Upcoming Talks

I have two talks planned over the next two months.  Hope to see you there!

Ancestral Health Symposium 2014: UC Berkeley, August 7-9

If you want to understand the most rigorous science available on leptin resistance-- a key mechanism of obesity and a major barrier to fat loss-- this talk is for you.  This is my primary area of professional expertise; I have years of firsthand research experience on the subject and I've published a number of related papers in peer-reviewed journals.  The talk will be accessible to nearly all levels of expertise.  AHS14 tickets are available here.  I've pasted the talk's abstract below.

What Causes Leptin Resistance?

Leptin is the primary hormonal regulator of body fatness.  Obese people exhibit a resistance to leptin’s effects in the brain, causing the brain to oppose fat loss by multiple mechanisms.  Research in animal models suggests that leptin resistance may be required for obesity to develop.  How does leptin resistance occur, and what causes it?  Research has not yet provided us with definitive answers, but several plausible possibilities have emerged.  This talk will review what is known about leptin resistance and its causes.

McDougall Advanced Study Weekend: Santa Rosa, CA, September 5-7

Dr. John McDougall invited me to speak at his yearly symposium after viewing my TEDx talk "The American Diet: a Historical Perspective".  I look forward to sharing my thoughts and interacting with a different audience than I'm used to.  The talk will be an expanded version of the one I presented at AHS13.  Tickets are available here.  I've pasted a modified version of my AHS13 abstract below.

Insulin and Obesity: Reconciling Conflicting Evidence

The pancreatic hormone insulin regulates the trafficking and metabolism of carbohydrate and fat, and its secretion is particularly stimulated by carbohydrate and protein.  Since circulating insulin is elevated in common obesity, and insulin influences fatty acid flux into and out of fat tissue, this has raised the possibility that elevated insulin causes common obesity, and that dietary carbohydrate is particularly fattening.  A large amount of evidence appears to support the hypothesis that insulin causes obesity, and a large amount of evidence appears to falsify it.  This presentation will outline a framework capable of reconciling this seemingly conflicting evidence.

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Fat and Carbohydrate: Clarifications and Details

The last two posts on fat and carbohydrate were written to answer a few important, but relatively narrow, questions that I feel are particularly pertinent at the moment:

• Was the US obesity epidemic caused by an increase in calorie intake?
• Could it have been caused by an increase in carbohydrate intake, independent of the increase in calorie intake?
• Does an unrestricted high-carbohydrate diet lead to a higher calorie intake and body fatness than an unrestricted high-fat diet, or vice versa?
• Could the US government's advice to eat a low-fat diet have caused the obesity epidemic by causing a dietary shift toward carbohydrate?

However, those posts left a few loose ends that I'd like to tie up in this post.  Here, I'll lay out my opinions on the relationship between macronutrient intake and obesity in more detail.  I'll give my opinions on the following questions:

• What dietary macronutrient composition is the least likely to cause obesity over a lifetime?
• What dietary macronutrient composition is best for a person who is already overweight or obese?
• Is fat inherently fattening and/or unhealthy?

From the beginning

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Food Reward Friday

This week's lucky "winner"... kettle corn!

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Has Obesity Research Failed?

I frequently encounter the argument that obesity research has failed because it hasn't stopped the global increase in obesity rates.  According to this argument, we need to re-think our approach to obesity research because the current approach just isn't working.

Grant funding for obesity research keeps increasing in the US, and the prevalence of obesity also keeps increasing*.  What gives?  Maybe if we just scrapped the whole endeavor we'd be better off.

Let's take a closer look at this argument and see how it holds up.

Why Do Research?

There are two fundamental reasons why we do research:

1. To gather accurate information about the natural world.  This information is intrinsically valuable because we like knowing how the world works, and it may eventually have practical value that's not immediately obvious.
2. Practical applications.  We want to solve problems and improve our lives.

If we want to determine whether or not obesity research has failed, we should evaluate it using those two metrics.

Has Obesity Research Gathered Accurate Information?

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Calorie Intake and Body Fatness on Unrestricted High-fat vs. High-carbohydrate Diets

In recent posts, we've explored the association between calorie intake and the US obesity epidemic, and the reasons why this association almost certainly represents a cause-and-effect relationship.  I also reviewed the evidence suggesting that carbohydrate and fat are equally fattening in humans, calorie for calorie.

One valid objection that came up in the comments is that calorie-controlled diets in a research setting may not reflect what happens in real life.  For example, in a context where calorie intake isn't tightly controlled, diet composition can impact calorie intake, in turn affecting body fatness.  This, of course, is true, and it forms one of the central pillars of our fat loss program the Ideal Weight Program.

Some low-carbohydrate diet advocates argue that the obesity epidemic was caused by US dietary guidelines that emphasize a carbohydrate-rich diet*.  The idea here is that the increase in calorie intake was due to the diet shifting in a more carbohydrate-heavy direction.  In other words, they're hypothesizing that a carbohydrate-rich eating style increases food intake, which increases body fatness**.  According to this hypothesis, if we had received advice to eat a fat-rich diet instead, we wouldn't be in the midst of an obesity epidemic.

Fortunately for us, this hypothesis has been tested-- many times!  Which eating style leads to higher calorie intake and body fatness when calories aren't controlled: a carbohydrate-rich diet, or a fat-rich diet?

Short-term Studies

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Food Reward Friday

This week's lucky "winner"... Lay's milk chocolate-dipped potato chips!!

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A New Understanding of an Old "Obesity Gene"

As you know if you've been following this blog for a while, obesity risk has a strong genetic component.  Genome-wide association studies (GWAS) attempt to identify the specific locations of genetic differences (single-nucleotide polymorphisms or SNPs) that are associated with a particular trait.  In the case of obesity, GWAS studies have had limited success in identifying obesity-associated genes.  However, one cluster of SNPs consistently show up at the top of the list in these studies: those that are near the gene FTO.

As with many of the genes in our genome, different people carry different versions of FTO.  People with two copies of the "fat" version of the FTO SNPs average about 7 pounds (3 kg) heavier than people with two copies of the "thin" version, and they also tend to eat more calories (1, 2).  

Despite being the most consistent hit in these genetic studies, FTO has remained a mystery.  As with most obesity-associated genes, it's expressed in the brain and it seems to respond somewhat to nutritional status.  Yet its function is difficult to reconcile with a role in weight regulation: 

• It's an enzyme that removes methyl groups from RNA, which doesn't immediately suggest a weight-specific function.
• It's not primarily expressed in the brain or in body fat, but in all tissues.
• Most importantly, as far as we know, the different versions of the gene do not result in different tissue levels of FTO, or different activity of the FTO enzyme, so it's hard to understand how they would impact anything at all.  

An important thing to keep in mind is that GWAS studies don't usually pinpoint specific genes.  Typically, they tell us that obesity risk is associated with variability in a particular region of the genome.  If the region corresponds to the location of a single gene, it's a pretty good guess that the gene is the culprit.  However, that's not always the case...

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