In addition to the Economics Department here at the University of Colorado Boulder, where I am a professor, I have been hanging out at the Institute for Behavioral Genetics, which is on the other end of campus, a beautiful hike past the football stadium and then along the Boulder Creek Path. 

One of the impressive people I have met at the Institute for Behavior Genetics is David Brazel, currently a Predoctoral Trainee of the Institute for Behavioral Genetics and of Molecular Cellular and Developmental Biology. 

Though he now focuses on drug addiction, in order to get into his joint program, David had to do a research proposal comparable in detail to a grant proposal, which was directed at research on obesity. So David read a lot of the previous research in this area. I had a chance to talk to David last Wednesday and David graciously gave his permission for me to share with you what I learned from that conversation and the hypotheses about obesity that I ran by David. I should say that what I learned, or thought I learned, may not exactly match what David said or what he thinks. What I have below represents what I ended up thinking after talking to him. 

Leptin and Ghrelin. Following Jason Fung in the way I lay out in "Obesity Is Always and Everywhere an Insulin Phenomenon, I have emphasized the role of insulin and its opponent hormone glucagon. David said that research has also pointed to leptin and ghrelin as extremely important. For example, the genes for leptin and ghrelin seem important in predicting obesity. This is something I need to look into more. 

Beige Fat. One of the intriguing things David mentioned was that some of the most important genes for obesity have to do with whether fat cells are trying to generate heat or not. Mice have such a high surface-area to volume ratio, they would get cold if they didn't have something called "brown fat," which generates a lot of heat. Humans don't have brown fat in the same sense as rodents, but they do often have fat cells with an enhanced number of mitochondria and enhanced heat generation that are called "beige fat." 

One way to make your fat cells more beige so that they burn more energy is to live in a cold climate. It may be that taking cold showers could make a difference, too. A lot of research remains to be done on this. 

Obesity research is still at an early stage in many areas. One general theme from my conversaition with David was this: while the views I have taken about obesity on this blog might be wrong, they are consistent with the existing research on obesity. This is saying much less than you might think: the results of existing research admit of many, many interpretations, and much is simply unknown. 

Is It Healthy for Humans to Eat What Is Healthy for Rats and Mice? One simple example is my suspicion of using rodent data to give advice about what humans should eat. (Thinking about rodent brown fat might steer you in the right direction, but thinking about which foods are fattening to rodents may steer you in the wrong one.) Several people I have talked to who are involved in genetics research have been sympathetic to this argument that I made in "The Case Against Sugar: Stephan Guyenet vs. Gary Taubes":

I am inclined to agree with Stephan that rodent data do not support the idea that sugar is more harmful than fat (though it does seem to support the idea that fat plus sugar is worse than fat alone). But I am struck by the possibility that rodents might be much better adapted to highcarb diets than humans are. This may even allow them to eat sugar with less harm than humans. Am I wrong in thinking that for many, many generations rodents outside laboratories have tended to eat highcarb diets? The "many, many generations" is important. Even if rodents had only been eating highcarb diets for the same number of years as humans, the larger number of generations per century would have allowed rodents that hang around humans to be naturally selected to tolerate highcarb diets more than long-generationed humans.

Every discipline tends to develop conventions that the best research that is feasible for the typical researcher should be treated with respect. But if the best experimental research that is feasible is studies on rodents that might be much better adapted to highcarb diets than humans and small-sample-size human studies, it shouldn't make it any more persuasive to those of us who are not acculturated diet scientists for them to say "This is the state of the art."

Both Stephan Guyenet, as I discuss in "The Case Against Sugar: Stephan Guyenet vs. Gary Taubes" and Seth Yoder, as I discuss in "The Case Against the Case Against Sugar: Seth Yoder vs. Gary Taubes," are insufficiently cautious in applying rodent data to recommendations about what humans should eat. This leads me to believe that it might be common for nutritionists to rely too heavily and too uncritically on results from rodent data. 

Almost everyone would agree that the adequacy of mice and rats as a model for human nutrition is a crucial scientific question. The specific research I would love to have someone point me to, and would love to see someone pursue if it hasn't been done already is to look closely at the coevolution of mice and rats with humans, and the evolutionary response of mice and rats to the human agricultural transition. I know there has been a lot of interesting work on the coevolution of humans and dogs, so this is a type of research that can be done. There may even be mouse remains partially preserved in ancient middens that would provide some ancient mouse DNA before, during and after the human agricultural transition. 

Belly Fat. It is known that belly fat is correlated with insulin resistance. But research has not fully established why. I threw out a possibility that extends the logic of this passage from "Obesity Is Always and Everywhere an Insulin Phenomenon": 

People often talk as if obesity itself caused many chronic diseases. But other than joint problems, and the social stigma of obesity, almost all of the diseases associated with obesity could be due to the common cause of elevated insulin levels. That is,

• chronically elevated insulin levels usually cause obesity, and

• chronically elevated insulin levels have many dangerous side effects. 

There is an interesting theoretical case in which chronically high insulin levels would be de-linked from obesity. Suppose the fat cells of someone caught in a carb rebound cycle became resistant to insulin, but his or her muscle cells retained their normal sensitivity to insulin. Because the fat cells would not respond much to the insulin signal telling them to take in glucose from the bloodstream and convert it into triglycerides and then fat, he or she would not gain much weight. But to keep blood glucose levels in line, insulin levels would have to go up even further to get the job done just from the muscle cell response to insulin. If high insulin levels cause most of the chronic diseases we associate with obesity, then while still normal in weight, he or she would be at risk for all of these chronic diseases. This is someone others might envy for being able to eat anything without gaining weight—right up until he or she died of a heart attack. ...

If, on the other hand, muscle cells become more resistant to insulin than fat cells, then the higher insulin levels that result from insulin resistance will lead to weight gain. Moreover, the fact that even a little food can still elevate insulin levels quite a bit will make weight loss very difficult. In saying this, I have in mind this model relating insulin levels to fat accumulation and decumulation

• high insulin level —> accumulation of body fat

• medium insulin levels over a substantial range —> body fat steady

• low insulin level —> fat burning

If you have insulin resistance for muscle cells but not fat cells, even small amounts of food will prevent reaching an insulin level low enough to lead to fat burning. The only way to get insulin levels low enough to lead to fat burning may be to have a substantial period of time with no food at all—fasting.  

One logical possibility for why belly fat is an especially good indicator of insulin resistance is that belly fat cells are one of the last type of fat cells to become insulin resistance. So they still respond strongly to the "take in blood sugar and turn it into fat" message of elevated insulin even when high levels of insulin shouting that message go less and less heeded by other fat cells. This is speculative, but what is known is that there are several distinct types of fat cells in the body. So it is not impossible that belly fat cells get insulin resistant at a slower rate on average than other types of fat cells. 

The Net Body Fat Accumulation Response to Insulin Curve. Talking to David, I waved my hands in the air trying to describe something like the graph below giving the picture I have in my mind of how the permanent weight gain or weight loss of fat accumulation or fat burning is related to insulin levels. Here, as in response to the other ideas I put forward, he said the basic idea was possible; the research hasn't been done to confirm or refute this idea. He also emphasized that the set of mechanisms would no doubt be more complex than this. 

I think there is a bit of optical illusion in the graph below: the horizontal axis really is flat, but a trick of the eye makes it look downward-sloping. The insulin level—really a stand-in for a linear combination of several hormones—is on the horizontal axis. Also on the horizontal axis is the equation giving where the insulin level comes from in this simplified model: the product of calories, average insulin index of the food one eats and one's level of insulin resistance. Insulin resistance increases the insulin response for any type of food. So the more insulin resistant you are, the more you need to shift to lower insulin-index foods and the more you need to fast if you want to achieve a low enough insulin level to lose weight. (See "Forget Calorie Counting; It's the Insulin Index, Stupid" on the foods to avoid and the foods to move toward to lower the average insulin index of the food you eat.) 

A key feature of the net body fat accumulation response to insulin curve that I have drawn is that it has a flat part. There is a range of insulin levels that lead to no weight gain and no weight loss. But a high enough insulin level, while it lasts, leads to weight gain; conversely, a low enough insulin level, while it lasts, leads to weight loss. A simple way to get a response curve of this shape is to have one signaling mechanism for weight gain that has a high insulin level threshold and another signaling mechanism for weight loss that has a low insulin level threshold. The main reason to think the shape might be something like this is that people are as close to steady in their weight as they are. Without a flat part to the response curve, that would be harder to get.  

It might seem that lowering calorie intake would be a good way to lower your insulin index. But calorie intake also matters for making sure your cells have enough nourishment and energy. The balance between pain and weight loss is dramatically different depending on what part of the response curve you are in:

• At a low enough insulin level, fat is released from your fat cells and your cells will have plenty of nourishment.
• At the right end of the flat part of the curve, your cells will also have plenty of nourishment.
• At the left end of the flat part of the curve, you aren't eating very many calories and your body isn't burning any fat, so there is not enough nourishment for your cells. This is sometimes called cellular starvation, and it isn't pleasant. 
• At a high enough insulin level, sugar will be taken out of your blood stream and stored as fat so fast that you are likely to feel quite hungry. It isn't exactly cellular starvation, but it is genuine hunger. 

Technically, in this simple model, the amount of nourishment available to cells is shown by which line you are on parallel to the purple line. The purple line itself can be seen as a dividing line between adequate and inadequate nourishment. What give this model its interesting results is that nourishment is linear in calories and net body fat accumulation, but net body fat accumulation is nonlinear in insulin levels. 

The bottom line is that you will feel hungry even shortly after eating a lot if you are eating a lot of high insulin index foods, but as long as you have plenty of fat to burn, you won't feel all that hungry if you are not eating anything at all. That is the revolutionary idea that I learned from reading Jason Fung's books The Obesity Code and The Complete Guide to Fasting—and an idea that matches my own experience and the experience a few other people who have shared their experiences as self-appointed guinea pigs with me. 

Don't miss these other posts on fighting obesity:

• Stop Counting Calories; It's the Clock that Counts
• Forget Calorie Counting; It's the Insulin Index, Stupid
• Obesity Is Always and Everywhere an Insulin Phenomenon
• The Case Against Sugar: Stephan Guyenet vs. Gary Taubes
• The Case Against the Case Against Sugar: Seth Yoder vs. Gary Taubes
• How Sugar Makes People Hangry
• The Keto Food Pyramid
• A Conversation with David Brazel on Obesity Research
• Mass In/Mass Out: A Satire of Calories In/Calories Out
• Carola Binder: The Obesity Code and Economists as General Practitioners
• Jason Fung: Dietary Fat is Innocent of the Charges Leveled Against It
• Faye Flam: The Taboo on Dietary Fat is Grounded More in Puritanism than Science
• Diseases of Civilization
• Sugar as a Slow Poison
• Katherine Ellen Foley—Candy Bar Lows: Scientists Just Found Another Worrying Link Between Sugar and Depression
• Ken Rogoff Against Sugar and Processed Food
• Kearns, Schmidt and Glantz—Sugar Industry and Coronary Heart Disease Research: A Historical Analysis of Internal Industry Documents
• Salt Is Not the Nutritional Evil It Is Made Out to Be
• Whole Milk Is Healthy; Skim Milk Less So
• How the Calories In/Calories Out Theory Obscures the Endogeneity of Calories In and Out to Subjective Hunger and Energy
• Putting the Perspective from Jason Fung's "The Obesity Code" into Practice
• Julia Belluz and Javier Zarracina: Why You'll Be Disappointed If You Are Exercising to Lose Weight, Explained with 60+ Studies (my retitling of the article this links to)
• Meat Is Amazingly Nutritious—But Is It Amazingly Nutritious for Cancer Cells, Too?
• Diana Kimball: Listening Creates Possibilities
• On Fighting Obesity
• The Heavy Non-Health Consequences of Heaviness
• Analogies Between Economic Models and the Biology of Obesity
• Debating 'Forget Calorie Counting; It's the Insulin Index, Stupid'

Also see the last section of "Five Books That Have Changed My Life."