others often use the former definition, and this causes the two sides to talk past one another. I believe this semantic miscommunication explains a substantial part of the disagreement.

I’ll give an example to make this more concrete. Here is a passage from a post on Taubes’s website, in which he quotes from a review paper written by my scientific mentor Mike Schwartz:

“Obesity, by definition, results from ingesting calories in excess of ongoing requirements,” Schwartz and his co-author write, and I’m arguing that any researcher who makes this statement for any reason other than to make the point that it’s meaningless and misleading is living and working in an energy balance paradigm — calories-in, calories-out.

Taubes interprets this passage as implying that energy imbalance is giving orders, leading him to heap contempt on it. Yet if one reads the paper, it’s about the biological regulation of fat mass and energy balance. Furthermore, the paper explicitly discusses the question of whether energy imbalance leads or follows in the development of common obesity, and concludes that the question is unresolved***.

Clearly, Taubes’s interpretation of the passage is not what the authors intended. The reason for the miscommunication is that the paper is making the uncontroversial observation that energy imbalance is a link in the causal chain of obesity, while Taubes interprets it as a statement about which side of the equation is giving orders. Taubes does this a lot, but in fairness I think the research community is often guilty of thinking/communicating less than optimally on this issue. In this particular case the context makes the intention clear, but that isn’t always true.

Extending the car analogy to obesity, the steel-man version of Taubes’s argument would state that yes, energy imbalance is in the causal chain leading to obesity, but it’s just taking orders. The left side of the energy balance equation– a biological process driving fat mass expansion– is what’s giving orders. That’s the theory, but is it correct?

What’s giving orders, and what’s taking them?

The first thing I’d like to point out is that the left and right sides of the energy balance equation could both be giving orders, and both be taking orders. The two possibilities aren’t mutually exclusive. And I think you can make a case for it going both ways. But even if the left side of the equation is giving orders, that doesn’t necessarily mean Taubes’s insulin-adipose mechanism is the explanation for it.

The second point I’ll make is that it can be difficult to discern which links in the causal chain are giving orders and which links are simply taking orders. In my opinion, this is a major challenge in scientific research. Let’s get back to the car analogy. Imagine that I conduct a study in which I pop the tires of one group of cars, but not a second group of cars, then I measure how fast the two groups drive. Examining the results, I might conclude that tires do in fact control the speed of a car, and therefore that tires are what determine why some cars tend to drive faster than others on my local highway. But even though my experiment demonstrated that tires are in the causal chain, my conclusion would be wrong because I haven’t demonstrated that tires give orders in the context I’m trying to understand.

Similarly, the examples that Taubes and others use to argue that insulin and adipose tissue “give orders” from the left side of the energy balance equation, rather than “taking orders” from the right side, are generally not from the condition of interest, common obesity. They’re from situations in which insulin signaling or adipose tissue function are pushed outside their normal operating parameters by experimental manipulation or disease, much like a car with popped tires: type 1 diabetes, insulin injection, mice with missing insulin genes or genetically manipulated adipose tissue function, etc. These experiments demonstrate that insulin and adipose tissue are in the causal chain of obesity, but not necessarily that they give orders in the context of regular people gaining weight.

When we examine the natural context– people living their normal lives and getting fatter or not– the picture suggests that insulin and adipose tissue are predominantly taking orders rather than giving orders:

• In people living their normal lives, circulating insulin level, and the insulin response to carbohydrate, don’t reliably predict who will gain weight and who won’t. A person with high insulin tends to gain about the same amount of weight over the years as a person with low insulin. It’s hard to understand how elevated insulin could be the primary cause of obesity, given these findings. That said, if insulin were playing a minority role it could be hard to detect in this type of study.
• The most unbiased and informative way I know of determining what’s “giving orders” in a natural context is human genetics research. Genome-wide association studies (GWAS) tell us which locations in the genome are correlated with specific traits in people living their normal lives, and examining the functions of the genes that happen to pop up tells us which systems are “giving orders”. For example, the genes that correlate with type 2 diabetes risk are primarily related to insulin signaling and the pancreas. This tells us that to a large degree, insulin signaling and the pancreas are the biological systems in charge of type 2 diabetes risk. The genes that correlate with height are related to growth of the skeletal system and connective tissues. In obesity, the genes that correlate with body fatness are predominantly related to the brain, not to insulin or adipose tissue. This suggests that in the case of common human obesity, the brain is the primary body system that’s giving orders, and insulin and adipose tissue are primarily taking orders.

This shouldn’t be particularly surprising, since the brain is already known to control both sides of the energy balance equation: it generates eating behavior, including what and how much we eat. It generates physical activity. It regulates metabolic rate. And it’s the only organ in the body known to contain a regulatory system for fat mass.

The brain is the body’s professional information-processing organ and it performs many functions that evolved to satisfy our ancestors’ needs related to energy and food. We can divide these into “homeostatic” and “non-homeostatic” functions that map onto the left and right side of the energy balance equation, respectively. Any control system can fail when placed outside its normal operating parameters, and these systems didn’t evolve for the modern context. Both homeostatic and non-homeostatic brain functions tend to favor overconsumption and maladaptive body fat gain in today’s world, as I describe in my book.

However– importantly– this still doesn’t tell us which side of the energy balance equation is giving orders. It remains possible that the left side is giving orders, but the brain is in charge of it. In fact, this is what people in my corner of the obesity research world (energy homeostasis) have been arguing might be happening for decades: the brain is in control of energy balance, so we should try to understand how that regulatory process is altered in obesity.

How do we answer this question? Let’s consider it from another angle. If energy balance is giving orders rather than taking them, we should be able to bring people from the obese state to the lean state, and from the lean state to the obese state, by changing energy balance alone.

Many studies (and many peoples’ experiences) have shown that reducing calorie intake causes fat loss, and if the cumulative calorie deficit is large enough, people can lose quite a bit of fat. At first glance, this seems like a home run for the argument that energy imbalance gives the orders. Certainly, there’s no doubt that energy imbalance has a powerful impact on fat mass!

However, when we look closer, the situation isn’t quite so cut and dried. The truth is that a person who has lost a substantial amount of fat is not the same as a person who had that leaner body all along. A weight-reduced person has a greater tendency to gain weight/fat, and when we look at this from the perspective of energy balance, we see that they have a hard time maintaining the lower calorie intake, and their metabolic rate has also slowed a bit more than their change in body mass would predict. In extreme cases, such as contestants on the weight loss game show The Biggest Loser, the decline in metabolic rate can actually be quite large. (As an aside, the tendency of a weight-reduced person to regain fat occurs in a state of reduced circulating insulin level.)

This is a phenomenon I call the “starvation response”, and it happens because body fat mass is biologically regulated. Current evidence suggests this regulation happens via the fat-regulating hormone leptin acting predominantly in the brain. Consistent with the genetics data, this is the only known system in the body that regulates fat mass. In my book The Hungry Brain, I review the research on this, which stretches back 180 years but has intensified since the discovery of leptin in 1994.

The “starvation response” to weight loss is an example of the left side of the energy balance equation giving orders, in addition to taking orders. When fat mass declines, there is a reaction from the body that seeks to modify energy balance in order to regain fat.

The situation is similar for fat gain. Increasing energy intake causes fat gain in scientific studies, but it’s hard to maintain substantial gains because the appetite reacts, pushing back against the change in energy balance. Whether or not fat gain via experimental overfeeding also causes a disproportionate increase in metabolic rate is controversial. It’s not difficult to cause a person to gain fat via overfeeding, but it seems to get more difficult the more you want them to gain, presumably because the body fat regulatory system “pushes back”. To some degree, this system protects against both fat loss and fat gain, but it’s obviously less effective at protecting against long-term fat gain in most people.

Insulin does not appear to play a key role in this process because overfeeding carbohydrate vs. fat has about the same effect on fat gain, despite different effects on insulin. Unlike the “starvation response”, the mechanism behind resistance to weight gain remains unclear, and is an active subject of research.

From all this, it’s clear that both sides of the energy balance equation can give orders that affect fat mass, and I think it makes a strong case that both sides do give orders in the context of voluntary weight loss. Yet, is experimental overfeeding an accurate model of the typical fattening process, or are we just popping tires? Does that scenario actually represent the process that causes common obesity in the real world? Here’s the truth: we don’t know for sure.

What we do know is that obesity consists of both a change in energy balance and a change in the biological system that regulates body fatness. Does energy imbalance cause fat gain, and the regulatory system adapts to higher fat mass over time, making it hard to slim back down? Or does the regulatory system go awry in the modern environment, driving fat gain and energy imbalance? Or both? It’s a chicken-and-egg question that we don’t yet have a definitive answer to.

We aren’t flying completely blind though. One way to examine this question is to see whether experimental overfeeding results in weight/fat gain that persists after the overfeeding period, or whether people shed all the excess weight. If people retain excess weight, it would imply that the regulatory system adapts to “defend” the higher level of fat mass, and in turn it would provide evidence that energy imbalance may be giving orders in the development of common obesity.

It turns out that people often do retain part of the excess weight/fat they gain during overfeeding. For example, Johannsen and colleagues overfed 35 young adults for 8 weeks, resulting in 17 pounds (7.5 kg) of weight gain and 9 pounds (4.2 kg) of fat gain. The researchers sent the volunteers home to live their normal lives, then measured their body weight and body composition six months later. At that point, they retained 43% of the excess weight they had gained during overfeeding, and a similar proportion of the excess fat.

This suggests that overfeeding had caused their body fat regulatory system to durably accept a higher “setpoint”. In turn, this implies that energy imbalance was probably giving the orders in this scenario. Some, but not all, other overfeeding studies have reported similar findings.

Experimental overfeeding might still seem like an artificial scenario, but consider that if we’re being honest, most of us “overfeed” ourselves periodically to some degree, meaning we eat/drink more than we need to because the food/drink is seductive, readily available, low-satiety, or for a variety of other reasons. Most annual weight gain in the US occurs during the 6-week holiday period, which represents only 12 percent of the year. On average, we lose some of that excess weight as we come out of the holiday period, but we retain some of it, to be built upon the next year. Our weight ratchets up a bit each year as a result of holiday eating, and the dynamics of it resembles a miniature version of experimental overfeeding.

This evidence isn’t definitive but it does suggest that energy imbalance probably gives orders in the development of common obesity, and therefore energy imbalance probably causes obesity under both definitions of the word “cause”. But this doesn’t exclude the possibility that the left side of the equation is also giving orders.

My guess is that both sides of the equation give orders in the real-life development of common obesity, but that the relative proportions depend on the person. But I don’t know for sure, and I doubt anyone does. This remains an important question for the research community. However, whichever side of the energy balance equation is giving orders, the brain appears to be the commander-in-chief of the equation as a whole.

I conclude the following:

• Energy in/out is causal in obesity, but in and of itself, that fact doesn’t necessarily mean it’s giving orders.
• In terms of modifying fat mass, both sides of the energy balance equation are able to give orders, and also take orders.
• In the context of voluntary weight loss, both sides give orders.
• In the context of people developing common obesity in the real world, we don’t have definitive answers about which side of the equation is giving orders. The evidence suggests that energy imbalance probably gives orders, but we don’t know whether the other side of the equation does as well. I suspect it’s probably both sides and the proportion depends on the person, but that’s just a guess.
• Regardless of which side of the energy balance equation is giving orders, the brain appears to be the commander-in-chief of the equation as a whole.
• Insulin and adipose tissue probably take orders, for the most part, although I don’t think current evidence rules out a minority role for them in giving orders.

Bonus: is the energy balance equation useful?

To those who do obesity research, the value of the equation is obvious: it helps narrow down the possible field of explanations for the body composition of a person or lab animal, or changes in body composition. For example:

• In people with obesity, energy intake and expenditure are typically higher than in people without obesity of the same sex and height. This tells us that common obesity is not the result of a reduced metabolic rate– a common but erroneous belief. It tells us that we should instead focus on mechanisms related to higher energy intake.
• The Hadza are a hunter-gatherer population in Tanzania, and they are characteristically lean. Although they have a higher physical activity level than a typical American, their overall energy expenditure is about the same as a typical American, after adjusting for the fact that their bodies are smaller and leaner. This tells us that higher energy expenditure due to exercise is not the reason they’re lean– we should instead focus on mechanisms related to lower energy intake.

These are just two examples off the top of my head; the energy balance equation has many applications in obesity research. If you want to understand body fatness, it’s valuable to understand the energy balance characteristics of your subjects of interest.

Acknowledgments

Many thanks to Kevin Hall and Karl Kaiyala for their helpful comments on a draft of this post.

Footnotes

*This can be estimated using a few simple assumptions. First, the energy density of fat is 86.9 MJ/lb, and the energy density of lean tissue is 16.72 MJ/lb. Then, assume two men of average height (5’9″), one who is lean (BMI 22, 149 lbs, 12% body fat) and one who has mild obesity
(BMI 32, 217 lbs, 30% body fat). This yields total body energy contents of 3,746 MJ and 8,197 MJ. The body of the man with obesity contains 2.2 times more energy than the body of the lean man, and 92% of the excess energy is contained in fat tissue. The number is not 100% because people with obesity tend to have more lean mass than people who are lean.

**The correlation is strong at R2 = 0.77. Calorie intake was measured over 18 days in a metabolic ward in people who were weight-stable. Data are from table 1 of this study. A similar relationship between BMI and energy intake has been reported in many other studies that measured energy intake accurately but indirectly by measuring energy expenditure in weight-stable people. The first law of thermodynamics (conservation of energy) allows us to convert between energy intake and energy expenditure in weight-stable people.

***This passage from the paper illustrates that the authors do not assume energy imbalance is “giving orders” in the context of common obesity. They describe the question as unresolved:

Another obstacle arises from a lack of scientific consensus regarding fundamental aspects of obesity pathogenesis. During caloric restriction, there is little question that reduced neuronal input from adiposity-related hormones activates responses (increased food intake, decreased metabolic rate) that favour recovery of lost weight. Whether the reverse is also true—that increased neuronal input from these hormones protects against weight gain—is hotly debated. Until this issue is resolved, the importance of several key observations, including CNS resistance to leptin and insulin documented in common forms of obesity, will remain uncertain. This is because if adiposity negative-feedback signals do not normally protect against weight gain, neuronal resistance to insulin and leptin cannot cause obesity. According to this view, the growing obesity epidemic can be attributed to an inherent lack of protection against obesity-promoting environmental factors, rather than to an underlying homeostatic disorder. Alternatively, if adiposity negative-feedback signals do, in fact, confer protection against obesity in normal-weight individuals, neuronal resistance to these signals must, by definition, favour weight gain, and unravelling the underlying causes takes on both pathophysiological and therapeutic urgency. As our understanding of normal and abnormal regulation of food intake and body adiposity grows in its sophistication, overcoming these obstacles will create new opportunities for therapeutic intervention.

Morton et al. Nature 443:289. 2006

April fools post!

A new study released today in the journal Nature upends our beliefs about Paleolithic peoples, suggesting that their diets may have been based solely on animal fat.

Previous research examining food particles in tooth plaque suggested that Paleolithic Homo sapiens and Homo neanderthalensis consumed a wide variety of plant and animal foods, leading to the belief that humans are natural omnivores. Yet new research suggests that while our ancestors may have chewed these foods, they probably didn’t swallow them.

Using the ratio of bismuth-84 to molybdenum-43 in six partially fossilized knee caps recovered from three European caves, a research team led by Nathan Hayes of the University of Pennsylvania was able to determine that the prehistoric humans ate no carbohydrate or protein at all, implying that their diet consisted entirely of fat.  Based on bones and tools found in the same strata, the researchers believe these populations harvested the fat of large mammals such as aurochs, mammoths, elk, and wooly rhinoceroses, leaving the meat to rot.

“We are very confident in our conclusions”, said Hayes.  “These people ate nothing but animal fat.”

The research community is stunned.  Liu Zhang, a Yale biochemist, remarked “The implications of this finding go far beyond nutrition.  It seems humans have a greater capacity to synthesize amino acids from fat than we thought.”

Hayes and his team believe the hunting grounds of Paleolithic humans in Europe were rich enough that they had no need to bother with inferior foods like plants and muscle tissue.  Herds of mammoths were so thick during this time that it was almost impossible to throw a spear without hitting one in the carotid artery.  Grains, legumes, fruit, and other plant foods were chewed for pleasure and to clean the teeth, but spat out rather than swallowed due to their inferior nutritional value.

Examining the kneecaps further, Hayes noted that the attachment points of their tendons were extremely robust.  “These guys were ripped”, exclaimed Hays.  “They definitely didn’t skip leg day.  Or maybe it was all the fat they ate.”

April Fools!!

This is a list of references I am likely to cite in my debate with Gary Taubes on the Joe Rogan Experience on March 19.  During the debate, I’ll be calling out numbers corresponding to the references below.  Scroll down to the number I mentioned to see the references for yourself.

Gary and I prepared a document explaining our models that you can download here.  For context, I am favorable toward low-carbohydrate diets, but the references below mostly reflect issues that Gary and I are likely to disagree on.

The brain

1.  The brain regulates body fatness

This is supported by a mountain of evidence going back 180 years.  The brain, and particularly a non-conscious part of the brain called the hypothalamus, contains the only known system in the body that regulates body fatness.  Damage to specific parts of the hypothalamus cause severe obesity or leanness in animals and humans, and experimentally controlling the activity of specific groups of neurons alters body fatness in animal models.  See these review papers for an overview of some of what we know.  I also give a lay-friendly overview of this research in my book The Hungry Brain.

Nearly all anti-obesity drugs that are currently approved by the FDA target the brain, including liraglutide, lorcaserin, phentermine/topiramate, and naltrexone/bupropion.  The only exception is orlistat, which reduces dietary fat absorption in the gut.  Interestingly, one of the most effective of these weight loss drugs, liraglutide, increases post-meal insulin secretion.

2.  The genetics of obesity point to the brain, not fat cells or insulin, as the primary determinant of body fatness

Obesity risk is strongly influenced by genetics, and recent studies have begun to uncover the specific genetic differences that make some people fatter than others.  This gives us the opportunity to see what these genes do, providing a window into the causes of common obesity.  Results show that gene variants that impact body fatness are primarily related to brain function— not primarily insulin or fat cells (although many mechanisms may contribute to a smaller degree).  Importantly, these (GWA) studies are unbiased because they examine the whole genome without preconceived notions about which genes or biological pathways might be important.

The largest and most recent study on the genetics of body fatness concluded that “[body mass index]-associated genes are mostly enriched among genes involved in neurogenesis and more generally involved in the development of the central nervous system.”

3.  The brain regulates appetite

This should be obvious, because appetite is a motivational state that is generated by the brain– like all motivational states.  In fact, we know so much about how appetite-regulating brain circuits work that researchers can turn appetite on and off at will by controlling specific types of neurons in animals.  Here are a few review papers that give a broad overview of much of what we know.  I give a lay-friendly overview of this research in my book The Hungry Brain.

4.  The determinants of appetite are complex and cannot be reduced to glucose and insulin

The brain determines hunger and satiety by in response to signals it receives from inside and outside the body.  From inside the body,  the brain receives information about the body’s energy status.  This comes from neural signals and hormones ascending from the small intestine, pancreas, liver, and fat tissue that tell the brain how much food is in the gut, what type of food it is, and how much fat the body contains.

From outside the body, the brain receives signals about what food cues surround you, and this can also stimulate hunger (think about smelling pizza).  All of this information is integrated by the brain, which uses it to generate the overall feeling of hunger or satiety.  For a review of some of the research on this see this paper.

5.  Lean people, and people with obesity, both “defend” their current level of body fatness against fat loss

When people lose fat, their brains initiate a sort of “starvation response” that favors the regain of lost fat over time.  This is familiar to most people who have dieted: increased hunger, more cravings, reduced metabolic rate, and eventual weight regain.  This is the brain’s response to fat loss, regardless of whether a person starts off lean or with obesity.  This suggests that the “setpoint” around which body fatness is regulated is increased in obesity, since the brain nonconsciously “defends” the obese state.  This is one of the key reasons why weight loss is challenging and often temporary.

We know this effect is due to a decline in the fat-regulating hormone leptin during weight loss, because replacing leptin to the pre-weight-loss level largely prevents this “starvation response”.  Therefore, the reason people with obesity “defend” a higher level of fat mass is that their brains require a higher level of leptin to feel like they aren’t starving.

6.  Single-gene mutations that lead to obesity in humans act in the brain

A number of single-gene mutations have been identified that lead to severe obesity in humans and animals.  These are all related to the brain systems that regulate body fatness, and particularly the fat-regulating hormone leptin.  I’m not aware of any mutations in insulin or fat cell-related genes that cause obesity.

Calories

7.  People with obesity eat, and expend, more calories than lean people

Studies using accurate methods consistently show that people with obesity eat, and expend, about 20-35 percent more calories than lean people, after correcting for height, sex, and physical activity level.  Calorie intake and expenditure increase continuously in parallel with body weight.  Since calorie intake is equal to calorie expenditure in a weight-stable person, measuring calorie expenditure is the simplest and most accurate way to demonstrate that intake and expenditure are both elevated.

8.  Reducing the calorie intake of a person with obesity to that of a lean person causes weight loss

People with obesity consume about 20-35 percent more calories than lean people.  Tightly controlled studies have demonstrated that restricting calorie intake by about this much in people with obesity causes rapid weight and fat loss, demonstrating that the elevated calorie intake is required to sustain the obese state.

9.  Calorie intake, not carbohydrate intake, is the main dietary determinant of body fat loss

Several controlled feeding studies have compared the effect of calorie-restricted diets with different proportions of fat and carbohydrate on weight and fat loss.  Fat loss is determined primarily by the number of calories in the diets, not the proportion of fat or carbohydrate, even when insulin levels differ substantially.  This was confirmed by a recent meta-analysis (study of studies) of 20 studies, which concluded that “for all practical purposes ‘a calorie is a calorie’ when it comes to body fat”.

10.  Changes in body fatness as a result of diet depend primarily on calorie intake, not carbohydrate intake

This was demonstrated by a meta-analysis (study of studies) of 20 tightly controlled studies in which people were fed diets that differed in carbohydrate and fat content, but not in protein or calorie content.  In other words, same calories, different carb:fat ratio.  Calorie-for-calorie, higher-carbohydrate diets led to slightly more body fat loss than higher-fat diets, but the difference was very small.  The researchers concluded that “for all practical purposes ‘a calorie is a calorie’ when it comes to body fat.”

11.  Energy expenditure (metabolic rate) is scarcely affected by differences in carbohydrate and fat intake

This was demonstrated by a meta-analysis (study of studies) of 28 tightly controlled feeding studies.  Altering the proportion of carbohydrate to fat in the diet had very little impact on metabolic rate when calorie and protein intake were the same, although metabolic rate was slightly higher on higher-carbohydrate diets.

A recent study received a lot of attention for finding that a very-low-carbohydrate diet led to a higher metabolic rate (+209 kcal/day) than a low-fat diet in people maintaining weight loss.  While this study was rigorous and innovative in many ways, some of the data it collected are clearly erroneous because they appear to break the first law of thermodynamics, which is physically impossible.  Once the erroneous data are removed, the effect size shrinks, loses its statistical significance, and becomes similar to the other 28 studies that were conducted before it.

Carbohydrate, sugar, and fat

12.  Low-fat, high-carbohydrate diets cause weight loss, even without deliberate portion control

The most rigorous study on this is the DIETFITS randomized controlled trial, which was partially funded by Gary Taubes’s organization NuSI.  In 609 people, a whole-food low-fat diet resulted in 12 pounds (5.3 kg) of weight loss at one year, not significantly different from the 13 pounds (6.0 kg) of weight lost on a whole-food low-carbohydrate diet.  Neither diet included advice to restrict calorie intake.  The low-fat diet supplied about twice as much carbohydrate, and 1.5 times as much sugar, as the low-carbohydrate diet, although neither diet was high in sugar.  It also had about twice the glycemic load.

Another study conducted at the University of Washington tested the effect of dietary fat restriction on calorie intake and body weight in 16 overweight people using very careful measurements.  When they were transitioned to a low-fat diet (15%) and told to eat as much as they wanted, their daily calorie intake dropped by 291 calories and they steadily lost weight and body fat over a 12-week period, losing 8 lbs (3.8 kg) total.  Importantly, their total carbohydrate intake increased from 253 grams per day to 318 grams per day.  Here’s the graph showing daily calorie intake and weight change (circles = calorie intake, diamonds = weight):

A meta-analysis (study of studies) representing 16 low-fat diet studies also reported that low-fat diets without deliberate portion control cause weight loss.

13.  A low-calorie diet composed almost entirely of refined carbohydrate, including sugar, causes substantial weight loss

This paper discusses 106 patients who lost an average of 140 pounds (64 kg) and improved their blood sugar control eating the “rice diet”, a diet composed almost entirely of white rice, fruit, juice, and white sugar.  Here is a photo of one man before and after the diet, from the paper:

The weight loss version of the rice diet was low in calories, supplied over 200 grams of mostly refined carbohydrate per day, and patients also increased physical activity.  This demonstrates that refined carbohydrate does not override the impact of calorie intake and physical activity on body fatness.

The rice diet was also effective for treating diabetes, whether or not it was calorie-restricted.

14.  Dietary fat can be fattening in a variety of nonhuman species

A review paper on this topic states that “With few exceptions, obesity is induced by high-fat diets in monkeys, dogs, pigs, hamsters, squirrels, rats, and mice.”  There are hundreds of studies demonstrating this, but the most conclusive one was published in 2018 by John Speakman’s lab.  They fed five different strains of mice diets varying in fat, carbohydrate, and protein content and showed that body fatness was primarily linked to the amount of fat the mice were eating.  Body fatness increased as dietary fat increased up to 60% of calories, and then body fatness declined as dietary fat increased further (this is consistent with other research showing that the very-high-fat, very-low-carb ketogenic diet promotes leanness in mice, as it does in humans).  Diets high in sugar and refined starch were not particularly fattening.  The takeaway is that the most fattening diet contains abundant fat and carbohydrate together, while diets at the extremes (very-low-fat and very-low-carb) are more slimming.

15.  Dietary fat can be fattening in humans

This really depends on context, since low-carbohydrate, high-fat diets tend to be slimming relative to diets that are high in both carbohydrate and fat.  Nevertheless, unrestricted diets rich in fat tend to lead to higher calorie intake and fat gain relative to unrestricted diets rich in carbohydrate.  This seems to be related to the high calorie density and palatability of fat.

Overfeeding fat under controlled conditions also causes body fat gain.

16.  Fat and carbohydrate are equally fattening when overconsumed

Two randomized controlled trials have reported the effect of overfeeding the same number of calories of high-carbohydrate vs. high-fat diets in humans, and both reported equal fat gain.

1. Horton and colleagues increased the calorie intake of volunteers by 50 percent by adding only fat vs. only carbohydrate for 14 days under tightly controlled conditions, and measured changes in body fat mass using gold-standard hydrostatic weighing. After 14 days, both groups had gained 3.3 lbs of fat, despite higher insulin levels in the high-carbohydrate group.  In the high-carbohydrate arm, most of the extra carbohydrate was refined starch and sugar.  In the high-fat arm, most of the extra fat was dairy fat (cream, butter).
2. Lammert and colleagues increased the calorie intake of volunteers by 1,194 calories per day for 21 days under tightly controlled conditions.  Subjects were fed either a high-carbohydrate (78% CHO, 11% fat) or a high-fat (31% CHO, 58% fat) diet containing the same amount of calories and protein, and the researchers measured changes in body fat mass using gold-standard hydrostatic weighing.  After 21 days, both groups had gained 1.8-1.9 lbs of fat.

17.  Sugar intake has been declining for 20 years in the US and 50 years in the UK, while obesity and diabetes rates have risen

Here is a graph showing sugar intake and the obesity rate in the US between 1980 and 2013.  The sugar data include all added sugars such as table sugar, honey, and high-fructose corn syrup, but not sugars naturally occurring in fruits and vegetables.

This graph illustrates the lack of correlation between sugar intake and obesity rates after 1999.  This decline in sugar intake has been confirmed by several independent lines of evidence.  The data suggest that sugar intake has dropped by 15-23 percent over the last two decades, primarily because people are drinking fewer sweetened beverages.  Diabetes rates have also increased during the decline in sugar intake.

Overall carbohydrate intake has also declined over the last two decades in the US:

This graph shows that sugar intake has declined by 22 percent in the UK over the last 50 years, while obesity and diabetes rates have increased substantially (prepared by Kevin Bass):

18.  Carbohydrate, fat, and protein intake in the US over the last century

This graph represents absolute carbohydrate, fat, and protein intake in the US since 1909.  It’s based on US Department of Agriculture data.

Note that fat is the only macronutrient that has consistently and substantially increased over time.  Carbohydrate intake declined in the 1940s-50s, rose again in the 1980s-90s, and has been declining since 1999.

Here are the same data, represented as percentages of total calorie intake:

Aside from a little bump in the 1980s and 1990s, as a percentage of calories the US diet has progressively become higher in fat and lower in carbohydrate.

19.  White flour intake was much higher in 1900 in the US than it is today

I downloaded this graph directly from the US Department of Agriculture website, although the web page I downloaded it from is no longer online.  It speaks for itself.  The large majority of this flour would have been refined, white flour from the late 1800s onward.

20.  Sugar intake in the US, 1822-2016

This graph represents added sugar intake, including honey and high-fructose corn syrup but not fruit sugars, from several data sources:

21.  Cultures with high intakes of sugar but otherwise healthy diets and lifestyles do not have obesity or diabetes

A well-studied Tanzanian hunter-gatherer population called the Hadza gets 15 percent of its average year-round calorie intake from honey, plus fruit sugar on top of it. This approximates US sugar intake, yet the Hadza do not exhibit obesity, diabetes, or cardiovascular disease.

Another mostly hunter-gatherer population, the Mbuti pygmies of the Congo, also ate large amounts of honey at the time they were studied:

The Mbuti of the Congo forests eat large amounts of honey. According to Ichikawa (1981), honey is their favorite food. At times, during the rainy season up to 80% of the calories in their diet come from honey.

They did not exhibit obesity or insulin resistance.

The Kuna of Panama are interesting because they generally have a non-industrialized diet and lifestyle, except that they obtain white sugar and a few sugar-containing foods via trade.  Their diet is 65 percent carbohydrate and 17 percent sugar (95 g/d), according to calculations I did based on dietary intake data.  That is more sugar than the average American currently consumes, although 62 percent of their sugar intake is from fruit.  The Kuna are lean and have excellent cardiovascular health.

This does not exonerate sugar by any means, but it does suggest that it is unlikely to be the primary cause of obesity, metabolic disease, and cardiovascular disease.

22.  During the Cuban economic crisis, sugar intake rose, calorie intake declined, and obesity plummeted

From 1989 through about 1995, the Cuban economy collapsed.  Calorie intake declined, fat intake declined, and the diet became very rich in sugar and other refined carbohydrates:

By 1993, carbohydrate, fat, and protein contributed 77 percent, 13 percent, and 10 percent of total energy, respectively, whereas in 1980 their respective contributions were 65 percent, 20 percent, and 15 percent (8). The primary sources of energy during the crisis were sugar cane and rice.

Sugar intake “rose to 28% of total energy intake“.  A shortage of gasoline meant that people began walking and riding bicycles more, such that total physical activity increased.  During this time, the prevalence of obesity decreased by about half, then eventually rebounded as the crisis resolved and the diet went back to normal.  The prevalence of underweight only increased slightly during the crisis, indicating that the decline in obesity was not due to widespread starvation.

23.  Cultures with very high intakes of carbohydrate tend to be lean, even if the carbohydrate is white rice

The traditional diet of most agricultural societies around the world is high in carbohydrate and low in fat.  Many of these cultures have been studied, and they are typically lean with low rates of diabetes and cardiovascular disease, even if they have abundant food.  The book Western Diseases: Their Emergence and Prevention contains many such examples.

In 1990, Staffan Lindeberg, MD, PhD conducted a detailed survey of the diet, lifestyle, and health of the residents of Kitava, a Melanesian island scarcely touched by industrialization. He found a diet based on starchy plant foods (African yam, sweet potato, taro, cassava), fruit, vegetables, seafood, and coconut, with 69 percent of calories coming from carbohydrate (compared to ~49% in the US currently).  Despite food abundance, none of the 247 Kitavans Lindeberg examined had obesity or diabetes, even in middle age and older.  They had no sign of cardiovascular disease and were unfamiliar with its symptoms.  Here is a photo of a Kitavan man being examined by Lindeberg (courtesy of Staffan Lindeberg):

The book Western Diseases: Their Emergence and Prevention contains historical data on the Japanese diet between 1950 and 1975, a time during which obesity was even more rare in Japan than it is today (p. 338).  In 1975, long after postwar food shortages were over, the Japanese diet was 62 percent carbohydrate, mostly from white rice.  The Japanese ate it daily as their primary staple food, and still do, yet the prevalence of overweight and obesity were, and continue to be, lower than any other industrialized nation.  People who emigrate from Japan to the US and begin eating a diet lower in white rice and higher in fat become much heavier, demonstrating that their leanness is not just genetic.

Cross-country comparisons show that nations with carbohydrate-focused diets tend to have the lowest obesity rates, while nations that eat a similar amount of carbohydrate and fat have the highest obesity rates (reproduced from this post with permission from Cian Foley):

There are certainly explanations for this besides macronutrients– such as poverty– but at the very least this shows that carbohydrate is not an overriding driver of fat gain.

24.  In human randomized controlled trials, sugar is only fattening by virtue of its calories

A meta-analysis of 30 randomized controlled trials reported that increasing sugar intake does not increase body weight unless total calorie intake increases. Importantly, calorie intake does often increase when people increase their consumption of sugar-sweetened beverages, so sugar-sweetened beverages aren’t off the hook.

Fructose is half of table sugar (sucrose).  A meta-analysis of 31 fructose feeding trials concluded that “Fructose does not seem to cause weight gain when it is substituted for other carbohydrates in diets providing similar calories. Free fructose at high doses that provided excess calories modestly increased body weight, an effect that may be due to the extra calories rather than the fructose.”

25.  In randomized controlled trials, low-carbohydrate and low-fat diets yield similar (unimpressive) long-term weight loss results

In real-life conditions, low-fat and low-carbohydrate diets both produce modest weight loss in the average person, usually less than 17 pounds at the 12 month mark.  Most meta-analyses (studies of studies) report that weight loss differences between the two diets are “minimal” at 12 months, although low-carbohydrate diets usually fare better up to 6 months.  The differences in weight loss between individuals on the same diet are much larger than the differences between diets.

People often dismiss these findings because the diets weren’t lower in carbohydrate.  This is a valid critique but it also applies to the low-fat diets used in these studies, which were typically not very low in fat.  Also, the fact that people usually don’t restrict carbohydrate or fat as much as instructed shows that most people find the diets hard to sustain in real life.

26.  Meta-analyses of ketogenic diet studies

In a quick literature search, I found one meta-analysis of ketogenic diet studies, which reports long-term weight loss after 12 or more months.  The ketogenic diets caused 2 pounds (0.9 kg) more weight loss than the low-fat diets.

27.  Adherence to ketogenic diets tends to be mediocre

A detailed review of the ketogenic diet literature concluded:

People who are left to their own devices generally do not adhere well to the diet. They typically start strong, but have a hard time adhering to the diet after 1-3 months. Carb intake increases and ketone levels drop.

I have little doubt that better adherence would lead to greater weight loss, but this is true of any weight loss diet.

28.  The Virta Health study

The Virta Health study is a non-randomized, controlled trial that reported outcomes for people with type 2 (common) diabetes who followed a ketogenic diet with intensive diet and medical support, vs. care as usual.  At one year, participants in the ketogenic diet arm lost 30 pounds (14 kg), lowered their average blood glucose substantially, and greatly reduced their need for diabetes medications other than metformin.  Metabolic and cardiovascular risk markers, and the low adverse event rate, suggest that the diet was safe over this period of time.  Two-year outcomes suggest that people had begun rebounding back to their original weights and health, but maintenance was still good by the standards of diet interventions.

The Virta Health study reports findings that are quite a bit more impressive than other studies of low-carbohydrate and ketogenic diets.  Here are a few reasons why that might be the case:

• Non-randomized trials like the Virta Health study tend to report better results than randomized trials because people self-select into the group they prefer.
• Participants may have been highly motivated because they had type 2 diabetes and the Virta Health program is expensive.
• The Virta Health program provides intensive support to help people adhere to the diet, so adherence was better than in most studies.

29.  Eating sugar does not impair weight loss on calorie-reduced diets

I am aware of three weight loss studies that have compared the weight loss response in people eating different amounts of sugar.  All three reported that sugar had no impact on weight loss in the context of calorie restriction.  One of the studies compared a diet that was 43 percent sugar (sucrose) to one that was 4 percent sugar.  Both diets caused the same amount of weight and fat loss over 6 weeks.

Diabetes

30.  Weight loss greatly reduces the risk of developing type 2 (common) diabetes

This was conclusively demonstrated by several large, multi-year, randomized controlled trials with actual diabetes diagnoses as the endpoint.  One of these trials was the Diabetes Prevention Program study, in which modest weight loss with a calorie-restricted low-fat diet and exercise caused a 58% reduction in the risk of developing diabetes over 2.8 years in 3,234 people with prediabetes.  The benefit was largely explained by weight loss, and it was still detectable 15 years later.  The diet focused on fat and calorie reduction and was not low in carbohydrate or sugar.

At least four other randomized controlled trials, conducted in four different countries, in people of different races and ethnicities, produced very similar results.

31.  Reducing fat intake, without reducing carbohydrate intake, causes weight loss and reduces type 2 (common) diabetes risk

The drug orlistat reduces the absorption of dietary fat in the gut by about 30 percent, without impacting carbohydrate absorption.  Large, multi-year placebo-controlled randomized trials have shown that orlistat causes weight loss and reduces the risk of developing type 2 diabetes by 37 percent.  This demonstrates that weight loss and protection against diabetes can occur as a result of reducing fat intake, without reducing carbohydrate intake.  Orlistat is a FDA-approved weight loss drug.

32.  Exercise substantially reduces the risk of developing type 2 (common) diabetes 

This was conclusively demonstrated by the Da Qing trial, a 6-year randomized controlled trial.  The trial reported that increasing exercise reduces the risk of progressing from prediabetes to diabetes by 46 percent.  A second randomized controlled trial reported that two years of supervised aerobic exercise reduced the risk of developing type 2 diabetes by 72 percent, and resistance training reduced the risk by 65 percent.  The fact that the exercise was supervised is important– it means the participants actually did it.

33.  Weight loss via a temporary very-low-calorie diet durably puts type 2 (common) diabetes into remission

This was conclusively demonstrated by large, a one-year randomized controlled trial in people with type 2 diabetes.  The intervention was 3-5 months of a very-low-calorie diet (825–853 kcal/day of a beverage, 59% C, 13% F, 26% P) followed by diet/lifestyle support for the remainder of the year.  This caused diabetes remission in 46 percent of people.  In other words, 46 percent of people were able to eat normally again and go off medication without experiencing diabetic blood sugar levels for months after the end of the low-calorie diet.  Among those who lost the most weight, 86 percent went into remission.

Insulin and insulin resistance

34.  Insulin resistance predicts a variety of age-related diseases

In 2001, Gerald Reaven’s group published a very simple but powerful study.  They directly measured insulin sensitivity in 147 lean and overweight middle-aged people and waited 6 years to see who got sick, who died, and who didn’t.  In the third of the group that was the most insulin resistant, 36 percent developed a health condition or died over the next 6 years, while in the third of the group with the least insulin resistance, none developed a health condition or died.  The health conditions that occurred in the insulin-resistant group included high blood pressure, coronary heart disease, stroke, cancer, type 2 diabetes, and death.

35.  People with higher insulin levels don’t gain more weight over time than people with lower insulin levels

Many studies have measured insulin levels in an attempt to predict who will gain weight and who will not.  Some studies have measured fasting insulin levels, others carbohydrate-stimulated insulin levels.  These studies were collected together in a review paper.  The research overall suggests that there is no reliable connection between current insulin level and future weight gain.  Of the 22 studies included in the review, 5 reported that higher insulin is correlated with more weight gain, 9 reported no correlation between the two, and 8 reported that higher insulin is correlated with less weight gain.

36.  Weight loss increases insulin sensitivity, regardless of whether it’s achieved by a low-fat or low-carbohydrate diet

This was demonstrated by a randomized controlled trial in 2009.  The low-fat (60% carbohydrate) and low-carbohydrate (20% carbohydrate) diet groups each cut about 500 calories per day and both lost about 9 pounds (4 kg) of body fat over 8 weeks.  At the end, insulin sensitivity improved, with no significant difference between groups.  Importantly, this study used a gold-standard method for measuring insulin sensitivity, making this result more informative than the vast majority of other low-fat vs. low-carb studies, which tend to indirectly estimate insulin sensitivity using the less reliable HOMA method.

This finding is echoed by an earlier randomized controlled trial in which a 21-day low-fat vs. low-carbohydrate diet, without weight loss, yielded no differences in insulin sensitivity in people with mild type 2 diabetes.  This trial also used a gold-standard measure of insulin sensitivity.

37.  Insulin resistance is “an appropriate response to nutrient excess“

Exposing cells and tissues to excess energy causes insulin resistance, regardless of whether the excess energy comes from carbohydrate (glucose), fat (fatty acids), or protein (amino acids).  This probably happens because excess energy is toxic to cells, so cells turn down their insulin responsiveness in order to take in less energy.

Nutrient excess causes insulin resistance in intact humans as well.  Temporarily increasing circulating levels of fat, carbohydrate, or protein in human volunteers markedly impairs their insulin sensitivity.

38.  When fat cells “fill up” due to fat gain, energy spills over onto other tissues, causing insulin resistance

As fat tissue expands, fat cells become less effective at taking up fat, especially after meals, and this fat spills over onto other tissues.  Depending on underlying genetic factors, different people have different “personal fat thresholds” at which fat gain causes their fat tissue becomes less effective at trapping fat, resulting in insulin resistance and often diabetes.

39.  The impact of foods on blood glucose and insulin has little do with how filling they are

This was most clearly demonstrated by a study that fed people the same number of calories from 38 common foods, including bread, potatoes, beans, meat, fruit, peanuts, candy, and pastries, and measured fullness ratings for two hours.  Fullness was unrelated to blood glucose responses, and weakly related to insulin responses (higher insulin release correlated with greater fullness).

In contrast, simple food properties like calorie density, protein content, and palatability were strongly related to fullness.

40.  Insulin resistance is caused (in large part) by exceeding the unique storage capacity of your own fat tissue

Studies have examined the genetics of insulin resistance, giving us insight into the biological pathways that underlie insulin resistance in the general population.  These studies tend to find that gene variants that reduce the storage capacity of fat tissue are associated with insulin resistance.

People with different genetic backgrounds tend to develop diabetes at different levels of body fatness.  For example, people of South Asian descent do not need to gain as much fat to develop diabetes as people of European and West African descent.  Together, this suggests that each person has a “personal fat threshold“, and if they gain fat beyond that threshold, their fat tissue is no longer able to contain fat effectively, it spills over onto other tissues, leading to insulin resistance and a high risk of diabetes.

41.  Mendelian randomization studies on the impact of insulin level on body fatness

Mendelian randomization is a genetic technique that can help to understand the relationship between risk factors and health conditions.  Several such studies have examined the relationship between insulin secretion and body fatness.  The first two reported no effect of insulin secretion or fasting insulin level on body fatness.  The third study reported that insulin secretion increases body fatness, but that this mechanism only accounts for 1-10 percent of between-person differences in body fatness.

Thus, all Mendelian randomization studies to date suggest that the impact of insulin on body fatness is either small or nonexistent.

42.  Of the three published studies funded by Taubes’s organization the Nutrition Science Initiative (NuSI), at least two, and possibly all three, refuted the carbohydrate-insulin hypothesis

The first study was a tightly controlled metabolic ward study reporting that metabolic rate slightly and transiently increased, but fat loss actually slowed, on a very-low-carbohydrate ketogenic diet (2% sugar), compared with a high-sugar (25%) higher-carbohydrate diet of equal calories.  This study also reported that the very-low-carbohydrate diet did not increase total energy levels in the bloodstream, as claimed by Taubes’s model.

The second study was a one-year randomized controlled diet trial (DIETFITS) reporting that a low-fat vs. low-carbohydrate diet led to the same degree of weight loss and the same metabolic rate after one year, and baseline insulin secretion did not predict who did better on which diet.

The third study reported that a very-low-carbohydrate diet led to higher calorie expenditure than a low-fat diet in people maintaining weight loss.  However, a reanalysis of the raw data suggests that the effect may be an artifact of faulty data.

Exercise

43.  Exercise tends to cause weight and fat loss in people with excess body fat

This has been demonstrated by dozens of randomized controlled trials, although the findings are not always consistent across individuals or trials, probably because many trials use modest exercise interventions and people adhere to them poorly.  Meta-analyses (studies of studies) tend to report that exercise causes weight and fat loss, including the most recent meta-analysis of 36 studies.

Greater volume of exercise, particularly when supervised to ensure compliance, causes greater weight and fat loss. In one randomized controlled trial that assigned overweight volunteers to different exercise amounts, greater amounts led to more body fat loss, with the greatest amount leading to a loss of 12 lbs of body fat over eight months relative to a group that did not exercise (175 min a week on a cycle trainer, treadmill, or elliptical).

Thanks to Adam Tzur of Sci-Fit for references.

44.  Exercise increases insulin sensitivity

This has been demonstrated by many randomized controlled trials.  Here are a few review papers of the evidence.

45.  Sedentary behavior causes insulin resistance

Athletes have high insulin sensitivity, yet ten days of inactivity markedly reduces it.  Five days of bed rest markedly increases insulin resistance in non-athletes as well.  Reducing daily walking time also promotes insulin resistance in only two weeks.

Food reward

46.  Fat and carbohydrate both cause dopamine release and increase eating drive, particularly when combined

The gut senses fat, carbohydrate, and protein, and this causes dopamine release in the brain that stimulates motivation and learning.  This has been extensively documented in animals, and in humans it has been replicated for fat and carbohydrate.

The combination of carbohydrate and fat causes greater activity in dopamine-responsive brain regions, and greater eating drive, than either alone.  To visualize this yourself, imagine how much you would want to eat regular ice cream, vs. fat-free ice cream, vs. unsweetened ice-cream.

47.  The most commonly/intensely craved foods combine carbohydrate and fat together, while foods that are high in sugar or fat alone are less commonly craved

This should be common sense (think of ice cream without the sugar or fat), but it has been extensively supported by research.  Foods rich in fat and carbohydrate together stimulate eating drive more than either alone, measured both by brain activity and people’s willingness to pay for the foods.

Studies on cravings and food addiction have found that foods combining carbohydrate and fat are the most likely to trigger cravings and addiction-like behaviors, including savory foods that contain no sugar.  The most commonly craved food is chocolate.  Foods that are only high in sugar or fat can also trigger cravings, but it’s less common.

48.  We eat more food when it tastes better

This is common sense, but here are some references to scientific studies just in case anyone doubts it.

Rigor

49.  Calling for more rigor in science does not necessarily make a person rigorous

Science has flaws at many levels that make it less efficient and effective than it could be.  However, using the concept of rigor selectively to criticize findings you don’t like is not rigorous.

Those who genuinely care about scientific rigor should be promoting the most effective tools we have for increasing it: Study preregistration, open data, proper application of statistics, conflict of interest regulations and disclosures, replication, meta-analysis, and Registered Reports.  They should also be promoting the organizations that develop and advance these tools like the Center for Open Science.  The most effective tools for increasing the rigor of science are coming from within science itself– designed by people who understand how science works.  Non-scientists can help by learning about these efforts, promoting them, and pushing for their adoption.

50.  Expert reviews of Taubes’s writing have uncovered extensive misuse of evidence

Gary Taubes has an extensive history of misrepresenting source material to benefit his narrative.  The most detailed fact checks of his books were written by Seth Yoder at The Science of Nutrition, and the results are frankly disturbing.  My own review of The Case Against Sugar also uncovered evidence misuse and a general unwillingness to cite relevant scientific evidence and apply logic appropriately.

51.  The Nutrition Science Initiative (NuSI), with Gary Taubes at its helm, attempted to interfere with the research that it funded once unfavorable results came in

Initially, NuSI assured researchers that it would have “no control over research design, conduct, or reporting”, which was essential due to Taubes’s conflicts of interest.  NuSI asked lead researcher Kevin Hall to communicate this to me, which he did in 2012 and I documented on my website.  Once the first results came in undermining the carbohydrate-insulin hypothesis, NuSI broke its agreement and began interfering with the scientific process, eventually causing the resignation of lead researcher Kevin Hall.  Hall concluded that “Potentially conflicted funders should not be involved in the conduct, analysis, or reporting of research. NuSI’s meddling in the EBC study violated both the final contract terms and our verbal agreement at the outset of the study.”

Miscellaneous

52.  The most fattening diet in animals and humans is human junk food, and its fattening effect cannot be explained by carbohydrate or fat alone

In rodents, the most fattening diet ever tested is the “cafeteria diet”, which consists of a buffet of calorie-dense, tasty human foods like condensed milk, chocolate chip cookies, salami, cheese, banana, marshmallows, milk chocolate, and peanut butter.  When rodents are given a choice between the cafeteria diet and their normal low-fat rodent pellets, not surprisingly they gorge on the human foods and virtually ignore the boring pellets.  Other species quickly grow fat on calorie-dense human food as well, including raccoons and monkeys.  Humans with ready access to a variety of calorie-dense, tasty foods also overeat and gain weight rapidly.

In rodents, diets that are only high in fat or only high in refined carbohydrate (including sugar) are not nearly as fattening as the cafeteria diet, demonstrating that neither fat nor refined carbohydrate alone can explain its full fattening effect.  Similar findings are observed in humans, where increasing sugar intake alone isn’t nearly as fattening as the cafeteria diet.

53.  Obesity has a strong genetic component

This has been demonstrated by many different studies in humans.  A meta-analysis (study of studies) of 115 such studies concluded that 75 percent of the difference in body fatness (BMI) between people is due to genetic differences.  Note: this is perfectly compatible with the idea that diet and lifestyle changes are responsible for the high prevalence of obesity in the 21st century; these studies describe the genetic component of differences in body fatness between people in a given environment.  If we all live in a fattening environment, those of us who are genetically susceptible to obesity will develop it.  Without a fattening environment, these genetic differences matter less and few people develop obesity.

54.  Synthesis of fat from carbohydrate is negligible in humans eating typical Western diets

The scientific term for this is de novo lipogenesis, and although the pathway exists in humans it only converts a tiny fraction of ingested carbohydrate into fat under realistic circumstances (typically less than 1 gram per day). In contrast, most people consume 50-200 grams of fat from the diet. See this review paper for the evidence, or the physiology textbook Metabolic Regulation, pages 200-201.

55.  Partially suppressing the release of fat from fat cells (lipolysis) does not cause fat gain, hunger, or a slower metabolic rate

A drug called acipimox inhibits lipolysis, or the release of fatty acids from fat cells, mimicking the effect of insulin.  As a consequence, free fatty acid levels in circulation decline (this is a key circulating fuel in the bloodstream).  The carbohydrate-insulin hypothesis predicts that this should lead to fat gain, hunger, and a reduced metabolic rate.  A 6-month placebo-controlled randomized controlled trial of acipimox showed that the drug reduces circulating free fatty acid levels by 38 percent but has no impact on body composition, calorie intake, or metabolic rate.

56.  The fat tissue of people with obesity releases fat at a greater rate than that of lean people, not a slower rate

The most informative study to date on this found that the greater a person’s fat mass, the higher the total rate of fat (free fatty acid) release.  Thus, nothing is “trapping” fat inside the fat cells of people with obesity– to the contrary, they release fat from their fat tissue at a greater rate than lean people.

We live in a complex world, and it’s impossible to be an expert on everything that impacts our lives.  In many domains, we have to trust the expertise of others to guide our decisions.  Yet not all experts hold rational beliefs, and many people who are framed as experts in media are not actually experts.  How do we separate the wheat from the chaff, focusing on high-quality sources of information and ignoring low-quality sources?

Over the years I’ve observed the behavior of various public figures in my areas of expertise, and I feel that I’ve developed pretty good nose for quickly sniffing out the credibility of public experts.  In this post, I’ve attempted to take my intuitions and put them in writing so I can pass at least some of them on to others.

Here is a list of some of the heuristics I use when I’m assessing the credibility of people who are framed as experts.  None of these are ironclad rules, but together they can help you get a quick sense of whether to listen to someone:

1. Does he have training or experience in the subject?  This is particularly relevant when someone disagrees with expert consensus.  Sometimes people get a platform just because they have a novel or interesting idea, even if that idea is unconvincing to a knowledgeable person.  It is of course possible that the non-expert is right and the experts are wrong, but it’s unlikely.  This is just a heuristic, since in some areas the experts are truly not knowledgeable.  For example, economists are barely better than chance at predicting the short-term behavior of the economy, but this doesn’t prevent some of them from prognosticating about it.
2. Does she try to explain everything with one idea?  The work of Philip Tetlock, PhD and others has shown that people who have one big idea to explain everything (“hedgehogs” or ideologues) are very bad at accurately modeling the world, predicting outcomes, and recommending effective actions.  These people are often selected for media attention because they are clear and confident about their beliefs.  The world is a complex place, and people who are able to model that complexity in their minds have better information than those who aren’t.  Look for people who tend to use multi-factor explanations.
3. Does he show nuance?  Related to #2.  There are usually exceptions and nuances.  Is this person able to build them into his mental model?
4. Is she able to change her mind?  Inability to change one’s mind is a hallmark of an irrational belief system.  Can you find examples of this person changing her mind in the past when presented with new evidence or a better interpretation of existing evidence?
5. Does he lean toward conspiracy explanations and/or blaming the government?  Large-scale conspiracies are improbable and the government is a favorite punching bag for cranks.
6. Does she cite evidence that isn’t representative of the literature as a whole?  This is common among experts, less common among the best experts, and very common among non-experts.  It’s also often easy to spot with a little effort.  Do a quick Google Scholar search for a recent meta-analysis on the topic, ideally from the Cochrane Collaboration.  Are the conclusions of the meta-analysis consistent with the evidence she is citing, or is she cherry-picking individual studies that support her position?
7. Does he portray experts who disagree with him as corrupt, stupid, or dishonest?  Corruption, irrationality, and dishonesty do exist among experts, but if someone makes these claims without presenting clear evidence for them, it’s a bad sign.  Accusing opposing experts of “lies”, “scams”, and other similar language is a red flag that the person making the claim is not objective.  Conflicts of interest are common among experts, and good to keep in mind, but it’s useful to consider possible conflicts of interest of the person pointing them out as well.
8. Does the topic relate to personal identity, or is it otherwise highly political or controversial?  Domains such as religion, politics, and nutrition relate strongly to peoples’ personal identities.  In this context, beliefs are often driven by group affiliation rather than rational consideration of evidence.  The likelihood that someone is providing high-quality information in these domains is lower than in less controversial areas like physics or neuroscience.

What did I miss?