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

This post has been revised and re-published. The original comments are preserved below. Typically this is done with posts that attract many visits at the time they are published, and whose topics become particularly relevant or need to be re-addressed at a later date.

Dried mussels: A little plate with 160 g of protein (plus some comments on high-protein low-carbohydrate dieting)

Many hunter-gatherer groups employed various methods of drying to preserve meats. Drying also increases significantly the protein content of meats; this is the case with dried mussels. I discussed this effect of drying before here with respect to small fish (). The photo below is of a plate with about 240 g of dried mussels that I prepared using the simple recipe below.



To prepare your mussels as in the photo above, you will have to steam and then dry them. You can season the mussels after you steam them, but I rarely season mine. Almost none of the food I eat requires much seasoning anyway, because I use nature’s super-spice, which makes everything that has a high nutrient content taste delicious: hunger ().

- Steam the mussels for about 10 minutes, or until all are open.
- Remove the mussels from the shells; carefully, to avoid small shell pieces from coming off into the mussels (they are not kind to your teeth).
- Preheat the oven to about 200 degrees Fahrenheit, and place the mussels in it (on a tray) for about 1 hour.
- Leave the mussels in the oven until they are cold, this will dry them further.

About 240 g of mussels, after drying, will yield a meal with a bit more than 160 g of protein – i.e., the proportion of protein will go from about 20 percent up to about 67 percent. In this case, most of the calories in the meal will come from the protein, if you had nothing else with it, adding up to less than 800 calories.

This comes in handy if you need to have lunch out, as the dried mussels can be carried in a plastic bag or container and eaten cold or after a light re-heating in a microwave. To me, they taste very good either way; but then again anything that is nutritious tends to taste very good when you are hungry, and I rarely have breakfast. I often eat them with pre-cooked sweet potato, which I eat with the skin (it tastes like candy).

You may want to think of dried mussels prepared in this way as a protein supplement, but a very nutritious one. You will be getting a large dose of omega-3 fats (3.11 g) with less omega-6 fats than you usually get through fish oil softgels (where n-6s are added for stability), about 1,224 percent of the recommended daily value (RDV) of magnesium, 461 percent of the RDV of selenium, 1,440 of the RDV of vitamin B12, a large dose of zinc, and (interestingly) almost 100 percent of the RDV of vitamin C.

Since mussels are very low in the food chain, accumulation of compounds that can be toxic to humans is not amplified by biomagnification (). But, still, mussels can be significantly affected by contaminants (e.g., petroleum hydrocarbons), so sourcing is important. The supermarket chain I use here in Texas, HEB, claims to do very careful sourcing. Telltale signs of contamination are developmental problems such as thin shells that shatter easily and stunted growth ().

For those readers who are on a low-carbohydrate diet, please pay attention to this: there is NO WAY your body will turn protein into fat if you are on a low-carbohydrate diet, unless you have a serious metabolic disorder (see this post: , and this podcast: ). And I mean SERIOUS; probably way beyond prediabetes. Do not believe the nonsense that has been circulating in some areas of the blogosphere lately.

A high-protein low-carbohydrate diet is one of the most effective diets at reducing body fat, particularly if you do resistance exercise (and you do not have to do it like a bodybuilder). That is not to say that a high-fat low-protein diet (like the "optimal diet") is a bad idea; in fact, the optimal diet is a good option if you do not do resistance exercise, but that is a topic for a different post.

Latitude and cancer rates in US states: Aaron Blaisdell’s intuition confirmed

In the comments section of my previous post on cancer rates in the US states () my friend Aaron Blaisdell noted that: …comparing states that are roughly comparable in terms of number of seniors per 1000 individuals, latitude appears to have the largest effect on rates of cancer.

Good point, so I collected data on the latitudes of US states, built a more complex model (with several multivariate controls), and analyzed it with WarpPLS 4.0 ().

The coefficient of association for the effect of latitude on cancer rates (path coefficient) turned out to be 0.35. Its P value was lower than 0.001, meaning that the probability that this is a false positive is less than a tenth of a percent, or that we can be 99.9 percent confident that this is not a false positive.

This was calculated controlling for the: (a) proportion of seniors in the population (population age); (b) proportion of obese individuals in the population (obesity rates); and (c) the possible moderating effect of latitude on the effect of population age on cancer rates. The graph below shows this multivariate-adjusted association.



What is cool about a multivariate analysis is that you can control for certain effects. For example, since we are controlling for proportion of seniors in the population (population age), the fact that we have a state with a very low proportion of seniors (Alaska) does not tilt the effect toward that outlier as much as it would if we had not controlled for the proportion of seniors. This is a mathematical property that is difficult to grasp, but that makes multivariate adjustment such a powerful technique.

I should note that the 99.9 percent confidence mentioned above refers to the coefficient of association. That is, we are quite confident that the coefficient of association is not zero; that is it. The P value does not support the hypothesized direction of causality (latitude -> cancer) or exclude the possibility of a major confounder causing the effect.

Nonetheless, among the newest features of WarpPLS 4.0 (still a beta version) are several causality assessment coefficients: path-correlation signs, R-squared contributions, path-correlation ratios, path-correlation differences, Warp2 bivariate causal direction ratios, Warp2 bivariate causal direction differences, Warp3 bivariate causal direction ratios, and Warp3 bivariate causal direction differences. Without going into a lot of technical detail, which you can get from the User Manual () without even having to install the software, I can tell you that all of these causality assessment coefficients support the hypothesized direction of causality.

Also, while we cannot exclude the possibility of a major confounder causing the effect, we included two possible confounders in the analysis and controlled for their effects. They were the proportion of seniors in the population (population age) and the proportion of obese individuals in the population (obesity rates).

Having said all of the above, I should also say that the effect is similar in magnitude to the effect of population age on cancer rates, which I discussed in the previous post linked above. That is, it is not the type of effect that would be clearly noticeable in a person’s normal life.

Sunlight exposure? Maybe.

We do know that our body naturally produces as much as 10,000 IU of vitamin D based on a few minutes of sun exposure when the sun is high (). Getting that much vitamin D from dietary sources is very difficult, even after “fortification”.

Aging and cancer: The importance of taking a hard look at the numbers

The table below is from a study by Hayat and colleagues (). It illustrates one common trend regarding cancer – it increases dramatically in incidence among those who are older. With some exceptions, such as Hodgkin's lymphoma, there is a significant increase in risk particularly after 50 years of age.



So I decided to get state data from the US Census web site (), on the percentage of seniors (age 65 or older) by state and cancer diagnoses per 1,000 people. I was able to get some recent data, for 2011.

I analyzed the data with WarpPLS (version 4.0 has been just released: ), generating the types of coefficients that would normally be reported by researchers who wanted to make an effect appear very strong.

In this case, the effect would be essentially of population aging on cancer incidence (assessed indirectly), summarized in the graph below. The graph was generated by WarpPLS. The scales are standardized, and so are the coefficients of association in the two segments shown. As you can see, the coefficients of association increase as we move along the horizontal scale, because this is a nonlinear relationship. The overall coefficient of association, which is a weighted average of the two betas shown, is 0.84. The probability that this is a false positive is less than 1 percent.



A beta coefficient of 0.84 essentially means that a 1 standard deviation variation in the percentage of seniors in a state is associated with an overall 84 percent increase in cancer diagnoses, taking the standardized unit of the number of cancer diagnoses as the baseline. This sounds very strong and would usually be presented as an enormous effect. Since the standard deviation for the percentage of seniors in various states is 1.67, one could say that for each 1.67 increment in the percentage of seniors in a state the number of cancer diagnoses goes up by 84 percent.

Effects expressed in percentages can sometimes give a very misleading picture. For example, let us consider an increase in mortality due to a disease from 1 to 2 cases for each 1 million people. This essentially is a 100 percent increase! Moreover, the closer the baseline is from zero, the more impressive the effect becomes, since the percentage increase is calculated by dividing the increment by the baseline number. As the baseline number approaches zero, the percentage increase from the baseline approaches infinity.

Now let us take a look at the graph below, also generated by WarpPLS. Here the scales are unstandardized, which means that they refer to the original measures in their respective original scales. (Standardization makes the variables dimensionless, which is sometimes useful when the original measurement scales are not comparable – e.g., dollars vs. meters.) As you can see here, the number of cancer diagnoses per 1,000 people goes from a low of 3.74 in Utah to a high of 6.64 in Maine.



One may be tempted to explain the increase in cancer diagnoses that we see on this graph based on various factors (e.g., lifestyle), but the percentage of seniors in a state seems like a very good and reasonable predictor. You may say: This is very depressing. You may be even more depressed if I tell you that controlling for state obesity rates does not change this picture at all.

But look at what these numbers really mean. What we see here is an increase in cancer diagnoses per 1,000 people of less than 3. In other words, there is a minute increase of less than 3 diagnoses for each group of 1,000 people considered. It certainly feels terrible if you are one of the 3 diagnosed, but it is still a minute increase.

Also note that one of the scales, for diagnoses, refers to increments of 1 in 1,000; while the other, for seniors, refers to increments of 1 in 100. This leads to an interesting effect. If you move from Alaska to Florida you will see a significant increase in the number of seniors around, as the difference in the percentage of seniors between these two states is about 10. However, the difference in the number of cancer diagnoses will not be even close to the difference in the presence of seniors.

The situation above is very common in medical research. An effect that is fundamentally tiny is stated in such a way that the general public has the impression that the effect is enormous. Often the reason is not to promote a drug, but to attract media attention to a research group or organization.

When you look at the actual numbers, the magnitude of the effect is such that it would go unnoticed in real life. By real life I mean: John, since we moved from Alaska to Maine I have been seeing a lot more people of my age being diagnosed with cancer. An effect of the order of 3 in 1,000 would not normally be noticed in real life by someone whose immediate circle of regular acquaintances included fewer than 333 people (about 1,000 divided by 3).

But thanks to Facebook, things are changing … to be fair, the traditional news media (particularly television) tends to increase perceived effects a lot more than social media, often in a very stressful way.

How to handle a dog attack

For most people, dog attacks are not very common. But they happen occasionally, and the experience can be traumatic. Incidentally, they are also a good reason why I am not a big fan of barefoot walking or running. Broken glass pieces and nails can be a problem if you are barefoot; so can dog attacks.

The photo below, from Dreamstime.com, shows a charging dog. It reminds me of an incident many years ago where a dog attacked my two oldest sons, who were very young at the time. They were unsuspectingly playing at a park in Southern New Jersey, when I saw a dog running in their direction across the park. Part of what I will say in this post is based on experiences like that.

I should also say that I grew up around dogs. My grandfather had a farm that was managed by my uncle, and dogs were critically important in managing the farm. One problem we had was that domesticated pigs would often become feral, or would mate with wild boars, in some cases leading to a particularly vicious breed of large feral pigs. I was once attacked by one of these feral pigs while hunting. One of the farm dogs came to my rescue and probably saved my life.



If you are like most people, when you go walking outdoors, you do not carry a walking stick or a cane. Maybe you should. But if you don’t, thick-soled sneakers can be used in a reasonably effective defense in a dog attack situation.

Dogs attacks’ main targets: The faces of children

Dogs tend to be loyal friends, but they must be monitored for signs of aggression, and can be particularly dangerous to children. A significant proportion of dog attack victims are children 5 years of age or younger, who more often than not sustain injuries to the face, with secondary target areas being the hands and feet ().

At the time of this writing the web sites Documentingreality.com and Arbtalk.co.uk had some grisly photos of dog attack victims (, ). They show evidence that the face is often targeted, and some possible consequences of real dog attacks.

Artificial selection: Dogs and Moby-Dick

Modern dogs are descendants of wolves who came into contact with humans about 12,000 year ago. (This general date is often cited, but is the subject of intense debate, with DNA studies suggesting much earlier contact.) Wolves are apex predators; this was true also for wolves that lived around the time they first came into contact with humans. They hunt and live in packs, and rely on fairly complex body language, a variety of sounds, and a keen sense of smell to communicate.

Even being apex predators, wolves were no match for humans. Therefore, as humans and groups of wolves co-evolved, dogs emerged. Dogs evolved instincts that made them sociable toward and submissive to humans, particularly those humans who fed them and also asserted authority over them – those become their “owners”.

Humans, in turn, came to rely heavily on dogs for protection and hunting, and probably evolved instincts that are still largely unexplored today. For example, there is strong evidence suggesting that having pet animals, many of which are dogs, is generally health-promoting (, ).

The evolution of sociability and submissiveness traits is an example of what is often referred to as “artificial selection”, where animals and plants evolve traits almost exclusively in response to the selection pressure applied by humans. In the case of dogs, this was later taken to new heights through selective breeding; leading to the emergence of a variety of dog breeds, some for utilitarian purposes and others for pure vanity, each with very distinctive characteristics.

Interestingly, artificial selection applied by humans does not always produce more sociable and submissive animals. The opposite happened around the mid 1800s due to excessive hunting of sperm whales. The least aggressive were easier to kill, so they were overhunted. Over generations, this placed selection pressure in favor of the evolution of aggressiveness toward humans. The attack on the Essex by a large bull sperm whale, which served as inspiration for Herman Melville's novel Moby-Dick, was one of the first incidents that resulted from this selection pressure (). Whaling increased, and, predictably, attacks started becoming more and more frequent.

When a dog attacks, stand your ground in a non-threatening way

Dogs, like wolves, are territorial animals. Many dog attacks are likely motivated by humans invading what a dog perceives as its territory at a given point in time. I mentioned earlier in this post that a dog once attacked two of my children. They were playing at a park during the winter. Nobody else was there. I saw this large black dog running from a distance in their direction, and I immediately knew that it was trouble. The dog probably saw us as invading its territory.

Having grown up surrounded by dogs, I pretty much knew what to do. I walked toward my children and placed myself between them and the charging dog. I told the children not to move at all, just freeze. The dog came running until it realized that we were not running. It was a “fake charge”, like most are. It stopped close to me, and barked very aggressively, coming closer. I was wearing boots. I raised one of my boots toward the dog’s snout, and when it bit it, I pushed the boot against its snout.

Here is where I think most people would tend to make a key mistake. They would probably try to hurt the dog to scare it off, by, say, kicking the dog as they would kick a soccer ball. The problem is that, because the dog is a lot faster than they are, if they do that they may end up missing the dog entirely and worse - they may end up losing their balance and falling to the ground. This is when dogs can do the most damage, since they would go for the face of the fallen person.

As a side note, often you hear that dogs attack the throat of their human victims, but that is not what the statistics show. Most victims of dog attacks display injuries on the face and extremities. The "myth" that dogs target the throat is probably based on the notion that dogs attack humans because they see them as prey. However, with exception of feral dogs such as Australian dingos, evidence of dogs preying on humans is very rare. I've reviewed many dog attack photos for this post, and could not find one with evidence that the throat was targeted.

So I pushed my boot against the dog’s snout a few times, firmly but not with the goal of hurting the dog, and did not do anything threatening toward the dog otherwise. This calmed the dog down a bit, but it was still acting aggressively and would not go away. Sometimes firm commands to "seat", "stop", "go away" make the dog react submissively. I tried them but they didn't work; instead they probably made the dog more excited. Then I did what probably is the one thing that most land animals instinctively fear from humans …

Sapiens the thrower

I picked up a few pieces of ice from the ground and threw at the dog. One piece of ice hit the dog on the side of its body; a couple of others were glancing blows. As a result the dog became visibly confused and submissive (telltale sign: tail between the legs), and ran away. Here is where another big mistake may happen. People may try to hurt the dog and become too excited when throwing objects at it. In doing so, they may end up not only missing the dog with the flying objects that they are throwing, but they may also excite the dog, and face another attack.

The best approach here is to focus on having whatever you are throwing at the dog land on top of or as close to the dog as possible; explicitly without trying to hurt it, in part because this improves your aim. Having flying objects coming from you toward the dog is enough to trigger the dog’s instinct to get out of the way of “Sapiens the thrower”. Moreover, if you don’t try to hurt you’ll be relatively calm, displaying the type body language that will trigger submissiveness.

I’ve long suspected that throwing has been a key component of Sapiens’ climb to the top of the food chain, to the point that all land animals have an instinctive fear of humans – even large predators, and much bigger animals such as elephants (as long as they are not “in musth”). One short video has been circulating on YouTube for years; it has various hunting scenes where primitive spears are used (). Many find this video cruel. It clearly shows the enormous evolutionary advantage of humans being able to throw pointy things at other animals. If humans happened to live when Tyrannosaurus rex was around, there is no doubt in my mind that the latter would be the prey.

Keep your face away and your hands closed

Typically you’ll avoid a full-blown dog attack by only standing your ground for a while and not acting aggressively toward the dog. After a short standoff period, you’ll just walk away unharmed. Unfortunately this may not happen if you are facing a dog that has been trained to attack. In this case, having a stick or something like it will help a lot. (In circus acts lions are “pushed around” by trainers holding objects like sticks and wooden chairs; sometimes that doesn't end well - .) If you don’t have one it would be useful to be wearing shoes that can withstand several bites. If not, you can use a piece of clothing, such as a bundled jacket, as a shield.

If you have a stick, or something like a stick, you should not try to hit the dog with it. You should place it near the snout, and push the stick against it each time the dog bites. If you do this calmly and firmly, without trying to hurt the dog (remember, the dog is a lot faster than you are), you will probably discourage biting after a while, turning the attack into a standoff.

What if you don’t have anything with which to defend yourself at first, and a dog attacks you? Keep your hands closed into fists, to avoid having fingers bitten off, and do your best to keep the dog away from your face. As desperate as these situations may be, try to be calm and look for objects that you can use to push the dog away, that you can throw at the dog, or that can be used to wrap around your arms. Frequently there will be objects around that can be of use – e.g., sharp stones, glass bottles, pieces of canvas, loose pieces of a fence, a hose, a tree’s branch. If you fall, try to stand up right away. Very likely you'll sustain injuries to your arms, and possibly legs.

Military and law enforcement personnel are often trained on fighting techniques to handle dog attacks barehanded, such as neck cranks, sharp blows to the throat of the animal, and blinding techniques. I am not sure whether these would be really useful to the average person. In any case, this post is not aimed at military and law enforcement personnel who deal with dog attacks on a regular basis.

Eat beef liver

Beef liver is nature’s super-multivitamin. (Beef heart is just as nutritious.) Dogs, like wolves, have an exquisite sense of smell. If you have seen one of the documentaries about the groundbreaking research by Shaun Ellis (a.k.a., “The Wolfman”), you probably know that wild wolves tend to strongly associate consumption of organ meats with very high status in a pack, to the point that they will instinctively act submissively toward humans that consume organ meats. It is quite possible that dogs do that too. So if you eat beef liver, maybe a dog will “think twice” before attacking you.

Offer the dog a cigarette and a beer

Most dogs can become aggressive from time to time, but not dogs that know how to chill. Therefore, you may consider carrying special dog cigarettes and beer around - only some brands work! Okay, a clarification: the "eat beef liver" advice is not a joke, nor are the others above it.



Notes and acknowledgements

The “charging dog” photo is from Dreamstime.com. The “drunken dog” montage was created with photos from the blog Agrestemundica.

Cesar Millan's site has a number of good suggestions on how to handle dog attacks (). However, I personally think that the way he handles dogs (e.g., often with open hands) is dangerous if copied by an inexperienced person. There is a great deal of "hidden" information that is conveyed to dogs by nuances of Cesar's body language. Those nuances are difficult to copy by an inexperienced person.

An interesting source of information on how to handle dog attacks is the web site Fightingarts.com (, ).

Waist-to-weight ratios in pictures: The John Stone transformation

John Stone is a bodybuilder and founder of a bodybuilding and fitness web site (). There he has provided pictures and stats of his remarkable transformation, which were used to prepare the montage below.



John’s height is reported as 5' 11.5". Below the photos are the months in which they were taken, the waist circumferences in inches, the weights in lbs, and the waist-to-weight ratios (WWRs). Abhi was kind enough to provide a more detailed plot of John Stone’s WWRs ().

Assuming that minimizing one’s WWR is healthy, an idea whose rationale was explained here before (), we could say that John was at his most unhealthy in the photo on the left.

The second photo from the left shows a slightly more healthy state, at a reported 8 percent body fat (his lowest). The two photos on the right represent states in which John’s WWR is at its lowest, namely 0.1544. That is, in these two photos John minimized his WWR; at a reported 14 and 13.8 percent body fat, respectively.

When we look at the WWRs in these photos, it seems that he is only marginally healthier in the second photo from the left than in the leftmost photo. In the two photos on the right, the WWRs are much lower (they are the same), suggesting that he was significantly healthier in those photos.

Interestingly, in both photos on the right John reported to have been at the end of bulking periods. Whenever he entered a cutting period his WWR started going up. This suggests that his ratio of lean body mass to total mass started decreasing just as soon as he started cutting. I suspect the same would happen if he continued gaining weight.

Which of the two photos on the right represents the best state? Assuming that both states are sustainable, over the long run I would argue that the best state is the one where the WWR was minimized with the lowest weight. There whole-day joint stress is lower. This corresponds to the photo at the far right.

By sustainable states I mean states that are not reached through approaches that are unhealthy in the long term; e.g., approaches that place organs under such an abnormal stress that they are damaged over time. This kind of damage is essentially what happens when we become obese – i.e., too fat. One can also become too muscular for his or her own good.

Could we have evolved traits that are detrimental to our survival?

Let us assume that we collected data on the presence or absence of a trait (e.g., propensity toward risky behavior) in a population of individuals, as well as on intermediate effects of the trait, downstream effects on mating and survival success, and ultimately on reproductive success (a.k.a. “fitness”, in evolutionary biology).

The data would have been collected over several generations. Let us also assume that we conducted a multivariate analysis on this data, of the same type as the analyses employing WarpPLS that were discussed here in previous posts (). The results are summarized through the graph below.



Each of the numbers next to the arrows in the graph below represents the strength of a cause-effect relationship. The number .244 linking “a” and “y” means that a one standard deviation variation in “a” causes a .244 standard deviation increase in “y”. It also means that a one standard deviation variation in “a” causes a 24.4 percent increase in “y” considering the average “y” as the baseline.

This type of mathematical view of evolution may look simplistic. This is an illusion. It is very general, and encompasses evolution in all living organisms, including humans. It also applies to theoretical organisms where multiple (e.g., 5, 6 etc.) sexes could exist. It even applies to non-biological organisms, as long as these organisms replicate - e.g., replicating robots.

So the trait measured by “a” has a positive effect on the intermediate effect “y”. This variable, “y” in turn has a negative effect on survival success (“s”), and a strong one at that: -.518. Examples: “a” = propensity toward risky behavior, measured as 0 (low) and 1 (high); and “y” = hunting success, measured in the same way. (That is, “a” and “y” are correlated, but “a”=1 does not always mean “y”=1.) Here the trait “a” has a negative effect on survival via its intermediate effect on “y”. If I calculate the total effect of “a” on “w” via the 9 paths that connect these two variables, I will find that it is .161.

The total effect on reproductive success is positive, which means that the trait will tend to spread in the population. In other words, the trait will evolve in the population, even though it has a negative effect on survival. This type of trait is what has been referred to as a “costly” trait ().

Say what? Do you mean to say that we have evolved traits that are unhealthy for us? Yes, I mean exactly that. Is this a “death to paleo” post? No, it is not. I discussed this topic here before, several years ago (). But the existence of costly traits is one of the main reasons why I don’t think that mimicking our evolutionary past is necessarily healthy. For example, many of our male ancestors were warriors, and they died early because of that.

What type of trait will present this evolutionary pattern – i.e., be a costly trait? One answer is: a trait that is found to be attractive by members of the other sex, and that is not very healthy. For example, a behavior that is perceived as “sexy”, but that is also associated with increased mortality. This would likely be a behavior prominently displayed by males, since in most species, including humans, sexual selection pressure is much more strongly applied by females than by males.

Examples would be aggressiveness and propensity toward risky behavior, especially in high-stress situations such as hunting and intergroup conflict (e.g., a war between two tribes) where being aggressive is likely to benefit an individual’s group. In warrior societies, both aggressiveness and propensity toward risky behavior are associated with higher social status and a greater ability to procure mates. These traits are usually seen as male traits in these societies.

Here is something interesting. Judging from our knowledge of various warrior societies, including American plains Indians societies, the main currency of warrior societies were counts of risky acts, not battle effectiveness. Slapping a fierce enemy warrior on the face and living to tell the story would be more valuable, in terms of “counting coup”, than killing a few inexperienced enemy warriors in an ambush.

Greater propensity toward risky behavior among men is widespread and well documented, and is very likely the result of evolutionary forces, operating on costly traits. Genetic traits evolved primarily by pressure on one sex are often present in the other (e.g., men have nipples). There are different grades of risky behavior today. At the high end of the scale would be things that can kill suddenly like race car driving and free solo climbing (, ). (If you'd like to know the source of the awesome background song of the second video linked, here it is: Radical Face's "Welcome Home".)

One interesting link between risky behavior and diet refers to the consumption of omega-6 and omega-3 fats. Risky behavior may be connected with aggressive behavior, which may in turn be encouraged by greater consumption of foods rich in omega-6 fats and avoidance of foods rich in omega-3 fats (, ). This may be behind our apparent preference for foods rich in omega-6 fats, even though tipping the balance toward more foods rich in omega-3 fats would be beneficial for survival. We would be "calmer" though - not a high priority among most men, particularly young men.

This evolved preference may also be behind the appeal of industrial foods that are very rich in omega-6 fats. These foods seem to be particularly bad for us in the long term. But when the sources of omega-6 fats are unprocessed foods, the negative effects seem to become "invisible" to statistical tests.