Food Reward: a Dominant Factor in Obesity, Part I

A Curious Finding

It all started with one little sentence buried in a paper about obese rats. I was reading about how rats become obese when they're given chocolate Ensure, the "meal replacement drink", when I came across this:

...neither [obesity-prone] nor [obesity-resistant] rats will overeat on either vanilla- or strawberry-flavored Ensure.

The only meaningful difference between chocolate, vanilla and strawberry Ensure is the flavor, yet rats eating the chocolate variety overate, rapidly gained fat and became metabolically ill, while rats eating the other flavors didn't (1). Furthermore, the study suggested that the food's flavor determined, in part, what amount of fatness the rats' bodies "defended."

As I explained in previous posts, the human (and rodent) brain regulates the amount of fat the body carries, in a manner similar to how the brain regulates blood pressure, body temperature, blood oxygenation and blood pH (2). That fact, in addition to several other lines of evidence, suggests that obesity probably results from a change in this regulatory system. I refer to the amount of body fat that the brain defends as the "body fat setpoint", however it's clear that the setpoint is dependent on diet and lifestyle factors. The implication of this paper that I could not escape is that a food's flavor influences body fatness and probably the body fat setpoint.

An Introduction to Food Reward

The brain contains a sophisticated system that assigns a value judgment to everything we experience, integrating a vast amount of information into a one-dimensional rating system that labels things from awesome to terrible. This is the system that decides whether we should seek out a particular experience, or avoid it. For example, if you burn yourself each time you touch the burner on your stove, your brain will label that action as bad and it will discourage you from touching it again. On the other hand, if you feel good every time you're cold and put on a sweater, your brain will encourage that behavior. In the psychology literature, this phenomenon is called "reward," and it's critical to survival.

The brain assigns reward to, and seeks out, experiences that it perceives as positive, and discourages behaviors that it views as threatening. Drugs of abuse plug directly into reward pathways, bypassing the external routes that would typically trigger reward. Although this system has been studied most in the context of drug addiction, it evolved to deal with natural environmental stimuli, not drugs.

As food is one of the most important elements of survival, the brain's reward system is highly attuned to food's rewarding properties. The brain uses input from smell, taste, touch, social cues, and numerous signals from the digestive tract* to assign a reward value to foods. Experiments in rats and humans have outlined some of the qualities of food that are inherently rewarding:

• Fat
• Starch
• Sugar
• Salt
• Meatiness (glutamate)
• The absence of bitterness
  
• Certain textures (e.g., soft or liquid calories, crunchy foods)
• Certain aromas (e.g., esters found in many fruits)
• Calorie density ("heavy" food)
  

We are generally born liking the qualities listed above, and aromas and flavors that are associated with these qualities become rewarding over time. For example, beer tastes terrible the first time you drink it because it's bitter, but after you drink it a few times and your brain catches wind that there are calories and a drug in there, it often begins tasting good. The same applies to many vegetables. Children are generally not fond of vegetables, but if you serve them spinach smothered in butter enough times, they'll learn to like it by the time they're adults.

The human brain evolved to deal with a certain range of rewarding experiences. It didn't evolve to constructively manage strong drugs of abuse such as heroin and crack cocaine, which overstimulate reward pathways, leading to the pathological drug seeking behaviors that characterize addiction. These drugs are "superstimuli" that exceed our reward system's normal operating parameters. Over the next few posts, I'll try to convince you that in a similar manner, industrially processed food, which has been professionally crafted to maximize its rewarding properties, is a superstimulus that exceeds the brain's normal operating parameters, leading to an increase in body fatness and other negative consequences.


* Nerves measure stomach distension. A number of of gut-derived paracrine and endocrine signals, including CCK, PYY, ghrelin, GLP-1 and many others potentially participate in food reward sensing, some by acting directly on the brain via the circulation, and others by signaling indirectly via the vagus nerve. More on this later.

Alcohol consumption, gender, and type 2 diabetes: Strange … but true

Let me start this post with a warning about spirits (hard liquor). Taken on an empty stomach, they cause an acute suppression of liver glycogenesis. In other words, your liver becomes acutely insulin resistant for a while. How long? It depends on how much you drink; possibly as long as a few hours. So it is not a very good idea to consume them immediately before eating carbohydrate-rich foods, natural or not, or as part of sweet drinks. You may end up with near diabetic blood sugar levels, even if your liver is insulin sensitive under normal circumstances.

The other day I was thinking about this, and the title of this article caught my attention: Alcohol Consumption and the Risk of Type 2 Diabetes Mellitus. This article is available here in full text. In it, Kao and colleagues show us a very interesting table (Table 4), relating alcohol consumption in men and women with incidence of type 2 diabetes. I charted the data from Model 3 in that table, and here is what I got:

I used the data from Model 3 because it adjusted for a lot of things: age, race, education, family history of diabetes, body mass index, waist/hip ratio, physical activity, total energy intake, smoking history, history of hypertension, fasting serum insulin, and fasting serum glucose. Whoa! As you can see, Model 3 even adjusted for preexisting insulin resistance and impaired glucose metabolism.

So, according to the charts, the more women drink, the lower is the risk of developing type 2 diabetes, even if they drink more than 21 drinks per week. For men, the sweet spot is 7-14 drinks per week; after 21 drinks per week the risk goes up significantly.

A drink is defined as: a 4-ounce glass of wine, a 12-ounce bottle or can of beer, or a 1.5-ounce shot of hard liquor. The amounts of ethanol vary, with more in hard liquor: 4 ounces of wine = 10.8 g of ethanol, 12 ounces of beer = 13.2 g of ethanol, and 1.5 ounces of spirits = 15.1 g of ethanol.

Initially I thought that these results were due to measurement error, particularly because the study relies on questionnaires. But I did some digging and checking, and now think they are not. In fact, there are plausible explanations for them. Here is what I think, and it has to do with a fundamental difference between men and women – sex hormones.

In men, alcohol consumption, particularly in large quantities, suppresses testosterone production. And testosterone levels are inversely associated with diabetes in men. Heavy alcohol consumption also increases estrogen production in men, which is not good news either.

In women, alcohol consumption, particularly in large quantities, increases estrogen production. And estrogen levels are (you guessed it) inversely associated with diabetes in women. Unnatural suppression of testosterone levels in women is not good either, as this hormone also plays important roles in women; e.g., it influences mood and bone density.

What if we were to disregard the possible negative health effects of suppressing testosterone production in women; should women start downing 21 drinks or more per week? The answer is “no”, because alcohol consumption, particularly in large quantities, increases the risk of breast cancer in women. So, for women, alcohol consumption in moderation may also provide overall health benefits, as it does for men; but for different reasons.

Upcoming Talks

I'll be giving at least two talks at conferences this year:

Ancestral Health Symposium; "The Human Ecological Niche and Modern Health"; August 5-6 in Los Angeles. This is going to be a great conference. Many of my favorite health/nutrition writers will be presenting. Organizer Brent Pottenger and I collaborated on designing the symposium's name so I hope you like it.

My talk will be titled "Obesity; Old Solutions to a New Problem." I'll be presenting some of my emerging thoughts on obesity. I expect to ruffle some feathers!

Tickets are going fast so reserve one today! I doubt there will be any left two weeks from now.


TEDx Harvard Law; "Food Policy and Public Health"; Oct 21 at Harvard. My talk is tentatively titled "The American Diet: a Historical Perspective." This topic interests me because it helps us frame the discussion on why chronic disease is so prevalent today, and what are the appropriate public health measures to combat it. This should also be a great conference.

Low bone mineral content in older Eskimos: Meat-eating or shrinking?

Mazess & Mather (1974) is probably the most widely cited article summarizing evidence that bone mineral content in older North Alaskan Eskimos was lower (10 to 15 percent) than that of United States whites. Their finding has been widely attributed to the diet of the Eskimos, which is very high in animal protein. Here is what they say:

“The sample consisted of 217 children, 89 adults, and 107 elderly (over 50 years). Eskimo children had a lower bone mineral content than United States whites by 5 to 10% but this was consistent with their smaller body and bone size. Young Eskimo adults (20 to 39 years) of both sexes were similar to whites, but after age 40 the Eskimos of both sexes had a deficit of from 10 to 15% relative to white standards.”

Note that their findings refer strictly to Eskimos older than 40, not Eskimo children or even young adults. If a diet very high in animal protein were to cause significant bone loss, one would expect that diet to cause significant bone loss in children and young adults as well. Not only in those older than 40.

So what may be the actual reason behind this reduced bone mineral content in older Eskimos?

Let me make a small digression here. If you want to meet quite a few anthropologists who are conducting, or have conducted, field research with isolated or semi-isolated hunter-gatherers, you should consider attending the annual Human Behavior and Evolution Society (HBES) conference. I have attended this conference in the past, several times, as a presenter. That gave me the opportunity to listen to some very interesting presentations and poster sessions, and talk with many anthropologists.

Often anthropologists will tell you that, as hunter-gatherers age, they sort of “shrink”. They lose lean body mass, frequently to the point of becoming quite frail in as early as their 60s and 70s. They tend to gain body fat, but not to the point of becoming obese, with that fat replacing lean body mass yet not forming major visceral deposits. Degenerative diseases are not a big problem when you “shrink” in this way; bigger problems are  accidents (e.g., falls) and opportunistic infections. Often older hunter-gatherers have low blood pressure, no sign of diabetes or cancer, and no heart disease. Still, they frequently die younger than one would expect in the absence of degenerative diseases.

A problem normally faced by older hunter-gatherers is poor nutrition, which is both partially caused and compounded by lack of exercise. Hunter-gatherers usually perceive the Western idea of exercise as plain stupidity. If older hunter-gatherers can get youngsters in their prime to do physically demanding work for them, they typically will not do it themselves. Appetite seems to be negatively affected, leading to poor nutrition; dehydration often is a problem as well.

Now, we know from this post that animal protein consumption does not lead to bone loss. In fact, it seems to increase bone mineral content. But there is something that decreases bone mineral content, as well as muscle mass, like nothing else – lack of physical activity. And there is something that increases bone mineral content, as well as muscle mass, in a significant way – vigorous weight-bearing exercise.

Take a look at the figure below, which I already discussed on a previous post. It shows a clear pattern of benign ventricular hypertrophy in Eskimos aged 30-39. That goes down dramatically after age 40. Remember what Mazess & Mather (1974) said in their article: “… after age 40 the Eskimos of both sexes had a deficit of from 10 to 15% relative to white standards”.

Benign ventricular hypertrophy is also known as athlete's heart, because it is common among athletes, and caused by vigorous physical activity. A prevalence of ventricular hypertrophy at a relatively young age, and declining with age, would suggest benign hypertrophy. The opposite would suggest pathological hypertrophy, which is normally induced by obesity and chronic hypertension.

So there you have it. The reason older Eskimos were found to have lower bone mineral content after 40 is likely not due to their diet.  It is likely due to the same reasons why they "shrink", and also in part because they "shrink". Not only does physical activity decrease dramatically as Eskimos age, but so does lean body mass.

Obese Westerners tend to have higher bone density on average, because they frequently have to carry their own excess body weight around, which can be seen as a form of weight-bearing exercise. They pay the price by having a higher incidence of degenerative diseases, which probably end up killing them earlier, on average, than osteoporosis complications.

Reference

Mazess R.B., & Mather, W.W. (1974). Bone mineral content of North Alaskan Eskimos. American Journal of Clinical Nutrition, 27(9), 916-925.

Beef meatballs, with no spaghetti

There are pizza restaurants, whose specialty is pizza, even though they usually have a few side dishes. Not healthy enough?

Well, don’t despair, there are meatball restaurants too. I know of at least one, The Meatball Shop, on 84 Stanton Street, in New York City.

Finally a restaurant that elevates the "lowly" meatball to its well deserved place!

Meatballs are delicious, easy to prepare, and you can use quite a variety of meats to do them. Below is a simple recipe. We used ground grass-fed beef, not because of omega-6 concerns (see this post), but because of the different taste.

- Prepare some dry seasoning powder by mixing sea salt, parsley, garlic power, chili powder, and a small amount of cayenne pepper.
- Thoroughly mix 1 pound of ground beef, one or two eggs, and the seasoning powder.
- Make about 10 meatballs, and place them in a frying pan with a small amount of water (see picture below).
- Cover the pan and cook on low fire for about 1 hour.

There is no need for any oil in the pan. On a low fire the small amount of water at the bottom will heat up, circulate, and essentially steam the meatballs. The water will also prevent the meatballs from sticking to the pan. Some moisture will also be released by the meat.

Part of the fat from the meat will be released and accumulate at the bottom of the pan. If you add tomato sauce and mix, the fat will become part of the resulting red sauce. This sauce will add moisture back to the dish, as the meatballs sometimes get a bit dry from the cooking.

Five meatballs of the type that we used (about 15 percent fat) will have about 57 g of protein and 32 g of fat; the latter mostly saturated and monounsaturated (both healthy). They will also be a good source of vitamins B12 and B6, niacin, zinc, selenium, and phosphorus.

Add a fruit or a sweet potato as a side dish to 3-5 meatballs and you have a delicious and nutritious meal that may eve impress some people!

US Omega-6 and Omega-3 Fat Consumption over the Last Century

Omega-6 and omega-3 polyunsaturated fats (PUFA) are essential nutrients that play many important roles in the body. They are highly bioactive, and so any deviation from ancestral intake norms should probably be viewed with suspicion. I've expressed my opinion many times on this blog that omega-6 consumption is currently too high due to our high intake of refined seed oils (corn, soybean, sunflower, etc.) in industrial nations. Although it's clear that the quantity of omega-6 and omega-3 polyunsaturated fat have changed over the last century, no one had ever published a paper that attempted to systematically quantify it until last month (1).

Drs. Chris Ramsden and Joseph Hibbeln worked on this paper (the first author was Dr. Tanya Blasbalg and the senior author was Dr. Robert Rawlings)-- they were the first and second authors of a different review article I reviewed recently (2). Their new paper is a great reference that I'm sure I'll cite many times. I'm going to briefly review it and highlight a few key points.

1. The intake of omega-6 linoleic acid has increased quite a bit since 1909. It would have been roughly 2.3% of calories in 1909, while in 1999 it was 7.2%. That represents an increase of 213%. Linoleic acid is the form of omega-6 that predominates in seed oils.

2. The intake of omega-3 alpha-linolenic acid has also increased, for reasons that I'll explain below. It changed from 0.35% of calories to 0.72%, an increase of 109%.

3. The intake of long-chain omega-6 and omega-3 fats have decreased. These are the highly bioactive fats for which linoleic acid and alpha-linolenic acid are precursors. Arachidonic acid, DHA, DPA and EPA intakes have declined. This mostly has to do with changing husbandry practices and the replacement of animal fats with seed oils in the diet.

4. The ratio of omega-6 to omega-3 fats has increased. There is still quite a bit of debate over whether the ratios matter, or simply the absolute amount of each. I maintain that there is enough evidence from highly controlled animal studies and the basic biochemistry of PUFAs to tentatively conclude that the ratio is important. At a minimum, we know that excess linoleic acid inhibits omega-3 metabolism (3, 4, 5, 6). The omega-6:3 ratio increased from 5.4:1 to 9.6:1 between 1909 and 2009, a 78% increase.

5. The biggest factor in both linoleic acid and alpha-linolenic acid intake changes was the astonishing rise in soybean oil consumption. Soybean oil consumption increased from virtually nothing to 7.4% of total calories, eclipsing all sources of calories besides sugar, dairy and grains! That's because processed food is stuffed with it. It's essentially a byproduct of defatted soybean meal-- the second most important animal feed after corn. Check out this graph from the paper:

I think this paper is an important piece of the puzzle as we try to figure out what happened to nutrition and health in the US over the last century.

Fat-ten-u

I recently bought the book Food in the United States, 1820s-1890. I came across an ad for an interesting product that was sold in the late 1800s called Fat-ten-u. Check your calendars, it's not April fools day anymore; this is for real. Fat-ten-u was a dietary supplement guaranteed to "make the thin plump and rosy with honest fleshiness of form." I found several more ads for it online, and they feature drawings of despondent, lean women and drawings of happy overweight women accompanied by enthusiastic testimonials such as this:

"FAT-TEN-U FOODS increased my weight 39 pounds, gave me new womanly vigor and developed me finely. My two sisters also use FAT-TEN-U and because of our newly found vigor we have taken up Grecian dancing and have roles in all local productions."

I'm dying to know what was in this stuff, but I can't find the ingredients anywhere.

I find this rather extraordinary, for two reasons:

• Social norms have clearly changed since the late 1800s. Today, leanness is typically considered more attractive than plumpness.
• Women had to make an effort to become overweight in the late 1800s. In 2011, roughly two-thirds of US women are considered overweight or obese, despite the fact that most of them would rather be lean.

A rhetorical question: did everyone count calories in the 1800s, or did their diet and lifestyle naturally promote leanness? The existence of Fat-ten-u is consistent with the idea that our bodies naturally "defended" a lean body composition more effectively in the late 1800s, when our diets were less industrialized. This is supported by the only reliable data on obesity prevalence in the 1890s I'm aware of: body height and weight measurements from over 35,000 Union civil war veterans aged 40-69 years old (1). In that group of Caucasian men, obesity was about 10% of what it is today in the same age group. Whether or not you believe that this sample was representative of the population at large, I can't imagine any demographic in the modern US with an obesity prevalence of 3 percent (certainly not 60 year old war veterans).

Here are two more ads for Fat-ten-u and "Corpula foods" for your viewing pleasure:

The China Study II: Carbohydrates, fat, calories, insulin, and obesity

The “great blogosphere debate” rages on regarding the effects of carbohydrates and insulin on health. A lot of action has been happening recently on Peter’s blog, with knowledgeable folks chiming in, such as Peter himself, Dr. Harris, Dr. B.G. (my sista from anotha mista), John, Nigel, CarbSane, Gunther G., Ed, and many others.

I like to see open debate among people who hold different views consistently, are willing to back them up with at least some evidence, and keep on challenging each other’s views. It is very unlikely that any one person holds the whole truth regarding health matters. Unfortunately this type of debate also confuses a lot of people, particularly those blog lurkers who want to get all of their health information from one single source.

Part of that “great blogosphere debate” debate hinges on the effect of low or high carbohydrate dieting on total calorie consumption. Well, let us see what the China Study II data can tell us about that, and about a few other things.

WarpPLS was used to do the analyses below. For other China Study analyses, many using WarpPLS as well as HealthCorrelator for Excel, click here. For the dataset used here, visit the HealthCorrelator for Excel site and check under the sample datasets area.

The two graphs below show the relationships between various foods, carbohydrates as a percentage of total calories, and total calorie consumption. A basic linear analysis was employed here. As carbohydrates as a percentage of total calories go up, the diet generally becomes a high carbohydrate diet. As it goes down, we see a move to the low carbohydrate end of the scale.

The left parts of the two graphs above are very similar. They tell us that wheat flour consumption is very strongly and negatively associated with rice consumption; i.e., wheat flour displaces rice. They tell us that fruit consumption is positively associated with rice consumption. They also tell us that high wheat flour consumption is strongly and positively associated with being on a high carbohydrate diet.

Neither rice nor fruit consumption has a statistically significant influence on whether the diet is high or low in carbohydrates, with rice having some effect and fruit practically none. But wheat flour consumption does. Increases in wheat flour consumption lead to a clear move toward the high carbohydrate diet end of the scale.

People may find the above results odd, but they should realize that white glutinous rice is only 20 percent carbohydrate, whereas wheat flour products are usually 50 percent carbohydrate or more. Someone consuming 400 g of white rice per day, and no other carbohydrates, will be consuming only 80 g of carbohydrates per day. Someone consuming 400 g of wheat flour products will be consuming 200 g of carbohydrates per day or more.

Fruits generally have much less carbohydrate than white rice, even very sweet fruits. For example, an apple is about 12 percent carbohydrate.

There is a measure that reflects the above differences somewhat. That measure is the glycemic load of a food; not to be confused with the glycemic index.

The right parts of the graphs above tell us something else. They tell us that the percentage of carbohydrates in one’s diet is strongly associated with total calorie consumption, and that this is not the case with percentage of fat in one’s diet.

Given the above, one may be interested in looking at the contribution of individual foods to total calorie consumption. The graph below focuses on that. The results take nonlinearity into consideration; they were generated using the Warp3 algorithm option of WarpPLS.

As you can see, wheat flour consumption is more strongly associated with total calories than rice; both associations being positive. Animal food consumption is negatively associated, somewhat weakly but statistically significantly, with total calories. Let me repeat for emphasis: negatively associated. This means that, as animal food consumption goes up, total calories consumed go down.

These results may seem paradoxical, but keep in mind that animal foods displace wheat flour in this dataset. Note that I am not saying that wheat flour consumption is a confounder; it is controlled for in the model above.

What does this all mean?

Increases in both wheat flour and rice consumption lead to increases in total caloric intake in this dataset. Wheat has a stronger effect. One plausible mechanism for this is abnormally high blood glucose elevations promoting abnormally high insulin responses. Refined carbohydrate-rich foods are particularly good at raising blood glucose fast and keeping it elevated, because they usually contain a lot of easily digestible carbohydrates. The amounts here are significantly higher than anything our body is “designed” to handle.

In normoglycemic folks, that could lead to a “lite” version of reactive hypoglycemia, leading to hunger again after a few hours following food consumption. Insulin drives calories, as fat, into adipocytes. It also keeps those calories there. If insulin is abnormally elevated for longer than it should be, one becomes hungry while storing fat; the fat that should have been released to meet the energy needs of the body. Over time, more calories are consumed; and they add up.

The above interpretation is consistent with the result that the percentage of fat in one’s diet has a statistically non-significant effect on total calorie consumption. That association, although non-significant, is negative. Again, this looks paradoxical, but in this sample animal fat displaces wheat flour.

Moreover, fat leads to no insulin response. If it comes from animals foods, fat is satiating not only because so much in our body is made of fat and/or requires fat to run properly; but also because animal fat contains micronutrients, and helps with the absorption of those micronutrients.

Fats from oils, even the healthy ones like coconut oil, just do not have the latter properties to the same extent as unprocessed fats from animal foods. Think slow-cooking meat with some water, making it release its fat, and then consuming all that fat as a sauce together with the meat.

In the absence of industrialized foods, typically we feel hungry for those foods that contain nutrients that our body needs at a particular point in time. This is a subconscious mechanism, which I believe relies in part on past experience; the reason why we have “acquired tastes”.

Incidentally, fructose leads to no insulin response either. Fructose is naturally found mostly in fruits, in relatively small amounts when compared with industrial foods rich in refined sugars.

And no, the pancreas does not get “tired” from secreting insulin.

The more refined a carbohydrate-rich food is, the more carbohydrates it tends to pack per unit of weight. Carbohydrates also contribute calories; about 4 calories per g. Thus more carbohydrates should translate into more calories.

If someone consumes 50 g of carbohydrates per day in excess of caloric needs, that will translate into about 22.2 g of body fat being stored. Over a month, that will be approximately 666.7 g. Over a year, that will be 8 kg, or 17.6 lbs. Over 5 years, that will be 40 kg, or 88 lbs. This is only from carbohydrates; it does not consider other macronutrients.

There is no need to resort to the “tired pancreas” theory of late-onset insulin resistance to explain obesity in this context. Insulin resistance is, more often than not, a direct result of obesity. Type 2 diabetes is by far the most common type of diabetes; and most type 2 diabetics become obese or overweight before they become diabetic. There is clearly a genetic effect here as well, which seems to moderate the relationship between body fat gain and liver as well as pancreas dysfunction.

It is not that hard to become obese consuming refined carbohydrate-rich foods. It seems to be much harder to become obese consuming animal foods, or fruits.

Great New Product

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Here's how it works: bozolol actually increases the uptake of fat-soluble vitamins from your food, while reducing inflammation in the arteries and helping you shed fat faster than a pork roast! Guaranteed! Learn more about it here. 

April fools!