Ancestral Health Symposium 2012

I recently returned from AHS12 and a little side trip to visit family.  The conference was hosted at Harvard University through the Harvard Food Law Society.  Many thanks to all the organizers who made it happen.  By and large, it went smoothly.

The science as expected ranged from outstanding to mediocre, but I was really encouraged by the presence and enthusiastic participation of a number of quality researchers and clinicians. The basic concept of ancestral health is something almost anyone can get behind: many of our modern health problems are due to a mismatch between the modern environment and what our bodies "expect".  The basic idea is really just common sense, but of course the devil is in the details when you start trying to figure out what exactly our bodies expect, and how best to give it to them.  I think our perspective as a community is moving in the right direction.

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New Review Paper by Yours Truly: High-Fat Dairy, Obesity, Metabolic Health and Cardiovascular Disease

My colleagues Drs. Mario Kratz, Ton Baars, and I just published a paper in the European Journal of Nutrition titled "The Relationship Between High-Fat Dairy Consumption and Obesity, Cardiovascular, and Metabolic Disease".  Mario is a nutrition researcher at the Fred Hutchinson Cancer Research Center here in Seattle, and friend of mine.  He's doing some very interesting research on nutrition and health (with an interest in ancestral diets), and I'm confident that we'll be getting some major insights from his research group in the near future.  Mario specializes in tightly controlled human feeding trials.  Ton is an agricultural scientist at the University of Kassel in Germany, who specializes in the effect of animal husbandry practices (e.g., grass vs. grain feeding) on the nutritional composition of dairy.  None of us have any connection to the dairy industry or any other conflicts of interest.

The paper is organized into three sections:

1. A comprehensive review of the observational studies that have examined the relationship between high-fat dairy and/or dairy fat consumption and obesity, metabolic health, diabetes, and cardiovascular disease.
2. A discussion of the possible mechanisms that could underlie the observational findings.
3. Differences between pasture-fed and conventional dairy, and the potential health implications of these differences.

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Is Sugar Fattening?

Buckle your seat belts, ladies and gentlemen-- we're going on a long ride through the scientific literature on sugar and body fatness.  Some of the evidence will be surprising and challenging for many of you, as it was for me, but ultimately it paints a coherent and actionable picture.

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What Causes Insulin Resistance? Part VII

In previous posts, I outlined the factors I'm aware of that can contribute to insulin resistance.  In this post, first I'll list the factors, then I'll provide my opinion of effective strategies for preventing and potentially reversing insulin resistance.

The factors

These are the factors I'm aware of that can contribute to insulin resistance, listed in approximate order of importance.  I could be quite wrong about the order-- this is just my best guess. Many of these factors are intertwined with one another. 
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The Brain Controls Insulin Action

Insulin regulates blood glucose primarily by two mechanisms:

1. Suppressing glucose production by the liver
2. Enhancing glucose uptake by other tissues, particularly muscle and liver

Since the cells contained in liver, muscle and other tissues respond directly to insulin stimulation, most people don't think about the role of the brain in this process.  An interesting paper just published in Diabetes reminds us of the central role of the brain in glucose metabolism as well as body fat regulation (1).  Investigators showed that by inhibiting insulin signaling in the brains of mice, they could diminish insulin's ability to suppress liver glucose production by 20%, and its ability to promote glucose uptake by muscle tissue by 59%.  In other words, the majority of insulin's ability to cause muscle to take up glucose is mediated by its effect on the brain. 

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Fast Food, Weight Gain and Insulin Resistance

CarbSane just posted an interesting new study that fits in nicely with what we're discussing here.  It's part of the US Coronary Artery Risk Development in Young Adults (CARDIA) study, which is a long-term observational study that is publishing many interesting findings.  The new study is titled "Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis" (1).  The results speak for themselves, loud and clear (I've edited some numbers out of the quote for clarity):
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Food Reward: a Dominant Factor in Obesity, Part III

Low-Fat Diets

In 2000, the International Journal of Obesity published a nice review article of low-fat diet trials.  It included data from 16 controlled trials lasting from 2-12 months and enrolling 1,910 participants (1).  What sets this review apart is it only covered studies that did not include instructions to restrict calorie intake (ad libitum diets).  On average, low-fat dieters reduced their fat intake from 37.7 to 27.5 percent of calories.  Here's what they found:
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Oltipraz

Oltipraz is a drug that was originally used to treat intestinal worms. It was later found to prevent a broad variety of cancers (1). This was attributed to its ability to upregulate cellular detoxification and repair mechanisms.

Researchers eventually discovered that oltipraz acts by activating Nrf2, the same transcription factor activated by ionizing radiation and polyphenols (2, 3, 4). Nrf2 activation mounts a broad cellular protective response that appears to reduce the risk of multiple health problems.

A recent paper in Diabetologia illustrates this (5). Investigators put mice on a long-term refined high-fat diet, with or without oltipraz. These carefully crafted diets are very unhealthy indeed, and when fed to rodents they rapidly induce fat gain and something that looks similar to human metabolic syndrome (insulin resistance, abdominal adiposity, blood lipid disturbances). Adding oltipraz to the diet prevented the fat gain, insulin resistance and inflammatory changes that occurred in the refined high-fat diet group.

The difference in fasting insulin was remarkable. The mice taking oltipraz had 1/7 the fasting insulin of the refined high-fat diet comparison group, and 1/3 the fasting insulin of the low-fat comparison group! Yet their glucose tolerance was normal, indicating that they were not low on insulin due to pancreatic damage. The low-fat diet they used in this study was also refined, which is why the two control groups (high-fat and low-fat) didn't diverge more in body fatness and other parameters. If they had used a group fed unrefined rodent chow as the comparator, the differences between groups would have been larger.

This shows that in addition to preventing cancer, Nrf2 activation can attenuate the metabolic damage caused by an unhealthy diet in rodents. Oltipraz illustrates the power of the cellular hormesis response. We can exploit this pathway naturally using polyphenols and other chemicals found in whole plant foods.

Is working standing up too expensive? It could cost you as little as $10

Spending too much time sitting down is clearly unnatural, particularly if you sit down on very comfortable chairs. Sitting down per se is probably natural, given the human anatomy, but not sitting down for hours in the same position. Also, comfortable furniture is an apparently benign Neolithic invention, but over several years it may stealthily contributed to the metabolic syndrome and the diseases of civilization.

Getting an elevated workstation may be a bit expensive. At work, you may have to go through a bit of a battle with your employer to get it (unless you are "teh boz"), only to find out that having to work standing up all the time is not what you really wanted. That may not be very natural either. So what is one to do? One possible solution is to buy a small foldable plastic table (or chair) like the one on the figure below, which may cost you less than $10, and put it on your work desk. I have been doing this for quite a while now, and it works fine for me.

The photo above shows a laptop computer. Nevertheless, you can use this table-over-table approach with a desktop computer as well. And you still keep the space under the foldable table, which you can use to place other items. With a desktop computer this approach would probably require two foldable tables to elevate the screen, keyboard, and mouse. This approach also works for reading documents and writing with a pen or pencil; just put a thick sheet of paper on the foldable table to make a flat surface (if the foldable table’s surface is not flat already). And you don’t have to be standing up all the time; you can sit down as well after removing the foldable table. It takes me about 5 seconds to do or undo this setup.

When you sit down, you may want to consider using a pillow like the one on the photo to force yourself to sit upright. (You can use it as shown, or place the pillow flat on the chair and sit on its edge.) Sitting on a very comfy chair with back support prevents you from using the various abdominal and back muscles needed to maintain posture. As a result, you may find yourself unusually prone to low back injuries and suffering from “mysterious” abdominal discomfort. You will also very likely decrease your nonexercise activity thermogenesis (NEAT), which is a major calorie expenditure regulator.

With posture stabilization muscles, as with almost everything else in the human body, the reality is this: if you don’t use them, you lose them.

What is a reasonable vitamin D level?

The figure and table below are from Vieth (1999); one of the most widely cited articles on vitamin D. The figure shows the gradual increase in blood concentrations of 25-Hydroxyvitamin, or 25(OH)D, following the start of daily vitamin D3 supplementation of 10,000 IU/day. The table shows the average levels for people living and/or working in sun-rich environments; vitamin D3 is produced by the skin based on sun exposure.

25(OH)D is also referred to as calcidiol. It is a pre-hormone that is produced by the liver based on vitamin D3. To convert from nmol/L to ng/mL, divide by 2.496. The figure suggests that levels start to plateau at around 1 month after the beginning of supplementation, reaching a point of saturation after 2-3 months. Without supplementation or sunlight exposure, levels should go down at a comparable rate. The maximum average level shown on the table is 163 nmol/L (65 ng/mL), and refers to a sample of lifeguards.

From the figure we can infer that people on average will plateau at approximately 130 nmol/L, after months of 10,000 IU/d supplementation. That is 52 ng/mL. Assuming a normal distribution with a standard deviation of about 20 percent of the range of average levels, we can expect about 68 percent of the population to be in the 42 to 63 ng/mL range.

This might be the range most of us should expect to be in at an intake of 10,000 IU/d. This is the equivalent to the body’s own natural production through sun exposure.

Approximately 32 percent of the population can be expected to be outside this range. A person who is two standard deviations (SDs) above the mean (i.e., average) would be at around 73 ng/mL. Three SDs above the mean would be 83 ng/mL. Two SDs below the mean would be 31 ng/mL.

There are other factors that may affect levels. For example, being overweight tends to reduce them. Excess cortisol production, from stress, may also reduce them.

Supplementing beyond 10,000 IU/d to reach levels much higher than those in the range of 42 to 63 ng/mL may not be optimal. Interestingly, one cannot overdose through sun exposure, and the idea that people do not produce vitamin D3 after 40 years of age is a myth.

One would be taking in about 14,000 IU/d of vitamin D3 by combining sun exposure with a supplemental dose of 4,000 IU/d. Clear signs of toxicity may not occur until one reaches 50,000 IU/d. Still, one may develop other complications, such as kidney stones, at levels significantly above 10,000 IU/d.

See this post by Chris Masterjohn, which makes a different argument, but with somewhat similar conclusions. Chris points out that there is a point of saturation above which the liver is unable to properly hydroxylate vitamin D3 to produce 25(OH)D.

How likely it is that a person will develop complications like kidney stones at levels above 10,000 IU/d, and what the danger threshold level could be, are hard to guess. Kidney stone incidence is a sensitive measure of possible problems; but it is, by itself, an unreliable measure. The reason is that it is caused by factors that are correlated with high levels of vitamin D, where those levels may not be the problem.

There is some evidence that kidney stones are associated with living in sunny regions. This is not, in my view, due to high levels of vitamin D3 production from sunlight. Kidney stones are also associated with chronic dehydration, and populations living in sunny regions may be at a higher than average risk of chronic dehydration. This is particularly true for sunny regions that are also very hot and/or dry.

Reference

Vieth, R. (1999). Vitamin D supplementation, 25-hydroxyvitamin D concentrations, and safety. American Journal of Clinical Nutrition, 69(5), 842-856.

Cortisol response to stress is much more elevated with ingestion of glucose than with protein or fat

Cortisol is a hormone that does a number of different things; a jack of all trades among hormones, so to speak. It tells the liver to produce glucose, preventing hypoglycemia. It also tells the liver to synthesize glycogen, which is in some ways the opposite of producing glucose. It tells the stomach to secret gastric acid. It is an anti-diuretic hormone. It suppresses the immune system, which is why it is frequently used to reduce inflammation, and treat allergies and various autoimmune diseases. It jump-starts an increase in free fatty acids in circulation, thus helping provide an important source of energy for endurance exercise.

Cortisol, together with epinephrine (a.k.a. adrenaline), even contributes to the creation of surprise-induced memories. It is because of this action of cortisol that Americans reading this post, especially those who lived in the East Coast in 2001, remember vividly where they were, what they were doing, and who they were with, when they first heard about the September 11, 2001 Attacks. I was living in Philadelphia at the time, and I remember those details very vividly, even though the Attacks happened almost 10 years ago. That is one of the fascinating things that cortisol does; it instantaneously turns short-term contextual memories temporally associated with a surprise event (i.e., a few minutes before and after the event) into long-term memories.

Similarly to insulin, you don’t want cortisol levels to be more elevated than they should naturally be. Natural levels being those experienced by our hominid ancestors on a regular basis. You need cortisol, but you don’t need too much of it. Many tissues in the body become resistant to hormones that are more elevated than they should be, like insulin and leptin, and this is also true for cortisol. It is a bit like people constantly shouting in your ears; after a while you cover your ears, or they get damaged, so people have to shout louder. If you frequently have acute elevations of cortisol levels, they may become chronically elevated due to cortisol resistance.

Chronically elevated cortisol levels are associated with the metabolic syndrome, the hallmark of the degenerative diseases of civilization.

Stress causes elevated cortisol levels. And those levels are significantly elevated if you consume foods that lead to a high blood glucose response after a meal. That is what an interesting experimental study by Gonzalez-Bono and colleagues (2002) suggests. The full reference and link to the study are at the end of this post. They used glucose, but we can reasonably conclude based on glucose metabolism research that foods rich in refined carbohydrates and sugars would have a very similar effect. If we think about the typical American breakfast, possibly even a stronger effect.

In order to do their study they needed to put the participants under stress. To cause stress the researchers did what many college professors have their students do at the end of the semester, which is also something that trial lawyers and preachers are good at, and something that most people hate doing. You guessed it. The researchers had their subjects do, essentially, some public speaking. The experimental task they used was a variation of the “Trier Social Stress Test” (TSST). The researchers asked the participants to conduct a 5-minute speech task and a 5-minute mental arithmetic task in front of an audience.

The participants were 37 healthy men who fasted for at least 8 h prior to the study. They were randomly assigned to one of four groups. The glucose group consumed 75 g of glucose dissolved in water. The fat group consumed 200 g of avocado. The protein group drank 83 g of proteins dissolved in water. The fourth group, the water group, drank plain water.

From a real world perspective, the fat and protein groups, unlike the glucose group, were arguably overloaded with their respective nutrients. Many people would not normally consume that much fat or protein in one single meal. This makes the results even more interesting, because it seems that fat and protein lead to virtually the same response as water, regardless of the amount ingested. The table below shows the cortisol responses for all groups.

As you can see, the cortisol response for the glucose group is a lot more elevated. How much more elevated? In the inner square at the top-left part of the figure you have the areas under the curve (AUC), which are essentially the estimates of the integrals of the cortisol curves for each of the groups. Usually AUC is a key measure when one looks at the potential negative impact of the elevated levels of a substance in the blood. Note that the cortisol AUC for the glucose group is much larger, about two times larger, than the cortisol AUCs for the other groups.

When one has a morning car commute, what is going to happen? Typically cortisol levels will be elevated, unless the commute is uneventful and done completely on “automatic pilot”; which is not very common, as people cut off in front of each other, make irritating mistakes etc.

What if, before that commute, one eats a “solid” breakfast with plenty of “healthy” sugary cereal covered with honey, a glass of “healthy” low-fat milk (of course, because fat “raises bad cholesterol”), and maybe three pancakes covered with syrup?

Cortisol levels will be much more elevated.

Doing this often, maybe after several years a person will become eligible for death by sudden cardiac arrest while doing some light activity.

Reference:

Gonzalez-Bono, E., Rohleder, N., Hellhammer, D.H., Salvador, A., & Kirschbaum, C. (2002). Glucose but Not Protein or Fat Load Amplifies the Cortisol Response to Psychosocial Stress. Hormones and Behavior, 41(3), 328–333.

Intervew with Chris Kresser of The Healthy Skeptic

Last week, I did an audio interview with Chris Kresser of The Healthy Skeptic, on the topic of obesity. We put some preparation into it, and I think it's my best interview yet. Chris was a gracious host. We covered some interesting ground, including (list copied from Chris's post):

• The little known causes of the obesity epidemic
• Why the common weight loss advice to “eat less and exercise more” isn’t effective
• The long-term results of various weight loss diets (low-carb, low-fat, etc.)
• The body-fat setpoint and its relevance to weight regulation
• The importance of gut flora in weight regulation
• The role of industrial seed oils in the obesity epidemic
• Obesity as immunological and inflammatory disease
• Strategies for preventing weight gain and promoting weight loss

Some of the information we discussed is not yet available on my blog. You can listen to the interview through Chris's post here.

Cheese consumption, visceral fat, and adiponectin levels

Several bacteria feed on lactose, the sugar found in milk, producing cheese for us as a byproduct of their feeding. This is why traditionally made cheese can be eaten by those who are lactose intolerant. Cheese consumption predates written history. This of course does not refer to processed cheese, frequently sold under the name “American cheese”. Technically speaking, processed cheese is not “real” cheese.

One reasonably reliable way of differentiating between traditional and processed cheese varieties is to look for holes. Cheese-making bacteria produce a gas, carbon dioxide, which leaves holes in cheese. There are exceptions though, and sometimes the holes are very small, giving the impression of no holes. Another good way is to look at the label and the price; usually processed cheese is labeled as such, and is cheaper than traditionally made cheese.

Cheese does not normally spoil; it ages. When vacuum-wrapped, cheese is essentially in “suspended animation”. After opening it, it is a good idea to store it in such a way as to allow it to “breathe”, or continue aging. Wax paper does a fine job at that. This property, extended aging, has made cheese a very useful source of nutrition for travelers in ancient times. It was reportedly consumed in large quantities by Roman soldiers.

Walther and colleagues (2008) provide a good review of the role of cheese in nutrition and health. The full reference is at the end of this post. They point out empirical evidence that cheese, particularly that produced with Lactobacillus helveticus (e.g., Gouda and Swiss cheese), contributes to lowering blood pressure, stimulates growth and development of lean body tissues (e.g., muscle), and has anti-carcinogenic properties.

The health-promoting effects of cheese were also reviewed by Higurashi and colleagues (2007), who hypothesized that those effects may be in part due to the intermediate positive effects of cheese on adiponectin and visceral body fat levels. They conducted a study with rats that supports those hypotheses.

In the study, they fed two groups of rats an isocaloric diet with 20 percent of fat, 20 percent of protein, and 60 percent of carbohydrate (in the form of sucrose). In one group, the treatment group, Gouda cheese (produced with Lactobacillus helveticus) was the main source of protein. In the other group, the control group, isolated casein was the main source of protein. The researchers were careful to avoid confounding variables; e.g., they adjusted the vitamin and mineral intake in the groups so as to match them.

The table below (click to enlarge) shows initial and final body weight, liver weight, and abdominal fat for both groups of rats. As you can see, the rats more than quadrupled in weight by the end of the 8-weight experiment! Abdominal fat was lower in the cheese group; one type of visceral fat, mesenteric, was significantly lower. Whole body weight-adjusted liver weight was higher in the cheese group. Liver weight increase is often associated with increased muscle mass. The rats in the cheese group were a little heavier on average, even though they had less abdominal fat.

The figure below shows adiponectin levels at the 4-week and 8-week marks. While adiponectin levels decreased in both groups, which was to be expected given the massive gain in weight (and probably body fat mass), only in the casein group the decrease in adiponectin was significant. In fact, the relatively small decrease in the cheese group is a bit surprising given the increase in weight observed.

If we could extrapolate these findings to humans, and this is a big “if”, one could argue that cheese has some significant health-promoting effects. There is one small problem with this study though. To ensure that the rats consumed the same number of calories, the rats in the casein group were fed slightly more sucrose. The difference was very small though; arguably not enough to explain the final outcomes.

This study is interesting because the main protein in cheese is actually casein, and also because casein powders are often favored by those wanting to put on muscle as part of a weight training program. This study suggests that the cheese-ripening process induced by Lactobacillus helveticus may yield compounds that are particularly health-promoting in three main ways – maintaining adiponectin levels; possibly increasing muscle mass; and reducing visceral fat gain, even in the presence of significant weight gain. In humans, reduced circulating adiponectin and increased visceral fat are strongly associated with the metabolic syndrome.

One caveat: if you think that eating cheese may help wipe out that stubborn abdominal fat, think again. This is a topic for another post. But, briefly, this study suggests that cheese consumption may help reduce visceral fat. Visceral fat, however, is generally fairly easy to mobilize (i.e., burn); much easier than the stubborn subcutaneous body fat that accumulates in the lower abdomen of middle-aged men and women. In middle-aged women, stubborn subcutaneous fat also accumulates in the hips and thighs.

Could eating Gouda cheese, together with other interventions (e.g., exercise), become a new weapon against the metabolic syndrome?

References:

Higurashi, S., Kunieda, Y., Matsuyama, H., & Kawakami, H. (2007). Effect of cheese consumption on the accumulation of abdominal adipose and decrease in serum adiponectin levels in rats fed a calorie dense diet. International Dairy Journal, 17(10), 1224–1231.

Walther, B., Schmid, A., Sieber, R., & Wehrmüller, K. (2008). Cheese in nutrition and health. Dairy Science Technology, 88(4), 389-405.

Saturated Fat and Insulin Sensitivity, Again

A new study was recently published exploring the effect of diet composition on insulin sensitivity and other factors in humans (1). 29 men with metabolic syndrome-- including abdominal obesity, low HDL, high blood pressure, high triglycerides, and high fasting glucose-- were fed one of four diets for 12 weeks:

1. A diet containing 38% fat: 16% saturated (SFA), 12% monounsaturated (MUFA) and 6% polyunsaturated (PUFA)
   
2. A diet containing 38% fat: 8% SFA, 20% MUFA and 6% PUFA
3. A diet high in unrefined carbohydrate, containing 28% fat (8% SFA, 11% MUFA and 6% PUFA)
4. A diet high in unrefined carbohydrate, containing 28% fat (8% SFA, 11% MUFA and 6% PUFA) and an omega-3 supplement (1.24 g/day EPA and DHA)
   

After 12 weeks, insulin sensitivity, fasting glucose, glucose tolerance, and blood pressure did not change significantly in any of the four groups. This is consistent with the majority of the studies that have examined this question, although somehow the idea persists that saturated fat impairs insulin sensitivity. I discussed this in more detail in a recent post (2).

The paper that's typically cited by people who wish to defend the idea that saturated fat impairs insulin sensitivity is the KANWU study (3). In this study, investigators found no significant difference in insulin sensitivity between volunteers fed primarily SFA or MUFA for 12 weeks. You wouldn't realize this from the abstract however; you have to look very closely at the p-values in table 4.

One of the questions one could legitimately ask, however, is whether SFA have a different effect on people with metabolic syndrome. Maybe the inflammation and metabolic problems they already have make them more sensitive to the hypothetical damaging effects of SFA? That's the question the first study addressed, and it appears that SFA are not uniquely harmful to insulin signaling in those with metabolic syndrome on the timescale tested.

It also showed that the different diets did not alter the proportion of blood fats being burned in muscle, as opposed to being stored in fat tissue. The human body is a remarkably adaptable biological machine that can make the best of a variety of nutrient inputs, at least over the course of 12 weeks. Metabolic damage takes decades to accumulate, and in my opinion is more dependent on food quality than macronutrient composition. Once metabolic dysfunction is established, some people may benefit from carbohydrate restriction, however.

Blood glucose variations in normal individuals: A chaotic mess

I love statistics. But statistics is the science that will tell you that each person in a group of 20 people ate half a chicken per week over six months, until you realize that 10 died because they ate nothing while the other 10 ate a full chicken every week.

Statistics is the science that will tell you that there is an “association” between these two variables: my weight from 1 to 20 years of age, and the price of gasoline during that period. These two variables are indeed highly correlated, by neither has influenced the other in any way.

This is why I often like to see the underlying numbers when I am told that such and such health measure on average is this or that, or that this or that disease is associated with elevated consumption of whatever. Statistical results must be interpreted carefully. Lying with statistics is very easy.

A case in point is that of blood glucose variations among normal individuals. Try plotting them on graphs. What do you see? A chaotic mess, even when the individuals are pre-screened to exclude anybody with blood glucose abnormalities that would even hint at pre-diabetes. You see wild fluctuations that, while not going up to levels like 200 mg/dl, are much less predictable than many people are told they should be.

Blood glucose levels are influenced by so many factors (Elliott & Elliott, 2009) that I would be surprised if they were as smooth as those in graphs that are frequently used to show how blood glucose is supposed to vary in healthy individuals. Often we see a flat line up until the time of a meal, when the line curves up rapidly and then goes down quickly. It usually peaks at around 140 mg/dl, dropping well below 120 mg/dl after 2 hours.

Those smooth graphs are usually obtained through algorithms that have statistical methods at their core. The algorithms are designed to generate a smooth representations of scattered or disorganized data points. A little bit like the algorithms in software tools that plot best-fit regression curves passing through scattered points (e.g., warppls.com).

The picture below (click on it to enlarge) is from a 2006 symposium presentation by Prof. J.S. Christiansen, who is a widely cited diabetes researcher. The whole presentation is available from: www.diabetes-symposium.org. It shows the blood glucose variations of 21 young and normal individuals, based on data collected over a period of 2 days. Each individual is represented by a different color. The points on each curve are actually averages of two blood glucose measurements; the original measurements themselves vary even more chaotically.

As you can see from the picture above, each individual has a unique set of responses to main meals, which are represented by the three main blood glucose peaks. Overall, blood glucose levels vary from about 50 to 170 mg/dl, and in several cases remain above 120 mg/dl after 2 hours since a large meal. They vary somewhat chaotically during the night as well, often getting up to around 110 mg/dl.

And these are only 21 individuals, not 100 or 1000. Again, these individuals were all normal (i.e., normoglycemic, in medical research parlance), with an average glycated hemoglobin (HbA1c) of 5 percent, and a range of variation of HbA1c of 4.3 to 5.4 percent.

We can safely assume that these individuals were not on a low carbohydrate diet. The spikes in blood glucose after meals suggest that they were eating foods loaded with refined carbohydrates and/or sugars, particularly for breakfast. So, we can also safely assume that they were somewhat "desensitized" (in terms of glucose response) to those types of foods. Someone who had been on a low carbohydrate diet for a while, and who would thus be more sensitive, would have had even wilder blood glucose variations in response to the same meals.

Many people measure their glucose levels throughout the day with portable glucometers, and quite a few are likely to self-diagnose as pre-diabetics when they see something that they think is a “red flag”. Examples are a blood glucose level peaking at 165 mg/dl, or remaining above 120 mg/dl after 2 hours passed since a meal. Another example is a level of 110 mg/dl when they wake up very early to go to work, after several hours of fasting.

As you can see from the picture above, these “red flag” events do occur in young normoglycemic individuals.

If seeing “red flags” helps people remove refined carbohydrates and sugars from their diet, then fine.

But it may also cause them unnecessary chronic stress, and stress can kill.

Reference:

Elliott, W.H., & Elliott, D.C. (2009). Biochemistry and molecular biology. 4th Edition. New York: NY: Oxford University Press.

Blood glucose control before age 55 may increase your chances of living beyond 90

I have recently read an interesting study by Yashin and colleagues (2009) at Duke University’s Center for Population Health and Aging. (The full reference to the article, and a link, are at the end of this post.) This study is a gem with some rough edges, and some interesting implications.

The study uses data from the Framingham Heart Study (FHS). The FHS, which started in the late 1940s, recruited 5209 healthy participants (2336 males and 2873 females), aged 28 to 62, in the town of Framingham, Massachusetts. At the time of Yashin and colleagues’ article publication, there were 993 surviving participants.

I rearranged figure 2 from the Yashin and colleagues article so that the two graphs (for females and males) appeared one beside the other. The result is shown below (click on it to enlarge); the caption at the bottom-right corner refers to both graphs. The figure shows the age-related trajectory of blood glucose levels, grouped by lifespan (LS), starting at age 40.

As you can see from the figure above, blood glucose levels increase with age, even for long-lived individuals (LS > 90). The increases follow a U-curve (a.k.a. J-curve) pattern; the beginning of the right side of a U curve, to be more precise. The main difference in the trajectories of the blood glucose levels is that as lifespan increases, so does the width of the U curve. In other words, in long-lived people, blood glucose increases slowly with age; particularly up to 55 years of age, when it starts increasing more rapidly.

Now, here is one of the rough edges of this study. The authors do not provide standard deviations. You can ignore the error bars around the points on the graph; they are not standard deviations. They are standard errors, which are much lower than the corresponding standard deviations. Standard errors are calculated by dividing the standard deviations by the square root of the sample sizes for each trajectory point (which the authors do not provide either), so they go up with age since progressively smaller numbers of individuals reach advanced ages.

So, no need to worry if your blood glucose levels are higher than those shown on the vertical axes of the graphs. (I will comment more on those numbers below.) Not everybody who lived beyond 90 had a blood glucose of around 80 mg/dl at age 40. I wouldn't be surprised if about 2/3 of the long-lived participants had blood glucose levels in the range of 65 to 95 at that age.

Here is another rough edge. It is pretty clear that the authors’ main independent variable (i.e., health predictor) in this study is average blood glucose, which they refer to simply as “blood glucose”. However, the measure of blood glucose in the FHS is a very rough estimation of average blood glucose, because they measured blood glucose levels at random times during the day. These measurements, when averaged, are closer to fasting blood glucose levels than to average blood glucose levels.

A more reliable measure of average blood glucose levels is that of glycated hemoglobin (HbA1c). Blood glucose glycates (i.e., sticks to, like most sugary substances) hemoglobin, a protein found in red blood cells. Since red blood cells are relatively long-lived, with a turnover of about 3 months, HbA1c (given in percentages) is a good indicator of average blood glucose levels (if you don’t suffer from anemia or a few other blood abnormalities). Based on HbA1c, one can then estimate his or her average blood glucose level for the previous 3 months before the test, using one of the following equations, depending on whether the measurement is in mg/dl or mmol/l.

    Average blood glucose (mg/dl) = 28.7 × HbA1c − 46.7

    Average blood glucose (mmol/l) = 1.59 × HbA1c − 2.59

The table below, from Wikipedia, shows average blood glucose levels corresponding to various HbA1c values. As you can see, they are generally higher than the corresponding fasting blood glucose levels would normally be (the latter is what the values on the vertical axes of the graphs above from Yashin and colleagues’ study roughly measure). This is to be expected, because blood glucose levels vary a lot during the day, and are often transitorily high in response to food intake and fluctuations in various hormones. Growth hormone, cortisol and noradrenaline are examples of hormones that increase blood glucose. Only one hormone effectively decreases blood glucose levels, insulin, by stimulating glucose uptake and storage as glycogen and fat.

Nevertheless, one can reasonably expect fasting blood glucose levels to have been highly correlated with average blood glucose levels in the sample. So, in my opinion, the graphs above showing age-related blood glucose trajectories are still valid, in terms of their overall shape, but the values on the vertical axes should have been measured differently, perhaps using the formulas above.

Ironically, those who achieve low average blood glucose levels (measured based on HbA1c) by adopting a low carbohydrate diet (one of the most effective ways) frequently have somewhat high fasting blood glucose levels because of physiological (or benign) insulin resistance. Their body is primed to burn fat for energy, not glucose. Thus when growth hormone levels spike in the morning, so do blood glucose levels, as muscle cells are in glucose rejection mode. This is a benign version of the dawn effect (a.k.a. dawn phenomenon), which happens with quite a few low carbohydrate dieters, particularly with those who are deep in ketosis at dawn.

Yashin and colleagues also modeled relative risk of death based on blood glucose levels, using a fairly sophisticated mathematical model that takes into consideration U-curve relationships. What they found is intuitively appealing, and is illustrated by the two graphs at the bottom of the figure below. The graphs show how the relative risks (e.g., 1.05, on the topmost dashed line on the both graphs) associated with various ranges of blood glucose levels vary with age, for both females and males.

What the graphs above are telling us is that once you reach old age, controlling for blood sugar levels is not as effective as doing it earlier, because you are more likely to die from what the authors refer to as “other causes”. For example, at the age of 90, having a blood glucose of 150 mg/dl (corrected for the measurement problem noted earlier, this would be perhaps 165 mg/dl, from HbA1c values) is likely to increase your risk of death by only 5 percent. The graphs account for the facts that: (a) blood glucose levels naturally increase with age, and (b) fewer people survive as age progresses. So having that level of blood glucose at age 60 would significantly increase relative risk of death at that age; this is not shown on the graph, but can be inferred.

Here is a final rough edge of this study. From what I could gather from the underlying equations, the relative risks shown above do not account for the effect of high blood glucose levels earlier in life on relative risk of death later in life. This is a problem, even though it does not completely invalidate the conclusion above. As noted by several people (including Gary Taubes in his book Good Calories, Bad Calories), many of the diseases associated with high blood sugar levels (e.g., cancer) often take as much as 20 years of high blood sugar levels to develop. So the relative risks shown above underestimate the effect of high blood glucose levels earlier in life.

Do the long-lived participants have some natural protection against accelerated increases in blood sugar levels, or was it their diet and lifestyle that protected them? This question cannot be answered based on the study.

Assuming that their diet and lifestyle protected them, it is reasonable to argue that: (a) if you start controlling your average blood sugar levels well before you reach the age of 55, you may significantly increase your chances of living beyond the age of 90; (b) it is likely that your blood glucose levels will go up with age, but if you can manage to slow down that progression, you will increase your chances of living a longer and healthier life; (c) you should focus your control on reliable measures of average blood glucose levels, such as HbA1c, not fasting blood glucose levels (postprandial glucose levels are also a good option, because they contribute a lot to HbA1c increases); and (d) it is never too late to start controlling your blood glucose levels, but the more you wait, the bigger is the risk.

References:

Taubes, G. (2007). Good calories, bad calories: Challenging the conventional wisdom on diet, weight control, and disease. New York, NY: Alfred A. Knopf.

Yashin, A.I., Ukraintseva, S.V., Arbeev, K.G., Akushevich, I., Arbeeva, L.S., & Kulminski, A.M. (2009). Maintaining physiological state for exceptional survival: What is the normal level of blood glucose and does it change with age? Mechanisms of Ageing and Development, 130(9), 611-618.

Dissolve Away those Pesky Bones with Corn Oil

I just read an interesting paper from Gabriel Fernandes's group at the University of Texas. It's titled "High fat diet-induced animal model of age-associated obesity and osteoporosis". I was expecting this to be the usual "we fed mice industrial lard for 60% of calories and they got sick" paper, but I was pleasantly surprised. From the introduction:

CO [corn oil] is known to promote bone loss, obesity, impaired glucose tolerance, insulin resistance and thus represents a useful model for studying the early stages in the development of obesity, hyperglycemia, Type 2 diabetes [23] and osteoporosis. We have used omega-6 fatty acids enriched diet as a fat source which is commonly observed in today's Western diets basically responsible for the pathogenesis of many diseases [24].

Just 10% of the diet as corn oil (roughly 20% of calories), with no added omega-3, on top of an otherwise poor laboratory diet, caused:

• Obesity
• Osteoporosis
• The replacement of bone marrow with fat cells
  
• Diabetes
• Insulin resistance
  
• Generalized inflammation
• Elevated liver weight (possibly indicating fatty liver)
  

Hmm, some of these sound familiar... We can add them to the findings that omega-6 also promotes various types of cancer in rodents (1).

20% fat is less than the amount it typically takes to make a rodent this sick. This leads me to conclude that corn oil is particularly good at causing mouse versions of some of the most common facets of the "diseases of civilization". It's exceptionally high in omega-6 (linoleic acid) with virtually no omega-3.

Make sure to eat your heart-healthy corn oil! It's made in the USA, dirt cheap and it even lowers cholesterol!

Vitamin D levels: Sunlight, age, and toxicity

Calcidiol is a pre-hormone that is produced based on vitamin D3 in the liver. Blood concentration of calcidiol is considered to be a reliable indicator of vitamin D status. In the research literature, calcidiol is usually referred to as 25-Hydroxyvitamin or 25(OH)D. Calcidiol is converted in the kidneys into calcitriol, which is the active form of vitamin D.

The table below (from: Vieth, 1999; full reference at the end of this post; click on it to enlarge), shows the average blood vitamin D levels of people living or working in sun-rich environments. To convert from nmol/L to ng/mL, divide by 2.496. For example, 100 nmol/L = 100 / 2.496 ng/mL = 40.1 ng/mL. At the time of this writing, Vieth (1999) had 692 citations on Google Scholar, and probably more than that on Web of Science. This article has had, and continues having, a high impact among researchers.

The maximum average level of blood (or serum) vitamin D shown in the table is 163 nmol/L (65 ng/mL). Given that the human body produces vitamin D naturally from sunlight, it is reasonable to assume that those blood vitamin D levels are not yet at the toxic range. In fact, one of the individuals, a farmer in Puerto Rico, had a level of 225 nmol/L (90 ng/mL). That individual had no signs of toxicity.

Several studies show that pre-sunburn full-body exposure to sunlight is equivalent to an oral vitamin D intake of approximately 250 µg (10,000 IU).

In spite of claims to the contrary, vitamin D production based on sunlight does not cease after 40 years of age or so. Studies reviewed by Vieth suggest that among the elderly (i.e., those aged 65 or above) pre-sunburn full-body exposure to sunlight is equivalent to an oral vitamin D intake of 218 µg (8,700 IU).

Sunlight-induced vitamin D production does seem to decrease with age, but not dramatically.

Post-sunburn sunlight exposure does not increase vitamin D production. Since each person is different, a good rule of thumb to estimate the number of minutes of sunlight exposure needed to maximize vitamin D production is the number of minutes preceding sunburn. For a light-skinned person, this can be as little as 7 minutes.

Vitamin D accumulation in the body follows a battery-like pattern, increasing and decreasing gradually. The figure below, from Vieth’s article, shows the gradual increase in blood vitamin D concentrations following the start of daily supplementation. This suggests that levels start to plateau at around 1 month, with higher levels reaching a plateau after 2 months.

While sunlight exposure does not lead to toxic levels of vitamin D, oral intake may. Below is a figure, also from Vieth’s article, that plots blood levels of vitamin D against oral intake amounts. The X’s indicate points at which intoxication symptoms were observed. While typically intoxication starts at the 50,000 IU intake level, one individual displayed signs of intoxication at 10,000 IU. That individual received a megadose that was supposed to provide vitamin D for an extended period of time.

Non-toxic levels of 10,000 IU are achieved naturally through sunlight exposure. This applies to modern humans and probably our Paleolithic ancestors. Yet, modern humans normally limit their sun exposure and intake of vitamin D to levels (400 IU) that are only effective to avoid osteomalacia, the softening of the bones due to poor mineralization.

Very likely the natural production of 10,000 IU based on sunlight was adaptive in our evolutionary past, and also necessary for good health today. This is consistent with the many reports of diseases associated with chronic vitamin D deficiency, even at levels that avoid osteomalacia. Among those diseases are: hypertension, tuberculosis, various types of cancer, gingivitis, multiple sclerosis, chronic inflammation, seasonal affective disorder, and premature senescence.

Reference:

Reinhold Vieth (May 1999). Vitamin D supplementation, 25-hydroxyvitamin D concentrations, and safety. American Journal of Clinical Nutrition, Vol. 69, No. 5, 842-856.

How much vitamin D? Vitamin D Council's recommendations

Since my recent post on problems related to vitamin D deficiency and excess I received several questions. I have also participated in several discussions in other blogs related to vitamin D in the past few days.

There is a lot of consensus about vitamin D deficiency being a problem, but not much about vitamin D in excess being a problem as well.

Some bloggers recommend a lot of supplementation, which may be dangerous because: (a) our body evolved to obtain most of its vitamin D from a combination of sunlight exposure and cholesterol, and thus body accumulation regulation mechanisms are not designed to deal with excessive oral supplementation; and (b) vitamin D, like many fat-soluble vitamins, accumulates in fat tissue over time, and is not easily eliminated by the body when in excess.

The Vitamin D Council has the following general recommendation regarding supplementation:

Take an average of 5,000 IU a day, year-round, if you have some sun exposure. If you have little, or no, sun exposure you will need to take at least 5,000 IU per day. How much more depends on your latitude of residence, skin pigmentation, and body weight. Generally speaking, the further you live away from the equator, the darker your skin, and/or the more you weigh, the more you will have to take to maintain healthy blood levels.

They also provide a specific example:

For example, Dr. Cannell lives at latitude 32 degrees, weighs 220 pounds, and has fair skin. In the late fall and winter he takes 5,000 IU per day. In the early fall and spring he takes 2,000 IU per day. In the summer he regularly sunbathes for a few minutes most days and thus takes no vitamin D on those days in the summer.

For those who have problems with supplementation, here is what Dr. Cannell, President of the Vitamin D Council, has to say:

For people who have trouble with supplements, I recommend sunbathing during the warmer months and sun tanning parlors in the colder months. Yes, sun tanning parlors make vitamin D, the most is made by the older type beds. Another possibility is a Sperti vitamin D lamp.

One thing to bear in mind is that if your diet is rich in refined carbohydrates and sugars, you need to change that before you are able to properly manage your vitamin D levels. You need to remove refined carbohydrates and sugars from your diet. No more white bread, bagels, doughnuts, table sugar, sodas sweetened with high-fructose corn syrup; just to name a few of the main culprits.

In fact, a diet rich in refined carbohydrates and sugars, in and of itself, may be one of the reasons of a person''s vitamin D deficiency in the case of appropriate sunlight exposure or dietary intake, and even of excessive levels of vitamin D accumulating in the body in the case of heavy supplementation.

The hormonal responses induced by a diet  rich in  refined carbohydrates and sugars promote fat deposition and, at the same time, prevent fat degradation. That is, you tend to put on body fat easily, and you tend to have trouble burning that fat.

This causes a "hoarding" effect which leads to an increase in vitamin D stored in the body, and at the same time reduces the levels of vitamin D in circulation. This is because vitamin D is stored in body fat tissue, and has a long half-life, which means that it accumulates (as in a battery) and then slowly gets released into the bloodstream for use, as body fat is used as a source of energy.

It should not be a big surprise that vitamin D deficiency problems correlate strongly with problems associated with heavy consumption of refined carbohydrates and sugars. Both lead to symptoms that are eerily similar; several of which are the symptoms of the metabolic syndrome.

Growth hormone: The fountain of youth

Growth hormone, also known as human growth hormone, seems to be implicated in a number of metabolic conditions associated with aging, and, more generally, poor health.

In adults, growth hormone deficiency is associated with: decreased calcium retention and osteoporosis, loss of muscle mass, increased fat deposition, decreased protein synthesis, and immunodeficiency. In children, growth hormone deficiency is associated with stunted growth.

Levels of growth hormones decline with age, and their decrease is believed to contribute to the aging process. Abdominal obesity is associated with low levels of growth hormone, and is also associated with the onset of the metabolic syndrome, a precursor of diabetes and cardiovascular disease.

While there are many treatments in the market that include exogenous administration of growth hormones (e.g., through injection), there are several natural ways in which growth hormone levels can be increased. These natural ways can often lead to more effective and sustainable results than prescription drugs.

For example, fasting stimulates the natural production of growth hormone. So does vigorous exercise, particularly resistance exercise with a strong anaerobic component (not cardio though). And, to the surprise of many people, deep sleep stimulates the natural production of growth hormone, perhaps more than anything else. (Although only once every 24 hours; sleeping all day does not seem to work.)

In fact, during a 24-hour period, growth hormone typically varies in pulses, or cycles. The pulses are somewhat uniformly distributed during the day, with a peak occurring at night. The graph below (source: Fleck & Kraemer, 2004) plots the typical variation of growth hormone during a 12-hour period, including the deep sleep period.

As you can see, growth hormone peaks during deep sleep; which is achieved a few hours after one goes to bed, and not too long before one wakes up.

By the way, if you want to know more about human physiology and metabolism, forget about popular diet and exercise books. Next to peer-reviewed academic articles (which are often hard to read), the best sources are college textbooks used in courses on physical education, nutrition, endocrinology, and related topics. The book from which the graph above was taken (Fleck & Kraemer, 2004), is a superb example of that.

Reference:

Fleck, S.J., & Kraemer, W.J. (2004). Designing resistance training programs. Champaign, IL: Human Kinetics.