Showing posts with label evolution. Show all posts
Showing posts with label evolution. Show all posts

We share an ancestor who probably lived no more than 640 years ago

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.

How come evolution hasn’t made us immortal? Death, like sex, helps animal populations avoid extinction

Genes do not evolve, nor do traits that are coded for our genes. We say that they evolve to facilitate discourse, which is alright. Populations evolve. A new genotype appears in a population and then either spreads or disappears. If it spreads, then the population is said to be evolving with respect to that genotype. A genotype may spread to an entire population; in population genetics, this is called “fixation”.

(Human chromosomes capped by telomeres, the white areas at the ends. Telomere shortening is caused by oxidative stress, and seems to be associated with death of cells and organisms. Source: Wikipedia.)

Asexual reproduction is very uncommon among animals. The most accepted theory to explain this is that animal populations live in environments that change very quickly, and thus need a great deal of genetic diversity within them to cope with the change. Otherwise they disappear, and so do their genes. Asexual reproduction leads to dramatically less genetic diversity in populations than sexual reproduction.

Asexual reproduction is similar to cloning. Each new individual looks a lot like its single parent. This does not work well in populations where individuals live relatively long lives. And even 1 year may be too long in this respect. It is just too much time to wait for a possible new mutation that will bring in some genetic diversity. To complicate matters, genetic mutation does not occur very often, and most genetic mutations are neutral with respect to the phenotype (i.e., they don’t code for any trait).

This is not so much of a problem for species whose members reproduce extremely fast; e.g., produce a new generation in less than 1 hour. A fast-reproducing species usually has a short lifespan as well. Accordingly, asexual reproduction is common among short-lived and fast-reproducing unicellular organisms and pathogens that have no cell structure like viruses.

Bacteria and viruses, in particular, form a part of the environment in which animals live that require animal populations to have a large amount of genetic diversity. Animal populations with low genetic diversity are unlikely to be able to cope with the barrage of diseases caused by these fast-mutating parasites.

We make sex chiefly because of the parasites.

And what about death? What does it bring to the table for a population?

Let us look at the other extreme – immortality. Immortality is very problematic in evolutionary terms because a population of immortal individuals would quickly outgrow its resources. That would happen too fast for the population to evolve enough intelligence to be able to use resources beyond those that were locally available.

In this post I assume that immortality is not the same as indestructibility. Here immortality is equated to the absence of aging as we know it. In this sense, immortals can still die by accident or due to disease. They simply do not age. For immortals, susceptibility to disease does not go up with age.

One could argue that a population of immortal individuals who did not reproduce would have done just fine. But that is not correct, because in this case immortality would be akin to cloning, but worse. Genetic diversity would not grow, as no mutations would occur. The fixed population of immortals would be unable to cope with fast-mutating parasites.

There is so much selection pressure against immortality in nature that it is no surprise that animals of very few species live more than 60 years on average. Humans are at the high end of the longevity scale. They are there for a few reasons. One is that our ancestors had offspring that required extra care, which led to an increase in the parents’ longevity. The offspring required extra care chiefly because of their large brains.

That increase in longevity was likely due to genetic mutations that helped our ancestors extend a lifespan that was programmed to be relatively short. Immortality is not a sound strategy for population survival, and thus there are probably many mechanisms through which it is prevented.

Death is evolution’s main ally. Sex is a very good helper. Both increase genetic diversity in populations.

We can use our knowledge of evolution to live better today. The aging clock can be slowed significantly via evolutionarily sound diet and lifestyle changes, essentially because some of our modern diet and lifestyle choices accelerate aging a lot. But diet and lifestyle changes probably will not make people live to 150.

If we want to become immortal, as we understand it in our current human form, ultimately we may want to beat evolution. In this sense, only very intelligent beings can become immortal.

Maybe we can achieve that by changing our genes, or by learning how to transfer our consciousness “software” into robots. In doing so, however, we may become something different; something that is not human and thus doesn’t see things in the same way as a human does. A conscious robot, without the hormones that so heavily influence human behavior, may find that being alive is pointless.

There is another problem. What if the only natural way to achieve some form of immortality is through organic death, but in a way that we don’t understand? This is not a matter of faith or religion. There are many things that we don’t know for sure. This is probably the biggest mystery of all; one that we cannot unravel in our current human state.

Maknig to mayn tipos? Myabe ur teh boz

Undoubtedly one of the big differences between life today and in our Paleolithic past is the level of stress that modern humans face on a daily basis. Much stress happens at work, which is very different from what our Paleolithic ancestors would call work. Modern office work, in particular, would probably be seen as a form of slavery by our Paleolithic ancestors.

Some recent research suggests that organizational power distance is a big factor in work-related stress. Power distance is essentially the degree to which bosses and subordinates accept wide differences in organizational power between them (Hofstede, 2001).

(Source: talentedapps.wordpress.com)

I have been studying the topic of information overload for a while. It is a fascinating topic. People who experience it have the impression that they have more information to process than they can handle. They also experience significant stress as a result of it, and both the quality of their work and their productivity goes down.

Recently some colleagues and I conducted a study that included employees from companies in New Zealand, Spain, and the USA (Kock, Del Aguila-Obra & Padilla-Meléndez, 2009). These are countries whose organizations typically display significant differences in power distance. We found something unexpected. Information overload was much more strongly associated with power distance than with the actual amount of information employees had to process on a daily basis.

While looking for explanations to this paradoxical finding, I recalled an interview I gave way back in 2001 to the Philadelphia Inquirer, commenting on research by Dr. David A. Owens. His research uncovered an interesting phenomenon. The higher up in the organizational pecking order one was, the less the person was concerned about typos on emails to subordinates.

There is also some cool research by Carlson & Davis (1998) suggesting that bosses tend to pick the communication media that are the most convenient for them, and don’t care much about convenience for the subordinates. One example would be calling a subordinate on the phone to assign a task, and then demanding a detailed follow-up report by email.

As a side note, writing a reasonably sized email takes a lot longer than conveying the same ideas over the phone or face-to-face (Kock, 2005). To be more precise, it takes about 10 times longer when the word count is over 250 and the ideas being conveyed are somewhat complex. For very short messages, a written medium like email is fairly convenient, and the amount of time to convey ideas may be even shorter than by using the phone or doing it face-to-face.

So a picture started to emerge. Bosses choose the communication media that are convenient for them when dealing with subordinates. If the media are written, they don’t care about typos at all. The subordinates use the media that are imposed on them, and if the media are written they certainly don’t want something with typos coming from them to reach their bosses. It would make them look bad.

The final result is this. Subordinates experience significant information overload, particularly in high power distance organizations. They also experience significant stress. Work quality and productivity goes down, and they get even more stressed. They get fat, or sickly thin. Their health deteriorates. Eventually they get fired, which doesn’t help a bit.

What should you do, if you are not the boss? Here are some suggestions:

- Try to tactfully avoid letting communication media being imposed on you all the time by your boss (and others). Explicitly state, in a polite way, the media that would be most convenient for you in various circusmtances, both as a receiver and sender. Generally, media that support oral speech are better for discussing complex ideas. Written media are better for short exchanges. Want an evolutionary reason for that? As you wish: Kock (2004).

- Discuss the ideas in this post with your boss; assuming that the person cares. Perhaps there is something that can be done to reduce power distance, for example. Making the work environment more democratic seems to help in some cases.

- And ... dot’n wrory soo mach aobut tipos ... which could be extrapolated to: don’t sweat the small stuff. Most bosses really care about results, and will gladly take an email with some typos telling them that a new customer signed a contract. They will not be as happy with an email telling them the opposite, no matter how well written it is.

Otherwise, your organizational demise may come sooner than you think.

References

Carlson, P.J., & Davis, G.B. (1998). An investigation of media selection among directors and managers: From "self" to "other" orientation. MIS Quarterly, 22(3), 335-362.

Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. Thousand Oaks, CA: Sage.

Kock, N. (2004). The psychobiological model: Towards a new theory of computer-mediated communication based on Darwinian evolution. Organization Science, 15(3), 327-348.

Kock, N. (2005). Business process improvement through e-collaboration: Knowledge sharing through the use of virtual groups. Hershey, PA: Idea Group Publishing.

Kock, N., Del Aguila-Obra, A.R., & Padilla-Meléndez, A. (2009). The information overload paradox: A structural equation modeling analysis of data from New Zealand, Spain and the U.S.A. Journal of Global Information Management, 17(3), 1-17.

How lean should one be?

Loss of muscle mass is associated with aging. It is also associated with the metabolic syndrome, together with excessive body fat gain. It is safe to assume that having low muscle and high fat mass, at the same time, is undesirable.

The extreme opposite of that, achievable though natural means, would be to have as much muscle as possible and as low body fat as possible. People who achieve that extreme often look a bit like “buff skeletons”.

This post assumes that increasing muscle mass through strength training and proper nutrition is healthy. It looks into body fat levels, specifically how low body fat would have to be for health to be maximized.

I am happy to acknowledge that quite often I am working on other things and then become interested in a topic that is brought up by Richard Nikoley, and discussed by his readers (I am one of them). This post is a good example of that.

Obesity and the diseases of civilization

Obesity is strongly associated with the diseases of civilization, of which the prototypical example is perhaps type 2 diabetes. So much so that sometimes the impression one gets is that without first becoming obese, one cannot develop any of the diseases of civilization.

But this is not really true. For example, diabetes type 1 is also one of the diseases of civilization, and it often strikes thin people. Diabetes type 1 results from the destruction of the beta cells in the pancreas by a person’s own immune system. The beta cells in the pancreas produce insulin, which regulates blood glucose levels.

Still, obesity is undeniably a major risk factor for the diseases of civilization. It seems reasonable to want to move away from it. But how much? How lean should one be to be as healthy as possible? Given the ubiquity of U-curve relationships among health variables, there should be a limit below which health starts deteriorating.

Is the level of body fat of the gentleman on the photo below (from: ufcbettingtoday.com) low enough? His name is Fedor; more on him below. I tend to admire people who excel in narrow fields, be they intellectual or sport-related, even if I do not do anything remotely similar in my spare time. I admire Fedor.


Let us look at some research and anecdotal evidence to see if we can answer the question above.

The buff skeleton look is often perceived as somewhat unattractive

Being in the minority is not being wrong, but should make one think. Like Richard Nikoley’s, my own perception of the physique of men and women is that, the leaner they are, the better; as long as they also have a reasonable amount of muscle. That is, in my mind, the look of a stage-ready competitive natural bodybuilder is close to the healthiest look possible.

The majority’s opinion, however, seems different, at least anecdotally. The majority of women that I hear or read voicing their opinions on this matter seem to find the “buff skeleton” look somewhat unattractive, compared with a more average fit or athletic look. The same seems to be true for perceptions of males about females.

A little side note. From an evolutionary perspective, perceptions of ancestral women about men must have been much more important than perceptions of ancestral men about women. The reason is that the ancestral women were the ones applying sexual selection pressures in our ancestral past.

For the sake of discussion, let us define the buff skeleton look as one of a reasonably muscular person with a very low body fat percentage; pretty much only essential fat. That would be 10-13 percent for women, and 5-8 percent for men.

The average fit look would be 21-24 percent for women, and 14-17 percent for men. Somewhere in between, would be what we could call the athletic look, namely 14-20 percent for women, and 6-13 percent for men. These levels are exactly the ones posted on this Wikipedia article on body fat percentages, at the time of writing.

From an evolutionary perspective, attractiveness to members of the opposite sex should be correlated with health. Unless we are talking about a costly trait used in sexual selection by our ancestors; something analogous to the male peacock’s train.

But costly traits are usually ornamental, and are often perceived as attractive even in exaggerated forms. What prevents male peacock trains from becoming the size of a mountain is that they also impair survival. Otherwise they would keep growing. The peahens find them sexy.

Being ripped is not always associated with better athletic performance

Then there is the argument that if you carried some extra fat around the waist, then you would not be able to fight, hunt etc. as effectively as you could if you were living 500,000 years ago. Evolution does not “like” that, so it is an unnatural and maladaptive state achieved by modern humans.

Well, certainly the sport of mixed martial arts (MMA) is not the best point of comparison for Paleolithic life, but it is not such a bad model either. Look at this photo of Fedor Emelianenko (on the left, clearly not so lean) next to Andrei Arlovski (fairly lean). Fedor is also the one on the photo at the beginning of this post.

Fedor weighed about 220 lbs at 6’; Arlovski 250 lbs at 6’4’’. In fact, Arlovski is one of the leanest and most muscular MMA heavyweights, and also one of the most highly ranked. Now look at Fedor in action (see this YouTube video), including what happened when Fedor fought Arlovski, at around the 4:28 mark. Fedor won by knockout.

Both Fedor and Arlovski are heavyweights; which means that they do not have to “make weight”. That is, they do not have to lose weight to abide by the regulations of their weight category. Since both are professional MMA fighters, among the very best in the world, the weight at which they compete is generally the weight that is associated with their best performance.

Fedor was practically unbeaten until recently, even though he faced a very high level of competition. Before Fedor there was another professional fighter that many thought was from Russia, and who ruled the MMA heavyweight scene for a while. His name is Igor Vovchanchyn, and he is from the Ukraine. At 5’8’’ and 230 lbs in his prime, he was a bit chubby. This YouTube video shows him in action; and it is brutal.

A BMI of about 25 seems to be the healthiest for long-term survival

Then we have this post by Stargazey, a blogger who likes science. Toward the end the post she discusses a study suggesting that a body mass index (BMI) of about 25 seems to be the healthiest for long-term survival. That BMI is between normal weight and overweight. The study suggests that both being underweight or obese is unhealthy, in terms of long-term survival.

The BMI is calculated as an individual’s body weight divided by the square of the individual’s height. A limitation of its use here is that the BMI is a more reliable proxy for body fat percentage for women than for men, and can be particularly misleading when applied to muscular men.

The traditional Okinawans are not super lean

The traditional Okinawans (here is a good YouTube video) are the longest living people in the world. Yet, they are not super lean, not even close. They are not obese either. The traditional Okinawans are those who kept to their traditional diet and lifestyle, which seems to be less and less common these days.

There are better videos on the web that could be used to illustrate this point. Some even showing shirtless traditional karate instructors and students from Okinawa, which I had seen before but could not find again. Nearly all of those karate instructors and students were a bit chubby, but not obese. By the way, karate was invented in Okinawa.

The fact that the traditional Okinawans are not ripped does not mean that the level of fat that is healthy for them is also healthy for someone with a different genetic makeup. It is important to remember that the traditional Okinawans share a common ancestry.

What does this all mean?

Some speculation below, but before that let me tell this: as counterintuitive as it may sound, excessive abdominal fat may be associated with higher insulin sensitivity in some cases. This post discusses a study in which the members of a treatment group were more insulin sensitive than the members of a control group, even though the former were much fatter; particularly in terms of abdominal fat.

It is possible that the buff skeleton look is often perceived as somewhat unattractive because of cultural reasons, and that it is associated with the healthiest state for humans. However, it seems a bit unlikely that this applies as a general rule to everybody.

Another possibility, which appears to be more reasonable, is that the buff skeleton look is healthy for some, and not for others. After all, body fat percentage, like fat distribution, seems to be strongly influenced by our genes. We can adapt in ways that go against genetic pressures, but that may be costly in some cases.

There is a great deal of genetic variation in the human species, and much of it may be due to relatively recent evolutionary pressures.

Life is not that simple!

References

Buss, D.M. (1995). The evolution of desire: Strategies of human mating. New York, NY: Basic Books.

Cartwright, J. (2000). Evolution and human behavior: Darwinian perspectives on human nature. Cambridge, MA: The MIT Press.

Miller, G.F. (2000). The mating mind: How sexual choice shaped the evolution of human nature. New York, NY: Doubleday.

Zahavi, A. & Zahavi, A. (1997). The Handicap Principle: A missing piece of Darwin’s puzzle. Oxford, England: Oxford University Press.

Human traits are distributed along bell curves: You need to know yourself, and HCE can help

Most human traits (e.g., body fat percentage, blood pressure, propensity toward depression) are influenced by our genes; some more than others. The vast majority of traits are also influenced by environmental factors, the “nurture” part of the “nature-nurture” equation. Very few traits are “innate”, such as blood type.

This means that manipulating environmental factors, such as diet and lifestyle, can strongly influence how the traits are finally expressed in humans. But each individual tends to respond differently to diet and lifestyle changes, because each individual is unique in terms of his or her combination of “nature” and “nurture”. Even identical twins are different in that respect.

When plotted, traits that are influenced by our genes are distributed along a bell-shaped curve. For example, a trait like body fat percentage, when measured in a population of 1000 individuals, will yield a distribution of values that will look like a bell-shaped distribution. This type of distribution is also known in statistics as a “normal” distribution.

Why is that?

The additive effect of genes and the bell curve

The reason is purely mathematical. A measurable trait, like body fat percentage, is usually influenced by several genes. (Sometimes individual genes have a very marked effect, as in genes that “switch on or off” other genes.) Those genes appear at random in a population, and their various combinations spread in response to selection pressures. Selection pressures usually cause a narrowing of the bell-shaped curve distributions of traits in populations.

The genes interact with environmental influences, which also have a certain degree of randomness. The result is a massive combined randomness. It is this massive randomness that leads to the bell-curve distribution. The bell curve itself is not random at all, which is a fascinating aspect of this phenomenon. From “chaos” comes “order”. A bell curve is a well-defined curve that is associated with a function, the probability density function.

The underlying mathematical reason for the bell shape is the central limit theorem. The genes are combined in different individuals as combinations of alleles, where each allele is a variation (or mutation) of a gene. An allele set, for genes in different locations of the human DNA, forms a particular allele combination, called a genotype. The alleles combine their effects, usually in an additive fashion, to influence a trait.

Here is a simple illustration. Let us say one generates 1000 random variables, each storing 10 random values going from 0 to 1. Then the values stored in each of the 1000 random variables are added. This mimics the additive effect of 10 genes with random allele combinations. The result are numbers ranging from 1 to 10, in a population of 1000 individuals; each number is analogous to an allele combination. The resulting histogram, which plots the frequency of each allele combination (or genotype) in the population, is shown on the figure bellow. Each allele configuration will “push for” a particular trait range, making the trait distribution also have the same bell-shaped form.


The bell curve, research studies, and what they mean for you

Studies of the effects of diet and exercise on health variables usually report their results in terms of average responses in a group of participants. Frequently two groups are used, one control and one treatment. For example, in a diet-related study the control group may follow the Standard American Diet, and the treatment group may follow a low carbohydrate diet.

However, you are not the average person; the average person is an abstraction. Research on bell curve distributions tells us that there is about a 68 percentage chance that you will fall within a 1 standard deviation from the average, to the left or the right of the “middle” of the bell curve. Still, even a 0.5 standard deviation above the average is not the average. And, there is approximately a 32 percent chance that you will not be within the larger -1 to 1 standard deviation range. If this is the case, the average results reported may be close to irrelevant for you.

Average results reported in studies are a good starting point for people who are similar to the studies’ participants. But you need to generate your own data, with the goal of “knowing yourself through numbers” by progressively analyzing it. This is akin to building a “numeric diary”. It is not exactly an “N=1” experiment, as some like to say, because you can generate multiple data points (e.g., N=200) on how your body alone responds to diet and lifestyle changes over time.

HealthCorrelator for Excel (HCE)

I think I have finally been able to develop a software tool that can help people do that. I have been using it myself for years, initially as a prototype. You can see the results of my transformation on this post. The challenge for me was to generate a tool that was simple enough to use, and yet powerful enough to give people good insights on what is going on with their body.

The software tool is called HealthCorrelator for Excel (HCE). It runs on Excel, and generates coefficients of association (correlations, which range from -1 to 1) among variables and graphs at the click of a button.

This 5-minute YouTube video shows how the software works in general, and this 10-minute video goes into more detail on how the software can be used to manage a specific health variable. These two videos build on a very small sample dataset, and their focus is on HDL cholesterol management. Nevertheless, the software can be used in the management of just about any health-related variable – e.g., blood glucose, triglycerides, muscle strength, muscle mass, depression episodes etc.

You have to enter data about yourself, and then the software will generate coefficients of association and graphs at the click of a button. As you can see from the videos above, it is very simple. The interpretation of the results is straightforward in most cases, and a bit more complicated in a smaller number of cases. Some results will probably surprise users, and their doctors.

For example, a user who is a patient may be able to show to a doctor that, in the user’s specific case, a diet change influences a particular variable (e.g., triglycerides) much more strongly than a prescription drug or a supplement. More posts will be coming in the future on this blog about these and other related issues.

The evolution of costly traits: Competing for women can be unhealthy for men

There are human traits that evolved in spite of being survival handicaps. These counterintuitive traits are often called costly traits, or Zahavian traits (in animal signaling contexts), in honor of the evolutionary biologist Amotz Zahavi (Zahavi & Zahavi, 1997). I have written a post about this type of traits, and also an academic article (Kock, 2009). The full references and links to these publications are at the end of this post.

The classic example of costly trait is the peacock’s train, which is used by males to signal health to females. (Figure below from: animals.howstuffworks.com.) The male peacock’s train (often incorrectly called “tail”) is a costly trait because it impairs the ability of a male to flee predators. It decreases a male’s survival success, even though it has a positive net effect on the male’s reproductive success (i.e., the number of offspring it generates). It is used in sexual selection; the females find big and brightly colored trains with many eye spots "sexy".


So costly traits exist in many species, including the human species, but we have not identified them all yet. The implication for human diet and lifestyle choices is that our ancestors might have evolved some habits that are bad for human survival, and moved away from others that are good for survival. And I am not only talking about survival among modern humans; I am talking about survival among our human ancestors too.

The simple reason for the existence of costly traits in humans is that evolution tends to maximize reproductive success, not survival, and that applies to all species. (Inclusive fitness theory goes a step further, placing the gene at the center of the selection process, but this is a topic for another post.) If that were not the case, rodent species, as well as other species that specialize in fast reproduction within relatively short life spans, would never have evolved.

Here is an interesting piece of news about research done at the University of Michigan. (I have met the lead researcher, Dan Kruger, a couple of times at HBES conferences. My impression is that his research is solid.) The research illustrates the evolution of costly traits, from a different angle. The researchers argue, based on the results of their investigation, that competing for a woman’s attention is generally bad for a man’s health!

Very romantic ...

References:

Kock, N. (2009). The evolution of costly traits through selection and the importance of oral speech in e-collaboration. Electronic Markets, 19(4), 221-232.

Zahavi, A. & Zahavi, A. (1997). The Handicap Principle: A missing piece of Darwin’s puzzle. Oxford, England: Oxford University Press.