Monday, February 27, 2017

Want to make coffee less acidic? Add cream to it

The table below is from a 2008 article by Ehlen and colleagues (), showing the amount of erosion caused by various types of beverages, when teeth were exposed to them for 25 h in vitro. Erosion depth is measured in microns. The third row shows the chance probabilities (i.e., P values) associated with the differences in erosion of enamel and root.


As you can see, even diet drinks may cause tooth erosion. That is not to say that if you drink a diet soda occasionally you will destroy your teeth, but regular drinking may be a problem. I discussed this study in a previous post (). After that post was published here some folks asked me about coffee, so I decided to do some research.

Unfortunately coffee by itself can also cause some erosion, primarily because of its acidity. Generally speaking, you want a liquid substance that you are interested in drinking to have a pH as close to 7 as possible, as this pH is neutral (). Tap and mineral water have a pH that is very close to 7. Black coffee seems to have a pH of about 4.8.

Also problematic are drinks containing fermentable carbohydrates, such as sucrose, fructose, glucose, and lactose. These are fermented by acid-producing bacteria. Interestingly, when fermentable carbohydrates are consumed as part of foods that require chewing, such as fruits, acidity is either neutralized or significantly reduced by large amounts of saliva being secreted as a result of the chewing process.

So what to do about coffee?

One possible solution is to add heavy cream to it. A small amount, such as a teaspoon, appears to bring the pH in a cup of coffee to a little over 6. Another advantage of heavy cream is that it has no fermentable carbohydrates; it has no carbohydrates, period. You will have to get over the habit of drinking sweet beverages, including sweet coffee, if you were unfortunate enough to develop that habit (like so many people living in cities today).

It is not easy to find reliable pH values for various foods. I guess dentistry researchers are more interested in ways of repairing damage already done, and there doesn't seem to be much funding available for preventive dentistry research. Some pH testing results from a University of Cincinnati college biology page were available at the time of this writing; they appeared to be reasonably reliable the last time I checked them ().

Monday, January 30, 2017

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.

Wednesday, December 28, 2016

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!

Thursday, October 20, 2016

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.

Friday, September 30, 2016

PLS Applications Symposium; 5 - 7 April 2017; Laredo, Texas


PLS Applications Symposium; 5 - 7 April 2017; Laredo, Texas
(Abstract submissions accepted until 10 February 2017)

*** Health researchers ***

The research techniques discussed in this Symposium are finding growing use among health researchers. This is in part due to steady growth in the use of the software WarpPLS (visit: http://warppls.com) among those researchers. For those interested in learning more, a full-day workshop will be conducted (see below).

*** Only abstracts are needed for the submissions ***

The partial least squares (PLS) method has increasingly been used in a variety of fields of research and practice, particularly in the context of PLS-based structural equation modeling (SEM). The focus of this Symposium is on the application of PLS-based methods, from a multidisciplinary perspective. For types of submissions, deadlines, and other details, please visit the Symposium’s web site:

http://plsas.net

*** Workshop on PLS-SEM ***

On 5 April 2017 a full-day workshop on PLS-SEM will be conducted by Dr. Ned Kock, using the software WarpPLS. Dr. Kock is the original developer of this software, which is one of the leading PLS-SEM tools today; used by thousands of researchers from a wide variety of disciplines, and from many different countries. This workshop will be hands-on and interactive, and will have two parts: (a) basic PLS-SEM issues, conducted in the morning (9 am - 12 noon); and (b) intermediate and advanced PLS-SEM issues, conducted in the afternoon (2 pm - 5 pm). Participants may attend either one, or both of the two parts.

The following topics, among others, will be covered - Running a Full PLS-SEM Analysis - Conducting a Moderating Effects Analysis - Viewing Moderating Effects via 3D and 2D Graphs - Creating and Using Second Order Latent Variables - Viewing Indirect and Total Effects - Viewing Skewness and Kurtosis of Manifest and Latent Variables - Conducting a Multi-group Analysis with Range Restriction - Viewing Nonlinear Relationships - Conducting a Factor-Based PLS-SEM Analysis - Viewing and Changing Missing Data Imputation Settings - Isolating Mediating Effects - Identifying and Dealing with Outliers - Solving Indicator Problems - Solving Collinearity Problems.

-----------------------------------------------------------
Ned Kock
Symposium Chair
http://plsas.net


Sunday, September 25, 2016

Niacin turbocharges the growth hormone response to anaerobic exercise: A delayed effect

Niacin is also known as vitamin B3, or nicotinic acid. It is an essential vitamin whose deficiency leads to pellagra. In large doses of 1 to 3 g per day it has several effects on blood lipids, including an increase in HDL cholesterol and a marked decreased in fasting triglycerides. Niacin is also a powerful antioxidant.

Among niacin’s other effects, when taken in large doses of 1 to 3 g per day, is an acute elevation in growth hormone secretion. This is a delayed effect, frequently occurring 3 to 5 hours after taking niacin. This effect is independent of exercise.

It is important to note that large doses of 1 to 3 g of niacin are completely unnatural, and cannot be achieved by eating foods rich in niacin. For example, one would have to eat a toxic amount of beef liver (e.g., 15 lbs) to get even close to 1 g of niacin. Beef liver is one of the richest natural sources of niacin.

Unless we find out something completely unexpected about the diet of our Paleolithic ancestors in the future, we can safely assume that they never benefited from the niacin effects discussed in this post.

With that caveat, let us look at yet another study on niacin and its effect on growth hormone. Stokes and colleagues (2008) conducted a study suggesting that, in addition to the above mentioned beneficial effects of niacin, there is another exercise-induced effect: niacin “turbocharges” the growth hormone response to anaerobic exercise. The full reference to the study is at the end of this post. Figure 3, shown below, illustrates the effect and its magnitude. Click on it to enlarge.


The closed diamond symbols represent the treatment group. In it, participants ingested a total of 2 g of niacin in three doses: 1 g ingested at 0 min, 0.5 g at 120 min, and 0.5 g at 240 min. The control group ingested no niacin, and is represented by the open square symbols. (The researchers did not use a placebo in the control group; they justified this decision by noting that the niacin flush nullified the benefits of using a placebo.) The arrows indicate points at which all-out 30-second cycle ergometer sprints occurred.

Ignore the lines showing the serum growth hormone levels in between 120 and 300 min; they were not measured within that period.

As you can see, the peak growth hormone response to the first sprint was almost two times higher in the niacin group. In the second sprint, at 300 min, the rise in growth hormone is about 5 times higher in the niacin group.

We know that growth hormone secretion may rise 300 percent with exercise, without niacin. According to this study, this effect may be “turbocharged” up to a 600 percent rise with niacin within 300 min (5 h) of taking it, and possibly 1,500 percent soon after 300 min passed since taking niacin.

That is, not only does niacin boost growth hormone secretion anytime after it is taken, but one still gets the major niacin increase in growth hormone at around 300 min of taking it (which is about the same, whether you exercise or not). Its secretion level at this point is, by the way, higher than its highest level typically reached during deep sleep.

Let me emphasize that the peak growth hormone level achieved in the second sprint is about the same you would get without exercise, namely a bit more than 20 micrograms per liter, as long as you took niacin (see Quabbe's articles at the end of this post).

Still, if you time your exercise session to about 300 min after taking niacin you may have some extra benefits, because getting that peak growth hormone secretion at the time you are exercising may help boost some of the benefits of exercise.

For example, the excess growth hormone secretion may reduce muscle catabolism and increase muscle anabolism, at the same time, leading to an increase in muscle gain. However, there is evidence that growth hormone-induced muscle gain occurs only when testosterone levels are elevated. This explains why growth hormone levels are usually higher in young women than young men, and yet young women do not put on much muscle in response to exercise.

Reference:

Stokes, K.A., Tyler, C., & Gilbert, K.L. (2008). The growth hormone response to repeated bouts of sprint exercise with and without suppression of lipolysis in men. Journal of Applied Physiology, 104(3), 724-728.

Friday, August 26, 2016

Growth hormone may rise 300 percent with exercise: Acute increases also occur in cortisol, adrenaline, and noradrenaline

The figure below (click to enlarge) is from the outstanding book Physiology of sport and exercise, by Jack H. Wilmore, David L. Costill, and W. Larry Kenney. If you are serious about endurance or resistance exercise, or want to have a deeper understanding of exercise physiology beyond what one can get in popular exercise books, this book should be in your personal and/or institutional library. It is one of the most comprehensive textbooks on exercise physiology around. The full reference to the book is at the end of this post.


The hormonal and free fatty acid responses shown on the two graphs are to relatively intense exercise combining aerobic and anaerobic components. Something like competitive cross-country running in an area with hills would lead to that type of response. As you can see, cortisol spikes at the beginning, combining forces with adrenaline and noradrenaline (a.k.a. epinephrine and norepinephrine) to quickly increase circulating free fatty acid levels. Then free fatty acid levels are maintained elevated by adrenaline, noradrenaline, and growth hormone. As you can see from the graphs, free fatty acid levels are initially pulled up by cortisol, and then are very strongly correlated with adrenaline and noradrenaline.  Those free fatty acids feed muscle, and also lead to the production of ketones, which provide extra fuel for muscle tissue.

Growth hormone stays flat for about 40 minutes, after which it goes up steeply. At around the 90-minute mark, it reaches a level that is quite high; 300 percent higher than it was prior to the exercise session. Natural elevation of circulating growth hormone through intense exercise, intermittent fasting, and restful sleep, leads to a number of health benefits. It helps burn abdominal fat, often hours after the exercise session, and helps build muscle (in conjunction with other hormones, such as testosterone). It appears to increase insulin sensitivity in the long run.

Aerobic activities normally do not elevate growth hormone levels, even though they are healthy, unless they lead to a significant degree of glycogen depletion. Glycogen is stored in the liver and muscle, with muscle storing about 5 times more than the liver (about 500 g in adults). Once those reserves go down significantly during exercise, it seems that growth hormone is recruited to ramp up fat catabolism and facilitate other metabolic processes. Walking for an hour, even if briskly, is good for fat burning, but generates only a small growth hormone elevation. Including a few all-out sprints into that walk can help significantly increase growth hormone secretion.

Having said that, it is not really clear whether growth hormone elevation is a response to glycogen depletion, or whether both happen together in response to another stimulus or related metabolic process. There are other factors that come into play as well. For example, circulating growth hormone increase is moderated by sex hormone (e.g., testosterone, estrogen) secretion, thus larger growth hormone increases in response to exercise are observed in older men than in older women. (Testosterone declines more slowly with age in men than estrogen does in women.) Also, growth hormone increase seems to be correlated with an increase in circulating ketones.

Heavy resistance exercise seems to lead to a higher growth hormone elevation per unit of time than endurance exercise. That is, an intense resistance training session lasting only 30 minutes can lead to an acute circulating growth hormone response, similar to that shown on the figure. The key seems to be reaching the point during the exercise where muscle glycogen stores are significantly depleted. Many people who weight-train achieve this regularly by combining a reasonable number of sets (e.g., 6-12), with repetitions in the muscle hypertrophy range (again, 6-12); and progressive overload, whereby resistance is increased incrementally every session.

Progressive overload is needed because glycogen reserves are themselves increased in response to training, so one has to increase resistance every session to keep up with those increases. This goes on only up to a point, a point of saturation, usually reached by elite athletes. Glycogen is the primary fuel for anaerobic exercise; fat is used as fuel in the recovery period between sets, and after the exercise is over. Glycogen is expended proportionally to the number of calories used in the anaerobic effort. Calories are expended proportionally to the total amount of weight moved around, and are also a function of the movements performed (moving a certain weight 1 feet spends less energy than moving it 3 feet). By the way, not much glycogen is depleted in a 30-minute session. The total caloric expenditure will probably be around 250 calories above the basal metabolic rate, which will require about 63 g of glycogen.

Many sensations are associated with reaching the glycogen depletion level required for an acute growth hormone response during heavy anaerobic exercise. Often light to severe nausea is experienced. Many people report a “funny” feeling, which is unmistakable to them, but very difficult to describe. In some people the “funny” feeling is followed, after even more exertion, by a progressively strong sensation of “pins and needles”, which, unlike that associated with a heart attack, comes slowly and also goes away slowly with rest. Some people feel lightheaded as well.

It seems that the optimal point is reached immediately before the above sensations become bothersome; perhaps at the onset of the “funny” feeling. My personal impression is that the level at which one experiences the “pins and needles” sensation should be avoided, because that is a point where your body is about to “force” you to stop exercising. (Note: I am not a bodybuilder; see “Interesting links” for more extensive resources on the subject.) Besides, go to that point or beyond and significant muscle catabolism may occur, because the body prioritizes glycogen reserves over muscle protein. It will break that protein down to produce glucose via gluconeogenesis to feed muscle glycogenesis.

That the body prioritizes muscle glycogen reserves over muscle protein is surprising to many, but makes evolutionary sense. In our evolutionary past, there were no selection pressures on humans to win bodybuilding tournaments. For our hominid ancestors, it was more important to have the glycogen tank at least half-full than to have some extra muscle protein. Without glycogen, the violent muscle contractions needed for a “fight or flight” response to an animal attack simply cannot happen. And large predators (e.g., a bear) would not feel intimated by big human muscles alone; it would be the human’s response using those muscles that would result in survival or death.

Overall, selection pressures probably favored functional strength combined with endurance, leading to body types similar to those of the hunter-gatherers shown on this post.

Even though the growth hormone response to exercise can be steep, the highest natural growth hormone spike seems to be the one that occurs at night, during deep sleep.

Exercising hard pays off, but only if one sleeps well.