Salt Experiment Results

As previously reported, I spent a few weeks this summer conducting a self-experiment on salt sensitivity and blood pressure. The experiment included a three week phase on a low carb whole foods diet with no added salt, followed by a moderately extreme salt loading phase. This post is a summary of my results.

I learned a lot from the experiment and came out of it with at least one bit of useful information. Will I try to restrict salt in my diet? Na (sorry, couldn't resist). I don't think salt restriction can work for me. From now on I will ensure that I get sufficient salt on a daily basis.

Executive Summary

Cutting to the chase, these are the main points I learned over the course of the experiment, roughly sorted from most to least interesting.

1. Salt restriction caused impaired thermoregulation. In hot weather, my cardiovascular system was not able to sufficiently lower my body temperature. This resulted in an elevated heart rate and hypethermia (up to 101.5 degrees in one instance). This can be dangerous, so be careful if you try this at home.

2. No clinically meaningful change in blood pressure. Systolic pressure was unchanged, though salt loading may have caused a small rise in diastolic pressure. This does not rule out long term negative effects from chronic salt loading (see discussion below), but it does show that, as previously discussed, my kidneys seem to basically work and can regulate my blood pressure through the maintenance of fluid and electrolyte balance in response to changes in my sodium intake.

3. Possible susceptibility to skin infections. Three days into the salt restriction phase, I came down with what was probably a staph infection in my right eyelid. This responded to antibiotics but it came back once I went off them. Since adding back salt I have had no problems with skin infections and no more antibiotics.

4. Possible strength loss. I did not perform well in the gym on my usual strength training program.

5. My taste for salt adapts quickly to restriction and loading. I experienced no cravings even when my sodium intake was too low. I can't just "listen to my body". Likewise, while the salt loading phase was difficult for the first two or three days, my taste rapidly adjusted to the added salt.

6. Bodyweight changes. I experienced substantial changes in body fluid levels (e.g. 6 pound weight gain within two hours of the transition from the salt restriction to the salt loading phase).

Conclusion: A low carb paleo diet must include added salt (for me). Can others do without? Perhaps, and some scientists such as Loren Cordain and Tim Noakes (e.g. this podcast episode 18 at 1:03:50) seem to think they can. Skip ahead to read my further musings on this question.

Study Design

The experiment was conducted in three phases. First, I did a one week lead-in phase (phase I) where I made no changes to diet or salt consumption. The purpose of phase I was to establish a blood pressure baseline through daily morning measurements (see Measurement Methods below).

This was followed by a three-week sodium restricted phase (phase II) during which I did not add any salt to my food. In addition, during phase II only, I avoided naturally salty foods such as shellfish. My sodium intake during phase II was limited to the sodium in the foods I was eating. Note however that there were one or two restaurant meals per week during this time where I was not able to strictly control for added salt. Sodium consumption on phase II was estimated to be between 800mg and 1000mg per day. phase II was originally scheduled for two weeks, but was extended due to the aforementioned infection and antibiotic use.

Finally, phase III was a salt-loading phase during which I added an additional 5 grams of sodium to my diet, for a total of nearly 6 grams of sodium per day including the sodium naturally occurring in my food. The supplemental salt during phase III consisted of hand harvested French Celtic sea salt (Eden Foods, Inc.) and was measured daily on an AMW-1000 digital scale. Because the Eden French Celtic sea salt is approximately 1/3 sodium by weight according to the label, the 5 grams of supplemental sodium per day was provided by approximately 15 grams of sea salt. Note that different varieties of salt will contain different percentages of sodium by weight. Sea salts vary significantly due to variations in residual water content (not, as commonly assumed, by the presence of other minerals). Please consult the label or a friendly analytical chemist for guidance.

The diet throughout this experiment consisted of meat, fish, eggs, coconut oil, butter, and non-starchy vegetables. In addition, I typically consumed a banana, an ounce (28g) of almonds and a bit of dark chocolate each day. Potassium intake was fairly consistent at around 4 g/day. Table 1 shows a typical day's macronutrient intake. Given the macronutrient ratio, I believe it is likely that the diet was ketogenic.

Table 1. Approximate daily macronutrient intake.

Macronutrient	grams	calories	percent (calories)
Carbohydrate	50	200	6.6%
Protein	155	620	20.5%
Fat	245	2205	72.9%
Total		3025	100%

Measurement Methods

Blood pressure was measured daily first thing each morning while seated, with the cuff of an Omron HEM-711 placed on the left upper arm over the brachial artery. I followed guidelines described by Agena et al (see Chart 2 of the linked paper). Each day's blood pressure value was determined by averaging the first three measurements taken that morning.

My first measurement of the day was typically higher than the average of the second and third measurements (systolic: +5, diastolic: +4, average over all three phases). This is referred to as the "alarm reaction" and is related to the more commonly known "white coat syndrome", where the presence of a doctor elicits a stress response and therefore an innacurately high blood pressure reading. My alarm reaction seems to be due to the fact that I get slightly stressed out about seeing what my blood pressure is, even when I measure it myself. Therefore I experience a slight rise in blood pressure while waiting to see the first reading each day. I kept all three readings for this experiment. My "true" normal blood pressure is on average slightly lower than these results which include the first "alarm" reading.

Results

I summarized my qualitative findings in the executive summary above. If you skipped that because you are not an executive, you can go back and read it now. Below are graphs showing my blood pressure and bodyweight during the three phases.

Figure 1: Possible mild elevation in diastolic blood pressure during the salt loading phase. Each point is the average of the three morning blood pressure readings for the day. Red = phase I, green = phase II, blue = phase III. Curves from ggplot2 "geom_smooth()" using default parameters.

Figure 2. No change in systolic blood pressure.

Figure 3: Bodyweight.

Figure 3 shows my daily bodyweight, measured each morning before consumption of any food or fluids. Note that my previous health goal (the 415 deadlift) involved an intentional increase in bodyweight and therefore significant excess calorie consumption. My current diet is lower in calories and Figure 3 therefore should show a long term downward trend in bodyweight.

Salt restriction clearly resulted in a rapid decrease in bodyweight over the first few days of phase II. There appears to be a stabilization towards the end of the salt restricted phase. The salt loading in phase III produced a very large initial weight gain, followed again by stabilization around the same level seen at the end of the salt restriction phase. As salt is primarily stored in bones and extracellular fluids, an increase in salt would be expected to correspond to an increase in extracellular fluid (since the body's bone mass should change slowly). The bodyweight changes shown in Figure 3 therefore reflect changes in extracellular fluid levels. While salt loading at the levels used in phase III produced a large acute change in body fluids, this was restored to normal over approximately 5 days.

Since my extracellular fluid volume was evidently restored within 5 days, it is not surprising that salt loading had no significant effect on my blood pressure. What is somewhat surprising was that there was no evidence of a temporary increase in blood pressure during the few days in which my extracellular fluid volume was in fact elevated. This suggests that there is an additional regulatory element working to restore blood pressure homeostasis at a shorter time scale than the dominant kidney-fluid mechanism previously discussed on the blog here.

Thanks to Mako Hill for guidance with ggplot2, without which these plots would look less nice.

Discussion

This experiment demonstrated to me that a low carb paleo diet with no added salt is potentially dangerous for me. Impaired thermoregulation is a big deal and would have been a life-threatening issue if I had to hunt for my food in a hot climate. Not only was my body temperature elevated in warm weather, but my pulse was elevated as well, suggesting my cardiovascular system was unable to restore my body temperature to normal. I'm clearly not salt sensitive, and I do not function well with a low salt diet. However, genetic studies suggest the ancestral human genotype is associated with high levels of salt sensitivity and ability to function with very low sodium intakes. How did humans evolve these traits? And why don't I seem to have them?

A Faustian Kidney Bargain

Susumo Watanabe has proposed in interesting hypothesis about the evolution of sodium metabolism in hominids. The theory is laid out in a 2002 paper called "Uric Acid, Hominid Evolution, and the Pathogenesis of Salit-Sensitivity," published in the journal Hypertension. It goes something like this. At some point during the evolution of our common ancestor with gorillas and chimpanzees, a series of mutations inactivated the gene for urate oxidase, an enzyme that breaks down uric acid. As a consequence, we have much higher blood levels of uric acid than other mammals. These mutations seem to have occurred between 24 and 8 million years ago, during the miocene, when our ancestors were believed to be subsisting primarily on fruits and leaves. This diet would have been exceptionally low in sodium. Since there is evidence of multiple independent mutations in this gene in multiple primate lineages, it is thought that mutations deactivating urate oxidase were strongly selected.

In rats, uric acid raises blood pressure acutely, but also causes renal vascular disease via renin/angiotensin systems. This over time makes the rats more salt sensitive. If there is very little salt available, salt sensitivity can be a good thing. Watanabe argues that, where salt is scarce, high uric acid is beneficial (via multiple pathways) for preventing blood pressure from going too low.

In addition to causing kidney disease, high uric acid causes other problems, like gout, and is associated with heart disease. So this looks like an engineering tradeoff with a number of downsides, but some benefits in the context of a miocene diet that was even lower in sodium than the lowest current estimates for paleolithic diets. The organism with this adaptation is supposed to partially destroy its kidneys on purpose in order to maintain sufficiently high blood pressure. This miocene environment is long gone. However, it is much easier to break a gene than to put it back together. Our urate oxidase gene has been broken more than once and it would take quite a long time to fix it.

It's kind of a crazy theory. I'm not sure I believe it but it is interesting to think about.

Some Hypotheses

During this experiment, I was eating almost exclusively meat, fish (often with bones), eggs and vegetables, plus added calories from butter, coconut oil and olive oil. The diet was grain, legume and dairy free and, as mentioned, possibly ketogenic. This would be considered by many online diet and health personalities to be a good low carb paleo diet, even though of course processed fats like butter and coconut oil are not Paleolithic foods.

So I want to discuss a few possible ways to resolve the apparent impossibility of eating this way without added salt.

Hypothesis 1: Low Carb, Low Crab, or Low Salt: choose any two

I have been eating a low carb diet, and my experiment suggests that, in that context, low salt is not a good idea. It is possible that a healthy human diet can be either low in carbohydrates or low in salt, but not both.

A great deal of evidence suggests that ketosis was not the norm for our paleolithic ancestors (see e.g. Kuipers et. al. 2012 for a thorough review of paleolithic diet research). In fact it would have been quite a struggle for me to eat this sort of macronutrient ratio without modern refined fats such as butter and coconut oil. Or ready access to marine mammal blubber (but then again the Inuit are not my paleolithic ancestors).

In contrast to the online paleo diet scene, most low carb diet advocates seem to line up behind the recommendation for ample supplementary salt. My result accord with that clinical experience. Low carbohydrate diets are usually said to have a diuretic effect in this community, at least in the initial stages (e.g. M.R. Eades, Jenny Ruhl). It is possible that my problems were caused by the interaction between diet-induced ketosis and salt restriction, and I would have done just fine without salt if I had some more carbohydrates. This hypothesis would be straightforward to test.

In order to keep my sodium intake sufficiently low during the salt restriction phase, I had to remove shellfish such as oysters and mussels from my diet. Crab is also salty and makes for a handy pun. It seems likely that daily shellfish consumption would have pushed my sodium intake into the healthy range. While shellfish does not get much attention these days in the paleo club, there is ample support (again see Kuipers et. al.) that it was an important contributor to actual paleolithic nutrition.

Hypothesis 2: Humans must drink blood. Or eat salt.

File this one in the "teen paranormal romance" department. This hypothesis states that the ancestral human diet was not as low in salt as commonly assumed.

Sodium is the body's primary extracellular cation, and most of it is located in the blood and other extracellular fluids. A pint of blood contains about 1.6 grams of sodium (see, e.g., these livestock reference ranges for blood sodium). That much blood per day should have been more than enough to push me into the healthy range of sodium consumption. On the other hand, salt depletion set in pretty quickly for me (probably 3-4 days), so this hypothesis assumes that fresh blood was consistently available to inland populations that did not have ready access to shellfish or sea water.

I find this hypothesis intriguing because of the fact that my putative ancestors were commanded not to drink blood (Genesis 9:4, Leviticus 17:13, Deuteronomy 12:15-16), and that salt is used in this tradition specifically to remove blood from meat before it is eaten. Presumably blood drinking was outlawed because it was thought to spread diseases and not because of tacky pop-culture connotations. Were my ancestors salting their meat not just for its preservative qualities, but also to make up for the reduction in sodium intake due to their prohibition on drinking blood?

Hypothesis 3: I'm Not (Genetically) a Paleolithic Human

Some say the human genome has hardly changed in the past 10,000 years. However, the hard evidence points to a number of significant evolutionary changes since the advent of agriculture, the classic example being lactase persistance (see Cochran and Harpending 2009 for a thorough argument on the rapidity of recent human evolution). Genes associated with hypertension and salt sensitivity are also apparently under strong evolutionary pressure. Alan Weder discusses this in an article published in 2007 in the journal Hypertension about evolution and hypertension. It is worth reading as an example of excellent science writing.

My experiment clearly demonstrates that I am not salt sensitive. This is not surprising given my European ancestry. As discussed by Weber, the genetics of salt resistance seem to correlate with adaptations to colder climates. It seems possible that in the course of such adaptation, my ancestors lost the ability to function optimally on a low salt diet.

Is a High Salt Diet Safe?

It is possible that, as much of mainstream medicine believes, a high salt diet actually is unhealthy over the long term. There is nothing in this experiment that contradicts that belief. Just because I am resistant to the short term blood pressure effects of salt loading, that does not mean I am immune to whatever long term negative effects a high salt diet may have. While epidemiological studies have their problems, it seems unwise to discount their findings altogether.

Edward Frohlich has argued that, notwithstanding the fact that most people's blood pressure does not respond to acute increases in sodium intake, sodium is nevertheless responsible long-term for increases in blood pressure. He argues that excess salt causes kidney damage over time (as with uric acid this is mediated by renin/angiotensin systems), resulting long-term in an increase in blood pressure. While much of this research is based on studies done on rats (including those of the "spontaneously hypertensive" variety), this line of thought is worth looking into and I will continue to do so.

Further Research is Needed

Studies always end with the statement that further research, and therefore research funding, is required. Well, I don't need funding but I will go a little further than a call for further research. Here are some ideas for areas of study and self experimentation.

• High carb low salt diet -- measure bodyweight and thermoregulation (e.g. via controlled hot baths or showers) over 5 day intervention period.
• Anthropological studies of salt and carbohydrate consumption among hunter-gatherers. Including seasonal variation. Genetics would be expected to play a significant role as there is ample evidence for recent evolution of salt sensitivity.
• Theories and evidence for salt use among paleolithic people. Support for consistent blood and/or shellfish consumption? Evidence for use of natural salt deposits?
• Sodium consumption and skin infections. Is salty sweat bacteriostatic within in sweat glands? Is low sodium consumption associated with skin infections? How salt sensitive is staph aureus? How about p. acnes? Have comensal skin bacteria evolved higher or lower levels of salt sensitivity? Are there differences between human populations (e.g. African vs. European skin flora)?
• Evidence for genetic selection of salt sensitivity in neanderthals. Is it possible I inherited some of my salt-related genetics from my neanderthal ancestors? If salt resistance is associated with adaptation to cold environments (see Weber), neanderthals would be expected to show these adaptations, and if they conferred a selective advantage, they should have been propagated if passed to human populations.

Computational Hemodynamics

This is a quick update on salt, and a digression about computation and blood pressure control. Read all the way to the end for a grain of salt advisory on the carbohydrate-insulin hypothesis.

My salt experiment is progressing and I've completed a 6 day baseline period, followed by a 3 week salt restriction period during which I consumed approximately 800-1,000 mg of sodium per day. I am now half way through a 2 week salt loading phase where I am consuming about 6,000 mg of sodium per day. It is quite a challenge to eat this much salt, though my taste buds have now gotten used to it.

Results? There has not really been a noticeable change in blood pressure between the three phases. Blood pressure during salt loading is almost certainly the same as the baseline diet, which was fairly low in salt to begin with. I'm still reviewing the data on the salt restriction phase, as there may have been a small drop there. I will report in more detail later.

Severe salt restriction had some negative side effects, most significantly an impairment in my body's ability to maintain a stable core temperature. In a warm environment, I might experience an increase in heart rate, and ultimately an elevated core temperature (up to 100.5 in one case). I also noticed a substantial drop in exercise performance. I was clearly dehydrated during this period, as evidenced by a drop in body weight. According to a google book called The Interface of Neurology and Internal Medicine (2007), salt restriction and dehydration can result in impaired thermoregulation possibly leading to heat stroke. I believe dehydration and the resulting drop in blood volume limits cardiac output, thereby preventing the cardiovascular system from performing its temperature regulatory functions.

Infinite Gain

In a former incarnation I was an electrical engineer.

Beloved of electrical engineers the world over, the operational amplifier (a.k.a. the "op amp") has been a mainstay of circuit design at least since the mid-1960s, when the first integrated circuit operational amplifier was introduced. An op amp has two inputs and one output, with the output dependent on the difference in voltage between the inputs, multiplied by a gain factor.

An ideal op amp by itself has effectively an infinite gain. This means it is not going to make a very useful amplifier unless it is built into a circuit that incorporates negative feedback. In this configuration, as articulated by Paul Horowitz and Winfield Hill in "The Art of Electronics," the op amp will do "whatever is necessary to make the voltage difference between the inputs zero."

An operational amplifier in the inverting closed-loop configuration. Rf provides negative feedback such that the voltages at the (+) and (-) inputs become equal. The circuit designer can manipulate Rin and Rf to produce the desired relationship between Vin and Vout.

Since the op amp is so useful in engineering, one might expect to find something like it in evolved biological systems that incorporate regulatory elements and negative feedback. In fact, there does appear to be an "infinite gain" element in the human blood pressure regulation system.

Computational Hemodynamics

In 1966, Arthur Guyton and Thomas Coleman developed a computer model of blood pressure regulation. The model was put together based on prior research on the various systems that work together to regulate blood pressure, including hormones (renin, angiotensin, aldosterone, antidiuretic hormone), heart pumping parameters (including pulse and stroke volume), fluid dynamics, electrolytes, local blood flow control, and various other factors. In a paper published in 1990 in the journal Hypertension, Guyton discusses the discovery he made using this computer model of an infinite gain regulatory element.

1966 was a long time ago in the computing world. Guyton and Coleman may have needed one of these to program their blood pressure model. Image from "Introductory Computer Programming" by Fredric Stuart, John Wiley & Sons, Inc. 1966.

After Guyton and Coleman started playing around with their computer model (did I mention it was 1966!), they saw some unexpected results. They increased one variable -- namely total peripheral resistance -- that "everyone already understood" would cause chronic hypertension. Instead, as Coleman reported to Guyton, "the patient developed hypertension all right, but the pressure came back to normal after a few days." Guyton and Coleman saw that the kidney's ability to regulate fluid and electrolytes was effectively an infinite gain feedback system: like an op amp, the kidney would do whatever was necessary to maintain stable blood pressure. While this surprised them at first, they found that this property could explain earlier observations that had been difficult to understand.

As Guyton stated in the 1990 paper, "the infinite gain property of the kidney-fluid mechanism for pressure control is so dominating that it will not allow a factor from outside this mechanism to alter the blood pressure permanently unless the kidney-fluid mechanism is itself altered at the same time." In other words, if you are looking for a cause for a long term change in blood pressure, look for something that is affecting kidney function.

Here is an except of a schematic diagram of Guyton's 1972 blood pressure model (this may be a revised version of the original 1966 model). A shrunken version of the full diagram is included at the end of this post. It's so big that it is worth checking out the fill size image, which you can get here.

A small segment of the Guyton 1972 schematic.

Biology as Computation

I think this story is a good example of a successful computational approach to a biological question. We can view the human blood pressure regulatory system as a computational system. It reads a variety of inputs and "computes" the organism's blood pressure. If we can accurately model the system's individual elements (based on lots of reductionist basic science) we can try to simulate the whole thing in a computer.

This story also shows that a reductionist approach to biology can mislead. Viewed in isolation, it seemed obvious to everyone that an increase in "total peripheral resistance" would result in a long-term rise in blood pressure. This was consistent with the fact that patients with hypertension typically also show an increased total peripheral resistance. However, in other cases where there is a clear primary cause for a rise in total peripheral resistance (e.g. multiple amputations), scientists frequently observed no long term increase in blood pressure.

The computer model helped provide an answer to these riddles. Instead of relying on an intuitive understanding of a single element, it let us watch what happens when all of the computational elements are allowed to interact. It then became obvious to Guyton and Coleman that the kidney's fluid regulation mechanism was powerful enough to override other factors that might try to drive blood pressure up or down. It could then be hypothesized that the increased total peripheral resistance seen in hypertensives was in fact a consequence, and not a cause, of elevated blood pressure. Work could then proceed on how exactly this came about.

Beyond Blood Pressure

Some complex systems may sometimes exhibit simple and comprehensible behaviors, while other complex systems will not. Computational approaches might help us figure out which is which. Computational approaches may be required when purely reductionist thinking is not enough. In other cases, when the basic "computational units" of the system being modeled are not individually well understood, a computational approach might lead us absolutely nowhere. And as anyone who has ever tried to build a complex system can tell you, if it is not extensively validated, it is almost guaranteed to break.

Blood pressure regulation is complex, though it is probably quite simple compared to many other biological systems. To me the diagram below looks about as complex as this schematic for the Intel 4004 microprocessor, introduced in 1971. The infinite gain property of kidney fluid regulation, discovered because of a computer model, allows for a powerful simplification. If the kidney is really driving the blood pressure boat, we could safely ignore most of the complexity of the total system and look only at the kidney's health and its specific regulatory drivers. Many other complex systems will not be reducible in this way.

Grain of salt advisory.

Consider this next time someone says carbs drive insulin which drives fat storage. Insulin works in a complex web of biological computational elements, including the mother of all biological computers, the human brain. Insulin viewed in isolation may or may not give us the answer. This is why my ears glaze over a bit when I hear someone start talking about "<hormone du jour> resistance." I'm not interested in the behavior of a single wire in a complex web. I want to know how the whole thing works.

Blood pressure regulation. It's complicated. From Guyton 1972.

Goals, Salt and Viromes

Here's an update on what's been going on here at megafauna central. Health goals, salt sensitivity, and the microvirome.

Eagle-eyed readers will have noticed that the quote in the mast-head has changed. The original version was "science is the disbelief in the authority of experts." I heard this quoted by Michael Vassar on the Bulletproof Executive podcast (episode 14). A reader told me that he was researching the quote and was unable to find a reliable attribution to Feynman. The closest Feynman quote he could find was "science is the belief in the ignorance of experts." This version appears in an essay called "What is Science?", which is included among other places in a collection called "The Pleasure of Finding Things Out" (Perseus, 1999). Now I like the original, wrong version better, since it is less confrontational and fits my personality. So I imagined myself going all Jonah Lehrer and sticking with it. However reason prevailed and I changed the quote to the one I'm pretty sure Feynman actually said. Getting a quote wrong in a podcast interview is understandable, but I should have done a better job of fact checking. As it is, it looks like I may have permanently polluted the Internet. Sorry!

Health Goals

I took a break from experimentation while on the home stretch for my 2012 health goal, which I mentioned at the end of my last butter post. Last week I completed that goal with a 415 pound deadlift, thanks in part to high butter consumption which allows me to keep my calorie intake high and maintain my bodyweight (twitter subscribers have already seen the video, which is low quality and not terribly interesting).

My next health goal is to achieve a reasonably fast one mile run. I don't run and never really have, so I'm hoping to find some "low hanging fruit" by exploring another fitness domain. I also have no idea what a reasonable goal might be, so I'll just muddle around for a few months and see where I end up. I'll be closely watching my resting heart rate and expect some short-term improvements there. I will be writing about my protocol and progress.

Now that my 2012 health goal is complete, I have a little time for experiments.

Salt Sensitivity

For a while I have been interested in lifestyle modifications that might affect blood pressure. While my blood pressure is considered normal, my systolic (the high number) is at the high end of the normal range.

It seems clear that salt raises blood pressure significantly for some people, and in those people, excess salt consumption is associated with a host of bad effects. These folks are called "salt sensitive." For others, blood pressure seems to be unaffected or even decrease when excess salt is added to the diet. These folks are called "salt resistant." I would like to find out which category I fall into.

The following graph from Sanada et al (Clinical Chemistry 2006) gives a good picture of what's going on with short-term changes in salt intake. It shows the daily sodium excretion of salt sensitive and salt resistant individuals during a dietary protocol in which salt is first decreased, then increased, and then returned to baseline (note, since the molecular mass of sodium is about 23, multiply the mmol values by 23 to determine milligrams of sodium per day).

It appears that salt resistant individuals rapidly increase their sodium excretion when the salt content of the diet goes up (this is accomplished through a reduction in renal sodium reabsorption, hence excess urinary sodium excretion). The net effect should be that the body maintains sodium homeostasis notwithstanding the rapid change in intake. Salt sensitive individuals appear to be slower to make that adjustment, as evidenced by the lag in the sodium excretion curve during the salt loading phase. Given the lag, it would appear that salt sensitive individuals might accumulate sodium in the body on a high salt diet, though it is unclear if this normalizes over a longer term (I haven't gone deep enough into the research to see if that is the case).

Effect of dietary sodium on sodium excretion in SR (○) and SS (▪) hypertensive Japanese. From Sandana et al (Clinical Chemistry 2006).

One recent paper suggests that salt resistance confers advantages in maintaining body temperature homeostasis (see Muller et al, Hypertension Research 2011). I had always assumed that salt sensitivity was the ancestral state and that salt resistance traits were associated with agricultural cultures that used salt to preserve food. However, the Muller paper suggests to me that salt sensitivity might actually be an adaptation for persistence hunting in hot climates by allowing improved thermoregulation. I have no idea if the genomics work on that question has been done.

Are You Salt Sensitive?

If your blood pressure is more than 100-110 over 70-75 (the norms reported for hunter-gatherers), perhaps it makes sense to find out if you are salt sensitive.

I reviewed the medical protocols for diagnosing salt sensitivity and found them to be fairly intensive. They seem to be confined to clinical research settings at this point. In other words, doctors don't know, and can't find out, if their patients are salt sensitive.

There seem to be two recognized approaches for diagnosing salt sensitivity in research settings. In the first, a low salt diet (~1g of sodium per day) is followed for two weeks followed by a high salt diet for another two weeks. A second standardized approach, described by Weinberger et al in 1986, is much quicker. It uses IV saline solution for the loading phase, followed by a low salt diet and the administration of furosemide, a diuretic that decreases renal reabsorption of sodium.

At least one study has shown that the two techniques are not well correlated with each other (see de la Sierra 2002, Journal of Human Hypertension). Since I am not interested in my response to diuretics, I am running myself through the dietary version of the test. I am one week into the low salt phase and have seen no noticeable change in blood pressure thus far. That's not unexpected though, since my baseline diet was pretty low in salt. I'll know much more once salt loading kicks in at the end of this week. What is most interesting to me so far is that I have had absolutely no cravings for salt.


In the mean time, health authorities strongly advise everyone to restrict salt, despite the fact that they have no idea what effect this will have on you in particular. Lemmings will jump. Ostriches may hide their heads from the truth.* I prefer to get the information I need to make good decisions.


* Yes, I understand that neither of these statements is true. I am lying about animals for rhetorical effect.

Microbiome

In microbiome news, I received the results of my Metametrix stool profile. It is pretty interesting but I believe this type of data is of very limited usefulness at this point. The profile works by sequencing the ribosomal RNA of the bacteria in your stools. This gives you an idea of the mix of "species" of bacteria that are present and in what quantities they appeared in your stools on that particular day. What information is missing given current technology?

• Changes in the microbiome over time
• Presence and expression of genes. Microbes are exceptionally promiscuous and share DNA via plasmids, phage, and other mechanisms. 16S ribosomal RNA does not tell us what genes are there or to what degree they are expressed
• Where the bacteria are located. Bacteria can colonize multiple niches (e.g. lumen vs. mucosal layers) and these differences can have meaningful effects
• Behavior of the bacteria that are there. Microbes communicate with each other and with the immune system. What are they saying?

I mentioned phage above. While it is well known these days that bacteria form an important part of the human digestive tract, it is not as widely appreciated that viruses are also a significant component. Viruses that infect bacteria, known as bacteriophages or "phages" for short, are the most abundant life forms on earth. If they were so inclined, they could link hands and stretch from one end of the galaxy to the other. And back. By comparison, humans could get 1/10 of the way to Mars, and would almost certainly be accompanied by terrible music.

Phage seem to represent the majority of all genetic variability on the planet. They associate with our gut microbiota and change in response to dietary interventions (see Minot et al, Genome Research 2011). Scientists seem to be at the very early stages of figuring out what phages are out there, what they look like, and what they might be doing. I don't think anyone has a clue about the impact they have on human health. So until these questions are answered, keep plenty of salt grains at the ready for the next time you hear a definitive-sounding pronouncement about the microbiome.

Recipe Section

If this blog were a mainstream health book, this would be the obligatory recipe section. So if you are interested in my take on minimalist high-butter cuisine, read on.

Bulletproof Mussels

(inspired by bulletproof coffee)
2 lbs mussels
1/2 stick Kerrygold butter

1. Clean mussels and add to large stockpot with 1 cup of water. Cover and simmer for 15 minutes.
2. Discard shells and remove meat to a bowl, leaving the broth in the stockpot. Melt butter in the broth. Whip with emersion blender. Pour over mussels and serve immediately.

Spinach Soup

1 lb spinach
1/2 stick Kerrygold butter
1/2 tsp ground cumin
1/2 tsp salt

1. Rince spinach and add to large stockpot with 1 cup of water. Bring to a boil, cover and simmer for 3-5 minutes.
2. Add butter, cumin and salt. Blend with emersion blender. Serve immediately.

Butter Poached Salmon

1 lb salmon, cubed
1/2 stick Kerrygold butter

1. Melt butter in small saucepan. Add salmon, cover and simmer for 5 minutes or until cooked through.
2. That's it (or were you hoping you'd get to use the blender?). Salt to taste and serve immediately.

Butter Not Like a Statin After All?

I began my original butter experiment without a hypothesis about the effects of butter on cholesterol. I was tracking blood lipids so that I could identify any possible adverse reactions. After initially seeing a positive change, the numbers started to go the wrong way, with HDL dropping and non-HDL going up. At the same time, I had switched from the Kerrygold butter I usually used to a local brand from my farmer's market. It was supposed to be "100% grass fed," but it did not have the deep yellow hue of the Kerrygold, so I suspected it could be responsible for the adverse results. After a day or two using an Icelandic brand (Smjor), I decided for the remainder of the experiment to test only Kerrygold butter. A few days after the switch back, the numbers moved back in the positive direction. I tracked for a few more weeks and then reported my initial results here.

After the original post, I spent about three more weeks on the same diet (1/2 stick of Kerrygold butter per day), followed by three weeks of butter elimination (during this elimination phase, there was some increase in coconut oil as a partial substitute for the butter calories). Finally, I went back on a high-butter diet for an additional five weeks. During this last phase I decided to double down and eat a full stick of Kerrygold butter every day (about 112 grams of butter and 90 grams of fat). The diets were otherwise similar, though I was likely consuming more total calories during the high-butter phases. Data points were generally taken weekly, on Sunday afternoons (not fasted, but I don't believe it makes much difference, since I am not measuring triglycerides).

Based on the additional data I can report that the addition of butter to my diet may have increased my HDL cholesterol. However, it has not had a convincing long-term effect on my non-HDL cholesterol. The HDL remains elevated from before, but non-HDL readings are consistent with my average numbers over the past three years or so. My working hypothesis at this point is that the change in non-HDL I observed originally was a temporary disturbance of homeostasis. This may have been due to the butter or to another unknown cause.

I also believe this data suggests that different brands of butter can have different effects on cholesterol values. I will show this data below, though given the design of this experiment, I will not be able to prove it without a follow-up experiment. However, I am satisfied with my original concern, which is that the addition of a good brand of butter to my diet does not seem to have any measurable adverse effect on cholesterol measurements.

Results

The additional data points are shown in the two plots below. The four green points show the data that was dropped from the original data set because I was not using Kerrygold butter. The last five points are for the latest diet where I am eating a full stick of butter per day.

HDL measurements over time. Red points indicate control. Blue and green points indicate experimental group with consumption of at least 0.5 sticks of butter per day for at least 7 days prior to testing (blue=Kerrygold). No statistically significant difference in control vs. experimental measurements when green points are included. Trend line is for red points only.

Non-HDL cholesterol over time. No statistically significant difference between control vs. experimental measurements when green points are included. Trend line is for red points only.

The next two plots show the same data, zoomed in to show points from the beginning of the original butter experiment to the present time. The three red points are the latest butter-elimination phase.

Trend line for blue points.

Trend line for blue points.

Overall, I think there is some basis for concluding that added butter is having a positive effect on HDL, although the results are not statistically significant when the green points are included. However, it is also possible that some other factor is concurrently causing my HDL to increase.

The trend towards positive HDL outliers has continued in the butter dataset and is especially strong in the latest readings where a full stick per day is consumed, suggesting a dose-response relationship. My last three readings are all greater than 100, which is the meter's measurement limit for HDL cholesterol. Since I am computing non-HDL cholesterol as Total minus HDL, this measurement limitation will inflate the non-HDL points by an indeterminate amount at the same time as it underestimates HDL. The highest reading ever recorded in the control dataset is 83, while the butter dataset has 5 readings above that level and three above 100.

The non-HDL numbers do look like noise at this point, except for the original cluster of low readings when the original butter experiment began. There probably was some underlying cause for that, though it is clear to me that if the butter had anything to do with it, the effect was temporary.

Note also that there are several negative outliers for HDL in the non-Kerrygold butter set. This suggests that different brands of butter can have different effects on cholesterol measurements. This phenomenon may warrant further study.

What's the Take Away?

Okay, I hear what you're saying: "Greg, that's a heck of a lot of colored dots. So what?" I think the bottom line is, I'm eating a whole stick of butter every day and my lipid profile has either stayed the same or gotten a little better. Works for me.

Measurement Accuracy

During this experiment, I observed that the CardioChek PA seems to be very accurate at measuring HDL, but much less accurate at measuring total (and therefore non-HDL) cholesterol. One of the newly collected data points shown above is the result of a VAP cholesterol panel ordered by my doctor. The same morning as the blood draw for that test, I took three successive readings of HDL and total cholesterol with the CardioChek PA. The VAP test showed an HDL of 68 and non-HDL of 233. The three HDL measurements on the CardioChek PA averaged out to 68, same as the VAP result, with a standard deviation of only 1.7%. For non-HDL, on the other hand, the average was 191 with a standard deviation of 15%. Compared to the 233 non-HDL measured by VAP, the CardioChek PA was off by 18% even when three separate measurements were averaged.

Therefore, variance seen in my HDL readings over time suggests that real changes are taking place in my body. However, variance in my non-HDL measurements will be substantially the result of measurement error in addition to physiological changes. To put this in perspective, the standard deviation of all of my non-HDL measurements over the last 2+ years taken together is only 15.8%, barely higher than the meter's built-in measurement noise.

The CardioChek also sells test strips for direct LDL measurement. I will probably check those out at some point, as they may prove to be more accurate than the total cholesterol strips.

Next Steps

Ideally, self-experimentation would be based on biomarkers that can be measured accurately and cheaply, and that quickly reflect real health trends. Blood sugar measurements are very useful in that regard, because it only takes one finger prick an hour after a meal to obtain useful information about your body's response to carbohydrates. Over the course of this experiment, I've become skeptical of the value of cholesterol measurements as a target of self-experimentation. Given the meter's built-in measurement noise and the long half-life of circulating lipoproteins, it takes weeks or months for changes to be clearly evident. That makes it difficult to do useful experiments.

My most pressing health goal until the end of 2012 is a 405 pound deadlift. High cholesterol and extra calories from butter are probably going to help me achieve that goal, so I will be putting my cholesterol investigations on hold for the time being. In the mean time I do have a few other experiments to report on, so stay tuned.

A Case of Physics Envy?

With the airing this week of the HBO obesity documentary "The Weight of the Nation," reporting on the obesity epidemic has reached a fever pitch. I wanted to take a break from my usual programming to mention an article I saw today in the New York Times entitled "A Mathematical Challenge to Obesity."

Until now, mathematical hubris has been mostly the province of economic forecasters and financial risk modelers. As we have seen many times, if you do not fully understand the system that you are modeling, your model will be junk even if you think it's the greatest thing in the world. Now it seems the modeling bug is looking to infect the nutrition field.

The article is an interview with a mathematician who works for the National Institute of Diabetes and Digestive and Kidney Diseases, a division of NIH that I never knew existed. The mathematician, in an act of physics envy, claims to have created a model of a human being based on a single equation. I thought I would just re-print the email I wrote to Claudia Dreifus, who is the Times writer who conducted the interview. Text in brackets are for context if you have not yet read the article (they were not in my email to Ms. Dreifus).

"I read your interview with Carson Chow and had a few questions. 

1. Mr. Carson claims to have proven that increased food availability "caused" the obesity epidemic. He says that if there is extra food, people eat more. Yet animals typically do not become obese under "ad libitum" conditions (i.e. unlimited  food availability). Why are humans different and how does Mr. Carson's mathematical model "prove" that?

2. How does he know the increase in food availability is a cause and not a result of the obesity epidemic? The alternative hypothesis is that people are hungrier than they were before, and since they want to eat more, the food system produces more.

3. Why does Mr. Carson say that all diets work, when the clinical studies on diets almost invariably show that they don't work over the long term? If Mr. Carson has not done any experiments, how can his work prove that dieting works at all?

[Carson Chow said "it's so easy for someone to go out and eat 6,000 calories a day."]

4. Has Mr. Carson tried eating 6,000 calories a day for more than a couple of days? I don't think it is so easy, and professional bodybuilders and powerlifters often say that eating that much is the hardest part of their sport.

5. I tried the bodyweight simulator on the NIDDK site. Mr. Carson's mathematical model says that if I go from a very low carbohydrate diet to to a 6,000 calorie diet consisting of 100% carbohydrate, I would be able to gain hundreds of pounds within a week while maintaining a single-digit body fat percentage. While I agree that carbohydrates can cause weight gain for some people, that result is a little hard to swallow. Did the New York Times check the calculations to confirm they produced sensible results before interviewing Mr. Carson?"

I will update the blog if I get a response.

That last point is the most interesting to me. I believe the sports world will change forever once athletes realize they can gain nearly 750 pounds of lean mass in a week, without exercising. It is amazing nobody has taken advantage of this phenomenon before, and the first football team fielding multiple 900+ pound players is sure to be a favorite next season.

Here is a screenshot from the simulator showing this absurd result. The mistake probably stems from having "baseline calories from carbs" alone in a denominator somewhere (the app at least will not let you set this value to zero, so they caught that part of the bug).

The Microbiome and Insulin Sensitvity

One of the largest organs in your body is technically outside of your body. It is the microbiota in your intestines. It comprises 90% of your cells and 99% of your genes. This organ regulates, and is regulated by, your immune system, your digestion and metabolism, and it even makes a whole bunch of neurotransmitters. It is very complex and interesting. I am going to discuss one recent study which should introduce some of the experiments I will be writing about over the next couple of weeks. Thanks to "This Week in Microbiology" (one of the best things on the entire Internet) for bringing this study to my attention.

John Ioannidis has written about the fact that many of the results in the biomedical research literature have never been replicated. And when scientists do try to replicate prior results, they often get contradictory outcomes. Contradictory results are part of science, and they are a sign that new hypothesis need to be considered. This paper is a great example of that.

The paper was published by Caricilli et. al. in December, 2011 in PLOS Biology and is entitled "Gut Microbiota is a Key Modulator of Insulin Resistance in TLR 2 Knockout Mice." The team of Brazilian scientists was working with mice that had been genetically modified to knock out the gene for toll-like receptor 2 (TLR 2), a component of the innate immune system. They found that these mice were insulin resistant and went on to develop a phenotype reminiscent of obesity and type 2 diabetes. This is in contrast to previous studies that showed the opposite effect in TLR 2 knockout mice. Same experiment, opposite result.

Three experiments from three labs.  Conflicting results.

The Brazilian team came up with a new hypothesis that might be able to explain all of the results. They showed that the genetic modification to the mouse's innate immune system resulted in changes to the composition of the mouse's gut flora. They believe that the gut flora, in turn, altered the mouse's insulin sensitivity. The effect depends on the flora present in the local environment in which the mouse is raised. This would be expected to vary from one lab to another. Therefore, a TLR2 mouse's insulin sensitivity may go up in some labs and down in others. The Brazilian team was careful to ensure that the mice they were using were raised not just in the same lab, but in the same room. Now that's some careful science.

The scientists characterized the gut flora of their control and TLR2 knockout mice (via sequencing 16S ribosomal RNA). They observed that firmicutes (a phylum of mostly gram-positive bacteria) are increased in their insulin resistant mice. When they transplanted this altered flora into healthy mice, they became insulin resistant too. When they used antibiotics which selectively kill off firmicutes in the TLR2 knockout mice, they went back to being insulin sensitive. Imagine that -- could we cure diabetes with antibiotics?

If you've read this far, you might be curious about your own microflora. Simply ship your feces to Metametrix and they'll analyze it by the same or a similar technique to that used in this paper. If you're insulin resistant, perhaps you have excess firmicutes and there may be strategies you can use to kick them to the curb. Of course mouse experiments do not necessarily translate to humans and healthy flora for a mouse will certainly differ from what is healthy in humans, but excess firmicutes have been found to be associated with obesity and diabetes in humans (in some but not all studies). Firmicutes have also been found to be reduced following gastric bypass surgery. A recent review paper by Tilg and Kaser (Gut Microbiome, Obesity, and Metabolic Disfunction) summarizes these findings. Of course, this information could turn out to be entirely useless -- perhaps it is not the categories of bacteria that matter, but specific strains, or the specific genes carried by (or expressed by) those strains. The interesting effects could depend not on what is there, but on the specific niches that particular strains have colonized (information that probably cannot be obtained from stool testing). We'll have to wait and see as this work is elaborated with new research, including the results of the Human Microbiome Project.

Is your Microbiome a Gland?

I mentioned above that the microbiome is in constant communication with your immune system and metabolic regulatory pathways. We saw from the Caricilli paper that changes in the microbiome can alter insulin sensitivity. One of the signaling molecules involved in this communication is lipopolysaccharide, or LPS. This is a component of the cell walls of gram negative bacteria. Your immune system is exquisitely sensitive to it. Concentrations measured in picograms per milliliter can cause measurable effects. This is a bit frightening when you realize that each of us is carrying around many grams (that's trillions of picograms) of LPS in our normal gut flora. Too much LPS and you die of sepsis, even if no live bacteria are present. Your immune system will kill you. For this reason, LPS has been referred to as bacterial endotoxin, though recent findings suggest it is much more than a mere toxin.

One very intriguing theory has been presented by John Marshall in a paper in Clinical Infectious Diseases (2005). He suggested that LPS should be thought of primarily not as a toxin, but as a hormone. It bears many similarities to our more familiar hormones. It exerts systemic effects by binding to specific receptors in multiple target tissues, triggering gene expression. It's effects are tightly regulated by a specific binding protein (creatively named "LPS binding protein") and multiple negative feedback loops. Typical of other hormones, it is harmful in excess, but beneficial in the right quantity and the right context. Of course it is quite odd for a hormone to be produced outside of your body, but in other respects it might fit the mold.

LPS typically spikes after meals, and has an acute systemic inflammatory effect. Going back to the mouse study, Caricilli et. al. found that their TLR2 knockout mice had higher serum LPS levels than the controls, and a greater increase in serum LPS following oral ingestion. The higher spike in LPS could be explained by the fact that the TLR2 knockout mice had lower levels of a tight junction protein that helps maintain gut barrier integrity. So it looks like an altered immune system resulted in an altered microbiome which changed intestinal barrier integrity which increased exposure to an exogenous hormone resulting in systemic inflammation, which caused metabolic dysfunction insulin resistance and obesity. Or, since the paper did not clearly establish cause and effect, any of the foregoing in any other causal permutation. Ok!

There is a lot more to say about LPS. What sorts of things cause it to increase, chronically or acutely? What regulates the body's response to it? And what about those curious negative feedback loops? More importantly, can we observe its effects through self-experimentation? Stay tuned for more.

Follow Up on Butter

Welcome readers. I wanted to post some follow up details on my experiments so far and say a bit more about the themes I will be writing more about. You'll notice that my headlines so far have been phrased as questions. This is not an homage to a popular quiz show -- they are questions because I don't know the answers. So with that in mind I wanted to revisit the results of my first experiment (Is Butter as Powerful as a Statin?).

Science is hard, and if you attempt it, you need to stay vigilant about not fooling yourself, because, as Richard Feynman has said, you're the easiest person to fool. So I'll be reviewing my initial results to see whether I've fooled myself. Of course when it comes to personal science, we should always be aware of this principle in reviewing work done by others. If someone has managed to fool himself (even for a moment), perhaps they might fool you too. I hope my readers will keep this in mind.

Commenter EricT highlighted the biggest weakness in my butter experiment.  I originally added the butter to my diet to see what sorts of subjective effects it might have (they were positive, but I did not track anything quantitative that I can present). I tracked my lipids at the time only in order to monitor whether they might move in an adverse direction. It looked like the Kerrygold butter caused beneficial changes while other brands did not. I therefore changed my hypothesis mid-stream, which is a substantial source of bias, effectively rendering my statistical analysis invalid (this particular weakness is not applicable to the second experiment on safe starches vs. HDL, though of course other weaknesses do apply). Meanwhile I am continuing the butter experiment and will present all additional data points in a couple of weeks so we can see whether the effect holds. In the mean time, by then I will have data from another VAP cholesterol test so I can have more confidence about what my CardioChek meter is actually measuring and how consistent it is. Stay tuned for that.  Meanwhile I have declared a "grain of salt" advisory on the butter post.

If the additional data points do not show a continuation of the effect seen previously, it would weigh strongly against the hypothesis that butter causes beneficial changes in lipids (though this is somewhat independent to the question of whether butter is good or bad from a cardiovascular perspective). Many alternative hypotheses could explain a negative outcome -- the effect could have been the result of the bias, a short-lived disruption of homeostasis, a systematic user error or environmental sensitivity with the CardioChek device, or an unknown and temporary cause coinciding in time with the applicable data points. Since I did not decide beforehand how long my experiment would last, the effect could also have been a statistical anomaly which only seemed "significant" because of the particular day on which I decided to compile my results (that is, you can't just wait until you get the result you want and choose that as the date on which to terminate your study).

In the mean time, I've been measuring another health marker that is related to gut health and the microbiome.  I am going to write about about that and then present some interesting and hopefully useful data over the next few weeks.

Do Carbs Lower HDL?

Attack of the Safe Starches

If you have been lurking around paleoland recently you will have heard the debate about safe starches (you may be sick of hearing about it in fact).  Last fall I ran an experiment to find out whether it might be a good idea to dip my toe into the safe starch swimming pool. I was tracking my lipids around this time with the CardioChek PA so I could have some idea of what was going on with my metabolism.  Here are the results.

I first experimented with a low carbohydrate diet in 2009 after reading Good Calories, Bad Calories by Gary Taubes. I lost 15 pounds in the first three months (though I had no idea I was carrying any extra fat).  I gained muscle without changing my exercise program.  My seasonal allergies went away.  My teeth got whiter, less sensitive and stopped collecting plaque.  I got fewer sunburns.  My joints stopped aching after exercise.  You get the idea.

Around this time I took an oral glucose tolerance test and found my numbers to be a bit high, though not in the pre-diabetic range just yet. I tend to get a high initial blood sugar spike, though the value quickly returns to normal. I thought this (along with the other general health improvements I experienced) was an indicator that a low carb diet was a good approach for me. I bought a cheap glucometer to play with and stuck with the low carb program.

Over the years my diet progressed to a paleo approach, while I continued to avoid starches. On most days I ate only eggs, meat, fish, some nuts and a good helping of green veggies. Given the safe starches controversy, I thought it would be interesting to try adding 100g or so of carbs per day in the form of sweet potatoes, just to see what would happen. There is a variety of chatter about the possibility that low carbohydrate diets can raise LDL, so I thought I might see a drop in non-HDL cholesterol with a bit of added starches. I did get a drop, but it wasn't to the non-HDL.

Results

Mean non-HDL did not change during the experiment (193 to 203, not statistically significant), but mean HDL dropped by a significant amount (67 to 57, p<0.001). I stopped the experiment after one month. You'll see in the plot below that the HDL went back up to the previous level after the daily sweet potato was dropped.

Boxplots show minimum, maximum and quintiles. Mean HDL: 67 (control), 57 (carbs).

The trendline is a linear model based on all low carb data points (before and after, but not including, the carb intervention).

Trendline based on all low-carb points.  Non-HDL cholesterol was not significantly affected.

Details of the Experiment

The data points were collected as previously discussed in the butter experiment. Data does not include any points during the butter experiment, as there was a significant change in HDL and non-HDL during that time. Statistical significance test is based on a linear model, calculated by ANOVA using R.

Sweet potatoes were eaten slowly so as not to spike blood sugar above 120, though spikes may have occurred on occasion. It usually takes me about an hour to eat one, though I can eat them very fast without a spike if I've recently completed a heavy workout.

There are a number of limitations to the interpretation of this data that are worth mentioning. Perhaps most significantly, this is a very short term test (1 month). It is possible that long term adaptations would have reversed the effects seen here. Second, there was only a single intervention period, which could have corresponded to another unknown variable which caused HDL to decrease. Since foods differ in micronutrient, mineral and toxin content, it is not possible to generalize from sweet potatoes to all carbohydrates.  I may have had a different result with white rice, white potatoes, taro, tapioca, etc.  Finally, of course this result applies to me only. There may be others who have a much higher carbohydrate tolerance, or who may even see the opposite result.

Is This Actionable Information?

So why am I bothering with this? First of all, simple curiosity. I have the ability to collect data that most people do not collect, and there is some interesting science concerning these molecules and what they may be able to tell me about my metabolism.

Does the decrease in HDL identified here represent an unhealthy change? Perhaps. Though HDL is commonly referred to as the "good cholesterol", I would not suggest that all decreases in HDL are unhealthy.  In fact I don't know how one would go about establishing the truth or falsehood of a statement like that. Conversely, we know of chemicals that raise HDL while simultaneously causing heart attacks.  My HDL was never "low" during the course of this experiment. However, together with certain other data I was also collecting at this time (which is a story for another day), I believe that 100 grams of starch per day is too much for me. At least in my current metabolic state, with my current lifestyle, exercise habits, sleep, stress level, etc.

Some smaller amount of starch is most likely "safe," and may be a good idea. These days I often eat a banana (about 20-30 grams of sugar+starch) after lunch, and I have not seen the negative effects caused in me by higher amounts of carbohydrate. As mentioned, I also have found that I can eat 100 grams of carbs immediately after a heavy workout with no significant change in my blood sugar (e.g. it might increase from 65 to 83 in response to a pound of sweet potatoes after two hours of powerlifting). These days, workouts like that occur about once a week (sometimes less), and I have not noticed any negative effects from eating carbs this infrequently.  Since many smart (and strong) people advocate carbs post-workout, I am willing to go along for now, at least while I do not have any contradictory evidence.

Published Research

Perhaps if I had looked this stuff up in the scientific literature first I would have been less surprised by my results. It turns out there is plenty of published research supporting the idea that carbs lower HDL. However, it is a bit surprising that the relationship continues even below 100g/day. I doubt there is published research on this relevant to long-term low carbers, so three cheers for personal science on that front. A study by a German team, published in January 2012 in the Annals of Nutrition and Metabolism, does a good job summing up the research that is out there.  Here is their conclusion regarding carbohydrates and HDL:

"There is convincing evidence that a higher carbohydrate proportion in the diet at the expense of total fat or saturated fatty acids intake lowers the plasma concentration of HDL cholesterol."

The paper is called "Evidence-Based Guideline of the German Nutrition Society: Carbohydrate Intake and Prevention of Nutrition-Related Disease." It is worth a read if you are interested and still awake. If instead you are sleeping (and not German), perhaps you are dreaming of a world in which the nutrition organizations in your country also use evidence as the basis for their guidelines.