The anatomy of a VAP test report

The vertical auto profile (VAP) test is an enhanced lipid profile test. It has been proposed, as a more complete test that relies on direct measurement of previously calculated lipid measures. The VAP test is particularly known for providing direct measurements of LDL cholesterol, instead of calculating them through equations ().

At the time of this writing, a typical VAP test report would provide direct measures of the cholesterol content of LDL, Lp(a), IDL, HDL, and VLDL particles. It would also provide additional measures referred to as secondary risk factors, notably particle density patterns and apolipoprotein concentrations. Finally, it would provide a customized risk summary and some basic recommendations for treatment. Below is the top part of a typical VAP test report (from the company Atherotech), showing measures of the cholesterol content of various particles. LDL cholesterol is combined for four particle subtypes, the small-dense subtypes 4 and 3, and the large-buoyant subtypes 2 and 1. A breakdown by LDL particle subtype is provided later in the VAP report.

In the table above, HDL cholesterol is categorized in two subtypes, the small-dense subtype 2, and the large-buoyant subtype 3. Interestingly, most of the HDL cholesterol in the table is supposedly of the least protective subtype, which seems to be a common finding in the general population. VLDL cholesterol is categorized in a similar way. IDL stands for intermediate-density lipoprotein; this is essentially a VLDL particle that has given off some of its content, particularly its triglyceride (or fat) cargo, but still remains in circulation.

Lp(a) is a special subtype of the LDL particle that is purported to be associated with markedly atherogenic factors. Mainstream medicine generally considers Lp(a) particles themselves to be atherogenic, which is highly debatable. Among other things, cardiovascular disease (CVD) risk and Lp(a) concentration follow a J-curve pattern, and Lp(a)’s range of variation in humans is very large. A blog post by Peter (Hyperlipid) has a figure right at the top that illustrates the former J-curve assertion (). The latter fact, related to range of variation, generally leads to a rather wide normal distribution of Lp(a) concentrations in most populations; meaning that a large number of individuals tend to fall outside Lp(a)’s optimal range and still have a low risk of developing CVD.

Below is the middle part of a typical VAP report, showing secondary risk factors, such as particle density patterns and apolipoprotein concentrations. LDL particle pattern A is considered to be the most protective, supposedly because large-buoyant LDL particles are less likely to penetrate the endothelial gaps, which are about 25 nm in diameter. Apolipoproteins are proteins that bind to fats for their transport in lipoproteins, to be used by various tissues for energy; free fatty acids also need to bind to proteins, notably albumin, to be transported to tissues for use as energy. Redundant particles and processes are everywhere in the human body!

Below is the bottom part of a typical VAP report, providing a risk summary and some basic recommendations. One of the recommendations is “to lower” the LDL target from 130mg/dL to 100mg/dL due to the presence of the checked emerging risk factors on the right, under “Considerations”. What that usually means in practice is a recommendation to take drugs, especially statins, to reduce LDL cholesterol levels. A recent post here and the discussion under it suggest that this would be a highly questionable recommendation in the vast majority of cases ().

What do I think about VAP tests? I think that they are useful in that they provide a lot more information about one’s lipids than standard lipid profiles, and more information is better than less. On the other hand, I think that people should be very careful about what they do with that information. There are even more direct tests that I would recommend before a decision to take drugs is made (, ), if that decision is ever made at all.

Familial hypercholesteromia: Why rely on cholesterol levels when more direct measures are available?

There are two forms of familial hypercholesteromia (FH), namely heterozygous and homozygous FH. In heterozygous FH only one copy of the gene that causes it is present, inherited either from the father or the mother. In homozygous FH, which is the most lethal form, two copies of the gene are present. FH is associated with early-onset cardiovascular disease (CVD).

Homozygous FH may happen if both the father and mother have heterozygous or homozygous FH. If both the father and mother have heterozygous FH, the likelihood that at least one in four children will have homozygous FH will be high. If both parents have homozygous FH the likelihood that all children will have homozygous FH will be high.

In fact, in the latter case, homozygous FH in the children is almost certain. One case in which it won’t occur is if the combining FH gene from the father or mother mutates into a non-FH gene before it is used in the assembly of the genome of the child. A gene mutation in a specific locus, only for the father or mother, is an unlikely event, and would lead to heterozygous FH. Two gene mutations at once in the same locus, for the father and mother, is a very unlikely event.

By the way, despite what many are led to believe based on fictional characters in movies and series like the X-Men and Hulk, mutations in functional genes usually lead to harmful traits. In our evolutionary past, those traits would have been largely removed from the gene pool by selection, making them rare or nonexistent in modern humans. Today we have modern medicine; a double-edged sword.

Mutations leading to super-human traits are very, very unlikely. The myostatin gene, for example, suppresses muscle growth. And yet the mutations that lead to little or no secretion of the related myostatin protein are very uncommon. Obviously they have not been favored by selection, even though their holders are very muscular – e.g., Germany’s “Incredible Hulky” ().

Okay, back to FH. Xanthelasmas are relatively common among those who suffer from FH (see photo below, from Globalskinatlas.com). They are skin deposits of cholesterol, have a genetic basis, and are NOT always associated with FH. This is important – several people have xanthelasmas but not FH.

FH is a fairly rare disease, even in its heterozygous form, with an overall incidence of approximately 0.2 percent. That is, about 1 in 500 people in the general population will have it. Genetically related groups will see a much higher or lower rate of incidence, as the disease is strongly influenced by a genetic mutation. This genetic mutation is apparently in the LDL receptor gene, located on the short arm of chromosome 19.

The table below, from a study by Miltiadous and colleagues (), paints a broad picture of the differences one would typically see between heterozygous FH sufferers and non-FH controls.

The main difference is in total cholesterol and in the relatively large contribution of LDL to total cholesterol. A large difference is also seen in Apolipoprotein B (indicated as "Apo B"), which acts as a LDL transporter (not to be confused with a LDL receptor). The LDL cholesterol shown on the table is calculated through the Friedewald equation, which is notoriously imprecise at low triglyceride levels ().

Looking at the total cholesterol row on the table, and assuming that the numbers after the plus/minus signs are standard deviations, we can conclude that: (a) a little more than two-thirds of the heterozygous FH sufferers had total cholesterol levels falling in between 280 and 446; and (b) a little more than two-thirds of the non-FH controls had total cholesterol levels falling in between 135 and 225.

Keep in mind that about 13.5 percent {calculated as: (95-68)/2} of the non-FH controls had total cholesterol levels between 225 and 270. This is a nontrivial percentage; i.e., these may be a minority but are not rare individuals. Heterozygous FH sufferers are rare, at 0.2 percent of the general population. Moreover, about 2 percent of the non-FH controls had non-pathological total cholesterol levels between 270 and 315. That is not so rare either, amounting to an “incidence” 10 times higher than heterozygous FH.

What would happen if people with heterozygous FH were to replace refined carbohydrates and sugars with saturated fat and cholesterol in their diets? Very likely their already high total cholesterol would go up higher, in part because their HDL cholesterol would go up (). Still, how could they be sure that CVD progression would accelerate if they did that?

According to some studies, the higher HDL cholesterol would either be generally protective or associated with protective factors, even among those with FH (). One of those protective factors may be a more nutrient-dense diet, as many foods rich in cholesterol are very nutrient-dense – e.g., eggs, organ meats, and seafood.

This brings me to my main point in this post. It is mainstream practice to diagnose people with FH based on total and/or LDL cholesterol levels. But the main problem with FH is that it leads to early onset of CVD, which can be measured more directly through simple tests, such as intima-media thickness and related ultrasound plaque tests (). These are noninvasive tests, done in 5 minutes or so, and often covered by insurance.

Even if simple direct tests are not perfect, it seems utterly nonsensical to rely on cholesterol measures to diagnose and treat FH, given the possible overlap between pathological and non-pathological high total cholesterol levels.

Daniel Suelo, the man who quit money, seems remarkably healthy

Daniel James Shellabarger (better known as Daniel Suelo) is portrayed in the bestselling 2012 nonfiction book by Mark Sundeen titled “The Man Who Quit Money” ().

Apparently Suelo stopped using money in 2000, and lives in a cave near the city of Moab in Utah. His diet comprises primarily wild vegetables and fruits, insects, and road kill; as well as discarded or donated food he gets from others when he visits the city. The photo below is from a recent BBC documentary. An interesting 2006 YouTube clip on Suelo is titled “Moneyless in Moab” ().

Suelo is listed as having been born in 1961 (), and the photo above appears to have been taken in 2012. If these dates are correct, he is 51 in the photo above. I cannot help but think that he looks remarkably healthy. The 40-50 age period is one that often sets the stage for many diseases of civilization in urban societies.

Suelo’s decision seems like a radical one, at least to me. There are always complex motivations behind radical decisions. In the case of Suelo, some of these motivations are captured in the comment below, which is part of a review of the book “The Man Who Quit Money” posted on Amazon.com by a reader.

[…] a picture of Suelo not as an untarnished hero, but a man who has wrestled with heartbreak, depression, disillusionment with his family's faith, and his repugnance to working for the pure sake of making money and buying things. Whether or not you are inspired to follow Suelo's example, this book will make you think.

Many people have been inspired by Suelo’s story, to some extent because they see that adopting a radical form of “simple living” () may not only be possible but also liberating. Obviously Suelo’s lifestyle, as it is now, would not be possible without the help of others who adopt a more “traditional” lifestyle. Below is a critical review by a reader of the book, posted on Amazon.com, which harshly reflects this perspective.

Any infantile mentality charmed by this inane story should simply generalize the message - visualize a world in which all of us live like the parasitic protagonist. How fortunate for Suelo that there are still people who engage in productive work and indirectly and unknowingly keep the human sponge alive […] Suelo never quit money he simply quit contributing anything and continues to survive simply as a parasite.

Still, Suelo’s story is interesting, including from a human health perspective. An article on Details.com by Christopher Ketcham provides a glimpse at what a day in Suelo’s life looks like (). It seems that on most days he has one main meal per day.

It is hard to get a sense of the nutrient composition of his diet. It looks like his diet is limited in but not devoid of industrial foods, and one in which food consumption is sporadic, opportunistic, and driven primarily by hunger and availability – not by stress or set meal times, for example.

He probably walks a lot; his cave is one hour away from Moab by foot, and it looks like he goes to Moab often. Apparently he almost never gets sick.

Suelo also writes a blog (), which has many followers, and also maintains other websites, from the Public Library in Moab. His first blog post has over 1,000 comments under it ().

The 2012 Atherosclerosis egg study: Plaque decreased as LDL increased with consumption of 2.3 eggs per week or more

A new study by David Spence and colleagues, published online in July 2012 in the journal Atherosclerosis (), has been gaining increasing media attention (e.g., ). The article is titled: “Egg yolk consumption and carotid plaque”. As the title implies, the study focuses on egg yolk consumption and its association with carotid artery plaque buildup.

The study argues that “regular consumption of egg yolk should be avoided by persons at risk of cardiovascular disease”. It hints at egg yolks being unhealthy in general, possibly even more so than cigarettes. Solid critiques have already been posted on blogs by Mark Sisson, Chris Masterjohn, and Zoe Harcombe (, , ), among others.

These critiques present valid arguments for why the key findings of the study cannot be accepted, especially the finding that eggs are more dangerous to one’s health than cigarettes. This post is a bit different. It uses the data reported in the study to show that it (the data) suggests that egg consumption is actually health-promoting.

I used the numbers in Table 2 of the article to conduct a test that is rarely if ever conducted in health studies – a moderating effect test. I left out the “egg-yolk years” variable used by the authors, and focused on weekly egg consumption (see Chris’s critique). My analysis, using WarpPLS (), had to be done only visually, because using values from Table 2 meant that I had access only to data on a few variables organized in quintiles. That is, my analysis here using aggregate data is an N=5 analysis; a small sample indeed. The full-text article is not available publicly; Zoe was kind enough to include the data from Table 2 in her critique post.

Below is the model that I used for the moderating effect test. It allowed me to look into the effect that the variable EggsWk (number of eggs consumed per week) had on the association between LDL (LDL cholesterol) and Plaque (carotid plaque). This type of effect, namely a moderating effect, is confusing to many people, because it is essentially the effect that a variable has on the effect of another variable on a third. Still, being confusing does not mean being less important. I should note that this type of effect is similar to a type of conditional association tested via Bayesian statistics – if one eats more eggs, what is the association between having a high LDL cholesterol and plaque buildup?

You can see what is happening visually on the graph below. The plot on the left side is for low weekly egg consumption. In it, the association between LDL cholesterol and plaque is positive – eating fewer eggs, plaque and LDL increase together. The plot on the right side is for high weekly egg consumption. In this second plot, the association between LDL cholesterol and plaque is negative – eating more eggs, plaque decreases as LDL increases. And what is the turning point? It is about 2.3 eggs per week.

So the “evil” particle, the LDL, is playing tricks with us; but thankfully the wonderful eggs come to the rescue, right? Well, it looks a bit like it, but maybe other foods would have a similar effect. In part because of the moderating effect discussed above, the multivariate association between LDL cholesterol and plaque was overall negative. This multivariate association was estimated controlling for the moderating effect of weekly egg consumption. You can see this on the plot below.

The highest amount of plaque is at the far left of the plot. It is associated with the lowest LDL cholesterol quintile. (So much for eggs causing plaque via LDL cholesterol eh!?) What is happening here? Maybe egg consumption above a certain level shifts the size of the LDL particles from small to large, making the potentially atherogenic ones harmless. (Saturated fat consumption, in the context of a nutritious diet in lean individuals, seems to have a similar effect.) Maybe eggs contain nutrients that promote overall health, leading LDL particles to "behave" and do what they are supposed to do. Maybe it is a combination of these and other effects.

Ancestral Health Symposium 2012: Evolutionarily sound diets and lifestyles may revolutionize health care

The Ancestral Health Symposium 2012 was very interesting on many levels. Aaron Blaisdell and the team of volunteers really did a superb job at organizing the Symposium. Boston is a great city with an excellent public transportation system, something that is always great for meetings, and a great choice for the Symposium. Needless to say, so was Harvard. Even though the program was packed there were plenty of opportunities to meet and talk with several people during the breaks.

We had our panel “New Technologies and New Opportunities”, which Paul Jaminet moderated. The panelists were Chris Keller, Chris Kresser, Dan Pardi, and myself. The first photo below, by Bobby Gill, shows Chris Keller speaking; I am on the far left looking at the screen. The second photo, by Beth Mazur, shows all the panelists. The third photo, also by Bobby Gill, shows a group of us talking to Stephan Guyenet after his presentation.

I talked a bit toward the end of the panel about the importance of taking nonlinearity into consideration in analyses of health data, but ended up being remembered later for saying that “men are women with a few design flaws”. I said that to highlight the strong protective effect of being female in terms of health, which was clear from the model I was discussing.

There is a good evolutionary reason for the protective effect of being female. Evolution is a population phenomenon. Genes do not evolve; neither do individuals. Populations evolve through the spread or disappearance of genotypes. A healthy population with 99 men and 1 woman will probably disappear quickly, and so will its gene pool. A healthy population with 99 women and 1 man will probably thrive, even with the drag of inbreeding depression. Under harsh environmental conditions, the rate of female-to-male births goes up, in some cases quite a lot.

I was able to talk to, or at least meet briefly face-to-face with, many of the people that I have interacted with online on this blog and other blogs. Just to name a few: Miki Ben-Dor, Aaron Blaisdell, Emily Deans, Andreas Eenfeldt, Glenn Ellmers, Benjamin Gebhard, Stephan Guyenet, Dallas Hartwig, Melissa Hartwig, Paul Jaminet, Chris Keller, Chris Kresser, Mathieu Lalonde, Robert Lustig, Chris Masterjohn, Beth Mazur, Denise Minger, Jimmy Moore, Katherine Morrison, Richard Nikoley, Dan Pardi, Kamal Patel, David Pendergrass, Mark Sisson, Mary Beth Smrtic, J. Stanton, Carlos Andres Toro, and Grayson Wheatley.

It would have been nice to have Peter (from Hyperlipid) there, as I think a lot of the attendants are fans. I attended Jamie Scott’s very interesting talk, but ended up not being able to chat with him. This is a pity because we share some common experiences – e.g., I lived in New Zealand for a few years. I did have the opportunity to talk at some length with J. Stanton, who is an inspiration. It was also great to exchange some ideas with my panelists, Miki Ben-Dor, Emily Deans, Stephan Guyenet, Chris Masterjohn, Kamal Patel, and David Pendergrass. I wish I had more time to talk with Denise Minger, who is clearly a very nice person in addition to being very smart. Talking about a smart person, it was also nice chatting a bit with Richard Nikoley; a successful entrepreneur who is in the enviable position of doing what he feels like doing.

I could not help but notice a tendency among some participants (perhaps many, judging from online threads) to pay a lot of attention to how other people looked in a very judgmental way. That person is too fat, his/her face is too red, she/he looks too old etc. So was this supposed to be the Ancestral Health Pageant 2012? There is nothing wrong with looking good. But many people adopt an evolution-inspired lifestyle because they are quite unhealthy to start with. And this includes some of the presenters. It takes time to change one’s health, relapses occur, and no one is getting younger. Moreover, some of the presenters’ ideas and advice may have much more dramatic positive effects on people other than themselves, because of their own pre-existing conditions. The ideas and advice are still solid.

A message that I think this Symposium conveyed particularly well was that an evolutionarily sound diet and lifestyle can truly revolutionize our health care system. Robb Wolf’s talk in particular, based on his recent experience in Nevada with law enforcement officers, made this point very effectively. The title of the talk is “How Markets and Evolution Can Revolutionize Medicine”. One very interesting idea he put forth was that establishments like gyms could expand the range of support activities they offer their customers, officially becoming the beginning of the health care chain. There are already health insurance plans that offer premium reductions for those who go to gyms. Being part of the health care chain would be different and a significant step forward - diet and exercise are powerful "drugs".

One thing that caught me a bit off-guard was Robb’s strong advocacy of the use of a drug, namely metformin (a.k.a. glucophage); even preventively in some special cases, such as with sleep-deprived law enforcement officers. I have to listen to that talk again when it is up online, to make sure that I understood it correctly. It seems to me that changing the nature of shift work among law enforcement officers, at least partially, may be a better target; current practices appear not only to impair the officers’ health but also their effectiveness in law enforcement activities. Besides, I think we need to better understand the nature and functions of cortisol, which is viewed by many as a hormone that exists only to do us harm.

Sleep deprivation is associated with an elevation in cortisol production. Elevated cortisol levels lead over time to visceral fat accumulation, which promotes systemic inflammation. Systemic inflammation is possibly the root cause of most diseases of civilization. But cortisol itself has powerful anti-inflammatory properties, and visceral fat is generally easy to mobilize through intense exercise – probably one of the key reasons why we have visceral fat. I think we need to understand this situation a bit better before thinking about preventive uses of metformin, which nevertheless is a drug that seems to do wonders in the treatment of type 2 diabetes.

Beth Mazur was kind enough to put up a post with links to various Ancestral Health Symposium 2012 summary posts, as well as pictures. Paul Jaminet has a post with an insightful discussion of our panel at the Symposium.

The 14-percent advantage of eating little and then a lot: Putting it in practice

In another post () I discussed evidence that the human body may react to “eating big” as it would to overfeeding, increasing energy expenditure by a certain amount. That increase seems to lead to a reduction in the caloric value of the meals during overfeeding; a reduction that seems to gravitate around 14 percent of the overfed amount.

And what is the overfed amount? Let us assume that your daily calorie intake to maintain your current body weight is 2,000 calories. However, one day you consume 1,000 calories, and the next 3,000 – adding up to 4,000 calories in 2 days. This amounts to 2,000 calories per day on average, the weight maintenance amount; but the extra 1,000 on the second day is perceived by your body as overfeeding. So 140 calories are “lost”.

The mechanisms by which this could happen are not entirely clear. Some studies contain clues; one example is the 2002 study conducted with mice by Anson and colleagues (), from which the graphs below were taken.

In the graphs above AL refers to ad libitum feeding, LDF to limited daily feeding (40 percent less than AL), IF to intermittent (alternate-day) fasting, and PF to pair-fed mice that were provided daily with a food allotment equal to the average daily intake of mice in the IF group. PF was added as a control condition; in practice, the 2-day food consumption was about the same in AL, IF and PF.

After a 20-week period, intermittent fasting was associated with the lowest blood glucose and insulin concentrations (graphs a and b), and the highest concentrations of insulin growth factor 1 and ketones (graphs c and d). These seem to be fairly positive outcomes. In humans, they would normally be associated with metabolic improvements and body fat loss.

Let us go back to the 14 percent advantage of eating little and then a lot; a pattern of eating that can be implemented though intermittent fasting, as well as other approaches.

So it seems that if you consume the same number of calories, but you do that while alternating between underfeeding and overfeeding, you actually “absorb” 14 percent fewer calories – with that percentage applied to the extra calorie intake above the amount needed for weight maintenance.

And here is a critical point: energy expenditure does not seem to be significantly reduced by underfeeding, as long as it is short-term underfeeding – e.g., about 24 h or less. So you don’t “gain back” the calories due to a possible reduction in energy expenditure in the (relatively short) underfeeding period.

What do 140 calories mean in terms of fat loss? Just divide that amount by 9 to get an estimate; about 15 g of fat lost. This is about 1 lb per month, and 12 lbs per year. Does one lose muscle due to this, in addition to body fat? A period of underfeeding of about 24 h or less should not be enough to lead to loss of muscle, as long as one doesn’t do glycogen-depleting exercise during that period ().

Also, underfeeding appears to increase the body’s receptivity to both micronutrients and macronutrients. This applies to protein, carbohydrates, vitamins etc. For example, the activity of liver and muscle glycogen synthase is significantly increased by underfeeding (the scientific term is “phosphorylation”), particularly carbohydrate underfeeding, effectively raising the insulin sensitivity of those tissues.

The same happens, in general terms, with a host of other tissues and nutrients; often mediated by enzymes. This means that after a short period of underfeeding your body is primed to absorb micronutrients and macronutrients more effectively, even as it uses up some extra calories – leading to a 14 percent increase in energy expenditure.

There are many ways in which this can be achieved. Intermittent fasting is one of them; with 16-h to 24-h fasts, for example. Intermittent calorie restriction is another; e.g., with a 1/3 and 2/3 calorie consumption pattern across two-day periods. Yet another is intermittent carbohydrate restriction, with other macronutrients kept more or less constant.

If the same amount of food is consumed, there is evidence suggesting that such practices would lead to body weight preservation with improved body composition – same body weight, but reduced fat mass. This is what the study by Anson and colleagues, mentioned earlier, suggested.

A 2005 study by Heilbronn and colleagues on alternate day fasting by humans suggested a small decrease in body weight (); although the loss was clearly mostly of fat mass. Interestingly, this study with nonobese humans suggested a massive decrease in fasting insulin, much like the mice study by Anson and colleagues.

Having said all of the above, there may be people who gain body fat by alternating between eating little and a lot. Why would that be? A possible reason is that when they eat a lot their caloric intake exceeds the increased energy expenditure.

The 14-percent advantage of eating little and then a lot: Is it real?

When you look at the literature on overfeeding, you see a number over and over again – 14 percent. That is approximately the increase in energy expenditure you get when you overfeed people; that is, when you feed people more calories that they need to maintain their current weight.

This phenomenon is related to another interesting one: the nonlinear increase in body weight and fat mass following overfeeding after a period starvation, illustrated by the top graph below from an article by Kevin Hall (). The data for the squares on the top graph is from the Minnesota Starvation Experiment (). The graph at the bottom is based mostly on the results of a simulation, and doesn’t clearly reflect the phenomenon.

Due to the significant amount of weight lost in what is called above the semistarvation stage (SS), the controlled refeeding period (CR) actually involved significant overfeeding. Nevertheless, weight was not gained right away, due to a sharp increase in energy expenditure. That is illustrated by the U-curve shape of the weight gain in response to overfeeding. Initially the gain is minimal, increasing over time, and continuing through the ad libitum refeeding stage (ALR).

Interestingly, overfeeding leads to increased energy expenditure almost immediately after it starts happening. It seems that even one single unusually big meal will significantly increase energy expenditure. Also, the 14 percent is usually associated with meals with a balanced amount of macronutrients. That percentage seems to go down if the balance is significantly shifted toward dietary fat (), probably because the metabolic “cost” of converting dietary fat into body fat is low. In other words, large meals with a lot of fat in them tend to cause a reduced increase in energy expenditure – less than 14 percent. Shifting the balance to protein appears to have the opposite effect, increasing energy expenditure even more, probably because protein is the jack-of-all-trades among macronutrients ().

The calorie surplus used in experiments where the 14 percent increase in energy expenditure is observed is normally around 1,000 calories, but the percentage seems to hold steady when people are overfed to different degrees () (). Let us assume that one is overfed 1,000 calories. What happens? About 140 calories are “lost” due to overfeeding.

What does this have to do with eating little, and then a lot, in an alternate way? It allows for some reasonable speculation, based on a simple pattern: when you alternate between underfeeding and overfeeding, you reduce food consumption for short period of time (usually less than 24 h), and then eat big, because you are hungry.

It is reasonable to assume, based on the empirical evidence on what happens during overfeeding, that the body reacts to “eating big” as it would to overfeeding, increasing energy expenditure by a certain amount. That increase leads to a reduction in the caloric value of the meals during overfeeding; a reduction of about 14 percent of the overfed amount.

But the body does not seem to significantly decrease energy expenditure if one reduces food consumption for a short period of time, such as 24 h. So you have the potential here for some steady fat loss without a reduction in caloric intake. Keeping a calorie intake up above a certain point is more important than many people think, because a calorie intake that is too low may lead to nutrient deficiencies (). This is possibly one of the reasons why carrying a bit of extra weight is associated with increased longevity in relatively sedentary populations ().

Is this 14-percent effect real, or just another mirage? If yes, what does it possibly translate into in terms of fat loss? More on these issues is coming in the next post.