Sudden cholesterol increase? It may be psychological

There are many published studies with evidence that cholesterol levels are positively associated with heart disease. In multivariate analyses the effects are usually small, but they are still there. On the other hand, there is also plenty of evidence that cholesterol is beneficial in terms of health. Here of course I am referring to the health of humans, not of the many parasites that benefit from disease.

For example, there is evidence () that cholesterol levels are negatively associated with mortality (i.e., higher cholesterol leading to lower mortality), and are positively associated with vitamin D production from skin exposure to sunlight ().

Most of the debris accumulated in atheromas are made up of macrophages, which are specialized cells that “eat” cell debris (ironically) and some pathogens. The drug market is still hot for cholesterol-lowering drugs, often presented in TV and Internet ads as effective tools to prevent formation of atheromas.

But what about macrophages? What about calcium, another big component of atheromas? If drugs were to target macrophages for atheroma prevention, drug users may experience major muscle wasting and problems with adaptive immunity, as macrophages play a key role in muscle repair and antibody formation. If drugs were to target calcium, users may experience osteoporosis.

So cholesterol is the target, because there is a “link” between cholesterol and atheroma formation. There is also a link between the number of house fires in a city and the amount of firefighting activity in the city, but we don’t see mayors announcing initiatives to reduce the number of firefighters in their cities to prevent house fires.

When we talk about variations in cholesterol, we usually mean variations in cholesterol carried by LDL particles. That is because LDL cholesterol seems to be very “sensitive” to a number of factors, including diet and disease, presenting quite a lot of sudden variation in response to changes in those factors.

LDL particles seem to be intimately involved with disease, but do not be so quick to conclude that they cause disease. Something so widespread and with so many functions in the human body could not be primarily an agent of disease that needs to be countered with statins. That makes no sense.

Looking at the totally of evidence linking cholesterol with health, it seems that cholesterol is extremely important for the human body, particularly when it is under attack. So the increases in LDL cholesterol associated with various diseases, notably heart disease, may not be because cholesterol is causing disease, but rather because cholesterol is being used to cope with disease.

LDL particles, and their content (including cholesterol), may be used by the body to cope with conditions that themselves cause heart disease, and end up being blamed in the process. The lipid hypothesis may be a classic case of reverse causation. A case in point is that of cholesterol responses to stress, particularly mental stress.

Grundy and Griffin () studied the effects of academic final examinations on serum cholesterol levels in 2 groups of medical students in the winter and spring semesters (see table below). During control periods, average cholesterol levels in the two groups were approximately 213 and 216 mg/dl. During the final examination periods, average cholesterol levels were 248 and 240 mg/dl. These measures were for winter and spring, respectively.



One could say that even the bigger increase from 213 to 248 is not that impressive in percentage terms, approximately 16 percent. However, HDL cholesterol does not go up significantly in response to sustained (e.g., multi-day) stress, it actually goes down, so the increases reported can be safely assumed to be chiefly due to LDL cholesterol. For most people, LDL particles are the main carriers of cholesterol in the human body. Thus, in percentage terms, the increases in LDL cholesterol are about twice those reported for total cholesterol.

A 32-percent increase (16 x 2) in LDL cholesterol would not go unnoticed today. If one’s LDL cholesterol were to be normally 140 mg/dl, it would jump to 185 mg/dl with a 32-percent increase. It looks like the standard deviations were more than 30 in the study. (This is based on the standard errors reported, and assuming that the standard deviation equals the standard error multiplied by the square root of the sample size.) So we can guess that several people might go from 140 to 215 or more (this is LDL cholesterol, in mg/dl) in response to the stress from exams.

And the effects above were observed with young medical students, in response to the stress from exams. What about a middle-aged man or woman trying to cope with chronic mental stress for months or years, due to losing his or her job, while still having to provide for a family? Or someone who has just been promoted, and finds himself or herself overwhelmed with the new responsibilities?

Keep in mind that sustained dieting can be a major stressor for some people, particular when one gets to that point in the dieting process where he or she gets regularly into negative nitrogen balance (muscle loss). So you may have heard from people saying that, after months or years of successful dieting, their cholesterol levels are inexplicably going up. Well, this post provides one of many possible explanations for that.

The finding that cholesterol goes up with stress has been replicated many times. It has been known for a long time, with studies dating back to the 1950s. Wertlake and colleagues () observed an increase in average cholesterol levels from 214 to 238 (in mg/dl); also among medical students, in response to the mental and emotional stress of an examination week. A similar study to the one above.

Those enamored with the idea of standing up the whole day, thinking that this will make them healthy, should know that performing cognitively demanding tasks while standing up is a known stressor. It is often used in research where stress must be induced to create an experimental condition. Muldoon and colleagues () found that people performing a mental task while standing experienced an increase in serum cholesterol of approximately 22 points (in mg/dl).

What we are not adapted for is sitting down for long hours in very comfortable furniture (, ). But our anatomy clearly suggests adaptations for sitting down, particularly when engaging in activities that resemble tool-making, a hallmark of the human species. Among modern hunter-gatherers, tool-making is part of daily life, and typically it is much easier to accomplish sitting down than standing up.

Modern urbanites could be seen as engaging in activities that resemble tool-making when they produce things at work for internal or external customers, whether those things are tangible or intangible.

So, stress is associated with cholesterol levels, and particularly with LDL cholesterol levels. Diehard lipid hypothesis proponents may argue that this is how stress is associated with heart disease: stress increases cholesterol which increases heart disease. Others may argue that one of the reasons why LDL cholesterol levels are sometimes found to be associated with heart disease-related conditions, such as chronic stress, and other health conditions is that the body is using LDL cholesterol to cope with those conditions.

Specifically regarding mental stress, a third argument has been put forth by Patterson and colleagues, who claimed that stress-mediated variations in blood lipid concentrations are a secondary result of decreased plasma volume. The cause, in their interpretation, was unspecified – “vascular fluid shifts”. However, when you look at the numbers reported in their study, you still see a marked increase in LDL cholesterol, even controlling for plasma volume. And this is all in response to “10 minutes of mental arithmetic with harassment” ().

I tend to think that the view that cholesterol increases with stress because cholesterol is used by the body to cope with stress is the closest to the truth. Among other things, stress increases the body’s overall protein demand, and cholesterol is used in the synthesis of many proteins. This includes proteins used for signaling, also known as hormones.

Cholesterol also seems to be a diet marker, tending to go up in high fat diets. This is easier to explain. High fat diets increase the demand for bile production, as bile is used in the digestion of fat. Most of the cholesterol produced by the human body is used to make bile.

Hands-On Workshop on PLS-SEM with WarpPLS; 12-13 August 2017; Penang, Malaysia

Structural equation modeling (SEM), or path analysis with latent variables, is one of the most general and comprehensive statistical analysis methods. Path analysis, multiple regression, ANCOVA, ANOVA and other widely used statistical analysis methods can be seen as special cases of SEM.

SEM use employing WarpPLS has been growing steadily among researchers investigating health-related topics.

We will be conducting a two-day hands-on workshop on SEM employing partial least squares methods (PLS-SEM) with WarpPLS. This software conducts composite-based (e.g., PLS-based) as well as factor-based SEM analyses. Factor-based SEM combines the precision of covariance-based SEM with the flexibility and ease-of-use of composite-based SEM. The dates are 12-13 August 2017. The workshop will take place in Penang, Malaysia.

For more details, please go to:

http://bit.ly/2tZRLKX

or

https://warppls.blogspot.com/2017/07/hands-on-workshop-on-pls-sem-with.html

Muscle loss during short-term fasting

This is an issue that often comes up in online health discussions, and was the topic of a conversation I had the other day with a friend about some of the benefits of intermittent fasting. Please note that the term "fast" is used in this post as synonymous with a period of time in which only water is consumed. If one consumes, say, a carrot during a 10 h "fast", then that is not really a fast.

Can the benefits of intermittent fasting be achieved without muscle loss? The answer is “yes”, to the best of my knowledge.

Even if you are not interested in bulking up or becoming a bodybuilder, you probably want to keep the muscle tissue you have. As a norm, it is generally easier to lose muscle than it is to gain it. Fat, on the other hand, can be gained very easily. This is today, in modern urban societies. Among our hominid ancestors, this situation was probably reversed to a certain extent.

Body fat percentage is positively correlated with measures of inflammation markers and the occurrence of various health problems. Since muscle tissue makes up lean body mass, which excludes fat, it is by definition negatively correlated with inflammation markers and health problems.

As muscle mass increases, so does health; as long as the increase in muscle mass is “natural” – i.e., it comes naturally for the individual, ideally without anything other than unprocessed food. Unnatural muscle gain may increase health temporarily, but problems eventually happen. For example, several years ago a colleague of mine gained a great deal of muscle mass by taking steroids. A few months later he had a spinal disc herniation while lifting, and never fully recovered. About a year ago he was obese, diabetic, and considering bariatric surgery.

If you are a natural lightweight, your frame may not adapt fast enough make you a natural heavyweight. And there is nothing wrong with being a natural lightweight.

In short-term fasts (e.g., up to 24 h) one can indeed lose some muscle mass as the body produces glucose using amino acids in muscle tissue through a process known as gluconeogenesis. In this sense, muscle is the body’s main reserve of glucose. Adipocytes are the body’s main reserves of fat.

Muscle loss is not pronounced in short-term fasts though. It occurs after the body’s glycogen reserves, particularly those in the liver, are significantly depleted. This often starts happening 8 to 12 hours into the fast, for people who do not fast regularly, and depending on how depleted their liver  glycogen (liver "sugar") reserves are when they start fasting. Those who fast regularly tend to have greater reserves of liver glycogen, a form of compensatory adaptation, and could go on fasting for as much as 20 h or so before their bodies need to resort to muscle catabolism to meet the brain's hunger for glucose (often about 5 g / h).

The liver is the main store of body sugar used to supply the glucose needs of the brain. This is interesting, since skeletal muscle often stores 5 times more sugar than the liver. That muscle sugar, also stored as glycogen, is pretty much "locked". It can be tapped during intense physical exertion (e.g., sprints, weight training), and pretty much nothing else can release it. The brains of our ancestors living 200 thousand years ago needed as much glucose as ours do, but their fight-or-flight needs took precedence. Our body today is like that; we are largely adapted to life in our ancestral past.

When the body is running short on glycogen, primarily liver glycogen, it becomes increasingly reliant on fat as a source of energy, sparing muscle tissue. That is, it burns fat and certain byproducts of fat metabolism, such as ketone bodies. This benign state is known as ketosis; not to be confused with ketoacidosis, which is a pathological state. There is evidence that ketosis is a more efficient state from a metabolic perspective (see, e.g., Taubes, 2007).

Often people feel an increase in energy, cognitive ability, and stress when they fast.

The brain also runs on fat (through ketone byproducts) while in ketosis, although it still needs some glucose to function properly. That is primarily where muscle tissue comes into the picture, to provide the glucose that the brain needs to function. While glucose can also be made from fat, more specifically a lipid component called glycerol, this usually happens only during very prolonged fasting and starvation.

You do not have to consume carbohydrates at all to make up for the glycogen depletion, after you break the fast. Dietary protein will do the job, as it is used in gluconeogenesis as well. However, it has to be plenty of protein, because of the loss due to conversion to glucose. This picture is complicated a bit by one interesting fact: the body tends to use protein first to meet its caloric needs, then resorting to carbohydrates and fat. Only ethanol takes precedence over protein.

Surprising? Think about this. Many animals, including humans, have a gene (frequently called the "myostatin gene") whose key function is to prevent amino acid storage in muscle beyond a certain point. Those people who have a mutation that impairs the function of this gene tend to put on muscle very easily, have low body fat percentages, and feel a lot of energy all the time. They are also hungry all the time. This genetic mutation is very rare. Children who have it look very muscular, and tend to grow to below-average height as adults.

Dietary protein also leads to an insulin response, which is comparable to that elicited by glucose. The difference is that protein also leads to other hormonal responses that have a counterbalancing effect to insulin (e.g., secretion of glucagon), by allowing for the body's use of fat as a source of energy. Insulin, by itself, promotes fat deposition and prevents fat release at the same time.

When practicing intermittent fasting, one can increase protein synthesis by doing resistance exercise (weight training, HIT), which tips the scale toward muscle growth, and away from muscle catabolism. Having said that, doing resistance exercise while fasting is usually not a good idea.

A combination of intermittent fasting and resistance exercise may actually lead to significant muscle gain in the long term. Fasting itself promotes the secretion of hormones (e.g., growth hormone) that have anabolic effects. The following sites focus on muscle gain through intermittent fasting; the bloggers are living proof that it works.

  http://bradpilon.com/

  http://leangains.com/

Muscle catabolism happens all the time, even in the absence of fasting. As with many tissues in the body (e.g., bones), muscle is continuously synthesized and degraded. Muscle tissue grows when that balance is tipped toward synthesis, and is lost otherwise.

Muscle will atrophy (i.e., be degraded) if not used, even if you are not fasting. In fact, you can eat a lot of protein and carbohydrates and still lose muscle. Just note what happens when an arm or a leg is immobilized in a cast for a long period of time.

Short-term fasting is healthy, probably because it happened frequently enough among our hominid ancestors to lead to selective pressures for metabolic and physiological solutions. Consequently, our body is designed to function well while fasting, and triggering those mechanisms correctly may promote overall health.

The relationship between fasting and health likely follows a nonlinear pattern, possibly an inverted U-curve pattern. It brings about benefits up until a point, after which some negative effects ensue.

Long-term fasting may cause severe heart problems, and eventually death, as the heart muscle is used by the body to produce glucose. Here the brain has precedence over the heart, so to speak.

Voluntary, and in some cases forced, short-term fasting was likely very common among our Stone Age ancestors; and consumption of large amounts of high glycemic index carbohydrates very uncommon (Boaz & Almquist, 2001).

References:

Boaz, N.T., & Almquist, A.J. (2001). Biological anthropology: A synthetic approach to human evolution. Upper Saddle River, NJ: Prentice Hall.

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

Amino acids in skeletal muscle: Are protein supplements as good as advertised?

When protein-rich foods, like meat, are ingested they are first broken down into peptides through digestion. As digestion continues, peptides are broken down into amino acids, which then enter circulation, becoming part of the blood plasma. They are then either incorporated into various tissues, such as skeletal muscle, or used for other purposes (e.g., oxidation and glucose generation). The table below shows the amino acid composition of blood plasma and skeletal muscle. It was taken from Brooks et al. (2005), and published originally in a classic 1974 article by Bergström and colleagues. Essential amino acids, shown at the bottom of the table, are those that have to be consumed through the diet. The human body cannot synthesize them. (Tyrosine is essential in children; in adults tryptophan is essential.)

The data is from 18 young and healthy individuals (16 males and 2 females) after an overnight fast. The gradient is a measure that contrasts the concentration of an amino acid in muscle against its concentration in blood plasma. Amino acids are transported into muscle cells by amino acid transporters, such as the vesicular glutamate transporter 1 (VGLUT1). Transporters exist because without them a substance’s gradient higher or lower than 1 would induce diffusion through cell membranes; that is, without transporters anything would enter or leave cells.

Research suggests that muscle uptake of amino acids is positively correlated with the concentration of the amino acids in plasma (as well as the level of activity of transporters) and that this effect is negatively moderated by the gradient. This is especially true after strength training, when protein synthesis is greatly enhanced. In other words, if the plasma concentration of an amino acid such as alanine is high, muscle uptake will be increased (with the proper stimulus; e.g., strength training). But if a lot of alanine is already present in muscle cells when compared to plasma (which is normally the case, since alanine’s 7.3 gradient is relatively high), more plasma alanine will be needed to increase muscle uptake.

The amino acid makeup of skeletal muscle is a product of evolutionary forces, which largely operated on our Paleolithic ancestors. Those ancestors obtained their protein primarily from meat, eggs, vegetables, fruits, and nuts. Vegetables and fruits today are generally poor sources of protein; that was probably the case in the Paleolithic as well. Also, only when very young our Paleolithic ancestors obtained their protein from human milk. It is very unlikely that they drank the milk of other animals. Still, many people today possess genetic adaptations that enable them to consume milk (and dairy products in general) effectively due to a more recent (Neolithic) ancestral heritage. A food-related trait can evolve very fast – e.g., in a few hundred years.

One implication of all of this is that protein supplements in general may not be better sources of amino acids than natural protein-rich foods, such as meat or eggs. Supplements may provide more of certain amino acids than others sources, but given the amino acid makeup of skeletal muscle, a supplemental overload of a particular amino acid is unlikely to be particularly healthy. That overload may induce an unnatural increase in amino acid oxidation, or an abnormal generation of glucose through gluconeogenesis. Depending on one’s overall diet, those may in turn lead to elevated blood glucose levels and/or a caloric surplus. The final outcome may be body fat gain.

Another implication is that man-made foods that claim to be high in protein, and that are thus advertised as muscle growth supplements, may actually be poor sources of those amino acids whose concentration in muscle are highest. (You need to check the label for the amino acid composition, and trust the manufacturer.) Moreover, if they are sources of nonessential amino acids, they may overload your body if you consume a balanced diet. Interestingly, nonessential amino acids are synthesized from carbon sources. A good source of carbon is glucose.

Among the essential amino acids are a group called branched-chain amino acids (BCAA) – leucine, isoleucine, and valine. Much is made of these amino acids, but their concentration in muscle in adults is not that high. That is, they do not contribute significantly as building blocks to protein synthesis in skeletal muscle. What makes BCAAs somewhat unique is that they are highly ketogenic, and somewhat glucogenic (via gluconeogenesis). They also lead to insulin spikes. Ingestion of BCAAs increases the blood concentration of two of the three human ketone bodies (acetone and acetoacetate). Ketosis is both protein and glycogen sparing (but gluconeogenesis is not), which is among the reasons why ketosis is significantly induced by exercise (blood ketones concentration is much more elevated after exercise than after a 20 h fast). This is probably why some exercise physiologists and personal trainers recommend consumption of BCAAs immediately prior to or during anaerobic exercise.

Why do carnivores often consume prey animals whole? (Consumption of eggs is not the same, but similar, because an egg is the starting point for the development of a whole animal.) Carnivores consume prey animals whole arguably because prey animals have those tissues (muscle, organ etc. tissues) that carnivores also have, in roughly the same amounts. Prey animals that are herbivores do all the work of converting their own prey (plants) to tissues that they share with carnivores. Carnivores benefit from that work, paying back herbivores by placing selective pressures on them that are health-promoting at the population level. (Carnivores usually target those prey animals that show signs of weakness or disease.)

Supplements would be truly natural if they provided nutrients that mimicked eating an animal whole. Most supplements do not get even close to doing that; and this includes protein supplements.

Reference

Brooks, G.A., Fahey, T.D., & Baldwin, K.M. (2005). Exercise physiology: Human bioenergetics and its applications. Boston, MA: McGraw-Hill.

Blood glucose variations in normal individuals: A chaotic mess

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Reference:

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

Tooth decay and silver diamine fluoride

Silver diamine fluoride (SDF) is a substance that can be applied on dental caries - where tooth mass has been destroyed by the action of bacteria that feed primarily on simple sugars. (Candy and sugary drinks are major culprits in this respect; fruits are not, in part because of the combination of a relatively low sugar content with the protective effect of the extra chewing needed.) Many studies have shown the effectiveness of SDF in the treatment of dental caries. The chart below is based on a study by Chu and colleagues ().

The chart above compares, in terms of normalized performance, “arrested” caries in a group of children using SDF against a control group not using SDF. Arrested caries are those in which there is no progression of the lesion; that is, in arrested caries the destruction of tooth mass is either stopped or reversed. The control group level can be seen as one in which a limited amount of arrest occurs (probably due to dietary changes and improved dental care), because the percentage of arrests among those treated with SDF was 100! And, yes, in spite of what most dentists will tell you, tooth decay can be reversed ().

As a side note, dentists do not necessarily tell their clients that tooth decay is irreversible because they want to keep the revenue flow coming into their offices. The sad reality is that most dental care patients will not be able to change their diet enough to reverse tooth decay. Because of that, it would arguably be professionally irresponsible to tell those patients that tooth decay progression can be stopped or reversed without treatment. As Weston Price has shown in his pioneering field studies (), reversing tooth decay requires not only elimination of refined sugars but also increased intake of fat-soluble vitamins (particularly vitamins A, D, and K2).

The chart below is from the same study by Chu and colleagues. It compares, also in terms of normalized performance, new caries formed over a period of time in a group of children using SDF against a control group not using SDF. As you can see from this and the previous chart, not only does SDF application stop or reverse tooth decay, it also prevents new dental caries from forming. From the empirical results it appears that this extends to teeth other than the teeth treated with SDF, presumably because of the action of the offending bacteria on the teeth that are next to those with caries.

SDF has been used in the past in various countries such as China, Japan, and New Zealand. Only recently the use of SDF has been approved in the USA. So, next time you go to the dentist to have dental caries treated, ask if they are able to use SDF and what the likely outcomes will be. Probably there will be no injections, drillings, or fillings. It seems that the only downside is that the brown spots characteristic of tooth decay tend to turn black after SDF is successfully used!

Virtual Paleo Summit video: What is your ideal weight?

You may want to check out my recent video at the (Virtual Paleo Summit) explaining the waist-to-weight ratio theory for estimation of one's ideal weight. The theory is also discussed below. It may look a little complex, but its application is very simple.

***

There is a significant amount of empirical evidence suggesting that, for a given individual and under normal circumstances, the optimal weight is the one that maximizes the ratio below, where: L = lean body mass, and T = total mass.

L / T

L is difficult and often costly to measure. T can be measured easily, as one’s total weight.

Through some simple algebraic manipulations, you can see below that the ratio above can be rewritten in terms of one’s body fat mass (F).

L / T = (T – F) / T = 1 – F / T

Therefore, in order to maximize L / T, one should maximize 1 – F / T. This essentially means that one should minimize the second term, or the ratio below, which is one’s body fat mass (F) divided by one’s weight (T).

F / T

So, you may say, all I have to do is to minimize my body fat percentage. The problem with this is that body fat percentage is very difficult to measure with precision, and, perhaps more importantly, body fat percentage is associated with lean body mass (and also weight) in a nonlinear way.

In English, it becomes increasingly difficult to retain lean body mass as one's body fat percentage goes down. Mathematically, body fat percentage (F / T) is a nonlinear function of T, where this function has the shape of a J curve.

This is what complicates matters, making the issue somewhat counterintuitive. Six-pack abs may look good, but many people would have to sacrifice too much lean body mass for their own good to get there. Genetics definitely plays a role here, as well as other factors such as age.

Keep in mind that this (i.e., F / T) is a ratio, not an absolute measure. Given this, and to facilitate measurement, we can replace F with a variable that is highly correlated with it, and that captures one or more important dimensions particularly well. This new variable would be a proxy for F. One the most widely used proxies in this type of context is waist circumference. We’ll refer to it as W.

W may well be a very good proxy, because it is a measure that is particularly sensitive to visceral body fat mass, an important dimension of body fat mass. W likely captures variations in visceral body fat mass at the levels where this type of body fat accumulation seems to cause health problems.

Therefore, the ratio that most of us would probably want to minimize is the following, where W is one’s waist circumference, and T is one’s weight.

W / T = waist / weight

Based on the experience of HCE () users, variations in this ratio are likely to be small and require 4-decimals or more to be captured. If you want to avoid having so many decimals, you can multiply the ratio by 1000. This will have no effect on the use of the ratio to find your optimal weight; it is analogous to multiplying a ratio by 100 to express it as a percentage.

Also based on the experience of HCE users, there are fluctuations that make the ratio look like it is changing direction when it is not actually doing that. Many of these fluctuations may be due to measurement error.

If you are obese, as you lose weight through dieting, the waist / weight ratio should go down, because you will be losing more body fat mass than lean body mass, in proportion to your total body mass.

It would arguably be wise to stop losing weight when the waist / weight ratio starts going up, because at that point you will be losing more lean body mass than body fat mass, in proportion to your total body mass.

One’s lowest waist / weight ratio at a given point in time should vary depending on a number of factors, including: diet, exercise, general lifestyle, and age. This lowest ratio will also be dependent on one’s height and genetic makeup.

Mathematically, this lowest ratio is the ratio at which d(W / T) / dT = 0 and d(d(W / T) / dT) / dT > 0. That is, the first derivative of W / T with respect to T equals zero, and the second derivative is greater than zero.

The lowest waist / weight ratio is unique to each individual, and can go up and down over time (e.g., resistance exercise will push it down). Here I am talking about one's lowest waist / weight ratio at a given point in time, not one's waist / weight ratio at a given point in time.

This optimal waist / weight ratio theory is one of the most compatible with evidence regarding the lowest mortality body mass index (, ). Nevertheless, it is another ratio that gets a lot of attention in the health-related literature. I am talking about the waist / hip ratio (). In this literature, waist circumference is often used alone, not as part of a ratio.