Sunday, April 19, 2015

Heavy physical activity may significantly reduce heart disease deaths, especially after age 45

The idea that heavy physical activity is a main trigger of heart attacks is widespread. Often endurance running and cardio-type activities are singled out. Some people refer to this as “death by running”. Others think that strength training has a higher lethal potential. We know based on the Oregon Sudden Unexpected Death Study that this is a myth ().

Here is some evidence that heavy physical activity in fact has a significant protective effect. The graph below shows the number of deaths from coronary heart disease, organized by age group, in longshoremen (dock workers). The shaded bars represent those whose level of activity at work was considered heavy. The unshaded bars represent those whose level of activity at work was considered moderate or light (essentially below the “heavy” level).

The data is based on an old and classic study of 6351 men, aged 35 to 74 years, who were followed either for 22 years, or to death, or to the age of 75. It shows a significant protective effect of heavy activity, especially after age 45 () . The numbers atop the unshaded bars reflect the relative risk of death from coronary heart disease in each age group. For example, in the age group 65-74, the risk among those not in the heavy activity group is 110 percent higher (2.1 times higher) than in the heavy activity group.

It should be noted that this is a cumulative effect, of years of heavy activity. Based on the description of the types of activities performed, and the calories spent, I estimate that the heavy activity group performed the equivalent of a few hours of strength training per week, plus a lot of walking and other light physical activities. The authors of the study concluded that “… repeated bursts of high energy output established a plateau of protection against coronary mortality.

Heavy physical activity may not make you lose much weight, but has the potential to make you live longer.

Monday, March 23, 2015

A viral cure for cancer only a few years away?

Adopting an evolutionarily sound lifestyle may reduce the probability that one will develop cancer, but there will be those who will nevertheless have cancer. As we live longer lives, cancer diagnoses are likely to become more and more common.

There are viruses that cause the formation and growth of cancer tumors: oncoviruses. However, and quite interestingly, there are also viruses that seek and kill cancer cells: oncolytic viruses. The video below discusses emerging treatments based on oncolytic viruses.

This Penn Medicine YouTube video is about 6 minutes in length. (A previous HBO video was about 40 minutes in length, and it was worth watching in full. However it became unavailable soon after I linked it here. Its title on YouTube was "Vice Special Report: Killing Cancer".)

Cancer treatment via oncolytic viruses had a promising start in the mid-1990s. However, due to technical complications it has been sidelined for years. Interest has been picking up dramatically in recent years. Could it be foundation for the long promised cure for cancer, as the video implies?

Only time and research will tell …

Monday, February 23, 2015

What is the probability that you are NOT diabetic if your fasting blood glucose is 110-126 mg/dl?

Often I hear from readers who have changed their diets and lifestyles toward a more evolutionarily sound direction () that their fasting blood glucose (FBG) readings have gone up. Frequently numbers in the range 110-126 mg/dl (6.1-7 mmol/l) are mentioned.

If you have a FBG reading of 110-126 mg/dl (6.1-7 mmol/l) very likely your doctor will tell you that you are either diabetic or well on your way be becoming diabetic.

Diabetes is a condition that in humans is most frequently associated with damage to the beta cells in the pancreas, significantly impairing insulin secretion. With limited insulin, glucose levels tend to go up, leading to high FBG levels and high glucose peaks after consumption of carbohydrates. The latter, high glucose peaks, appear to be particularly damaging when happening regularly over time.

What is the probability that you are NOT diabetic with this FBG reading?

I put together the table below, based on data from a widely cited meta-analysis () conducted by the research group called The Emerging Risk Factors Collaboration. It shows the distribution of FBG levels in urban settings among individuals who do not have diabetes.

The numbers in this table are fairly consistent with those from various other surveys of large numbers of individuals in urban settings.

The study mentioned above also tells us that the incidence of diabetes in urban populations is in the neighborhood of 6.8 percent. This may not sound like much, but as disease incidences goes, it is very high – approximately 1 in every randomly selected group of 15 people has diabetes.

The vast majority of those diagnosed will have diabetes mellitus type 2, which tends to develop over time and be associated with the metabolic syndrome ().

We know from Bayes' theorem, which is a fundamental element of the increasingly popular Bayesian statistics, that the probability of an event A given that an event B has occurred [denoted P(A|B)] is given by:


In the equation above, P(B|A) is the probability of event B given A, P(A) is the probability of event A, and P(B) is the probability of event B.

To answer the question posed in the title of this blog post, we need to calculate the probability that a person will have no diabetes given that he or she has a fasting blood glucose of 110-126 mg/dl.

Replacing A and B in the equation above with “NoDiabetes” (short for not having diabetes) and “FBG=110-126 mg/dl” respectively, we arrive at the formula to calculate the probability that answers the question:

P(NoDiabetes|FBG=110-126 mg/dl)=P(FBG=110-126 mg/dl|NoDiabetes)*P(NoDiabetes)/P(FBG=110-126 mg/dl).

From the table above we know that P(FBG=110-126 mg/dl|NoDiabetes)=7 percent. From our previous discussion, we know that P(NoDiabetes)=(100-6.8)/100 =93.2 percent.

Finally, the study tells us that P(FBG=110-126 mg/dl) is 9.1 percent. This includes individuals with diabetes (2.1 percent) and without diabetes (7 percent).

With these numbers, we can calculate the probability that a person will have no diabetes given that he or she has a FBG of 110-126 mg/dl:

P(NoDiabetes|FBG=110-126 mg/dl)=0.07*(1-0.068)/0.091=0.72.

That is, if your fasting blood glucose is in the 110-126 mg/dl range (6.1-7 mmol/l) then the probability that you DO NOT have diabetes is 72 percent. It would be much safer to bet that you do not have diabetes than that you do, even at that relatively high range.

Surprising eh!?

The above discussion not only highlights the lack of reliability of fasting blood glucose levels for diabetes diagnoses in the 110-126 mg/dl range (6.1-7 mmol/l), but also begs the question – what could cause high fasting blood glucose levels in healthy individuals?

Some of the folks I heard from have gone through insulin sensitivity tests (see, e.g., ), and were found to be insulin sensitive (in at least one case, highly sensitive), even though their baseline glucose levels are generally high. This goes against the possible speculation that they are prediabetics well on their way to becoming diabetic.

One possibility has been discussed in a previous post, which also mentions what could happen with HbA1c levels ().

Friday, January 30, 2015

How much protein does one need to be in nitrogen balance?

The figure below, from Brooks et al. (2005), shows a graph relating nitrogen balance and protein intake. A nitrogen balance of zero is a state in which body protein mass is stable; that is, it is neither increasing nor decreasing. It seems that the graph was taken from this classic study by Meredith et al. The participants in the study were endurance exercisers. As you can see, age is not much of a factor for nitrogen balance in this group.

Nitrogen balance is greater than zero (i.e., an anabolic state) for the vast majority of the participants at 1.2 g of protein per kg of body weight per day. To convert lbs to kg, divide by 2.2. A person weighing 100 lbs (45 kg) would need 55 g/d of protein; a person weighing 155 lbs (70 kg) would need 84 g/d; someone weighing 200 lbs (91 kg) would need 109 g/d.

The above numbers are overestimations of the amounts needed by people not doing endurance exercise, because endurance exercise tends to lead to muscle loss more than rest or moderate strength training. One way to understand this is compensatory adaptation; the body adapts to endurance exercise by shedding off muscle, as muscle is more of a hindrance than an asset for this type of exercise.

Total calorie intake has a dramatic effect on protein requirements. The above numbers assume that a person is getting just enough calories from other sources to meet daily caloric needs. If a person is in caloric deficit, protein requirements go up. If in caloric surplus, protein requirements go down. Other factors that increase protein requirements are stress and wasting diseases (e.g., cancer).

But what if you want to gain muscle?

Wilson & Wilson (2006) conducted an extensive review of the literature on protein intake and nitrogen balance. That review suggests that a protein intake beyond 25 percent of what is necessary to achieve a nitrogen balance of zero would have no effect on muscle gain. That would be 69 g/d for a person weighing 100 lbs (45 kg); 105 g/d for a person weighing 155 lbs (70 kg); and 136 g/d for someone weighing 200 lbs (91 kg). For the reasons explained above, these are also overestimations.

What if you go well beyond these numbers?

The excess protein will be used primarily as fuel; that is, it will be oxidized. In fact, a large proportion of all the protein consumed on a daily basis is used as fuel, and does not become muscle. This happens even if you are a gifted bodybuilder that can add 1 lb of protein to muscle tissue per month. So excess protein can make you gain body fat, but not by protein becoming body fat.

Dietary protein does not normally become body fat, but will typically be used in place of dietary fat as fuel. This will allow dietary fat to be stored. Dietary protein also leads to an insulin response, which causes less body fat to be released. In this sense, protein has a fat-sparing effect, preventing it from being used to supply the energy needs of the body. As long as it is available, dietary protein will be favored over dietary or body fat as a fuel source.

Having said that, if you were to overeat anything, the best choice would be protein, in the absence of any disease that would be aggravated by this. Why? Protein contributes fewer calories per gram than carbohydrates; many fewer when compared with dietary fat. Unlike carbohydrates or fat, protein almost never becomes body fat under normal circumstances. Dietary fat is very easily converted to body fat; and carbohydrates become body fat when glycogen stores are full. Finally, protein seems to be the most satiating of all macronutrients, perhaps because natural protein-rich foods are also very nutrient-dense.

It is not very easy to eat a lot of protein without getting also a lot of fat if you get your protein from natural foods; as opposed to things like refined seed/grain products or protein supplements. Exceptions are organ meats and seafood, which generally tend to be quite lean and protein-rich.


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

Wilson, J., & Wilson, G.J. (2006). Contemporary issues in protein requirements and consumption for resistance trained athletes. Journal of the International Society of Sports Nutrition, 3(1), 7-27.

Monday, December 15, 2014

You can eat a lot during the Holiday Season and gain no body fat, as long as you also eat little

The evolutionary pressures placed by periods of famine shaped the physiology of most animals, including humans, toward a design that favors asymmetric food consumption. That is, most animals are “designed” to alternate between eating little and then a lot.

Often when people hear this argument they point out the obvious. There is no evidence that our ancestors were constantly starving. This is correct, but what these folks seem to forget is that evolution responds to events that alter reproductive success rates (), even if those events are rare.

If an event causes a significant amount of death but occurs only once every year, a population will still evolve traits in response to the event. Food scarcity is one such event.

Since evolution is blind to complexity, adaptations to food scarcity can take all shapes and forms, including counterintuitive ones. Complicating this picture is the fact that food does not only provide us with fuel, but also with the sources of important structural components, signaling elements (e.g., hormones), and process catalysts (e.g., enzymes).

In other words, we may have traits that are health-promoting under conditions of food scarcity, but those traits are only likely to benefit our health as long as food scarcity is relatively short-term. Not eating anything for 40 days would be lethal for most people.

By "eating little" I don’t mean necessarily fasting. Given the amounts of mucus and dead cells (from normal cell turnover) passing through the digestive tract, it is very likely that we’ll be always digesting something. So eating very little within a period of 10 hours sends the body a message that is similar to the message sent by eating nothing within the same period of 10 hours.

Most of the empirical research that I've reviewed suggests that eating very little within a period of, say, 10-20 hours and then eating to satisfaction in one single meal will elicit the following responses. Protein phosphorylation underlies many of them.

- Your body will hold on to its most important nutrient reserves when you eat little, using selective autophagy to generate energy (, ). This may have powerful health-promoting properties, including the effect of triggering anti-cancer mechanisms.

- Food will taste fantastic when you feast, to such an extent that this effect will be much stronger than that associated with any spice ().

- Nutrients will be allocated more effectively when you feast, leading to a lower net gain of body fat ().

- The caloric value of food will be decreased, with a 14 percent decrease being commonly found in the literature ().

- The feast will prevent your body from down-regulating your metabolism via subclinical hypothyroidism (), which often happens when the period in which one eats little extends beyond a certain threshold (e.g., more than one week).

- Your mood will be very cheerful when you feast, potentially improving social relationships. That is, if you don’t become too grouchy during the period in which you eat little.

Recently I was participating in a meeting that went from early morning to late afternoon. We had the option of taking a lunch break, or working through lunch and ending the meeting earlier. Not only was I the only person to even consider the second option, some people thought that the idea of skipping lunch was outrageous, with a few implying that they would have headaches and other problems.

When I said that I had had nothing for breakfast, a few thought that I was pushing my luck. One of my colleagues warned me that I might be damaging my health irreparably by doing those things. Well, maybe they were right on both grounds, who knows?

It is my belief that the vast majority of humans will do quite fine if they eat little or nothing for a period of 20 hours. The problem is that they need to be convinced first that they have nothing to worry about. Otherwise they may end up with a headache or worse, entirely due to psychological mechanisms ().

There is no need to eat beyond satiety when you feast. I’d recommend that you just eat to satiety, and don’t force yourself to eat more than that. If you avoid industrialized foods when you feast, that will be even better, because satiety will be achieved faster. One of the main characteristics of industrialized foods is that they promote unnatural overeating; congrats food engineers on a job well done!

If you are relatively lean, satiety will normally be achieved with less food than if you are not. Hunger intensity and duration tends to be generally associated with body weight. Except for dedicated bodybuilders and a few other athletes, body weight gain is much more strongly influenced by body fat gain than by muscle gain.

Monday, November 10, 2014

Can salmon be a rich source of calcium?

Removing the bones from cooked fish, before eating the flesh, is not only a waste of mineral nutrients. In some cases it can be difficult, and lead to a lot of waste of meat.

We know that many ancestral cultures employed slow-cooking techniques and tools, such as earth ovens (a.k.a. cooking pits; see ). Slow-cooking fish over a long time tends to soften the bones to the point that they can be eaten with the flesh.

The photo below shows the leftovers of a whole salmon that we cooked recently. We baked it with vegetables on a tray covered with aluminum foil. We set the oven at 300 degrees Fahrenheit, and baked the salmon for about 5 hours.

The end result is that we can eat the salmon, a rich source of omega-3 fat, with the bones. No need to remove anything. Just take a chunk, as you can see in the photo, and eat it whole.

It is a good idea to marinate the salmon for a few hours prior to baking it. This will create enough moisture to ensure that the salmon does not dry up during the baking process.

If you are a carnivore, you can make a significant contribution to sustainability by eating the whole animal, or as much of the animal as possible. This applies to fish, as I discussed here before (, , ).

Add eating less to this habit, and your health will benefit greatly.

Monday, October 13, 2014

Will the aluminum pan and foil give you Alzheimer’s?

Aluminum (or aluminium) is a silvery metal that is both ductile and light. It is abundant in nature. These characteristics make it a favorite in many industries. Food utensils, such as pans and pots, are often made of aluminum. This use is dwarfed by aluminum’s widespread use in the canning of foods and drinks (e.g., sodas and beers).

Based on a systematic literature review published in 2008, Ferreira et al. argued that there is credible evidence of an “association” between Alzheimer’s disease and aluminum intake (). This argument has been challenged by other researchers, but has nevertheless gained media attention. Positive and negative associations will always be found where there are nonzero correlations, but correlation does not guarantee causation.

A research report commissioned by the U.S. Environmental Protection Agency, authored by Krewski et al. and published in 2007, reviewed a number of studies on the health effects of aluminum (). Several interesting findings emerged from this extensive review of the literature.

For example, a targeted study published in the late 1980s and early 1990s suggested that the daily intake of aluminum of a 14-16 year old male in the U.S. was about 11.5 mg; the main sources being additives to the following refined foods: cornbread (36.6% of total intake), American processed cheese (17.2%), pancakes (9.0%), yellow cake with icing (8%), taco/tostada (3.5%), cheeseburger (2.7%), tea (2.0%); hamburger (1.8%), and fish sticks (1.5%).

The meat that goes into the manufacturing of industrial hamburgers is not a significant source of aluminum. The same goes for the fish in the fish sticks. It is the industrial refining that makes the above-mentioned foods non-negligible sources of aluminum. One could argue that processed cheese should not be called “cheese”, as it is far removed from “real” cheese in terms of nutrient composition – particularly aged raw milk cheese.

Aluminum-treated water is widely believed to be a major source of aluminum to the body, with the potential of leading to health-detrimental accumulation. It appears that this is a myth based on several of the studies reviewed by Krewski et al.

One study concluded that humans drinking aluminum-treated water over a period of 70 to 80 years would have a total accumulation of approximately 1.5 mg of aluminum in their brain (1 mg/kg, the average adult human brain weighs 1.5 kg). At the high end of normal levels, and not much compared to the 34 mg found in some of those exposed to the Camelford water pollution incident (). And here is something else to consider. The study made two unlikely assumptions for emphasis: that all the ingested aluminum was absorbed, and that those exposed suffered from a condition that entirely prevented excretion from excess ingested aluminum.

Krewski et al.’s report and virtually all empirical studies I reviewed for this post suggest that the intake of aluminum from cooking utensils is negligible.

Is aluminum intake via food additives, arguably one of the main sources for most people living in urban environments today, likely to cause neurological diseases such as Alzheimer's disease?

My review of the evidence left me with the impression that most of the studies suggesting that aluminum intake can lead to neurological diseases make causal mistakes. One representative example is Rifat et al.’s study published in 1990 in The Lancet ().

This old study is interesting because it looked at the effects of ingestion of finely ground aluminum between 1944 and 1977 by miners, where the aluminum was ingested because it was believed to be protective against silicotic lung disease (caused by inhalation of crystalline silica dust).

As a side note, I should say that the intake levels reported in Rifat et al.’s study seem lower than what one would expect to see from a modern diet of refined foods. This seems odd. The levels may have been underestimated by Rifat et al. Or, what is more worrying, they may be quite high in a modern diet of refined foods.

Having said that, Rifat et al.’s article reports “… no significant differences between exposed and non-exposed miners in reported diagnoses of neurological disorder …” However, the tables below from their article show significant differences between exposed and non-exposed miners in their performance in cognitive tests. Those exposed to aluminum performed worst.

Two major variables that one would expect Rifat et al. to have controlled for are age and lung disease. They did control for age and a few other factors, with the corresponding results indicated as “adjusted” in the tables. However, they did not control for lung disease – the very factor that motivated aluminum intake.

Lung disease is likely to limit the supply of oxygen to the brain, and thus cause cognitive problems in the short and long term. Therefore, the cognitive impairments suggested by Rifat et al.'s study may have been caused by lung disease, and not by exposure to aluminum. This type of problem is a common feature of studies of the health effects of aluminum.

Will cooking in aluminum pans and aluminum foils give you Alzheimer’s? I doubt it.