This call is closed. Beta testing has been successfully completed. HealthCorrelator for Excel (HCE) is now publicly available for download and use on a free trial basis. For those users who decide to buy it after trying, licenses are available for individuals and organizations.
To download a free trial version – as well as get the User Manual, view demo YouTube videos, and download and try sample datasets – visit the HealthCorrelator.com web site.
Sunday, November 28, 2010
Tuesday, November 23, 2010
Text Messages and Public Health: Can They Remove Barriers for "Calling" 9-1-1?
Text messages are a great time saver. You do not have to have a long conversation with someone...instead you can just send a quick message like "I made it home safe!" or "Can you pick up milk on your way home?" These text messages work well to support our busy lives, but can they also be incorporated into effective public health interventions and systems?This week, the Federal Communications Commission (FCC) announced that it is looking into letting citizens report crimes via text message. An article posted by Wired discusses the possibility and highlights some of the "barriers" that this new strategy could help to address. First and foremost, it could allow citizens to report a crime without being overheard if they were in dangerous situations (e.g., kidnapping, robbery). The FCC specifically pointed to the 2007 shootings at VirginiaTech and reported that texts could have allowed emergency personnel to respond more quickly and with a better understanding of the circumstances inside the campus buildings.
While at first glance, it may seem surprising to use text messaging for 9-1-1 reporting (due to potential logistical considerations and challenges), it would not be the first time that texts were being integrated into public health interventions and emergency response systems. For example:
- Text messages are used to disseminate key health messages to various priority populations. E.g., The Text4Baby campaign allows mothers to self select into their program by texting "Baby" to the program number. The mothers then receive weekly text messages (timed to their due date or baby's birth day) regarding key health issues for their babies (e.g., nutrition, immunizations, etc).
- Many workplaces and college campuses have signed up for emergency response systems that will send out automatic alerts to email and phones (via text message) during a crisis (e.g., shooter on site).
In addition to the great potential with this strategy, there are also several barriers that must be addressed in the planning:
- Costs (equipment, training, staffing)
- Regulation and Oversight: Will text message support be required or voluntary at emergency centers? Who will conduct a formative and ongoing evaluation of the system?
- Interpretation of messages: Operators will need special training to (quickly) interpret and respond to text messages. Texts are often written in short hand, so you would need someone very skilled to decipher them accurately. It may also be time consuming to support the texting back and forth that may be required to receive all relevant information from the "caller" in order to dispatch an appropriate response.
Monday, November 22, 2010
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.
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.
Monday, November 15, 2010
No Matter How Graphic The Images, Fear Based Messages Will Continue To Be Ineffective For Prevention
All over the news in the past week, we have seen samples of the new graphic images being proposed for addition to cigarette packages. They include corpses and people dying of cancer. However, just because these images and warnings are larger and more graphic, does not mean that they will be effective in smoking prevention. A story ran today on Boston.com called "Will graphic cigarette warnings help- or hurt?" Two experts in tobacco prevention are quoted regarding their concerns about the new images. Gregory Connelly of the Harvard School of Public Health points to the results coming from Canada after using similar images. Smokers there simply purchased sleeves to cover up the images on their cigarette packs. Also, the smoking rate did not go down. The second expert is a wonderful professor of mine from the Boston University School of Public Health, Dr. Michael Siegel. Dr. Siegel writes regularly regarding this topic on his blog, "The Rest of the Story: Tobacco Analysis and Commentary". In the Boston.com article, he states "I do not actually think it's going to have much of an impact". His argument- the images are too late. The smokers are seeing the images after they have already purchased cigarettes. And (drum roll please....) people already know smoking is bad for them.
As someone who grew up during the "This is your brain. This is your brain on drugs. Any questions?" era...I wonder why we have not made much progress since then? Numerous studies have shown that scare tactics (or fear appeals) are not effective for preventing or producing sustained reductions of Alcohol, Tobacco, or other Drug use among youth. In addition to the issues outlined above, there is another problem with the fear based approach:
Although the fear based messages may increase knowledge (e.g., if they did not know it already, smokers will learn that cigarettes are bad for them from the graphic images)- knowledge does not equal behavior change. Especially when you are dealing with an addictive behavior. Addictive behaviors like smoking and drug use are impacted by much more than a rational weighing of pros and cons. There is the biological component of addiction, local-state-national prevention policies, social norms around the behavior, consequences experienced (or not experienced), ease of access to the substance, social support for quiting, money to support the addiction, etc. As you can see, knowledge alone will not change this kind of complex behavior.
Many of the most successful prevention strategies around this and other public health issues will continue to be a refocus from increasing individual knowledge to changing an environment that supports the behavior. In other words, laws that create smoke-free workplaces and crack down on establishments that sell cigarettes to underage kids will always be more effective at keeping the population healthy versus trying to educate (or scare) one individual at a time.
Your mind as an anabolic steroid
The figure below, taken from Wilmore et al. (2007), is based on a classic 1972 study conducted by Ariel and Saville. The study demonstrated the existence of what is referred to in exercise physiology as the “placebo effect on muscular strength gains”. The study had two stages. In the first stage, fifteen male university athletes completed a 7-week strength training program. Gains in strength occurred during this period, but were generally small as these were trained athletes.
In the second stage the same participants completed a 4-week strength training program, very much like the previous one (in the first stage). The difference was that some of them took placebos they believed to be anabolic steroids. Significantly greater gains in strength occurred during this second stage for those individuals, even though this stage was shorter in duration (4 weeks). The participants in this classic study increased their strength gains due to one main reason. They strongly believed it would happen.
Again, these were trained athletes; see the maximum weights lifted on the left, which are not in pounds but kilograms. For trained athletes, gains in strength are usually associated with gains in muscle mass. The gains may not look like much, and seem to be mostly in movements involving big muscle groups. Still, if you look carefully, you will notice that the bench press gain is of around 10-15 kg. This is a gain of 22-33 lbs, in a little less than one month!
This classic study has several implications. One is that if someone tells you that a useless supplement will lead to gains from strength training, and you believe that, maybe the gains will indeed happen. This study also provides indirect evidence that “psyching yourself up” for each strength training session may indeed be very useful, as many serious bodybuilders do. It is also reasonable to infer from this study that if you believe that you will not achieve gains from strength training, that belief may become reality.
As a side note, androgenic-anabolic steroids, better known as “anabolic steroids” or simply “steroids”, are synthetic derivatives of the hormone testosterone. Testosterone is present in males and females, but it is usually referred to as a male hormone because it is found in much higher concentrations in males than females.
Steroids have many negative side effects, particularly when taken in large quantities and for long periods of time. They tend to work only when taken in doses above a certain threshold (Wilmore et al., 2007); results below that threshold may actually be placebo effects. The effective thresholds for steroids tend to be high enough to lead to negative health side effects for most people. Still, they are used by bodybuilders as an effective aid to muscle gain, because they do lead to significant muscle gain in high doses. Adding to the negative side effects, steroids do not usually prevent fat gain.
References
Ariel, G., & Saville, W. (1972). Anabolic steroids: The physiological effects of placebos. Medicine and Science in Sports and Exercise, 4(2), 124-126.
Wilmore, J.H., Costill, D.L., & Kenney, W.L. (2007). Physiology of sport and exercise. Champaign, IL: Human Kinetics.
In the second stage the same participants completed a 4-week strength training program, very much like the previous one (in the first stage). The difference was that some of them took placebos they believed to be anabolic steroids. Significantly greater gains in strength occurred during this second stage for those individuals, even though this stage was shorter in duration (4 weeks). The participants in this classic study increased their strength gains due to one main reason. They strongly believed it would happen.
Again, these were trained athletes; see the maximum weights lifted on the left, which are not in pounds but kilograms. For trained athletes, gains in strength are usually associated with gains in muscle mass. The gains may not look like much, and seem to be mostly in movements involving big muscle groups. Still, if you look carefully, you will notice that the bench press gain is of around 10-15 kg. This is a gain of 22-33 lbs, in a little less than one month!
This classic study has several implications. One is that if someone tells you that a useless supplement will lead to gains from strength training, and you believe that, maybe the gains will indeed happen. This study also provides indirect evidence that “psyching yourself up” for each strength training session may indeed be very useful, as many serious bodybuilders do. It is also reasonable to infer from this study that if you believe that you will not achieve gains from strength training, that belief may become reality.
As a side note, androgenic-anabolic steroids, better known as “anabolic steroids” or simply “steroids”, are synthetic derivatives of the hormone testosterone. Testosterone is present in males and females, but it is usually referred to as a male hormone because it is found in much higher concentrations in males than females.
Steroids have many negative side effects, particularly when taken in large quantities and for long periods of time. They tend to work only when taken in doses above a certain threshold (Wilmore et al., 2007); results below that threshold may actually be placebo effects. The effective thresholds for steroids tend to be high enough to lead to negative health side effects for most people. Still, they are used by bodybuilders as an effective aid to muscle gain, because they do lead to significant muscle gain in high doses. Adding to the negative side effects, steroids do not usually prevent fat gain.
References
Ariel, G., & Saville, W. (1972). Anabolic steroids: The physiological effects of placebos. Medicine and Science in Sports and Exercise, 4(2), 124-126.
Wilmore, J.H., Costill, D.L., & Kenney, W.L. (2007). Physiology of sport and exercise. Champaign, IL: Human Kinetics.
Monday, November 8, 2010
Kids, Gender Identity, and Bullying: Moms Fight Back
Last week on Facebook, no less than ten friends posted a link to the Nerdy Apple Bottom website post "My son is gay". The post was written by the mother of a 5-year old boy who dressed as Daphne (from Scooby Doo) for Halloween. She talks about his arrival at school in his costume and the harsh reaction received...mostly from other parents. She documents her internal reaction to this reception, which prompted much discussion and cheering among my Facebook friends:"If you think that me allowing my son to be a female character for Halloween is somehow going to 'make' him gay, then you are an idiot. Firstly, what a ridiculous concept. Secondly, if my son is gay, OK. I will love him no less. Thirdly, I am not worried that your son will grow up to be an actual ninja so back off".
As of tonight, this post had 41,311 comments.
Coincidentally, the November 15th edition of People Magazine runs a story called "A Tale of Acceptance". The story profiles a Seattle mother named Cheryl Kilodavis who also has a 5-year old son that likes to dress up as a girl character. When the behavior began three years ago, she and her husband discussed it and decided to let him dress how he liked. In order to help other kids accept him, Cheryl decided to write a children's story. She calls her self-published book, "My Princess Boy".
Cheryl first shared the book at her son's school. The vice principal loved it and put copies in all the classes. Cheryl soon had orders from nine other schools and now that there has been so much press coverage, the family is searching for a publisher and trying to keep up with the book requests.
Of course, not all of the press has been positive. A New York Times article late last week discussed some therapists' concerns about these young boys being "outed" by their parents by having their pictures posted on YouTube, blogs, and talk shows. Some commenters wonder why these mothers do not protect their children from ridicule by making them dress in costumes that are more gender appropriate.
The discussion of bullying and suicide over the past few months has seemed to provide a real "teachable moment" for this country. People want to talk about it (as evidenced by the 41,000+ comments on the Nerdy Apple Bottom site). People want to teach kids how to respect themselves and each other. Therefore, they seem fascinated by "My Princess Boy", which uses words and illustrations that can allow even the youngest children to participate in the discussion around personal expression and acceptance. These blogs and books and support from children's schools can really help to change the social norms around what is "normal" behavior and dress. We must be creative in designing a way to evaluate these normative changes. Hopefully we will see a reduction in negative outcomes for students (e.g., reports of bullying, rates of depression, and suicide). But hopefully we will also see a reduction in risk factors further up stream, like attitudes around acceptance and gender roles.
High-heat cooking will AGE you, if you eat food deep-fried with industrial vegetable oils
As I said before on this blog, I am yet to be convinced that grilled meat is truly unhealthy in the absence of leaky gut problems. I am referring here to high heat cooking-induced Maillard reactions (browning) and the resulting advanced glycation endproducts (AGEs). Whenever you cook a food in high heat, to the point of browning it, you generate a Maillard reaction. Searing and roasting meat usually leads to that.
Elevated levels of serum AGEs presumably accelerate the aging process in humans. This is supported by research with uncontrolled diabetics, who seem to have elevated levels of serum AGEs. In fact, a widely used measure in the treatment of diabetes, the HbA1c (or percentage of glycated hemoglobin), is actually a measure of endogenous AGE formation. (Endogenous = generated by our own bodies.)
Still, evidence that a person with an uncompromised gut can cause serum levels of AGEs to go up significantly by eating AGEs is weak, and evidence that any related serum AGE increases lead the average person to develop health problems is pretty much nonexistent. The human body can handle AGEs, as long as their concentration is not too high. We cannot forget that a healthy HbA1c in humans is about 5 percent; meaning that AGEs are created and dealt with by our bodies. A healthy HbA1c in humans is not 0 percent.
Thanks again to Justin for sending me the full text version of the Birlouez-Aragon et al. (2010) article, which is partially reviewed here. See this post and the comments under it for some background on this discussion. The article is unequivocally titled: “A diet based on high-heat-treated foods promotes risk factors for diabetes mellitus and cardiovascular diseases.”
This article is recent, and has already been cited by news agencies and bloggers as providing “definitive” evidence that high-heat cooking is bad for one’s health. Interestingly, quite a few of those citations are in connection with high-heat cooking of meat, which is not even the focus of the article.
In fact, the Birlouez-Aragon et al. (2010) article provides no evidence that high-heat cooking of meat leads to AGEing in humans. If anything, the article points at the use of industrial vegetable oils for cooking as the main problem. And we know already that industrial vegetable oils are not healthy, whether you cook with them or drink them cold by the tablespoon.
But there are a number of good things about this article. For example, the authors summarize past research on AGEs. They focus on MRPs, which are “Maillard reaction products”. One of the summary statements supports what I have said on this blog before:
"The few human intervention trials […] that reported on health effects of dietary MRPs have all focused on patients with diabetes or renal failure."
That is, there is no evidence from human studies that dietary AGEs cause health problems outside the context of preexisting conditions that themselves seem to be associated with endogenous AGE production. To that I would add that gut permeability may also be a problem, as in celiacs ingesting large amounts of AGEs.
As you can see from the quote below, the authors decided to focus their investigation on a particular type of AGE, namely CML or carboxymethyllysine.
"...we decided to specifically quantify CML, as a well-accepted MRP indicator ..."
As I noted in my comments under this post (the oven roasted pork tenderloin post), one particular type of diet seems to lead to high serum CML levels – a vegetarian diet.
So let us see what the authors studied:
"... we conducted a randomized, crossover, intervention trial to clarify whether a habitual diet containing high-heat-treated foods, such as deep-fried potatoes, cookies, brown crusted bread, or fried meat, could promote risk factors of type 2 diabetes or cardiovascular diseases in healthy people."
Well, “deep-fried potatoes” is a red flag, don’t you think? They don’t say what oil was used for deep-frying, but I bet it was not coconut or olive oil. Cheap industrial vegetable oils (corn, safflower etc.) are the ones normally used (and re-used) for deep-frying. This is in part because these oils are cheap, and in part because they have high “smoke points” (the temperature at which the oil begins to generate smoke).
Let us see what else the authors say about the dietary conditions they compared:
"The STD was prepared by using conventional techniques such as grilling, frying, and roasting and contained industrial food known to be highly cooked, such as extruded corn flakes, coffee, dry cookies, and well-baked bread with brown crust. In contrast, the STMD comprised some raw food and foods that were cooked with steam techniques only. In addition, convenience products were chosen according to the minimal process applied (ie, steamed corn flakes, tea, sponge cakes, and mildly baked bread) ..."
The STD diet was the one with high-heat preparation of foods; in the STMD diet the foods were all steam-cooked at relatively low temperatures. Clearly these diets were mostly of plant-based foods, and of the unhealthy kind!
The following quote, from the results, pretty much tells us that the high omega-6 content of industrial oils used for deep frying was likely to be a major confounder, if not the main culprit:
"... substantial differences in the plasma fatty acid profile with higher plasma concentrations of long-chain omega-3 fatty acids […] and lower concentrations of omega-6 fatty acids […] were analyzed in the STMD group compared with in the STD group."
That is, the high-heat cooking group had higher plasma concentrations of omega-6 fats, which is what you would expect from a group consuming a large amount of industrial vegetable oils. One single tablespoon per day is already a large amount; these folks were probably consuming more than that.
Perhaps a better title for this study would have been: “A diet based on foods deep-fried in industrial vegetable oils promotes risk factors for diabetes mellitus and cardiovascular diseases.”
This study doesn’t even get close to indicting charred meat as a major source of serum AGEs. But it is not an exception among studies that many claim to do so.
Reference
H Birlouez-Aragon, I., Saavedra, G., Tessier, F.J., Galinier, A., Ait-Ameur, L., Lacoste, F., Niamba, C.-N., Alt, N., Somoza, V., & Lecerf, J.-M. (2010). A diet based on high-heat-treated foods promotes risk factors for diabetes mellitus and cardiovascular diseases. The American Journal of Clinical Nutrition, 91(5), 1220-1226.
Elevated levels of serum AGEs presumably accelerate the aging process in humans. This is supported by research with uncontrolled diabetics, who seem to have elevated levels of serum AGEs. In fact, a widely used measure in the treatment of diabetes, the HbA1c (or percentage of glycated hemoglobin), is actually a measure of endogenous AGE formation. (Endogenous = generated by our own bodies.)
Still, evidence that a person with an uncompromised gut can cause serum levels of AGEs to go up significantly by eating AGEs is weak, and evidence that any related serum AGE increases lead the average person to develop health problems is pretty much nonexistent. The human body can handle AGEs, as long as their concentration is not too high. We cannot forget that a healthy HbA1c in humans is about 5 percent; meaning that AGEs are created and dealt with by our bodies. A healthy HbA1c in humans is not 0 percent.
Thanks again to Justin for sending me the full text version of the Birlouez-Aragon et al. (2010) article, which is partially reviewed here. See this post and the comments under it for some background on this discussion. The article is unequivocally titled: “A diet based on high-heat-treated foods promotes risk factors for diabetes mellitus and cardiovascular diseases.”
This article is recent, and has already been cited by news agencies and bloggers as providing “definitive” evidence that high-heat cooking is bad for one’s health. Interestingly, quite a few of those citations are in connection with high-heat cooking of meat, which is not even the focus of the article.
In fact, the Birlouez-Aragon et al. (2010) article provides no evidence that high-heat cooking of meat leads to AGEing in humans. If anything, the article points at the use of industrial vegetable oils for cooking as the main problem. And we know already that industrial vegetable oils are not healthy, whether you cook with them or drink them cold by the tablespoon.
But there are a number of good things about this article. For example, the authors summarize past research on AGEs. They focus on MRPs, which are “Maillard reaction products”. One of the summary statements supports what I have said on this blog before:
"The few human intervention trials […] that reported on health effects of dietary MRPs have all focused on patients with diabetes or renal failure."
That is, there is no evidence from human studies that dietary AGEs cause health problems outside the context of preexisting conditions that themselves seem to be associated with endogenous AGE production. To that I would add that gut permeability may also be a problem, as in celiacs ingesting large amounts of AGEs.
As you can see from the quote below, the authors decided to focus their investigation on a particular type of AGE, namely CML or carboxymethyllysine.
"...we decided to specifically quantify CML, as a well-accepted MRP indicator ..."
As I noted in my comments under this post (the oven roasted pork tenderloin post), one particular type of diet seems to lead to high serum CML levels – a vegetarian diet.
So let us see what the authors studied:
"... we conducted a randomized, crossover, intervention trial to clarify whether a habitual diet containing high-heat-treated foods, such as deep-fried potatoes, cookies, brown crusted bread, or fried meat, could promote risk factors of type 2 diabetes or cardiovascular diseases in healthy people."
Well, “deep-fried potatoes” is a red flag, don’t you think? They don’t say what oil was used for deep-frying, but I bet it was not coconut or olive oil. Cheap industrial vegetable oils (corn, safflower etc.) are the ones normally used (and re-used) for deep-frying. This is in part because these oils are cheap, and in part because they have high “smoke points” (the temperature at which the oil begins to generate smoke).
Let us see what else the authors say about the dietary conditions they compared:
"The STD was prepared by using conventional techniques such as grilling, frying, and roasting and contained industrial food known to be highly cooked, such as extruded corn flakes, coffee, dry cookies, and well-baked bread with brown crust. In contrast, the STMD comprised some raw food and foods that were cooked with steam techniques only. In addition, convenience products were chosen according to the minimal process applied (ie, steamed corn flakes, tea, sponge cakes, and mildly baked bread) ..."
The STD diet was the one with high-heat preparation of foods; in the STMD diet the foods were all steam-cooked at relatively low temperatures. Clearly these diets were mostly of plant-based foods, and of the unhealthy kind!
The following quote, from the results, pretty much tells us that the high omega-6 content of industrial oils used for deep frying was likely to be a major confounder, if not the main culprit:
"... substantial differences in the plasma fatty acid profile with higher plasma concentrations of long-chain omega-3 fatty acids […] and lower concentrations of omega-6 fatty acids […] were analyzed in the STMD group compared with in the STD group."
That is, the high-heat cooking group had higher plasma concentrations of omega-6 fats, which is what you would expect from a group consuming a large amount of industrial vegetable oils. One single tablespoon per day is already a large amount; these folks were probably consuming more than that.
Perhaps a better title for this study would have been: “A diet based on foods deep-fried in industrial vegetable oils promotes risk factors for diabetes mellitus and cardiovascular diseases.”
This study doesn’t even get close to indicting charred meat as a major source of serum AGEs. But it is not an exception among studies that many claim to do so.
Reference
H Birlouez-Aragon, I., Saavedra, G., Tessier, F.J., Galinier, A., Ait-Ameur, L., Lacoste, F., Niamba, C.-N., Alt, N., Somoza, V., & Lecerf, J.-M. (2010). A diet based on high-heat-treated foods promotes risk factors for diabetes mellitus and cardiovascular diseases. The American Journal of Clinical Nutrition, 91(5), 1220-1226.
Monday, November 1, 2010
Marie Claire Blogger vs. Mike & Molly: A "Heavyweight" Fight
Last week a blogger for Marie Claire Magazine named Maura Kelly posted an article called, "Should 'Fatties' Get a Room? (Even on TV)?" The post is focused on a new fall sitcom for CBS called "Mike & Molly". I must disclose that I have not watched this show, but have read that it centers on a couple that meets at an Overeaters Anonymous Group. Ms. Kelly takes a strong position that this show is "promoting obesity" and is grossed out by having to watch two obese people make out (or do anything else, like walk across a room).As you can imagine, this post has been met with quite a reaction, including 3,195 reader comments (as of tonight) that prompted Ms. Kelly to post an update (aka apology). The update apologizes to those readers that were offended (many of which state that they have since canceled their Marie Claire subscription) and offers that perhaps her strong reaction to these overweight actors comes from her own history as an anorexic. The gist I get from the comments, is that most readers do not feel the apology is sincere and expected a better response from Marie Claire (that would include firing Ms. Kelly and/or making it clear that they will not support this type of discrimination). There has also been a strong response from the celebrity community, including Sharon Osborne on "The Talk" who said that she was appalled and wondered about what Ms. Kelly would think of her. Sharon admitted that she's 30 pounds overweight...should she not be allowed to kiss her husband or walk across the room?
According to the Centers for Disease Control and Prevention (CDC), 34% of adults are overweight and about the same percentage are obese. If approximately 70% of our adult population is overweight or obese, why don't we have more characters that accurately reflect what people actually look like and the challenges that they face? Hasn't there been some effort to portray more diverse characters in other ways (e.g., race and ethnicity)? Why would being overweight be so offensive to the viewing population? And is Mike & Molly really the first show to do this? Growing up, I was a fan of the sitcom "Roseanne" (1988-1997). The primary couple on the show (Rosanne Barr and John Goodman) were very overweight and struggled quite openly with weight, diet, and exercise on the show. Perhaps my memory is fuzzy, but I never remember hearing that viewers were horrified by these characters showing affection on the show.
Ironically, as I was getting ready to put this post together today, I caught the Oprah show. She had on Portia Di Rossi who discusses her battle with Anorexia and Bulimia in her new book "Unbearable Lightness".
Portia spoke about her breakout role in Ally McBeal in the 1990s. Many of you may remember the media headlines at that time calling the three female leads "Scary Skinny" (which they were- Portia was down to 82 pounds at one point). Ironically, she specifically discussed her fear about a scene where she seduces her boss in her lingerie in the law office. Although she was skeletal and sick looking, did we hear from viewers or writers that they were "grossed out" to watch her make out with her boss on the show?
So what is best for viewers? What messages regarding "normal" should we be sending to viewers? If actors are too skinny, the concern is that the image is not realistic and it is causing young girls to have eating disorders trying to achieve this ideal. However, when a show like Mike & Molly is showing characters that accurately represent 70% of the population, there is also controversy. From a public health perspective, I would say that characters should accurately reflect the viewing population- people tend to respond to people that they can relate to. If you are creating a health communication product (e.g., poster or brochure), you test it with the target audience to make sure that they connect to the images. If you are concerned about "promoting obesity", then have the characters modeling healthy behaviors. For example, Mike & Molly are attending an Overeaters Anonymous Group, which means they are taking steps to improve their lifestyle.
I for one, would be very happy to see more realistic characters on television. I would also like to see research on how those characters can be used as a health communication tool to promote positive body image and health behaviors among the viewing population.
Amino acids in skeletal muscle: Are protein supplements as good as advertised?
When protein-rich foods, like meat, are ingested they are first broken down into peptides through digestion. As digestion continues, peptides are broken down into amino acids, which then enter circulation, becoming part of the blood plasma. They are then either incorporated into various tissues, such as skeletal muscle, or used for other purposes (e.g., oxidation and glucose generation). The table below shows the amino acid composition of blood plasma and skeletal muscle. It was taken from Brooks et al. (2005), and published originally in a classic 1974 article by Bergström and colleagues. Essential amino acids, shown at the bottom of the table, are those that have to be consumed through the diet. The human body cannot synthesize them. (Tyrosine is essential in children; in adults tryptophan is essential.)
The data is from 18 young and healthy individuals (16 males and 2 females) after an overnight fast. The gradient is a measure that contrasts the concentration of an amino acid in muscle against its concentration in blood plasma. Amino acids are transported into muscle cells by amino acid transporters, such as the vesicular glutamate transporter 1 (VGLUT1). Transporters exist because without them a substance’s gradient higher or lower than 1 would induce diffusion through cell membranes; that is, without transporters anything would enter or leave cells.
Research suggests that muscle uptake of amino acids is positively correlated with the concentration of the amino acids in plasma (as well as the level of activity of transporters) and that this effect is negatively moderated by the gradient. This is especially true after strength training, when protein synthesis is greatly enhanced. In other words, if the plasma concentration of an amino acid such as alanine is high, muscle uptake will be increased (with the proper stimulus; e.g., strength training). But if a lot of alanine is already present in muscle cells when compared to plasma (which is normally the case, since alanine’s 7.3 gradient is relatively high), more plasma alanine will be needed to increase muscle uptake.
The amino acid makeup of skeletal muscle is a product of evolutionary forces, which largely operated on our Paleolithic ancestors. Those ancestors obtained their protein primarily from meat, eggs, vegetables, fruits, and nuts. Vegetables and fruits today are generally poor sources of protein; that was probably the case in the Paleolithic as well. Also, only when very young our Paleolithic ancestors obtained their protein from human milk. It is very unlikely that they drank the milk of other animals. Still, many people today possess genetic adaptations that enable them to consume milk (and dairy products in general) effectively due to a more recent (Neolithic) ancestral heritage. A food-related trait can evolve very fast – e.g., in a few hundred years.
One implication of all of this is that protein supplements in general may not be better sources of amino acids than natural protein-rich foods, such as meat or eggs. Supplements may provide more of certain amino acids than others sources, but given the amino acid makeup of skeletal muscle, a supplemental overload of a particular amino acid is unlikely to be particularly healthy. That overload may induce an unnatural increase in amino acid oxidation, or an abnormal generation of glucose through gluconeogenesis. Depending on one’s overall diet, those may in turn lead to elevated blood glucose levels and/or a caloric surplus. The final outcome may be body fat gain.
Another implication is that man-made foods that claim to be high in protein, and that are thus advertised as muscle growth supplements, may actually be poor sources of those amino acids whose concentration in muscle are highest. (You need to check the label for the amino acid composition, and trust the manufacturer.) Moreover, if they are sources of nonessential amino acids, they may overload your body if you consume a balanced diet. Interestingly, nonessential amino acids are synthesized from carbon sources. A good source of carbon is glucose.
Among the essential amino acids are a group called branched-chain amino acids (BCAA) – leucine, isoleucine, and valine. Much is made of these amino acids, but their concentration in muscle in adults is not that high. That is, they do not contribute significantly as building blocks to protein synthesis in skeletal muscle. What makes BCAAs somewhat unique is that they are highly ketogenic, and somewhat glucogenic (via gluconeogenesis). They also lead to insulin spikes. Ingestion of BCAAs increases the blood concentration of two of the three human ketone bodies (acetone and acetoacetate). Ketosis is both protein and glycogen sparing (but gluconeogenesis is not), which is among the reasons why ketosis is significantly induced by exercise (blood ketones concentration is much more elevated after exercise than after a 20 h fast). This is probably why some exercise physiologists and personal trainers recommend consumption of BCAAs immediately prior to or during anaerobic exercise.
Why do carnivores often consume prey animals whole? (Consumption of eggs is not the same, but similar, because an egg is the starting point for the development of a whole animal.) Carnivores consume prey animals whole arguably because prey animals have those tissues (muscle, organ etc. tissues) that carnivores also have, in roughly the same amounts. Prey animals that are herbivores do all the work of converting their own prey (plants) to tissues that they share with carnivores. Carnivores benefit from that work, paying back herbivores by placing selective pressures on them that are health-promoting at the population level. (Carnivores usually target those prey animals that show signs of weakness or disease.)
Supplements would be truly natural if they provided nutrients that mimicked eating an animal whole. Most supplements do not get even close to doing that; and this includes protein supplements.
Reference
Brooks, G.A., Fahey, T.D., & Baldwin, K.M. (2005). Exercise physiology: Human bioenergetics and its applications. Boston, MA: McGraw-Hill.
The data is from 18 young and healthy individuals (16 males and 2 females) after an overnight fast. The gradient is a measure that contrasts the concentration of an amino acid in muscle against its concentration in blood plasma. Amino acids are transported into muscle cells by amino acid transporters, such as the vesicular glutamate transporter 1 (VGLUT1). Transporters exist because without them a substance’s gradient higher or lower than 1 would induce diffusion through cell membranes; that is, without transporters anything would enter or leave cells.
Research suggests that muscle uptake of amino acids is positively correlated with the concentration of the amino acids in plasma (as well as the level of activity of transporters) and that this effect is negatively moderated by the gradient. This is especially true after strength training, when protein synthesis is greatly enhanced. In other words, if the plasma concentration of an amino acid such as alanine is high, muscle uptake will be increased (with the proper stimulus; e.g., strength training). But if a lot of alanine is already present in muscle cells when compared to plasma (which is normally the case, since alanine’s 7.3 gradient is relatively high), more plasma alanine will be needed to increase muscle uptake.
The amino acid makeup of skeletal muscle is a product of evolutionary forces, which largely operated on our Paleolithic ancestors. Those ancestors obtained their protein primarily from meat, eggs, vegetables, fruits, and nuts. Vegetables and fruits today are generally poor sources of protein; that was probably the case in the Paleolithic as well. Also, only when very young our Paleolithic ancestors obtained their protein from human milk. It is very unlikely that they drank the milk of other animals. Still, many people today possess genetic adaptations that enable them to consume milk (and dairy products in general) effectively due to a more recent (Neolithic) ancestral heritage. A food-related trait can evolve very fast – e.g., in a few hundred years.
One implication of all of this is that protein supplements in general may not be better sources of amino acids than natural protein-rich foods, such as meat or eggs. Supplements may provide more of certain amino acids than others sources, but given the amino acid makeup of skeletal muscle, a supplemental overload of a particular amino acid is unlikely to be particularly healthy. That overload may induce an unnatural increase in amino acid oxidation, or an abnormal generation of glucose through gluconeogenesis. Depending on one’s overall diet, those may in turn lead to elevated blood glucose levels and/or a caloric surplus. The final outcome may be body fat gain.
Another implication is that man-made foods that claim to be high in protein, and that are thus advertised as muscle growth supplements, may actually be poor sources of those amino acids whose concentration in muscle are highest. (You need to check the label for the amino acid composition, and trust the manufacturer.) Moreover, if they are sources of nonessential amino acids, they may overload your body if you consume a balanced diet. Interestingly, nonessential amino acids are synthesized from carbon sources. A good source of carbon is glucose.
Among the essential amino acids are a group called branched-chain amino acids (BCAA) – leucine, isoleucine, and valine. Much is made of these amino acids, but their concentration in muscle in adults is not that high. That is, they do not contribute significantly as building blocks to protein synthesis in skeletal muscle. What makes BCAAs somewhat unique is that they are highly ketogenic, and somewhat glucogenic (via gluconeogenesis). They also lead to insulin spikes. Ingestion of BCAAs increases the blood concentration of two of the three human ketone bodies (acetone and acetoacetate). Ketosis is both protein and glycogen sparing (but gluconeogenesis is not), which is among the reasons why ketosis is significantly induced by exercise (blood ketones concentration is much more elevated after exercise than after a 20 h fast). This is probably why some exercise physiologists and personal trainers recommend consumption of BCAAs immediately prior to or during anaerobic exercise.
Why do carnivores often consume prey animals whole? (Consumption of eggs is not the same, but similar, because an egg is the starting point for the development of a whole animal.) Carnivores consume prey animals whole arguably because prey animals have those tissues (muscle, organ etc. tissues) that carnivores also have, in roughly the same amounts. Prey animals that are herbivores do all the work of converting their own prey (plants) to tissues that they share with carnivores. Carnivores benefit from that work, paying back herbivores by placing selective pressures on them that are health-promoting at the population level. (Carnivores usually target those prey animals that show signs of weakness or disease.)
Supplements would be truly natural if they provided nutrients that mimicked eating an animal whole. Most supplements do not get even close to doing that; and this includes protein supplements.
Reference
Brooks, G.A., Fahey, T.D., & Baldwin, K.M. (2005). Exercise physiology: Human bioenergetics and its applications. Boston, MA: McGraw-Hill.
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