The Spark of Reason

Comment on Guyenet vs. Taubes; or Why I Don't Give a Crap What the Kitavans Eat

2011-08-12T09:16:00.000-07:00

This post started as a comment to Stephan Guyenet's excellent post on the carbohydrate hypothesis of obesity, got too long, and so I'm putting it here. Do read Stephan's post, and keep an open mind. It's got loads of interesting and cutting-edge science, and this sort of debate and information exchange is how science progresses. If you find yourself experiencing cognitive dissonance, remember that absolute belief is antithetical to science. We always must update our beliefs as new information emerges.

Short summary of Stephan's blog post: the hypothesis that carbohydrates in general are fattening is probably over-simplified and does not reflect the most recent scientific understanding of metabolic regulation. It also leads one into a variety of paradoxes, a la the "French Paradox" of the diet-heart hypothesis.

I think part of what we're seeing here is the rather poor taxonomy of nutrition. We discuss things in terms of macronutrients, but those macronutrients come with (or without) all kinds of other metabolically relevant substances. And even within a given macronutrient group there can be significant metabolic differences, e.g. for fatty acids of different chain lengths, or between glucose and fructose (though Dr. Feinman might have something to say about the latter).

I've posted here before on my favorite example of this, and it seems like a good time to revisit (working from memory and about 4 hours of sleep, so please correct me if necessary). The Aztecs had a corn-based diet. They did experience obesity, but despite documenting a wide variety of health issues in detail never described diabetes. The Egyptians ate a wheat-based diet, also experienced obesity (along with heart disease, cancer, and the whole host of other fun "diseases of civilization"), and did document diabetes. Two high-carb diets, both resulting in some level of obesity, but from what we can tell (thousands of years later), both having radically different metabolic endpoints.

Two take-home points here. First is that we likely need to consider a broader dietary context than that imposed by our artificial macronutrient classification scheme, i.e. wheat and corn both provide primarily carbohydrates as energy, but probably do not have the same metabolic effects, particularly when considering over the timescale of a human life. Second, obesity is a symptom. A given symptom may result from multiple underlying conditions. We need to focus the discussion on more specific pathologies than just "obesity".

In the US and many other Westernized countries, one can take a look around and do a "liver check". How many people do you see with a protruding pot belly as opposed to a general body-wide distribution of fat? Most people I see have the big belly, sometimes even being very lean elsewhere (particularly in the arms and legs); there are a few "Rubinesque" figures as well, but the pot bellies seem to be running away with the obesity stakes. The big belly is indicative of fatty liver. Considering how central the liver is in metabolic regulation, it should come as no surprise that an inflamed fatty liver could lead to a whole host of metabolic disturbances: obesity, abnormal lipid profile, elevated blood sugar, elevated insulin, etc. In other words, metabolic syndrome.

I would argue that the rapidly growing health problem is not simply obesity, but metabolic syndrome (remember obesity is only one symptom, and there are thin people with metabolic syndrome too). We want to understand both how we arrive at metabolic syndrome (so our children can avoid it), and also how to treat it for those who did not avoid it. It is clear "carbohydrates" across the board are not causal in the development of metabolic syndrome. Stephan provides several counter-examples; another is the Tarahumara, who like the old-school Pima subsist largely on corn, beans, and squash, but who have one of the lowest rates of Type 2 diabetes in the world.

But the cure is not necessarily the reverse of the cause when it comes to disease. Metabolic syndrome brings a whole host of issues, not the least of which is broken carbohydrate metabolism. So while carbs in general may not lead to metabolic syndrome, once you've arrived dumping carbohydrates on your broken carbohydrate metabolism is tantamount to doing jumping jacks on two broken legs. I believe the science (along with a massive stack of anecdotal evidence) is pretty clear here, in that the most successful treatment for metabolic syndrome is carbohydrate restriction.

So while yes, Virginia, the Kitavans eat a very high-carbohydrate diet and exhibit general metabolic health, for my personal dietary choices I don't really give a crap. The Kitavans have healthy carbohydrate metabolisms, but I don't (prior to going low carb I had a trophy beer gut, which in retrospect was my liver telling me "You're killing me slowly"). If you look down toward your feet and can see only your protruding liver, you might consider trading in the bagels for bacon (better yet, get yourself a blood glucose meter and check your post-bagel blood sugar - it might frighten you). It is important to remember that carbohydrate restriction is successful as a treatment for a disease, but it doesn't necessarily follow that all carbs are bad for everybody. We have several examples of cultures who thrive on diets of lean protein and whole food sources of carbohydrate, like starchy tubers and fruit. We also have examples of cultures thriving largely on protein and fat. Humans appear to have a remarkable ability to survive as omnivores eating whole foods, which in no small part explains why we are one of the most widely spread species on the planet. So if you have a healthy metabolism, you probably can choose from a wide variety of whole foods (and by "whole food" I mean something you could plausibly obtain from Nature without the aid of much more technology than fire and a sharp stick). Once your metabolism is broken, you will likely need to make some choices to avoid those things which, due to your disease state, have become effectively toxic. In other words, make your nutritional choices based on actual knowledge of metabolism and your own state of health rather than picking a buzz-phrase and applying it blindly.

And for God's sake, stop eating wheat ;-)

On Taubes and Toilets

2011-01-29T11:06:00.000-08:00

One of our toilets has been acting balky lately. Last night I went to flush it and nothing happened. I started pondering on the possible causes of this, and had a brief vision of a bunch of Ph.D's standing around, stroking their chins and sagely examining the toilet through glasses perched on the ends of their noses. After a few knowing glances at each other, they pronounced: "From the First Law of Thermodynamics, we know the problem with your toilet is that, at some point in the past, less water came in than left!"

Maybe I should have skipped that last martini at dinner last night.

Anyway, my imaginary colleagues were only acting as scientists often do, pronouncing "truth" without getting to the root cause of the issue. Or perhaps my subconscious has been imprinted from too many conversations like this with my children:

Me: "How did you get so dirty?"
Child: "I was playing in dirt."

Back to the toilet. My imaginary scientist friends, while technically correct, were (as scientists often are) totally unhelpful. If I were to fix my toilet, I would need to know how it works, particularly the possible failure modes. In other words, I need to get to the root cause of why it didn't flush. Once I know what's actually broken, I can fix it. Invoking the First Law of Thermodynamics might make one sound smart, but it doesn't get my toilet flushing again. And believe me, in this case it was a vital importance to identify and repair the root cause, posthaste.

The toilet is actually an example of a self-regulating system, by which I mean that when it works correctly, I don't have to pay attention to it. If you're not familiar with the workings of the common toilet, check out this entry at HowStuffWorks.com. Basically, there's some clever gadgets in there that make sure things go smoothly. When you push the handle down, it pulls up the flapper, basically a rubber stopper with a hole in the bottom. There's air inside the stopper, which causes it to float open as long as the water level is above the stopper. Once the water is gone, the stopper closes. That's the output side. The input side is controlled by a float-activated valve. When the water level falls, so does the float, which opens the valve and lets water into the tank. As the tank fills, the float rises until it hits the switch and shuts the valve, turning off the water. This whole setup is basically tuned to ensure that you have enough water leaving the tank at the proper rate to get a good flush, while not having too much water enter the tank and thus flooding your bathroom. The toilet has an additional fail-safe to avoid the latter fate, in the form of an overflow pipe. If your float switch doesn't work, then the water goes down the overflow pipe instead of all over your floor.

My particular problem was too little water, not too much. Since I have confidence in the First Law of Thermodynamics (at least in approximately flat regions of spacetime, like my bathroom), I know that something caused the tank to not fill. The water didn't fill the tank at some point then magically vanish. One possibility was that my water main had broken. Checked the sink faucet, plenty of water there. Rather than stand around and be mystified by the inner workings of my toilet, I opened it up and took a look inside. No water alright, and it looked like the float was stuck. A quick poke and the toilet started filling. The moral of the story is that the laws of physics don't tell you how things work, but rather the constraints under which they work (e.g. the amount of water leaving the toilet in a flush is the same as the amount that entered when it filled). To solve my problem I needed to understand the mechanism by which the toilet regulated water flow and level, and how that regulation could go wrong. In other words, if you know what causes the toilet to work correctly, then you can infer what might cause it work incorrectly, and take appropriate action.

If you've read Gary Taubes most recent work, Why We Get Fat, you probably have realized by now that my toilet story is a bit of a setup. Why We Get Fat (WWGF) is generally described as "Good Calories, Bad Calories" lite, but it is a bit more than that. Taubes has focused on obesity in particular, and honed his arguments and presentation, and brought in some more recent research as well. It's an excellent and fast-paced read, and I highly recommend it.

The key hypothesis of WWGF in terms of obesity is the same as GCBC: that obesity is the result of a failure in the regulation of metabolism, specifically carbohydrate metabolism. A broad set of critics attack both GCBC and WWGF on various detailed points, while missing the big picture. For instance, there's much ado about the specifics of Taubes' hypothesis on how this failure in carbohydrate metabolism arises. Taubes posits that overconsumption of carbohydrates basically leads to insulin resistance (though notes that the situation may not be so simple), while others point to various evidence that it may be specific carbohydrates (fructose), or vegetable oil, lack of physical activity, etc. These make for nice academic discussions, but if you're one of the millions of people with a broken metabolism, none of this is very helpful. Much as was the case with me and my toilet, if you're going to fix your metabolic machine, you need to have some idea of how it works and what might be go wrong. WWGF is a great place to start educating yourself, provided you don't fall in the trap of running around screaming "I can't see the forest because I've got blood in my eyes from running into all of these damned trees!"

The publication of WWGF has also revived the strident preaching from the members of the Holy Church of the First Law of Thermodynamics. Now, I'll give you a pass if you read GCBC and perhaps came away thinking that Taubes implied that low carbohydrate diets somehow got around energy conservation. GCBC was a dense book, and Taubes (who was a degree in physics) no doubt thought that the First Law was just generally held to be true and that nobody would question his belief in it, and so didn't focus on it much. Taubes clearly learned the hard way that you can't take these things for granted. WWGF has two chapters on this topic, and makes it very clear that 1) Yes, Virginia, the First Law of Thermodynamics is alive and kicking, but 2) that the First Law adds no information as to the cause of obesity, or what you might do to fix it. If you read WWGF and still think Taubes is claiming that thermodynamics doesn't apply to biological organisms, then you either didn't really read the book, weren't paying any attention, or have the logical facilities of a monkey on crack.

The real lesson of WWGF is the same as my toilet story: just knowing the constraints on the workings of your body (e.g. conservation of energy) is not the same as knowing how the pieces actually fit together, the cause-effect relationships that make the whole machine go. You can't fix something without having some idea of how it works, whether it is a toilet or the human body. Like my toilet, your metabolism (and that of all living organisms) is self-regulating. Humans seem to be control-freaks in general, and we think that every aspect of life needs constant attention, much like driving a car (I wish people paid as much attention to driving as they do to other less consequential things, like whether or not their children poop enough times a day). But when my toilet works right, I don't have to sit in the bathroom and monitor it, waiting to shut off the water if there's an overflow, or fiddling with the float valve switch. It just does it's thing. Metabolism is the same way. Energy regulation is the key aspect of life, from bacteria to humans, and most life doesn't have the capacity to fret about how many calories it ate or how much it exercised. If your metabolism is operating correctly, by definition it is impossible to eat too much. When you have too much energy stored, the body has ways of eliciting biochemistry and behavior (which is just complicated biochemistry) to bring things back into balance: appetite is decreased, thermogenesis is increased, you have the urge to move around, etc.

If you're obese, you don't have a character or mental defect any more than my balky toilet does. You have a physical problem in metabolic regulation. Invoking the First Law of Thermodynamics and berating obese people as having a behavioral issue does not address the root cause of obesity, any more than a similar approach would have worked in fixing my toilet (I'm having visions of registered dieticians bitching out my commode for lack of self-control). WWGF is a great place to start "opening the box" and empowering yourself to start giving the "experts" the finger, stop feeling like a failure because your experience doesn't agree with their beliefs, and get down to actually solving the problem.

Have We Reached the Tipping Point?

2010-11-16T16:26:00.000-08:00

A very quick post here. Take a look at this article: http://www.foodnavigator-usa.com/Science-Nutrition/Low-fat-diets-could-increase-heart-disease-risk-say-nutrition-experts/

If the American Dietetic Association is flipping on low-fat diets, I'd say that signals the beginning of the end (hat tip to the Hold the Toast blog). Still waiting for Dean Ornish to jump out tell us we've been punk'd.

Also check out the Fat Head take on the Twinkie diet. Nice analysis of the food logs.

If you are what you eat, what does that say about "The Twinkie Diet" professor?

2010-11-10T08:26:00.000-08:00

I've had a few questions on the "Twinkie Diet" that's been buzzing about the Internet, so here's a few thoughts...

The gist of the Twinkie business is that professor of human nutrition Mark Haub lost 27 pounds over 10 weeks by eating largely "junk food", like Twinkies. The "secret" was that he cut calories from 2600/day to 1800/day. Haub's point was to show "in weight loss, pure calorie counting is what matters most -- not the nutritional value of the food". This gets the "well DUH!" award for the month. Suppose you ate nothing at all. You'd be getting zero nutritional value. Do you think you might lose weight? Hmmmm, could be, doc.

The deeper issue here is apparent ignorance of people like professors of human nutrition about the basics of metabolic regulation. To first order, if you keep the macronutrient ratios about the same in your diet and reduce calories, you will also reduce the amount of insulin your body secretes in response to that food. As oft noted on this blog, insulin is a major metabolic hormone, governing a wide variety of processes having to do with the utilization and storage of energy, not the least of which is driving fat storage. More insulin means more fat storage. Less insulin means less fat storage. Drop insulin enough and on average more fat leaves the fat cells than is stored. The root cause of fat loss under calorie restriction is NOT simply restricting calories, but the result that calorie restriction has on your hormones, particularly insulin. For anecdotal evidence of this, you could ask a Type II diabetic who has to take insulin injections how hard it is to lose fat even by starving. More controlled experiments have been performed in animals. For instance, you can take an obese rat, keep it's insulin levels artificially high, and starve it. Said rat will literally starve to death while obese, consuming it's internal organs for energy, because the high insulin level effectively keeps fat locked up in fat cells.

So yes, of course, you can eat a calorie restricted diet of Twinkies and lose fat. But failing to understand how all of the metabolic dots are connected leads to several common backwards assertions made in the article, e.g. "Being overweight is the central problem that leads to complications like high blood pressure, diabetes and high cholesterol". Sure about that doc? Or do obesity, high blood pressure, diabetes, and high (LDL) cholesterol have a common cause, like say excess insulin? After all, there are skinny people with high blood pressure, diabetes, and high cholesterol. There are obese people who otherwise tape out as very healthy. So obesity is clearly not a cause, at least not the root cause. Insulin modulates a large number of genes, and so the precise set of symptoms a person experiences from hyperinsulinemia is going to be a function of their specific genetic makeup. A key test of a scientific hypothesis is its predictive power. The hypothesis that obesity causes Type II diabetes misses by tens of percent. But 100% of Type II diabetics are hyperinsulinemic, whether or not they are obese. Where would you put your money?

The key take-away here is that there is a large body of "health professionals" who essentially view the human body as a black box, and as such tend to come up with hand-waving and over-simplified "rules" linking various externally observable effects, like "calories in, calories out" (strictly true, but pointless because it makes no connection between cause and effect). As such, the recommendations of these people rarely rise above the level of old-wives' tales, in terms of the strength of evidence supporting them. When we "open the box", and begin to understand how the inputs and outputs are connected, and further how the body maintains control over metabolism and behavior in an attempt to maintain "health", things become much clearer. If your health expert has this knowledge, you are very lucky. Most are ignorant, and likely will remain so, as once a person deems themselves an "expert", they no longer feel the need to learn anything new (particularly if it contradicts their "expertness"). So it is going to be up to you to gain some measure of knowledge, so that you can make informed decisions for yourself.

If you are a person with any degree of scientific interest and background, then I hope you will have read "Good Calories, Bad Calories" (or a similar book) by now. If not, then shame on you for purposefully maintaining your ignorance. While no book (even a scientific textbook) has the whole story, GCBC does a fantastic job of delving into the very well-established metabolic science linking insulin and various health issues. As oft noted within, most of this stuff is not considered controversial at all. The processes by which insulin regulates fat storage have been established for decades. The gap is simply one of knowledge, where "professors of human nutrition", medical doctors, and the like either don't learn this stuff, or fail to connect the dots: what you eat affects your hormones, which affect biological processes like fat storage, which affect other hormones, which can ultimately affect what you eat. Behavior, after all, is just another manifestation of biology. So it's going to be up to you to educate yourself to some extent. If you're more of a right-brain person or otherwise find GCBC a daunting read, Gary Taubes' forthcoming book "Why We Get Fat" might be more up your alley.

But if you choose to remain ignorant, and blindly follow "expert advice", you deserve exactly what you get.

Stupid = Fat + Sick?

2010-09-27T08:45:00.000-07:00

Just a quickie to point you to a great "tell it like it is" article at the Huffington post. Link below:

http://www.huffingtonpost.com/justin-stoneman/post_868_b_720398.html

The short version: before taking "expert" advice, check their shoes . . . and their motivations. I'll repeat it again: the only person who truly has your best interests at heart is YOU. Everyone else has some other axe to grind. Once in awhile you might luck out and find an "expert" whose goals are aligned with yours, but don't hold your breath.

Of Mice and Men, Meat and Wheat

2010-09-04T13:23:00.000-07:00

Last week, I saw a very interesting show on the Science Channel (or one of the Discovery family), called "How Food Made Us Human". I don't see any more showings coming up, but recommend you keep an eye out, definitely worth watching. Much of the material will be review for those who follow recent ideas on metabolism and evolution, but it was well done: easy to follow, concise, with some nice hands-on demonstrations of the concepts. One I like in particular was the "chewing machine". Some scientists rigged up a gizmo the simulate chewing, and then put in "teeth" taken from casts of Australopithecus and (I think) Homo habilis fossil jaws. Australopithecus has flat teeth, hypothesized to be better for grinding tough fibrous vegetation, while Homo habilis' teeth are smaller with more ridges, better for tearing. And this is exactly what was demonstrated: the Australopithecus jaws made short work of a carrot in a single bite, but barely put a dent in a piece of raw meat. Homo habilis nearly cut the meat in half with a single bite.

In another fun experiment, several human subjects were "locked up" at a zoo, and fed something like the diet of our closest primate relatives (chimps and gorillas), consisting of raw fruits and vegetables. It was mostly vegetables, if I remember correctly, lots of clips of people gnawing on carrots, raw broccoli, and the like. Long story short, everybody hated it. They spent about half the day doing nothing but chewing, and were starving nonetheless. I believe the average weight loss quoted was something like 10 pounds in two weeks (I meant to watch the show again and take notes, but this is the first "free" time I've gotten, and it's only because I'm at the park with the kids). Subjects apparently spoke of the desire for meat quite a bit (when they weren't bitching about all of the chewing and frequent bathroom visits). It's a fun experiment you can try at home yourself!

One part of the show which rather surprised me: one of the scientists visited a remote tribe in Africa who were still living a fairly primal hunter-gatherer existence. What struck me was that these people looked like crap, nothing like the sort of pictures taken by Weston A. Price, or the fossilized H. habilis jaws shown in the chewing experiment. Their faces showed signs of nutritional stress, with small jaws and crowded teeth. One hint here may be the effort they went through to get meat. In the show, they had a porcupine cornered in its burrow (BTW, this thing was huge, the size of a really big dog). The tribesmen spent the better part of the day digging 6-foot deep holes, until they forced the porcupine into the Hobson's choice of which hole to get speared in. It was a tremendous amount of effort to get some meat, and one of the hunters basically said "porcupine sucks, but at least it's meat". They also discussed how socially important it was for hunters to bring back meat, that it brought them status in the tribe, etc. Clearly, meat is at the top of the menu for these people. Yet that they would go to such lengths to obtain it (particularly when they find porcupine distasteful) makes me wonder if hunting isn't so good in this region anymore. Perhaps game has become scarce, hence the appearance of nutritional stress? Yet they're hanging in there, if nothing else a testament to the tremendous adaptability of humanity, made possible by our big brains (and what do you suppose made those big brains possible?)

Anyway, "How Food Made Us Human" has spawned a couple of trains of thought, which I want to share with you here. The first has to do with a mouse experiment demonstrated on the show; the second with the correlations between diet changes and physiological changes over the course of evolution.

The mouse experiment was very interesting, intended to show the effect of cooking on caloric bioavailability. Take some mice, feed them raw sweet potatoes, and measure the change in body mass as well as activity (based on distance run on the exercise wheel). Now cook the sweet potato and do the same thing. If you're still stuck in the calories-in calories-out (CICO) paradigm, the results should spawn massive cognitive dissonance. The mice who ate the cooked food showed the following differences when compared to those eating the raw food:

They exercised significantly more, AND
They were heavier.

That's worth thinking about for a moment, particularly if you think that obesity is caused by conscious choices favoring gluttony and sloth. When the mice ate cooked sweet potato, they exercised MORE than those eating the raw version. Does cooking food spur psychological changes that cause you to become less lazy? But despite exercising more, the mice still got heavier. Put that in your pipe and smoke it, CICOs.

Of course this all makes perfect sense when considered from the standpoint of evolution and metabolic regulation. Cooking makes calories more available. Though they didn't explicitly say so in the show, one presumes that the quantity of potato was held constant between the two groups (since not doing so would void the entire point of the experiment). So the only difference (presumably) was raw vs. cooked. Mice didn't evolve eating cooked food. The higher caloric availability likely "fooled" their digestive systems into taking up calories too rapidly, faster than required to support normal metabolic operations. Rate of digestion is regulated by hormonal and nervous feedback mechanisms: when the brain and other internal sensory systems think there's enough energy around, gastrointestinal motility decreases, slowing the rate at which food leaves the stomach to be digested and absorbed in the small intestine; and of course when an energy deficit is detected, food moves more rapidly out of the stomach. When the stomach is empty AND your body senses an energy deficit, you get hungry, and are driven to find more food.

That's how it supposed to work. Like all feedback control systems, if you push outside the "designed" range of stability, it starts failing. I expect this to be particularly the case with biological systems. Biological responses tend to follow "S-curve" shapes. There's nothing deep about this. It simply reflects the fact that biological responses are limited by available resources. At some point you run out of the capacity to make more hormones, neurotransmitters, receptors, etc. Insulin response is a great example. As a function of blood glucose, the secretion of insulin follows a shape much like that seen on the Wikipedia page. At some point you either saturate the ability to detect glucose, or saturate the ability of the pancreas to crank out insulin, or both. The point is that it is possible to exceed your body's ability to effectively control blood sugar levels via the action of insulin, simply by changing the effective "sugar density" of the food you consume.

Back to our mice: when faced with an excess of calories, how can the mouse's body respond? It can either store energy, or burn it off (or both). We know some of it got stored, as the mice got heavier. The show gave one example of "burning it off", in the spontaneous increase in activity. I don't know if they measured it, but I'd wager that the mice also gave off more heat, which I think is a more effective way dumping energy. Muscles are remarkably efficient, and it is surprising how much mechanical work you can get out of a kilocalorie, when compared to the equivalent thermal energy (1 kilocalorie will raise 1 kilogram of water only 1 degree C in temperature, but raise a 1 kg mass over 400 meters against gravity). So the outcome of the mouse experiment is wildly inconsistent with the CICO paradigm, but precisely what one might predict from evolution and metabolic regulation. It would be very interesting to see what would happen if the mice were allowed to continue eating cooked sweet potatoes for a longer time period. I wonder if they would develop mouse metabolic syndrome?

The second line of thought follows the main line of reasoning from the show, which is thus: by incorporating more nutrient dense foods into their diets, our hominid ancestors set in path a major evolutionary shift, where gut size was exchanged for brain size. The argument is elegant: if you eat food with greater bioavailable caloric density, you can spend less energy on digestion. That opens up an evolutionary pathway to increase brain size and energy expenditure at the expense of the gut, because you can extract the same energy from food with a smaller and less-demanding digestive system. And indeed, the fossil record seems to indicate that the major jumps in hominid brain sizes came at two critical nutritional junctures. The first was around the time we started eating meat. The second was when we started cooking food, and cooking is hypothesized to have led to modern humans.

It's interesting to consider the evolutionary advantage brought about by our big brains. What advantage did they bring our hominid ancestors? The scientist visiting the African hunter-gatherers went on a bit about how hunting is a fairly complex behavior, particularly as practiced by humans. But there's a lot more to it than that. The brain remembers - it stores information. And an "advanced" brain not only remembers information, but can extrapolate it to the future, making choices now that create advantages later. For instance, it's good to know that when the rains come, wildebeest are going to show up and a certain place, and that there's an effective method for cutting one out of the herd, how to make the tools you need to kill and butcher it, which parts are good to eat, etc. In the context of hunting and gathering, there's a positive feedback loop between the increase in nutrient density and encephalization, each reinforcing the other.

Of course, there's been another major shift in nutrient density since the advent of cooking: agriculture. The advent of agriculture is an interesting case. At first blush it doesn't seem so hot. The main thrust of human agriculture has been domestication of annual grasses for their seeds, i.e. grains. Across the world, in geographically separate locations, populations growing different crops (wheat, corn, rice) uniformly appear to show significant increases in the chronic "diseases of civilization". But evolution doesn't care if your teeth fall out or you drop dead from cancer at age 40. All evolution cares about is reproductive fitness, and agricultural humans had an undeniable reproductive advantage over hunter-gatherers; otherwise we wouldn't be having this conversation.

We had a hint from the mouse experiment above that an increase in dietary effective energy density could lead to "metabolic overload", exceeding the body's ability to balance and regulate the intake and expenditure of energy. And indeed, the evidence continues to mount that a good chunk of our modern epidemic of chronic diseases may be attributable to such metabolic malfunction. It makes me wonder what happened to our Australopithecus ancestors when they started eating meat: did they suffer metabolic disease as well? It's an academic question, of course, as chronic disease or no, meat-eating proved to increase reproductive success. We might ask a similar question about what occurred as cooking gained popularity. These are hard questions to answer from the fossil record. Agriculture happened much more recently, and further is amenable to archaeology (agriculturists tend to gather in large numbers in one spot, as opposed to wandering all over the place looking for food).

But here's a thought: we noted above that big brains are useful for remembering lots of stuff. This is important when living as a hunter-gatherer, because the dynamics of nature are complex. Maximizing reproductive potential in this context means being able to remember and extrapolate the myriad (and often subtle) cause-and-effect relationships of the natural world, along with whatever technological innovations are required to take advantage of this knowledge. This information does not get passed on genetically, but rather through communication, i.e. parents teaching children. Knowledge is power, in a very tangible sense, when talking about hunter-gatherer survival. Greater knowledge implies greater ability to obtain nutrient-dense food, hence greater reproductive fitness; it also means that it takes longer to get that knowledge into the brains of your offspring. It is often argued that diseases of civilization have little effect on evolution, because they generally kill you after the reproductive years. But that assumes the only information being passed along is genetic. If memories are also required for the reproductive success of your offspring, it pays to live long enough to pass along that information. And if you follow this line of reasoning, it's clear there's a volume of information at which the parent will not be able to effectively communicate the body of knowledge while still performing hunting and gathering activities required for survival. Enter Grandma and Grandpa. If the information volume for reproductive effectiveness is sufficiently large, it pays to live long enough to pass along that information to your offspring, their offspring, and so forth. Correspondingly, adoption of new dietary practices must either preserve this longevity, OR require less information to be effective.

So where does agriculture fit in? Is the adoption of agriculture, which brings with it ever-increasing energy density in food, driving us toward the next phase of "big brain" evolution? Good question - but consider this: how much do you need to know to be an effective agriculturist? I would argue rather little, compared to hunting and gathering. A hunter-gatherer may have thousands of foods in their diet, and they have to know where and when to find them, how to prepare them, etc. Agriculturists have relatively narrow diets, and there's a relatively simple and fixed pattern to the whole business: plow the land, plant the seeds, keep out the weeds, harvest. Lather, rinse, repeat. So I think you can argue that agriculture has a much smaller information burden than hunting/gathering. The tremendous technological increases since the advent of agriculture are a testament to how relatively little brain-power is needed for obtaining food anymore, as we apparently had plenty of spare brain capacity to monkey around with things not directly related to getting fed.

Now it is well known that brain volume decreased dramatically with the advent of agriculture. So did adult lifespan. Yet the agriculturists clearly laid the smack-down on the hunter gatherers, evolutionarily speaking. So neither long-term health nor brain size is a reproductive advantage once you start growing your own food (or at least the foods that our ancestors chose to cultivate). There's no point in fueling a big brain if you've got nothing to put in it. And there's no point in keeping old people around if they are not able to contribute directly to the reproductive fitness of their offspring. If you can't work the fields, don't make babies, and we don't need your accumulated wisdom, then you're pretty much just eating food better used for making more genetic copies. So for an agriculturist, dropping dead at 35 may actually have been an advantage.

It makes me wonder what direction agriculture (and more recently, industrial food processing) is driving our "humanness". Does the ever-growing energy density and general availability of food imply we'll evolve even smaller guts and bigger brains? I'll put my money on "No". After all, look around you: it's not like the smartest people are the most successful reproductively. You can damn near be vegetative, contribute nothing to society at all, yet we will ensure you've got all the Big Macs and Twinkies you can stuff in your face to fuel the generation of lots of babies to do the same thing. In our current environment, evolution favors being chronically ill and stupid. It doesn't really matter how much we wring our hands about ethics, culture, and society: reproductive success always wins. So if humanity wishes to achieve its stated long-term goals of giving people long and healthy lives while living sustainably on Earth, we'd better figure out how to align those goals with Nature's overriding law of reproductive fitness.

Cognitive Dissonance: Not Just for the Layperson

2010-07-23T06:27:00.000-07:00

I must admit, I had not carefully read Dr. Campbell's "last word" from the "discussion" of his reply to Denise Minger. His refusal to engage in discussion told me everything I needed to know. But in spelunking around for something else on that page, I came across this quote:

I had hoped to have had a civil discourse, but this is difficult when the questions come from uncivil people. I also don’t have time to answer superficial questions of others like ‘what is the detailed mechanism of protein induction of high cholesterol levels’ – that easily could become an entire but relatively useless dissertation when the “mechanism” most decidedly is a symphony of mechanisms, as I explained in our book. At this point, the far more important observation is the dramatic increase in serum cholesterol.

Hmmm, I wonder what Campbell's definition of "uncivil" is? Seems to have some conceptual overlap with the second sentence, i.e. those who ask "superficial" questions are being "uncivil". The question in question came from me, and I'm glad to see it had one of the desired effect. My preferred outcome would have been that Dr. Campbell actually answered the question. Then I would have learned something. It is unfortunate that he instead evaded the question as above, because then all we learn is that a) he doesn't have an answer, but b) thinks he does, and is thrown into painful cognitive dissonance when confronted by the truth of his ignorance. The nonsense about there being a "symphony of mechanisms" is, I believe, a subtle trick played on Dr. Campbell by his own mind. There are indeed many possible causes, and may be several interacting processes. But he confuses "I don't know which of the many possibilities contributes to the effect" with "here is what we know, a complex process". Classic mental band-aid for cognitive dissonance.

Anyway, I think my goal has been accomplished. I wanted to know if Dr. Campbell had any relevant information. If not, I wanted him to publicly torpedo his own credibility. Mission accomplished. Next time he wants to show up and bash a low-carb or paleo book an Amazon, you have ample material to demonstrate his irrationality.

What T. Colin Campbell Didn't Want You to See

2010-07-22T08:57:00.000-07:00

T. Colin Campbell has chosen to not participate in any discussion of his own "scientific results". Take a look at his last word on the topic, note metadiscussion of what "science is about" rather than actually discussing any science, and check the shoes.

The great thing about the Internet, of course, is that it is impossible to censor anything. I'm pasting the comments I submitted to Campbell's site below. These were not approved. Compare with the openness displayed by Denise Minger in publishing comments from all comers, and fostering open discussion. Draw your own conclusions. If you have submitted comments to campbellcoalition.com that were not published, feel free to post them in the comments here. I'll send through anything that isn't overt spam.

To be fair, these comments may yet show up. There is a perfectly acceptable explanation that they haven't been published yet. I'm sure most bloggers have experienced "falling behind in comment moderation". If these comments are published, I partly retract my criticism. But the main portion remains valid: exchange of information is crucial to scientific progress. If you're not willing to exchange information, you're not interested in scientific progress.

I posted this just because it seemed odd to be revising such a benign comment. Who does this, and why?

Uh, why did your answer to my original question change from ““Dr. Campbell said he will be able to post comments now and then, although he cannot respond to every question.” to “Dr. Campbell said he will participate to the extent possible.”? Those seem like they say the same thing to me.

At any rate, I expect Dr. Campbell will find it a better use of his time to respond to specific points here rather than having to write lengthy detailed work such as above.

Here's a harder question:

From the response above:

“First and foremost, our extensive work on the biochemical fundamentals of the casein effect on experimental cancer in laboratory animals (only partly described in our book) was prominent because these findings led to my suggestion of fundamental principles and concepts that apply to the broader effects of nutrition on cancer development.”

Can you explain what these fundamental principles might be, or at least direct me to a detailed discussion? Proteins are broken down in to amino acids in the gut (at least in healthy individuals). These amino acids are then transported throughout the body, where they may be used to build new proteins. How does a specific mixture of amino acids trigger cancer growth? And of course I doubt most free-living organisms eat large quantities of isolated casein. So if I eat a meal containing casein, the mixture of amino acids absorbed reflects that off the total protein content of the meal, not just the casein.

It seems that in order for casein to have a specific role, it would need to trigger some other biological response beyond it’s simple amino acid content. For example, we know that most cancers have a very high glucose requirement, as they largely rely on anaerobic glucose metabolism for energy. We might then expect insulin to be required to stimulate glucose transport. Some cancers do indeed show higher expression of insulin receptors, see e.g.

http://cancerres.aacrjournals.org/content/52/14/3924.abstract

From this we might hypothesize that dietary carbohydrates would drive cancer growth by providing both a supply a glucose and increased insulin secretion. It further can encompass other observations, e.g. the association of dietary fat and cancer. When eaten in combination with carbohydrate, fat will amplify insulin secretion.

Returning to your hypothesis that casein has a unique potential to stimulate cancer growth. What metabolic pathways are followed that create the “casein effect”? Is there some specific hormonal signal uniquely stimulated by casein?

And a link to a multivariate analysis that would answer at least some of Dr. Campbell's objections:

Here is an interesting blog on a multivariate analysis of China Study data:

http://healthcorrelator.blogspot.com/2010/07/china-study-again-multivariate-analysis.html

I put these comments under the post "The Challenge of Telling the Truth:

Nelson,

Your suggestion about keeping an “open attitude” is a good one. However, you need to keep an open attitude about scientific evidence as well. The way you talk about “truth of health” sounds a lot more like religion than science. Perhaps this is simply a communication gap. I sincerely hope that you and your father have the sort of open and inquisitive minds required for scientific progress. There is no absolute “truth” in science, as this would imply we have perfect information. I doubt even the staunchest supporter of any dietary dogma would claim that we have perfect understanding of the deep complexities of human biology.

I will reiterate here what I have said elsewhere: scientific progress is about two-way communication. You and your father likely have information that supports your hypotheses, information that others do not have. However, I’m sure you’d agree that others have information that you do not as well. The only way to reach “agreement” is communication, so we’re all on the same page. This is why dialog is so fundamental to scientific progress. I hope you and your father will participate in this dialog.

---------

“Despite lacking an adequate understanding of statistics and causality, this person used her intelligence and writing skills to compose a critique that might seem persuasive to laypeople.”

You might wish to expand on this a bit. It sounds like you’re saying she is both stupid (“lacking…understanding”) and intelligent in the same sentence. And I’m sure you would agree that “laypeople” need to have greater understanding of the issues so that they can make informed decisions, rather than simply picking an “expert” to blindly follow. Perhaps you can provide a little Statistics 101 discussion for us to better illustrate the shortcomings in Ms. Minger’s analysis for the lay public?

Yes, We Have No Bananas

2010-07-22T05:48:00.000-07:00

Just a very quick post. It's been almost a week since I submitted my registration for 30bananasaday.com. Prolific commenter "durianrider" is one of the principles at this site. You can read some of his "insightful" comments on the last post. Note, however, the one question I asked repeatedly, to which he gives no attention. Not only do I think I will never get approved to post on 30bananasaday.com, I doubt I'll even get a reason. Draw your own conclusions.

Another interesting development is the new(ish) web site campbellcoalition.com. Dr. Campbell's response to Denise Minger's critique is featured prominently, and better yet, Dr. Campbell has indicated that he may participate in some discussion here. I've posted a few questions, and urge others to do the same. I recommend you focus the discussion on scientific topics, as opposed to his opinion of Denise Minger, etc. Come armed with some hard questions on the connections between nutrition and metabolism, particular as they relate to Dr. Campbell's hypotheses. I believe this exercise has two realistic outcomes: either Dr. Campbell has some answers (which actually would be very cool), or he stonewalls. Either way we learn something interesting.

*** UPDATE ***
Well, it didn't take long for us to learn something interesting. From the comments on Dr. Campbell's reply to Denise Minger:

Based on the response received thus far, we have determined that our prior idea of a reasoned and civil discourse, with participation by Dr. Campbell, is not feasible and have decided to discontinue this discussion thread. Before closing, however, Dr. Campbell wanted to respond to comments from Denise Minger. Her comments are posted above, and Dr. Campbell’s response follows.

In other words, Dr. Campbell is going to have the last word, like it or not. So much for scientific discourse. The Campbells certainly could have chosen the path taken by Denise Minger - posting all discussion, whether "civil" or not, and choosing the reply to those questions or issues that are clearly intended to foster scientific discussion, and ignoring ad hominem attacks etc. Dr. Campbell's chosen course speaks to his true motivations.

If you have questions you posted to Campbell's site which did not make it through moderation, I invite you to repost in the comments here. Others can then see exactly what offended Dr. Campbell so greatly that he opted out of the discussion.

Going Bananas

2010-07-16T09:34:00.000-07:00

I got an "interesting" comment on my last post about Denise Minger's critique of "The China Study". It's the one from "durianrider" - check it out, particularly his "challenge". I've already answered the challenge, but invite others to also provide information about any elite non-vegan athletes they may know of. I have no illusions that we'll change durianrider's mind, or that of any "true believer", but the way to counter misinformation is with good information. Individuals need all the information they can get to make informed decisions, so let's make sure they get it, and support their right for informed choice. Personally, if you choose to be a vegan, that's fine with me. I have no stake in your personal lifestyle choice, but I do want to help people at least make that choice an informed one, rather than one based the propaganda of zealots.

And T. Colin Campbell, if you're out there, let's see if you have the courage of your convictions. I have a Ph.D. and was an academic research scientist for many years, so I should be "worthy" of scientific discourse with you. And discourse is at the root of scientific progress. How can you expect to educate people like me on your views if you are unwilling to discuss them with opponents in a public forum?

Related note: durianrider is also one of the principals of the 30bananasaday.com site, along with "freelee". Some of the discussion on the post "Debunking the China Study Critics" is pretty interesting, from a sociological point of view. I am going to try registering for the site, and see if they have any willingness to let in opposing views. The registration page and forum guidelines make me suspect they are intolerant of those who might not agree with them, e.g. this quote:

We will not tolerate "anti-fruit" posts or advice that recommends calorie restriction/or the suggestion that others are "overeating on fruit", also recommending others restrict their water intake will not be supported on 30BaD, these threads will be deleted and you will be given a warning. This advice is not only unproductive but dangerous to the health of our members.

One of the best signs of dogmatic belief is the intolerance of information which contradicts said belief. I'll reserve judgment on 30bananasaday.com until my application gets accepted or rejected, as I plan to make it quite clear that I will be providing evidence that runs counter to their mission.

For my part, I welcome discussion from all corners, provided it is reasonably civil (i.e. contains actual information rather than emotional spewing). The definition of rationality is that two people with the same information will draw the same conclusions. But the only way those two people can achieve the same state of information is through communication. Even if you completely disagree with my views, there's a reasonable chance that I will learn something from you which may help me make better choices. So bring it on!

The China Study: Crushed by its Own Data

2010-07-09T03:39:00.000-07:00

You may have already seen this outstanding analysis of the data from "The China Study". If you haven't, I highly recommend you give it a read. It's long, but well worth the effort. Readers of this blog know my opinion of T. Colin Campbell and his "scientific" work. Now somebody has taken the time to actually crunch the numbers, using Campbell's own data to demonstrate that his conclusions are baseless (at least when confined to this data), and probably the result of confirmation bias.

I also love the observation that, despite his constant whining about the "dangers of reductionism" in science, Campbell's entire argument against animal protein really hinges on a strongly reductionist experiment, namely the isolated effect of casein fed to rats in large doses. Snap!

Readers know of my criticisms of classical statistics, but it should be noted that I don't really have a problem with the mathematics, but the application. Math is what it is, either right or wrong. My issue is that classical statistics is used incorrectly, to draw inferences about hypotheses, when the underlying mathematical framework has nothing to do with inference. The key problem is that "statistics" are just numbers derived from data, like correlations. They don't say anything about a hypothesis: you will calculate the same correlation between two datasets, regardless of your hypothesis about what causes that correlation. Anyway, I don't want to get off on a rant. My point here is that the author, Denise Minger, does an excellent job of confining her analysis and conclusions within the bounds of what classical statistics can tell you. And along the way, she does a great job of demonstrating how easy it is to fool yourself (as T. Colin Campbell did - repeatedly) by over-interpreting these numbers which, in the end, cannot tell you anything more than what's in the data.

Ms. Minger has also done a great service in providing a concrete example of the issues in observational studies. You've likely read often that epidemiological studies are of little use in distinguishing between competing hypotheses. Now you have an example, replete with numbers. Ms. Minger demonstrates in several cases how a seemingly "obvious" conclusion vanishes once you dig into the large number of uncontrolled variables inherent in all observational studies. It's easy to find correlations in large datasets with many uncontrolled variables. The problem is that people take these correlations to mean more (or less) than they really do in terms of supporting/undermining a particular hypothesis, and the conclusions they draw are essentially ad hoc, not based on any rigorous mathematical analysis, but rather hand-waving about what is "obvious". An oft-quoted example is that men who shave daily have a higher incidence of heart disease. It is "obvious" that heart disease is not caused by shaving, right? Or is it? There's a whole lot of other information that goes into that judgment. We generally take this sort of thing for granted, especially when made in pronouncements from "esteemed" scientists like T. Colin Campbell. But if you dig into the reasoning behind these conclusions, you generally find a tangled web of assumptions, hypotheses assumed to be true, but which have varying (if any) actual evidence to support them. Ms. Minger does a great job of teasing these out of Campbell's reasoning, and demonstrating how the data itself provides little evidence one way or another, precisely because it cannot distinguish between the potential effects of the many intertwined and uncontrolled variables.

Anyway, enough of my babbling. Go read the article, you'll be glad you did (unless you're an uncritical fan of T. Colin Campbell, in which case you've got bigger problems).

Alzheimer's and RAGE

2010-05-21T07:25:00.001-07:00

Something I wrote in an email a while ago . . .

Advanced glycation endproducts (AGEs) are the endpoints of some complicated chemistry that occurs when simple sugars (glucose, fructose, etc.) react with proteins (and apparently fats too). They’re toxic for a variety of reasons, and trigger an inflammatory response via the receptor for advanced glycation endproducts, or RAGE.

It turns out that RAGE binds to a whole bunch of things, and amongst them is the amyloid beta peptide, which is implicated in the development of Alzheimer’s. Amyloid beta is apparently produced via neural activity. I can’t figure out if it has a function or is just a by-product. I suspect it has some function, because the body has a mechanism for achieving a balance in the central nervous system (CNS). One kind of receptor (LRP) causes active transport out of the CNS to the blood, while RAGE triggers transport from the blood to the CNS across the blood-brain barrier. More RAGEs means you’ll have more amyloid beta in your brain. I couldn’t verify this, but I would guess that insulin drives the formation of RAGE. It makes sense, as your body would be preparing for glycation damage (more AGEs) from increased blood sugar, whether the source was food or glucose released due to stress. And indeed, diabetics have higher concentrations of RAGE (as do the blood vessels in the brains of Alzheimer’s victims).

We learned today that stress actually increases amyloid beta production in the brain, via the action of corticotrophin releasing factor, or CRF. I got in contact with one of the authors of that study and he was nice enough to send me a reprint of the paper. It’s a pretty solid piece of research. Amongst other things, they showed that the more you stress mice, the more amyloid beta is produced. They could introduce CRF directly into the brain, and observe increased amyloid beta production. They could block the action of CRF, stress the mice, and see that less amyloid beta was produced. And finally they could directly block neural activity, and either stress the mice or introduce CRF, and again would see reduced amyloid beta. So it was a pretty solid case, albeit in mice. It would be surprising if humans turned out to be much different, though it’s certainly possible. CRF is released as part of the stress response. It is also released as a result of insulin-induced hypoglycemia, i.e. insulin goes up, blood sugar crashes, CRF pumps out.

One last piece of the puzzle: by itself, amyloid beta is soluble, and shouldn’t form solid plaques (or at least do so slowly). But test-tube experiments show that formation of solid “fibrillar aggregates” of amyloid beta are accelerated if you provide seeds of altered amyloid beta. And what’s one form of the alteration? Glycation damage from sugar.

So, less than surprisingly my hypothesis is that the route to Alzheimer’s mirrors that of heart disease. A high-carbohydrate diet leads to the following effects:

Increase in density of receptors for advanced glycation endproducts, which leads to increased amyloid beta concentrations in the brain.
Release of CRF, which increases production of amyloid beta in the brain.
Damage to amyloid beta, which increases the formation rate of solid aggregates, which may be contributory toward the formation of the plaques associated with Alzheimer’s.

And of course, there’s the usual feedback between stress and diet: psychosocial stress makes you want to eat more carbohydrates, which makes you more stressed, etc.

When Listening to Scientists, Be Sure to Check Their Shoes

2010-05-10T08:30:00.000-07:00

During college, I worked on and off as an intern at IBM Boulder. I remember when I changed departments, to work on management software for the facilities group (whose job it was to keep track of the walls and such - seriously, not as simple as you'd think). One of the senior guys named Tom took me out for my inaugural trip to the coffee machine. Back then we didn't have nice coffee set-ups like many companies do now, just a machine that gave you little paper cup of battery acid for a quarter. As we approached, there were some people ahead of us a the machine, including one of the managers I had just met. "You're gonna owe me a coffee," said Tom.

"Uh, okay," I said, thinking it was some new guy tradition to buy coffee. "Why?"

"See that guy?" asked Tom, indicating the manager.

"Sure, " I replied.

"Check his shoes."

I dutifully looked at the shoes. Seeing nothing out of the ordinary, I asked "What about his shoes?"

"They're full of shit."

I bought the coffee.

When you're getting information from scientists or other "experts", there are some good signs that indicate when a shoe check might be needed (to see what they're full of). One of the best is when scientists argue for/against a particular hypothesis by lecturing about the scientific method, rather than actual evidence. Usually this is a bitch-fest about how opponents of their views are unscientific self-interested boobs, while casting themselves like Gandalf on the Bridge of Khazad-dûm (paraphrasing a bit):

You cannot pass! I am a servant of the Secret Fire, wielder of the Flame of Science. The dark fire will not avail you, Flame of Dumb-Dumb! Go back to the shadow. You shall not pass!

Riiiiiight.

(Of course, since I spend a good chunk of this blog lecturing about scientific method, maybe I should check my own shoes :-)

I recently came across a couple of excellent examples of exactly this phenomenon, and thought we'd all benefit (and maybe get a good laugh) from checking the shoes of those involved. The first is T. Colin Campbell's "review" of the latest Atkins diet book. I haven't read the book, and am no particular fan of Atkins over any other diet, beyond the fact that it applies well-understood metabolic principles to achieve predictable results. And I won't spend time dissecting Campbell's review. He doesn't say anything that amounts to much beyond the Gandalf quote above (I can't shake this mental image of Campbell on the bridge, wielding a carrot and handful of wheat against a cow with a platter of bacon on its back). Jimmy Moore already did a great job of chewing up Campbell's argument, so I'll direct you there and to the links within (definitely see also Chris Masterjohn's review of "The China Study", and Campbell's unintentionally humorous reply). I just find it funny that Campbell is lecturing anybody about the scientific method, when he seems to apply it selectively, if it all. For instance, see his discussion about his personal "scientific philosophy" and "holistic" approach in The Protein Debate. I think it's pretty clear that Campbell is a conditional fan of the "scientific method," as long as it leads you to conclusions that agree with his own.

BTW, if you haven't read The Protein Debate, you should. For a long time you had to pay for access, but now it seems to be available for free. Loren Cordain provides a review of a lot of interesting evidence ranging from archaeological to biological, along with tons of references. Cordain has his own axe to grind, of course, so don't be fooled into thinking he's giving the whole picture. But he certainly provides a lot more background (164 references) than Campbell (0 references). Funny that Campbell complained in his Amazon review that Atkins never published a peer-reviewed paper and lectured on the requirement of peer review in "real" science (shoe check), yet neglects to reference said when arguing his own position. Read Campbell's part in the debate for lots of "check his shoes" examples. Plus it's great fun to see Campbell get handed his own ass - on a platter, with a side of bacon.

The second example is a letter to Science Magazine, entitled "Climate Change and the Integrity of Science". According to the guardian.co.uk,

A group of 255 of the world's top scientists today wrote an open letter aimed at restoring public faith in the integrity of climate science.

In a strongly worded condemnation of the recent escalation of political assaults on climatologists, the letter, published in the US Journal Science and signed by 11 Nobel laureates, attacks critics driven by "special interests or dogma" and "McCarthy-like" threats against researchers. It also attempts to set the record straight on the process of rigorous scientific research.

Wow, 255 scientists including 11 Nobel laureates? That's a lot of shoes to check. And we'll have to check those of Nobel winners twice.

The letter actually gets off to a good start:

We are deeply disturbed by the recent escalation of politicalassaults on scientists in general and on climate scientistsin particular. All citizens should understand some basic scientificfacts. There is always some uncertainty associated with scientificconclusions; science never absolutely proves anything. Whensomeone says that society should wait until scientists are absolutelycertain before taking any action, it is the same as saying societyshould never take action. For a problem as potentially catastrophicas climate change, taking no action poses a dangerous risk forour planet.

Clearly you cannot wait until uncertainties are resolved before making choices about how to deal with the possible outcomes of those uncertainties. And in theory, science is all about performing inference in the face of uncertainty, understanding how incomplete information about the world informs beliefs about competing hypotheses. Alas, the letter ruins this excellent start by espousing the opposite course, demanding that we should agree with their "facts":

Scientific conclusions derive from an understanding of basiclaws supported by laboratory experiments, observations of nature,and mathematical and computer modeling. Like all human beings,scientists make mistakes, but the scientific process is designedto find and correct them. This process is inherently adversarial—scientistsbuild reputations and gain recognition not only for supportingconventional wisdom, but even more so for demonstrating thatthe scientific consensus is wrong and that there is a betterexplanation. That's what Galileo, Pasteur, Darwin, and Einsteindid. But when some conclusions have been thoroughly and deeplytested, questioned, and examined, they gain the status of "well-establishedtheories" and are often spoken of as "facts."
For instance, there is compelling scientific evidence that ourplanet is about 4.5 billion years old (the theory of the originof Earth), that our universe was born from a single event about14 billion years ago (the Big Bang theory), and that today'sorganisms evolved from ones living in the past (the theory ofevolution). Even as these are overwhelmingly accepted by thescientific community, fame still awaits anyone who could showthese theories to be wrong. Climate change now falls into thiscategory: There is compelling, comprehensive, and consistentobjective evidence that humans are changing the climate in waysthat threaten our societies and the ecosystems on which we depend.

Oh brother, how much self-aggrandizing hyperbole can you pack into two paragraphs? Right off we get the lecture on the scientific method. The authors compare themselves to Galileo, Pasteur, Darwin, and Einstein (such name-dropping is another indication a shoe-check is required). The comparison with other "well-established" theories also needs some examination in comparison with the anthropogenic global warming (AGW) hypothesis:

The Big Bang (or whatever process created the Universe), formation of the Earth, and evolution have all occurred already. For that matter, so has significant climate change on Earth, without help from human beings. What we don't have is a way of testing specific predictions about the behavior of a very complex nonlinear system, namely that human behavior is the driving force behind the recently observed global temperature variations, and that changes in human behavior can alter the course of future climate change. Big difference.
The Big Bang, while "well-established" in the minds of physicists, is really only well-established in a semi-dogmatic sense. There are fairly major holes in the theory, in terms of predictive power. The current hypothesis required for getting from a Big Bang event to the Universe observed today ("inflation") has no evidential support - at all. It may be the best hypothesis we have at this point, but there's plenty of room for it to be supplanted by new information (and it wouldn't require much). The example is the most appropriate one for comparison to the AGW hypothesis, though for reasons opposite what the authors intended.
Estimates of the age of the Earth leverage some other very basic "facts", amongst them that statistical behaviors of radioactive elements are observed to be the same every time we look. The nucleus of an atom on the Earth largely can be treated as an isolated system: it doesn't have a whole lot of complex interactions with the environment, in particular there really aren't any nonlinear feedback loops or other dynamical behavior to consider when doing radioactive dating. Inference of the age of the Earth can then be performed with some accuracy, as the relevant "givens" and observations don't admit much uncertainty. By contrast, global climate has many MANY interacting variables, most of which we probably don't even know about yet, and considerable uncertainty underlying the ones we do know about. It is difficult to see how any specific prediction of the future dynamic behavior of global climate could be as accurate as that for the past behavior of radioactive elements that have been sitting around in a rock for billions of years.
Evolution is about as close to a "fact" as you're going to get. First of all, it effectively follows from a combination of the "laws" of thermodynamics (mainly the first and second) and the ability of a system (whether it is a molecule or a complex organism) to a) maintain a relative narrow set of states against environmental fluctuations, and b) reproduce itself at a rate greater than it's destruction. Evolution is just math, in the end. And of course, it is observed repeatedly in the laboratory and Nature. There may be many specific models that predict different evolutionary endpoints, or routes by which currently observed endpoints were achieved. But the fundamental phenomenon, that mutable self-reproducing systems will evolve, applies to all of these models, and all predictions are necessarily consistent with this "meta-behavior". By contrast, global climate is an instance of a specific system, which we model given what (very little) we know about the intertwined physical, chemical, and biological systems on the Earth, and continued warming is a specific prediction of that model. As climate is a system showing chaotic behavior across many timescales, it may be fundamentally unpredictable, for all practical purposes. So calling this prediction a "fact" is stretching thin even the approximate definition of "fact" made by the authors.

The letter goes on to state a variety of "facts" or "conclusions" which the authors imply are more or less incontrovertible, which would seem to contradict their initial points about uncertainty and the scientific method. I think the key problem here (and in most science) is the idea that there is any "conclusion" in science. The only real conclusion is the relative belief in one hypothesis over competing hypotheses, as opposed to a specific identification of "truth". But standard statistics is completely backwards on this point, instead testing if observed data are likely given that a hypothesis is true. It's not the likelihood of the hypothesis being tested, but that of the data. The truth of the hypothesis is assumed in this analysis. So when a scientist finds that their data is strongly consistent with the observations, they "conclude" the hypothesis is a "fact". But that ignores both any prior information (similar to "black box" diet studies which don't include knowledge of metabolism in assessing outcomes) as well as competing hypotheses. Your pet hypothesis might be consistent with the data at the 99% level, but if mine is 99.9% consistent, and further more consistent with other prior information, then it is more likely to be true. By not quantitatively assessing competing hypotheses, the authors of the letter are guilty of exactly the sort of "hiding heads in the sand" behavior of which they accuse their detractors:

We also call for an end to McCarthy-like threats of criminalprosecution against our colleagues based on innuendo and guiltby association, the harassment of scientists by politiciansseeking distractions to avoid taking action, and the outrightlies being spread about them. Society has two choices: We canignore the science and hide our heads in the sand and hope weare lucky, or we can act in the public interest to reduce thethreat of global climate change quickly and substantively. Thegood news is that smart and effective actions are possible.But delay must not be an option.

I think everybody involved here is "ignoring the science" in one way or another. Threats of criminal prosecution is the sort of idiot knee-jerk response made by politicians, who, incapable of thinking for themselves, blindly follow the "expert du jour". When it turns out the politician made stupid and shortsighted decisions based on "expert" advice, they want to turn on the expert rather than accepting responsibility for acting like an idiot. Physician, heal thyself!

But the authors of this letter are no better. AGW proponents seem to ignore the elephant in the living room: the climate is probably going to change at some point whether or not human activity has anything to do with it. If anything is going to doom humanity, it is our anthropocentric view, that we are the masters of the Earth, able to bend Nature to our will. History shows that environmental conditions are large unstable, requiring organisms to adapt or die. We clearly should not ignore the possibility of climate change and the effects it will have on human life. But should we focus our resources on trying to force Nature to behave as we wish (and probably failing over the long term)? Or is it better to learn from history, assume that change is coming, and figure out how we will adapt to Nature's whims? I'm guessing the personal goals of the "scientists" aligns strongly with one of these scenarios, not so much the other.

And that's the real issue with both examples: the gap between the personal goals of those providing information and the goals of the receivers of that information. I've discussed this before, more in the context of organizations like pharmaceutical companies. But scientists are just as self-interested as any other organism or organization. The personal goals of academic scientists are centered around career advancement and getting funding for research. For both, you need to make some scientific hypothesis and be "right" about it, not necessarily in the sense of having actual evidence quantitatively weighting the hypothesis, but in getting some large chunk of the scientific community to buy in. Achieving said buy-in is the core goal of academic scientists, and whether or not "consensus" is obtained through actual evidence isn't really relevant to the practitioners. They generally think that the consensus so obtained is itself evidence that they're right, but there's circular reasoning and confirmation bias written all over that. When you are evaluating the evidence put forth by a scientist, you not only must evaluate the quality of that evidence, but also the context in which it is presented, because the presenter undoubtedly (and probably unconsciously) re-weights things based on their own beliefs and goals. The scientist has a vested interest in being considered "right", which can be a lot different than actually being "right". The stronger those beliefs and goals relative to the actual evidence, the more likely you'll hear about "facts" and the "scientific method" as opposed to detailed evidence, both supportive and contradictory.

So when a scientist speaks, be sure to check the shoes.

Mother Nature (and Monsanto): Thriving on The Law of Unintened Consequences

2010-05-08T13:53:00.000-07:00

I loved this article: U.S. Farmers Cope with Roundup-Resistant Weeds. Here's an excerpt:

Roundup — originally made by Monsanto but now also sold by others under the generic name glyphosate — has been little short of a miracle chemical for farmers. It kills a broad spectrum of weeds, is easy and safe to work with, and breaks down quickly, reducing its environmental impact.
Sales took off in the late 1990s, after Monsanto created its brand of Roundup Ready crops that were genetically modified to tolerate the chemical, allowing farmers to spray their fields to kill the weeds while leaving the crop unharmed. Today, Roundup Ready crops account for about 90 percent of the soybeans and 70 percent of the corn and cotton grown in the United States.
But farmers sprayed so much Roundup that weeds quickly evolved to survive it. “What we’re talking about here is Darwinian evolution in fast-forward,” Mike Owen, a weed scientist at Iowa State University, said.
Now, Roundup-resistant weeds like horseweed and giant ragweed are forcing farmers to go back to more expensive techniques that they had long ago abandoned.

My first reaction on reading this was that Monsanto obviously screwed up. I mean, what idiot couldn't see this coming? But on second thought I'll bet they did see it coming. The later portion of the article discusses how Monsanto and other chemical companies are developing genetically-modified food plants (wheat, corn, soy) to be resistant to other herbicides as well (including one using a component of Agent Orange - mmmmm, Agent Orangey tofu). So of course, farmers will not have to buy additional pesticides, and probably pony up more cash for the next generation of resistant seeds. And you can see that going indefinitely, with the cash register ringing the whole time for Monsanto etc.

And to be clear: I don't think that companies like Monsanto are doing something evil. They're behaving exactly the way we ask them to in a (more or less) free market economy. They are taking a strategy that maximizes their value (or at least their assessment of it). That strategy may or may not have anything to do with maximizing your health or minimizing environmental impact. If there's any evil here, it's that of complacency on the part of the consumers, who (as a group) hold the ultimate power to change how corporations value their strategy. Corporations are notoriously short-sighted, as demonstrated by how readily many major financial institutions drove their respective buses off of a cliff recently. The start-up I used to work for developed a whole set off mathematical and software tools with the idea of allowing public corporations to value long-term strategy in the face of uncertainty. We spent some time studying how corporations actually make decisions vs. how they should given a way of optimizing value given whatever they knew (and knew they didn't know). The gap is typically quite large. Corporations, like people, are shortsighted, and much better at rationalizing why they did something after the fact than making a rational decision in the first place.

The good news is that corporate myopia gives consumers a fairly large lever. If you want corporations to "care" about your long-term health and well-being, be an informed consumer, and make your buying choices to reflect your own goals. It's the "informed" part that's important here.

I wonder how the course chosen by chemical/seed companies will play out. Maybe something like this:

Continued increase in spectrum of pesticides, resistance of weeds, and genetic engineering of food crops. At some point, the weeds are basically resistant to anything that won't outright kill humans.
Companies introduce a genetically modified bug to eat the weeds. New food crops are engineered to produce chemicals that repel the bugs. The insects eventually kill off most of the weeds, but evolve to be resistant to the food crop insect toxins, and start eating our food.
Cycle continues, introducing ever-more genetically engineered species introduced from higher in the food web.
Eventually the genetically-engineered humans are produced to act as workers to contain all of the new pest species. These "humans" are built to thrive on weeds, and as such prove to have considerably greater reproductive fitness of the old-school "natural" humans, whose fate as a species is basically sealed.

Why do you eat grains?

2010-05-07T16:05:00.000-07:00

That question isn't is smart-assed as it sounds. Bear with me.

I've blabbed before as to how I've often asked nutrition experts "What's so healthy about 'healthy whole grains'?" I've never gotten an actual answer, and as far as I can tell the best one could say is "nothing in particular." And while I have discussed the possible ways that grain consumption could lead to disease, I would have to admit that the evidence that grains have some particular disease-causing properties (outside of those with obvious clinically-detectable problems, like celiac) seems more correlation than causation at this point.

So I've started rethinking this question more as "why does anybody eat anything?" Clearly the need, at some level, to seek out and consume food has to be innate. And animals evolve amazingly complex behaviors around food. I remember giving my dog an egg for the first time, shell and all. As he does with any food, I expected him to swallow it more or less whole, maybe with a couple of crunches for good measure. Instead, he gently picked it up from his bowl, put it on the ground, and ever-so-delicately cracked it open with his front teeth, then licked out the inside and left the shell. I'm pretty sure that wasn't a learned behavior, unless he's been climbing trees and getting into robins' nests behind my back.

But in general, and probably particularly for omnivores, directed behavior associated with food (like "go find some more of those sweet orange spherical thingies") is learned. Babies put everything in their mouths for a reason: they're figuring out which things are worth seeking out and sticking in their mouths again. You may want to check out this fascinating paper on the topic. The short version is this: there seem to be two main areas of the brain associated with taste. The primary taste cortex handles the innate sensing of taste: sweet, salt, bitter, sour, and umami, along with the texture and viscosity of food (to sense fat), temperature, capsaicin, etc. The response of the primary taste cortex is NOT attentuated by satiety. Something sweet tastes just as sweet whether you're hungry or full. But the primary taste cortex doesn't assign value to a particular taste, i.e. it does not decide whether something tastes "good" or "bad". That's the job of the secondary taste cortex. It is the secondary taste cortex that "decides" sweet things taste good when you're hungry, but no so much after eating a whole box of candy. Secondary taste cortex neurons learn what's good and what isn't, and are further tuned to specific foods. For instance, you can be fed to satiety with fat, and certain neurons will decrease their response to further fat. But the response of those same neurons to the taste of glucose does not decrease, regardless of whether or not you're full of butter. In other words, "there's always room for dessert".

Anyway, let me get to the punch-line from the closing paragraph:

The outputs of the orbitofrontal cortex reach brain regions such as the striatum, cingulate cortex, and dorsolateral prefrontal cortex where behavioural responses to food may be elicited because these structures produce behaviour which makes the orbitofrontal cortex reward neurons fire, as they represent a goal for behaviour. At the same time, outputs from the orbitofrontal cortex and amygdala, in part via the hypothalamus, may provide for appropriate autonomic and endocrine responses to food to be produced, including the release of hormones such as insulin.

In other words, the external response to food (behavior) is a learned response driven by the secondary taste cortex, while the internal response (e.g. hormonal) is innate, originating in the primary taste cortex. That means that you learn what things taste "good" by the secondary taste cortex integrating feedback (positive and negative) from the rest of the body (primary taste cortex, glucose sensors, etc.), reinforcing or weakening the association of that taste with the behavior that led to those stimuli. So the fact that you "like" potato chips is intimately tied up with the impulse to get off the coach at midnight and stumble into the kitchen to finish off the bag. And the only reason you "like" any food is because your brain learned to, associating the flavor with some feedback signals which it interprets as being associated with a net positive outcome.

One other point which is probably obvious, but important: the smaller the time between the flavor stimulus and relevant physiological response, the stronger the change in association with the behavior. Thus, getting cancer 10 years after eating a poisonous plant is not very helpful in weakening that behavior. It is certainly possible to crave something that produces a strong short-term reward, but has a net negative outcome. The brain (both consciously and unconsciously) is notably short-sighted in its assessment of value.

Which brings me back to the original question: why do people eat grains? And I don't mean that as implying there's some moral judgment to made - food morality is just another religion. And there's obviously a spectrum of answers depending on the temporal proximity of the act of eating to a specific endpoint. On end is "prepared properly, they taste good" (I like sourdough toast dripping in butter as much as the next guy, though I eat it rarely). On the other end is the evolutionary argument so brilliantly put forth by Kurt Harris, basically that the net effect of domesticating grains was an advantage in reproductive fitness over hunter-gatherers, regardless of the relative "health" of those doing the reproducing. Evolution cares about making babies, and doesn't care if you have bad teeth and a bum ticker, as long as you contribute genes to more babies than the guy still killing perfectly serviceable beasts of burden with a rock on a stick.

No, I'm interested in the middle area (logarithmically speaking), which is why we learned to like grains. And why do we like them so much that we're willing to go to some amount of trouble to eat them? Why do I so love sourdough toast and butter, even though it doinks my blood sugar and gives me acne?

(Maybe it's the butter - New Zealand makes REALLY good butter.)

I have nothing but vague guesses, and am hoping to get some interesting discussion in the comments.

"The Myth of Green Beef": Pseudo-logic in action

2010-04-18T08:01:00.000-07:00

Check out this article: "The Myth of Green Beef".

The author, Helene York, provides a wonderfully clear example of "pseudo-logic", reasoning that is technically correct, but based on flawed or incomplete assumptions. Check out this quote:

Linked to cardiovascular disease and maligned for its industry's dependence on federal corn subsidies, it now has a reputation as the Hummer of foods—an excessive contributor to environmental ills including climate change, nitrogen blooms, pollution, and depletion of Midwestern aquifers—not to mention E. coli contamination that has sickened and scared thousands.

Hmmm, sounds like the root of the problem here is the federal corn subsidies. Bon-Appetit Management, where Ms. York is the director for strategic initiatives, ran the cafe at my former company. I know from personal experience that a good chunk of the food provided by Bon-Appetit is made possible by federal subsidies corn, wheat, and soy. And of course there is a tidal wave of scientific evidence emerging that said foods are more likely the culprit cardiovascular disease, via the metabolic disturbances they create. The evidence that red meat per se causes any disease has, to my knowledge, never risen above association (the E. coli issue is problem with factory farmed animals, and only then for people whose health is otherwise compromised, maybe from eating "healthy" soy goo and avoiding the sun).

Here's another classic:

Voluntary rancher fees from an industry association's advocacy program have underwritten pro-meat marketing campaigns, stipends for researchers to raise doubts (but not conclusive evidence) about scientific studies, and dissemination of talking points that are misleading at best. "Reducing intakes of meat and dairy would only lead to hunger," I read recently, and the headline of an industry newsletter stated, "Meat and dairy intakes not linked to climate change." These news items represent a disturbing trend: raise doubts, obfuscate the facts, and misinform.

Isn't that EXACTLY what Ms. York is doing here? What makes her "facts" better than those she criticizes? Why are her studies more "scientific" than those that contradict her "conclusive" evidenct? Talk about confirmation bias. This is the fundamental problem we face when turning scientific information (or more precisely, the lack thereof) into decisions. Humans seem to have a psychological propensity to gravitate toward "absolute truths", and their absolute belief in those truths are motivated more by social and emotional factors than any sort of actual accounting of the evidence. Indeed, people like Ms. York seem to get wound around some sort of moral axle that drives their reasoning process. Beef is "bad" in her world. That's a "fact". Thus beef must be bad for your health, the environment, at the root of the global economic meltdown, bad hair days, etc. And maybe I'm pessimistic, but I have a feeling that, more than anything, serving beef might be "bad" for Bon-Appetit's bottom line. I would guess it is cheaper to sling soy/corn/wheat processed food (where you can reap the benefit of less prep and less annoying middle men sucking off the teat of government subsidies).

But let's be optimistic, and presume Ms. York's motives are altruistic, that she really wants to save our hearts and our planet from the evils of a nice juicy steak. Does her reasoning hold water? I believe you would need to take the following assumptions as "facts" to support her conclusions:

Human activity causes global warming.
This warming trend will continue.
Changes in human activity can reverse the trend.

This is where we run into trouble. The implication is that we have both a great enough understanding of global climate to make reliable predictions, and further that even if we had such detailed understanding, that behavior could be reliably extrapolated decades into the future. I'm no expert in global climate, but I know a thing or two about modeling complex systems, particularly in the face of uncertainty about the details. I seriously doubt that global climate models even begin to approach anything beyond a coarse representation of reality. There are plenty of aspects to the problem that we know we don't know, like the response of aquatic life to increased CO2 concentrations. There are significant uncertainties as well, e.g. solar and volcanic activity. And no doubt there's plenty of stuff we don't even know about, the "don't know what you don't know" category.

And it gets worse. Climate is basically just another word for weather. I don't know if you've noticed, but it's pretty hard to predict the weather even a week into the future, much less 50 years. And short-term weather modeling is much better understood for the simple reason that when examining a shorter time period, less variables are likely to have a large effect (e.g. large glaciers don't change enough in a week to affect your forecast significantly). Even so, the weather remains unpredictable, and this unpredictability is intrinsic. Weather is an example of a non-linear system, one which exhibits a phenomenon called deterministic chaos. A brief digression might be in order.

Consider a simple experiment, say measuring the time it takes a marble to fall from a height of one meter. We call such a system "deterministic" because the equations used to model it have no uncertainty. Given a particularly position and velocity for the marble, we can calculate the precise position and velocity an instant later. And this is a good approximation in our experiment. We might induce a little uncertainty in how our hand releases the marble, some from the measurement of the height, maybe some from air currents, etc. But we can repeat this experiment and get the pretty much the same results every time. In other words, small errors in our information about the marble's state translate into small errors in our predictions. The more accurate our information about the marble, the more accurate our prediction of the time to fall one meter.

A system exhibiting deterministic chaos is deterministic in the strict sense of the term: given precise knowledge of it's state, we can predict exactly what will happen next. But unlike our marble experiment, chaotic systems amplify uncertainty. In other words, even small inaccuracies in your information about the system quickly become large. Worse yet, this amplification is exponential in time, so getting more accurate information might make them predictable for a slightly longer period, but it's still going to fall apart on you pretty quickly. Chaotic systems are predictable only in principle, but in practice your information is never perfect, and predictability drops exponentially with time. Deterministic chaos as we now think of it was "discovered" by Edward Lorenz, who was modeling (you guessed it) global weather.

So, even assuming that the East Anglia boobs, with their lost data and bogus statistical analyses, were "right" about there being a significant increase in mean global temperatures, how does that help us predict the future behavior of a complex chaotic system where are models are incomplete and full of uncertainties?

Now when I drop this line of argument during discussions of global warming, the AGW crowd (after a bit of cognitive dissonance induced brain paralysis) come up with something like the following argument: human activity MIGHT be causing global warming, and since the downside has a value which is essentially negative infinity (extinction of the human race), we have to do everything possible to avoid it. Such an argument is more pseudo-logic, in this case by excluding the most likely scenario. AGW arguments center around whether or not the (supposedly) observed warming trend is caused by humans, and extrapolate that to conclude that humans might be able to reverse said trend. But this ignores the most likely scenario, which is that the climate will undergo a significant shift regardless of anything humans have done or will do. Why do I say this is the most likely scenario? Because it has happened many times in the past, and given the chaotic nature of climate, it is unlikely to stay in the current meta-stable state for long (many argue that the rise of civilization was made possible by unusual relative stability of climate). Arguments such as those put forth by Ms. York completely miss the point. We don't need to be worried about whether eating less hamburgers can affect the climate, we need to start hedging our risk that the climate will change regardless of what we do. It's the short-sighted thinking and associated bad decision-making of individuals like Ms. York that will doom us, missing that the forest around them is burning down while hugging the tree right in front of their face.

But back to the main thread. So the whole global warming argument is bogus. That's about as close to a fact as you're going to get, since it's really just mathematics (climate is chaotic, our knowledge of it is uncertain). Let's wander from math to the realm of science, where we consider evidence. The more detailed assumption underlying Ms. York's proposal is that cattle farming is particularly bad for the environment. She's basically equating cows with global destruction. This begs the question of how the Earth managed to survive millions of years of grazing animals, all of whom presumably had the same basic digestive strategy of modern plant eaters.

Possess large gut full of bacteria which can break down cellulose.
Eat plants, and lots of 'em.
Bacteria eat the cellulose, make CO2/methane/etc. as by-products.
Fart voluminously to avoid exploding.

I'll close by noting that there's nothing particularly "green" about any large-scale agriculture. Grain-fed cattle are no doubt the caboose on the train to ecological destruction, as cattle inefficiently convert grain into food (compared, say, to a chicken). But that whole process, like most modern agriculture, represents a massive perversion of a natural process, requiring considerable human intervention. And that perversion goes right back to the fields of corn/wheat/soy grown to feed both cows and people. The ecological issues have been described elsewhere (my favorite discussion is in Lierre Keith's fantastic book The Vegetarian Myth), but the bottom line is that the sort of large-scale monocultures we see today are an ecological dead end. Sooner or later you deplete the resources required to grow specific foods in high densities: soil, water, and petroleum for chemical fertilizers. Feeding people directly with that food instead of "wasting" on cattle might delay the end a bit, but you still get there, and if history shows us anything it's that making more food just winds up making more people who will wind up starving when the train crashes Thanks a billion, Norm Borlaug, for "saving a billion people from starvation" by setting the stage for multiple billions to starve. This is the poster child for why the sort of short-term thinking displayed by Ms. York is to be avoided.

So if there's any "myth" to be dispelled here, it's that there's anything "green" about the food industry, which includes the erstwhile Ms. York and her employer, Bon-Appetit Management.

And winding back to the usual topic of this blog, we shouldn't forget the health consequences of a diet consisting mostly of processed soy/wheat/corn. There is plenty of evidence from all corners indicating that "diseases of civilization" arise from said foods. I'm still waiting for someone to detail the metabolic pathways by which eating a steak leads to diabetes, cancer, and heart disease. Any takers?

Interview on "Livin' La Vida Low-Carb Show"

2010-04-08T19:14:00.000-07:00

Just a quick post - Jimmy Moore was kind enough to interview me on his "Livin' La Vida Low-Carb Show". It was tremendous fun, and we got to discuss some interesting stuff. Check it out.

I've been trying to get a blog done on some recent thoughts on the laws of thermodynamics and metabolic regulation. Hoped to have it by the time Jimmy's show was on, didn't quite make it. Hopefully will wrap it up by this weekend - stay tuned.

Review of the SousVide Supreme

2009-12-24T17:28:00.000-08:00

Wow, the last post was in August. Been pretty busy with the day job lately. Odd how it works out - my startup job (http://www.provisdom.com, still close to my heart), for which I probably worked 10-12 hours a day, still seemed to leave me more time to do things like cook for the family. That's probably because I got to choose which 10-12 hours I worked, rather than having to spend an hour commuting each way and a solid 8+ hours sitting in a cubicle.

I have to admit, when I first found out that the Eades's world-changing project was a home sous-vide unit, I was a tad disappointed. I was familiar with the concept of sous-vide, being a fan of shows like Top Chef. I also have to admit that in hindsight I really didn't "get it". The brilliance of the SousVide Supreme is that it enables my food habit in the face of my new work regimen. Our family eats meat - lots of meat. And they've become accustomed to it being prepared to a certain standard which is not really possible to achieve on an 8-5 schedule, because I generally get home after 6. To prepare a good roast chicken or steak (accompanied by Bordelaise sauce, the omission of which will lead to family chilliness until remedied) takes at least 2 hours.

So it was a lot of crockpot and takeout during the week - until the SousVide Supreme came along. I pre-ordered mine, and awaited it with great excitement. It predictably didn't arrive until I was away from home during the Thanksgiving holidays, which caused me a certain amount of childish angst. But I finally got my grubby paws on it, made some righteously tasty food, and am ready to share my initial experiences and impressions.

The short version is this: if you're a meat-eater, get one. It's worth every penny.

I won't go too much into describing the unit, which has been done many other places. It is a little on the large side - but part of the issue is that our cabinets seem to have been made before appliances were invented. And you can cook an awful lot of food for the size. I made two tri-tips a couple of days ago, total weight five pounds, in a device the size of a bread-maker, and almost certainly with far less electricity than would have been required to achieve the same in my oven (which now seems cavernously inefficient). And I think the success of sous-vide can best be described by one guest's comment after the first bite: "Holy crap".

If you don't know, "sous vide" is French for "under vacuum". The sous vide technique involves sealing the food in a vacuum bag and cooking in a water bath with precisely controlled temperature. There are multiple advantages to this approach. First, because the food (typically meat, though other foods benefit as well) is sealed, there isn't much moisture loss. The vacuum seal also ensures the water contacts the entire surface of the food. Water has much higher heat capacity and conductivity than air, so transfers heat to the food more effectively than the typical radiative/convective(air) transfer which occurs in a standard oven. Once up to temperature, the SousVide Supreme apparently requires about the same energy as a 60-watt lightbulb, something like 10x less than a conventional oven, I would imagine.

But the real winner is that you set the water temperature to be the same as the final desired food temperature. "Normal" cooking requires a certain amount of precision by the chef. One applies relatively higher heat to the meat in an attempt to get the inside "done" before the whole thing turns to jerky. Unless you have a meat thermometer, the whole business is more art than science, because two pieces of meat have different fat/moisture/salt/etc. contents, all of which affects the thermal conductivity and the rate at which "doneness" is achieved. For instance, grass-fed beef typically has much lower fat content than grain-fed, and as a result cooks much faster (and is more rapidly rendered inedible). A thermometer helps, but of course the thermometer only measures the temperature at the center of the meat, at the location inserted, which may be of different size/fat content/etc. than the rest of the meat. I used to have a whole arsenal of techniques and tricks depending on the cut of meat, what it ate, etc.

With sous-vide, you just pick your final temperature. The aforementioned tri-tip was done at 128F. Imagine trying to cook a steak at 128F in your oven. Not only would it take forever, but you'd be left with something resembling the bottom of a shoe at the end of the process. Better yet, you can leave the meat in the thing for a considerable amount of time (I'm talking hours) without risking overcooking. For instance, when we had our guests a couple of nights ago, I took out one tri-tip, gave it a shot in the broiler to give it some color (more on this in a moment), and left the other one in while we fed the kids (who hammered a good chunk of the first steak). About an hour later I just pulled out tri-tip #2, browned it up, and served hot. And it was outrageously good: tender, juicy, and brimming with flavor.

And this has proved to be the real winner for me, with my new commuter lifestyle. I can drop in some steaks/chicken/chops before I leave for work in the morning, and have fabulous meat ready to eat 10-12 hours later when we all get home, plus a few minutes to heat a pan or the broiler and apply a tasty brown crust. And I'm not kidding about the fabulous. It does take a bit of experimentation with temperature and preparation to really nail it. I'll share a few things I've learned.

First is that "doneness" of meat results from a non-trivial combination of time and temperature. If you really want to nerd it up on this topic, check out "A Practical Guide to Sous Vide Cooking", originating from my alma mater (go Buffs!) The killing of any nasty bugs that might ruin your post-dining experience also results from a similar combination of time and temperature. Anyway, the first thing I tried was a London broil, which I cooked at the recommended 134F on a work day. So it cooked for about 10 or 11 hours at that temp. Was it the best steak ever? No (though my son claimed it was). But it was pretty darned good, a touch dry in texture (a sign it was starting to overcook), but nice and pink in color. Sous vide lesson 1: if you're going to leave your meat in for a long time, lower the temp a bit. The next try was with rib-eyes, done at about 130F, I believe, very nice, though could have been done lower still. The tri-tips came out great after 6 hours at 128F, and I think I'd drop it to 126F if I were going to leave it in all day.

The next couple of tries were with chicken. Both were done as work-day meals, using breasts, legs, and thighs cut up. These were sealed with butter, salt, and pepper, and again cooked for about 11 hours. The first batch I did at the temperature recommended in the SousVide Supreme manual, which I think was 141F. The breasts were a bit dry (I'm a dark meat person by a long shot), but still better than most chicken breasts I'd had. The thighs and legs really shined, though: juicy and very flavorful. The next batch I did at 136F, and were dynamite. We all know the old saw about "tastes like chicken", which I thought was odd, since most chicken I'd had didn't taste like much of anything by itself. Not the sous-vide version, though. Tremendous flavor, and a big hit with the family. The downside: I tried to brown the skin in my stainless steel pan, but for the most part it just stuck, leaving all the tastiness behind. I'm going to try in the broiler, but I think sous-vide lesson 2 is to have a kitchen torch handy for browning. This allows high heat to be locally applied, to minimize the risk of drying out. Believe me, once you've had sous-vide chicken, you're not going to want to take that risk.

We also tried pork chops, which I just sealed with salt. The chops themselves were just bulk-package center-cut, a little on the thin side. They came out fantastic, far more succulent and tasty than any pork chop I'd ever had. The bad news is that I again tried to brown in a pan, which dried them up pretty quickly. Sous-vide lesson 3: use thicker cuts of meat to prevent drying when you brown. I'll give it another whirl with some nice thick-cut chops.

We've had some nice success with "contrary" cooking, using our new pressure cooker in conjunction with the SousVide Supreme. The "contrary" comes from the fact that things you usually cook fast with the stove or oven are cooked slowly by sous-vide, and things usually done slowly in a crockpot are done quickly (relatively) in the pressure cooker. One example is cheeseburgers topped with pulled pork. I did the burgers for 3 hours at 134F - pretty good, though again I think I could go lower, particularly considering that I'm going to brown them in a pan. The pulled pork takes about an hour under pressure, and I just let the pressure release naturally over another hour or so. The combination is fabulous.

A better example was inspired by an interview with Heston Blumenthal while he was traveling on the SousVide Supreme tour. He stated that he always did stocks in the pressure cooker, since otherwise the flavors escape. This was a bit of a light-bulb moment for me (which ultimately led to the purchase of the pressure cooker). I would always make stock on the stove, cooking it for about 24 hours. My wife complained bitterly that the smell was driving her crazy because it made her hungry. I think she was having the same insight as Blumenthal. There were some additional issues with cooking stock on the stove. One was the time, which meant that stock had to be done in advance in large batches rather than cooking during the work day. If I didn't freeze the stock (which is something of a hassle), it had a tendency to grow interesting bacteria. The bacteria were at least nice enough to be fluorescent pink so I didn't put us all in the hospital.

Now, with the pressure cooker, I can just make stock in parallel while the beef is cooking in the SousVide Supreme. Sauces are a fantastic way to bring variety to meat dishes, and further serve as a vehicle for nutrients that you might not otherwise consume. Here's my recipe for beef stock, followed by that for Bordelaise sauce, which I think is the perfect pairing with steak.

Beef Stock

Ingredients

Two or three beef marrow bones, preferably the joint end with lots of cartilaginous goodness attached
One package of oxtails (about 0.5-1 lb usually).
0.5 lb sliced beef heart
3 large carrots, coarsely chopped
2 sticks celery, coarsely chopped
1-2 large yellow onions, coarsely chopped
One bunch thyme (I use one of those little plastic packages of fresh thyme)
One bunch parsley
One cup red wine
4 cups water, plus any extra needed to cover

Procedure

Pre-heat the oven to 350F.
In an oven-safe pan over high heat, brown the bones and oxtails on the stove. Throw in the veggies near the end (note that stores now often carry pre-made mirepoix, chopped carrots, celery, and onions, which saves some prep. I use about 4 cups of pre-made when I can get it).
Put all of this in the oven for 45 minutes.
Put the thyme, parsley, and beef heart in the pressure cooker. Add the browned meat and veggies on top, along with the water. Add extra water if needed to ensure everything is covered.
Deglaze the pan with the red wine. I usually use Bordeaux, as (not surprisingly) it seems to match well with the other flavors in the Bordelaise (which originated in the French region of Bordeaux). Make sure to scrape all the brown goodies off the bottom of the pan, and add all of this to the pressure cooker.
Cook under high pressure for 1.5-3 hours. 3 hours gives the best flavor, but my pressure cooker only times up to 99 minutes. If I'm at home, I do two rounds of 99 minutes.

Sauce Bordelaise

Ingredients

4 cups beef stock
2-2/3 cups red wine (again, I like Bordeaux, and it doesn't need to be expensive)
6 large shallots, coarsely chopped
One bunch thyme
8 oz. butter, cubed
Salt and pepper to taste
Xanthan gum or other thickener

Procedure

Reduce the beef stock to 2-2/3 cup.
Combine wine, shallots, thyme, salt, and pepper in a sauce-pan. Cook until the liquid is reduced to about 1-1/3 cup.
Strain red wine reduction. A chinois works well for this, and allows you to mash some of the yum-yums out of the solids.
Combine reduced beef stock and red wine in a sauce pan and bring to a boil.
Melt in the butter.
Thicken. I use Xanthan gum, which works well, but is fairly touchy. I add a little at a time, give it a few minutes to cook and see how thick things are, repeating until I get the desired consistency. The traditional recipe uses a flour/butter roux as a thickener, which works fine. I try to avoid wheat, and don't really like the flour taste in the sauce anyway. But if you want to make a roux, you make it first and then add the liquid.

This is outrageously good on steak, even more so on sous-vide steak, which retains more beefy flavor and really matches well with the sauce. Use the left-overs for breakfast. Steak and eggs over easy smothered in Bordelaise is a little slice of heaven.

Sous-vide Ice Cream
Home-made ice cream is another of our favorite treats, often made to go along with our steak and Bordelaise. I use a modified version of Dr. Mary Dan Eades' sugar-free recipe. Making ice cream used to be something of a procedure, since the recipe is custard-based (technically a Creme Anglaise). When made on the stove the custard requires constant attention, and you have to temper the eggs, etc. With the SousVide Supreme, you can just mix everything, stick in a bag, and cook it. Here's the recipe.

Ingredients

1.5 cup half-and-half
1.5 cup heavy cream
2 whole eggs plus 4 egg yolks
0.25 cup Splenda
0.5 cup polydextrose
1 vanilla bean, split and scraped OR 4 T vanilla extract
Enough ice water to submerge the bag

Procedure

Preheat the SousVide supreme to 82C.
Combine all ingredients in a mixing bowl.
Pour mixture into a vacuum bag. Make sure you scrape out the polydextrose from the bottom. It doesn't dissolve very well in cold liquid, and has a tendency to congeal into a big clump.
Vacuum and seal the bag, and place in the SousVide Supreme (note you can do this with a zip-lock by zipping most of the way, submerging in the water bath the squeeze out the air, then zipping completely shut).
Cook for 20 minutes.
Remove the bag and squish the contents. It's hot, but I'm able to do this with my bare hands, though you can use oven mitts. Pay particularly attention to the polydextrose, which settles to the bottom. It will incorporate better in the hot liquid.
Return the bag to the water bath for another five minutes.
Submerge in ice water and squish it around some more. At this point you can either leave it in the ice water to chill, or transfer to the refrigerator.
Dump in the ice cream maker (if you used vanilla beans, remove the pods first).

This is very yummy, as well as easy and fast enough to do on a work night. Polydextrose is soluble fiber, basically polymerized glucose in a configuration that human digestive enzymes can't break down. It has some of the same chemical and flavor properties of sugar, and for the purposes of ice cream, lowers the freezing point of water giving smaller ice crystals and a creamier texture. I get a kick out of telling people the ice cream they're eating is high fiber. It does make some people gassy, though, so adjust the amount as required.

Wrap-Up

The SousVide Supreme really is revolutionary, particularly if you have a busy work week. Some of the high points:

Makes cooking of gourmet-quality meat nearly fool-proof.
Tremendously simplifies cooking of certain dishes (compare the ice cream procedure above with what is normally required for a Creme Anglaise).
Low electricity usage compared to an oven.
Very well engineered (the universal bag rack is something to marvel at, no doubt required spatial thinking skills that are well beyond my capability).
Food can be cooked in advance, shocked in ice, and frozen. Reheat to the perfect temperature in the SousVide Supreme.
Meat can be left in for an extended period without overcooking.

In theory, you should be able to use cheaper cuts of meat. I haven't had a chance to try this yet, but chuck roast sous-vide is next on the menu. I'll let you know how it turns out. In fact, what I really want to try is grass-fed chuck, which in theory would be downright inedible when cooked by normal means. The SousVide Supreme is a tad pricey on the face of it, but I found the benefits to be well worth the money.

A GUT Feeling about Insulin

2009-08-09T08:23:00.000-07:00

Ask ten people how to lose weight (fat), and you'll likely get ten different answers. In fact, if you ask ten "experts" the same question, you'll probably also get ten answers (usually attached to some product or service requiring you to part with some money). Why all of the confusion? After all, it seems a fairly simple question at its base: how do you burn more fat than you store?

I believe there's two key failures in critical thinking underlying the confusion. The first is that obesity itself is a "disease", which needs to be "cured". Many other diseases (heart disease, cancer, etc.) are associated with obesity, and the prevailing thought is that curing obesity reduces risk for these other diseases. However, this ignores the mountain of evidence that an organism's metabolism is self-regulating. In this view, obesity is a symptom of of some underlying disease process which causes systemic failure of metabolic regulation. It is this underlying disease which needs to be fixed; further, it is possible that you can have this disease and not be obese (there are plenty of skinny Type II diabetics). Modern medicine is very skilled at treating symptoms and ignoring the root cause; indeed, this effect is rampant for obesity treatments. How many people do you know that have lost large amounts of fat, only to have it come back worse?

The second failure comes from "black box" thinking. When hearing various prescriptions for curing obesity, I'm reminded of a famous Sidney Harris cartoon. For instance, a friend was recently telling me about a lemon juice diet. You drink lots of lemon juice, and the fat miraculously flows out of the fat cells. This supposedly had something to do with changing the acidity of your blood, but of course when prompted this person couldn't supply any actual physiological mechanism to explain this effect.

To understand the problems with black-box thinking, we can use the example of, uh, a black box. It has a hole where you can put stuff in, and lots of different colored lights that blink in response to whatever you provide as input. Your job is figure out the rules of how the input relates to the blinking lights. As we try different things we find many patterns of colored lights, with no obvious patterns. For instance, we supply two different cube-shaped objects, but each elicits a different light pattern. So "cubiness" is not apparently relevant to the lights.

The behavior of our black box may appear complex, but we don't really know if it's inherently complex, or if we just lack enough information to tease out the rules. We might crack the box open and examine how it actually works, and find that there really is a simple rule at the core, i.e. specific lights turn on depending on the molecular composition. The rule turns out to be simple, but it's the variety of different inputs that result in apparently complex behavior. Once you know how the box works inside, it becomes relatively easy to predict its response to a given input.

If you notice, most studies on diet and health take the black box approach: they diddle some inputs, and observe how those inputs are associated the outputs (e.g. fat loss). But if you don't have some understanding of what's going on inside the box, you just wind up with a mass of confusing observations and associations. So the lack of consensus and mercurial nature of dietary recommendations should come as no surprise.

Unification and Symmetry
Science often faces such situations. The core difficulty is a lack of symmetry. Symmetry means "sameness in the face of change". A perfectly smooth cue ball will look the same no matter how you turn it. Paint some dots on the ball, and you break the symmetry.

We often encounter cases where our observations seem to reflect a lack of symmetry, but if we look hard enough we find a deeper symmetry, one that unifies our observations under a common model. Such was the case in particle physics in the 20th century. Physicists had observed a vast zoo of different particles, first in cosmic rays (high-energy particles from space), then in "atom smashers". There were also four apparently disparate "forces" of nature: electromagnetic, weak nuclear, strong nuclear, and gravitation. The drive (which continues today) was to unify these different things by identifying the underlying symmetry. A "grand unified theory" (or GUT) would explain the all subatomic phenomena with a single model. Some progress has been made, e.g. many of the different particles were found to be composed from a much smaller family of more fundamental particles called quarks. The electromagnetic and weak nuclear forces (the latter causes radioactive decay) we discovered to actually be one in the same, the apparent difference occuring because the universe is relatively cold.

A Unified Theory of Fat Storage
Can we find a corresponding unifying principle for how fat loss and gain are related to diet? I think the answer is a qualified "yes". We likely need to restrict the domain of our model to one where the observed effect (obesity) has a common cause. Metabolic regulation is complex, and excess fat storage can have multiple root causes. We'll focus here on one possible cause, because it appears to be common and becoming more so: too much insulin, and/or not enough sensitivity to that insulin. Insulin is arguably the boss hormone for metabolic regulation: it effects many systems, and itself is affected by many factors. By examining the effect of insulin both on the behavior of individual cells and at the level of global metabolic regulation, we can in effect "open the box": see how inputs affect insulin and insulin response, then follow the effects of insulin in the body, particularly on fat storage.

I am going to make the bold claim that insulin is the unifying factor, tying together many different observations about fat gain/loss. I intentionally said "many" instead of all, because there are other metabolic pathways influencing fat storage (e.g. increased adrenaline promotes release of fatty acids from fat cells). I'll make the further claim that just about any successful reducing strategy (one that results in fat loss) can be explained by its effects on insulin, whether that strategy involves diet, physical activity, drugs/supplements, or a combination. We should also be able to explain both the relative efficacy of different strategies both in terms of rate of fat loss and final equilibrium fat mass (e.g. many diets result in fat loss, but all seem to "stall" at some point; we should be able to explain this stall via our model). Some examples are given below.

Our Grand Unified Theory theory then provides a more solid foundation for discussing the relative merits of different reducing strategies, and more importantly for making decisions about which lifestyle modifications are most appropriate. Instead of sifting through piles of observational evidence and "expert" testimony, you simply ask two questions:

Is my obesity insulin related? (The answer is probably "Yes" for most, but not all. Those whose obesity has some other cause, like a genetic leptin disorder, will need to seek other avenues of treatment).
How does X affect my insulin? From here you should be able to make a more informed decision about whether or not to pursue X for fat loss.

Perhaps more importantly, by moving the focus from a symptom (obesity) to an underlying cause, we can begin to recognize that controlling insulin should have wide-ranging implications for health (insulin does many things beyond controlling blood sugar and fat storage).

A Brief Primer on Insulin
The effect of insulin on fat storage has been covered elsewhere in detail, most notably in Gary Taubes' book Good Calories, Bad Calories. But it is probably worthwhile to hit the high points again. Insulin also does not act in isolation, but plays an intricate dance with other hormones and the nervous system. Some of these relationships are covered here.

Insulin is a protein (you can see a computer-generated representation here). Like all proteins, there is a gene that encodes the particular sequence of amino acids for manufacturing insulin. One of the interesting facts about insulin is that it's structure is remarkably consistent across time and species. Thus, species which appear genetically divergent, like humans and hagfish, do make different forms of insulin and the insulin receptor, but they're more simillar than different: human insulin has a large degree of cross-reactivity with hagfish insulin receptors, and vice-versa. So insulin has been around a long time, and the relative lack of cross-species mutation is an indication of it's key role in the survival of an organism.

The effects of insulin are initiated when an insulin molecule binds to an insulin receptor at the surface of a cell membrane. This binding triggers a series of chemical reactions, generally culminating at the cell nucleus, where genes are either up-regulated (meaning they make more of some protein) or down-regulated. Most people are familiar with the role of insulin in controlling blood sugar. One major effect of insulin binding is the manufacture of glucose transport (GLUT) proteins, which move glucose out of the blood, across the cell membrance, and into the cell. But insulin has many other effects. It is mitogenic, which means that it promotes cell division (i.e. insulin is a growth hormone). Insulin plays a key role in the manufacture of cholesterol from glucose, both by up-regulating transport of glucose into the cell and controlling manufacture of HMG-CoA reductase, and enzyme required to transform HMG-CoA into cholesterol (side note: statins block manufacture of HMG-CoA reductase). And there's a pile of other functions as well.

When insulin binds to an insulin receptor, it not only causes a chemical signal to be sent. The entire insulin/receptor complex is also absorbed by the cell (endocytosis), removing the insulin from circulation. A condition in which there is too much insulin in the blood (hyperinsulinemia) could thus result either from too much insulin being produced in the pancreas, or from a relative lack of insulin receptors. Correspondingly, insulin resistance (the failure of cells to respond to the insulin signal) could result from a lack of insulin receptors, a failure in the chemical signal chain, or from some other molecule (like a lectin) physically blocking the insulin receptor.

We should also realize that insulin does it's thing via it's effect on genes. Genetic differences can thus imply diferent responses to insulin. Genes carry the code to manufacture proteins, and a rather small difference in gene activation by insulin can result in large visible differences between individuals. This is particularly true for fat storage. We'll see below how insulin triggers manufacture of lipoprotein lipase (LPL) which is necessary for fat storage. A small difference in the amount of LPL made in response to insulin results in a small difference in net amount of fat storage. But whether that small difference results in net negative or positive storage could determine whether or not an individual will become obese.

On to the point. Insulin controls fat storage primarily through three pathways:

Up-regulation of lipoprotein lipase (LPL)
Down-regulation of hormone sensitive lipase (HSL)
Up-regulation of glucose transporters.

The basic unit of fat is a fatty acid. Fatty acids are not water soluble, as anyone who has tried to mix oil and water knows. Blood is mostly water, and having fat droplets wandering around your blood vessels is not good. So fats need some other water soluble molecule to transport them around in the blood. Individual fatty acids can be transported bound to a molecule of albumin, but this mostly occurs for fatty acids released from fat cells. Dietary fats and those made in the liver are carried mostly as triglycerides in large molecules called lipoproteins. Triglycerides are also the storage form of fat in fat cells. A triglyceride is composed of three fatty acids stuck to a glycerol backbone.

Triglycerides are too large to pass across the cell membrane. In order for fatty acids to get in/out of a fat cell, they must be freed from the triglycerides. Enzymes which perform this task are called lipases. Lipoprotein lipase (LPL) acts on lipoproteins in the blood to free fatty acids for transport into the fat cells. Hormone sensitive lipase (HSL) acts on triglycerides inside the fat cell, freeing fatty acids for transport out of the fat cell. The precise mechanism by which the fats actually make it across the cell membrane isn't entirely clear. Cell membranes are largely made of fatty acids themselves (in the form of phospholipids), so it's like that free fatty acids passively diffuse across the cell membrane (whereas water soluble substances, like glucose, generally require the help of a transport molecule). There is also evidence of fat transporter molecules, though these may be more important in cells like muscle that may need energy faster than can be supplied by passive diffusion.

The fatty acids inside the fat cell, regardless of their origin, are candidates for esterification, which just means they can be incorporated into triglycerides. This in turn requires a supply of glucose to manufacture the glycerol backbone (actually a molecule named glycerol-3-phosphate, or alpha glycerol phosphate; we'll use G3P). Insulin is necessary to effect transport of glucose from the blood inside of the fat cell, and also up-regulates a key enzyme (G3P dehydrogenase) required to form G3P from glucose.

Insulin increases LPL and decreases HSL. The relative concentration of fatty acids inside and outside of the fat cell are thus governed by insulin, as well as the availability of lipoproteins in the blood. Fatty acids tend to move from high concentration to low. If insulin is low, HSL activity is increased, fatty acids tend to build up in the cell and diffuse out to the blood. If insulin is high, LPL activity is increased, fatty acids build up outside the cell and tend to move in. Once inside the cell, insulin governs the relative rate at which fat is stored, not only through HSL, but also by effecting glucose transport and regulating G3P dehydrogenase.

There are other metabolic pathways which affect this process. Some, like de novo lipogenesis, are also regulated by insulin. Others, like acylation stimulation protein (ASP), appear to be independent of insulin. There are ongoing arguments as to the relative importance of the various pathways, but I think the evidence is pretty clear that insulin is king of the hill when it comes to fat storage. For instance, Type I diabetics, who make little or no insulin, basically lack the ability store fat. If ASP were important in humans, Type I diabetics should be able to store plenty of fat (since one of the symptoms of Type I diabetes is ravenous hunger, I think we would have observed this). Any Type I diabetic who injects insulin, however, is familiar with the "fat pad" that forms at the injection site, due to (ta da) the high concentration of insulin in that area.

So, lots of concepts and big words in the above. The takeaway is simple: more insulin means fat cells store fat; less insulin means fat cells release fat. The equilibrium point (at which you're neither storing nor releasing) is thus largely determined by average insulin levels. We should then be able to predict the effect of various lifestyle changes from their effect on insulin. Let's see how that works out for some commonly recommended reducing strategies.

Low Carbohydrate Diet

This ought to be a no-brainer. Of all macronutrients, carbohydrates have the largest direct effect on insulin levels. Protein also stimulates a little insulin release, but nothing like a quantities of readily available carbohydrate (dietary protein also stimulates release of the hormone glucagon, which tends to counteract insulin's effect of driving glucose from the blood into fat cells, thus reducing fat storage). By itself, fat does not stimulate insulin release (in fact it seems to decrease it mildly). But fat does cause release of hormones like CCK, which amongst other things cause the pancreas to release more insulin for a given stimulus of glucose or amino acids (this is called the "incretin effect"). So eating fat and refined carbohydrates together (which is most food in the Western diet) ought to really crank your insulin. High average insulin means more fat storage - look around any public place if you want to see this in action.

Conversely, removing carbohydrates from the diet should drastically reduce average insulin levels (unless you have some non-dietary problem, like an insulin-producing tumor, in which case you've got bigger problems that being fat). The decrease in insulin should move the body away from fat storage to fat release. Since this fat is now available for energy, appetite should decrease and/or activity should increase spontaneously. All of these effects have been observed repeatedly in both animal and human studies.

Low Calorie Diet (Starvation)
Suppose we just cut calories across the board. Say your nominal caloric intake was 2400 kcal/day, including an average of 300g of carbohydrates. Leaving fructose out of the equation (fructose does not directly stimulate insulin release, but does cause the liver to become temporarily insulin resistant, the net effect of which may be to increase average insulin levels), that's equivalent to about a cup and a half of sugar each day (the gut rapidly breaks down "complex carbohydrates" into glucose for absorption into the blood). Since the total amount of glucose in a normal person's blood is about 1 tsp, this 1.5 cups should have a drastic effect on average insulin levels, as the body works very hard to keep blood glucose in a narrow range (too much or too little glucose in the blood will kill you in a hurry).

Now, let's not change what we eat, just how much. We'll go from 2400 kcal/day down to 1600 kcal/day. That implies we're now eating 200g of carbohydrate per day, implying that average insulin levels should drop significantly. Again, this should result fat loss, since we've decreased insulin from the level that promoted our previous equilibrium. And that's precisely what's seen: starvation diets result in fat loss. However, that 200g of carbohydrate still promotes a fair amount of insulin secretion. We would thus expect initially rapid fat loss, tapering off over time, and finally stalling at the new equilibrium point. And once the fat stops coming out of the fat cells, your body is literally starving, and will likely make you fall off the wagon, so to speak. As your body has become used to lower levels of insulin (i.e. your insulin sensitivity has increased), resuming previous levels of carbohydrate and fat consumption should result in rapid weight gain, overshooting your previous equilibrium point. Which, again, is exactly what is seen.

Low Fat Diet

The low-fat diet is an interesting case, and what is called "low-fat" often involves both calorie restriction and the trading out of refined carbohydrates for more whole food sources, which tend to have less effect on blood sugar and thus insulin. Both latter effects of course will drop your average insulin, and result in some fat loss. The interesting thing here is that reduction in dietary fat should also reduce secretion of incretin hormones like CCK, and thus further reduce insulin. So low-fat diets "work", as is often observed. In fact, I would predict it works better than just generically cutting calories. I don't know if this has been observed. The confusion most people have is the idea that eating fat makes you fat, and thus erroneously conclude reducing fat makes you thin. But all of this action is ultimately effected by insulin.

And that's the rub, because it means it is difficult (and probably unhealthy) to eat low-fat forever. If you don't eat much fat, then you need carbohydrates for energy (using too much protein for energy results in nitrogen poisoning). If you get those carbohydrates from the usual sources, like bread, rice, or pasta, your insulin will go up, and you'll get fat again, whether you eat fat or not (note that excess dietary carbohydrate is converted to fat by the liver). Successful maintenance of a low-fat diet means getting carbohydrates from sources which are slowly digested, and/or maintaining a high enough level of physical activity to burn off excess glucose and enhance insulin sensitivity (more on this below).

Physical Activity

We've all heard the old chestnut that to effect fat loss you just need to "eat less and exercise more". We've seen above how calorie reduction can affect insulin levels. But does exercise do the same thing?

Interestingly, the answer is a qualified "Yes". Let's start with an extreme case (which, as it turns out, forms the basis for the very successful "slow burn" type exercise regimens). Muscle stores glycogen, a form of starch, for use as quick energy. The glucose to make that glycogen gets into the muscle cells via the action of insulin. In the case of muscle cells, insulin stimulates the cell to move a preformed store of GLUT4 molecules to the surface, so glucose can be rapidly absorbed from the blood. Now suppose you completely exhaust the muscle of its glycogen stores. What do you suppose its response will be?

Not surprisingly, the cell cranks out more insulin receptors in an effort to rebuild it's energy. After all, you might need that quick energy to escape the next hungry lion that crosses your path. So exercise increases insulin sensitivity of muscle, and we learned above that when insulin binds to an insulin receptor the cell absorbs the whole complex. So, independent of diet effects, we expect exercise to reduce average insulin levels; further, in doing so, the muscles also clear out some glucose. Both of these effects should lead to some degree of fat loss. Any increase in net physical activity should result in this effect to some degree. Your muscle cells will only make insulin receptors if they need to. If you start as a total couch potato, and then start walking a mile a day, your muscles need to adapt to even this small increase in activity (walking a mile burns about an extra 100 kcal).

And of course, that's what people see. How many friends have you known that started a new exercise regime and rapidly lost some weight? This is often accompanied by pronouncements like "I can eat anything I want, as long as I exercise enough". That's true, at least to the point where the new fat storage/release equilibrium is reached, at which point fat loss stops. Since the individual is no longer getting positive feedback of fat loss for their physical exertion, they usually cut back or quit, but continue eating "anything I want", and of course just get fat again.

And all of this ignores the elephant in the living room, which is overall metabolic regulation. If you use more calories than are totally available to you from food and storage (remember that high insulin makes stored fat unavailable), you should get hungry. Further, the body knows what it wants, and will try very hard to make you eat it. If you burn up the muscles' store of carbohydrate, the resultant temporary increase in insulin sensitivity will drop your blood sugar. Your brain senses that drop, and tells you to go eat some carbohydrates. People often "reward" themselves with a food treat after a workout, or maybe have a sugary energy drink or similar. Of course, this tends to defeat whatever gain in insulin sensitivity your exercise created.

The Challenge

The examples above, I believe, illustrate explanatory power of the insulin hypothesis, bringing many approaches which seemed disparate or opposed (like low fat vs. low carb) under a single explanation. My challenge to you, O Gentle Reader, is to provide counter-examples. Are there fat-loss strategies that cannot be explained by the insulin model? Give it your best shot in the comments.

Your Elephant Stepped on my Coffee Table

2009-06-06T09:07:00.000-07:00

Take a look at this press release: http://www.bidmc.org/News/InResearch/2009/June/POMCNeurons.aspx

The summary is this: genetically leptin-resistant mice will become obese and develop Type II diabetes. These researchers restored leptin-sensitivity for the pro-opiomelanocortin (POMC) neurons in the arcuate nucleus (ARC), an area of the hypothalamus involved with energy regulation, including appetite and blood sugar control. As a result, the mice both lost fat AND spontaneously increased their level of activity. They did not lose fat because they were exercising, they were excercising because they were losing fat.

Now contrast that to the prevailing view of obesity and (supposedly) related health issues like diabetes: you're a lazy slob, sit on the couch, eat too much, and therefore become fat and diabetic. Gary Taubes "Good Calories, Bad Calories" laid the foundation for challenging this hypothesis, drawing on decades of research showing that energy regulation is governed by an intricate dance of hormones and the central nervous system. In this view, people overeat because they're becoming fat as a result of some malfunction in this system; correspondingly, lean people are more active for the same reason.

This latest piece of research supports the hormone hypothesis. Leptin plays a key role in energy regulation, and is manufactured by fat cells depending on how much fat they contain. More fat, more leptin. Amongst other things, leptin acts on the brain to turn off appetite, i.e., when you've stored up enough energy, stop eating. It is further hypothesized that the ARC may a play role in blood glucose control, e.g. providing CNS signals to the liver to regulate glucose manufacture. This role is certainly supported by the research linked above.

The key question becomes what causes the ARC to become leptin-resistant. The authors seem to completely miss this, instead gushing about "novel drug targets" (i.e. $$$). There are plenty of clues laying about, however. Stephan at Whole Health Source notes that leptin resistance precedes insulin resistance in the development of Type II diabetes. So what causes leptin resistance? Apart from genetic defects, this is an open question, but a reasonable conjecture would be wheat germ agglutinin (WGA), a kind of protein called a lectin which is found in grains. Lectins like WGA have the annoying capability of binding to hormone receptors. This is all the more annoying because they can avoid protease enzymes in the digestive system and pass into the blood intact (most proteins are broken into amino acids, as loading up your body with intact foreign proteins is bad juju).

WGA is so effective at binding hormone receptors that scientists regularly use it for studying these. For instance, they'll take the WGA with a radioactive substance and then see where it winds up sticking on a cell. Neurotransmitters are basically just hormones released in neuronal synapse, and scientists use it to study how things are transported in the brain. So, WGA a) binds to leptin receptors and b) wanders around your brain. And what does WGA do when it locks into your leptin receptors? Unknown, but in the test tube, at least, it blocks the effects of leptin. Hmmm, throw in insulin resistance of the liver from excess fructose, sounds like a recipe for Type II diabetes.

The Paradox Paradox

2009-05-20T07:00:00.000-07:00

By denying scientific principles, one may maintain any paradox.
Galileo Galilei

Paradox: [Latin paradoxum, from Greek paradoxon from neuter sing. of paradoxos, conflicting with expectation, para-, beyond; see para–¹, + doxa, opinion (from dokein, to think; see dek-).]
(noun)
A seemingly contradictory statement that may nonetheless be true: the paradox that standing is more tiring than walking.
One exhibiting inexplicable or contradictory aspects: “The silence of midnight, to speak truly, though apparently a paradox, rung in my ears” (Mary Shelley)
An assertion that is essentially self-contradictory, though based on a valid deduction from acceptable premises.
A statement contrary to received opinion.

This morning I ran across an article discussing the "paradox" that obesity seems to play a protective role in heart disease. We seem to be presented with a flood of paradoxes relating to health and nutrition - and indeed said paradoxes present equal confusion to (too) many scientists. Let's talk a bit about what a paradox really is, and then I'll show why the Galileo quote was right on the money. To say it another way, any scientist who cries "paradox" is being fundamentally unscientific. You'd never get them to admit it (because they probably don't believe it), but their use of paradox is in the sense of the 4th definition above, rather than indicating a true logical paradox. And we all know how well science and opinion mix.

Most paradoxes are only superficially paradoxical, and can be resolved on deeper inspection. Real paradoxes are rare. Consider this example from the Wikipedia entry on "paradox":

... consider a situation in which a father and his son are driving down the road. The car collides with a tree and the father is killed. The boy is rushed to the nearest hospital where he is prepared for emergency surgery. On entering the surgery suite, the surgeon says, "I can't operate on this boy. He's my son."
Sounds paradoxical, right? But the issue is simply a bad assumption: since most surgeons are men, one erroneously extrapolates that ALL surgeons are men. Obviously the surgeon must be the boy's mother. This is a common source of claimed paradoxes in science: extrapolating something that is believed at some level (e.g. obesity causes heart disease) to a statement of absolute truth.

Let's consider mathematics, starting with simple Boolean logic. The point of logic is to reason deductively about the truth of a statement, given the truth of other statements. A paradox would imply you could get different answers depending on how you worked through the problem, i.e. two different sets of steps valid within the rules of logic would give different answers. If such paradoxes did exist, they clearly render logic useless, since you could never consistently prove something true. The dictionary definition of "paradox" admits a subtly different situation, which is a statement like "I am a liar". The rules of logic can neither prove nor disprove this statement. But this more an artifact of language and technical aspects of formal mathematical systems as opposed to the sort of "scientific paradox" claimed by the authors of the heart disease/obesity paper.

Generalizing the case of logic to all math leads to the same conclusion. A mathematical system which admits true paradoxes is pointless. A true paradox would indicate inconsistency in the rules and assumptions used to build the system. Problems labeled "paradoxical" in math are really counter-intuitive, like the Banach-Tarski Paradox, where one can prove that there is a way of dividing up a 3-dimensional ball, moving the pieces around without stretching them, and reassembling to get two balls of the same size as the original. Sounds pretty paradoxical, right? But it's really just counter-intuitive: the size of the set of points in the one ball (called the cardinality) is actually the same as the size of the set of points in the two balls. The size of a set is different than it's measure (which in this case would be the volume). The result that we can double the volume of a set of points without changing the cardinality of that set violates our intuition, but is consistent within the mathematical definitions of measure and cardinality (this is roughly equivalent to realizing that that size of the set of even integers is the same as the size of the set of all integers: they're both infinite).

Can we ever have a true scientific paradox? Mathematical truth is purely conceptual, and can thus be "absolute". We define the axioms and rules and mentally manipulate these to prove or disprove other statements. Science is messier. Nothing is absolute in science, because all scientific theories must be supported by observational evidence from the real world. Our observations are limited by various practical considerations. Our data is never 100% accurate, we can never be sure we've observed all of the relevant variables, etc. So our belief in a scientific hypothesis is always conditioned on the evidence which itself is subject to limitations of our ability to observe and collect information. Scientific belief thus exists in a continuum between absolute truth and falsehood, and is always conditioned on the available evidence. As new evidence is obtained, we update our beliefs accordingly toward greater or less truth as indicated by the new evidence.

So you can never have a scientific paradox. Scientific honesty demands that observation of evidence contradicting a hypothesis causes you to lower your belief in that hypothesis. A paradox requires two statements which can be shown to be contradictory yet simultaneous true. But neither evidence nor hypotheses carry absolute truth, and our beliefs in either are always conditioned on the other. The scientifically relevant method evaluates belief of hypotheses conditioned on evidence.

Science as most often practiced, using frequentist statistics, evaluates belief in data assuming the truth of a hypothesis, so it's no wonder scientists spend so much time confused about "paradoxes". Take a hypothesis and data that appears to contradict that hypothesis. Then try to test the hypothesis quantifying your belief in the data presuming truth of that hypothesis. When the number comes back low, you basically have two choices: come up with a reason why the data is "wrong" (e.g. a mistake in experimental design, broken instrument, drunken graduate student), or realize that your hypothesis (again, whose truth was assumed as part of the analysis) is possibly not true. If you believe your data AND are 100% convinced of the hypothesis (which begs the question of why you did the experiment in the first place), you'll think you've got a paradox. The only real paradox is that people get paid to make this fundamental error in inference - over and over and over . . .

Our friends who observed the apparently paradoxical protective effect of obesity in heart disease patients have fallen into this trap. The right thing to do upon observing this effect is to update belief in the hypothesis that obesity causes heart disease. The new evidence lowers our belief in that hypothesis, and simultaneously signals that we should evaluate competing hypotheses in the light of all of the available evidence. Indeed, if one were to do a proper analysis of the evidence, it would be clear that no more supports the hypothesis that obesity causes heart disease any more than it does the hypothesis that heart disease causes obesity. Not all heart disease patients are obese, and not all obese people suffer from heart disease. Further, there's no strong metabolic evidence indicating the arrow of causality.

The smart thing to do in such situations is to start looking at hypotheses where a third culprit is the underlying cause of the observed associated effects. So what might cause both obesity and heart disease, or in some people one but not the other?

A growing body of evidence links poor blood sugar control to heart attack risk (see this recent study, for instance). The body maintains blood glucose in a narrow range, because both too little or too much are dangerous. Too little and the brain starves. Too much and you overwhelm the systems which repair the damage caused by sugar, in particular that to the arterial lining. You cannot excrete excess blood glucose like you can excess water or salt (at least not without severely damaging the kidneys). So your options are to either store it, or turn it into something else. The muscles and liver have a limited capacity for storage of glucose. Once they're full, the liver, as directed by insulin, will turn the rest into fat, and your fat tissue, again as directed by insulin, will store that fat.

At least that's how it's supposed to work. Insulin is a hormone, and hormones activate genes to manufacture proteins. The response to a hormonal stimulus is thus partially determined by genetics. Your genes will determine, for instance, the relative expression of lipoprotein lipase and hormone sensitive lipase in response to insulin levels. This in turn governs the ability to take fat from the blood and store it, or release that fat from fat cells to be used as energy. Similarly one guesses that insulin sensitivity of muscle and liver tissue has some genetic basis, and these may further be altered by disease, nutrition, etc. (overconsuption of either alcohol or fructose will make the liver insulin resistant, thus impeding its ability to store glucose, transform it to fat, or scale back manufacture of glucose from protein).

In the framework of this hypothesis, a person with greater propensity towards fat storage has a potential advantage when it comes to heart disease, as it provides another "sink" for excess blood glucose. A perpetually skinny person may be at a disadvantage. If your fat cells don't respond to insulin signals, then the fat has nowhere to go and stacks up in your blood as "triglycerides". If your liver and/or muscle don't properly respond to insulin, glucose begins to build up in the blood. Neither situation is likely good for the development of heart disease, and in reality both seem to occur simultaneously for susceptible individuals.

The news blurb doesn't state whether blood glucose or triglycerides tested, and the publisher of Journal of the American College of Cardiology doesn't provide free access to the publication. Perhaps a reader with access can post a comment as to whether blood glucose was tested and the results. Regardless, it is the unwillingness or inability of the authors to consider alternative hypotheses which leads them to cry "Paradox!" in such a public manner. Such individuals are clearly mired in irrational dogma and/or trying to drum up extra funding. From a broader view, any hypothesis (like diet-heart) which embraces paradoxes (like the "French paradox") are probably junk science. Treat them accordingly lest you extinguish your own spark of reason.

Pearls Before H1N1

2009-05-03T16:48:00.000-07:00

The swine flu is making me sick. I don't have the virus (at least no symptoms), but the whole panic over it annoys me on multiple fronts. Take this recent AP story as an example. 241 cases? Is this really worth worrying about? I find the following quote particularly telling:

Even if the swine virus doesn't prove as potent as authorities first feared, Besser said that doesn't mean the U.S. and World Health Organization overreacted in racing to prevent a pandemic, or worldwide spread, of a virus never before seen.
With a new infectious disease, "you basically get one shot, you get one chance to try to reduce the impact," Besser said. "You take a very aggressive approach and as you learn more information you can tailor your response."
It was just over a week ago that authorities learned the new flu CDC had detected in a few people in California and Texas was causing a large outbreak and deaths in Mexico, triggering global alarm.
"We didn't know what its lethality was going to be. We had to move. Once you get behind flu, you can't catch up," Homeland Security Secretary Janet Napolitano said.

Maybe an informed reader can help me out here. Is there any reason to believe that the "very aggressive approach" makes any difference at all? Do all of these countermeasures have any effect? I get the feeling there's a whole bunch of "virus nerds" at the CDC just waiting for the opportunity to do something, which more than anything is to feed public hysteria and justify their existence. Maybe I'm being overly pessimistic, but the track record of government science types is pretty abysmal. I do think that they think they're being helpful, but I really have a difficult time shaking the feeling that anything public health authorities do to try and stop a virus (which has evolved over billions of years to be very efficient at spreading infection) is roughly equivalent to piling up cheesecloth to protect yourself from a tsunami.

Western culture seems to be developing increasingly extreme paranoia about all things health related. And of course, this is fueled by the media and other groups (like the CDC) who stand to benefit from spreading fear. Too many people spend too much time worrying about "silent killers": cancer, heart disease, viral diseases, you name it. Correspondingly, there exists as MASSIVE "industry" concerned with disseminating information and treatment. Just look at the amount of money spent helping us with that most deadly of conditions, "high cholesterol". Can you watch TV anymore without seeing at least one advertisment for statins (geez, there's one on now - GO TIVO) or a wonder food (like Ch**rios for crying out loud) that is going to save you from the "silent killer". Ch**rios and statins: the delicious and healthy way to start the day.

Fear is a complicated emotion, and that complication no doubt stems from the underlying complicated nature of trying to survive. I believe the major psychological source of fear is uncertainty, i.e. "was that sound Grog relieving himself due to over-consumption of cachonga root, or a bear coming to eat me?". I suspect the physiological source of fear is hormones, namely the stress hormones. Certainly stress brings about an increase in irrational fear (is there such a thing as rational fear?), and certain drugs can activate those same pathways and create tremendous fear. Our society seems now more than ever in the grip of fear inducers. Though science and technology have advanced human knowledge, the fact is that most of that knowledge is held by precious few. "Back in the day", when we all lived in the forest, you needed lots of knowledge to survive. The "unknown" was largely those aspects of Nature humans could not control, like the weather, hungry bears, and infection. Now we trust that to the "experts", tacitly ceding them control over our lives. And other aspects of lifestyle probably contribute to stress. Crappy nutrition certainly increases stress hormones, as does chronic illness. The diabetes "epidemic" is a pretty good sign that a major portion of the population is suffering from chronic illness due to poor nutrition (and a pronounced lack of sunshine).

The combination is a real mess: a sick and fear-filled population driving a culture of experts to save them from their own ignorance. And of course the experts turn out to have little relevant expertise. Their major source of validation comes from the feedback that we give them. How many people do you know whose doctor fills them full of pills to no effect? The patient experiences little actual improvement in health, yet they keep going back for more. What if people started thinking for themselves and kicked their doctor to the curb in favor of self-informed care? I suspect a swift kick in the pocketbook would change MDs' opinion of statins in a big hurry. Similarly, let's have some fun and watch the shakeout if (as I think is highly probable) swine flu turns out to be a dud. Congress and the media will praise the CDC for quick and decisive action, and they'll wind up with a nice budget increase, which is all the validation they need. I suspect we won't see any sort of critical introspection as to whether or not all of this flopping about and general panic has a measurable benefit on public health. Nobody gets budget increases for that.

In a really nice post on critical thinking, Dr. Mike Eades appropriated one of thousands of fabulous lines from George Carlin (who I personally think was probably smarter than everyone at the CDC - combined). I shall re-appropriate it here:

Think of how stupid the average person is, and then realize that half of them are stupider than that.

I spent about 10 years "in" science, 3 to get my M.S. and Ph.D. another 7 as a post-doc and researcher. I had the chance to interact with many scientists, mostly from physics, but also from other fields, and if there's one thing I can tell you with great certainty it is that the distribution of intelligence amongst scientists pretty much mirrors that of the population at large. By "intelligence", I mean the ability to rationally weight complex evidence as it relates to different hypotheses. My point here is not to say that scientists are dumb (though as we learned from Carlin, half of them are dumb, by definition), but that you likely have the same reasoning capability as the average scientist. In fact, you're probably a little better than the average scientist. Scientists favor complex solutions, precisely because they are hard to understand. This validates their own self-perception of being smarter than the average bear. As a scientist I've had more than one scientific discussion end with "That's too simple to be right." Not, mind you, "that idea contradicts this piece of evidence". It's just too simple for their taste. So I dressed up the same simple idea with complex-appearing math and verbiage, leading to acceptance.

The swine flu situation presents us with the opportunity to watch this in action. I was just watching a clip from a news conference, where some "expert" was simultaneously back-pedaling on the severity of the present threat, while drumming up some more fear about the future. The thrust of it was that the Spanish Flu "took a summer break", and then re-awoke to slaughter millions. So keep on wiping down those door handles and pouring in the taxpayer dollars for stockpiling flu vaccines and anti-virals. Yet our expert likely missed on the glaringly obvious simple hypothesis: people almost never get flu in the summer, an effect seen in both hemispheres. That applied also to the highly deadly Spanish Flu, which apparently spent the summer at the beach before coming back to clobber Western civilization. Or maybe something about the summer that made people more immune to a pre-existing infection. Gee, I wonder what that could be?

(For those in the cheap seats, it's Vitamin D3.)

Can I say with certainty that Vitamin D3 is the answer to the swine flu? No. But the CDC nerds also have no reason to say that it isn't, other than it's a) too simple, and b) puts a fair dent in their raison d'etre. Even WebMD, normally a bastion of medical orthodoxy, is at least considering the possibility. I presume flu cases are being tested for H1N1 antibodies. I wonder if anybody is bothering to test for Vitamin D3 while they're at it?

Nah, too simple. Ramp up that expensive anti-viral production. Far more tasteful.

Twitterpated

2009-05-03T07:37:00.000-07:00

I'm following the leads of Dr. Eades and Jimmy Moore on to Twitter. It's hard to find time to blog with my new job, and I wind up with stacks of links I want to talk about. Twitter seems like a good solution to at least push information I find interesting (and perhaps more often, incredibly dumb).

http://twitter.com/sparkofreason

Listening to Experts Makes You Stupid

2009-03-24T07:00:00.000-07:00

Got to work early this morning, and I thought this article deserved a quickie post:

http://www.newscientist.com/article/dn16826-brain-quirk-could-help-explain-financial-crisis.html?DCMP=OTC-rss&nsref=online-news

I think you could replace "Financial Crisis" with "Health Crisis" in the headline and nicely sum up the current boom in metabolic diseases etc. Most of us have done it at one point or another: uncritically accept the advice given by experts, even when a little thought shows it makes little sense. Now we've learned that the brain has a specific mechanism where it essentially shuts off given "expert advice". This perhaps explains why people seem to be thrown into such cognitive dissonance when presented with evidence which is rationally a slam dunk, but also contradicts what their doctors, the government, the media, and so forth have told them. I'm sure many of you have encountered irrational anger from friends and family when you question nutritional dogma. One of the weirdest things for me is how bent people get when I push them to justify why exactly "healthy whole grains" are so healthy. Still waiting (going on a couple of years now) for a response beyond "everybody knows that, so shut up."

That's not to say expert advice is necessarily bad - you just need to use your own brain as well, and weigh the expert information appropriately. Tom Naughton makes this point very nicely in "Fat Head" (see discussion of "functioning brain").

BTW, I'm finding "Fat Head" to be the most effective tool yet in overcoming the mental block created by "expert advice" (as opposed to my usual boring biochemistry lecture - maybe not so surprising). I suspect it's the humor that somehow breaks down the barriers of cognitive dissonance. It would be funny (in every sense of the word) if laughter made us more rational.

Fat Head: The Blog

2009-03-22T13:33:00.000-07:00

Tom Naughton of the fantastic "Fat Head" movie has started his own blog at http://www.fathead-movie.com/. Great stuff, and like the movie, informative and very funny. Be sure to check out his first post and learn how to make your very own misleading study supporting ridiculous preconceptions.

Wheat Head

2009-02-26T12:47:00.000-08:00

How's this for a mind-blower:

Schizophrenia, gluten, and low-carbohydrate, ketogenic diets: a case report and review of the literature

Synopsis: 70-year-old schizophrenic experienced complete remission of symptoms after adopting a low-carbohydrate diet. Now, of course, this is just one case study, and needs to be replicated a LOT more times. But it really caught my eye, as from my last post I've been thinking about the mental effects of diet, particularly grains. Schizophrenia is one extreme case of neurological disturbance, but as with all things biological, disease expression is rarely binary. The manifestation of symptoms covers a spectrum when viewed across the population. We just tend to pay the most attention to the extreme cases. Suppose grains were implicated as causal in schizophrenia. It's a good bet they then contribute to other less obvious forms of mental disturbance. Since grains are so widely consumed, this may be actually viewed as the "norm".

Indeed, other neurological conditions are known to benefit from removal of dietary grains, including pediatric epilepsy (discussed in the paper), ADHD, autism, and multiple sclerosis. I've been doing some poking around on wheat germ agglutinin and the brain. Turns out WGA does indeed cross the blood-brain barrier, will bind to insulin receptors in the brain, and probably all kinds of other stuff as well. Google "WGA brain", and you'll find WGA is actually used extensively to map out neuronal pathways, so clearly has potential neurological effects beyond just binding to insulin receptors.

I propose that the sequel to "Fat Head" be "Wheat Head". That covers a lot of ground, from Weston A. Price's observations on cranial development (there definitely seems to be distinct "Wheat Head" phenotypes), to dental disease to the neurological implications, and probably more.

Wouldn't it be fun if the food pyramid were making us fat, sick, deformed, and crazy all at once?

The Children of the Wheat

2009-02-25T07:21:00.000-08:00

Hello everyone out there in blog world. Let me start by apologizing for my prolonged absence. The recent lack of posting is partly a result of being busy with other aspects of life, not the least of which was searching for a new job. I feel very fortunate to have found an opportunity given the current economic situation; even more fortunate that I will be helping to build the next generation of genetic sequencing machines. So I get to have a job not only on the cutting edge of science, but also hopefully contributing to the health of our society. I expect to be pretty busy with the new gig, so I don't know that I'll be able to post much in the coming months either.

The other reason for the lack of posts is that I haven't really had much new to say. The one thing I'd like to get to is the rest of the energy regulation series, particularly some info about innate and learned food preferences, including why carbohydrates may be addictive (short answer: insulin tweaks an area of the brain called the insula, also lit up by drugs such as cocaine and opiates). I've started a few posts and abandoned them, mainly because they seemed to be covering the same ground. Let me throw out some these random thoughts here, rambling about in no particular order, sort of a brain dump before I disappear again.

First, I want to recommend a couple of DVDs. First is Tom Naughton's Fat Head, which is both funny and educational. Fat Head provides a gentle and highly accessible introduction to some of the topics covered in Gary Taubes' Good Calories, Bad Calories. Even my kids (8 and 4) "got it", though I suppose it didn't hurt that I've been pumping them full of the background info for a few years :-). Watch for the moment when Tom's doctor sees the measurable effects of eating an all fast-food low carb diet. The expression on his face is absolutely priceless (and to his credit, he didn't just blow it off like many in the mainstream of health would). Also watch the bonus interview footage, great stuff. I particularly liked a quote from Dr. Al Sears, something to the effect of "If you're not dead, you can still heal." Most doctors today seem resigned to mitigating the effects of metabolic syndrome through medication, rather than actually healing. I believe they're generally well-intentioned, just misinformed. But experience has shown that given the opportunity, the body has an amazing ability to heal itself, IF you can remove or at least mitigate the underlying factors reinforcing the underlying disease process. More on this later. Jimmy Moore has a great interview with Tom Naughton as well.

At one point in the bonus interviews, Dr. Sears discusses how rabbits were ultimately used as a model for heart disease. Apparently researchers started out by feeding dogs large quantities of lard, but the dogs would not develop athersclerosis. Of course that should have been obvious from the outset: saturated fat and cholesterol-containing animal fat are a cornerstone of the evolutionary diet of canines. Since the researchers didn't get their preconceptions validated using dogs, they switched to rabbits, whose natural diet is grass, and who thus never evolved any mechanisms for handling large dietary quantities of either fat or cholesterol. Not surprisingly, the poor bunnies' metabolism went berserk, and the researchers extrapolated this result to humans. Talk about confirmation bias.

Here's a personal related anecdote. Our dog Picasso is about 12 years old now. He was getting pretty porky and arthritic, and also began drinking a ridiculous amount of water, so I suspected he was developing doggy diabetes. I was going to take him to the vet, but first checked out the ingredients on his "healthy" doctor-recommended food. First ingredient: corn starch. I felt like a dope for not checking that earlier, and switched him to a diet of raw food, mainly patties made from ground up whole chickens, supplented with leftover bacon grease (we eat a lot of bacon here) and raw organ meats like heart, liver, kidneys, and tripe. The water-drinking issue disappeared almost immediately. Over time, Picasso has really trimmed up, looks like a young dog now, with a nice shiny coat. He's become a lot more friendly and playful now as well. People are always surprised to learn he's nearly 12. Hint hint: the evolutionary diet of humans is much closer to that of canines than bunny wabbits.

The other DVD is "My Big Fat Diet", which actually provides several examples of the healing powers of the human body. This documentary follows Dr. Jay Wortman as he treats metabolic syndrome in a group of Canadian Namgis First Nation people via a low carb diet. The results: not only did they lose fat, but also reduced or eliminated many of the other symptoms of metabolic syndrome along with associated medications. Even more striking was how the Namgis' sense of community and family returned as their bodies healed. Every time I watch My Big Fat Diet, I wonder how many of our various societal ills are fueled by poor health resulting from bad nutrition. The Western diet promotes a situation where the body perceives itself to be in constant crisis: insulin resistance essentially implies starvation at the cellular level, high blood sugar and dietary polyunsaturated fat contribute to glycative/oxidative stress, and hyperinsulinemia probably leads to chronically high levels of stress hormones like cortisol. Is it any wonder we find our society to be populated by individuals with greater focus on the immediate benefits to themselves rather than considering the much greater long-term benefits of contributing to societal well-being?

Another fun fact from My Big Fat Diet is how the Namgis used fat rendered from the tiny Oolichan fish to supply fat soluble vitamins, particularly Vitamin D in the winter. The Namgis traditionally made the association between the yellow color of the Oolichan grease and sunshine, which I thought was pretty insightful. I started a post on Vitamin D, but there's so much info out there already I decided I had little extra to add. Vitamin D deficiency is quickly making it's way into the mainstream medical consciousness as well, which is outstanding. The hormonal version of Vitamin D activates over 1000 genes (something I hope to learn more about in my new job), so it probably should not be surprising that Vitamin D deficiency can lead to a broad spectrum of health problems, particularly those like multiple sclerosis which are known to be influenced by genetic risk factors.

And it's very interesting to think about diseases like influenza, traditionally thought of as being primarily infectious and requiring immunization. But the influenza virus has certainly been around as long as humans, and it's hard to fathom how humanity could have survived if we were all getting knocked flat by the flu once a year. A whole tribe of hunter-gatherers on their backs with flu seems like prime cave bear food. And the flu doesn't behave like an infectious disease, as does the common cold. For instance, Google has a cool new resource estimating flu activity in the US, based on search queries. I've been watching this thing all winter, and it definitely does not show any sort of epidemic pattern. You'd expect flu hotspots to spread geographically over time, but instead the map is pretty much random. This sort of non-infectious pattern for influenza is generally observed, where it just pops up simultaneously in geographically separated locations rather than spreading.

A good hypothesis is that humans generally have a given flu virus all year (and I wonder if anybody has bothered to test for influenza antibodies in the summer). We carry all kinds of viruses all the time, they're just suppressed by our immune systems. But if the immune system becomes weakened, say due to Vitamin D deficiency brought about by lack of sunlight exposure in the winter, the virus can take hold and make you sick. Further, it is known that the majority of symptoms from both flu and cold are basically due to your own immune reaction, not the virus itself. The innate immune system uses cells like neutrophils, whose job it is to seek and destroy potentially infectious agents like viruses and bacteria using both physical and chemical means. But once ramped up, these hunter-killer cells will also destroy your own tissue, and so need to be moderated. If not controlled, your immune system will kill you, which is precisely what happened to victims of the Spanish flu epidemic (Epidemiol Infect 2006;134:1129–1140). What is the primary mechanism for moderating this immune response? Vitamin D.

Another personal anecdote: winter used to be medically difficult for our family, as it is for most people. We'd have our two kids at the doctor at least once a month for ear/sinus infections, strep throat, etc. and the we adults would usually drag around some kind of virus for a few weeks. But that's just part of life, right? Wrong. Since we began supplementing with Vitamin D in the winter (about two years ago), zero doctor visits. I don't even think the kids have had a fever in this time, certainly not one high enough to cause any concern. We do get sick, but it's minor, never more than an annoyance, and short-lived. While the other kids at school are dropping left and right from strep throat and flu, our kids now sail through pretty much unscathed. I've seen it multiple times with friends and family as well. They have some drawn out respiratory disease, like a persistent cough. When we finally get them on the Vitamin D train, it's gone, never to return. I also used to get bad hayfever attacks - no more. Yes, it's anecdotal, but this is what you'd expect from the well-established interaction between Vitamin D and the immune system.

So it's good to see the mainstream picking up on this. They seem to be "getting it" on other fronts as well, albeit slowly. MSNBC recently had a long article on omega-3's, which also discussed the general problems inherent in vegetable oils processed from seeds and soybeans. It's frustrating, because they get some of it "right" (in the sense that their conclusions follow logically from all of the available evidence), yet still are hung up on issues like dietary cholesterol and almost completely miss certain living elephants, as it were. I posted a longish comment on the article, but my essential criticism is one I've voiced before: if you start with bad or incomplete prior information, even the most rigorously logical analysis will lead to goofy conclusions. This in turn implies choices for diet, supplements, medical treatments etc. Read the article, and watch how some key assumptions lead to all kinds of wild inferences and extrapolations.

Michael Pollan's book "In Defense of Food" is another example of this. Though Pollan's "The Omnivore's Dilemma" remains one of my favorites, I had avoided reading "In Defense of Food", mainly because it espoused the mantra "Eat food. Not too much. Mostly plants." I'm all for eating food vs. factory produced foodlike substances, but the last two statements smack of dogma. But our local library decided to feature this book, so I thought I'd better read it in the interest of causing trouble.

Pollan gets some of it right (again, in terms of drawing logical inferences from the available evidence), but frustratingly misses the big stuff, like the total lack of evidence that dietary fiber contributes to health, or that red meat consumption causes disease. For instance, he discusses Good Calories, Bad Calories, but cherry-picks the evidence that apparently supports his preconceptions and ignores the rest. He rails against reductionism, apparently following in the footsteps of T. Colin Campbell (just about the worst possible choice), missing the point that the point of studying isolated aspects of nutrition and metabolism is to inform the "big picture". While a complex system like the human body may be greater than the sum of it's parts, you certainly have no hope of understanding the whole without at least understanding the parts.

Pollan then gives 24 rules which we should follow when selecting and eating food. This is a great example of how starting from goofy assumptions just leads to over-complication. Who is going to walk around a store or look at a menu and mentally check off 24 different things? There's no way that the simple act of eating should require that level of mental effort; it certainly didn't for our hunter-gatherer ancestors. Some of his recommendations are good, like shop at your farmers market or eat wild foods, but a lot of it is just nonsense. For instance, he wants us to "Eat slowly". What other animal consciously regulates it's rate of food intake? Do lions devour their prey at a measured pace, and teach their young to do the same? Like most, Pollan is enthused about a plant-based diet, all hopped up on the idea that we require thousands of different phytonutrients for health. The evidence for this? "In all my interviews with nutrition experts, the benefits of a plant-based diet provided the only point of consensus." Really - after extolling the evils of "nutritionism" for half the book, now you're going to follow the consensus of nutrition experts? Aren't these the same boobs who developed ideas like the food pyramid? Take a walk around your local mall, and you can see how well that's played out in the context of human health. Remember also that scientific consensus rarely is the result of critical examination of the evidence. Rather it's a social phenomenon: the scientists keep repeating the same thing to each other, and eventually it becomes "truth". If you're lucky, somebody with half a brain gets the ball rolling by actually making a logical inference from evidence, but the usual situation is that of the diet-heart hypothesis, where an initial unproved hypothesis turns into scientific "fact" simply through social forces.

Pollan further wants us to focus on eating leaves. This recommendation certainly makes sense for a cow or a gorilla, both of which have vast digestive tracts built for the long process of breaking down cellulose and freeing the nutrition in leaves. Both animals also eat enormous quantities of leaves to meet caloric requirements, e.g. upwards of 60 lbs. daily for a gorilla. Of course humans can predigest leaves through cooking, and we can add fat to help assimilation of the micronutrients, acids to neutralize antinutrients like phytic acid, etc. But those are recent developments in the course of evolution. Humans almost certainly did not evolve getting any significant calories from raw leaves. Our digestive systems just can't handle it, and you need to eat many pounds of leaves daily to have any hope of of meeting caloric requirements. It seems far more likely that humans would have gravitated toward more calorically dense plant foods, like fruit, nuts, and starchy root vegetables. Of course the most nutritionally dense foods are of animal origin, including seafoods, organs, and eggs.

Pollan's first rule is the worst: "Don't eat anything your great grandmother wouldn't recognize as food." First of all, I don't have the faintest idea what my great-grandmother would or would not consider food, and since she's long since passed on, I can't ask her. But given that margerine popped up over 100 years ago, I would guess that would pass as food for her. Does that make it okay to eat margerine? And how about bread? Great grandma probably considered "bread" as food, but bread is the end result of extensively processing wheat, which in its raw state would be toxic. So is bread "food", and should I eat bread? Evidence seems to be mounting that the answer is "no". So this guideline is pointless.

The mental processing required to figure what to eat should be low. Humans evolved as omnivores, which means we can eat a very wide variety of foods. Any minimally processed food that doesn't taste bad or make you immediately ill is almost certainly going to be healthy (I'm trying to think of a counterexample, with no luck). If your food requires a lot of technology and industrial processing to render it edible, you might want to rethink whether it actually qualifies as "food". Dr. Sears makes this point during his bonus interview on the Fat Head DVD, noting that had our ancestors tried raw grains or soybeans, they would have found them distasteful and contracted a painful bellyache, not exactly a stimulus to eat more of those foods. Unlike fruit, which evolved to be desirable to eat in order to spread seeds, grains and legumes do not want their seeds to be eaten, as that of course prevents those seeds from ever growing into plants. So these plants developed a variety of chemical and physical defenses to discourage predation. Some animals, notably birds, responded with adaptations which allow them to flourish on grains (birds have a crop used to grind up the grains, and enzymes to block anti-nutrients like protease inhibitors). Mammals (and humans in particularly) generally lack these adaptations. Note, for example, the effort required to prevent grain-fed cattle from dropping dead inconveniently early.

The wonders of science allow us to turn wheat and soybeans into foodlike substances that at least won't immediately put you in the hospital, and of course these pseudo-foods are made more attractive by formulating them to appeal to innate flavor and texture triggers like fattiness, saltiness, and sweetness. But in our industrialized food environment, we can no longer rely on our senses to distinguish what is good to eat. By contrast, we see "primitive" peoples able to thrive on a wide variety of foods obtainable from their environment, from the flesh/fat laden diet of the Inuit to the largely carbohydrate-based diet of the Kitavans (supplemented with seafood for certain minerals and fat-soluble vitamins). The common thread is that they pretty much directly eat what they obtain from their environment, and intervening processing is usually minimal and aimed at either making nutrients more accessible (cooking) or for preservation (drying/smoking). They don't need 24 rules to figure out what to eat, and neither should we.

Returning to the point about whether or not bread is "food": the role of grains in the modern diet deserves examination. Let me start by putting some context around this. It is, I think, increasingly clear that our "diseases of civilization" are strongly rooted in metabolic disturbances caused by food. Volek and Feinman have made a very strong argument that "metabolic syndrome" can be defined by the response of an individual to dietary carbohydrate, and that the cure is removal of such from the diet. This hypothesis is supported by many scientific studies, both "Fat Head" and "My Big Fat Diet", as well as the personal anecdotes of many thousands (including myself, having lost 100 lbs. and restored many aspects of health on a low carb diet). But the cause of a disease is not necessarily the inverse of the cure, i.e. just eating too many carbohydrates doesn't necessarily cause metabolic syndrome. The traditional diet of the Kitavans and Tarahumara is carbohydrate-based, but neither group develops metabolic syndrome. So I'd venture that it's the type of carbohydrates that drive the development of metabolic syndrome. Once you've broken your metabolism, then any significant quantity of dietary carbs will cause you problems, but what got you to that broken state? For example, your gasoline-powered car can go a long time burning gasoline with no significant issues. Put diesel in the tank, though, and you've really screwed things up, and no longer can use gasoline as fuel until you've fixed the damage done by the diesel.

Now I'll be the first to admit that this question is sort of academic. After all, if you just ate low carb across the board, you'd avoid any subclasses of carbohydrate food that could contribute to chronic metabolic problems. But the reality is that our food environment is flooded with refined-carbohydrate-rich (pseudo)foods. They are deeply ingrained in our culture, pushed on us from every direction. And there's also the issue of what to eat if your metabolism is not broken. I think about this particularly in terms of what to feed my children. Is it better to let the kids eat a slice of pizza or french fries? Chocolate-covered pretzels or a lollipop? And you can't monitor their food intake 24/7. You know they'll be offered crap from every direction when you're not around, so how can you teach them to make reasonable choices, e.g. taking bad instead of worse?

I don't think the scientific evidence is really there to provide a definitive answer. But we can make some reasonable guesses based on what is known about various aspects of metabolism and physiology and how these may hypothetically respond to various inputs. I'm increasingly of the opinion that in the spectrum of carbohydrates wheat is particularly bad. Stephan at the Whole Health Source blog has many articles discussing potential antinutrients in grains, definitely worth reading. One interesting aspect of grains are lectins, which are proteins that basically have the ability to bind to cellular receptors. Lectins in food are often not broken down to amino acids in the gut, and thus can cause mischief in the digestive system and, if they cross over into circulation (which they do), in the rest of the body as well.

Wheat germ agglutinin (WGA) has been studied in the test tube. If you Google "wga insulin receptor" you'll find a lot of papers, probably because WGA can bind to insulin receptors, which makes it easier to study various aspects of the receptor chemistry. From a physiological standpoint, WGA at least has the potential to be troublesome. For instance, not only does WGA bind to insulin receptors, it sticks there. When an insulin molecule binds to an insulin receptor, the whole complex is absorbed by the cell. One insulin molecule thus generates a specific and discrete response in a cell. When WGA binds to an insulin receptor, the complex is not absorbed, it just sits there activating at least part of the insulin signaling chain until it is knocked off (certain sugars accomplish this, like N-acetyl glucosamine). That's potentially nasty. In test tube experiments, at least, WGA is just as effective at insulin at stimulating glucose tranport and blocking lipolysis in fat cells. Stephan also notes that WGA has the potential to block leptin receptors. Leptin resistance is one of the hallmarks of metabolic syndrome.

It is, of course, treacherous to infer effects of grain lectins on a whole organism based on these test-tube experiments. I don't know of any studies which have really studied such effects in detail. But certain anecdotal evidence is at least consistent with the idea that wheat may play a special role in causing metabolic problems. Take the recent much-ballyhooed study of obesity in China. If you look at the data, you'll note that while there is a trend for the more obese subjects to eat more carbohydrates than the less obese, the differences are fairly small, on the order of 10% or less. By contrast, the most obese quartile for men at 5x more wheat flour than the least obese quartile. Hmmm.

The movie My Big Fat Diet provided another interesting bit of evidence. There's a big annual festival held by the Namgis each year. The chief (whose name escapes me) who had Type II diabetes and heart disease had been on a low carb diet for some time, which had allowed him to control his blood sugar entirely without any medication. At the festival he had one piece of "traditional" bannock, a deep-fried bread made from white wheat flour. His blood sugar then soared, and then did not return to normal for a week. Now I very much doubt that such elevated blood sugar was simply the result of the carbohydrate in the bread. Even given his impaired carbohydrate metabolism, this should have been cleared in the course of a day or so. But what if WGA from the flour was instead binding to insulin receptors and sticking there, causing his liver to crank out more sugar? Complete speculation, but interesting to think about.

Finally, I can relate my own experience. After going low carb, I would generally find that even moderate "cheating" would lead to some obvious long-term effects, the most notable was that I'd break out in painful acne. But one night we were at our favorite local restaurant. They have a wonderful scallop dish with a fantastic sauce, and the whole thing is on top of thinly sliced red potatoes. I decided to go ahead and eat the potatoes, mainly just to get at the sauce without being socially unacceptable by drinking it straight from the bowl. Interestingly, though this represented a lot of carbohydrates for me, it had no noticeable effect. I've reproduced this with potatoes a number of times, which seem to not freak out my metabolism when eaten in moderation. On the flip-side, even a small amount of bread will reliably trigger a breakout that lasts a week or more. A more dramatic example occurs with beer. If I drink even two or three premium beers now, I will get quite ill, and then suffer a week or so of acne. It's not the alcohol, because an equivalent amount of red wine or vodka has little effect beyond the usual buzz.

One final crumb for thought: why have we as a society developed such a love for wheat? There's plenty of other places you can load up on starch, such as potatoes, corn, and rice. But we seem to have a special soft spot for wheat-based foods, and cultures seem to be quite willing to displace other forms of carbohydrate with wheat (e.g. the Chinese as discussed above). Remember near the beginning of the post I noted that insulin stimulates the area of the brain known as the insula. One function of the insula is to mediate food-related rewards, e.g. eat some nice sweet fruit, get a bit of an insulin spike, and the insula reinforces that behavior. That makes sense from an evolutionary standpoint: fruit is nutrient dense, but doesn't last for long, so it's a good idea to load up on it while it's around. Certain addictive drugs like cocaine and opiates light up the same area, just with much greater intensity. Suppose WGA were able to get in to the insula and bind to insulin receptors there? That would probably reinforce our desire for wheat, even more so if WGA shows the "stickiness" observed in the test tube. Totally unproven hypothesis, but it seems like one worth testing.

Well, I think I've pretty much emptied my head at this point. Let me just close with a quote from Sir William Drummond:

He who will not reason is a bigot; he who cannot is a fool; and he who dares not is a slave.

I feel like this sums up the situation we currently face as a society. Too often, we rely on "experts" to think for us. In other words, we tend to be "slaves" (I personally believe that most people are not "fools": they have the capacity to think, they just don't bother). Yet these "experts" are far too often "bigots", driven by personal goals and desires rather than reason. Scientists generally don't engage in what constitutes actual science, in the sense of testing a hypothesis and objectively evaluating belief in that hypothesis, because there's no money in that. Instead they concentrate on confirming the beliefs of those who hold the purse-strings, and that makes them "bigots" in the sense described by Drummond.

So don't be a slave. All it takes to break free from the bonds the bigots would impose is to start using your own brain, and this intellectual freedom (and only this) will allow you to make choices which maximize your own health, wealth, and well-being.

Chili Verde Recipe

2009-02-24T09:24:00.000-08:00

I had some friends ask me for this recipe, so thought this would be a good place to share. This is adapted from Dana Carpender's "Chicken Chili Verde" recipe, which can be found in her excellent cookbook "15 Minute Low-Carb Recipes".

6 lbs. pork shoulder, cut in 1/2" pieces (country/picnic style "boneless ribs" are a good choice)
2-3 medium yellow onions, diced
3 12 oz. bottles salsa verde
3 bay leaf
3 tsp. cumin
3 tbsp. minced garlic
Fresh ground pepper to taste
Sour cream or creme fraiche
Shredded cheese

Brown the pork over medium high heat. You'll probably need to do this in batches. If you put too much pork in the pan at once, it just steams and turns gray. A good heavy cast iron or stainless pan is essential for this - aluminum just doesn't conduct heat well enough. Add pork to crockpot.
Brown onions in the same pan as the pork. Be sure to scrape up as much of the brown goodness from the bottom of the pan. Add onions to crockpot.
Add spices and salsa to crockpot. Stir together if you are so inclined.
Cook for 6-8 hours on low. Serve hot topped with sour cream (I like creme fraiche better - more buttery) and shredded cheese.

Obviously, this makes a lot, but it keeps well and never lasts long in our household. You can always halve or third the recipe. If you're in a hurry, you can skip the browning steps and just throw everything in the crockpot. Still good, just not as good.

Book Review: The Jungle Effect, by Daphne Miller, M.D.

2008-10-28T05:33:00.000-07:00

Our local library recently began advertising a talk by Dr. Daphne Miller, author of The Jungle Effect. The essential concept of the book is to examine epidemiological "cold spots" for various modern diseases, such as diabetes, heart disease, depression, and cancer. These cold spots are areas notably low in the incidence of said diseases. Dr. Miller visited each area and studied the local cuisines, with the idea that food is a driving force behind development of these diseases which often show the highest incidence amongst those eating a modern Western diet.

I was quite excited when I first read about The Jungle Effect. One reviewer went so far as to dub Dr. Miller the modern equivalent of Weston Price. I'm a big fan of Price's work as a shining example of the application of the scientific method and what can be discovered with limited resources and a determined rational mind. I also believe cultural wisdom that has stood the test of time deserves to be weighed along with more "scientific" evidence, and of course am in favor of whole, nutrient-dense foods (who isn't?). As I read The Jungle Effect, however, my enthusiasm waned and frustration set in. While I do believe that the foods put forth by Dr. Miller would constitute a much healthier diet than eaten by most in modernized society, the scientific rationale falls well short, and I believe leads to confusion and complication that is both unnecessary and unjustified.

Let's start with the good. First and foremost, Dr. Miller is an excellent writer, and clearly passionate about helping people improve their health. The Jungle Effect covers five different traditional cuisines associated with disease cold spots:

Copper Canyon, Mexico (the Tarahumara): Diabetes
Crete: Heart Disease
Iceland: Depression
Cameroon: Bowel Trouble
Okinawa: Breast and Prostate Cancer

Dr. Miller's descriptions of these cultures and their cuisines are vivid and fascinating. Many of the recipes sound very tasty, and despite the often relatively high carbohydrate content (often from honey, sugar, or maple syrup) are probably considerably more healthy than the average Western diet. Indeed, the patients for which she "prescribed" these diets apparently saw positive results, e.g. in reducing blood sugar, blood pressure, weight, depression symptoms, etc. So there is clearly some upside here, at least compared with the diet and health of the average American.

But in the end, The Jungle Effect suffers from some fundamental flaws. My criticisms here are meant to be constructive. As noted in the last post, sharing information is important if we hope to understand and sort out differences in our beliefs. Dr. Miller's approach is "traditional" not only in searching out elements of indigenous cuisines, but also in adhering to the nutritional orthodoxy. She obviously received the usual medical training, and consulted a nutritionist while writing the book. But many of you reading this realize that widely-held beliefs about the health effects of various foods are constructed on evidence that is weak at best, with contradictory evidence often being ignored. This results in some clear cognitive dissonance. For instance, Dr. Miller briefly discusses the Inuit (Eskimos) and the high level of health maintained on their traditional diet consisting almost entirely of high-fat meat. Yet much of the rest of the book warns against the dangers of red meat and too much fat, particularly saturated fat. I suspect there's also some confirmation bias at work in her selection of which cultures to study. One wonders why she didn't visit the Inuit, Masai, or for that matter the Namgis tribe featured in the excellent documentary My Big Fat Diet. The latter case is particularly interesting, as the Namgis who returned to a traditional high-fat diet experienced rapid and major health improvements, considerably more dramatic than those described for Dr. Miller's patients. Evidence modifies beliefs, but our beliefs should not cause us to filter the evidence.

Dr. Miller does briefly attempt to explain away the apparent Inuit "paradox" by noting the wild animals traditionally eaten themselves eat nutrient dense food, and pass that nutrition along to predators. But then the best one could say is that it isn't meat per se that is unhealthy, just meat fed an unnatural diet (Dr. Miller generally recommends very low meat intake, particularly red meat, usually without distinguishing the source). Give her credit for singing the praises of nutrient-dense organ meats. She also gets some points for not invoking genetics as the root of the apparent paradox. If you ever feel the urge to do this, then you should undertake the following procedure:

Find a friend with some heavy boots.
Have them kick you in the backside.
After each kick, say the following: "I will not blame the observed failure of my hypothesis on unobserved genetic factors."
Repeat 2-4 until rationality sets in.

The Jungle Effect would have benefited from deeper critical thinking, rather than absolute reliance on consensus (see Galileo quote at the top of the page). One aspect of this would be a broader sample of indigenous cuisines, including those high in animal products. It would also have been nice to see some integrative analysis of the different diets. Weston Price studied a wide variety of indigenous cultures, and was able to distill some common nutritional factors resulting in robust health, even so far as to discover a new fat soluble vitamin (which he called Activator X, now thought to be Vitamin K2). I would like to know, for example, how the health of the various cultures compared across the spectrum of diseases. Cameroon may have low incidence of colon cancer, but how do their rates of diabetes, heart disease, etc. compare to the other cultures described in the book? For that matter, one would like to compare traditional Inuit on that basis as well, to include the full spectrum of dietary macronutrient compositions.

Indeed, Dr. Miller notes that the Tarahumara, while notably free of diabetes, are not particularly healthy otherwise. Following Weston Price's cue, I looked for information on Tarahumara dental health, the idea being that dental health is a reflection of overall health, certainly of the status of vitamins involved in immune support and mineral metabolism. I'd be interested in getting Dr. Miller's view, since she was on the spot and got to observe the Tarahumara. I did find this article, which implies that the traditional Tarahumara suffer from significant dental disease, though it's pretty thin on details. We might also compare visually them with a hunter-gatherer. Here's a photo of an indigenous Tarahumaran, who according to Dr. Miller subsists largely on corn, beans, squash, and relatively little meat. Compare with a Kalapalo tribesman, who eats a lot of fish (they don't hunt animals) and jungle fruits and vegetables. Draw your own conclusions. Personally, I wish I had some Kalapalo biceps.

The nutritional context could also have been expanded in time. Modern indigenous diets do not necessarily represent the evolutionary diet of humans. Those sampled by Dr. Miller all relied heavily on agriculture, yet those foods available through agriculture have been part of the human diet for a very short time, evolutionarily speaking. The paleo-anthropological evidence certainly indicates that the pre-agricultural diet often relied heavily on meat from large mammals, and there are some clear markers of health decline at the agricultural boundary (decreased skeletal stature and skull size, evidence of mineral deficiencies, tooth decay). The modern indigenous diets likely evolved from other influences beyond evolution: extinction of large prey animals, geopolitical forces, changing climate, etc. Over time, these cultures may have identified the healthiest combinations of whatever foods were available, but that doesn't mean the available foods are the healthiest as defined by human evolutionary heritage. So again, it's necessary to consider all available evidence, not just that which agrees with our preconceptions.

Let's discuss some of the key nutritional beliefs that underpin Dr. Miller's arguments. Despite being widely held, a critical examination shows that the actual scientific evidence for many of these beliefs is thin at best, and often contradictory. Gary Taubes' Good Calories, Bad Calories (GCBC) gives a broad critical examination of the evidence, so there's no need to go into depth here (I suspect Dr. Miller has not read GCBC - if I can catch up with her at the talk this Sunday, I'll offer her a copy). Start with saturated fat. Obviously it is generally thought that saturated fat is a causal factor in many diseases, from diabetes to cancer to heart disease. Dr. Miller cites Ancel Keys work as evidence for this, but the problems with Keys' studies are well documented in GCBC and in many other places. The biggest one, of course, is that epidemiological research such as the Seven Countries Study can only show statistical associations, not causation, and are susceptible to counfounding from the large number of uncontrolled variables. Other epidemiological studies (like Framingham) have shown the opposite of Keys' conclusions, and to my knowledge there are few (if any) controlled studies that illustrate any causal connection between saturated fat and disease. Stephan is starting a new series at Whole Health Blog on this topic, which I recommend.

Apart from experimental evidence, one would also like to have a plausible mechanism by which saturated fat causes disease. As I discussed here, despite a half-decade of research, nobody has any idea how it is that saturated fat leads to heart disease. "Experts" continue to pound on the health evils of saturated fat, despite evidence that is weak at best and generally contradictory. Dr. Miller calls out saturated fat as a pro-oxidant food "known to cause oxidative stress". Again, we see uncritical acceptance of the consensus. Saturated fats are LESS susceptible to oxidation than unsaturated fats, particularly polyunsaturated fats from vegetable oils, flax, etc. From simple chemistry, one expects polyunsaturates to induce substantially more oxidative stress (credit Dr. Miller with recommending limited vegetable oil intake, though I don't agree with her recommendations for taking flax oil). And of course the human body preferentially manufactures saturated fat from excess sugars, likely an evolutionary response. Were saturated fat to actually increase oxidative stress, one would have to hypothesize some mechanism by which the body preferentially oxidizes it, or by which saturated fat induces some other biological response that leads to oxidative stress. How or why an organism would evolve such responses escapes me, and I'm not aware that any have been experimentally or even theoretically identified.

Let's compare the utter lack of hypotheses tying saturated fat to heart disease with an alternative: athersclerosis is at least partially caused by excess sugar and polyunsaturated fat. Here's the rationale (discussed in several places on the web):

Fats are transported in the blood in lipoproteins.
Lipoproteins tend to embed themselves at places where arteries sustain damage, such as branches (veins, under considerable lower pressure, do not exhibit atherosclerosis).
Macrophages have specific receptors for LDL that has been damaged by oxidation or glycation, but no receptor for undamaged LDL. Oxidized/glycated LDL is consumed by the macrophages, which can lead to accumulation of "foam cells" forming the atherosclerotic plaque.
Consumption of polyunsaturated fat promotes oxidation of LDL. Lipoproteins consist of a large protein coat, interspersed with phospholipids (two fatty acids on a phosphate backbone). If the phospholipid contains a polyunsaturated fatty acid, it is more susceptible to oxidation.
Increased blood sugar, either via consumption of large amounts of refined carbohydrates or due to metabolic dysfunction (e.g. insulin resistance) increase the potential for glycation damage of LDL, where the sugar binds to the protein and alters its structure in a manner similar to oxidation.
So, PUFA + sugar = damaged LDL = inflammatory response = atherosclerosis.

Now, I'm not saying this is the answer, but it at least makes logical sense, follows currently accepted beliefs about chemistry and human biology, and I would guess explains the epidemiological evidence at least as well as the saturated fat hypothesis (which never was particularly clear to start with). It's certainly better than "we have no idea", as put forth in textbooks and by "experts". More research is needed to really nail things down, but I think we can see that the PUFA/sugar hypothesis, which has some basis in accepted science, should receive a greater weight than the saturated fat hypothesis, which has no basis whatsoever.

Another issue is dietary fiber. Dr. Miller is a big fan for the usual reasons: fiber makes you feel full, scrapes the inside of your colon, etc. The satiety argument requires a very narrow view of appetite regulation, as I discuss here and here. It is true that the mechanical distension of the stomach contributes to satiety, probably both via nervous system signals and suppression of ghrelin secretion. But those are two of many other nervous and hormonal signals indicating the macronutrient and energy content of food, energy availability in the body, etc. Fiber has no effect on these other aspects. That's to be expected - otherwise we'd be able to eat only highly fibrous food with little energy content, feel full, and wind up starving to death. Not a very good evolutionary strategy.

Dr. Miller discusses the origins of the fiber hypothesis, from Denis Burkitt's work in Africa. Taubes gives a more detailed history in GCBC. It is interesting to note that Burkitt's hypothesis originated from Peter Cleave's "saccharine-disease hypothesis", namely that refined carbohydrates were at the root of a host of modern diseases. Burkitt was initially impressed with Cleave's work, noting that Cleave possessed "perceptive genius, persuasive argument and irrefutable logic." But over time he modified the argument to accent the absence of fiber rather than the presence of refined carbohydrates. Now, there's nothing wrong with this hypothesis per se, but one must be aware that testing refined vs. unrefined carbohydrate in the diet does not distinguish between these hypotheses: unrefined carbohydrate has more fiber. And there is other evidence that absence of fiber is not the health issue it's made out to be. Says Taubes:

Burkitt and Trowell called their fiber hypothesis a "major modification" of Cleave's ideas, but the never actually addressed the reasons why Cleave had identified refined carbohydrates as the problem to begin with: How to explain the absence of these chronic diseases in cultures whose traditional diets contained predominantly fat and protein and little or no plant foods and thus little or no fiber - the Masai and the Samburu, the Native Americans of the Great Plains, the Inuit? And why did chronic diseases begin appearing in these populations only with the availability of Western diets, if they weren't eating copious fiber prior to this nutrition transition? Trowell did suggest, as Keys had, that the experience of these populations might be irrelevant to the rest of the world. "Special ethnic groups like the Eskimos," he wrote, "adapted many millenia ago to special diets, which in other groups, not adapted to these diets, might induce disease." Trowell spent three decades in Kenya and Uganda administering to the Masai and other nomadic tribes, Burkitt had spent two decades there, and yet that was extent of the discussion.

Sounds like Keys, Burkitt, and Trowell could all use the boot treatment I described above. Taubes' discussion highlights another related hypothesis, namely that red meat is bad, for which the argument at least partially stems from the fiber hypothesis. We can't distinguish between the unrefined carbohydrate and fiber hypotheses by exchanging refined for unrefined carbohydrates, but we can distinguish between red meat vs. fiber hypothesis by exchanging red meat for whole fruits, vegetables, and grains. Taubes addresses this as well:

By the end of the 1990s, clinical trials and large-scale prospective studies had demonstrated that the dietary fat and fiber hypotheses of cancer were almost assuredly wrong, and similar investigations had repeatedly failed to confirm that red meat played any role* (*Those clinical trials that tested the dietary-fat-and-fiber hypotheses of cancer, as we discussed earlier, replaced red meat in the experimental diets with fruits, vegetables, and whole grains. When these trials failed to confirm that fat causes breast cancer, or that fiber prevents colon cancer, they also failed to confirm the hypothesis that red-meat consumption plays a role in either.) Meanwhile, cancer researchers had failed to identify any diet-related carcinogens or mutagens that could account for any of the major cancers. But cancer epidemiologists made little attempt to derive alternative explanations for those 10 to 70 percent of diet-induced cancers, other than to suggest that overnutrition, physical inactivity, and obesity perhaps played a role.

Long story short: when scientists looked specifically for a causal link between fiber and cancer prevention or red meat and cancer causation, they found diddly-squat. Since these hypotheses were originally generated by weak epidemiological evidence, the contradictory evidence from more controlled trials weakens the hypotheses further. The refined carbohydrate hypothesis, on the other hand, provides considerable explanatory power and consistency with known biological properties of cancer, such as the necessity for cancer growth to be driven by insulin and a ready supply of glucose. The refined carb hypothesis also explains all of Dr. Miller's epidemiological observations. Given the above, it certainly seems more likely that, for instance, the absence of colon cancer in Cameroon has less to do with the presence of fiber than the absence of refined carbohydrates.

Finally, Dr. Miller appears to be significantly misinformed as to what is considered a "low carbohydrate diet". She generally uses the term "high protein diet", which underscores the root of the misunderstanding. The term "high protein diet" presumably indicates that it is low in both carbohydrates AND fat, which is problematic to health. One of my favorite books (which The Jungle Effect has inspired me to re-read) is Marvin Harris' Good to Eat. Harris notes that indigenous cultures never get the bulk of their calories from lean protein. Energy is invariably provided by fat and/or carbohydrate, with the amount of protein being remarkably constant across cultures. Dr. Miller correctly notes the underlying reason for this: protein is "dirty" fuel. Not being a pure hydrocarbon like sugar or fat, the conversion of protein to energy essentially results in pollution from nitrogen and other substances, which our kidneys then need to filter. A high-protein diet can overload the body's ability to dispose of these toxins, leading to sickness and ultimately death, even though plenty of food is provided. Dr. Miller relates experiences of some of her patients on high protein diets, that they basically felt unsatisfied and craved carbohydrates. This matches nicely with the phenomenon of rabbit starvation, where pioneers would feast on extremely lean rabbit meat, only to still be hungry. After some time they would eat 3 to 4 pounds of rabbit at a sitting, yet ultimately would waste away and essentially starve to death with full stomachs. It is no surprise that a high protein diet (as defined by restriction of both carbohydrate and fat) is doomed to failure.

But "low carbohydrate" does not necessarily imply "high protein". Indeed, had Dr. Miller read any of the large number of books on low carbohydrate diets, Googled the topic, or consulted with any number of experts, she would have found the recommendations are generally for high fat. This is at odds with the idea that fat is unhealthy, of course, so it may not be surprising that those adhering to current nutritional dogma would infer that any healthy diet must be low fat, so lowering carbohydrate leaves only raising protein. As discussed in the last post, our beliefs are always conditioned on other beliefs, and obviously placing undue weight on some supporting hypothesis leads to poor inferences. Even a moment's consideration of the Inuit diet, for example, would indicate the true nature of a healthy low carbohydrate diet.

Anyway, I could spend many more paragraphs discussing The Jungle Effect (I made a ton of notes while reading - something that the Kindle, for all its flaws, is good for). But I think you get the point. Hopefully Dr. Miller takes the time to read this review in the intended spirit, which is not to bash her work. I think some of what she espouses has value, and I love the idea of studying indigenous diets, provided it's done in an appropriately broad context. But the conclusions one draws from this study need to be consistent with the all of the actual relevant scientific evidence, not just the arbitrary socially-driven beliefs that form "consensus". Otherwise you risk coming to unjustifiable and/or inconsistent conclusions and sub-optimal recommendations, forcing the addition of ad hoc hypotheses, artificial dietary rules, etc. As I've said, changing lifestyles is hard enough without a lot of extra rules to follow. A healthy diet should be easy. Making it hard and motivated by inconsistent rationales just reduces the chances that people will actually make the change and improve their health.

Information, Knowledge, and Wisdom

2008-10-06T09:41:00.000-07:00

There are three kinds of lies: lies, damned lies, and statistics.
Benjamin Disraeli, British politician (1804 - 1881)

Statistics: The only science that enables different experts using the same figures to draw different conclusions.
Evan Esar, Esar's Comic Dictionary, American Humorist (1899 - 1995)

Where is the knowledge that is lost in information? Where is the wisdom that is lost in knowledge?
T.S.Eliot (1888 - 1965)

As discussed in the last post, we are today faced with a dizzying array of contradictory "recommendations" when it comes to health and lifestyle, particularly what to eat. How is it possible that all of these experts come to such differing conclusions? The quotes above illustrate certain root aspects of the problem. First, there is a gross misunderstanding of what "statistics" really is meant to accomplish, how it is properly applied, and what the answer "means". Second, and at least partly because of the first issue, the vast quantities of hard information ("facts" or "data") we have available tend to get filtered and twisted to erroneous conclusions, often supporting goals (e.g. "sell more books") other than maximizing the health of the population. Finally, despite the apparent rigor, technology, and expertise applied for answering key scientific questions, the process of actually turning scientific results into useful decisions is generally an exercise muddled thinking rather than rational inference.

The first two quotes embody general perceptions about "statistics". Those holding these views, by the way, include most professional scientists. When I worked as a research scientist in gamma-ray astrophysics, I can't tell you how many times colleagues would say things like "You can get any answer you want using statistics". Of course, they were quite happy to (supposedly) get the answers they wanted via application of statistical methods, but that irony isn't the point, because the incontrovertible truth is precisely opposite: there's only one right answer. Esar's quote embodies this attitude, so let's pick it apart. First, statistics is not a "science". Science involves the broader exercise of observing, modeling using mathematics, and interpreting observations in terms of those models. Statistics is just math, and as in any well-posed mathematical problem, there's only one right answer. I've thought of only three ways in which two scientists could come up with different answers to the same statistical problem:

Somebody made a math error (happens more often than you think, see Point 3).
They used different input information (in which case it's not really the same problem in both cases).
They used different approximate methods (often badly) to solve the problem.

You may remember learning statistics in school. Most people hate it, because by and large, it doesn't really make any sense. "Statistics" as it is usually thought of consists of a big cookbook, recipes for diddling around with "data" and turning them into some small set of numbers called "statistics", like mean and variance. But there's no core concepts tying the recipes together, just lots of rules like "if the data looks like this and you want to ask this question, then use such-and-such technique". What you may not remember (or even have been taught) is that "such-and-such technique" is usually not an exact mathematical result, but only a reasonable approximation when the "if" part of the rule is close to being true. This part is forgotten far too often by people who should know better. For instance, many statistical tests only become exact in the limit that the number of degrees-of-freedom (# of data points minus # of model parameters) goes to infinity. If such tests are to be good approximations, you need lots of degrees of freedom, but I've seen professional scientists in peer-reviewed publications blithely apply those tests only valid in the infinite limit to a model with three parameters, and data containing only five points. Last time I checked, "5-3=2", and "2" is not a particularly good approximation of "infinity".

But the problem runs even deeper, because even when scientists do the math right and apply the recipes under the appropriate conditions, more often than not they're still not answering the right question. Pure science attempts to answer questions like "does eating lollipops induce insulin resistance". Applied science wants to actually make decisions, e.g. "should I eat this lollipop, given what I know about it's effects on insulin resistance, the effects of insulin resistance on health?" etc. Almost always, the answers given in scientific papers are of the form "We compute a 95% probability that we would have observed these data if lollipops cause chronic insulin resistance". That's a much different statement than "We compute a 95% chance that lollipops chronically increase insulin resistance given the data we observe and other prior information," and only this latter statement is of any use on the applied end of things, when deciding whether or not to eat lollipops.

A very simple example might help to illustrate the issues. Suppose somebody wants you to gamble on a coin flip: you bet $1, and if the coin comes up heads, you win your dollar plus another $2. If the coin comes up tails, you lose your $1. How do you decide whether or not to play this game? Right from the start, we can see standard statistics is going to have trouble, because you have no data. Intuitively you might guess that there is a 50% chance of heads, and indeed if you had no other information at all, you would be right. With two possibilities, and no information to distinguish which would be more likely, you would assign equal probabilities to both outcomes. Our decision to play or not comes down to how much money we'd expect to have in each case. If we don't play, we have a guaranteed $1 in our pocket. If we do play, then with no other information there's a 50% chance we'll have $3, and a 50% chance we'll have zero, so $3*0.5 + $0*0.5 = $1.50. On average, we have $1.50 if we play and $1 if we don't, so we should play, given that we lack any other information about the game.

But what if our information were different? For example, suppose somebody we trust tells us that she knows the coin-flip guy is a scam artist, having been arrested several times. Now what do you do? Most people would now intuitively keep their money, and indeed a mathematical analysis would likely indicate that this is the proper course of action, as on average you would now expect to lose more often than not. But notice that the only thing that has changed is our knowledge about the game: the coin being flipped is the same, as is the person doing the flipping, and presumably the laws of physics governing coin flips. Purposely ignoring this new information would be fantastically stupid, particularly given that it came from a trusted source. Note that we still have no "data" in the traditional sense.

What if we had some data? Suppose the person we're playing against offers to let us flip the coin one hundred times before betting, and 99 out of 100 come up heads. Now you have some more information about the coin. Assuming that you're not doing something to introduce a bias, you have some additional confidence that the coin itself is biased towards heads, even more inducement to play the game, because the likelihood that you would have observed 99 heads out of 100 flips would be low for a fair coin. But that data and the associated likelihood are only part of the picture: do you now ignore the input of your trusted friend? Does your data trump the information they provided? Obviously it cannot. The aforementioned likelihood of seeing 99 of 100 flips come up heads was calculated with the a priori assumption that the game was fair. But your friend's input tells you that fairness is unlikely, and given your other information about scam artists, the likelihood that you saw 99 heads when you were flipping the coin and no money was at stake should be considerably higher. And the likelihood of 99 heads answers the wrong question anyway. Our decision to play or not must be based on the probability that the coin, when flipped by our opponent, will come up heads, not on the probability that you would have flipped 99 heads in 100 tries assuming the coin was fair.

The key point here is that information is information is information. The data gathered in a particular experiment is just more information which can be used to update our beliefs in different hypotheses. But most experiments don't start from zero, where the gathered data is the only available information. Usually others have conducted experiments that gathered other data. There's generally other relevant information as well. In the lollipop/insulin resistance example, we know that the glucose in the lollipop raises insulin, and that the fructose may at least temporarily contribute to insulin resistance. Any reasonable analysis must include this additional information when evaluating our belief in the hypothesis under test ("lollipops induce chronic insulin resistance"). Ignoring this information is no different than arbitrarily excluding data from our analysis (after all, data is just a kind of information); yet this is precisely how most scientific results are presented and interpreted.

Have a headache yet? I know, I know, this is some tough material. The whole area of reasoning under uncertainty is mathematically and philosophically deep. This is about the fourth time I've tried writing a reasonably accessible post, and have concluded that it's fundamentally hard to talk about. But if you're going to make good decisions about your health, it's good to have at least some idea where the flaws are in most scientific analyses, and also how to think about the issues in the "right way" so as not to be misled. So let's take a moment to review the key lessons you should take away at this point:

Though I didn't explicitly say it above, the notion of a probability really reflects the degree of belief in some statement (e.g. "the next coin flip will be heads"). Probabilities are real numbers between 0 and 1 (or 0% and 100%), where 0 represents absolute belief that the statement is false, and 1 absolute belief that it is true.
We don't necessarily need "data" to assess the probability that a statement is true, any type of information will do. There's nothing special about data, they're just more information to be used in updating degrees of belief (probabilities).
To properly assess the probability of a hypothesis, we must include not just the data, but also any other relevant background information.
If the outcome of a decision you're making depends on a hypothesis being true, then you need to know the probability of that hypothesis being true given all of the relevant available information. The probability that some particular data would have been observed assuming the hypothesis to be true necessarily ignores relevant information, precisely because it assumes the truth of the hypothesis without accounting for the possibility that the hypothesis is false. This is impossibly circular: you can't assess the degree of belief in a hypothesis if your analysis uniformly assumes it to be true.

Hopefully you can start to see why nutritional science and the associated recommendations are all over the place. In practice, scientists very often

Selectively ignore prior information;
Misapply statistical approximations to calculate the wrong number (probability of data assuming hypothesis is true);
Interpret their results as indicating absolute truth or falsehood;
Perform this interpretation via vague mental gymnastics rather than rigorous mathematics.

This situation is all the more vexing in the Information Age, where everyone basically has access to the same set of information. Thus all scientists can quickly call up published papers, experimental databases, etc. The input information is effectively the same for everybody, yet the output conclusions are nearly as numerous as scientists themselves. But looking at the four bullets above, we see ample opportunity to create divergent conclusions and recommendations with no hope of reconciling them. The last two are particularly troubling in the context of nutrition, because there's no hope of making decisions of what to eat when conflicting hypotheses are presented in terms of absolute truth/falsehood, with little visibility as to the actual mental manipulations that go into making that assessment. Lesson 4 above tells us that we need a probability of truth in order to make a decision, because we have to evaluate the expected outcome accounting for the possibility that the relevant hypothesis(es) may be false. Go back to the coin-flip game. Suppose we were forced to assert with absolute certainty whether the next flip would be heads. We get a different a different decision for "true" than for "false"; but we don't actually know what the outcome of the flip will be, and there can only be one right decision in terms of maximizing our expected winnings given our information about the uncertain outcome of the coin flip.

Now it may sound as if the picture is bleak for science, but rather amazingly, science seems to eventually bumble around to the correct conclusions. It's just a highly inefficient process because of the issues above. Scientists tend to hold on to certain "widely believed" hypotheses like grim death regardless of the actual evidential support; but eventually there comes a point when evidence for an alternative hypothesis becomes so overwhelming it becomes impossible to ignore (if you're paying attention, you can watch this process at work right now for low-carb diets). Science would benefit greatly, of course, by adopting a more rigorous analytical approach addressing the issues above. Such an approach exists, generally denoted "Bayesian Statistics". I don't like this term, since the methodology neither focuses on "statistics" per se (rather on probabilities), and it's namesake the Rev. Thomas Bayes really made only a tangential contribution to the whole business. "Probability Theory" is a more apt term, reflecting the idea that it extends the idea of logic to the case where we're not 100% sure of the truth/falsehood of statements.

At the end of the post, I'll briefly discuss Probability Theory further and give a few references for those who are interested in the technical details. But for those just trying to puzzle through the maze of information presented by the media, doctors, etc. we can borrow some of the ideas from Probability Theory, putting together a way of thinking about evidence (information), hypotheses (knowledge), and decisions (wisdom). The T. S. Eliot quote at the top describes the situation we wish to avoid, one that many people experience now, struggling to make wise choices when faced with an avalanche of information and knowledge from different sources.

So let's see how we can apply the four lessons above in everyday thinking.

Probabilities are just numbers representing degrees of belief. I'm not suggesting you carry a bunch of numbers around in your head to track your beliefs, but do recognize that most ideas are neither absolutely true nor absolutely false. We intuitively recognize that such absolutism is pathological, as seen by the often bizarre irrationality exhibited by dogmatists, who refuse to move from a position regardless of the weight of the evidence against that position. Probability Theory encapsulates that behavior mathematically. When new evidence is introduced, Probability Theory gives a formula for updating your beliefs (see math below), basically multiplying your current probability by the weight of that new evidence. But zero times anything is zero, i.e. if you were absolutely sure your current idea was right and all others were wrong, no amount of evidence would ever change your probability. So make sure you are always flexible in reassessing your beliefs. Mental discipline is required. The brain's natural tendency is to seek absolutes, as exhibited by the phenomenon of cognitive dissonance. Learn to be comfortable with uncertainty. Decisions can still be made in the absence of certainty; as Herdotus said, "A decision was wise, even though it led to disastrous consequences, if the evidence at hand indicated it was the best one to make; and a decision was foolish, even though it led to the happiest possible consequences, if it was unreasonable to expect those consequences."
Just because you're not a scientist (or even if you are) and don't have detailed access to scientific data, it does not mean you can't weigh evidence and update your beliefs. Information is information is information, whether its numbers or a brief newspaper story. The trick is in getting the weight in the right ballpark. A good rule of thumb: individual reports or results generally should not sway your belief very much. Strong belief is usually built on multiple independent results from different sources.
Be sure to include all of the information you have available. Another manifestation of cognitive dissonance: when presented with evidence contradicting a strong belief, we give it zero weight. That's a mistake. Contradictory evidence should lessen your belief at least a little, like it or not. Do include evidence from all sources, including anecdotal and personal experience. Just be careful not to overweight that evidence. Be aware that truth is usually conditional. Take the following hypothesis: "You can't become obese on a zero-carb diet." The truth of that hypothesis is conditional on other hypotheses, e.g. "Insulin is the hormone governing fat storage" and "Insulin is primarily driven by carbohydrate consumption". Changes in the belief of these supporting hypotheses necessarily changes the belief in the main hypothesis, for example knowledge of the ASP pathway for fat storage changes our belief that insulin runs the show, and hence modifies our belief that zero-carb diets make you immune to obesity.
We saw at the beginning that there are only three ways that scientists should disagree when assessing hypotheses. Adapting that to mental inference, disagreement implies that one or both people are irrational and/or have different information. Don't waste your time with arguing irrational people. Anybody who says things like "we'll have to agree to disagree" is irrational, because they have no information supporting their position and/or are unwilling to accept information that may modify their beliefs. But if you find yourself in disagreement with someone who seems rational, then engage in discussion to share the differing information that is at the root of your disagreement. You may not come to agreement - it's difficult to extract all relevant information and knowledge from somebody's head - but you at least will likely learn something new.
Decisions require not only the quantification of information as probabilities (or at least some qualitative mental equivalent), but also a clearly defined goal. The goal in our coin-flip game was straightforward: on average, maximize the amount of money in your pocket. It's not so easy to quantify the goal of maximizing health. People try, which is why doctors love to measure things like cholesterol and blood sugar, but such metrics can only provide a narrow view of one particular aspect of overall health (and even if they didn't, treatment decisions are generally not properly analyzed anyway). Treatment decisions often involve modification of one or a small set of such numbers, which is incredibly myopic as it ignores overall health (hence the spectacular failure of "intensive therapy" to lower blood sugar in Type II diabetics by pumping them full of insulin). Remember also to include the potential long-term effects of your decisions, e.g. cranking up the insulin of those Type II diabetics lowers blood-sugar in the short-term, but increases probability of early death, which presumably outweighs the short-term benefits.

The above is sort of a loose mental approximation to Probability Theory and Decision Theory. Those doing actual scientific research should be doing inference within the rigorous mathematical framework. I want to briefly discuss this, and I'll provide a few references as well. A full discussion of the subject would (and does) fill one or more large books; yet the conceptual basis is fairly simple, so I'll focus on that. The important thing to remember here is this: it's just math. There are a small number of concepts that we must accept axiomatically, and everything else follows mathematically. Arguments against the use of Probability Theory for scientific inference must necessarily focus on the fundamental concepts, because everything else is a mathematically rigorous result following from those concepts, listed below:

Degrees of belief (probabilities) are represented by real numbers.
Qualitative correspondence with common sense, e.g. if your belief in some background information increases (e.g. "Coin-flip guy is cheating") then so should your belief in a hypothesis conditioned on that information ("I will lose the coin flip when coin-flip guy does the flipping").
The procedure for assessing degrees of belief (probabilities) must be consistent, where consistency can be described in three ways:

If a conclusion can be reasoned out in more than one way, then all ways must lead to the same answer.
Conclusions must be reached using all of the available evidence.
Equivalent states of knowledge lead to the same probabilities based on that knowledge.

That's it. The whole of Probability Theory follows from these ideas, which seem to form a sensible and complete set of principles for scientific inference.

To make use of Probability Theory, we need some mathematical rules for manipulating the probabilities of different propositions. A little notation first: let A|C mean "A is true if C is true". AB|C means "A and B are true given C", while A+B|C means "A or B is true given C". Let ~A|C mean "A is false given C". If p(A|C) denotes the probability that A is true given C, then we have the following product and sum rules:

p(AB|C) = p(A|C) p(B|AC) = p(B|C) p(A|BC)
p(A + B|C) = p(A|C) + p(B|C) - p(AB|C)

From the product rule, it follows that absolute certainty of truth must be represented by the value 1, since 1 times 1 equals 1. Further, since A and ~A cannot be simultaneously true, we wind up with 0 representing absolute certainty of falsehood, e.g. if p(A|C) = 1, then p(~A|C) = 0. It can be proven that these rules are uniquely determined, assuming probabilities are represented by real numbers (Concept 1) and structural consistency (Concept 3.1).

That's most of Probability Theory, IMHO far more conceptually elegant and mathematically simple than the mess of statistics most of us were taught. That's not to say that actually solving problems is necessarily easy, but with a sound conceptual basis and simple rules, it's a lot easier to solve them consistently, get numbers that actually make sense, and combine different scientific results to understand their impact on various hypotheses.

This last point is important. We discussed earlier how new information ("data") must be used to update our beliefs. We shouldn't look at two different scientific results and try to pick between them. Rather our belief in a hypothesis derived from the first result must be adjusted when we get the second result. Try figuring out how to do this using standard statistics. The Probability Theory recipe for this follows trivially from the product rule. Let's rewrite the second equality in the product rule as follows:

p(H|DI) p(D|I) = p(D|HI) p(H|I)

where "H" represents a hypothesis being tested, "D" some observed data, and "I" our prior information (which might include results of other experiments, knowledge of chemistry, etc.) Each term represents a different proposition:

p(H|DI) : The probability that our hypothesis is true, given the observed data AND background information. This is called the posterior, and is the key quantity for scientific inference and decision-making.
p(D|I) : The probability that we would have observed the data given the background information independent of the hypothesis, called the evidence.
p(D|HI) : The probability that we would have observed the data given both the hypothesis AND the background information, called the likelihood.
p(H|I) : The probability that the hypothesis is true given only the background information, denoted the prior.

With a single algebraic step we can solve for the posterior, which is the quantity of interest:

p(H|DI) = p(D|HI) p(H|I) / p(D|I)

So we now have a very simple recipe for updating our beliefs given new data. I find it to be intuitively nice and tidy: to update your new belief from the old, multiply by the ratio of the likelihood (probability for measuring the data given the hypothesis and other information) to the evidence (probability that you would have seen the data in any case). If your hypothesis increases the probability of obtaining that dataset, then your belief in that hypothesis increases accordingly, and vice versa. If your hypothesis tells you nothing about the data, then the ratio is 1, and your belief does not change.

This formula goes by the name of Bayes' Theorem, so named for the Rev. Thomas Bayes who originally derived a form published in a posthumous paper in 1763. The version shown above was actually published by Laplace in 1774, so we see these ideas have been around for awhile. The power of Bayes' Theorem is hopefully clear: given some prior probability, i.e. our degree of belief in a hypothesis, we know how to update the probability when new data is observed, independent of how we arrived at our prior probability. So no matter what experiments I did (or even if no experiments have been done) to arrive at p(H|I), I can simply update that belief given my new data. Note that the term usually reported in scientific results is the likelihood, which is only part of the story.

If you've ever looked at a "meta-analysis", where somebody tries to combine results from many different experiments, you may have noted that it involves a lot of statistical pain, and often includes cutting out some results (e.g. favoring clinical over epidemiological studies), which violates the whole idea of using all available information. This sort of combination would be straightforward using Probability Theory, presuming all of the original results to be combined were also derived with Probability Theory. No reason to leave out some of the results due to "lack of control". A proper Probability Theory treatment would, for example, quantitatively account for the large number of "uncontrolled variables" (which really implies a lack of information connecting cause and effect) in a population study and adjust the probabilities accordingly.

Now, the few of you who have actually made it this far may be wondering why, if Probability Theory is so much better than standard statistics, is it not widely applied? As with many such situations in science, the answer is complicated, and at least partly tied up with human psychology and sociology. You can read about it more in the references, but I'll hit a few high points. It is interesting to note that Probability Theory was accepted and used prior to the mid-19th century or so. Laplace, for example, used it to estimate the mass of Saturn with considerable accuracy, so much so that an additional 150 years of data only improved the result by only 0.63%. Despite this, there were some technical problems. One is that the mathematical equations arising from application of Probability Theory can be difficult or impossible to solve via pencil and paper. This is largely alleviated by using computers to do the calculations, but 19th century scientists did not have that option.

There were also philosophical issues. Nineteenth-century thinkers were pushing toward the idea that there existed some some sort of objective scientific truth independent of human thought. The idea that probabilities represented degrees of belief was apparently too squishy and subjective, so they adopted the idea "let the data speak for themselves", and that probabilities reflected the relative frequencies of different measured outcomes in the limit of an infinite number of observations. So if you flip a fair coin infinitely many times, exactly half of the outcomes (50%) would be heads. At the core of the philosophical disagreement lay a couple of technical difficulties. First, there was no known reason to accept the sum and product rules as "right" within the context of Probability Theory (one could propose other rules), yet they arose naturally from the frequency interpretation (Cox later showed the rules could be uniquely determined assuming the basic concepts of Probability Theory). Second, Bayes' Theorem tells us how to update our beliefs given data. But if you "peel the onion" so to speak, going back to the point before any data had been collected, how do you assign the prior probability p(H|I)?

This proved to be a sticky problem. Special cases could be solved, e.g. it's clear that for the coin-flip problem with no other information that you should assign 50%/50%. But for more complicated problems where one had partial information, no general method existed for calculating a unique prior. It wasn't until the 1950's that physicist Edwin Jaynes successfully addressed this issue, borrowing ideas from information theory statistical physics. Jaynes introduced the idea of Maximum Entropy, which basically told you to assign probabilities such that they were consistent with the information you had, while adding no new information (information theory tells you how to measure information in terms of probabilities; entropy is just a measure of your lack of information). The underlying arguments are deep, stemming from the idea of Concept 3.3 that equivalent states of knowledge represent a symmetry, and that your probability assignments must reflect that symmetry. To do otherwise would be adding information without justification. But the horse was out of the barn at that point. The frequency approach had been used in practice for decades, and even in the 50's the computing technology required for practical widespread use of Probability Theory did not exist.

Today, of course, computers are cheap and ubiquitous, and indeed the use of Probability Theory is beginning to increase. But the progress is slow, and as is often the case, widespread change will require the next generation of scientists to really grab the idea and run with it while the current generation fades away.

Whew, that was quite the marathon post. I've hardly done the topic justice, but hopefully you at least got some ideas about what's wrong with how scientific inference is presently done, how you can avoid being confused by apparently conflicting results, and where the solution lies. Below are the promised references.

Probability Theory: The Logic of Science, E. T. Jaynes: The "bible" of Probability Theory. Jaynes was perhaps the central figure in the 20th century to advance Probability Theory as the mathematical framework reflecting the scientific method. This book is jam-packed with "well, duh" moments, followed by the realization that almost everyone in science reasons in ways which range from unduly complex and opaque to mathematically inconsistent. Not an easy book to read, full of some difficult math, but also plenty of conceptual exposition and very clear thinking about difficult topics. Jaynes does tend to rant a bit at times, but usually against determined stupidity. Required reading for all scientists, and anybody who needs to make critical decisions in the face of incomplete information.
Articles about probability theory: an online collection, including the works of Jaynes. You can download the first three chapters of "Probability Theory" in case you want a taste before plunking down 70 bucks. I particularly like this article detailing the historical development.
Data Analysis: A Bayesian Tutorial, D. Sivia and J. Skilling: A more pithy presentation aimed at practitioners. Clearly written without being too math-heavy, "Data Analysis" hits the high points and illustrates some key concepts with real-world applications. A good place to get your feet wet before tackling the intellectual Mt. Everest of Jaynes' book.

Think Bigger, Eat Simpler

2008-09-29T08:15:00.000-07:00

Hi everybody. Sorry to have dropped off the blogosphere, been busy with the day job. I'm going to steal a few minutes from writing software to share a few thoughts.

I've been increasingly frustrated with the narrow thinking and shoddy logic which goes into "dietary recommendations", because it seems to me that the situation is really pretty simple. Everybody and their sister is getting into this game, with the drive towards very specific "eat 12% of this" sort of thinking, usually accompanied by some sort of pseudo-logical justification. Example: Jimmy Moore had a great interview (Part 1, Part 2) with Dr. Stephen Gundry, author of yet another diet book. In the interview, Gundry claims we should eat 95% plants. Why? Because that's what gorillas eat. Gorillas are genetically similar to humans, and maintain massive size and very low body-fat. That argument ignores the important differences between gorillas and humans, not the least of those being gorillas' vastly larger digestive tract and jaws with associated musculature, both required for effective digestion of large quantities of plant matter (gorillas eat upwards of 30 lbs. of vegetation daily). Indeed, by Dr. Gundry's logic of genetic similarity, we should eat like chimpanzees, genetically closer to us than gorillas, and whose diet is mostly fruit. Maybe Dr. Gundry doesn't like fruit, or chimps aren't muscley enough for him.

Another example, also courtesy of Jimmy Moore: Dr. Richard Johnson, author of another of the plethora of diet and nutrition books, claims that it's really fructose that is the root cause of our current rash of metabolic diseases. I think the metabolic science certainly indicates that overconsumption of fructose has significant potential for negatively impacting health. But in his explanation to Jimmy, Dr. Johnson focuses on animal studies rather than the underlying metabolic processes. Animal studies as such can never be more than suggestive about the corresponding effects in humans. Worse, Johnson seems to think that his fructose hypothesis excludes all other hypotheses as to the origin of obesity and other metabolically-related diseases, specifically targeting Taubes' hypothesis from Good Calories, Bad Calories. That's shaky ground, as Taubes builds on broadly accepted fundamentals of biochemistry and cellular biology, while Johnson largely seems to be making inferences from mouse studies. But the thing that annoys me the most is that the two hypotheses are clearly not mutually exclusive; indeed, one might expect the two effects to be synergistic in driving the development of metabolic syndrome, an effect certainly reflected in the decreasing average age of the onset of Type II diabetes.

At the top of the whole mess is the government's food pyramid. I don't have the time to get into it here, but if you want a real laugher some time, you should read the scientific justification for the food pyramid. And for the life of me I can't understand why our society takes that as the standard for nutrition. Anybody who's even semi-conscious can look around right now and see how skilled our government is in screwing things up just as badly as possible. Why would their nutritional recommendations be any different? Jimmy Moore recently pointed to a bit in the New York Times showing how diet has changed since 1970. You'll note that the major changes involve food pyramid-ish recommendations, like eating more veggies, grains, and vegetable oils. Yet public health is swirling down the toilet, but maybe that's to be expected given the usual governmental competency.

I would assert that there is no single "expert opinion" that constitutes the final word on human nutrition. Most of these experts are trying to sell books, videos, food, etc. and to do so must necessarily distinguish themselves from all of the other "experts". By the way, this extends to the government as well, as you'll find that appointees to head departments like the USDA generally come from the food industry. As a society, we've fallen into the trap of uncritical reliance on "experts" to tell us how to live our lives, rather than using our own brains to figure some fairly obvious things for ourselves. I can tell you from first-hand experience that, on average, most scientists are no smarter than you, regardless of your education or profession. More than anything, scientists know a lot of big words and few actual concepts, and spend most of their careers blindly misapplying them.

In the excellent book The Omnivore's Dilemma, Michal Pollan points out that omnivores devote a significant amount of brain-power to figuring out what is edible. That's an obvious necessity when you can eat just about anything. Humans and their big brains represent the extreme endpoint of this pattern. Two million years of human evolution have pushed brain development with the primary goal of becoming more effective at hunting and gathering food, allowing us to populate an extraordinary variety of ecological niches around the planet. Only over the last several thousand years, and mostly the last 100 or so, have we sacrificed evolution's gift in favor of "experts": doctors, scientists, media, government, etc. If you want to eat healthy, you need to use that big brain and figure out what works for you.

I don't want to offer yet another "expert" opinion on this topic, but to get the thinking started, let me throw out a few broad ideas. None of these are particularly original, but I think we need to "think bigger and eat simpler". A lot of the confusion around dietary recommendations stems, I believe, from the "experts" taking a narrow view, often a single idea (e.g. "animal products are bad", "all carbs are bad"). They also need to make the money you spend on their book seem worthwhile. Combine this with the narrow viewpoint, and you can wind up with "diet plans" that are complicated and difficult to follow. More often than not it also seems like the food sucks. Healthy eating should be easy - after all, we did it for hundreds of thousands of years with no experts or books. Major lifestyle changes are hard enough without having to do a bunch of math and suffering through unsatisfying meals.

First and foremost, realize what humans must have eaten during the course of evolving that big brain. We didn't have agriculture, nor factories to tear apart and reconstitute our food into unrecognizable forms. We ate more or less whole foods of both plant and animal origin. Debates about how much of this or that type of food are probably irrelevant, and both the archaeological record and modern hunter-gatherers indicate humans can thrive over considerable dietary variety. Ultimately humans require energy (preferably from fats or carbohydrates), protein, and a variety of micronutrients (vitamins and minerals). Whatever combination gets that for you is probably workable, as witnessed by the wide dietary variety of remaining hunter-gatherers who exhibit excellent health. The Inuit eat almost all animal products and get most of their energy from fat, while the Kitavans eat a large proportion of starchy vegetables, supplemented by seafood. Both groups exhibit comparable health, and little evidence of diabetes, heart disease, cancer, etc.

The key, I think, is the emphasis on whole foods, or at least foods that have a recognizable natural source, since that is what has been on the menu for all of human existence prior to the advent of agriculture. With very little extra thought, we can narrow that group down further by considering what could be reasonably hunted (just about anything that moves) or gathered. Consider grains, for example. Try this experiment some time: find a nice field full of wild grass that has gone to seed. Now go and gather up enough seeds to provide significant calories, say about a kilogram. Then process that grain into an edible form, using only naturally available tools like rocks (and if you actually do all of this, please don't eat the grains, because if you don't prepare them right you'll wind up in the hospital). Now compare that level of effort to digging up some root vegetables, picking fruit, or taking one of your grinding rocks and bonking a deer on the head. I think everyone who spouts off about "healthy whole grains" should be forced to do this exercise.

It doesn't necessarily follow that foods outside of human evolutionary experience are bad; but it seems highly unlikely that any food types we've eaten for the last two million years or so are likely to have much negative impact on health. Processed foods don't have to be bad for you, but what's the point of eating them? We don't have to eat processed food to get our nutrients, and more often than not the processing destroys much of the nutritional content, while potentially exposing us to nutrients in forms and quantities we are not designed to handle (e.g. high-fructose corn syrup, refined starch, high concentrations of polyunsaturated fats, lectins from grains). In fact, if there's one thing I think just about all diet gurus would agree upon, it's that we should be trading in more refined foods in favor of whole foods (just remember that despite the marketing phrase "whole grain foods", whole grain foods are nearly all highly refined).

Do some research on the actual nutritional content of foods, and apply a little critical thinking. When you compare with the usual (and usually dogmatic) recommendations, you are going to find lots of surprises. For instance, NutritionData.com cites spinach as being "a very good source of calcium", yet you'd have to eat about two pounds of spinach to get 100% of the RDA of calcium (and of course the RDA levels were designed to avoid overt disease, not optimize health). I'm not saying you shouldn't eat spinach, but rather be aware of what you're actually getting for realistic intake as opposed to trusting vague characterizations like "a very good source". An interesting and surprising exercise is to use NutritionData.com (or your favorite nutrition database) to find whole foods highest in various nutrients. I did this, comparing 200 calorie servings across all of the tracked nutrients; you can view the results here.

Another use for your big omnivore brain is paying attention to your body's response to different foods. As omnivores, such feedback is important. Throughout our evolutionary history our menu choices have often been very broad (much broader even than in the supposed "plenty" of modern life, where the apparent variety is really just different manipulations of corn, soy, and wheat). Maintaining optimal health would have required the ability to make distinctions between food sources in terms of nutrient density and availability without the use of a laboratory. For example, try filling your stomach with raw leaves (like spinach). I think you'll find that while your stomach feels full temporarily, you won't feel "satisfied", and will be hungry again soon (1 kg of raw spinach has only 230 kcal). If you finish a meal and are soon after thinking about the next meal, you're probably missing something. A good meal should make you feel good, not only right after, but also for most of the time until your next meal. For example, meals high in refined carbohydrates give most people a temporary "rush", but soon after result in a "crash". Don't try to overcome the crash with another rush.

Hunger is healthy, but you should only experience intense hunger if you're actually running a serious caloric deficit. If you're starving two hours after a 1000 kcal meal, something is screwed up, since that 1000 kcal should easily last you eight hours, assuming moderate levels of activity. Cravings are not necessarily a bad thing, but you should consider them in the context of two million years of human evolution. If you're craving something sweet, consider that it may be because your body is looking for the nutrients found in fruit. If you're craving something fatty, ignore the gurus' admonitions against fat, and just eat it. Again, your craving may not be so much for fat specifically, for for the nutrients that often accompany fat in whole foods. Satisfy your fat craving with a whole nutrient-dense source (e.g. avocado, grass-fed butter, coconut milk smoothie).

Keep it simple. No other animal has the capability to count calories or exercise "willpower", and humans had no need for such until the last century. Your body will tell you what it needs. You just need to listen, and use that big brain to filter the available options down to something that is reasonably likely to fulfill those needs as opposed to refined junk that temporarily tricks your body into thinking it's requirements have been met.

Finally, find yourself a person of advanced age who's still going strong. Modern life has pretty much destroyed the social cohesiveness humans experienced over our two million years of evolution, where those who successfully made it to old age could pass along their wisdom of how they got there. You will probably learn more of value from that individual than from a room full of diet book authors. Be sure to be open to what they tell you. For instance, more than once I've heard centenarians credit their health to a daily breakfast of bacon and eggs. Don't discount this as genetics or luck just because the bozo nutritionist at your gym said those things are unhealthy. The centenarian has spent 100 years listening to their body, while the nutritionist is just blindly repeating something from a book.

And though I'm sure one exists, I have yet to hear anyone credit a daily bagel and skim milk for reaching the century mark.

Energy Conservation: It's Not Just a Good Idea, It's the Law

2008-07-22T09:56:00.000-07:00

Michael Eades latest blog points us to a review of Gary Taubes' Good Calories, Bad Calories by Dr. George Bray. Gary Taubes was given the opportunity to respond, and as usual, pretty much brings the wood, from the standpoint of logical clarity and consistency. I haven't read Bray's review in detail, but skimming over it I have to wonder how carefully he read the book. Indeed, he seems to essentially agree with Taubes that fat storage is driven by hormonal factors as part of overall metabolic regulation, and gives some examples where obesity results from failures in these regulatory mechanisms (which we'll also explore in subsequent posts in the Energy Regulation series). Despite this apparent agreement, Bray spends about 13 pages simultaneously trying to disagree with Taubes. Smells like cognitive dissonance, at least from my cursory reading. Taubes reply does a nice job at cutting through the fog.

Bray (like many others) seems to interpret Taubes work as somehow implying a violation or misunderstanding of the First Law of Thermodynamics, which is sort of humorous considering Taubes has a degree in physics from Harvard. Physics students pretty much get these sort of fundamental laws beaten into them from day one. In addition to Bray's review, there was a lot of noise about the First Law of Thermodynamics in response to the recently reported study about low-carbohydrate vs. low-fat diets. Being a physicist, I find misapplication of the First Law thoroughly annoying, so let's dig into this topic a bit and hopefully raise the level of understanding.

Use of the term "First Law of Thermodynamics" is a bit of historical accident. Bray actually uses the term I prefer, "Law of Conservation of Mass and Energy". Actually, "Mass" is redundant, since mass is just another word for energy, so let's shorten that to the "Law of the Conservation of Energy". The statement of energy conservation is simple: in a closed system, the total quantity of energy does not change. Energy may change "forms", e.g. the stored electrical chemical energy of battery can be converted to a light. But the total amount remains unchanged. The field of thermodynamics was largely developed in the 19th century, before we knew about atoms and such. We now understand that energy conservation in "thermodynamic systems" (consisting of very large numbers of atoms) simply follows from the more general law of energy conservation for all physical systems.

Why is energy conservation a "law"? There are many "conservation laws" in physics, and they all arise because of symmetries. Mathematically, physicists model the world via equations of motion, which basically tell how the state of the system under study changes as a function of changes in time and space coordinates. A "coordinate" is just a numerical label for a point in space (or spacetime). Suppose we're doing an experiment inside of a cubical box, 1 meter on each side. We might pick a point in the box, say the bottom left front corner, to be the "origin", labeled as (0,0,0). The top right back corner is then (1, 1, 1) in meters.

But this choice is arbitrary. I could just as easily pick any other point as the origin, say the front left corner of the parking lot, and update all of my other coordinate values accordingly. This is called a "transformation". Similarly, I could move my experiment box from it's original location. In neither case would I expect the experiment to have a different outcome. That's a symmetry: I changed one thing (coordinate origin, location of box), but it did not change the physics occurring inside the box. In this case, we would say the laws of physics are symmetric with respect to position.

A given symmetry in the equations of motion implies that some physical quantity is conserved, i.e. cannot change in a closed system. Symmetry with respect to position implies the conservation of linear momentum. Suppose I turn the box and observe the same outcome. This rotational symmetry implies conservation of angular momentum. Now let's do the experiment today, come back tomorrow, and repeat. If we get the same result, we have a time translation symmetry, which implies the conservation of energy. So basically, the "Law of Energy Conservation" arises from the observed fact that all of the fundamental equations of motion in physics are invariant under time shifts. It doesn't matter whether you look now or later, the laws governing how systems evolve in space and time are unchanged. Note that this is not the same as saying that the state of the system doesn't change, just that the laws which predict how the system goes from one state to another are not affected by the passage of time (this doesn't have to be true, it is just observed to be so in all cases so far).

Now, the above discussion is a bit watered down. The mathematically rigorous version is "Noether's Theorem", and involves differential calculus and continuous transformations. One of the best physics books I've read is Lagrangian Interaction, by Noel Doughty. Very technical, but a highly illuminating read on the power of symmetry in understanding the universe. There are many other fascinating and powerful applications of symmetry as well, one of my favorites being in Probability Theory. But we'll visit that another time.

So, to review: The First Law of Thermodynamics is just another statement of the more general Law of Energy Conservation. Energy conservation in a closed system arises because the laws of physics do not change with time. If you were to ever observe an apparent violation of energy conservation, it must be either that you are not observing a closed system (haven't taken everything into account), or you've discovered new laws of physics. The former is far more likely than the latter. For example, suppose you put some water in a cup, stuck in a thermometer, and put the whole she-bang into the freezer. The temperature would drop as time passed, indicating that the average energy of the water is decreasing. But this does not imply violation of energy conservation. Were you to also measure the net heat output from the freezer, you'd find the missing energy.

Back to our original story. Bray makes the point "Over the period of about 100 years from 1787 to 1896, the Laws of Conservation of Matter and Energy were shown to apply to human beings, just as they do to animals." That's a no-brainer given what we've learned above, since humans and animals are physical systems, ultimately governed by the same physical laws as the subatomic particles which comprise these systems. They didn't know about atoms and Noether's Theorem in the 19th century, so the explicit study of energy conservation in living organisms is understandable. But now it's not even a point of discussion, so I don't know why Bray (and so many others) keep lecturing about it. As far as anyone can tell, energy conservation is built-in to the fabric of the universe. The core issue isn't violation of this law, it's whether your metabolic theory or experiment has done a complete accounting of all energy inputs and outputs.

Energy enters the body in the form of food. In healthy people, the only way it can leave the body is through physical exertion or heat. Energy may be used in the body to fuel other biological processes ("base metabolic rate"), or it can be stored in various chemical forms. Misinterpretations seem to arise because there is an assumption that base metabolic rate and heat output are independent of caloric intake, and further independent of macronutrient composition. If you assume that intake is independent of storage and output, you can draw some strange conclusions. The body has ways of regulating total input, storage, and output in an attempt to maintain energy balance in a healthy range. As such, the output side must be related to the input side, otherwise energy regulation would be doomed to failure.

Consider a simpler example: drinking water. When we're thirsty, we drink water. The signal for thirst is generated in the brain as a function of the detected water content in the body. Too low, you get thirsty. But when you drink some water, it takes time for the water to get absorbed into the blood and signal the brain. So we tend to drink more water than we actually need; that's probably also a good evolutionary strategy, sort of "better safe than sorry". The body then has mechanisms to get rid of the excess, mostly as urine. The amount of urine we produce is clearly correlated to the amount of water we drink. If water output were independent of water input, we'd be in constant danger of either dehydration or water poisoning, depending on availability of water. Like food in Western society (and increasingly elsewhere), water is abundantly available, yet people aren't dropping dead from over-hydration because the input, usage, and output are regulated by the body. Why should we expect any different for energy regulation?

Like I said earlier, if it appears that energy conservation is violated in an experiment, such as the recent low-carb vs. low-fat diet study, the most likely explanation is that the experimenters did not measure all of the energy output. They did estimate physical activity, but it's more difficult to measure heat output. Similarly, Taubes is not saying "calories don't count", but rather that you must consider all methods of energy output when discussing energy balance. Further, you must consider the physiological mechanisms that control energy input, storage, and output, because that tells you relationships amongst them. When you do this, you find not only that output correlated with input, but also that the macronutrient composition potentially affects input, storage, and output as well. Macronutrients not only affect energy balance but other physiologically important quantities. Blood sugar, for example, is tightly regulated. If it goes too high or too low, the body has problems. So we would expect a different biological response if we eat the same calories as sugar or as fat, and of course this is exactly what is observed. It should not be surprising that high-carbohydrate or high-fat diets have very different effects on metabolism. Violation of energy conservation is not required to explain the results, just that the system has different responses to different inputs, and that the caloric content of food is only one aspect that is detected and monitored by the body.

Bray actually seems to agree with this point: "The concept of energy imbalance as the basis for understanding obesity at one level does not preclude any of the influences that affect or modify food intake or energy expenditure, including the quantity and quality of food, toxins, genes, viruses, sleeping time, breast feeding, medications, etc. They are just the processes that modify
one or other component of the energy-balance system." I think the fundamental disagreement may be whether fat storage depends sensitively on the precise balance between energy intake and output, i.e. that storage is driven by eating even a little too much. But that implies a pronounced lack of robustness in the regulatory system, one which is not observed, any more than it is in regulating water balance.

Anyway, the next time someone tells you that low-carb diets can't work because they violate the First Law of Thermodynamics, you can reply with "Low-carbohydrate diets exhibit continuous symmetry under time translation transformations, hence do not violate conservation of energy." That ought to shut 'em up.

Even More Dissonance

2008-07-17T08:02:00.000-07:00

A recently published study comparing various weight-loss approaches has been getting a lot of press and Internet buzz, probably because the results contradict mainstream thinking about diet and health. It's pleasantly surprising that this is getting some media coverage - usually such dissonance-inducing results are largely ignored. Regina Wilshire posted an especially amusing blog, showing how different people interpret these results. You can taste the cognitive dissonance, as each individual spins the results according to their own beliefs.

The essence of the study results is that those following a low-carbohydrate diet had greater weight-loss and improvements in blood lipids. The Mediterranean diet did well also. Both of these results are predictable from what we know about metabolic regulation, but for the mainstream, this result clearly induces significant dissonance. I particularly enjoyed Dean Ornish's attempt at reconciling this dissonance. Here's a choice quote:

I'm also very skeptical of the quality of data in this study. For example, the investigators reported that those on the "low-fat" diet consumed 200 fewer calories per day—or 10,000 fewer calories per year—than those on the Mediterranean diet, yet people lost more weight on the Mediterranean diet. That's physiologically impossible.

I think Dr. Ornish needs to bone up on his biochem. We'll hit this point later in the series on Energy Regulation, but the body very definitely has a mechanism to dump excess fat calories in the form of heat. And of course Ornish's calorie-centric focus completely ignores other regulatory effects, such as insulin's effect on fat storage. Ornish does spend plenty of time telling you all about himself, what he believes, why his particular diet flavor is superior, etc. The article reads more like an infomercial than scientific exposition. Comparison of different scientific hypotheses requires inclusion of ALL relevant evidence. Ornish heavily weighs evidence of his own creation, which (not surprisingly) supports his own preconceived notions. If you selectively weigh evidence in this way, you can come to any conclusion you want.

Here's another fun quote from Ornish: "Most people associate an Atkins diet with bacon, butter and brie, not a plant-based diet like the one I recommend." There's that "I" again. Shouldn't the diet be recommended by the evidence, not one individual? I guess Dr. Ornish is smarter than the rest of us. Maybe he would grace us with a more detailed explanation of why he's "right" given our knowledge of metabolic regulation at the molecular and cellular level?

I'm not holding my breath.

Ornish's comment also highlights one of the major origins of dissonance surrounding these recent results: the seemingly unshakable belief that saturated fat ("bacon, butter, and brie") plays a role in a wide range of disease processes. We saw in the original post on cognitive dissonance that there actually exists essentially no evidence of causality (I just confirmed this with an ex-official of the American Heart Association). For example, there may be some statistical association between saturated fat consumption and development of heart disease (particularly if you limit the observational data set), but there's no evidence at all of causality at the molecular and cellular level. Let's look at a some ways in which this association might arise:

Fast food is often high in saturated fat. It's also often high in total refined carbohydrates, particularly fructose. The damage wrought by increase carbohydrates (fructose is particularly good at this) and the hormonal derangement from repeated insulin spikes (and probably fructose as well) quite logically predicts an increase in heart disease. The likely high consumption of oxidized fats from deep-fried foods is the cherry on top of this sundae. Lipoprotein molecules are composed of a water soluble membrane including both proteins and fatty acids. White blood cells have a specific receptor for oxidized LDL (but not unoxidized LDL), so if your LDL includes some oxidized fat from your French fries, you should expect an increased immune response, which is known to be important in the development of atherosclerosis. So if a population has a high consumption of fast food, not only is their saturated fat consumption higher, so is the consumption of refined carbohydrates and oxidized fats. Which of these actually causes the observed increase in heart disease?
Grain-fed beef is known to have some nutritional issues. Grains are not the natural food of cattle, who prefer to eat leafy material, which tends to be rich in the omega-3 alpha-linolenic acid. When compared with grass-fed beef, grain-fed has a significantly higher ratio of omega-6/omega-3 fatty acids. There is a biochemical reason to believe this could increase heart disease, due to the pro-inflammatory effect of omega-6 fats. Grain-fed beef is also much higher in saturated fat, so there would be an association between saturated fat intake and increased omega-6/omega-3 ratio.
Grain-fed beef is also higher in total fat. Guess what - carbohydrates make cows fat too! But this fat is essentially "empty calories" in that the increased fat intake does not bring significant additional micronutrients, probably displacing calories from foods that are nutrient dense. Again, at the molecular/cellular level, there are good reasons to believe these micronutrients (like magnesium) are protective against the development of heart disease.
Eating a crappy diet like fast food makes people sick. Sick people tend to stay inside. If you don't go outside, in all likelihood you are deficient in Vitamin D. Vitamin D deficiency is implicated in a whole host of diseases, including heart disease. I'll bet saturated fat consumption is correlated with Vitamin D deficiency as well.

I'm sure with a little thought we could come up with several more. The point is this: associating causality with an individual statistical correlation is a very slippery slope. If you have no evidence for causality, making such an association implies that you are ignoring other possible causes WITHOUT EVIDENCE. Attempting to treat sick people based on this association could be expected to be ineffective at best, harmful at worst. And of course you wind up with the precise situation we observe today, which is that some bogus dogmatic belief blocks the advancement of science due to cognitive dissonance.

Energy Regulation 2: Appetite

2008-07-13T06:34:00.000-07:00

In Energy Regulation 1, I asserted that the body had many regulation mechanisms for energy intake, storage, and utilization. This regulatory network presumably evolved to maintain health over a wide range of conditions: different seasonally available foods, physical requirements, hot and cold temperatures, etc. Let's start digging in to the details of what is known, which will then should inspire some ideas on what aspects of modern life could potentially knock things askew, resulting in a situation where the body actually defends an unhealthy state like obesity.

A few caveats first. Metabolic regulation is a complex and evolving subject, and much of the knowledge is very recent (if you want to give yourself a headache, check out this spreadsheet I made trying to illustrate the various parts and their relationships). Even if you were to consider all of the available science I doubt the picture is anywhere near complete, and of course I've probably only been exposed to some smallish subset of what is known. If anybody out there finds gaps in this presentation, please fill them in via the comments. Additionally, much of the research on metabolic regulation is done on animals and extrapolated to humans. Nobody is going to do experiments where, say, they directly infuse oleic acid into the brains of people. Some of the published reviews are unfortunately vague as to whether the mechanisms discussed have been studied in humans.

One final issue is that the reviews are very focused on dietary fat, and to a lesser extent carbohydrates. But protein is essential for life, so there must be appetite and metabolic controls regulating protein intake, but this is largely not discussed. For instance, I'm guessing somewhere in the body there's something that detects amino acids and influences appetite, particularly preference for protein-rich food.

With that in mind, we'll start at the beginning. Animals eat when they're hungry. In a healthy organism, hunger is a signal that available and/or stored energy is getting low and need to be replenished. Humans have three primary energy stores: the stomach, glycogen (starch) in muscle and liver tissue, and fat (triglycerides) in adipose tissue. Now, if this system is working right, low available energy should be equivalent to low stored energy. But we're going to see it's quite plausible that conditions can arise where the body thinks available energy is low, yet excess energy is in storage.

The brain acts as a central controller, receiving various signals from the body and adjusting many different "knobs" to maintain a healthy state. Peripheral tissues also exercise some independent controls as well, e.g. the pancreas will secrete insulin in response to rising blood glucose without nervous system control. This combination of central and peripheral controls provides for both robustness and responsiveness.

The major nervous system player in metabolic regulation is the hypothalamus, an area at the base of the brain, roughly the size of an almond. The hypothalamus is the main connection between the rest of the brain and the various hormone systems of the body, sharing a private circulatory system with the pituitary gland, and projecting nerve connections to various other endocrine organs as well. The hypothalamus is also well situated to sample various chemical concentrations in the blood. Most of the brain is protected by the "blood-brain barrier" (BBB), closely-packed cells which tightly control what substances pass from the blood to the brain. But the hypothalamus is located near a region where the BBB is incomplete. It's leaky, in a sense, so the hypothalamus gets a taste of much of what's in the blood. The hypothalamus can be further divided into "nuclei", which have different sensory and control functions. Of particular interest here are the arcuate nucleus (ARC), the ventromedial nucleus (VMN), and the dorsomedial hypothalamus (DMH).

The brainstem is a close neighbor of the hypothalamus, sharing lots of neural connections. The particular region called the nucleus of the solitary tract (NTS) is the termination of the afferent fibers of the vagus nerve (afferent nerves cause signals to arrive at the brain; efferent nerves allow signals to exit the brain). The vagus nerve connects to many different organs, including those of the digestive system. The NTS appears to integrate different signals (both hormonal and nervous) and send them along to the hypothalamus. The hypothalamus does some additional integration, and projects to other brain areas involved in behaviors like finding food and eating it.

I've used the term "integrate" a couple of times. What does that mean? The neurons in the brainstem and hypothalamus receive many different signals: from other nerves, from hormones like insulin, and can directly sense nutrients like glucose. The "decision" of whether the neuron fires or expresses certain proteins must factor in all of these signals. For example, the brain requires a certain blood glucose concentration to function properly. If glucose falls, regardless of the level of insulin, the brain should take some action (like stimulating appetite), because otherwise you'll die.

The ARC in particular contains two populations of special neurons. One of these expresses cocaine- and amphetamine-related transcript (CART) along with pro-opiomelanocortin (POMC). These neurons seem to be associated with appetite suppression. For instance, POMC can be chopped up to yield alpha-melanocyte-stimulating hormone (alpha-MSH), which in turn binds to the melanocortin-4 (MC-4) receptor. Genetic problems causing defects in the MC-4 receptor result in obesity characterized by overeating. The other population expresses agouti-related protein (AgRP) and neuropeptide-Y (NPY), both of which increase appetite. If NPY is infused into rat brains, they respond with a several-fold increase in food intake that lasts 6-8 hours, similar to rats that have been fasted for 36-48 hours.

Having two opposing systems (as opposed to just one that gets turned up or down) allows for rapid fine-tuning of metabolism; this idea of opposing systems which maintain balance is found elsewhere, e.g. the sympathetic and parasympathetic endocrine systems. Both classes of neurons appear to "detect" both available energy in the blood as well as hormonal levels and probably nerve signals, with opposing results. Energy nutrients go through part of the same cycle used to actually generate energy, and the resultant metabolic products appear to trigger opening/closing of ion channels on the cell membrane. Hormones like leptin and insulin have similar effects, hence the "integration" of these signals. Changing the balance of ions inside and outside the neuron affect the "action potential", make it more or less susceptible to firing, expressing proteins, etc.

NPY neurons, for example, are glucose inhibited (GI), meaning the more glucose is around, the less active they beome. If blood sugar falls, the NPY neurons become more active, and as we saw above, NPY appears to strongly stimulate appetite. So blood sugar falls, and you get hungry. Similarly if insulin or leptin falls, these neurons are activated, and again you get hungry. But what if insulin is high AND glucose is low? Well, the brain needs a certain glucose level to operate, so I would guess that the low glucose wins, because the alternative is a hypoglycemic coma and death. Have you ever had a major blood-sugar crash a few hours after a large carbohydrate-laden meal? It's the "Chinese food makes you hungry an hour later" thing (see e.g. Teriyaki Stix Beef Bowl: 102g of carbohydrate, probably all highly refined). I would bet the extreme feelings of hunger (kind of like you were starved for 36-48 hours) is the result of increasing NPY concentrations in the hypothalamus, in turn triggered by low blood glucose, even though your insulin is still elevated. Rats show a preference for high-carbohydrate meals when stimulated with NPY. If the same is true for humans, then we shouldn't be surprised that a blood-sugar crash sends us scurrying for the vending machine to fearlessly slay and consume a candy bar, regardless of how much energy is stored in the stomach or fat. So we begin to see how the system can be broken to store excess energy, mainly fat.

The scenarios described above relate more to the instantaneous availability of energy in the blood as opposed to the amount stored. The major energy store (in terms of calories) is white adipose tissue (WAT). Fat cells, or adipocytes, are not passive buckets, but rather metabolically active both in the storage/release of fatty acids as well as the secretion of hormonal signals relating to appetite and metabolic regulation. The best-known of these is leptin, a hormone whose secretion is proportional to the amount of stored fat. Leptin suppresses appetite, probably via multiple actions. Leptin inhibits the NPY/AgRP neurons (which stimulate appetite) and excites POMC/CART neurons (which decrease appetite). Leptin also slows gastric emptying, the rate at which food leaves the stomach and enters the small intestine. So more leptin (everything else being constant) should keep the stomach fuller for a longer time, and the stomach of course sends it's own signals relating to appetite and satiety. Leptin may also increase base metabolic rate via diet-induced thermogenesis, a topic we'll explore later. There is a genetic defect that causes people to secrete little or no leptin. Individuals with this genetic problem tend to overeat considerably, and extrapolating from rats may additionally have a lower metabolic rate, with the result of extreme obesity. Administration of leptin to these individuals substantially aids this condition.

Fat cells secrete other hormones as well. Adiponectin secretion is inversely correlated with stored fat: more fat, less adiponectin, and vice versa. Adiponectin has potentially influences many things, including appetite, insulin sensitivity, inflammation, and vascular function. Interleukin-6 (IL-6) causes insulin resistance in fat cells, which tends to make them release fat instead of store fat. The hypothalamus also expresses and contains receptors for IL-6, particularly in areas controlling body composition. Fat cells also express tumor necrosis factor alpha (TNF-alpha), which inhibits lipoprotein lipase (the enzyme required to get fat out of lipoproteins and into fat cells), stimulates breakdown and release of triglycerides in fat cells, and may also induce insulin resistance.

So we see mechanisms in place to control fat storage through appetite. As more fat is stored, more leptin is secreted, which should blunt the appetite. As fat is lost, leptin levels drop, which should promote appetite. Leptin (and other hormones from fat cells) may additionally modulate metabolic rate, to encourage fat burning when there is an excess, and discourage it during a deficit. So again there's a lot of knobs to turn, all aimed at maintaining fat storage in a particular range.

Our final stop is the gastrointestinal (GI) tract along with the closely related pancreas. When we eat, food hits the stomach, which does a nominal amount of digestion both mechanical and chemical. The stomach represents short-term energy storage, more or less the "gas tank" for the body, and so it's no surprise that the stomach is involved in appetite as well. Indeed, most people think of appetite in terms of "my stomach is full/empty", but we've seen above that many other factors come in to play as well. The stomach signals the full/empty state both through nerves and hormones. Stretch receptors on the stomach wall send signals via the vagus nerve indicating fullness. The stomach also secretes the hormone ghrelin, which strongly stimulates appetite. Empty stomach means more ghrelin, full stomach means less. Increasing ghrelin increases brain concentrations of NPY. So an empty stomach definitely tends to increase your appetite, but gastric signals must be integrated with the variety of other signals to actually determine the degree of appetite stimulation.

Most of the hormonal action occurs in the small intestine and pancreas, and indeed there is some interplay between these organs. The pancreas is not only an endocrine organ (which sends hormones into the blood), it is also exocrine, emitting various substances like enzymes and bile salts require to break down food so it can be absorbed through the small intestine. The small intestine itself secretes a several hormones in various quantities, depending on the total caloric content as well as the individual levels of carbohydrate, protein (really amino acids), and fat. These hormones have a wide variety of effects, including stimulation/inhibition of pancreas endocrine and exocrine functions, modification of the rate at which food passes through the GI tract, metabolic control, and of course appetite. I'm not going to cover nearly all of these hormones or their effects. Check out the spreadsheet, or this paper and this paper for details.

A major hormone secreted by the small intestine is cholecystokinin (CCK, and no, I don't know how to pronounce it). Dietary fat and protein more potently stimulate of CCK release than does carbohydrate, and long-chain fatty acids seem to have a greater effect than short-chain. CCK affects a number of systems, e.g. inducing gallbladder contraction (to release the bile needed to digest the fat which stimulated CCK release in the first place). CCK also slows gastric emptying. Again this makes sense from a regulatory standpoint. Once the small intestine has received some energy nutrients, CCK signals the stomach to stop sending more until the present batch is done processing.

CCK also strongly suppresses appetite. In rats, administering CCK reduced food intake in a dose-dependent manner: more CCK, less food eaten. The exact mechanism is unclear, but it seems to be a combination of reduction in gastric emptying (stomach stays full) and detection by the nervous system. In both monkeys and humans, the fullness of the stomach seems to modulate the appetite suppression of CCK. The afferent fibers of the vagus nerve as well as the brainstem express CCK receptors. The Otsuka-Long-Evans-Tokushima fatty rat (try saying that 3 times fast) is a genetic variant which lacks the CCK-1 receptor, and both overeats and becomes obese.

A few notes on other GI hormones. PYY-36 is released in proportion to calories and meal composition, with fat resulting in higher concentrations than protein or carbohydrate, and may inhibit food intake. Glucagon-like peptides GLP-1 and GLP-2 are cleavage products of preproglucagon. GLP-1 increases insulin secretion and suppresses glucagon release. It also slows gastric emptying and inhibits food intake. Key areas of the brain such as the ARC express GLP-1 receptors. GLP-2 release is potently stimulated by fat and carbohydrates, and may enhance the digestive and absorptive capabilities of the small intestine. Oxyntomodulin (OXM) is released in proportion to calories ingested. It suppresses appetite and gastric motility, enhances insulin secretion, decreases food intake, and possibly increases metabolic rate.

So the takeaway here is that the GI tract sends numerous hormonal signals indicating energy is present and being absorbed, please don't send any more. One interesting side-note is that the levels of some of these hormones, notably PYY-3-36, GLP-1, and OXM, all increase after gastric bypass surgery. The effect of this should be to suppress appetite, and possibly increase metabolic rate, which would explain the success of such surgeries to reduce obesity. I find this interesting, because by itself I would guess reduction in stomach size should probably have little effect on overall food intake because of the other mechanisms regulating appetite based on stored and available energy. But diddle the relevant hormones, and voila, sustained appetite reduction and weight-loss. Hopefully the increasing understanding of these regulatory mechanisms will give rise to better treatments, since surgery seems an extreme way of accomplishing the desired effect.

Finally, we come to the pancreas. The best-known pancreatic hormone is insulin, arguably the Big Mama of metabolic regulation. It is interesting to note that the protein structures of both insulin and NPY are remarkably conserved across evolution. If you look at a primitive animal like a hagfish, it's insulin and insulin receptors are fairly similar to that of humans, so much so that hagfish insulin significantly stimulates human insulin receptors. The implication is that the role of insulin is central in metabolism and development, and fairly successful as relatively drastic changes across species required little mutation of insulin. We're most familiar with insulin's role in controlling blood sugar, both by increasing tissue uptake of glucose and by regulating glucose output from the liver. Insulin also regulates many other aspects of metabolism, like fat storage and cell division. Subsequent posts will visit these in greater detail.

Insulin is manufactured by the pancreatic beta-islet cells (B-cells). When glucose enters the B-cell, it is metabolized to ATP, the primary short-term "energy currency" of the body. But rather than using that ATP for energy, some of it closes potassium ion channels. This depolarizes the cell membrane, allowing calcium ions to enter the cell and causing stored insulin to be released. The presence of glucose in the cell additionally signals the cell to manufacture more insulin. Amino acids also trigger insulin release to varying degrees, depending on the particular flavor, as do ketone bodies. The effect of fatty acids is complex and not well understood. It appears that fatty acids are necessary for normal glucose-stimulated insulin secretion. Increasing fatty acid concentrations in the short term (1-2 hours) will cause more insulin to be released for a given glucose concentration. But long term, elevated fatty acids impair insulin secretion. Both the nervous system and other hormones also affect the amount of insulin released.

Insulin affects appetite, both directly and indirectly. The indirect path involves sensitization of the body to other satiety signals like CCK (a role shared with leptin). Insulin also appears to directly signal the hypothalamus, increasing activity of POMC/CART neurons and decreasing activity of NPY/AgRP neurons. We all know that the pancreas secretes insulin in response to blood glucose, but insulin secretion is also modulated by a number of other factors. We saw above how some GI hormones potentiate greater insulin release (the so-called incretin effect). Insulin levels are also a function of body-fat: the more fat that is stored, the higher insulin is in all states (fed, fasting, etc.) So insulin signals both energy availability and energy storage, but the primary effects indicate that over the long term insulin (along with leptin) signal how much fat is stored.

If insulin is infused directly to the brain (of a rat, presumably), the result is a decrease in food intake and loss of body weight in a dose-dependent manner. If insulin receptors are blocked, food intake and body weight increase. When insulin levels in the brain are held constant over long time periods via slow infusions, animals modify their diet and body composition until a certain body weight is achieved, and that weight is subsequently defended at a level determined by the insulin concentration.

We saw an example above where high insulin could be overridden by low blood glucose to cause hunger. Insulin suppresses appetite only when blood glucose is maintained at a proper level. Insulin-induced hypoglycemia (whether from a high-carbohydrate meal or administration of insulin) triggers an override mechanism in the brain, inducing hunger and eating to avoid going into a coma. Type 1 diabetics have the opposite problem: high blood glucose and low insulin. Type 1 diabetics are typically ravenously hungry despite high glucose, again showing the integrative capacity of the brain; yet they will fail to gain weight regardless of how much they eat, as the lack of insulin disrupts other metabolic functions.

The pancreatic B-cells also co-secrete another hormone called amylin. Insulin and amylin a secreted in a fixed molecular ratio of about 10 to 100 to one. Various disease states (including obesity) and pharmacological interventions increase the amount of amylin relative to insulin. While insulin appears to primarily signal stored fat levels, amylin signals both the amount of stored fat and energy availability from food intake. Amylin is secreted in proportion to body fat and meal size. Giving rats a does of amylin prior to a meal reduces meal size. Blocking amylin receptors produces a long-lasting increase in food intake and fat storage. Amylin appears to act in the area postrema (AP) of the hindbrain. AP neurons activated by amylin are also activated by glucose, CCK, and GLP-1, and the AP projects to the NTS, which in turn projects to areas of the hypothalamus regulating appetite and metabolism.

Type I diabetes occurs due to destruction of the pancreatic B-cells, so Type I diabetics also lack amylin, which is thought to contribute to their large appetites. Type II diabetics treated with insulin often gain more weight (duh), but this can be mitigated be treatment with an amylin analog. Some doctors are prescribing amylin analogs in obese patients who are not being treated with insulin. Since amylin serves both as a satiety an adiposity signal, this works as expected: these people both eat less and lose fat. But just as most obese people are insulin resistant, they're also amylin resistant. Administration of amylin to an already overtaxed system is, I think, a questionable long-term strategy. Additionally we know the body wants to keep the insulin/amylin ratio fixed, probably for a good reason. Adding exogenous amylin to the mix perturbs this balance even more than it already is, rather than helping to restore it to a healthy state.

Last, but not least, is glucagon, manufactured and secreted by pancreatic alpha-islet cells (A-cells). Metabolically, glucagon tends to counter the effects of insulin, e.g. increasing glucose output from the liver. Glucagon secretion is stimulated mainly by protein, possibly by fat, and not at all by carbohydrate; indeed, glucose inhibits A-cell glucagon secretion. Pancreatic hormones are dumped into the portal vein, so the liver gets first shot at them. Apparently the liver removes most of the glucagon, and rather little makes it into systemic circulation. Even so, glucagon acts as a satiety signal. Rather than acting directly in the brain, glucagon's action probably occurs in the liver, which then sends a signal to the brain via the vagus nerve. Animals whose afferent vagal nerves have been blocked do not have their feeding inhibited by glucagon.

So let's see how some different meals may affect appetite. We'll revisit these later, after we've gone through the other aspects of metabolic regulation and can look at the big picture; but the isolated effects on appetite are still interesting. These are my guesses, not proven by any scientific research. Feel free to add your own scenarios to the comments.

We discussed above what may happen after a high-carbohydrate low-fat meal, like the Teriyaki Stix Beef Bowl (102g carbohydrate, 33g protein, 7g fat). The stomach fills, reducing ghrelin secretion and sending the "full" signal to the brain. The large amount of refined carbohydrates should elicit a large insulin and amylin response, further potentiated by the release of hormones like GLP-1 and OXM. The protein in particular stimulates CCK release, which along with insulin, amylin, and other GI hormones suppress appetite. But the major insulin release induces hypoglycemia. The initial effects probably are an increase in gastric emptying via nervous system control to try and balance out the blood sugar, but of course this tends to raise insulin even more. Sooner or later the depressed blood glucose causes an increase in brain NPY, and powerful hunger, despite the fact that rather little of the meal may actually have been used for energy.

How about a "healthy" low-calorie meal, maybe a really big salad, lots of veggies and fat-free dressing. The conventional wisdom is that the large fiber load (and amount of water) fills up the stomach, contributing to satiety. That's true, to a certain extent, as filling the stomach triggers both the stretch receptors and reduces ghrelin. But the relative lack of any energy nutrients implies correspondingly low secretion of appetite control hormones like CCK. The brain also will not detect much rise in blood sugar or fatty acids. In turn, gastric emptying and intestinal motility is not inhibited and may in fact be accelerated, so the stomach empties faster than it would in a high-calorie meal. Appetite suppression from stomach distension rapidly fades, and you're hungry again.

How about a "cardiac arrest" meal of a big steak smothered in mushrooms and butter? This is a calorically dense meal, probably occupies considerably less stomach volume than the big salad, so maybe we don't get as much from stretching the stomach. But once this hits the small intestine, we get should get lots of hormones like CCK and glucagon to suppress appetite and gastric emptying. Some insulin and amylin are secreted as well. The glucagon helps keep blood sugar stable, and the additional protein from the steak may temporarily bump up blood sugar as well. The fat makes it into the circulation more slowly, and should help to both suppress appetite and gastric emptying over the longer term. Additionally, fat sensing by the hypothalamus also help the liver regulate blood sugar, so we don't get the "low glucose" override.

So to summarize:

The high-carbohydrate high-calorie fast-food meal makes you get hungry faster due to insulin-induced hypoglycemia. This happens despite consumption of plenty of energy.
The low-calorie low-glycemic salad fills you up in the short term, but you get hungry again quickly simply due to lack of available energy.
The high-fat high-calorie meal suppresses appetite for a longer time, both by avoiding adverse conditions like hypoglycemia, as well as providing a measured release of energy into the blood via the small intestine.

Now I ask you, which of these meals is the most likely to cause fat gain?

These examples are interesting (so I think), but again must be considered in the larger context of metabolic regulation. Obesity is not a simple result of overeating, fat-loss not the simple result of undereating. Both are a combined effect of different regulatory mechanisms. Appetite is just one piece of the puzzle. Genetically-modified rats, for example, illustrate different behavioral and physical outcomes depending on the nature of the mutation. Some overeat and maintain normal body weight. Some eat normally and get fat, and some both overeat and get fat. Conversely, to lose fat almost certainly requires restoration of the proper regulatory balance. By itself, the recommendation to "eat less and move more" is meaningless. We need to consider the effect on the hormonal and nervous system mechanisms, which require detailed thinking about the effects of food and exercise on human biochemistry.

Dissonance Redux

2008-07-07T15:18:00.000-07:00

Michael Eades' most recent blog gives an outstanding example of cognitive dissonance in action. In short, a recent study found that obesity in China was correlated with higher intake of vegetable foods. But "everybody knows" that vegetables are healthy, right? So the authors conclude it can't be the vegetables causing obesity, it must be the vegetable oil the Chinese cook them in. The funny (but simultaneously sad) thing is that their own published data not only refutes this hypothesis, but also clearly supports the alternative hypothesis that refined carbohydrate consumption leads to hormonal imbalances which in turn lead to obesity. It's right there on the page. Talk about cognitive dissonance.

Dr. Eades did an excellent job hitting the big points, so I just want to add a few thoughts. I can't get access to the original paper (I have no interest in handing Nature any of my money for this paper, especially given that someone was clearly asleep at the wheel to let it past peer-review), but I would infer that it is an epidemiological study. So we can't give it a lot of weight, any more than we should give much weight to the mostly epidemiological evidence that support current mainstream dietary recommendations. That said, the authors' conclusion is clearly goofy, and ignores considerable information. The differences in fat consumption between less and more obese groups was fairly minimal: essentially zero in men, and about 6g in women. The statistical measure of the "trend" (indicating correlation between quantities) indicates lack of signficance in correlating fat intake with obesity for both men and women. But here's a list of items whose trend was indicated at greater than 99.9% confidence (the "+" and "-" indicate positive or negative correlation):

Fresh vegetables (+)
Fruits (+)
Rice (-)
Wheat flour (+)
Whole grain (+)
Root vegetables (+)
Pickled vegetables (+)
Fish (+)
Milk (+)
Eggs (+)
Calories (+, women only)
Protein (+)
Carbohydrate (+)
Plant food fats (+)
Animal food fats (-)
Vegetable oil (+, women only)
Physical activity (+)

Thus, people who ate more vegetables were more obese, people who ate more fat from animal sources were less obese, etc. Indeed, if you look at the actual amounts of food consumed, what we find between the least and most obese quartiles are major increases in wheat flour (5x men, 20x women), whole grain (18x men, 22x women), root vegetables (4x men, 4.7x women), and milk (75x men, 92x women). Physical activity in the most obese quartile was somewhat less than two times greater that in the least obese. In other words, those people following a diet and lifestyle (at least given the presented data) similar to that recommended by the USDA were the most obese, on average. The focus on vegetable consumption is actually a little weird, being only about 50% higher in the most obese quartile, compared to the least obese, considerably less variation than than that for wheat etc. I guess it's more dissonance: "everyone knows" that wheat, whole grains, etc. are healthy, so why even go there?

The ultimate scientific test of a theory is its predictive power. The theory underlying USDA recommendations basically says if you eat like the food pyramid and exercise more, you should be at lower risk of obesity. When confronted with data which contradicts the theoretical predictions, you have two choices: question the data, or question the theory. These guys did neither, instead waving their hands and adding an additional hypothesis which still failed the predictive test for one study group (men), but which I guess let them sleep at night.

Let's now consider an alternative hypothesis: that most obesity is a symptom of an underlying hormonal imbalance caused by overconsumption of refined carbohydrates. This theory predicts precisely the results seen, without any bogus ad hoc additions. Carbohydrates drive insulin drive fat storage. For that matter, milk proteins may also have a larger effect on insulin than other proteins, and of course milk does add to the carbohydrate load. There's even evidence supporting Gary Taubes' hypothesis on the connection between caloric intake and physical activity: those with higher caloric intake were, on average, more physically active. There's no evidence of causality: it may be that eating more calories increases activity, or that those with increased activity get hungrier, or both. While the weight supplied by this study is rather thin, it does at least provide further confirmation of what we would expect given current knowledge of metabolic regulation, which is considerably better than the nonsensical conclusions put forth by the authors.

Energy Regulation 1: Do Calories Count? And Who's Counting?

2008-06-28T08:11:00.000-07:00

In the last post discussing acylation stimulation protein, I made several references to the various regulatory mechanisms that control energy intake, utilization and storage. My claim is that if all of these are working correctly, the body will more or less maintain itself in a healthy state, as that is presumably the evolutionary point of all this stuff. "Healthy state" includes not becoming obese. My guess is that unless you break one or more of these mechanisms, you would find it very difficult to store much excess body fat, because the body doesn't want that, and tries very hard to avoid it by influencing behavior and metabolism.

As we'll see, there are lots of possible things to break and ways to break them: genetic defects, drugs, disease. But for most of us, the major influence is probably diet, mainly through it's influence on insulin. Insulin is arguably the "master hormone" in charge of energy balance. As we'll see, insulin not only controls of blood sugar, but also acts as a signal to start or stop eating, and signals the amount of stored energy in the form of body fat. Insulin interacts with many other hormonal and nervous system mechanisms, and screwing up insulin balance also potentially fouls up a lot of other things as well; take a look at all of the problems inherent in "metabolic syndrome", and you'll get the picture.

I don't believe obesity is a disease in itself, but rather the symptom of an underlying metabolic problem. To "cure" obesity, you really need to restore the appropriate balance, so that the regulatory systems can operate properly. For instance, some obese people have a genetic defect that causes them to make little or no leptin, a hormone secreted by fat cells which is involved in control of both appetite and fat storage. Once you know somebody has this problem, it can be treated by giving them leptin to make up for their deficit. Type I diabetics (who are not obese) lack insulin, so they are treated with insulin. But Type II diabetics have too much of both leptin or insulin, and reduced response to both. Treating them with either leptin or insulin would not be expected to succeed in restoring their metabolic balance and thus normal bodyweight, an expectation borne out by experience. If you're going to fix a problem, you'd better have some idea of the root cause.

So this is the first in a series of posts to delve into the broad topic of "energy regulation", including feeding behavior, energy utilization, and energy storage. Considerable scientific progress has been made on these topics in recent years, but the understanding is far from complete. I'm going to try and touch on the high points, and hopefully avoid too many technical details (which honestly, I don't completely understand myself). Part 1 will be mostly a setup to the subsequent discussion. At the end of this post, I'll put some links to scientific publications or textbooks used, so you can delve into the details if desired.

There's been a lot of discussion lately about whether or not "calories count" in weight gain or weight loss. Much of the argument surrounding this point seems to be unfortunately misguided, with people taking absolute positions on either side. The reality is more complicated. The short answer to the first question is "Yes, calories do count", but is qualified by the fact that many hormonal and nervous system mechanisms regulate caloric intake, storage, and output. Roughly speaking, these are influenced by caloric content of food, but greater influence is exerted by the composition of those calories. As we go through this series, we'll see several examples where macronutrient composition plays a much larger role in influencing the biological response than does simple calorie content. In short, as far as metabolic regulation is concerned, the oft-repeated phrase "a calorie is a calorie" does not apply.

Thinking about the question "Who's counting calories" starts us down the path of understanding. After all, what organisms in nature consciously count the calories they eat or expend? That's easy: humans, and humans alone. Clearly an animal like a rat isn't keeping a tally like "I ate 5 extra grams of rat chow this morning, did 20 minutes on the exercise wheel to compensate" etc. Somehow, they "just know" how much to eat and be active, and their body adjusts accordingly. It is often stated that humans become obese due to an overabundance of readily available food. But in their natural environment, animals will not become obese regardless of food abundance UNLESS there is some other biological imperative to do so. Foxes don't get fat when there's lots of rabbits around, they make more baby foxes. Storage of excess body fat is again clearly regulated by other mechanisms. Mice, for instance, will lay on bodyfat as winter approaches in anticipation of hibernation. Further, they will store excess fat largely independent of how much or little they are fed. Bears similarly lay down fat stores for winter hibernation. Yet once they pass a certain age, they lose the ability to store enough fat for the winter, regardless of how much food is consumed. So the amount of input calories would not seem to be the major controlling factor in fat storage or loss.

Many recommendations for diet and health are based on a grossly oversimplified view of how food intake is regulated. The fullness of the stomach is widely thought to be the primary regulator. You eat until the stomach is full, food moves into the intestines, where your body sucks up whatever it can at a fixed rate until the stomach is more or less empty. Then you get hungry and eat again. This supposedly happens about once every four hours, leading to the idea of three meals a day during waking hours. This oversimplification spawns silly ideas like drinking lots of water or eating high-fiber foods to make you feel more full on less calories, or even sillier interventions like bariatric surgery. Just a little thought shows these ideas can't be right. If it were, a rat would happily eat wood chips and water until it felt full, and would ultimately starve to death from a lack of energy nutrients. Clearly the rat "knows" the energy content of possible food items, and thus avoids the wood chip diet. And we'll see later that surgery such as gastric bypass does more than simply shrink stomach capacity: it also causes measurable and significant changes in the levels of hormones associated with appetite and energy regulation.

The oversimplified view is part of the web of flawed thinking underlying diet. Obesity is not simply a result of being gluttonous, and weight-loss is not simply a process of curtailing caloric intake. "Willpower" is unlikely to enter in to the equation, unless your plan for avoiding or reducing obesity requires that you fight against millions of years of evolutionary programming, life-preserving impulses, and mechanisms regulating appetite and metabolism. Rats and bunnies and bears don't need willpower if fed their natural diet; but feed them something outside of their evolutionarily defined diet, and their bodies often go haywire, with obesity as one possible outcome. One presumes the same holds for humans. Similarly, I think it's pretty easy to poke holes in the idea that higher brain functions (e.g. "willpower") have the capability to override behavior which is key for survival of the organism. Next time somebody blabbers at you about having "willpower" to lose or keep off excess fat, ask them if they have the willpower to hold their breath until they pass out. Fighting against hunger is, I think, the same thing: you can do it for awhile, but the body isn't going to let itself die, and will sooner or later induce behavior it thinks is necessary for survival. This will hopefully become more clear as we delve into the regulation of diet and metabolism.

Before diving into some of the biochemical details, it might be useful to think of a simple model system which requires similar regulatory capabilities. The hybrid electric vehicle (HEV) seems to be a good one, and has some nice similarities with the body. An HEV takes fuel (usually gasoline or diesel) from an external source, and stores it in the gas tank. It also can store energy in a battery, and when moving also "stores" kinetic energy (the energy of motion). Energy can be used from these various sources as demanded by the usage of the car. When accelerating, gasoline is burned in an internal combustion engine and/or electricity from the battery is used to power an electric engine. Energy can be converted amongst it's different forms. The internal combustion engine can be used to either accelerate the car (increasing kinetic energy) or charge the battery. Kinetic energy can be converted to stored electrical energy through regenerative braking.

All of this requires some regulation, so that you don't store/use too much energy, possibly causing inefficient use or damage. One mechanism is simply mechanical: the gas tank has a maximum capacity. If you try to put in more gas than it can hold, gasoline spills out all over your shoes. The battery has a maximum capacity as well: charge it too much, and it may explode. The car's "brain" (a computer and related electronics) monitors the various systems as well as the energy requirements based on your usage. Thus, if the battery registers as not full, applying the brakes will generate electricity which charges the battery. If the battery is full, then that energy must be "wasted" as heat, because there's no place else to put it. If power requirements exceed that of the electrical motor or if the battery is empty, then the internal combustion engine needs to be turned on.

The human body has many parallels. Fuel is supplied externally, but we can take in multiple types: carbohydrate, fat, protein, and alcohol (though obviously the latter is not recommended). This fuel is stored in the stomach, much like the gas tank. Rather amazingly, unlike an HEV, the body needs only one power plant for all different fuel types: the mitochondria. The body has "batteries" as well. Fat cells can store fat, muscles and the liver store glycogen (the storage form of sugar), and lean tissue throughout the body contains protein, though this is generally used for energy only in emergency situations. Different fuel types can be interconverted: carbohydrates can be changed to fat, protein to glucose, fats to ketones. Excess energy can be wasted as heat. And all of this is monitored and regulated by a combination of the nervous system and glands, to maintain the body in a healthy state over a wide variety of usage conditions, whether sleeping or avoiding becoming a bear's lunch. As humans are omnivores, the system can also deal with a very wide range of different macronutrients from plant and animal sources.

The differences between people and HEV cars are informative as well. An HEV can't go get it's own fuel. Instead, it reports on the fuel status to the driver via the fuel gauge. Humans of course need to obtain their own fuel. The "fuel gauge" is ultimately appetite, which is driven by a complex system of hormones and several parts of the brain. An HEV also uses fuel for only one thing, which is to generate energy. While energy is one main purpose of food intake in humans, humans are also constantly regenerating new tissue and other functional substances like hormones and enzymes. Food provides the raw material for this as well. As we'll see in a bit, these functions, most importantly including growth in children, are also closely tied in to the same systems which regulate food intake and energy metabolism.

The cycle of food intake and energy usage/storage can be broken into several steps. Each of these tends to have several interacting regulatory mechanisms, both hormonal and nervous. The steps are:

Appetite stimulation, which in turn stimulates food-seeking behavior.
Initiation of the meal (start putting stuff in your mouth).
Termination of the meal (stop putting stuff in your mouth).
Movement of food from the stomach to the small intestine for digestion and absorption.
Utilization or storage of nutrients.
When everything eaten is used up, start again.

If the regulation of any step is disrupted, we have the possibility of non-optimal health, the most outward symptom of which is obesity. For instance, researchers use several strains of rats and mice which have been genetically modified to be predisposed to obesity. The modified genes affect different regulatory systems, with various different outcomes like overeating, underactivity, increased storage of fat over lean tissue, etc. (the "willpower" gene has yet to be identified.) But the main outcome is the same: obesity. When you break a regulatory mechanism, the animal exhibits some combination of behavioral and/or metabolic changes that cause it to become obese. Conversely, if you repair whatever is broken, or compensate for it's effects, the animals generally lose their obesity and normalize metabolism. Why would it be any different in humans?

Subsequent posts will delve into these regulatory mechanisms more deeply, and explore some possible implications for diet and health. Again, much is unknown in this field, so the best we can do is take what is known and apply rational inference; but I think we'll see that some knowledge of how eating and energy storage are controlled provides a powerful explanatory framework for much of what is observed in terms of obesity, weight-loss, and just general health.

Here are some links to the science papers, if you want to get a head start:

Reviews on Appetite: a group of 14 papers on the topic
Neuronal Glucose Sensing: What do we know after 50 years?: A nice (but technical) discussion of how the nervous system can directly detect blood glucose levels, and how this influences other regulatory systems.
Central Administration of Oleic Acid Inhibits Glucose Production and Food Intake: Similar to the above, but evidence of how the brain detects fatty acids in the blood, and again what effects this has on other aspects of metabolism.
Attenuation of Insulin-Evoked Responses in Brain Networks Controlling Appetite and Reward in Insulin Resistance: some discussion of how insulin affects reward behavior associated with eating, which in turn informs as to why foods that strongly affect insulin are labeled "comfort foods" and may be addicting.
Why Zebras Don't Get Ulcers, Third Edition by Robert M. Sapolsky: Good info on endocrine systems, particularly related to stress. Also provides some understanding of how different systems interact and affect each other.
Good Calories, Bad Calories by Gary Taubes
Metabolic Regulation: A Human Perspective by Keith Frayn

Petition the NIH to Weigh All Scientific Evidence

2008-06-25T10:16:00.000-07:00

A recent comment from Lauri Cagnassola asked for support on a petition to the National Institutes of Health (NIH). Dr. Cagnassola is the managing editor of the journal Nutrition and Metabolism, and the petition is basically asking the NIH to consider all scientific evidence surrounding the issue of blood sugar control in Type 2 diabetics. Particular focus is on an NIH statement about the ACCORD study: "Intensively targeting blood sugar to near-normal levels ... increases risk of death." What makes this statement somewhat brain-dead is that it is not qualified by "using the methods for blood sugar control employed in the ACCORD study", which I believe were largely intensive drug therapy, possibly including insulin. There are plenty of good reasons to think that intensive insulin therapy could shorten your life, and this sort of blanket conclusion is dangerous, obviously, since the implication is that we should just give up on controlling blood sugar in diabetics, since presumably the cure is worse than the disease.

There is plenty of evidence, however, both anecdotal and clinical, that Type 2 diabetes is often effectively controlled through diet. See, for example, this recent study, as well as the excellent documentary "My Big Fat Diet". Proper testing of a hypothesis requires that all relevant evidence be included in evaluating that hypothesis, and the NIH appears to be only considering the narrowly defined evidence admitted by current dogmatic beliefs. The usual complaint when diet is brought up to this group of people is something like "we don't know the long term effects of a low-carbohydrate diet in patients with Type 2 diabetes." Of course you don't, because you've neither looked at the currently available evidence, nor attempted studies to gain your own evidence.

The petition is asking to change that. Of all scientific organizations involved in studying human health and making treatment or lifestyle recommendations, the NIH is one of the very few truly public institutions. It is funded by your tax dollars, and is supposed to represent the best interest of the general population, not of specific interests such as drug or food companies. Their responsibility is to consider all available evidence, since getting it wrong can literally be the difference between life and death. If you feel similarly, please sign the petition, and also consider contacting your congressional representatives. Elected officials are more sensitive to the public voice than bubble-world bureaucrats, and they hold the purse-strings for funding the NIH.

Reading List and Gratuitous Commentary

2008-06-24T08:07:00.000-07:00

A reader recently asked for recommended reading, and I thought it would be good to just post it to the blog rather than burying in comments.

Some of the stuff listed is fairly technical. But one thing that is important to realize is that a lot of the technicality in biochemistry is big words. Don't get scared off by terms like "fructose-1,6-bisphosphatase", instead try to grasp the big picture. Similarly, biological systems are "complex", in the sense of having a lot of interacting parts. But in the end, it's pretty much "the leg bone is connected to the hip bone". You don't need to build a radically new mental framework to think about this stuff, as you might with something like quantum field theory. And the details of many processes aren't really so important in making health-related decisions, e.g. knowing the precise chemical reactions by which lipoprotein lipase cleaves fatty acids from triglycerides isn't as important as knowing that in the neighborhood of fat cells, insulin makes it occur more.

Enough babbling. Here's the list (with more specific babbling), roughly ordered from easiest to hardest:

The Protein Power Lifeplan by Michael R. Eades and Mary Dan Eades: Packed with very readable accounts of the relevant science. The Eades are good about delineating what appears clear from available scientific evidence, and what they've inferred "makes sense".
Life Without Bread by Christian B. Allan and Wolfgang Lutz: Another readable account, complementary in many ways to what is presented in other books. The discussion on hormonal balance is pretty interesting by itself.
Nutrition and Physical Degeneration by Weston A. Price, DDS, and Price-Pottenger Nutrition Foundation: After you read this, you'll never look at someone's face the same way. Nutritional information is largely observational, but at least some of Price's conclusions are being borne about by more detailed biochemical research. Price guessed a lot of stuff we seem to be rediscovering today. Also has lots of anthropological information, particularly illustrating connections between food and culture.
Good to Eat: Riddles of Food and Culture by Marvin Harris: Very entertaining and thought-provoking, and should start you thinking about the interrelationships of food and culture.
Why Zebras Don't Get Ulcers, Third Edition by Robert M. Sapolsky: A detailed but funny and readable account of how the body's hormonal systems work, with a particular accent on stress.
Good Calories, Bad Calories by Gary Taubes: Very detailed and dense accounting both of how several "sacred cows" of modern nutrition came to be, as well as the (largely ignored) scientific evidence against them. A great read both for the sociology and the science, and packed with info. Worth reading more than once, and required reading before diving into any textbooks.
Cholesterol and Health Website by Chris Masterjohn: Very thorough and detailed write-ups of various nutritional topics, mostly centered around lipid metabolism. About the same level as Taubes. Definitely read Masterjohn's discussion of The China Study for a good example of bad science.
Metabolic Regulation: A Human Perspective by Keith Frayn: A good stepping stone to the more detailed textbooks. Reading Frayn after Taubes is recommended, since they cover a lot of the same ground, Frayn in more technical detail. Frayn tries to connect the biochemical details to current nutritional dogma. Ignore this and draw your own conclusions.
Advanced Nutrition and Human Metabolism by Sareen S. Gropper and Jack L. Smith: The hard stuff. Similar comment applies in following the science to your own conclusions.
Nutrition and Metabolism Society Website: All about including knowledge of metabolism into health-related decisions. See also their open-access journal, Nutrition and Metabolism.
Reviews on Appetite: An entire issue of the Philosophical Transactions of the Royal Society B devoted to the details how hormones and the central nervous system control energy intake. Great stuff, and hopefully the subject of my next blog post.

A Swift Kick in the ASP

2008-06-12T08:59:00.000-07:00

Gary Taubes' Good Calories, Bad Calories provided a nice and readable description of the current understanding of fat metabolism, in particular the major mechanism of how dietary calories wind up in fat cells, and how stored fat is made available for energy. The mechanism is fairly simple, and is a scientific "fact" as much as there ever can be one (lots of supporting evidence, no alternative hypotheses). Dietary fats, as well as those created in the liver from carbohydrates, are transported around the body in large molecules called lipoproteins. We've all been inundated with propaganda about lipoproteins, e.g. low-density lipoprotein (LDL) is "bad cholesterol", high-density lipoprotein is "good cholesterol", very low-density lipoprotein (VLDL) is "triglycerides", which are also "bad". The popular nomenclature is terrible and confusing.

Lipids are substances like fat and cholesterol which are not water soluble. To be carried in the blood (which is mostly water), lipids are carried inside of large lipoprotein molecules, which basically wrap up a droplet of lipids in a protein coat. Protein is water soluble, problem solved. The specific proteins on the surface of the lipoprotein allow it to bind to various receptors, so different lipoproteins can perform different functions, depending on receptor binding. Thus, cellular LDL receptors grab LDL from the blood so the cells can extract cholesterol, while HDL bind to receptors that allow it to take away "used" cholesterol for recycling in the liver, e.g. when cells die.

Most of the fat transported by lipoproteins is in the form of triglycerides (more technically known as triacylglycerol), a largish molecule consisting of three fatty acids attached to a "backbone" molecule of glycerol. Two kinds of lipoproteins carry most of the triglycerides: chylomicrons and VLDL. Chylomicrons are manufactured in the intestinal lining, packaging up digested fatty acids and cholesterol. The chylomicrons are (for reasons unknown to me) transported through the lymphatic system and dumped into the blood via the thoracic duct. Cells then have the opportunity to grab fat or cholesterol from the chylomicron, and some other changes happen to the surface proteins which rather quickly render it a chylomicron remnant. The liver vacuums up chylomicron remnants and repackages any lipids as VLDL (which also carries fat created by the liver from excess glucose). The VLDL then returns to the blood, and again cells can grab fats as necessary.

The triglyceride molecules carried by chylomicrons and VLDL are too large to pass across the cell membrane. In order to get some fat into a cell, the individual fatty acids must be released from the tryglyceride; fatty acid molecules can cross the cell membrane. The primary enzyme which performs this tasks is lipoprotein lipase, or LPL.

So that (long-winded) explanation gets us through part one of how fat is stored: LPL frees fatty acids from triglycerides in lipoproteins so they can get inside of the fat cells. Now, fat cells don't store fatty acids directly, but instead create their own triglycerides. However, the glycerol molecule itself also cannot cross the cell membrane. Instead, the fat cells ultimately make their own glycerol (actually a substance known as alpha glycerol phosphate) from glucose, which in turn must be supplied by the blood. Fat storage thus requires two crucial ingredients: action of LPL on chylomicrons or VLDL to free fatty acids, and availability of glucose including the ability to transport that glucose from the blood into the fat cell, which requires some specialized molecules called glucose transporters, or GLUTs.

Now Taubes points out that the primary control mechanism for both LPL activity and glucose transport is the hormone insulin. More insulin means more LPL and more glucose transport, thus more fat storage. Additionally, inside the fat cell lives an enzyme called hormone sensitive lipase, or HSL. HSL performs the same essential task as LPL, but from inside the fat cell: it frees fatty acids from stored triglycerides, so they can be made available to the blood (being carried away bound to the blood protein albumin). HSL response to insulin is opposite of LPL: less insulin means more HSL activity. So when insulin is high, fat tends to be stored, and when it is low, fat tends to be released. It's a nice tidy story, and gives a biochemical basis for the hypothesis that overconsumption of carbohydrates is what drives most obesity. Eating carbs not only raises insulin, it also makes available lots of glucose, thus supplying both of the critical ingredients for fat storage, while simultaneously suppressing the release of fat from fat cells.

I like this story, but have long had the nagging suspicion it is not complete. Consider, for example, the Inuit, whose traditional diet consists almost entirely of protein and fat. Protein does raise insulin. Insulin is the sort of the "key" for opening cells the macronutrients (protein, fats, and carbohydrates). Even if you don't eat any carbs, you need insulin to go up in response to protein consumption so your cells can take up the constituent amino acids and use them for building tissue, making functional proteins like hormones, etc. Protein consumption also triggers the pancreas to secrete another hormone called glucagon, which amongst other things blocks the entry of glucose into cells.

So, naively, a meal containing only fat and protein is somewhat blocked from having the fat stored, because glucagon inhibits the fat cells from taking in the glucose required to build triglycerides. But you do need to store some fat. Fat cells are a sort of energy reservoir, providing a steady source of energy between meals, so even if you eat zero carbohydrates, there should be a mechanism for storing a bit of fat. My guess was that this was accomplished through a precise balance of insulin, glucagon, and blood glucose. And it has to be precise, because too little storage and you run out of gas, but too much and you get fat and slow, making it more likely that you become polar bear food. But biological systems are rarely precise, rather achieving balance through robustness rather than precision. It also seemed like there should be some dose dependent mechanism for fat storage, e.g. eat more fat, store more fat. We certainly evolved that mechanism for storing away energy from carbohydrate-rich meals, and it seemed that something similar should be in place to take advantage of fat-rich meals, like bone marrow.

So this post at the Emotions for Engineers blog caught my attention, because at one point it mentions an alternative metabolic pathway fat storage. Sounded juicy, so I dropped a comment asking for elaboration, and was directed to information on acylation stimulation protein, or ASP. There seems to be a fair amount of confusion both in the scientific literature and on the Internet as to exactly how/why ASP did it's thing, and the implications for obesity. I did a big of digging, and though I certainly haven't solved the mystery, I did uncover some clues. This paper, in particular, provides a lot of useful information.

Fat tissue is increasingly recognized as an endocrine organ, generating several hormones related metabolism. You've probably heard of leptin. When fat cells expand from storing fat, they release leptin. Leptin does several things, most notably sensitizing other parts of the body such as the hypothalamus to the effects of hormones affecting satiety and gastrointestinal activity (see this excellent review for more). In short, when fat cells store more fat, they release more leptin, which makes you less hungry, until the fat cells shrink causing them to release less leptin, allowing you to get hungry again. There are many different such mechanisms regulating energy storage, metabolism, and hunger, forming a robustly controlled system, one that works well across a wide variety of input conditions.

ASP is another hormone secreted by fat cells, with several effects. First, ASP can increase LPL activity, making fatty acids available for transport into the fat cells. Second, ASP increases the expression of glucose transporters in fat cells, allowing them to bring in the glucose required to store fat. So ASP plays roughly the same role as insulin in fat storage, but rather than being generated by the pancreas in response to carbohydrates, is generated by the fat cells themselves. Better yet, ASP stimulates the production of triglycerides inside the fat cells. But what causes ASP to be secreted?

The answer, at least in test-tubes, is chylomicrons. When fat cells are exposed to chylomicrons they generate lots of ASP. By contrast, exposing the same cells to glucose, fatty acids, VLDL, HDL, or LDL elicits little ASP response. Further, the ASP response exhibits both a time and concentration dependence on chylomicron concentration.

This is an important clue. As discussed above, chylomicrons are the first step in transporting dietary fats into the body. When you eat a lot of fat, you make more chylomicrons, which causes the fat cells to make more ASP, which stimulates greater fat storage. But the chylomicrons only hang around for a relatively short time, being converted in the liver to VLDL. The receptor for VLDL (VLDL-R), when activated, does increase LPL activity, but to my knowledge does not stimulate glucose transport into fat cells. Thus the fat in VLDL is available to be used for energy, because the LPL frees the fatty acids for transport across cell membranes; but without some other hormonal signal (e.g. insulin), rather little of this fat can be stored in adipose tissue.

Two questions then arise in the context of a low-carbohydrate/high-fat diet. The most obvious one is "can I get fat by eating too much fat?" Taubes lays out the case that overconsumption of carbohydrates drives fat storage through the action of insulin, but can overconsumption of fat do the same via the action of ASP? When viewed with the most narrow lens, the answer is clearly "yes". While insulin's effects on LPL and glucose transport are considerably stronger than ASP, ASP does ultimately trigger the same conditions leading to fat storage. So if you eat enough fat for a long enough time, in principle you will become obese.

But if we take a step back, things are not so simple. The body has many feedback mechanisms for regulating energy content, such as leptin secretion by large fat cells, leading to suppression of appetite. These mechanisms regulate feelings of hunger, metabolic rate, how fast the stomach empties, etc. The system has presumably evolved to be robust over a wide range of environmental and nutritional conditions, allowing us to have enough energy to make it through times between meals while not having to carry so much that physical performance and other health aspects are compromised. The whole chain of events described above provides a nice example. Eat lots of fat, intestines create lots of chylomicrons. Chylomicrons stimulate fat cells to make ASP, which in turn increases fat storage. As fat cells store fat, they release leptin, which suppresses appetite and sensitizes the body to other satiety signals. But chylomicrons are fairly quickly turned into VLDL, which do not stimulate fat storage, but do make fat available for energy. The brain can detect VLDL levels, and regulate gastric emptying, appetite, etc. until the fat in the VLDL is used up. And that's just one of a complex web of interactions between hormones, the nervous system, metabolism, and digestion.

To become obese (at least without trying really hard), some key regulatory mechanism needs to be broken. For instance, there is a genetic defect which causes the fat cells to not produce leptin. People (or mice) with this defect have an unstoppable appetite, and become extremely obese. Treating them with leptin can reverse this condition. Another example is Cushing's disease, which is a small tumor on the pituitary. The net effect of Cushing's disease is that it causes the body to have high levels of the hormone cortisol. I had a friend with Cushing's disease. He ran five miles every day, and by any measure ate a healthy diet, yet continued to gain weight. Why? Increased cortisol (from the sympathetic endocrine system) can cause compensatory secretion of insulin (from the opposing parasympathetic endocrine system). Chronically high insulin will make you fat no matter how much you exercise or how little you eat. Keep insulin high, and you can literally starve to death while remaining obese.

But it appears the big hitter is carbohydrate consumption, particularly refined carbohydrates. These cause both drastic increases in insulin levels and make available lots of glucose for triglyceride storage. Though insulin nominally acts to suppress appetite and GI motility, high levels drive energy nutrients out of the blood and into the cells, ultimately leading the brain to "override" other mechanisms such as leptin, because low levels of energy nutrients in the blood basically signal imminent starvation; indeed, the brain itself needs a certain level of blood sugar to be maintained for proper operation. So eating carbs not only causes you to efficiently store fat, it also drives you to eat more food, and that food is typically more carbs to stabilize your blood sugar, leading to a vicious cycle.

I don't see a similar issue when eating a high-fat/low-carb diet. Fat ingestion does not cause hormonal derangement. Energy levels in the blood are maintained, allowing the various appetite regulation mechanisms to operate normally without getting an emergency override to eat more food despite available energy in the body. ASP production is stimulated only by chylomicrons, which are relatively short-lived, allowing a limited amount of dietary fat to be stored, while the rest is made available as energy. In principle, you could get fat by eating enough fat, but in practice it would probably be very difficult. You would have to force yourself to eat even though you felt extremely full, and continue to do so over a long time period. Not impossible, but definitely an uphill battle against a whole host of hormonal and nervous control systems, very much the analog of trying to lose weight on a low-fat/high-carbohydrate diet.

While it may be hard to gain fat through a high-fat diet, it is likely possible to keep on a certain level of body-fat. Low-carbohydrate diets are known to "stall", where the last 20 or so pounds just won't come off, regardless of carbohydrate restriction. I suspect our friend ASP plays a crucial role here. The low insulin levels on a low-carb diet will allow the fat cells to free fatty acids, but if you are consuming enough fat, at some point this effect will be balanced by that of ASP, and voila, no more fat loss.

Cognitive Dissonance and Scientific Progress

2008-05-29T10:34:00.000-07:00

I recently read Mistakes Were Made (but not by me). The central theme of this book is the psychological phenomenon of cognitive dissonance, which basically describes the feeling of discomfort we have when confronted with inconsistent thoughts. The mind naturally tries to resolve such dissonance, attempting to bridge the gap with some other explanatory device. The book gives lots of good examples, but the one major area it left out is the role of cognitive dissonance in scientific progress.

There's a strong argument to be made the cognitive dissonance is the major driver of science. When we find evidence that contradicts an existing theory, we find ourselves in a dissonant state. Resolution of that dissonance requires some other explanation, which might be that the experiment which gathered the evidence was wrong. But, if the results are repeated enough times, that argument goes away, and we're left with formulation of a new theory, one which encompasses not only the new evidence, but also all of the old evidence supporting the old theory.

Unfortunately, cognitive dissonance is simultaneously a major impediment to scientific progress. One reason is that it is a lot easier to cling to an old theory by shutting your eyes to new evidence, or explaining it away with ad hoc hypotheses (theories which have no actual support, other than accounting for the gap between the old hypothesis and the new evidence). This is actually a major problem. The effect of cognitive dissonance is that established theories are held with such mental strength that it is automatically assumed that the evidence supporting them also carries great weight; conversely, when confronted with evidence contradicting the established theory, one must then assume that either the new evidence has much less weight than the old, or that the ad hoc hypotheses dreamed up to bridge the evidential gap are themselves supported by weighty evidence. The ad hoc hypotheses themselves become part of the "truth", making the whole mental structure even more difficult to dislodge.

I'll start with an example from physics. Physics is supposedly the "queen of the sciences", not only because it deals with the most fundamental physical phenomena, but also the things studied in physics are often "simple", in the sense of lending themselves to highly controlled experiments and being described by mathematical models with a relatively small number of variables. Contrast with something like human metabolism, where we have to deal with a highly complex system of millions of interacting parts. Yet even so, physicists are just as susceptible to cognitive dissonance as anyone else.

The example is that of the theory of "luminiferous aether". This aether was a substance proposed to permeate everything in the universe, providing a medium through which light waves could travel. In retrospect, it was something of an ad hoc theory to start with. Physicists knew that various physical media could transmit waves: strings, water, air, etc. From this it was extrapolated that light waves must also travel through some medium, and thus was born aether theory. In the nineteenth century, James Clerk Maxwell unified the theories of electricity and magnetism, showing that both phenomena were actually one in the same: electromagnetism. One consequence of Maxwell's theory was that the electromagnetic field could be shown to propagate in waves at the speed of light, which quickly led to the conclusion that light was in fact electromagnetic waves.

Maxwell's equations showed that these waves always propagated with the same speed in vacuum. According to Isaac Newton's view of space and time, this then implied that the aether must define a universal frame of reference, and all other motion (like that of the Earth around the Sun) occurred relative to this frame, moving through the aether. But for this to hold required that the aether have some fairly impressive physical properties. It was simultaneously a fluid (in order to fill space) but also more rigid than steel (to support the high-frequency oscillations of light waves). Aether could have neither mass nor viscosity, otherwise it would affect the motions of the planets. Finally it had to be non-dispersive, transparent, incompressible, and continuous at a very small scale. Great stuff, where can I get some?

It gets better. In 1887, Michaelson and Morley published results of an experiment to show the existence of the aether. The idea was simple: if light travels through the aether with a fixed speed, then the motion of the Earth through aether should affect the observed speed of light. So you measure the speed of light in the direction the Earth is moving, and then perpendicular to that direction (the actual Michaelson-Morley experiment is considerably more clever, but that's the basic result). The problem was that they found zero difference in the speed of light in the two directions. This stimulated a flurry of other ad hoc hypotheses. One of these was the Lorentz-Fitzgerald contraction hypothesis, which posited that objects moving through the ether shrunk in the direction of motion by an amount which precisely counterbalanced the difference in the speed of light, thus "explaining" the Michaelson-Morley result. Efforts to preserve aether theory got progressively more complicated and ridiculous until Einstein developed the Special Theory of Relativity, which explained all of the observed evidence quite nicely as resulting from the geometry of spacetime, doing away with the aether once and for all.

So we can see the strength of cognitive dissonance. Initially physicists experienced dissonance because they could not reconcile the idea of light waves traveling in a vacuum with what they knew about the propagation of matter waves. The aether theory was thus developed to resolve this dissonance, even though there was essentially no evidential support. As contradictory evidence arose, lots of smart people went through a lot of trouble to preserve the existing "cognitive harmony", inventing increasingly unlikely and unsupported hypotheses for the sole purpose of hanging on to the aether concept. It would have been logical to simply note that the idea never had any evidential support in the first place, and kick it to the curb. Special Relativity didn't accomplish this in a single stroke either. It took some time to gather independent evidence supporting Einstein's theory and for aether theory's strongest proponents to die off (though Einstein won two Nobel Prizes, neither were for his theory of Special Relativity). That's pretty much the norm in science, believe it or not.

Before going on, you might think the physicists would have learned from this episode. No dice. Modern cosmology (the study of the origins of the Universe) faces its own cognitive dissonance, essentially a disconnect between how the Universe was in the first few instants and how it is now. It was a pretty major fly-in-the-ointment for the Big Bang theory. The idea of Cosmic Inflation was devised to overcome this gap. Amongst other things, it postulates an essentially undetectable field called the "inflaton", permeating all of space, and having some rather precise and fortuitous properties in order to give us the observed Universe. Sound familiar? And the observational evidence for Cosmic Inflation is basically nil; yet challenges to the Cosmic Inflation hypothesis are typically met with considerable skepticism.

So let's examine some scientific matters of more immediate importance in this light. Gary Taubes' book Good Calories, Bad Calories appears to be doing a good job of stirring up cognitive dissonance in the various areas connected with nutrition and metabolism. But is Taubes himself a victim of cognitive dissonance, or possibly taking a contrarian stance to sell books? To try and answer this question, I dove in to some textbooks on human metabolism and nutrition to get some idea of what the mainstream really thought, and what evidence supported their hypotheses. What I found was many examples of cognitive dissonance, mirroring the story of aether theory (I also found that Taubes' science seems to hit the mark). The situation is rather worse in the case of human nutrition and metabolism. First, the system under study is very complex, with many interacting parts. That makes it hard enough to study cause and effect, even for a single cell. In the case of an actual person, further difficulties arise due to ethical concerns, i.e. you can't take a bunch of people, lock them up in a metabolic ward, and feed them nothing but vegetable oil for a year. So there are many gaps in understanding of metabolic phenomena and associated diseases, creating cognitive dissonance. As with the aether, these gaps are generally filled by hypotheses with poor evidential support, which then become very difficult to remove.

So let's take on the development of coronary heart disease (CHD). Roughly, the idea is that CHD is caused by imbalance of lipids (fats and cholesterol) in the blood, along with the lipoproteins (LDL, HDL) that transport this fat-soluble substances through the blood, which is mainly water. In the 1950s, CHD was perceived as a major health problem, and there was a gap in understanding the cause of this disease. In stepped Ancel Keys, who advanced the theory that CHD was caused by too much cholesterol in the blood getting deposited on arterial walls, and that in turn was caused by eating too much cholesterol and saturated fat. This part connecting diet to blood lipids to CHD is called the "diet-heart hypothesis". The evidence supporting the diet-heart hypothesis was Keys "Seven Countries Study", an epidemiological survey which showed a statistical association between consumption of saturated fat and incidence of CHD. Other studies showed a statistical association between blood cholesterol and CHD.

The problems with this evidence are well-documented elsewhere, particularly in Good Calories, Bad Calories. The short version is this: epidemiological evidence like this is extraordinarily weak. Take consumption of saturated fat. People across the world don't just differ in how much saturated fat they eat, but also in how many carbohydrates, other kinds of fat, protein, how much they smoke, daily stress, exposure to sun, yada yada yada. There are probably thousands of interrelated variables, so it's very difficult to pick one as the key cause of a disease, unless (as in the case of smoking) the association is statistically overwhelming AND supported by other biochemical and cellular evidence. For saturated fat and CHD, it's not even close; indeed, if you take a wider sample than Keys did, the association goes away completely.

The other problem is that statistical associations do not show causality. High cholesterol might cause heart disease. Heart disease might cause high cholesterol. Some third variable might cause both to happen. Simply measuring the association between two variables does not distinguish between any of these options. Instead, we need to delve deeper into the underlying physical processes to identify the cause. Smoking is a good example, where you can dive down to the cellular level and show rather precisely how the chemicals from cigarette smoke cause physiological changes leading to CHD, that smoking increases the probability of arterial spasm, etc. We then have (no pun intended) a smoking gun, other evidence supporting our original hypothesis that was generated from the weaker evidence of statistical association. So, is there a smoking gun connecting dietary lipids to CHD?

Apparently not. I've gone through three advanced textbooks on metabolism. First was
Keith Frayn's Metabolic Regulation: A Human Perspective, which had little to say on the topic beyond repeating observations of statistical association. Indeed, going through the discussion of cholesterol production at the cellular level, one might guess that dietary carbohydrates are potentially the culprit for high cholesterol, because key enzymes in cholesterol synthesis are regulated by insulin and the availability of glucose. This point is not discussed at all by Frayn.

So I then moved on to Gropper and Smith's Advanced Nutrition and Human Metabolism, scientifically considerably more dense than the Frayn book. To be fair, I should note that the version I read was from 2005, and apparently there is a 2008 version, which I'll have to try and obtain as well. At any rate, Gropper and Smith have this to say on the topic: "Despite years of investigation, the mechanism by which hypercholesterolemic fatty acids exert their effects has not been conclusively defined." This is followed by four different hypotheses as to why saturated fats (and trans-fats) might raise cholesterol, but none with any real evidential support.

Surely, somebody had something intelligent to say on this topic, right? So I moved on to Lipid Biochemistry, edited by Gurr, Harwood, and Frayn (yes, the same Frayn). This book was from 1991, but I was hoping it's greater focus on the topic of lipids (covered in mind-spinning technical detail) would provide some insight, at least in to the details of reasonable theoretical mechanisms. Here's what they had to say: "The mechanism for the effects of different dietary fatty acids on serum cholesterol concentration is not clearly understood." There was a bit of hand-waving about apparent shifts between esterified/non-esterified cholesterol pools in liver, but no details, all the more surprising given the intense biochemical detail for related topics in this book.

Sound familiar?

Both books had some other nice examples of cognitive dissonance. Gropper and Smith at one point note

Contrary to widespread belief, changing the amount of cholesterol in the diet has only a minor influence on blood cholesterol concentration in most people. This is because compensatory mechanisms are engaged, such as HDL activity in scavenging excess cholesterol and the down-regulation of cholesterol synthesis by dietary cholesterol.

But later on the same page, we find this:

Consumption of the following lipids shows a positive correlation with the risk of cardiovascular disease (CVD), primarily due to a hypercholesterolemic effect or to unfavorable shifts in LDLC:HDLC ratios:
Total fat

Saturated fatty acids

Cholesterol, and

Trans fat.

Now, if you already know that the body compensates for dietary cholesterol, and better yet know how it does this, then clearly the association between dietary cholesterol and high blood cholesterol is NOT causative. Dietary cholesterol can't be "hypercholesterolemic". Talk about dissonance: these two statements are on the same page of the book.

It's worth reflecting on the magnitude of the situation with the lipid hypothesis. Despite over 50 years of intense study, the best anyone can say about the biochemical mechanisms connecting dietary lipids and CHD is that they're "not clearly understood". "Not clearly understood", by the way, is scientist-speak for "clueless", because if they had any clue at all, there would be at least some plausible working hypothesis in place. Instead we've got nothing. Zippo. Nada. Zilch. And the situation is actually far worse, because the original epidemiological evidence has been repeated refuted by other studies such as Framingham, which found an inverse correlation between saturated fat consumption and CHD incidence, not the positive correlation touted by Gropper and Smith. Such selective weighting of evidence again shows the strength of cognitive dissonance. We tend to think of people like scientists and doctors as possessing greater-than-average powers of reasoning, to be immune to effects of cognitive dissonance. But they're just people too, in the end, subject to the same psychological flaws as the rest of the population. It's actually worse for them, because they have the same opinion of themselves, of being supremely rational and even-handed in how they weigh evidence. As such, scientists are, in a way, the most susceptible to the effects of dissonance, because they are the most convinced that they have reasoning powers to avoid such irrational behavior.

Bear that in mind next time your doctor starts a sentence with "We know that . . ." Your doctor may "know" that consumption of saturated fat increases risk of heart disease, but if you ask him/her WHY they're so sure, you're going to witness some cognitive dissonance first hand.

Masterjohn Reviews "The Cholesterol Wars"

2008-04-17T11:15:00.000-07:00

Chris Masterjohn is one of my favorite Internet writers on topics of nutrition and health. He's very, very thorough and has an excellent ability to logically "connect the dots" without getting mired down in dogma. Chris recently posted a review of Daniel Steinberg's book The Cholesterol Wars: The Skeptics vs. the Preponderance of the Evidence, where Steinberg argues in favor of the lipid hypothesis of coronary heart disease (CHD). As usual, Chris not only reviews the book, but a lot of the surrounding science as well, and gives a pretty clear and cutting-edge picture of what probably really causes CHD, including some details of why various experiments (like statin treatment) have confounding effects that mislead scientists into thinking that cholesterol level (or more particularly, LDL:HDL ratio) are the root cause. He also points out where Steinberg is probably right (at least supported by the scientific evidence) and where some arguments typically advanced by cholesterol skeptics are probably off-base. Great stuff.

One interesting point is that Steinberg differentiates between the diet-heart hypothesis (the idea that dietary saturated fat and cholesterol affect CHD) and the lipid hypothesis (the theory that some defect of lipids in the blood affect CHD). That's an important distinction, which had never really occurred to me, nor apparently to just about everybody else, regardless of their position on this issue. I was coincidentally in the middle of writing a major post which amongst other things discusses the fact that there is just about zero biochemical evidence that dietary saturated fat affects LDL levels. I'm going to put that on hold until I read Steinberg's book, which apparently discusses some of the biochemical and metabolic aspects of lipoproteins in some detail.

You can read Chris' review here: http://www.cholesterol-and-health.com/Daniel-Steinberg-Cholesterol-Wars.html

Baby-step

2008-03-10T11:58:00.000-07:00

A key theme of this blog is that you need information to make good decisions about their health, rather than simply assuming that others (government, doctors, industry, etc.) are necessarily making the best choice for you. A recent change from the FDA should provide more information for educated decisions. The essence of the new law is that data from all clinical trials submitted to the FDA will be made publicly available, rather than just those results the submitter chose to publish. I don't have much to add, except to express hope that this marks the beginning of a trend towards greater transparency from the health and nutrition industries.

Read more about it here.

Frosted Paleolithic Flakes

2008-03-06T05:51:00.000-08:00

I think the paradox frog news has put me in a negative frame of mind. I've just finished chapter 6 of Keith Frayn's Metabolic Regulation: A Human Perspective, and had an irresistible urge to vent. Mind you, as an information resource it's a great book, but Frayn does tend to extrapolate the biochemistry with amazing tunnel vision, framed by health and nutrition dogma that itself has little supporting evidence.

I'm planning a larger post on the topics of carbohydrates, insulin, and fat storage when I finish the book, but what I just read sent me over the edge. Here's an excerpt:

First, imagine that the subject for this 'thought experiment' is sufficiently health-conscious as to eat a mainly carbohydrate breakfast: cereals and semi-skimmed milk, perhaps, but no bacon and eggs. Such a breakfast is likely also to be lower in energy content than a high-fat breakfast.

The disposition of glucose and amino acids will be much as described earlier, although there may be a sharper peak in glucose (and hence insulin) concentration, depending upon the amount and type of carbohydrate eaten. Release of non-esterified fatty acids from adipose tissue will be suppressed, leading to preservation of the adipose tissue triacylglycerol store.

What amazes me is that in this description of a "healthy breakfast", he's actually describing the potential development of obesity. The last sentence basically just says "insulin keeps the fat in the fat cells." Does it ever have a chance to get out? Maybe:

About an hour after this breakfast, our health-conscious subject sets out for some exercise - nothing strenuous, perhaps a swim or brisk walk for an hour, or even cycling to work . . . depending on how strenuous the exercise is, sympathetic nervous activity and increased adrenaline in plasma may gently switch on fat mobilisation in adipose tissue.

Note the qualification: "may gently switch on fat mobilisation", but only if the exercise is sufficiently strenuous. But how strenuous is strenuous enough? Is there some biological mechanism which notifies the conscious mind that you've exercised precisely enough to burn fat so you do not store excess, but not so hard that you will lose too much fat? Did the human body evolve eating some analogs of "cereals and skim milk"? And did our ancestors regularly exercise an hour after eating this breakfast?

So I think we can get some idea how much you need to twist what is known about the basic biochemical and cellular responses to food in order to support the current dogma of what supposedly constitutes "healthy eating". Maintenance of stable body fat stores following Frayn's description would require that a person precisely balance their carbohydrate intake and exercise after every single meal. In this scenario, metabolic regulation is not very robust, in the sense of maintaining the body's state over a wide range of conditions. Further, it requires a lot of conscious tracking of macronutrient intake and exercise.

Something tells me Paleolithic humans had bigger problems. Do you think perhaps evolution has solved this problem for us? Hmmmmm . . .

Jumping on Insulin

2008-03-06T05:30:00.000-08:00

Apparently, the "paradoxical frog" secretes a substance which promotes insulin release. The frog is so named because it actually shrinks as it gets older, from a 27mm tadpole to 4mm as an adult. Now we have a new reason to call it "paradoxical": it may allow doctors to treat Type II diabetes by exacerbating the key symptoms of the disease (elevated insulin and insulin resistance).

Here's the press release: Reuters (2008, March 5). South American Frog Secretions Stimulate Insulin Release, Could Offer Diabetes Treatment Hope. ScienceDaily. Retrieved March 6, 2008, from http://www.sciencedaily.com /releases/2008/03/080304224051.htm

Polyunsaturated Logic

2008-02-29T08:45:00.000-08:00

I recently started reading Metabolic Regulation: A Human Perspective, by Keith Frayn, because I wanted to dig in further to the science discussed in Gary Taubes' Good Calories, Bad Calories. Not that I don't believe what Gary is saying, but it's always better to get your information from the proverbial horse's mouth. Anyway, Metabolic Regulation is turning out to be a good book, explains things reasonably well, and I'll be posting interesting tidbits in the future. The science of metabolism is mostly big words. There aren't really any hard concepts, so if you can get past the vocabulary, you can learn a lot about how your body works (or at least the current understanding at the time the book was written).

This is the second time I've gotten into an advanced book on this topic, and in both cases have noticed something very interesting. Despite going into incredible detail about metabolic processes, qualifying the conclusions appropriately (e.g. "this result holds in a test tube, but may not hold in a complete living organism), they still push certain dogmatic ideas without any comparable level of evidence. It amazes me that the authors, who otherwise present information in excruciating molecular detail, don't choke when they start preaching dogma without evidence. Weird.

The major piece of dogma is the connection between saturated fat, cholesterol, and heart disease, the so-called lipid hypothesis. It's not difficult to make arguments that these connections are not causal (e.g. saturated fat does not cause heart disease), but are rather erroneous inferences from experiments or observations of varying design quality. Malcolm Kendrick lays out a pretty solid case against the lipid hypothesis in his book The Great Cholesterol Con; you can also read about it here. When I get into the textbooks, I expect them to support the lipid hypothesis with similar detail, perhaps even greater, providing insight as to the key molecular mechanisms by which saturated fat raises serum LDL, how that LDL then exerts a direct causal effect in the development of heart disease.

But instead, I get nothing. Just recitation of the hypothesis, and no evidence beyond the usual epidemiological handwaving, really not much more than you would get from a newspaper article. Metabolic Regulation at least acknowledges the weakness of the evidence (still almost all epidemiological), though still proceeds as though the lipid hypothesis were proven, even giving a mathematical expression for the relationship between serum cholesterol and dietary fats of different saturation indices.

Given the widespread belief that saturated fatty acids (SFA) raise LDL, and that polyunsaturated fatty acids (PUFA) lower LDL, you'd think somebody would have nailed the biochemistry by now. Talk about a killer drug target: "Take Satfatium, eat all the butter and bacon you want, and keep your cholesterol normal!" They could even use Robert Jarvik as the spokesperson! Talk about a cash cow. Despite the obvious and overwhelming motivations to nail down the SFA->LDL mechanism, I haven't been able to find diddly-squat, other than some weak hypotheses having to do with SFA binding to LDL or cholesterol receptors. That seems unlikely, given the relative lack of chemical and physical similarities between SFA and cholesterol (both are lipids, but that's about as far as it goes), and the relevant parts of LDL for receptor binding are proteins, not lipids. But could it happen anyway? Possibly, but it seems like an easy thing to study in a test-tube. Scientists study all kinds of cellular receptors in vitro, why not this one? Maybe it has been studied, showed bupkus, and never got published. Most scientists are averse to publishing negative results, especially when they contradict the prevailing dogma.

It's easy to play mental games and generate hypotheses; however, that your hypothesis supports some other well-believed hypothesis doesn't make it more true than one which contradicts widely believed ideas. That's backward thinking. Scientific truth is always conditional: belief in one thing is always conditioned on the truth of other information. Thus, the degree of belief in the lipid hypothesis is conditioned on the hypothesis that SFA raises LDL and that LDL exerts a causal effect on the development of heart disease: the lipid hypothesis is only true GIVEN that SFA raises LDL AND LDL causes heart disease. If any of the conditioning statements are false, the rest of it falls apart. This sort of conditional truth is generally ignored in science, partly because of the ass-backwards way most scientists do statistics, where they actually consider the evidence that the data would have been observed GIVEN that the hypothesis were true, rather than the evidence that the hypothesis is true given the data. And no, those are not mathematically the same thing.

I'll finish this post with a little brain-bubble that occurred to me. This is total speculation, and really just shows how one can create nice-sounding hypotheses from limited information. Anyway, eating more PUFA supposedly lowers total serum cholesterol. Eating more SFA supposedly raises total serum cholesterol. I don't believe either of these statements has anywhere near unequivocal experimental proof (feel free to post evidence otherwise), as the results seem to be all over the place; but let's pretend they're true, like nearly everybody else does. Now, one hypothesis as to why PUFA lowers serum is that PUFA displaces monounsaturated fatty acids (MUFA) in cell membranes. Cell membranes contain both SFA and MUFA, along with a little PUFA. The ratios of these are thought to govern the "fluidity" of the cell membrane, because as we know, SFA can pack more closely together, and thus tend to be more solid at higher temperatures. Cholesterol plays a similar role, also promoting membrane rigidity.

Now the PUFA theory we're discussing holds that eating a lot of vegetable oil raises the PUFA content of the cell membrane. It's not good if the membrane is too fluid, so in the absense of saturated fat the body reacts by driving cholesterol into the cells to increase their rigidity, thus decreasing serum cholesterol. So maybe the opposite happens as well: eat lots of SFA, cell membranes become too rigid, so they release cholesterol into the blood, and total serum cholesterol rises. Beautiful, logically consistent, and also has the "benefit" of supporting the prevailing dogmatic belief in the lipid hypothesis.

Of course, it's all a house of cards. My hypothesis depends on the PUFA/cell membrane hypothesis, for which there is little or no proof. Unfortunately, scientists are incredibly bad at sorting out these logical relationships, for whatever reason, and hand-waving hypotheses like mine often wind up widely considered as "true". I think what happens is that people neglect that actual evidence. They look at the PUFA hypothesis, think "that seems reasonable", and follow the logical chain that "proves" the SFA hypothesis. "Seems reasonable" is not evidence, though, and that distinction is too often lost on the very people who should know better.

ACCORD and ADVANCE

2008-02-21T08:45:00.001-08:00

I previously discussed the "surprising" negative results of the ACCORD trial, designed to test the effects of intensive blood glucose control in Type II diabetics. The media was full of statements to the effect that "don't panic, lower blood in Type II diabetics sugar is good", which seems a no-brainer. I suggested that the increased insulin dosage received by the intervention group could explain the increased mortality, due to various known effects of insulin, especially on cardiovascular health.

The ADVANCE Study is even bigger than ACCORD, but with the same essential goals. It's essentially a drug trial (really two drugs, one for blood pressure and one for blood sugar). After the ACCORD results, the ADVANCE investigators quickly trotted out a press release noting that their preliminary results saw no adverse effects in the treatment group. The difference between ACCORD and ADVANCE? ADVANCE did not treat with insulin, but rather with the drug Diamicron MR, from the class of sulfonylurea drugs. Sulfonylurea drugs work by increasing the insulin production of the pancreas, so in the coarsest sense, both ACCORD and ADVANCE are treating blood sugar by increasing insulin. But Diamicron MR has some other effects which may be protective against heart attack. We also don't know how much extra insulin was provided/created in ACCORD vs. ADVANCE. And for whatever it's worth (not much, really) Diamicron MR is helping the pancreas to fulfill it's natural function in response to blood sugar variations, so there may be some difference compared to just dumping exogenous insulin into a patient's blood. But that's hand-waving at this point.

ADVANCE has yet to publish its results, so we don't know whether the treatment was ultimately beneficial or not, only that there is currently no evidence of adverse effects of the treatment. I personally believe both ADVANCE and ACCORD are treating the wrong thing. Type II diabetes is fundamentally the result of insulin resistance. High blood sugar is a symptom. If you can reduce insulin resistance, the blood sugar will follow.

Drugs like Metformin can increase insulin sensitivity. But what causes insulin resistance in the first place? There are multiple hypotheses, but the simplest one which seems to fit the facts is consumption of refined carbohydrates. Refined carbohydrates rapidly increase blood sugar, requiring the pancreas to output large quantities of insulin. Insulin stays high in the blood well after the sugar has been forced into the cells, so insulin receptors continue to be bombarded, and this constant overstimulus likely results in down-regulation of cellular insulin receptors. Insulin performs other more powerful functions beyond blood sugar control, and it is logical to believe that cells adapt their insulin response to the ambient insulin level in order to maintain reasonable allostasis. There is considerable evidence both anecdotal and clinical that patients can restore insulin sensitivity (more or less) by simply removing the stimulus of refined carbohydrates and other "high glycemic" foods from the diet. The medical community seems to have forgotten the old chestnut:

Patient: Doctor, it hurts when I do this.
Doctor: Then don't do that.

If eating carbohydrates increases insulin and leads to insulin resistance, then don't eat carbohydrates. Now, this is easier said than done. The higher your insulin, the more deranged your metabolism, and that derangement is such that it creates major sugar cravings, because insulin resistant cells can't effectively get energy from the blood. A diabetic's cells think the body is in danger of dying from starvation. The body tends to do what it can to avoid death, like sending signals to the brain to get some sugar and get it NOW. So Type II diabetic's might require some level of drug intervention to help get their metabolism back on track, but the focus of the treatment needs to be curing the cause of the disease (insulin resistance) and not simply alleviating symptoms.

Insulin Insanity

2008-02-08T12:23:00.000-08:00

The New York Times recently reported how a large study on the effects of lowering blood sugar in Type II diabetics had to be stopped due to ethical concerns, because a lot more people were dying in the treatment group. This was the ACCORD study run by the NHLBI and NIH, which enrolled over 10000 Type II diabetics. The treatment group received "intensive" therapy to control blood sugar, mainly in the form of insulin.

The increase in deaths seems to be a big surprise to most involved, eliciting a lot of handwaving explanations. But if you just think a little about the nature of Type II diabetes and the action of insulin in the body, I suspect the outcome makes perfect sense; worse, had anybody applied some logical thinking to well-established medical knowledge, the outcome would have seemed preordained. The problem here (which seems to be endemic in modern medicine) is that few people seem to be able to see the forest for the trees. Insulin and sugar have well-known physiological effects, and any hypothetical treatment for Type II diabetes should account for these. Of course, almost nobody does this, leading to the current mess.

Let's start by being clear on what Type II diabetes is. Diabetes is generally thought of as a condition where blood sugar is chronically too high; but is chronically high blood sugar the cause of the disease, or just a symptom? In Type I diabetics, the patient's immune system attacks the pancreas (the organ responsible for making insulin), destroying it's ability to secrete insulin. Insulin is one of the body's most powerful hormones, governing many aspects of metabolism, not least being blood sugar levels. Blood sugar is tightly regulated in the body, because sugar has several damaging toxic effects; but you need a little sugar in the blood to power certain cells, like red blood cells. So Type I diabetics, lacking insulin, suffer increasing blood sugar, and all of the attendant bad effects, on average having significantly shortened lives.

Type II diabetes is really the opposite condition: too much insulin. You still have the symptom of increased blood sugar, but now it occurs because your body's cells have a downgraded response to the insulin secreted by the pancreas. Since the cells don't respond as readily to the insulin signal, sugar tends to build up in the blood, so the pancreas cranks out more insulin, which further desensitizes the cellular insulin response, resulting in a vicious cycle where both insulin and blood glucose levels increase over time. Ultimately your pancreas reaches the limit of what it can do, blood sugar goes through the roof, and you're classified as a Type II diabetic.

Now it makes sense to treat a Type I diabetic with insulin, because they have a serious lack. Insulin does a lot of things besides regulate blood sugar, and if you don't have any, you're in big trouble. But insulin is a seriously powerful hormone. It has many effects beyond reducing blood sugar, and these are just as well-known as the effects of high blood sugar itself. There's a reason why, in the presence of a too much insulin, your cells lower their response: too much insulin is damaging. Insulin resistance is a protective mechanism, and in Type II diabetics, it's out of control. From an evolutionary standpoint, one could go so far as to argue that insulin is more toxic than high blood glucose, otherwise the mechanism for insulin resistance would not have evolved (but that's just speculation on my part).

Giving insulin to a Type II diabetic is like dumping water in a sinking boat. It just exacerbates the original problem by further increasing insulin resistance AND subjecting the body to further damaging effects of chronically elevated insulin levels.

Now, you might argue that the "experts" had more information, and that I am oversimplifying things. I probably am oversimplifying things, but not as much as the so-called experts. Check out these quotes from the NYT article:

“It’s confusing and disturbing that this happened,” said Dr. James Dove, president of the American College of Cardiology. “For 50 years, we’ve talked about getting blood sugar very low. Everything in the literature would suggest this is the right thing to do,” he added.

Dr. Irl Hirsch, a diabetes researcher at the University of Washington, said the study’s results would be hard to explain to some patients who have spent years and made an enormous effort, through diet and medication, getting and keeping their blood sugar down. They will not want to relax their vigilance, he said.

“It will be similar to what many women felt when they heard the news about estrogen,” Dr. Hirsch said. “Telling these patients to get their blood sugar up will be very difficult.”

Dr. Hirsch added that organizations like the American Diabetes Association would be in a quandary. Its guidelines call for blood sugar targets as close to normal as possible.

And some insurance companies pay doctors extra if their diabetic patients get their levels very low.

The low-blood sugar hypothesis was so entrenched that when the National Heart, Lung and Blood Institute and the National Institute of Diabetes and Digestive and Kidney Diseases proposed the study in the 1990s, they explained that it would be ethical. Even though most people assumed that lower blood sugar was better, no one had rigorously tested the idea. So the study would ask if very low blood sugar levels in people with Type 2 diabetes — the form that affects 95 percent of people with the disease — would protect against heart disease and save lives.

Not very scientific, wouldn't you say? Everybody just assumed that lowering blood sugar was "the right thing to do", come hell or high water. In a sense, that's true: high blood sugar definitely causes serious damage. The problem is that nobody gave any thought whatsoever to the potential downsides of the treatment, especially in light of the known cause and symptoms of Type II diabetes, and the known effects of high insulin. The result? Many people killed in an effort to prove the dogma, not to mention millions of dollars wasted. With even a little rational thinking based on well-established knowledge, those lives would have been spared, and those dollars put to much more productive use. And the scary thing is, they still don't get it:

Clearly, people without diabetes are different from people who have diabetes and get their blood sugar low.
It might be that patients suffered unintended consequences from taking so many drugs, which might interact in unexpected ways, said Dr. Steven E. Nissen, chairman of the department of cardiovascular medicine at the Cleveland Clinic.

"Clearly", Type II diabetics with low blood sugar are different from non-diabetics: they have high insulin. They knew that before the study, but chose to ignore it, and blindly continue to do so. Apparently most of the deaths in the study were from heart attacks. Should we be surprised? Below is an excerpt from an excellent article about insulin (go down to the section "Insulin and Cardiovascular Disease"):

But there are certain tissues that aren't becoming resistant such as your endothelium; the lining of the arteries doesn’t become resistant very readily, so all that insulin is affecting the lining of your arteries.

If you drip insulin into the femoral artery of a dog, there was a Dr. Cruz who did this in the early 70s by accident, the artery will become almost totally occluded with plaque after about three months.

The contra lateral side was totally clear, just contact of insulin in the artery caused it to fill up with plaque. That has been known since the 70s and has been repeated in chickens and in dogs; it is really a well-known fact that insulin floating around in the blood causes a plaque build-up. They didn't know why, but we know that insulin causes endothelial proliferation. This is the first step as it causes a tumor, an endothelial tumor.

Insulin also causes the blood to clot too readily and causes the conversion of macrophages into foam cells, which are the cells that accumulate the fatty deposits. Every step of the way, insulin is causing cardiovascular disease. It fills the body with plaque, it constricts the arteries, it stimulates the sympathetic nervous system, it increases platelet adhesiveness and coaguability of the blood.

Insulin is a part of any known cause of cardiovascular disease. It influences nitric oxide synthase; you produce less nitric oxide in the endothelium. We know that helps mediate vasodilatation and constriction, i.e. angina.

So it would seem that, given what is known about the effects of insulin on arteries, an increase in deaths from heart attack should have been the expected outcome.

Once again, do you want these people making decisions about your health? If you are a Type II diabetic, the outcome of this study should serve as motivation to find out for yourself what is known about the cause of the disease, and the treatment options available. Don't blindly follow the brain-dead dogma espoused by most physicians and scientists, apparently blind themselves to long-established knowledge about the effects of insulin. Get the information for yourself, and ask your doctor hard questions about WHY you should do what he/she recommends. If the best answer they can give is "because I said so", you might consider looking for another doctor.

Questioning Dietary Guidelines

2008-01-22T15:42:00.000-08:00

These guys got it right: http://www.sciencedaily.com/releases/2008/01/080122154703.htm