Monday, October 25, 2010

The amounts of water, carbohydrates, fat, and protein lost during a 30-day fast

When it comes to losing fat and maintaining muscle, at the same time, there are no shortcuts. The process generally has to be slow to be healthy. When one loses a lot of weight in a few days, most of what is being lost is water, followed by carbohydrates. (Carbohydrates are stored as liver and muscle glycogen.) Smaller amounts of fat and protein are also lost. The figure below, from Wilmore et al. (2007), shows the weights in grams of stored water, carbohydrates (glycogen), fat, and protein lost during a 30-day water fast.

On the first few days of the fast a massive amount of water is lost, even though drinking water is allowed in this type of fast. A significant amount of glycogen is lost as well. This is no surprise. About 2.6 g of water are lost for each 1 g of glycogen lost. That is, water is stored by the body proportionally to the amount of glycogen stored. People who do strength training on a regular basis tend to store more glycogen, particular in muscle tissue; this is a compensatory adaptation. Those folks also tend to store more water.

Not many people will try a 30-day fast. Still, the figure above has implications for almost everybody.

One implication is that if you use a bioimpedance scale to measure your body fat, you can bet that it will give you fairly misleading results if your glycogen stores are depleted. Your body fat percentage will be overestimated, because water and glycogen are lean body mass. This will happen with low carbohydrate dieters who regularly engage in intense physical exercise, aerobic or anaerobic. The physical exercise will deplete glycogen stores, which will typically not be fully replenished due to the low intake of carbohydrates.

Light endurance exercise (e.g., walking) is normally easier to maintain with a depleted “glycogen tank” than strength training, because light endurance exercise relies heavily on fat oxidation. It uses glycogen, but more slowly. Strength training, on the other hand, relies much more heavily on glycogen while it is being conducted (significant fat oxidation occurs after the exercise session), and is difficult to do effectively with a depleted “glycogen tank”.

Strength training practitioners often will feel fatigued, and will probably be unable to generate supercompensation, if their “glycogen tank” is constantly depleted. Still, compensatory adaptation can work its “magic” if one persists, and lead to long term adaptations that make athletes rely much more heavily on fat than the average person as a fuel for strength training and other types of anaerobic exercise. Some people seem to be naturally more likely to achieve this type of compensatory adaptation; others may never do so, no matter how hard they try.

Another implication is that you should not worry about short-term weight variations if your focus is on losing body fat. Losing stored water and glycogen may give you an illusion of body fat loss, but it will be only that – an illusion. You may recall this post, where body fat loss coupled with muscle gain led to some weight gain and yet to a much improved body composition. That is, the participants ended up leaner, even though they also weighed more.

The figure above also gives us some hints as to what happens with very low carbohydrate dieting (i.e., daily consumption of less than 20 grams of carbohydrates); at least at the beginning, before long term compensatory adaptation. This type of dieting mimics fasting as far as glycogen depletion is concerned, especially if protein intake is low, and has many positive short term health benefits. The depletion is not as quick as in a fast because a high fat and/or protein diet promotes higher rates of fat/protein oxidation and ketosis than fasting, which spare glycogen. (Yes, dietary fat spares glycogen. It also spares muscle tissue.) Still, the related loss of stored water is analogous to that of fasting, over a slightly longer period. The result is a marked weight loss at the beginning of the diet. This is an illusion as far as body fat loss is concerned.

Dietary protein cannot be used directly for glycogenesis; i.e., for replenishing glycogen stores. Dietary protein must first be used to generate glucose, through a process called gluconeogenesis. The glucose is then used for liver and muscle glycogenesis, among other things. This process is less efficient than glycogenesis based on carbohydrate sources (particularly carbohydrate sources that combine fructose and glucose), which is why for quite a few people (but not all) it is difficult to replenish glycogen stores and stimulate muscle growth on very low carbohydrate diets.

Glycogen depletion appears to be very healthy, but most of the empirical evidence seems to suggest that it is the depletion that creates a hormonal mix that is particularly health-promoting, not being permanently in the depleted state. In this sense, the extent of the glycogen depletion that is happening should be positively associated with the health benefits. And significant glycogen depletion can only happen if glycogen stores are at least half full to start with.


Wilmore, J.H., Costill, D.L., & Kenney, W.L. (2007). Physiology of sport and exercise. Champaign, IL: Human Kinetics.

Wednesday, October 20, 2010

Obesity and the Brain

Nature Genetics just published a paper that caught my interest (1). Investigators reviewed the studies that have attempted to determine associations between genetic variants and common obesity (as judged by body mass index or BMI). In other words, they looked for "genes" that are suspected to make people fat.

There are a number of gene variants that associate with an increased or decreased risk of obesity. These fall into two categories: rare single-gene mutations that cause dramatic obesity, and common variants that are estimated to have a very small impact on body fatness. The former category cannot account for common obesity because it is far too rare, and the latter probably cannot account for it either because it has too little impact*. Genetics can't explain the fact that there were half as many obese people in the US 40 years ago. Here's a wise quote from the obesity researcher Dr. David L. Katz, quoted from an interview about the study (2):
Let us by all means study our genes, and their associations with our various shapes and sizes... But let's not let it distract us from the fact that our genes have not changed to account for the modern advent of epidemic obesity -- our environments and lifestyles have.
Exactly. So I don't usually pay much attention to "obesity genes", although I do think genetics contributes to how a body reacts to an unnatural diet/lifestyle. However, the first part of his statement is important too. Studying these types of associations can give us insights into the biological mechanisms of obesity when we ask the question "what do these genes do?" The processes these genes participate in should be the same processes that are most important in regulating fat mass.

So, what do the genes do? Of those that have a known function, nearly all of them act in the brain, and most act in known body fat regulation circuits in the hypothalamus (a brain region). The brain is the master regulator of body fat mass. It's also the master regulator of nearly all large-scale homeostatic systems in the body, including the endocrine (hormone) system. Now you know why I study the neurobiology of obesity.

* The authors estimated that "together, the 32 confirmed BMI loci explained 1.45% of the inter-individual variation in BMI." In other words, even if you were unlucky enough to inherit the 'fat' version of all 32 genes, which is exceedingly unlikely, you would only have a slightly higher risk of obesity than the general population.

Tuesday, October 19, 2010

Slow-cooked meat: Round steak, not grilled, but slow-cooked in a frying pan

I am yet to be convinced that grilled meat is truly unhealthy in the absence of leaky gut problems. I am referring here to high heat cooking-induced Maillard reactions and the resulting advanced glycation endproducts (AGEs). If you are interested, see this post and the comments under it, where I looked into some references provided by an anonymous commenter. In short, I am more concerned about endogenous (i.e., inside the body) formation of AGEs than with exogenous (e.g., dietary) intake.

Still, the other day I had to improvise when cooking meat, and used a cooking method that is considered by many to be fairly healthy – slow-cooking at a low temperature. I seasoned a few pieces of beef tenderloin (filet mignon) for the grill, but it started raining, so I decided to slow-cook them in a frying pan with water and some olive oil. After about 1 hour of slow-cooking, and somewhat to my surprise, they tasted more delicious than grilled!

I have since been using this method more and more, with all types of cuts of meat. It is great for round steak and top sirloin, for example, as well as cuts that come with bone. The pieces of meat come off the bone very easily, are soft, and taste great. So does much of the marrow. You also end up with a delicious sauce. Almost any cut of beef end up very soft when slow-cooked, even cuts that would normally come out from a grill a bit hard. Below is a simple recipe, for round steak (a.k.a. eye round).

- Prepare some dry seasoning powder by mixing sea salt, black pepper, dried garlic bits, chili powder, and a small amount of cayenne pepper.
- Season the round steak pieces at least 2 hours prior to placing them in the pan.
- Add a bit of water and olive oil to one or more frying pans. Two frying pans may be needed, depending on their size and the amount of meat.
- Place the round steak pieces in the frying pan, and add more water, almost to the point of covering them.
- Cook on low fire covered for 2-3 hours.

Since you will be cooking with low fire, the water will probably not evaporate completely even after 3 h. Nevertheless it is a good idea to check it every 15-30 min to make sure that this is the case, because in dry weather the water may evaporate rather fast. The water around the cuts should slowly turn into a fatty and delicious sauce, which you can pour on the meat when serving, to add flavor. The photos below show seasoned round steak pieces in a frying pan before cooking, and some cooked pieces served with sweet potatoes, orange pieces and a nectarine.

A 100 g portion will have about 34 g of protein. (A 100 g portion is a bit less than 4 oz, cooked.) The amount of fat will depend on how trimmed the cuts are. Like most beef cuts, the fat will be primarily saturated and monounsatured (both very healthy), with approximately equal amounts of each. It will provide good amounts of the following vitamins and minerals: iron, niacin, phosphorus, potassium, zinc, selenium, vitamin B6, and vitamin B12.

Wednesday, October 13, 2010


I'll be out of town until the beginning of November, so I won't be responding to comments or e-mails for a while. I'm going to set up a post or two to publish while I'm gone.

As an administrative note, I get a number of e-mails from blog readers each day. I apologize that I can't respond to all of them, as it would require more time than I currently have to spare. The more concise your message, the more likely I'll read it and respond. Thanks for your understanding.

Monday, October 11, 2010

Sleep Post Correction

An astute commenter pointed out that I misread the numbers in the paper on sleep and fat loss. I wrote that out of the total 3.0 kg lost, the high-sleep group lost 2.4 kg as fat, and the low-sleep group lost 1.4 kg of fat out of 2.9 kg total.

In fact, the high-sleep group lost 1.4 out of 2.9 kg as fat, and the low-sleep group lost 0.6 out of 3.0 kg as fat. So I got the numbers all mixed up. Sorry for the mistake. The main point of the post still stands though: sleep deprivation negatively influences body composition.

The correct numbers are even more interesting than the ones I made up. Even in the high-sleep group, nearly half the body weight lost by simple calorie restriction was lean mass. That doesn't make calorie restriction look very good!

In the sleep-deprived group, 80% of the weight lost by calorie restriction came out of lean mass. Ouch!

That illustrates one of the reasons why I'm skeptical of simple calorie restriction as a means of fat loss. When the body "wants" to be fat, it will sacrifice lean mass to preserve fat tissue. For example, the genetically obese Zucker rat cannot be starved thin. If you try to put it on a severe calorie-restricted diet, it will literally die fat because it will cannibalize its own lean mass (muscle, heart, brain, etc.) to spare the fat. That's an extreme example, but it illustrates the point.

The key is not only to balance energy intake with expenditure (which the brain does automatically when it's working correctly), but to allocate energy appropriately to lean and fat mass.

Blood glucose levels in birds are high yet HbA1c levels are low: Can vitamin C have anything to do with this?

Blood glucose levels in birds are often 2-4 times higher than those in mammals of comparable size. Yet birds often live 3 times longer than mammals of comparable size. This is paradoxical. High glucose levels are generally associated with accelerated senescence, but birds seem to age much slower than mammals. Several explanations have been proposed for this, one of which is related to the formation of advanced glycation endproducts (AGEs).

Glycation is a process whereby sugar molecules “stick” to protein or fat molecules, impairing their function. Glycation leads to the formation of AGEs, which seem to be associated with a host of diseases, including diabetes, and to be implicated in accelerated aging (or “ageing”, with British spelling).

The graphs below, from Beuchat & Chong (1998), show the glucose levels (at rest and prior to feeding) and HbA1c levels (percentage of glycated hemoglobin) in birds and mammals. HbA1c is a measure of the degree of glycation of hemoglobin, a protein found in red blood cells. As such HbA1c (given in percentages) is a good indicator of the rate of AGE formation within an animal’s body.

The glucose levels are measured in mmol/l; they should be multiplied by 18 to obtain the respective measures in mg/dl. For example, the 18 mmol/l glucose level for the Anna’s (a hummingbird species) is equivalent to 324 mg/dl. Even at that high level, well above the level of a diabetic human, the Anna’s hummingbird species has an HbA1c of less than 5, which is lower than that for most insulin sensitive humans.

How can that be?

There are a few possible reasons. Birds seem to have evolved better mechanisms to control cell permeability to glucose, allowing glucose to enter cells very selectively. Birds also seem to have a higher turnover of cells where glycation and thus AGE formation results. The lifespan of red blood cells in birds, for example, is only 50 to 70 percent that of mammals.

But one of the most interesting mechanisms is vitamin C synthesis. Not only is vitamin C a powerful antioxidant, but it also has the ability to reversibly bind to proteins at the sites where glycation would occur. That is, vitamin C has the potential to significantly reduce glycation. The vast majority of birds and mammals can synthesize vitamin C. Humans are an exception. They have to get it from their diet.

This may be one of the many reasons why isolated human groups with traditional diets high in fruits and starchy tubers, which lead to temporary blood glucose elevations, tend to have good health. Fruits and starchy tubers in general are good sources of vitamin C.

Grains and seeds are not.


Beuchat, C.A., & Chong, C.R. (1998). Hyperglycemia in hummingbirds and its consequences for hemoglobin glycation. Comparative Biochemistry and Physiology Part A, 120(3), 409–416.

Holmes D.J., Flückiger, R., & Austad, S.N. (2001). Comparative biology of aging in birds: An update. Experimental Gerontology, 36(4), 869-883.

Tuesday, October 5, 2010

The China Study II: Does calorie restriction increase longevity?

The idea that calorie restriction extends human life comes largely from studies of other species. The most relevant of those studies have been conducted with primates, where it has been shown that primates that eat a restricted calorie diet live longer and healthier lives than those that are allowed to eat as much as they want.

There are two main problems with many of the animal studies of calorie restriction. One is that, as natural lifespan decreases, it becomes progressively easier to experimentally obtain major relative lifespan extensions. (That is, it seems much easier to double the lifespan of an organism whose natural lifespan is one day than an organism whose natural lifespan is 80 years.) The second, and main problem in my mind, is that the studies often compare obese with lean animals.

Obesity clearly reduces lifespan in humans, but that is a different claim than the one that calorie restriction increases lifespan. It has often been claimed that Asian countries and regions where calorie intake is reduced display increased lifespan. And this may well be true, but the question remains as to whether this is due to calorie restriction increasing lifespan, or because the rates of obesity are much lower in countries and regions where calorie intake is reduced.

So, what can the China Study II data tell us about the hypothesis that calorie restriction increases longevity?

As it turns out, we can conduct a preliminary test of this hypothesis based on a key assumption. Let us say we compared two populations (e.g., counties in China), based on the following ratio: number of deaths at or after age 70 divided by number deaths before age 70. Let us call this the “ratio of longevity” of a population, or RLONGEV. The assumption is that the population with the highest RLONGEV would be the population with the highest longevity of the two. The reason is that, as longevity goes up, one would expect to see a shift in death patterns, with progressively more people dying old and fewer people dying young.

The 1989 China Study II dataset has two variables that we can use to estimate RLONGEV. They are coded as M005 and M006, and refer to the mortality rates from 35 to 69 and 70 to 79 years of age, respectively. Unfortunately there is no variable for mortality after 79 years of age, which limits the scope of our results somewhat. (This does not totally invalidate the results because we are using a ratio as our measure of longevity, not the absolute number of deaths from 70 to 79 years of age.) Take a look at these two previous China Study II posts (here, and here) for other notes, most of which apply here as well. The notes are at the end of the posts.

All of the results reported here are from analyses conducted using WarpPLS. Below is a model with coefficients of association; it is a simple model, since the hypothesis that we are testing is also simple. (Click on it to enlarge. Use the "CRTL" and "+" keys to zoom in, and CRTL" and "-" to zoom out.) The arrows explore associations between variables, which are shown within ovals. The meaning of each variable is the following: TKCAL = total calorie intake per day; RLONGEV = ratio of longevity; SexM1F2 = sex, with 1 assigned to males and 2 to females.

As one would expect, being female is associated with increased longevity, but the association is just shy of being statistically significant in this dataset (beta=0.14; P=0.07). The association between total calorie intake and longevity is trivial, and statistically indistinguishable from zero (beta=-0.04; P=0.39). Moreover, even though this very weak association is overall negative (or inverse), the sign of the association here does not fully reflect the shape of the association. The shape is that of an inverted J-curve; a.k.a. U-curve. When we split the data into total calorie intake terciles we get a better picture:

The second tercile, which refers to a total daily calorie intake of 2193 to 2844 calories, is the one associated with the highest longevity. The first tercile (with the lowest range of calories) is associated with a higher longevity than the third tercile (with the highest range of calories). These results need to be viewed in context. The average weight in this dataset was about 116 lbs. A conservative estimate of the number of calories needed to maintain this weight without any physical activity would be about 1740. Add about 700 calories to that, for a reasonable and healthy level of physical activity, and you get 2440 calories needed daily for weight maintenance. That is right in the middle of the second tercile.

In simple terms, the China Study II data seems to suggest that those who eat well, but not too much, live the longest. Those who eat little have slightly lower longevity. Those who eat too much seem to have the lowest longevity, perhaps because of the negative effects of excessive body fat.

Because these trends are all very weak from a statistical standpoint, we have to take them with caution. What we can say with more confidence is that the China Study II data does not seem to support the hypothesis that calorie restriction increases longevity.


Kock, N. (2010). WarpPLS 1.0 User Manual. Laredo, Texas: ScriptWarp Systems.


- The path coefficients (indicated as beta coefficients) reflect the strength of the relationships; they are a bit like standard univariate (or Pearson) correlation coefficients, except that they take into consideration multivariate relationships (they control for competing effects on each variable). Whenever nonlinear relationships were modeled, the path coefficients were automatically corrected by the software to account for nonlinearity.

- Only two data points per county were used (for males and females). This increased the sample size of the dataset without artificially reducing variance, which is desirable since the dataset is relatively small (each county, not individual, is a separate data point is this dataset). This also allowed for the test of commonsense assumptions (e.g., the protective effects of being female), which is always a good idea in a multivariate analyses because violation of commonsense assumptions may suggest data collection or analysis error. On the other hand, it required the inclusion of a sex variable as a control variable in the analysis, which is no big deal.

- Mortality from schistosomiasis infection (MSCHIST) does not confound the results presented here. Only counties where no deaths from schistosomiasis infection were reported have been included in this analysis. The reason for this is that mortality from schistosomiasis infection can severely distort the results in the age ranges considered here. On the other hand, removal of counties with deaths from schistosomiasis infection reduced the sample size, and thus decreased the statistical power of the analysis.

Monday, October 4, 2010

The Big Sleep

This blog usually focuses on diet, because that's my specialty. But if you want Whole Health, you need the whole package: a diet and lifestyle that is broadly consistent with our evolutionary heritage. I think we all know that on some level, but a recent paper has reminded me of it.

I somehow managed to get on the press list of the Annals of Internal Medicine. That means they send me embargoed papers before they're released to the general public. That journal publishes a lot of high-impact diet studies, so it's a great privilege for me. I get to write about the studies, and publish my analysis at the time of general release, which is the same time the news outlets publish their stories.

One of the papers they sent me recently is a fat loss trial with an interesting twist (1; see below). All participants were told to eat 10% fewer calories that usual for two weeks, however half of them were instructed to sleep for 8 and a half hours per night, and the other half were instructed to sleep for 5 and a half hours*. The actual recorded sleep times were 7:25 and 5:14, respectively.

Weight loss by calorie restriction causes a reduction of both fat and lean mass, which is what the investigators observed. Both groups lost the same amount of weight. However, 80% of the weight was lost as fat in the high-sleep group (2.4/3.0 kg lost as fat), while only 48% of it was lost as fat in the low-sleep group (1.4/2.9 kg lost as fat). Basically, the sleep-deprived group lost as much lean mass as they did fat mass, which is not good!

There are many observational studies showing associations between insufficient sleep, obesity and diabetes. However, I think studies like that are particularly vulnerable to confounding variables, so I've never known quite what to make of them. Furthermore, they often show that long sleep duration associates with poor health as well, which I find highly unlikely to reflect cause and effect. I discussed one of those studies in a post a couple of years ago (2). That's why I appreciate this controlled trial so much.

Another sleep restriction trial published in the Lancet in 1999 showed that restricting healthy young men to four hours of sleep per night caused them to temporarily develop glucose intolerance, or pre-diabetes (3).

Furthermore, their daily rhythm of the hormone cortisol became abnormal. Rather than the normal pattern of a peak in the morning and a dip in the evening, sleep deprivation blunted their morning cortisol level and enhanced it in the evening. Cortisol is a stress hormone, among other things, and its fluctuations may contribute to our ability to feel awake in the morning and ready for bed at night.

The term "adrenal fatigue", which refers to the aforementioned disturbance in cortisol rhythm, is characterized by general fatigue, difficulty waking up in the morning, and difficulty going to sleep at night. It's a term that's commonly used by alternative medical practitioners but not generally accepted by mainstream medicine, possibly because it's difficult to demonstrate and the symptoms are fairly general. Robb Wolf talks about it in his book The Paleo Solution.

The investigators concluded:
Sleep debt has a harmful impact on carbohydrate metabolism and endocrine function. The effects are similar to those seen in normal ageing and, therefore, sleep debt may increase the severity of age-related chronic disorders.
So there you have it. Besides making us miserable, lack of sleep appears to predispose to obesity and diabetes, and probably sets us up for the Big Sleep down the line. I can't say I'm surprised, given how awful I feel after even one night of six hour sleep. I feel best after 9 hours, and I probably average about 8.5. Does it cut into my free time? Sure. But it's worth it to me, because it allows me to enjoy my day much more.

Keep your room as dark as possible during sleep. It also helps to avoid bright light, particularly in the blue spectrum, before bed (4). "Soft white" bulbs are preferable to full spectrum in the evening. If you need to use your computer, dim the monitor and adjust it to favor warm over cool colors. For people who sleep poorly due to anxiety, meditation before bed can be highly effective. I posted a tutorial here.

1. Nedeltcheva, AV et al. "Insufficient Sleep Undermines Dietary Efforts to Reduce Adiposity." Annals of Internal Medicine. 2010. Advanced publication.

* The study was a randomized crossover design with a 3 month washout period, which I consider a rigorous design. I think the study overall was very clever. The investigators used calorie restriction to cause rapid changes in body composition so that they could see differences on a reasonable timescale, rather than trying to deprive people of sleep for months and look for more gradual body fat changes without dietary changes. The latter experiment would have been more interesting, but potentially impractical and unethical.

Saturday, October 2, 2010

Potatoes and Human Health, Part III

Potato-eating Cultures: the Quechua

The potato is thought to have originated in what is now Peru, on the shores of lake Titicaca. Native Peruvians such as the Quechua have been highly dependent on the potato for thousands of years. A 1964 study of the Quechua inhabitants of Nuñoa showed that they obtained 74% of their calories from potatoes (fresh and chuños), 10% from grains, 10% from Chenopodia (quinoa and cañihua), and 4% from animal foods. Total energy intake was 3,170 calories per day (1).

In 2001, a medical study of rural Quechua men reported an average body fat percentage of 16.4% (2). The mean age of the volunteers was 38. Body fat did increase slowly with age in this population, and by age 65 it was predicted to be about 20% on average. That's below the threshold of overweight, so I conclude that most men in this population are fairly lean, although there were a few overweight individuals.

In 2004, a study in rural Quechua women reported a body fat percentage of 31.2% in volunteers with a mean age of 35 (3). Body fat percentage was higher in a group of Quechua immigrants to the Peruvian capital of Lima. Among rural women, average fasting insulin was 6.8 uIU/mL, and fasting glucose was 68.4 mg/dL, which together suggest good insulin sensitivity and glucose control (4). Insulin and glucose were considerably lower in the rural group than the urban group. Blood pressure was low in both groups. Overall, this suggests that overweight is common among Quechua women.

Rural Quechua are characteristically short, with the average adult man standing no more than 5' 2" (2). One might be tempted to speculate that this reflects stunting due to a deficient diet. However, given the fact that nearly all non-industrial populations, including contemporary hunter-gatherers, are short by modern standards, I'm not convinced the Quechua are abnormal. A more likely explanation is that industrial foods cause excessive tissue growth in modern populations, perhaps by promoting overeating and excessive insulin and IGF-1 production, which are growth factors. I first encountered this hypothesis in Dr. Staffan Lindeberg's book Food and Western Disease.

I don't consider the Quechua diet to be optimal, but it does seem to support a reasonable level of metabolic health. Rural Quechua men subsisting on potatoes are relatively lean, while women are often overweight, though less overweight than urban Quechua who eat fewer potatoes. Unfortunately, I don't have more detailed data on other aspects of their health, such as gastrointestinal health.

Potato-eating Cultures: the Aymara

The Aymara are another potato-dependent people of the Andes, who span Peru, Bolivia and Chile. The first paper I'll discuss is titled "Low Prevalence of Type II Diabetes Despite a High Body Mass Index in the Aymara Natives From Chile", by Dr. Jose Luis Santos and colleagues (5). In the paper, they show that the prevalence of diabetes in this population was 1.5%, and the prevalence of pre-diabetes was 3.6%. The prevalence of both remained low even in the elderly. Here's a comparison of those numbers with figures from the modern United States (6):

That's quite a difference! The prevalence of diabetes in this population is low, but not as low as in some cultures such as the Kitavans (7, 8).

Now to discuss the "high body mass index" referenced in the title of the paper. The body mass index (BMI) is the relation between height and weight, and often, but not always, reflects fatness. The average BMI of this population was 24.9, which is very close to the cutoff between normal and overweight (25).

Investigators were surprised to find such a low prevalence of diabetes in this population, despite their apparent high prevalence of overweight. Yet if you've seen pictures of rural native South Americans, you may have noticed they're built short and thick, with wide hips and big barrel chests. Could this be confounding the relationship between BMI and body fatness? To answer that question, I found another paper that estimated body fat using skinfold measurements (9). That study reported that both men and women remained relatively lean throughout life (ages 4-65), with only two of 23 subjects classified as overweight on the basis of body fat percentage, and none classified as obese.

Back to the first paper. In this Aymara group, blood pressure was on the high side. Serum cholesterol was also a bit high for a traditionally-living population, but still lower than most modern groups (~188 mg/dL). I find it very interesting that the cholesterol level in this population that eats virtually no fat was the same as on Tokelau, where nearly half of calories come from highly saturated coconut fat (10, 11). Fasting insulin is also on the high side in the Aymara, which is also interesting given their good glucose tolerance and low prevalence of diabetes.

This shows that a lifetime of high-carbohydrate, high-glycemic food does not necessarily lead to overweight or metabolic problems in the context of a traditional diet and lifestyle.

Potato-eating Cultures: the Irish

Potatoes were introduced to Ireland in the 17th century. They were well suited to the cool, temperate climate, and more productive than any other crop. By the early 18th century, potatoes were the main source of calories, particularly for the poor who ate practically nothing else. In 1839, the average Irish laborer obtained 87% of his calories from potatoes (12). In 1845, the potato blight Phytophthora infestans struck, decimating potato plantations nationwide and creating the Great Famine.

There isn't much reliable information on the health status of the Irish prior to the famine, besides reports of vitamin A deficiency symptoms (13). However, they had a very high fertility rate, and anecdotal reports described them as healthy and attractive (14):
As far as fecundity is concerned, the high nutritional value of the potato diet might have played a significant role, but little supportive evidence has been presented so far... What is known is that the Irish in general and Irish women in particular were widely described as healthy and good-looking. Adam Smith's famous remark that potatoes were "peculiarly suitable to the health of the human constitution" can be complemented with numerous observations from other contemporary observers to the same effect.
Controlled Feeding Studies

Starting nearly a century ago, a few scientists decided to feed volunteers potato-only diets to achieve various research objectives. The first such experiment was carried out by a Dr. M. Hindhede and published in 1913 (described in 15). Hindhede's goal was to explore the lower limit of the human protein requirement and the biological quality of potato protein. He fed three healthy adult men almost nothing but potatoes and margarine for 309 days (margarine was not made from hydrogenated seed oils at the time), all while making them do progressively more demanding physical labor. They apparently remained in good physical condition. Here's a description of one of his volunteers, a Mr. Madsen, from another book (described in 16; thanks to Matt Metzgar):
In order to test whether it was possible to perform heavy work on a strict potato diet, Mr. Madsen took a place as a farm laborer... His physical condition was excellent. In his book, Dr. Hindhede shows a photograph of Mr. Madsen taken on December 21st, 1912, after he had lived for almost a year entirely on potatoes. This photograph shows a strong, solid, athletic-looking figure, all of whose muscles are well-developed, and without excess fat. ...Hindhede had him examined by five physicians, including a diagnostician, a specialist in gastric and intestinal diseases, an X-ray specialist, and a blood specialist. They all pronounced him to be in a state of perfect health.
Dr. Hindhede discovered that potato protein is high quality, providing all essential amino acids and high digestibility. Potato protein alone is sufficient to sustain an athletic man (although that doesn't make it optimal). A subsequent potato feeding study published in 1927 confirmed this finding (17). Two volunteers, a man and a woman, ate almost nothing but potatoes with a bit of lard and butter for 5.5 months. The man was an athlete but the woman was sedentary. Body weight and nitrogen balance (reflecting protein gain/loss from the body) remained constant throughout the experiment, indicating that their muscles were not atrophying at any appreciable rate, and they were probably not putting on fat. The investigators remarked:
The digestion was excellent throughout the experiment and both subjects felt very well. They did not tire of the uniform potato diet and there was no craving for change.
In one of his Paleo Diet newsletters titled "Consumption of Nightshade Plants (Part 1)", Dr. Loren Cordain referenced two feeding studies showing that potatoes increase the serum level of the inflammatory cytokine interleukin-6 (22, 23). However, one study was not designed to determine the specific role of potato in the change (two dietary factors were altered simultaneously), and the other used potato chips as the source of potato. So I don't find these studies particularly relevant to the question at hand.

Just yesterday, Chris Voigt of the Washington State Potato Commission embarked on his own n=1 potato feeding experiment as a way to promote Washington state potatoes. He'll be eating nothing but potatoes and a little fat for two months, and getting a full physical at the end. Check out his website for more information and updates (18). Mr. Voigt has graciously agreed to a written interview with Whole Health Source at the end of his experiment. He pointed out to me that the Russet Burbank potato, the most popular variety in the United States, is over 135 years old. Stay tuned for more interesting facts from Mr. Voigt in early December.

Observational Studies

With the recent interest in the health effects of the glycemic index, a few studies have examined the association between potatoes and health in various populations. The results are all over the place, with some showing positive associations with health, and others showing negative associations (19, 20, 21). As a whole, I find these studies difficult to interpret and not very helpful.


Some people feel good when they eat potatoes. Others find that potatoes and other members of the nightshade family give them digestive problems, exacerbate their arthritis, or cause fat gain. I haven't encountered any solid data to substantiate claims that nightshades aggravate arthritis or other inflammatory conditions. However, that doesn't mean there aren't individuals who are sensitive. If potatoes don't agree with you, by all means avoid them.

The Bottom Line

You made it to the end! Give yourself a pat on the back. You deserve it.

In my opinion, the scientific literature as a whole, including animal and human studies, suggests rather consistently that potatoes can be a healthy part of a varied diet for most people, and they probably do not generally promote digestive problems, fat gain, or metabolic dysfunction.  Nevertheless, I wouldn't recommend eating nothing but potatoes for any length of time. If you do choose to eat potatoes, follow these simple guidelines:
  • Don't eat potatoes that are green, sprouting, blemished, or damaged
  • Store them in a cool, dark place. They don't need to be refrigerated but it will extend their life
  • Peel them before eating if you rely on them as a staple food
Enjoy your potatoes!