Drs. Francisco Cervantes and Marivic Torregosa, and the 2013 Ancestral Health Symposium

Last year I traveled to South Korea to give presentations on nonlinear structural equation modeling and WarpPLS (). These are an advanced statistical analysis technique and related software tool, respectively, which have been used extensively in this blog to analyze health data, notably data related to the China Study.

I gave a couple of presentations at Korea University, which is in Seoul, and a keynote address at a conference in Gwangju, in the south part of the country. So I ended up seeing quite a lot of this beautiful country, and meeting many people. Some of my impressions regarding health and lifestyle issues need separate blog posts, which are forthcoming.

One issue that kept me thinking, as it did when I visited Japan a few years ago as well, was the obvious leanness of the South Koreans, compared with Americans, even though you don’t see a lot of emphasis on dieting there. Interestingly, this phenomenon also poses a challenge to many dietary schools of thought. For example, consumption of high-glycemic-index carbohydrates seems to be relatively high in South Korea.

The relative leanness of South Koreans is probably due to a combination of factors. A major one, it seems, is often forgotten. It is related to epigenetics. This term, “epigenetics”, is often assigned different meanings depending on the context in which it is used. Here it is used to refer to innate predispositions that don’t have a primarily genetic basis ().

Epigenetic phenomena often give the impression that acquired characteristics can be inherited, and are frequently, and misguidedly, used as examples in support of a theory often associated with Jean-Baptiste Pierre Antoine de Monet, better known as Lamarck.

A classic example of epigenetics, in this context, is that of a mother with type II diabetes giving birth to a child that will develop type II diabetes at a young age. Typically type II diabetes develops in adults, but its incidence in children has been increasing lately, particularly in certain areas. And I think that this classic example is in part related to the general leanness of South Koreans and of people in other cultures where adoption of highly industrialized foods has been relatively slow.

In other words, I think that it is possible that a major protection in South Korea, as well as in Japan and other countries, is the cultural resistance, particularly among older generations, against adopting modern diets and lifestyles that deviate from their traditional ones.

This brings me to Drs. Francisco Cervantes and Marivic Torregosa (pictured below). Dr. Cervantes is the Chief Director of Laredo Pediatrics and Neonatology, a pediatrician who studied and practiced in a variety of places, including Mexico, New Jersey, and Texas. Dr. Torregosa is a colleague of mine, a college professor and nurse practitioner in Laredo, with a Ph.D. in nursing and a research interest in child obesity.



As it turns out, Laredo, a city in Southwestern Texas near the border with Mexico, seems like the opposite of South Korea in terms of health, and this may well be related to epigenetics. This presents an enormous opportunity for research, and for helping people who really need help.

In Laredo, as well as in other areas where insulin resistance and type II diabetes are rampant, there is a great deal of variation in health. There are very healthy folks in Laredo, and very sick ones. This great deal of variation is very useful in the identification of causative factors through advanced statistical analyses. Lack of variation tends to have the opposite effect, often “hiding” causative effects.

Drs. Cervantes, Torregosa, and I had a presentation accepted for the 2013 Ancestral Health Symposium, organized by the Ancestral Health Socienty (). It is titled “Gallbladder Disease in Children: Separating Myths from Facts”. It is entirely based on data collected and analyzed by Dr. Cervantes, who is very knowledgeable about statistics. Below is the abstract.

Cholesterol’s main role in the body is to serve as raw material for bile acids; the conversion of cholesterol to bile acids by the liver accounts for approximately 70 percent of the daily disposal of cholesterol. Bile acids are then stored in the gallbladder and secreted to aid in the digestion of dietary fat. It is often believed that high cholesterol levels cause gallbladder disease. In this presentation, we will discuss various aspects of gallbladder disease, with a focus on children. The presentation will be based on data from 2116 patients of the Laredo Pediatrics & Neonatology. The patients, 1041 boys and 1075 girls, are largely first generation American-born children of Hispanic descent; a group at very high risk of developing gallbladder disease. This presentation will dispel several myths, and lay out a case for a strong association between gallbladder disease and abnormally high body fat levels. Gallbladder disease appears to be largely preventable in children through diet and lifestyle modifications, some of which will be discussed during the presentation.

Many people seem to be unaware of the fact that cholesterol production and disposal are strongly associated with secretion of bile acids. Most of the body's cholesterol is used to produce bile acids, which are reabsorbed from the gut, in a cyclical process. This is the reason behind the use of "bile acid sequestrants" to reduce cholesterol levels.

The focus on gallbladder disease in the presentation comes from an interest by Dr. Cervantes, based on his many years of clinical experience, in using gallbladder disease markers to identify and prevent other conditions, including several conditions associated with what we refer to as diseases of affluence or civilization.

Dr. Cervantes is unique among clinical practitioners in that he spends a lot of time analyzing data from his patients. His knowledge of data analyses techniques rivals that of many professional researchers I know. And he does that at his own expense, something that most clinical practitioners are unwilling to do. Dr. Cervantes and I will be co-authoring blog posts here in the future.

The 2013 PLoS ONE sugar and diabetes study: Sugar from fruits is harmless

A new study linking sugar consumption with diabetes prevalence has gained significant media attention recently. The study was published in February 2013 in the journal PLoS ONE (). The authors are Sanjay Basu, Paula Yoffe, Nancy Hills and Robert H. Lustig.

Among the claims made by the media is that “… sugar consumption — independent of obesity — is a major factor behind the recent global pandemic of type 2 diabetes” (). As it turns out, the effects revealed by the study seem to be very small, which may actually be a side effect of data aggregation; I will discuss this further below.

Fruits are exonerated

Let me start by saying that this study also included in the analysis the main natural source of sugar, fruit, as a competing variable (competing with the effects of sugar itself), and found it to be unrelated to diabetes. As the authors note: “None of the other food categories — including fiber-containing foods (pulses, nuts, vegetables, roots, tubers), fruits, meats, cereals, and oils — had a significant association with diabetes prevalence rates”.

This should not surprise anyone who has actually met and talked with Dr. Lustig, the senior author of the study and a very accessible man who has been reaching out to the public in a way that few in his position do. He is a clinician and senior researcher affiliated with a major university; public outreach, in the highly visible way that he does it, is probably something that he does primarily (if not solely) to help people. Dr. Lustig was at the 2012 Ancestral Health Symposium, and he told me, and anyone who asked him, that sugar in industrialized foods was his target, not sugar in fruits.

As I noted here before, the sugar combination of fruits, in their natural package, may in fact be health-promoting (). The natural package probably promotes enough satiety to prevent overconsumption.

Both (unnatural) sugar and obesity have effects, but they are tiny in this study

The Diabetes Report Card 2012 () provides a wealth of information that can be useful as a background for our discussion here.

In the USA, general diabetes prevalence varies depending on state, with some states having higher prevalence than others. The vast majority of diabetes cases are of type 2 diabetes, which is widely believed to be strongly associated with obesity.

In 2012, the diabetes prevalence among adults (aged 20 years or older) in Texas was 9.8 percent. This rate is relatively high compared to other states, although lower than in some. So, among a random group of 1,000 adult Texans, you would find approximately 98 with diabetes.

Prevalence increases with age. Among USA adults in general, prevalence of diabetes is 2.6 percent within ages 20–44, 11.7 percent within ages 45–64, and 18.9 percent at age 64 or older. So the numbers above for Texas, and prevalence in almost any population, are also a reflection of age distribution in the population.

According to the 2013 study published in PLoS ONE, a 1 percent increase in obesity prevalence is associated with a 0.081 percent increase in diabetes prevalence. This comes directly from the table below, fifth column on the right. That is the column for the model that includes all of the variables listed on the left.



We can translate the findings above in more meaningful terms by referring to hypothetical groups of 1,000 people. Let us say we have two groups of 1,000 people. In one of them we have 200 obese people (20 percent); and no obese person in the other. We would find only between 1 and 2 people with diabetes in the group with 200 obese people.

The authors also considered overweight prevalence as a cause of diabetes prevalence. A section of the table with the corresponding results in included below. They also found a significant effect, of smaller size than for obesity – which itself is a small effect.



The study also suggests that consumption of the sugar equivalent of a 12 oz. can of regular soft drink per person per day was associated with a 1.1 percent rise in diabetes prevalence. The effect here is about the same as that of a 1 percent increase in obesity.

That is, let us say we have two groups of 1,000 people. In one of them we have 200 people (20 percent) consuming one 12 oz. can of soft drink per day; and no one consuming sugar in the other. (Sugar from fruits is not considered here.) We would find only about 2 people with diabetes in the group with 200 sugary soda drinkers.

In other words, the effects revealed by this study are very small. They are so small that their corresponding effect sizes make them borderline irrelevant for predictions at the individual level. Based on this study, obesity and sugar consumption combined would account for no more than 5 out of each 100 cases of diabetes (a generous estimate, based on the results discussed above).

Even being weak, the effects revealed by this study are not irrelevant for policy-making, because policies tend to influence the behavior of very large numbers of people. For example, if the number of people that could be influenced by policies to curb consumption of refined sugar were 100 million, the number of cases of diabetes that could be prevented would be 200 thousand, notwithstanding the weak effects revealed by this study.

Why are the effects so small?

The effects in this study are based on data aggregated by country. When data is aggregated by population, the level of variation in the data is reduced; sometimes dramatically, a problem that is proportional to the level of aggregation (e.g., the problem is greater for country aggregation than for city aggregation).

Because there can be no association without correlation, and no correlation without variation, coefficients of association tend to be reduced when data aggregation occurs. This is, in my view, the real problem behind what statisticians often refer to, in “statospeech”, as “ecological fallacy”. The effects in aggregated data are weaker than the effects one would get without aggregation.

So, I suspect that the effects in this study, which are fairly weak at the level of aggregation used (the country level), reflect much stronger effects at the individual level of analysis.

Bottom line

Should you avoid getting obese? Should you avoid consuming industrialized products with added sugar? I think so, and I would still have recommended these without this study. There seems to be no problem with natural foods containing sugar, such as fruits.

This study shows evidence that sugar in industrialized foods is associated with diabetes, independently from obesity, but it does not provide evidence that obesity doesn’t matter. It shows that both matter, independently of one another, which is an interesting finding that backs up Dr. Lustig’s calls for policies to specifically curb refined sugar consumption.

Again, what the study refers to as sugar, as availability but implying consumption, seems to refer mostly to industrialized foods where sugar was added to make them more enticing. Fruit consumption was also included in the study, and found to have no significant effect on diabetes prevalence.

Here is a more interesting question. If a group of people have a predisposition toward developing diabetes, due to any reason (genetic, epigenetic, environmental), what would be the probability that they would develop diabetes if they became obese and/or consumed unnatural sugar-added foods?

This type of question can be answered with a moderating effects analysis, but as I noted here before (), moderating effects analyses are not conducted in health research.

The War of the End of the World: The health puzzle posed by its survivors

The War of Canudos took place in Brazil in 1896 and 1897. Canudos was a settlement of several thousand deeply religious Christians, led by a man known as Antonio Conselheiro. They opposed the recent establishment of the Republic of Brazil, particularly the institution of income taxes and civil marriage; the former was considered government-sponsored theft and the latter a sacrilege. The republic had been declared in 1889 following a military coup that deposed Dom Pedro II, an emperor beloved by the common people and under whose rule slavery had recently been abolished.

Canudos was located in the Brazilian sertão, an inhospitable semi-arid region in the northeastern part of the country. The inhabitants of Canudos were the sertanejos. The term jagunço was used to refer to the males, especially the outlaws. Many of the sertanejos lived in semi-starvation, in poor sanitary conditions, and with very limited (if any) access to healthcare. Infant mortality was very high at the time. Those who reached adulthood were typically of small stature, and very thin; not lean, thin – often described as “skin and bones”.

Below is what a typical young jagunço would look like at the time of the War of Canudos. (Some authors differentiate between jagunços and cangaceiros based on small differences in cultural and dress traditions; e.g., the hat in the photo is typical of cangaceiros.) The jagunços tended to be the best fed among the sertanejos. They were also known as cold-blooded killers. The photo is a cropped version of the original one; the grizzly original is at the top of a recent blog post by Juan Pablo Dabove (). The blog post discusses Vargas Llosa’s historical fiction book based on the War of Canudos, the masterpiece titled “The War of the End of the World” ().

Jorge Mario Pedro Vargas Llosa, a Peruvian-Spanish writer and politician, was the recipient of the 2010 Nobel Prize in Literature; “The War of the End of the World” is considered one of his greatest literary achievements. Euclides da Cunha wrote the most famous non-fictional account on the War of Canudos, another masterpiece that has been called “Brazil’s greatest book”, titled “Rebellion in the Backlands” (). The Portughese title is “Os Sertões”. Vargas Llosa’s book is based on da Cunha’s.

Sergio Rezende’s movie, “Guerra de Canudos” (), is a superb dramatization of the War of Canudos. I watched this movie after reading Vargas Llosa’s and da Cunha’s books, and was struck by two things: (a) the outstanding performances, especially by José Wilker, Cláudia Abreu, Marieta Severo, and Paulo Betti; and (b) the striking resemblance of the latter (Betti) to Royce Gracie (), a very nice man whom I interviewed () for my book on compensatory adaptation (), and who is no stranger to Ultimate Fighting Championship and mixed martial arts fans ().

In a nutshell, the War of Canudos went more or less like this. There were four military campaigns against the settlement. The third was a major one, led by one of Brazil’s most accomplished military leaders at the time, Colonel Antônio Moreira César. The jagunços, resorting to guerrilla warfare, fought off the government troops in the first three. The fourth, led by General Arthur Oscar de Andrade Guimarães, saw the jagunços defeated in a war of attrition primarily due to lack of access to food and water, after heavy losses among government troops. At the end, nearly all of the surviving jagunços were executed, by knife – to their absolute horror, and the perverse pleasure of the executioners bent on revenge, as the victims believed that they would not go to heaven if their lives were ended by knife, even against their will.

Ned, what is your point regarding health!?

After going through numerous sources, paper-based and online, academic and non-academic, I am convinced that a significant number of the survivors of the Canudos War lived to their 90s and beyond. This conclusion is based chiefly on comparisons of various dates, especially of interviews with survivors. No single source dedicated to this particular health-related aspect of the War of Canudos seems to exist. There is a video clip that shows some of the survivors (), speaking in Portuguese, with their ages shown in subtitles (“years”, in Portuguese, is “anos”). One of them, a man, is listed as being a supercentenarian.

In modern USA those who live to the age of 90 and beyond are outliers. Less than 2 percent of the population reach the age of 90 (). Most of them are women. My impression is that among the survivors of the War of Canudos, the 90+ percentage was at least 5 times higher; even with access to sanitation and healthcare in modern USA being much better at any age.

If my impression is correct, how can it be explained?

I think that some of the readers of this blog will be tempted to explain the high longevity based on calorie restriction. But the empirical evidence suggests that poor nutrition, in terms of micronutrients and macronutrients, is associated with increased mortality, not the other way around (, , ). Mortality due to poor nutrition is frequently from infectious diseases, in the young and the old. Degenerative diseases are widespread among the overnourished, not the well nourished, and kill mostly at later ages. It is not uncommon for infectious diseases to “mask” as degenerative diseases – e.g., viral diabetes ().

Often people point at hunter-gatherer populations and argue that they are healthy because of their low calorie intake. But mortality from infectious diseases among hunter-gatherers is very high, particularly in children. Others point to the absence of industrial foods engineered for overconsumption, which I think is definitely a factor in terms of degenerative diseases. Some say that a main factor is retention of lean body mass as one ages, referring mostly to muscle tissue, a hypothesis to which the case of the sertanejos poses a problem – what lean body mass!? And, on top of all of their problems, the sertanejos regularly faced long droughts, which may be why they typically had a “dry” look.

Yet others point to low stress. It is reasonable to think that stress is a mediating factor in the development of many modern diseases. Still, the sertanejos living in Canudos have had to endure quite a lot of stress, before and after the War of Canudos. In fact, the depictions of their lives at around the time of the War of Canudos suggest very stressful, miserable lives, prior to the conflict; which in part explains the early success of a religious settlement where life was marginally better.

By the way, the traditional Okinawans have also endured plenty of stress (), and they have had the highest longevity rates in recorded history. Food scarcity has frequently been combined with stress in their case, as with many other long-living groups. Causality is complex here, probably changing direction in different subsets of the data, but I have long suspected that the combination of stress and overnourishment is a particular unnatural one, to which humans are badly maladapted.

A main factor is almost always forgotten: the effective immune systems of those who have been subjected to starvation, poor sanitation, lack of healthcare, and other challenges – especially in childhood – and survived to adulthood. And here some counterintuitive things can happen. For example, someone may be very sickly early in life and barely survive childhood, and then become very resistant to infectious diseases later, thus appearing to be very healthy, to the surprise of relatives and friends who remember “that sickly child”. Immunocompetence is something that the body builds up in response to exposure.

As they say in northeastern Brazil, in characteristic drawl: “Ol’ sihtaneju ain’t die easy”.

The 2012 Atherosclerosis egg study: More smoking is associated with more plaque, unless you eat more eggs

I blogged before about the study by David Spence and colleagues, published online in July 2012 in the journal Atherosclerosis (). This study attracted a lot of media attention (e.g., ). The article is titled: “Egg yolk consumption and carotid plaque”. The study argues that “regular consumption of egg yolk should be avoided by persons at risk of cardiovascular disease”. It hints at egg yolks being unhealthy in general, possibly even more so than cigarettes.

I used the numbers in Table 2 of the article (only 5 rows of data, one per quintile; i.e., N=5) to conduct a type of analysis that is rarely if ever conducted in health studies – a moderating effects analysis. A previous blog post summarizes the results of one such analysis using WarpPLS (). It looked into the effect of the number of eggs consumed per week on the association between blood LDL cholesterol and plaque (carotid plaque). The conclusion, which is admittedly tentative due to the small sample (N=5), was that plaque decreased as LDL cholesterol increased with consumption of 2.3 eggs per week or more ().

Recently I ran an analysis on the moderating effect of number of eggs consumed per week on the association between cumulative smoking (measured in “pack years”) and plaque. As it turns out, if you fit a 3D surface to the five data points that you get for these three variables from Table 2 of the article, you end up with a relatively smooth surface. Below is a 3D plot of the 5 data points, followed by a best-fitting 3D surface (developed using an experimental algorithm).

Based on this best-fitting surface you could then generate a contour graph, shown below. The “lines” are called “isolines”. Each isoline refers to plaque values that are constant for a set of eggs per week and cumulative smoking combinations. Next to the isolines are the corresponding plaque values. The first impression is indeed that both egg consumption and smoking are causing plaque buildup, as plaque clearly increases as one moves toward the top-right corner of the graph.

But focus your attention on each individual isoline, one at a time. It is clear that plaque remains constant for increases in cumulative smoking, as long as egg consumption increases. Take for example the isoline that refers to 120 mm2 of plaque area. An increase in cumulative smoking from about 14.5 to 16 pack years leads to no increase in plaque if egg consumption goes up from about 2 to 2.3 eggs per week.

These within-isoline trends, which are fairly stable across isolines (they are all slanted to the right), clearly contradict the idea that eggs cause plaque buildup. So, why does plaque buildup seem to clearly increase with egg consumption? Here is a good reason: egg consumption is very strongly correlated with age, and plaque increases with age. The correlation is a whopping 0.916. And I am not talking about cumulative egg consumption, which the authors also measure, through a variable called “egg-yolk years”. No, I am talking about eggs per week. In this dataset, older folks were eating more eggs, period.

The correlation between plaque and age is even higher: 0.977. Given this, it makes sense to look at individual isolines. This would be analogous to what biostatisticians often call “adjusting for age”, or analyzing the effect of egg consumption on plaque buildup “keeping age constant”. A different technique is to “control for age”; this technique would be preferable had the correlations been lower (say, lower than 0.7), as collinearity levels might have been below acceptable thresholds.

The underlying logic of the “keeping age constant” technique is fairly sound in the face of such a high correlation, which would make “controlling for age” very difficult due to collinearity. When we “keep age constant”, the results point at egg consumption being protective among smokers.

But diehard fans of the idea that eggs are unhealthy could explain the results differently. Maybe egg consumption causes plaque to go up, but smoking has a protective effect. Again taking the isoline that refers to 120 mm2 of plaque area, these diehard fans could say that an increase in egg consumption from 2 to 2.3 eggs per week leads to no increase in plaque if cumulative smoking goes up from about 14.5 to 16 pack years.

Not too long ago I also blogged about a medical case study of a man who ate approximately 25 eggs (20 to 30) per day for over 15 years (probably well over), was almost 90 years old (88) when the case was published in the prestigious The New England Journal of Medicine, and was in surprisingly good health (). This man was not a smoker.

Perhaps if this man smoked 25 cigarettes per day, and ate no eggs, he would be in even better health eh!?

Does tallness cause heart disease? No, but sex does

Popular beliefs about medical issues are sometimes motivated by a statistical phenomenon known as “spurious relationship”, among other names. Two variables X and Y are influenced by a third variable C, which leads to X and Y being correlated and thus the impression that X and Y are causally associated.

Take a look at the table below, which I blogged about in a previous post (). This table shows that there is a strong unadjusted correlation between height and arterial stiffness, a marker of heart disease. The likelihood that the correlation is due to chance is lower than one tenth of a percentage point (P<.001).

Interestingly, the authors of the study even use height as a control variable to narrow down the “true” causes of arterial stiffness (column with adjusted results), assuming that height did indeed influence arterial stiffness and what they found to be a key predictor of arterial stiffness, 2-hour postprandial glucose.

But there is no convincing evidence that height causes heart disease, with exception of pathological extremes – e.g., acromegaly. Extremes tend to influence statistical results somewhat, leading to conflicting conclusions that end up being disseminated by the popular media (). This is one of the sources of popular beliefs about medical issues.

Another, more important, source are real confounders. And this takes us back to the issue of height being associated with heart disease. In fact, height will typically be significantly associated with heart disease in almost any study that includes men and women and does not control for biological sex.

One of the reasons is that women overall tend to have a significantly lower incident of heart disease than men. The other is that height is significantly lower among women than men, on average, even though there are several women who are taller than the average man.

The table above was from a study including both sexes. Therefore, the strong association between height and arterial stiffness is a “reflection” of the strong association between being male and increased arterial stiffness. If one were to add a variable coded as 0 for male and 1 for female, and use it in a multivariate analysis of predictor of arterial stiffness, together with height, the effect of height would probably “disappear”.

Biological sex is the control variable, the “confounder”, that the authors should have used to narrow down the “true” causes of arterial stiffness (second column in the table). In the absence of biological sex, controlling for height accomplished something similar, but in a “wobbly” way, leaving many readers scratching their heads in confusion.

The bipolar disorder pendulum: Depression as a compensatory adaptation

As far as explaining natural phenomena, Darwin was one of the best theoretical researchers of all time. Yet, there were a few phenomena that puzzled him for many years. One was the evolution of survival-impairing traits such as the peacock’s train, the large and brightly colored tail appendage observed in males.

Tha male peacock’s train is detrimental to the animal’s survival, and yet it is clearly an evolved trait ().

This type of trait is known as a “costly” trait – a trait that enhances biological fitness (or reproductive success, not to be confused with “gym fitness”), and yet is detrimental to the survival of the individuals who possess it (). Many costly traits have evolved in animals because of sexual selection. That is, they have evolved because they are sexy.

Costly traits seem like a contradiction in terms, but the mechanisms by which they can evolve become clear when evolution is modeled mathematically (, ). There is evidence that mental disorders may have evolved as costs of attractive mental traits (); one in particular, bipolar disorder (a.k.a. manic-depression), fits this hypothesis quite well.

Ironically, a key contributor to the mathematics used to understand costly traits, George R. Price (), might have suffered from severe bipolar disorder. Most of Price’s work in evolutionary biology was done in the 1970s; toward the end of his life, which was untimely ended by Price himself. For many years he was known mostly by evolutionary biologists, but this has changed recently with the publication of Oren Harman’s superb biographical book titled “The Price of Altruism: George Price and the Search for the Origins of Kindness” ().

Bipolar disorder is a condition characterized by disruptive mood swings. These swings are between manic and depressed states, and are analogous to the movement of a pendulum in that they alternate, seemingly gravitating around the "normal" state. See the figurative pendulum representation below, adapted from a drawing on Thinkquest.org.

Bipolar disorder is generally associated with creative intelligence, which is a very attractive trait (). Moreover, the manic state of the disorder is associated with hypersexuality and exaggerated generosity (). So one can clearly see how having bipolar disorder may lead to greater reproductive success, even as it creates long-term survival problems.

On one hand, a person may become very energetic and creative while in the manic state. This could be one of the reasons why many who suffer from bipolar disorder have fairly successful careers in fields that require creative intelligence (), which are many and not restricted to fields related to the fine and performing arts. Creative intelligence is highly valued in most knowledge-intensive professions ().

On the other hand, sustained acute mania or depression are frequently associated with serious health problems (). This is why the clinical treatment of bipolar disorder often starts with an attempt to keep the pendulum from moving too far in one direction or another. This may require medication, such as clinical doses of the elemental salt lithium, prior to cognitive behavioral therapy. The focus of cognitive behavioral therapy is on changing the way one sees and thinks about the world, particularly one’s “social world”.

Prolonged acute mania, usually accompanied by severely impaired sleep, may lead to psychosis. This, psychosis, is an extreme state characterized by hallucinations and/or delusions, leading to hospitalization in most cases. It has been theorized that depression is an involuntary compensatory adaptation () aimed at moving the pendulum in the other direction, out of the manic state, before more damage ensues ().

Elaborate approaches have been devised to treat and manage bipolar disorder treatment that involve the identification of mania and depression “prodromes” (), which are signs that a full-blown manic or depressive episode is about to start. Once prodromes are identified, cognitive behavioral therapy techniques are employed to prevent the pendulum from moving further in one direction or the other. The main goal of these techniques is to change one’s way of thinking about various issues (e.g., fears, pessimism). These techniques take years of practice to be used effectively.

Identification of prodromes and subsequent use of cognitive behavioral therapy seems to be particularly effective when dutifully applied with respect to manic episodes (). The reason for this may be related to one interesting fact related to bipolar disorder: manic episodes are not normally dreaded as much as depression episodes.

In fact, many sufferers avoid taking medication because they do not want to give up the creative and energetic bursts that come with manic episodes, even though they absolutely do not want the pendulum to go in the other direction. The problem is that, if depression is indeed a compensatory adaptation to mania, it seems reasonable to assume that extreme manic episodes are likely to be followed by extreme episodes of depression. Perhaps the key to avoid prolonged acute depression is to avoid prolonged acute mania.

As someone with bipolar disorder becomes more and more excited with novel and racing thoughts (a prodrome of mania), it would probably make sense to identify and carry out calming activities – to avoid a fall into despairing depression afterwards.

The anatomy of a VAP test report

The vertical auto profile (VAP) test is an enhanced lipid profile test. It has been proposed, as a more complete test that relies on direct measurement of previously calculated lipid measures. The VAP test is particularly known for providing direct measurements of LDL cholesterol, instead of calculating them through equations ().

At the time of this writing, a typical VAP test report would provide direct measures of the cholesterol content of LDL, Lp(a), IDL, HDL, and VLDL particles. It would also provide additional measures referred to as secondary risk factors, notably particle density patterns and apolipoprotein concentrations. Finally, it would provide a customized risk summary and some basic recommendations for treatment. Below is the top part of a typical VAP test report (from the company Atherotech), showing measures of the cholesterol content of various particles. LDL cholesterol is combined for four particle subtypes, the small-dense subtypes 4 and 3, and the large-buoyant subtypes 2 and 1. A breakdown by LDL particle subtype is provided later in the VAP report.

In the table above, HDL cholesterol is categorized in two subtypes, the small-dense subtype 2, and the large-buoyant subtype 3. Interestingly, most of the HDL cholesterol in the table is supposedly of the least protective subtype, which seems to be a common finding in the general population. VLDL cholesterol is categorized in a similar way. IDL stands for intermediate-density lipoprotein; this is essentially a VLDL particle that has given off some of its content, particularly its triglyceride (or fat) cargo, but still remains in circulation.

Lp(a) is a special subtype of the LDL particle that is purported to be associated with markedly atherogenic factors. Mainstream medicine generally considers Lp(a) particles themselves to be atherogenic, which is highly debatable. Among other things, cardiovascular disease (CVD) risk and Lp(a) concentration follow a J-curve pattern, and Lp(a)’s range of variation in humans is very large. A blog post by Peter (Hyperlipid) has a figure right at the top that illustrates the former J-curve assertion (). The latter fact, related to range of variation, generally leads to a rather wide normal distribution of Lp(a) concentrations in most populations; meaning that a large number of individuals tend to fall outside Lp(a)’s optimal range and still have a low risk of developing CVD.

Below is the middle part of a typical VAP report, showing secondary risk factors, such as particle density patterns and apolipoprotein concentrations. LDL particle pattern A is considered to be the most protective, supposedly because large-buoyant LDL particles are less likely to penetrate the endothelial gaps, which are about 25 nm in diameter. Apolipoproteins are proteins that bind to fats for their transport in lipoproteins, to be used by various tissues for energy; free fatty acids also need to bind to proteins, notably albumin, to be transported to tissues for use as energy. Redundant particles and processes are everywhere in the human body!

Below is the bottom part of a typical VAP report, providing a risk summary and some basic recommendations. One of the recommendations is “to lower” the LDL target from 130mg/dL to 100mg/dL due to the presence of the checked emerging risk factors on the right, under “Considerations”. What that usually means in practice is a recommendation to take drugs, especially statins, to reduce LDL cholesterol levels. A recent post here and the discussion under it suggest that this would be a highly questionable recommendation in the vast majority of cases ().

What do I think about VAP tests? I think that they are useful in that they provide a lot more information about one’s lipids than standard lipid profiles, and more information is better than less. On the other hand, I think that people should be very careful about what they do with that information. There are even more direct tests that I would recommend before a decision to take drugs is made (, ), if that decision is ever made at all.