Most of us have heard of cytokines, signaling molecules secreted by cells that affect other cells. Examples are the various interleukins, some of which stimulate inflammation and others of which reduce inflammation. They are like text messages between cells.
When some cellular stress occurs, let's say an infection in your finger, certain cytokines are the distress signals, telling other types of cells to rush to the site and fix it. Then when things seem to be OK, different cytokines tell the cells to cool it, to stop trying to fix things (fixing involves inflammation) and let the site get back to normal.
Fat cells used to be considered boring blobs of stored calories, with no interesting functions. Then they discovered that fat cells also secreted signaling molecules, which they termed adipokines. One of the most widely known adipokine is leptin.
Hormones are also signaling molecules, and some people debate about which signaling molecules should be called cytokines or adipokines and which should be called hormones. Traditionally, hormones were considered to be molecules secreted by one organ that affected other organs. For example, beta cells secrete insulin, which has effects all over the body.
Cytokines were considered to be hormonelike molecules secreted by numerous cells throughout the body that affected immune system cells. Adipokines were considered to be hormonelike molecules secreted by fat cells. In both cases, a certain type of cell rather than a certain organ secretes the signaling molecules. And unlike hormones, which are usually synthesized and then stored within the cell for rapid release when needed, cytokines tend to be synthesized only when needed.
But there's a lot of overlap between cytokines and hormones, and some people think it's time to stop trying to classify the numerous new signaling molecules that seem to be discovered every week. The important thing is what they do.
Recently a new type of cellular "kine" has been proposed: the hepatokine.
A protein called selenoprotein P is produced in the liver and transports the trace mineral selenium from the liver to the cells that need it. These researchers found that selenoprotein P concentrations are higher in people with type 2 diabetes than they are in healthy people, and they proposed that overproduction of selenoprotein P in the liver causes insulin resistance and type 2 diabetes. Their research results were consistent with this hypothesis.
Interestingly, their results suggested that selenoprotein P works via AMPK, which is also affected by the diabetes drug metformin.
They said their research "raises the possibility that the liver functions as an endocrine organ by producing a variety of hepatokines and that the dysregulation or impairment of hepatokine production might contribute to the development of various diseases."
Whether or not selenoprotein P turns out to be vital in causing type 2 diabetes, I find this paper fascinating because it gives us a new way of approaching diabetes: looking for important modulators in a new place. Sometimes takes a shakeup of traditional ideas in order to make breakthroughs.
If there are adipokines and hepatokines, might there not also be musculokines or myokines? Skelatokines or osteokines? Or other "kines" in places no one has thought to look?
Maybe the tongue produces signaling molecules when it tastes different kinds of foods. We know that the sight, smell, and even thought of food can trigger nervous signals that affect gastric and insulin secretion (the cephalic phase of digestion). Why not small molecules as well?
Progress in genetic research is proceeding rapidly, but we still don't know what really causes type 2 diabetes. Perhaps these new ideas will stimulate new research that will come up with something that will help us prevent this epidemic disease.
Wednesday, December 22, 2010
Wednesday, November 24, 2010
Preconceptions . . . Again
Maybe it's a waste of time to point out the biased preconceptions one sees in various science journals; most of the intelligent people I assume are the primary readers of this blog can spot them for themselves. But they annoy me so much I can't not point them out.
The latest one occurred in an article titled "Overweight Primarily a Problem Among Wealthier Women in Low To Middle-Income Countries" and published in the American Journal of Clinical Nutrition.
Researchers at the Harvard School of Public Health reported that in less affluent countries, being overweight is more common among women with higher incomes (they studied only women). In contrast, in more affluent countries like the United States, obesity is associated with poverty.
I think this is intuitively obvious. When it's difficult to get enough food, then only richer people will obtain enough calories to become fat. When food is plentiful but starchy and fatty food is cheaper than meat and vegetables, then the poorer you are, the more apt you are to be fat.
A famous photo of an emaciated boy holding out a bowl and begging for rice, while behind him a fat (by the standards of those days) merchant woman sits among huge bags of rice, illustrates this. The boy isn't counting calories; he's starving.
So initially, I found the study pretty ho-hum. Then I came on this attempt at an explanation:
"The researchers theorize that these findings could be due to a number of factors, including that women in higher income groups are more likely to have diets richer in animal fats than lower-income women."
In other words, they started with the assumption that obesity (and probably all the other ills of a "Western" diet) stem from too much animal fat. So that must surely be the explanation here too.
Couldn't it also be because the richer women were able to buy white bread and jam instead of fiber-filled vegetables the poorer people probably grew themselves?
They do make a couple of other suggestions:
"Also, cultural norms in developing countries may favor fatty body shapes among wealthier women. Richer women are also less likely than poor women to engage in regular physical labor."
I'm sure the difference in physical work does make a difference. But if cultural norms in developing countries favored fatty body shapes among wealthier women (as a sign that you could afford a lot of food), wouldn't you think the same would be true among poor people as well? Wouldn't poor people want to look as if they were rich?
Sometimes the logic in nutrition papers boggles my mind.
The latest one occurred in an article titled "Overweight Primarily a Problem Among Wealthier Women in Low To Middle-Income Countries" and published in the American Journal of Clinical Nutrition.
Researchers at the Harvard School of Public Health reported that in less affluent countries, being overweight is more common among women with higher incomes (they studied only women). In contrast, in more affluent countries like the United States, obesity is associated with poverty.
I think this is intuitively obvious. When it's difficult to get enough food, then only richer people will obtain enough calories to become fat. When food is plentiful but starchy and fatty food is cheaper than meat and vegetables, then the poorer you are, the more apt you are to be fat.
A famous photo of an emaciated boy holding out a bowl and begging for rice, while behind him a fat (by the standards of those days) merchant woman sits among huge bags of rice, illustrates this. The boy isn't counting calories; he's starving.
So initially, I found the study pretty ho-hum. Then I came on this attempt at an explanation:
"The researchers theorize that these findings could be due to a number of factors, including that women in higher income groups are more likely to have diets richer in animal fats than lower-income women."
In other words, they started with the assumption that obesity (and probably all the other ills of a "Western" diet) stem from too much animal fat. So that must surely be the explanation here too.
Couldn't it also be because the richer women were able to buy white bread and jam instead of fiber-filled vegetables the poorer people probably grew themselves?
They do make a couple of other suggestions:
"Also, cultural norms in developing countries may favor fatty body shapes among wealthier women. Richer women are also less likely than poor women to engage in regular physical labor."
I'm sure the difference in physical work does make a difference. But if cultural norms in developing countries favored fatty body shapes among wealthier women (as a sign that you could afford a lot of food), wouldn't you think the same would be true among poor people as well? Wouldn't poor people want to look as if they were rich?
Sometimes the logic in nutrition papers boggles my mind.
Saturday, November 13, 2010
Free Full Text
Mary Ann Liebert, Inc, publisher of many journals, is offering free full text of their diabetes-related journals through the end of November. The offer is in recognition of World Diabetes Day.
The three journals are Diabetes Technology & Therapeutics, Metabolic Syndrome and Related Disorders, and Childhood Obesity.
I've often seen abstracts in the first journal and wished I could read the full texts, but access was too expensive. So this is a good chance to download the articles that interest you, if any.
The three journals are Diabetes Technology & Therapeutics, Metabolic Syndrome and Related Disorders, and Childhood Obesity.
I've often seen abstracts in the first journal and wished I could read the full texts, but access was too expensive. So this is a good chance to download the articles that interest you, if any.
Friday, October 22, 2010
Are Parasites in Charge?
Parasites can influence the behavior of the organisms they inhabit.
For example, mice infected with the protozoan Toxoplasma gondii, the organism that causes toxoplasmosis, become lethargic and lose their fear of cats, the primary host of the parasite
Clearly, in a cat-infested environment, such mice don't last very long. And the cats that eat the infected mice become infected themselves and then spread the eggs (oocysts) through their feces.
The behavior modification caused by other parasites in other organisms are even more bizarre.
So, could human behavior also be influenced by some of the parasites we all carry? Some people think yes.
Our guts are filled with bacteria. Many of these bacteria are beneficial. For example, gut bacteria produce most of the B vitamin biotin that we need. Other bacteria can cause obvious harm, for example, gut inflammation, pain, and diarrhea. The diarrhea benefits the bacteria because it increases the probability that other people will come in contact with the abundant fluid and become infected themselves.
Effects on behavior could be more subtle. We know that animals infected with rabies virus behave differently. They become more aggressive and tend to bite. Because the virus colonizes the salivary gland, such bites pass the infection on.
But why am I babbling about all this, interesting though it might be?
It's because I'm wondering if it's gut bacteria that program some people to eat more than normal, causing obesity. Why would the bacteria do that? Well, the more you eat, the more food there will be in the gut, which means the more the bacteria could grow.
There is some evidence that gut bacteria are related to obesity: overweight people tend to have different types of bacteria than normal-weight people. And some animal studies showed that transferring the gut bacteria from mice prone to metabolic syndrome into normal mice caused the normal ones to develop metabolic syndrome too.
So this idea that gut bacteria are associated with obesity is not new. Whether the bacterial population causes the obesity or the obesity provides a gut environment friendly to certain types of bacteria, or perhaps both in a vicious circle, has not yet been definitively proved.
A recent study reported at the Stockholm meeting of the European Association for the Study of Diabetes showed that transplanting fecal matter from thin people into obese people with prediabetes did not result in any weight loss. However, the recipients did see their insulin resistance decrease.
Clearly, obesity, type 2 diabetes, and gut populations are related somehow. One possibility is that certain bacteria are especially efficient converters of food and fiber into compounds that can easily be taken up in the gut, essentially adding calories to whatever we eat.
But I'm wondering if there's more than a metabolic effect. I wonder if the gut bacteria, like the parasites that change behavior in mice and spiders, are subtly changing the behavior of their hosts.
If the bacteria made the hosts feel sluggish, they wouldn't want to move around a lot and burn off calories. If the bacteria made the hosts hungry all the time, they would eat more than they needed to maintain their weight.
The bacteria could then happily munch on the extra calories, rapidly multiply, and infect other people.
Is this really true? No one knows. But the idea intrigues me.
For example, mice infected with the protozoan Toxoplasma gondii, the organism that causes toxoplasmosis, become lethargic and lose their fear of cats, the primary host of the parasite
Clearly, in a cat-infested environment, such mice don't last very long. And the cats that eat the infected mice become infected themselves and then spread the eggs (oocysts) through their feces.
The behavior modification caused by other parasites in other organisms are even more bizarre.
So, could human behavior also be influenced by some of the parasites we all carry? Some people think yes.
Our guts are filled with bacteria. Many of these bacteria are beneficial. For example, gut bacteria produce most of the B vitamin biotin that we need. Other bacteria can cause obvious harm, for example, gut inflammation, pain, and diarrhea. The diarrhea benefits the bacteria because it increases the probability that other people will come in contact with the abundant fluid and become infected themselves.
Effects on behavior could be more subtle. We know that animals infected with rabies virus behave differently. They become more aggressive and tend to bite. Because the virus colonizes the salivary gland, such bites pass the infection on.
But why am I babbling about all this, interesting though it might be?
It's because I'm wondering if it's gut bacteria that program some people to eat more than normal, causing obesity. Why would the bacteria do that? Well, the more you eat, the more food there will be in the gut, which means the more the bacteria could grow.
There is some evidence that gut bacteria are related to obesity: overweight people tend to have different types of bacteria than normal-weight people. And some animal studies showed that transferring the gut bacteria from mice prone to metabolic syndrome into normal mice caused the normal ones to develop metabolic syndrome too.
So this idea that gut bacteria are associated with obesity is not new. Whether the bacterial population causes the obesity or the obesity provides a gut environment friendly to certain types of bacteria, or perhaps both in a vicious circle, has not yet been definitively proved.
A recent study reported at the Stockholm meeting of the European Association for the Study of Diabetes showed that transplanting fecal matter from thin people into obese people with prediabetes did not result in any weight loss. However, the recipients did see their insulin resistance decrease.
Clearly, obesity, type 2 diabetes, and gut populations are related somehow. One possibility is that certain bacteria are especially efficient converters of food and fiber into compounds that can easily be taken up in the gut, essentially adding calories to whatever we eat.
But I'm wondering if there's more than a metabolic effect. I wonder if the gut bacteria, like the parasites that change behavior in mice and spiders, are subtly changing the behavior of their hosts.
If the bacteria made the hosts feel sluggish, they wouldn't want to move around a lot and burn off calories. If the bacteria made the hosts hungry all the time, they would eat more than they needed to maintain their weight.
The bacteria could then happily munch on the extra calories, rapidly multiply, and infect other people.
Is this really true? No one knows. But the idea intrigues me.
Friday, October 15, 2010
Popular Press Spins
When I was in graduate school, way back in the 1960s, almost every news report about some scientific finding ended by trying to explain why this finding would help to cure cancer. This was the era of the War on Cancer, and scientists hoped that relating their research to curing cancer would increase their chances of getting big research grants.
In the virus course I took with Jim Watson, the exams usually included a question in which we had to explain why some newspaper report of a scientific finding was wrong, that it actually would have nothing to do with cancer. They were fun questions.
Today, instead of trying to show how new studies can help to cure cancer, most popular press stories I see suggest that the findings provide a new target for new drugs, probably hoping to increase their chances of getting funding from drug companies.
Many of the stories appearing in popular science releases like Eurekalert and Science Daily are written by PR people at the institutions where the research is done. Their goal is to call attention to their institutions, professors, and funding sources as well as to the research itself. As a result, usually more than half of the articles is garbage.
When I was a newspaper editor, we'd get tons of press releases like this, and part of our job was to rewrite them without the self-promoting garbage. But these science news sites don't do this. Most of them simply print the press releases verbatim; you can read exactly the same stories on myriad sites.
An example from Science Daily:
"Researchers at the University of Edinburgh report a new experimental compound that can improve memory and cognitive function in aging mice. The compound is being investigated with a view to developing a drug that could slow the natural decline in memory associated with aging.
"With support from the Wellcome Trust Seeding Drug Discovery award, the team has identified a preclinical condition that they hope to take into human trials within a year."
Note that in the first two paragraphs they've mentioned the institution, the potential for drug development, and the funding source. They haven't mentioned what we all want to know: what this compound is. You have to slog through a lot of other boring stuff before they'll reveal that. Some stories even list all the researchers, their degrees, and their positions at the university before they'll tell you what the new finding actually was.
Here's another one:
"University of Michigan scientists have identified events inside insulin-producing pancreatic cells that set the stage for a neonatal form of non-autoimmune type 1 diabetes, and may play a role in type 2 diabetes as well. The results point to a potential target for drugs to protect normally functioning proteins essential for producing insulin."
In this case the PR people managed to make the institution the first word of the article.
You may say, "So what!" and that's partially true. We just have to learn to skim most of these articles to get to the crux of the story. And these popular press releases are important in alerting us to new journal articles that we'd probably never know of otherwise. Most of the press releases do have links to the original articles, although in many cases we can only read the abstracts unless we want to pay.
But I think the important thing is to remember that these articles are written by PR people whose goal is different from our goal. Their goal is to publicize their institution and overemphasize the importance of the research there. Our goal is to understand as completely as possible how good the evidence supporting the claims in the summary article is.
Whenever possible, I try to get the full text of an important article. I don't make the effort for what I consider less important ones. Time is not infinite. I once spent 2 days researching the science behind a story about using lettuce and some complex molecular biology to give people insulin by eating lettuce. Most of the popular press summaries didn't really understand what the research showed.
But if I spent 2 days researching every article I read, I wouldn't be able to read very many, and in the long run I'm hoping that having a surface acquaintance with a lot of research will be more useful than having an in-depth acquaintance with just a little.
I'm sure most of you are already aware of the way the press spins news about science research. But it never hurts to examine it again.
It's a reader-beware situation out there.
In the virus course I took with Jim Watson, the exams usually included a question in which we had to explain why some newspaper report of a scientific finding was wrong, that it actually would have nothing to do with cancer. They were fun questions.
Today, instead of trying to show how new studies can help to cure cancer, most popular press stories I see suggest that the findings provide a new target for new drugs, probably hoping to increase their chances of getting funding from drug companies.
Many of the stories appearing in popular science releases like Eurekalert and Science Daily are written by PR people at the institutions where the research is done. Their goal is to call attention to their institutions, professors, and funding sources as well as to the research itself. As a result, usually more than half of the articles is garbage.
When I was a newspaper editor, we'd get tons of press releases like this, and part of our job was to rewrite them without the self-promoting garbage. But these science news sites don't do this. Most of them simply print the press releases verbatim; you can read exactly the same stories on myriad sites.
An example from Science Daily:
"Researchers at the University of Edinburgh report a new experimental compound that can improve memory and cognitive function in aging mice. The compound is being investigated with a view to developing a drug that could slow the natural decline in memory associated with aging.
"With support from the Wellcome Trust Seeding Drug Discovery award, the team has identified a preclinical condition that they hope to take into human trials within a year."
Note that in the first two paragraphs they've mentioned the institution, the potential for drug development, and the funding source. They haven't mentioned what we all want to know: what this compound is. You have to slog through a lot of other boring stuff before they'll reveal that. Some stories even list all the researchers, their degrees, and their positions at the university before they'll tell you what the new finding actually was.
Here's another one:
"University of Michigan scientists have identified events inside insulin-producing pancreatic cells that set the stage for a neonatal form of non-autoimmune type 1 diabetes, and may play a role in type 2 diabetes as well. The results point to a potential target for drugs to protect normally functioning proteins essential for producing insulin."
In this case the PR people managed to make the institution the first word of the article.
You may say, "So what!" and that's partially true. We just have to learn to skim most of these articles to get to the crux of the story. And these popular press releases are important in alerting us to new journal articles that we'd probably never know of otherwise. Most of the press releases do have links to the original articles, although in many cases we can only read the abstracts unless we want to pay.
But I think the important thing is to remember that these articles are written by PR people whose goal is different from our goal. Their goal is to publicize their institution and overemphasize the importance of the research there. Our goal is to understand as completely as possible how good the evidence supporting the claims in the summary article is.
Whenever possible, I try to get the full text of an important article. I don't make the effort for what I consider less important ones. Time is not infinite. I once spent 2 days researching the science behind a story about using lettuce and some complex molecular biology to give people insulin by eating lettuce. Most of the popular press summaries didn't really understand what the research showed.
But if I spent 2 days researching every article I read, I wouldn't be able to read very many, and in the long run I'm hoping that having a surface acquaintance with a lot of research will be more useful than having an in-depth acquaintance with just a little.
I'm sure most of you are already aware of the way the press spins news about science research. But it never hurts to examine it again.
It's a reader-beware situation out there.
Thursday, August 5, 2010
Lipids and Diet
Low-carb and low-fat diets result in similar weight loss at 2 years when both are accompanied by comprehensive lifestyle counseling, according to a recent research project by Gary Foster and colleagues published in the Annals of Internal Medicine.
But people in the low-carb diet showed better lipid profiles after 2 years.
You have to pay to read the full text of the article, but low-carb advocate Jimmy Moore has an extensive discussion of the results including some graphs.
This study is important because it shows that various improvements in people following low-carb diets are not simply temporary. Although 2 years can't really be called long term, it's heading in the right direction.
What I find fascinating is the reaction to this article. I can't find it at all on either Science Daily or Eurekalert, both popular summaries of science news. They're always quick to report studies that say red meat is bad or low-carb diets cause problems. Why aren't they summarizing this study? Many other media outlets are, so it's not that the study is obscure.
Others have put a positive or a negative spin or a neutral spin on the study (not mentioning the better lipid profiles is actually a negative spin), some by the way they write their headlines. If you support low-carb diets, you can emphasize the fact that the lipid levels improved on that diet. If you don't, you can focus on the fact that weight loss was the same. Many people remember only the headlines; here are a few of them:
Positive:
Low-carb diets improve cholesterol long term (Medicinenet)
Low-carbohydrate diet beats low-fat diet in decreasing heart risk (Thaindian news)
Low-carb diet better for heart health than low-fat diet (The Money Times)
Neutral
Low-carb, low-fat diets tied for long term weight loss (uamshealth.com) (University of Arkansas for Medical Sciences)
Study disputes low-carb diet concerns (Philadelphia Inquirer)
Low-carb diet as good as low-fat one (Press TV)
When people do studies of "low-carb" diets that include 150 grams of carbs, low-carb supporters scream that such diets aren't really low carb (and I agree with this), that if they'd tested 50 g or 30 g or 20 g a day, they would have seen different results.
In this case, the low-fat supporters are screaming that a diet with <30% fat isn't really a low-fat diet, that if they'd limited fat to 10%, they would have seen different results.
I agree that this study would have been better if they'd tested 4 different diets: very low carb ketogenic diet (<50 g carbs), low-carb diet (50-130 g), low-fat diet (<30% fat), very low fat (<10%).
But I think the researchers were trying to compare a standard Atkins diet (the diet many people think about when they think low carb, even though there are other low-carb diets that I think are better) with "standard care," which still often means following the old Food Pyramid with 60% carbs and <30% fat.
They may also have worried that few of the study subjects would have been willing to stick to the stricter diets for 2 years or more. Even with the more moderate diets, attrition was high: 32% for the low-fat diet and 42% for the low-carb diet at the end of 2 years.
The low-fat diet was limited in calories; the low-carb diet was not.
Both groups lost weight, rapidly at first, reaching a nadir at 6 months, and then regained some of the weight, so that by the end of 2 years, they'd lost an average of 7% of their starting weight.
Interestingly, this was the goal in the Diabetes Prevention Program weight-loss study of people at high risk of developing diabetes. The DPP showed that modest weight loss (the goal of 7% was not actually reached) could reduce the risk of progressing to overt diabetes. The same phenomenon occurred in that study too: subjects initially lost weight fast, then leveled off and started regaining again.
I think we've all experienced this phenomenon. We try a new diet and are enthusiastic and follow it exactly. Then after some time we hit a plateau and we also get bored with the diet and gradually revert to our old habits.
It's also possible that the body wants to maintain a certain weight that is higher than the weight we want it to have (the set-point theory), and after some time the metabolism changes to encourage the regaining of the weight.
People will never agree on the best diet for weight loss, partly because different people do better on different diets: YMMV, or "Your mileage may vary." But the more we know about various diets and various groups of dieters, preferable for as long as possible, the better.
Like weight loss, lipid levels tend to be different in the short term than they are in the long term. For example, in this study, triglycerides rapidly decreased in the low-carb group but then went up again and by the end of 2 years were about the same as the levels in the low-fat group. LDL levels went up in the low-carb group but later went down again. Only HDL levels were consistently higher on the low-carb diet throughout the study.
It's not clear whether the fluctuating lipid levels were because after 12 weeks the people on the low-carb diet were instructed to slowly start adding back carbs until their weight stabilized. This is what Atkins told people to do. But in fact, the weights in the low-carb group continued to drop after 12 weeks and then instead of "stabilizing" started to climb.
So it's also possible that the body was adapting to a different diet and adjusting the lipid levels after a certain amount of time on the diet. Perhaps we have a "lipid set-point" as well as a weight set-point, and the body keeps trying to reach it.
Regardless of the reasons for these shifts, in order to really understand how diets affect various heart health risks, we need longer-term data. Foster and colleagues have made a valuable first step. Perhaps even longer studies will follow.
But people in the low-carb diet showed better lipid profiles after 2 years.
You have to pay to read the full text of the article, but low-carb advocate Jimmy Moore has an extensive discussion of the results including some graphs.
This study is important because it shows that various improvements in people following low-carb diets are not simply temporary. Although 2 years can't really be called long term, it's heading in the right direction.
What I find fascinating is the reaction to this article. I can't find it at all on either Science Daily or Eurekalert, both popular summaries of science news. They're always quick to report studies that say red meat is bad or low-carb diets cause problems. Why aren't they summarizing this study? Many other media outlets are, so it's not that the study is obscure.
Others have put a positive or a negative spin or a neutral spin on the study (not mentioning the better lipid profiles is actually a negative spin), some by the way they write their headlines. If you support low-carb diets, you can emphasize the fact that the lipid levels improved on that diet. If you don't, you can focus on the fact that weight loss was the same. Many people remember only the headlines; here are a few of them:
Positive:
Low-carb diets improve cholesterol long term (Medicinenet)
Low-carbohydrate diet beats low-fat diet in decreasing heart risk (Thaindian news)
Low-carb diet better for heart health than low-fat diet (The Money Times)
Neutral
Low-carb, low-fat diets tied for long term weight loss (uamshealth.com) (University of Arkansas for Medical Sciences)
Study disputes low-carb diet concerns (Philadelphia Inquirer)
Low-carb diet as good as low-fat one (Press TV)
When people do studies of "low-carb" diets that include 150 grams of carbs, low-carb supporters scream that such diets aren't really low carb (and I agree with this), that if they'd tested 50 g or 30 g or 20 g a day, they would have seen different results.
In this case, the low-fat supporters are screaming that a diet with <30% fat isn't really a low-fat diet, that if they'd limited fat to 10%, they would have seen different results.
I agree that this study would have been better if they'd tested 4 different diets: very low carb ketogenic diet (<50 g carbs), low-carb diet (50-130 g), low-fat diet (<30% fat), very low fat (<10%).
But I think the researchers were trying to compare a standard Atkins diet (the diet many people think about when they think low carb, even though there are other low-carb diets that I think are better) with "standard care," which still often means following the old Food Pyramid with 60% carbs and <30% fat.
They may also have worried that few of the study subjects would have been willing to stick to the stricter diets for 2 years or more. Even with the more moderate diets, attrition was high: 32% for the low-fat diet and 42% for the low-carb diet at the end of 2 years.
The low-fat diet was limited in calories; the low-carb diet was not.
Both groups lost weight, rapidly at first, reaching a nadir at 6 months, and then regained some of the weight, so that by the end of 2 years, they'd lost an average of 7% of their starting weight.
Interestingly, this was the goal in the Diabetes Prevention Program weight-loss study of people at high risk of developing diabetes. The DPP showed that modest weight loss (the goal of 7% was not actually reached) could reduce the risk of progressing to overt diabetes. The same phenomenon occurred in that study too: subjects initially lost weight fast, then leveled off and started regaining again.
I think we've all experienced this phenomenon. We try a new diet and are enthusiastic and follow it exactly. Then after some time we hit a plateau and we also get bored with the diet and gradually revert to our old habits.
It's also possible that the body wants to maintain a certain weight that is higher than the weight we want it to have (the set-point theory), and after some time the metabolism changes to encourage the regaining of the weight.
People will never agree on the best diet for weight loss, partly because different people do better on different diets: YMMV, or "Your mileage may vary." But the more we know about various diets and various groups of dieters, preferable for as long as possible, the better.
Like weight loss, lipid levels tend to be different in the short term than they are in the long term. For example, in this study, triglycerides rapidly decreased in the low-carb group but then went up again and by the end of 2 years were about the same as the levels in the low-fat group. LDL levels went up in the low-carb group but later went down again. Only HDL levels were consistently higher on the low-carb diet throughout the study.
It's not clear whether the fluctuating lipid levels were because after 12 weeks the people on the low-carb diet were instructed to slowly start adding back carbs until their weight stabilized. This is what Atkins told people to do. But in fact, the weights in the low-carb group continued to drop after 12 weeks and then instead of "stabilizing" started to climb.
So it's also possible that the body was adapting to a different diet and adjusting the lipid levels after a certain amount of time on the diet. Perhaps we have a "lipid set-point" as well as a weight set-point, and the body keeps trying to reach it.
Regardless of the reasons for these shifts, in order to really understand how diets affect various heart health risks, we need longer-term data. Foster and colleagues have made a valuable first step. Perhaps even longer studies will follow.
Wednesday, July 7, 2010
Is Avandia Safe?
Stastics is not my strong suit, so I confess that I find reading about these massive human trials of drugs and other treatments to be more of a chore than a pleasure. Each study may use a different population group, a different drug dosage, a different end point, and a different time to the end point.
Furthermore, most of these trials are supported by drug companies, and I don't trust the results. There are many ways to manipulate the data to make small differences sound like large differences, or to explain away results that aren't what you wanted.
And you can't trust the headlines written by popular science news services like Science Daily or those in general medical magazines. They'll just restate the conclusions emphasized by the authors of a particular study and then reiterate the background of the topic. In many diabetes news stories, more space is devoted to explaining the difference between type 1 and type 2, giving the numbers now suffering from these conditions, and then describing the "obesity epidemic" than in describing what's new.
Three Science Daily headlines about Avandia (rosiglitazone from studies reported at the recent American Diabetes Association meeting in Orlando, Florida, illustrate how difficult it is for us to know what is really going on. They were as follows:
1. No Link Between Diabetes Drug Rosiglitazone and Increased Rate of Heart Attack, Study Finds.
2. Type 2 Diabetes Medication Rosiglitazone Associated With Increased Cardiovascular Risks and Death, Study Finds.
3. New Meta-Analysis Demonstrates Heart Risks Associated With Rosiglitazone.
What's going on here?
First note that the first headline mentions "heart attack," the second refers to "cardiovascular risks and death," and the third refers to "heart risks." None say what the risks are compared to, and cardiovascular risks or heart risks could refer to a lot of different things. I suspect most people wouldn't delve deeply into the details and would interpret these headlines simply as (1) Avandia good, (2) Avandia bad, and (3) Avandia bad.
Let's start with study number 3. This is a meta-analysis, and like many other people, I don't trust meta-analyses. What they do is try to take a lot of small studies in which the results weren't statistically significant and pool them all together so that the results become significant.
This is because the statistical significance depends on both the magnitude of an effect and the number of people in the study. So, for example, let's say you were testing a drug called SugarDown and found that among 300,000 people matched to controls not taking the drug, 200,000 saw their A1cs decrease by at least 1 point and only 100,000 of the control subjects reached this endpoint. That is, twice as many people taking the drug had a desired result.
But if you gave the drug to only 3 people matched to controls, 2 of those taking the drug reached the end point and only 1 not taking the drug reached the end point, this might suggest to you that this drug was worth trying in a larger trial, but even though twice as many taking the drug had a desired result, just as in the larger trial, the results would obviously not be significant. The result could have been the result of chance.
When the results are more extreme -- let's say all 3 people taking the drug dropped dead 15 minutes after taking it and none of the controls did, then there's less chance that the results would be from chance.
These are obviously extremes; most studies have more realistic numbers. But no trial is perfect. Too many study patients make the studies too expensive, and too few patients make the results unreliable.
A meta-analysis tries to overcome these limitations.
The problem is that unlike the studies themselves -- which are usually "double-blinded," meaning that neither the patient nor the researchers know which ones got the real drug and which one got the placebo -- the researchers doing the meta-analyses have the results of all the trials in front of them.
They are able to pick which ones to use. This can be difficult when each study has a different end point and different parameters. And even a researcher without an ulterior motive might have unconscious biases that would result in rejection of one study that had an undesired result and the use of another that had a desired result.
With those caveats, here's what this study, by Steven Nissen and Kathy Wolski, published in the Archives of Internal Medicine, concluded: "Eleven years after the introduction of rosiglitazone, the totality of randomized clinical trials continued to demonstrate increased risk for myocardial infarction [heart attack] although not for cardiovascular or all-cause mortality. The current findings suggest an unfavorable benefit to risk ratio for rosiglitazone."
In other words, in this meta-analysis of rosiglitazone (Avandia) studies, more patients had heart attacks when on rosiglitazone, but no more died.
Study number 2, published in JAMA, which was not a meta-analysis, concluded that "Compared with prescription of pioglitazone, prescription of rosiglitazone was associated with an increased risk of stroke, heart failure, and all-cause mortality and an increased risk of the composite of acute myocardial infarction (heart attack), stroke, heart failure, or all-cause mortality in patients 65 years or older." [Italics mine}
So this study was limited to people over 65, and the results were compared with those of patients getting a similar drug, pioglitazone, not with those of patients not getting any of this type of drug. It's always possible that some drug might have a positive effect on some outcome compared with no drug, but it might have a less positive effect than another drug, so compared with the second drug the results would appear to be negative.
Their conclusions also refer to stroke, heart failure (not heart attack), and all-cause mortality. They found no increase in heart attack rates, but then they lump heart attacks together with the other end points and say there was an increase in this composite result!
That's like saying eating beans causes a lot of gas, and a composite consisting of people who ate beans, crackers, and chicken soup had more gas than people who ate none of these things. Many people reading that statement would avoid crackers and chicken soup before important meetings, even though the crackers and chicken soup had no effect on gas production.
The conclusion in the Abstract of the article doesn't specifically mention that the drug had no significant effect on heart attack rates. It just mentions the significant effect on stroke, heart failure, and all-cause mortality and the effect on the composite index.
Some busy physicians quickly reading this composite conclusion in the Abstract (and many people don't take the time to read an entire article, assuming the Abstract summarizes it correctly) might conclude that heart attack rates were increased as well as the other endpoints.
This article has other flaws. They mention in the Introduction that 7 previous studies showed that rosiglitazone increased heart attack rates, but they don't say 7 out of how many or increased compared with what. Seven studies out of 8 would be one thing; 7 studies out of 50 would be another.
The authors noted that most studies that showed an increase in heart attacks with rosiglitazone (again, they don't say increased compared to what) were done in younger patients (54 to 65 years old), whereas their study was in people older than 65 years.
This is another source of confusion for people trying to decide whether or not to use a drug. What helps or harms in one patient population might not do the same in another population.
Study number 1 seems to contradict the other two. It has not yet been published but was presented at the ADA meeting. According to this study, rosiglitazone had no effect on heart attack rates or mortality. Then they also used a composite outcome -- heart attack, mortality, and stroke -- and said rosiglitazone reduced this composite outcome.
But only stroke rates actually decreased, by 64%, whereas the "rates of heart attack and death on their own showed no significant difference between those who took rosiglitazone and those who did not." Once again, the composite outcome is confusing, and people may come to an erroneous conclusion.
This study was limited to patients with diabetes and existing cardiovascular disease. Some got revascularization for their cardiovascular disease. Some got insulin or metformin instead of rosiglitazone.
And the results reported at the ADA meeting were from a post-trial analysis of the results from the BARI-2D trial, which was not designed to test the safety of rosiglitazone. Hence the drug was not randomly assigned. Reanalysis of studies designed to test something else are somewhat questionable.
So is rosiglitazone safe to take? The evidence is not clear-cut. The FDA will soon meet to discuss the safety issue, presumably taking into account other studies in addition to the three discussed here.
But these three studies are a good example of the slippery slope we have to deal with when results of large clinical trials are published: confused statistics, biased authors with ties to drug companies, and different patient groups, comparisons, and end points.
I wonder how many bad drugs are on the market because of confusing clinical studies. So too, I wonder how many good drugs might have been dropped from the pipeline because of equally confusing clinical studies.
Evaluating risks vs benefits is not simple, and the best choice for a large population is not always the best choice for an individual patient. You might be allergic to a drug that helps most patients. Conversely, a drug that harms most patients might be wonderful for you.
All this is one reason that controlling with good food and exercise should always be the first choice. But this isn't always enough. Then we and our physicians have to evaluate which drugs will work best for us.
It is not a simple task.
Furthermore, most of these trials are supported by drug companies, and I don't trust the results. There are many ways to manipulate the data to make small differences sound like large differences, or to explain away results that aren't what you wanted.
And you can't trust the headlines written by popular science news services like Science Daily or those in general medical magazines. They'll just restate the conclusions emphasized by the authors of a particular study and then reiterate the background of the topic. In many diabetes news stories, more space is devoted to explaining the difference between type 1 and type 2, giving the numbers now suffering from these conditions, and then describing the "obesity epidemic" than in describing what's new.
Three Science Daily headlines about Avandia (rosiglitazone from studies reported at the recent American Diabetes Association meeting in Orlando, Florida, illustrate how difficult it is for us to know what is really going on. They were as follows:
1. No Link Between Diabetes Drug Rosiglitazone and Increased Rate of Heart Attack, Study Finds.
2. Type 2 Diabetes Medication Rosiglitazone Associated With Increased Cardiovascular Risks and Death, Study Finds.
3. New Meta-Analysis Demonstrates Heart Risks Associated With Rosiglitazone.
What's going on here?
First note that the first headline mentions "heart attack," the second refers to "cardiovascular risks and death," and the third refers to "heart risks." None say what the risks are compared to, and cardiovascular risks or heart risks could refer to a lot of different things. I suspect most people wouldn't delve deeply into the details and would interpret these headlines simply as (1) Avandia good, (2) Avandia bad, and (3) Avandia bad.
Let's start with study number 3. This is a meta-analysis, and like many other people, I don't trust meta-analyses. What they do is try to take a lot of small studies in which the results weren't statistically significant and pool them all together so that the results become significant.
This is because the statistical significance depends on both the magnitude of an effect and the number of people in the study. So, for example, let's say you were testing a drug called SugarDown and found that among 300,000 people matched to controls not taking the drug, 200,000 saw their A1cs decrease by at least 1 point and only 100,000 of the control subjects reached this endpoint. That is, twice as many people taking the drug had a desired result.
But if you gave the drug to only 3 people matched to controls, 2 of those taking the drug reached the end point and only 1 not taking the drug reached the end point, this might suggest to you that this drug was worth trying in a larger trial, but even though twice as many taking the drug had a desired result, just as in the larger trial, the results would obviously not be significant. The result could have been the result of chance.
When the results are more extreme -- let's say all 3 people taking the drug dropped dead 15 minutes after taking it and none of the controls did, then there's less chance that the results would be from chance.
These are obviously extremes; most studies have more realistic numbers. But no trial is perfect. Too many study patients make the studies too expensive, and too few patients make the results unreliable.
A meta-analysis tries to overcome these limitations.
The problem is that unlike the studies themselves -- which are usually "double-blinded," meaning that neither the patient nor the researchers know which ones got the real drug and which one got the placebo -- the researchers doing the meta-analyses have the results of all the trials in front of them.
They are able to pick which ones to use. This can be difficult when each study has a different end point and different parameters. And even a researcher without an ulterior motive might have unconscious biases that would result in rejection of one study that had an undesired result and the use of another that had a desired result.
With those caveats, here's what this study, by Steven Nissen and Kathy Wolski, published in the Archives of Internal Medicine, concluded: "Eleven years after the introduction of rosiglitazone, the totality of randomized clinical trials continued to demonstrate increased risk for myocardial infarction [heart attack] although not for cardiovascular or all-cause mortality. The current findings suggest an unfavorable benefit to risk ratio for rosiglitazone."
In other words, in this meta-analysis of rosiglitazone (Avandia) studies, more patients had heart attacks when on rosiglitazone, but no more died.
Study number 2, published in JAMA, which was not a meta-analysis, concluded that "Compared with prescription of pioglitazone, prescription of rosiglitazone was associated with an increased risk of stroke, heart failure, and all-cause mortality and an increased risk of the composite of acute myocardial infarction (heart attack), stroke, heart failure, or all-cause mortality in patients 65 years or older." [Italics mine}
So this study was limited to people over 65, and the results were compared with those of patients getting a similar drug, pioglitazone, not with those of patients not getting any of this type of drug. It's always possible that some drug might have a positive effect on some outcome compared with no drug, but it might have a less positive effect than another drug, so compared with the second drug the results would appear to be negative.
Their conclusions also refer to stroke, heart failure (not heart attack), and all-cause mortality. They found no increase in heart attack rates, but then they lump heart attacks together with the other end points and say there was an increase in this composite result!
That's like saying eating beans causes a lot of gas, and a composite consisting of people who ate beans, crackers, and chicken soup had more gas than people who ate none of these things. Many people reading that statement would avoid crackers and chicken soup before important meetings, even though the crackers and chicken soup had no effect on gas production.
The conclusion in the Abstract of the article doesn't specifically mention that the drug had no significant effect on heart attack rates. It just mentions the significant effect on stroke, heart failure, and all-cause mortality and the effect on the composite index.
Some busy physicians quickly reading this composite conclusion in the Abstract (and many people don't take the time to read an entire article, assuming the Abstract summarizes it correctly) might conclude that heart attack rates were increased as well as the other endpoints.
This article has other flaws. They mention in the Introduction that 7 previous studies showed that rosiglitazone increased heart attack rates, but they don't say 7 out of how many or increased compared with what. Seven studies out of 8 would be one thing; 7 studies out of 50 would be another.
The authors noted that most studies that showed an increase in heart attacks with rosiglitazone (again, they don't say increased compared to what) were done in younger patients (54 to 65 years old), whereas their study was in people older than 65 years.
This is another source of confusion for people trying to decide whether or not to use a drug. What helps or harms in one patient population might not do the same in another population.
Study number 1 seems to contradict the other two. It has not yet been published but was presented at the ADA meeting. According to this study, rosiglitazone had no effect on heart attack rates or mortality. Then they also used a composite outcome -- heart attack, mortality, and stroke -- and said rosiglitazone reduced this composite outcome.
But only stroke rates actually decreased, by 64%, whereas the "rates of heart attack and death on their own showed no significant difference between those who took rosiglitazone and those who did not." Once again, the composite outcome is confusing, and people may come to an erroneous conclusion.
This study was limited to patients with diabetes and existing cardiovascular disease. Some got revascularization for their cardiovascular disease. Some got insulin or metformin instead of rosiglitazone.
And the results reported at the ADA meeting were from a post-trial analysis of the results from the BARI-2D trial, which was not designed to test the safety of rosiglitazone. Hence the drug was not randomly assigned. Reanalysis of studies designed to test something else are somewhat questionable.
So is rosiglitazone safe to take? The evidence is not clear-cut. The FDA will soon meet to discuss the safety issue, presumably taking into account other studies in addition to the three discussed here.
But these three studies are a good example of the slippery slope we have to deal with when results of large clinical trials are published: confused statistics, biased authors with ties to drug companies, and different patient groups, comparisons, and end points.
I wonder how many bad drugs are on the market because of confusing clinical studies. So too, I wonder how many good drugs might have been dropped from the pipeline because of equally confusing clinical studies.
Evaluating risks vs benefits is not simple, and the best choice for a large population is not always the best choice for an individual patient. You might be allergic to a drug that helps most patients. Conversely, a drug that harms most patients might be wonderful for you.
All this is one reason that controlling with good food and exercise should always be the first choice. But this isn't always enough. Then we and our physicians have to evaluate which drugs will work best for us.
It is not a simple task.
Monday, May 17, 2010
Stupid Fat Study
No this isn't about "stupid fats." It's a stupid study, in my opinion.
I try to give research scientists the benefit of the doubt, because I've done lab research myself, and I know how difficult it can be to get reliable results. It's even more complex today than it was when I was in graduate school.
Nevertheless, I think this study, reported in Science Daily, really takes the cake. The SD title is "High-Fat Meals a No-No for Asthma Patients, Researchers Find."
So what did the researchers do?
They fed two different meals to 40 people with asthma and measured any resulting inflammation. Diet 1 was 1000 calories, 52% fat, and consisted of fast-food burgers and hash brown potatoes. Diet 2 was 200 calories, 13% fat, and consisted of reduced-fat yogurt.
They found that people eating diet 1 had more inflammation. So they concluded that the inflammation was caused by fat!
How can you possibly assign blame when the diets differed in so many ways?
An equally valid headline might have been "High-calorie meals a no-no for asthma patients" or "Hash-brown potatoes a no-no for asthma patients" or "Dairy products good for asthma patients" or "Eating lots of fat in combination with lots of carbohyrate a no-no for asthma patients" or "Hamburger buns a no-no for asthma patients."
Instead, they focused on the one ingredient they probably started out believing would be bad and ignored the rest.
This study was presented at the American Thoracic Society 2o10 conference in New Orleans.
One of the researchers said, "This is the first study to show that a high fat meal increases airway inflammation." No it didn't. It showed that a high-fat, high-calorie, high-carbohydrate, commercial junk-food meal increased airway inflammation.
Unfortunately, headlines are all that many people read and remember. Keep in mind that headlines can be misleading. Before accepting the conclusions in any study you think might be important for you, read as much of the full text as you are able to and then make up your own mind.
We can't depend on other people to inform us correctly. We have to take control ourselves.
I try to give research scientists the benefit of the doubt, because I've done lab research myself, and I know how difficult it can be to get reliable results. It's even more complex today than it was when I was in graduate school.
Nevertheless, I think this study, reported in Science Daily, really takes the cake. The SD title is "High-Fat Meals a No-No for Asthma Patients, Researchers Find."
So what did the researchers do?
They fed two different meals to 40 people with asthma and measured any resulting inflammation. Diet 1 was 1000 calories, 52% fat, and consisted of fast-food burgers and hash brown potatoes. Diet 2 was 200 calories, 13% fat, and consisted of reduced-fat yogurt.
They found that people eating diet 1 had more inflammation. So they concluded that the inflammation was caused by fat!
How can you possibly assign blame when the diets differed in so many ways?
An equally valid headline might have been "High-calorie meals a no-no for asthma patients" or "Hash-brown potatoes a no-no for asthma patients" or "Dairy products good for asthma patients" or "Eating lots of fat in combination with lots of carbohyrate a no-no for asthma patients" or "Hamburger buns a no-no for asthma patients."
Instead, they focused on the one ingredient they probably started out believing would be bad and ignored the rest.
This study was presented at the American Thoracic Society 2o10 conference in New Orleans.
One of the researchers said, "This is the first study to show that a high fat meal increases airway inflammation." No it didn't. It showed that a high-fat, high-calorie, high-carbohydrate, commercial junk-food meal increased airway inflammation.
Unfortunately, headlines are all that many people read and remember. Keep in mind that headlines can be misleading. Before accepting the conclusions in any study you think might be important for you, read as much of the full text as you are able to and then make up your own mind.
We can't depend on other people to inform us correctly. We have to take control ourselves.
Friday, May 7, 2010
ACCORD again
A couple of years ago, it was reported that intensive treatment of type 2 diabetes, aiming for a hemoglobin A1c level below 6, increased cardiovascular events compared with patients aiming for an A1c between 7 and 7.9. The study was called ACCORD, and the glucose arm of the study was stopped early because of the excess deaths in the intensive-treatment group.
On the basis of this one study, a lot of doctors told their diabetes patients who had A1c values in the normal ranges that they were too low and they should attempt to get them higher!
They seemed to apply this advice to everyone with type 2, even though the patients in the ACCORD study were older (between 40 and 79 years), had had diabetes for a median of 10 years, and already had signs of heart disease or had several risk factors for heart disease.
I've previously discussed the ACCORD trial here, here, and here.
A conservative interpretation of the study was that aiming for a normal A1c might be harmful in older people with longstanding type 2 and pre-existing signs of or risk factors for cardiovascular disese but it would be OK for younger people who had recently been diagnosed. The idea was that if damage from high blood glucose levels has already been done, it may be too late to help by getting those levels down.
Another interpretation was that these people had been put on traditional high-carbohydrate American Diabetes Association diets, so they needed a lot of drugs to get their A1cs in normal ranges, and it was the combination of so many drugs that caused the increased cardiac events.
Another interpretation was that they'd brought the A1cs down too quickly, and that was what caused the harm.
And another was that the intensive-control group had more serious incidents of hypoglycemia.
Now comes a new interpretation of this study that says that those who were actually able to reach the normal A1c goals had lower rates of cardiovascular events. It was the patients who were unable to reach the goals despite the intensive treatment who had increased rates of cardiovascular events.
Mortality was greater in the intensive-treatment group only when the A1c was above 7.
The new interpretation was published in the May 2010 issue of Diabetes Care.
None of the mainstream analyses of the ACCORD study have suggested that instead of intensive treatment with drugs, patients might benefit by using lower-carb diets to get their A1c levels down. We know that works. Why can't the cardiologists understand it?
I think one thing the back-and-forth recommendations resulting from the ACCORD trial tell us is that we shouldn't forget to use common sense. If we're discussing treatment of a mentally compromised relative who is 99 and unable to understand why he shouldn't eat huge dishes of ice cream and chocolate sauce, perhaps trying to enforce a low-carb diet so the poor man would have no enjoyment in life wouldn't make sense.
One vision that haunts me is the description of an old diabetic woman in a nursing home. Everyone else got ice cream for dessert, and the nurses said, "You can't have ice cream because you are diabetic." The old woman cried all during dessert because she wanted the ice cream so much. That's cruel. Especially because they were probably stuffing her with starches like bread and potatoes.
But if we're still pretty healthy and able to manage our diabetes diet ourselves, and if we understand how harmful high blood glucose levels can be, we should make an effort to get the best A1c levels we can manage, even if some study shows that this might be harmful to some people.
We shouldn't reverse our treatment plan on the basis of one study, which is what the doctors who told all their type 2 patients to get their A1cs higher did. One study doesn't prove much. The study might have been poorly designed. The population studied might not be representative of the population as a whole, or it might not match your own situation (a study of 80-year-old male veterans might not apply to a 40-year old woman). The statistics used might have been faulty. The treatment in the study might have been different from what you are using.
There are many reasons that one study might be misleading. It's only consistent results that are significant. We shouldn't totally ignore any study. But we need to take them with a grain of salt.
On the basis of this one study, a lot of doctors told their diabetes patients who had A1c values in the normal ranges that they were too low and they should attempt to get them higher!
They seemed to apply this advice to everyone with type 2, even though the patients in the ACCORD study were older (between 40 and 79 years), had had diabetes for a median of 10 years, and already had signs of heart disease or had several risk factors for heart disease.
I've previously discussed the ACCORD trial here, here, and here.
A conservative interpretation of the study was that aiming for a normal A1c might be harmful in older people with longstanding type 2 and pre-existing signs of or risk factors for cardiovascular disese but it would be OK for younger people who had recently been diagnosed. The idea was that if damage from high blood glucose levels has already been done, it may be too late to help by getting those levels down.
Another interpretation was that these people had been put on traditional high-carbohydrate American Diabetes Association diets, so they needed a lot of drugs to get their A1cs in normal ranges, and it was the combination of so many drugs that caused the increased cardiac events.
Another interpretation was that they'd brought the A1cs down too quickly, and that was what caused the harm.
And another was that the intensive-control group had more serious incidents of hypoglycemia.
Now comes a new interpretation of this study that says that those who were actually able to reach the normal A1c goals had lower rates of cardiovascular events. It was the patients who were unable to reach the goals despite the intensive treatment who had increased rates of cardiovascular events.
Mortality was greater in the intensive-treatment group only when the A1c was above 7.
The new interpretation was published in the May 2010 issue of Diabetes Care.
None of the mainstream analyses of the ACCORD study have suggested that instead of intensive treatment with drugs, patients might benefit by using lower-carb diets to get their A1c levels down. We know that works. Why can't the cardiologists understand it?
I think one thing the back-and-forth recommendations resulting from the ACCORD trial tell us is that we shouldn't forget to use common sense. If we're discussing treatment of a mentally compromised relative who is 99 and unable to understand why he shouldn't eat huge dishes of ice cream and chocolate sauce, perhaps trying to enforce a low-carb diet so the poor man would have no enjoyment in life wouldn't make sense.
One vision that haunts me is the description of an old diabetic woman in a nursing home. Everyone else got ice cream for dessert, and the nurses said, "You can't have ice cream because you are diabetic." The old woman cried all during dessert because she wanted the ice cream so much. That's cruel. Especially because they were probably stuffing her with starches like bread and potatoes.
But if we're still pretty healthy and able to manage our diabetes diet ourselves, and if we understand how harmful high blood glucose levels can be, we should make an effort to get the best A1c levels we can manage, even if some study shows that this might be harmful to some people.
We shouldn't reverse our treatment plan on the basis of one study, which is what the doctors who told all their type 2 patients to get their A1cs higher did. One study doesn't prove much. The study might have been poorly designed. The population studied might not be representative of the population as a whole, or it might not match your own situation (a study of 80-year-old male veterans might not apply to a 40-year old woman). The statistics used might have been faulty. The treatment in the study might have been different from what you are using.
There are many reasons that one study might be misleading. It's only consistent results that are significant. We shouldn't totally ignore any study. But we need to take them with a grain of salt.
Sunday, May 2, 2010
Saturated Fat and the Popular Press
The May issue of the mainstream magazine Scientific American had an article saying that dietary carbohydrates are more important than fats in terms of heart disease risk.
Wow!
Many people thought the news would never reach the mainstream press. But it finally has. The article cites the recent meta-analysis by Krauss and colleagues that suggested that the amount of saturated fat in the diet is not related to heart disease.
I would note several caveats. First, although some of the studies in the meta-analysis used food diaries to assess intake, others used the ubiquitous "food frequency questionnaires," which may not be accurate, as discussed here.
Second, Krauss et al. suggested that the effect of saturated fat may depend on what people substitute for the saturated fat. (This assumes that no one would want to decrease calories by simply eating less saturated fat, which is what makes the most sense to me.) Eating more unsaturated fat may decrease heart disease rates, whereas eating more carbohydrates may increase heart disease rates. Not everyone agrees with this, however.
Finally, the Scientific American article says it's mostly highly processed carbohydrates that are the villains, and the author writes, "some high-fiber carbohydrates are unquestionably good for the body." Many people do, in fact, question that statement, especially in relation to people with diabetes.
The author of the Scientific American article is not urging people to pig out on saturated fats. She says that current studies "do not suggest that saturated fats are not so bad; they indicate that carbohydrates could be worse."
It takes a long time for generally accepted ideas to be thrown out. Further studies may convince people that the "healthy whole grains" that people (including those with diabetes) are currently being urged to make the focus of their diets are just as bad as white bread, pasta, and sodas.
But for now, every little nail hammered into the brittle saturated fat hypothesis of heart disease helps. Saying that high-glycemic-index carbohydrates may increase heart disease risk is a step toward accepting the idea that all carbohydrates may do the same, especially in people with a genetic propensity to insulin resistance.
Publicizing the evidence in a mainstream popular magazine will help to spread the news, because the popular press operates with a herd mentality. If one mainstream news outlet carries a story, everyone else has to report on it too.
In fact, just today I got in the mail a copy of the Harvard Medical School Focus, which included a brief comment titled "For Heart Health: More Polyunsaturated Fat, Fewer Refined Carbohydrates." This discusses both the Krauss paper cited above and another paper that supports the idea that substituting polyunsaturated fat for saturated fat instead of carbohydrate will reduce heart disease risks.
Perhaps the brittle saturated fat hypothesis of heart disease it will soon be shattered.
Wow!
Many people thought the news would never reach the mainstream press. But it finally has. The article cites the recent meta-analysis by Krauss and colleagues that suggested that the amount of saturated fat in the diet is not related to heart disease.
I would note several caveats. First, although some of the studies in the meta-analysis used food diaries to assess intake, others used the ubiquitous "food frequency questionnaires," which may not be accurate, as discussed here.
Second, Krauss et al. suggested that the effect of saturated fat may depend on what people substitute for the saturated fat. (This assumes that no one would want to decrease calories by simply eating less saturated fat, which is what makes the most sense to me.) Eating more unsaturated fat may decrease heart disease rates, whereas eating more carbohydrates may increase heart disease rates. Not everyone agrees with this, however.
Finally, the Scientific American article says it's mostly highly processed carbohydrates that are the villains, and the author writes, "some high-fiber carbohydrates are unquestionably good for the body." Many people do, in fact, question that statement, especially in relation to people with diabetes.
The author of the Scientific American article is not urging people to pig out on saturated fats. She says that current studies "do not suggest that saturated fats are not so bad; they indicate that carbohydrates could be worse."
It takes a long time for generally accepted ideas to be thrown out. Further studies may convince people that the "healthy whole grains" that people (including those with diabetes) are currently being urged to make the focus of their diets are just as bad as white bread, pasta, and sodas.
But for now, every little nail hammered into the brittle saturated fat hypothesis of heart disease helps. Saying that high-glycemic-index carbohydrates may increase heart disease risk is a step toward accepting the idea that all carbohydrates may do the same, especially in people with a genetic propensity to insulin resistance.
Publicizing the evidence in a mainstream popular magazine will help to spread the news, because the popular press operates with a herd mentality. If one mainstream news outlet carries a story, everyone else has to report on it too.
In fact, just today I got in the mail a copy of the Harvard Medical School Focus, which included a brief comment titled "For Heart Health: More Polyunsaturated Fat, Fewer Refined Carbohydrates." This discusses both the Krauss paper cited above and another paper that supports the idea that substituting polyunsaturated fat for saturated fat instead of carbohydrate will reduce heart disease risks.
Perhaps the brittle saturated fat hypothesis of heart disease it will soon be shattered.
Saturday, April 3, 2010
Is Dieting a Sport?
One thing that annoys me (well, OK, a lot of things annoy me; I'm becoming a curmudgeon) is when people approach dieting like a team sport.
You pick your favorite diet, and then you defend that diet come heck or high water. When a scientific paper supporting your diet choice is published, you crow. When a scientific paper supporting some other diet is published, you ignore it.
A couple of recent papers concerning the impact of saturated fat on heart disease illustrate this unscientific approach by some people in the science-discussing community.
In January, a study titled Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease was published online ahead of print publication. The study concluded that "there is no significant evidence for concluding that dietary saturated fat is associated with an increased risk of CHD or CVD."
The study was pretty much ignored by the mainstream science press, which tends to support the official American Heart Association low-fat approach to heart health. The New York Times didn't mention it. The various popular science summary services like Science Daily and EurekAlert also didn't report on it.
As diabetes blogger David Mendosa wrote, "I couldn't find any mainstream articles about it today. Not one of the four sources that I rely on heavily for leads to new studies has carried a word about this one."
But response in the low-carb community was immediate. People on low-carb diets tend to eat a lot of fat, often including a lot of saturated fat. Blog after blog reported on this study, and some of the bloggers made fun of the "low fatters" and patted each other on the back for following the "correct" diet.
More recently, another paper, titled Effects on Coronary Heart Disease of Increasing Polyunsaturated Fat in Place of Saturated Fat: A Systematic Review and Meta-Analysis of Randomized Controlled Trials was published online. This paper concluded that replacing saturated fat with unsaturated fat could reduce the risk of having a coronary heart disease "event" almost 20%.
This study was picked up by the science reporting services like Science Daily, but to date, I haven't seen a single one of the sites or blogs that publicized the "no effect of saturated fat" study mention this other study, and I've been looking.
To be fair, I get the URLs of some lipid blogs from the links in other blogs, and because people tend to link to blogs that agree with them, they do tend to read each other's posts and come to similar conclusions. But I find this business of ignoring the studies you don't agree with sad.
This isn't science. This is religion, or politics . . . or sports. When I was a child, I was a big supporter of the Washington Senators, the team that ended up in the basement year after year. The big excitement was whether they'd end up last, as usual, or perhaps claw their way up to next-to-last. So I know what it's like to root for a loser. You grasp at straws.
For example, Dean Ornish, who advocates an extremely low fat diet to prevent heart disease, was once asked about the fact that when your fat intake is low, your HDL cholesterol, the "good" cholesterol, goes down as well as your LDL, the "bad" cholesterol, so the ratio remains the same or even gets worse.
He said well, maybe when you're not eating fat, you don't need HDL.
But finding the best diet for people with diabetes shouldn't be pursued like this. We need to look at all the evidence, whether it supports our preconceived notions or not.
In fact, these two studies are not that far apart in their conclusions. What the first study said was that there was no significant evidence for linking saturated fat with heart disease. But they hinted at the results of the second study: "More data are needed to elucidate whether CVD risks are likely to be influenced by the specific nutrients used to replace saturated fat."
And the second study concluded that yes, it does matter what you replace the saturated fat with. Replace it with carbohydrate, and people's risk goes up. Replace it with unsaturated fat, and people's risk goes down.
Both studies were meta-analyses, and like many people, I'm not a big fan of meta-analyses, as I discussed here. Nevertheless, they hint at possible relationships.
And I don't think we should sit around throwing darts and this study or that study and maintaining the ideas we've had for decades. What we need to do is to look at all the evidence and try to interpret it in the best way we can given today's scientific and statistical tools. We need to try to find out why different studies seem to give different results and figure out how we can apply those findings to individual patients.
When I was in graduate school, forced to read a little in the history of biology, one thing that struck me was that often when there were two different schools of thought on some topic, it turned out they were both wrong. The answer turned out to be something else, which they couldn't have known because the technology for testing for that thing had not yet been developed.
So it's possible that a similar thing applies to research on dietary fats. Maybe it's not the saturation/unsaturation of the fats that is important but how fresh they are. Maybe it's the degree to which the fats are oxidized, or glycated because of high blood glucose, or modified in some other way that makes the most difference in heart disease.
Maybe the type of fat depends on what you're doing with that fat. Unsaturated fats, expecially the omega-3 fats found in fish, are easily oxidized when warm. This is what causes the "fishy" smell when fish sit around before you cook them. Using fish oil for frying would be a bad idea. The best fats for frying are the saturated fats. But most studies don't ask about how the various fats were used, or how fresh they were.
Maybe we can tolerate any kind of fat when it's not modified by food additives or the many chemical pollutants in our environment. Even organic food and bottled water are not free from contaminants, especially when the water is bottled in plastic.
Maybe we can tolerate almost any kind of fat in limited quantities, but when we overwhelm our metabolism with huge amounts of any kind of fat we'll see our heart health decline.
If it turns out that any type of food does, indeed, affect heart disease, we need to study why that food has that effect. We need to determine if it's eating any of the suspect food or eating a tremendous amount of that food that is important.
We need to abandon more studies designed to prove some preconceived notion (fat is bad, or fat is good) and instead encourage studies that show why different studies appear to give different results. Was it study design? Poor use of statistics? Poor choice of patient populations? Poor choice of endpoints?
You can look at short-term effects or long-term effects. You can lump together all cardiovascular events, including mortality, or you can study only mortality, or you can separate strokes from heart attacks, or you can try to study them all. In the latter case you need gargantuan overall sample sizes to have statistical significance in all the groups. And that means very expensive studies, especially if it's a long-term study.
You can study saturated fat from meat, butter, chicken, and coconut oil or you can study saturated fat from fast-food burgers, luncheon meats, hot dogs, french fries, potato chips, and southern fried chicken. The latter sources are apt to be associated with other behaviors such as eating a lot of processed convenience foods and drinking lots of sodas. So is it the effect of saturated fat that you're measuring or an overall unhealthy eating pattern?
So until we find the best possible diet, what do I think is the best diet for both preventing heart disease and controlling diabetes?
A l0w-carb diet. I've been following a low-carb diet for about 14 years.
But if you start out on a "standard American diet" that is high in both carbs and fats, I think the best approach is to drastically reduce the carbs and not replace them with anything. This way, your percentage of fat will increase; a typical low-carb diet includes about 60% fat. But your calories will go down.
In fact, studies have shown that when most people switch from a typical American diet to a low-carb diet, they reduce calories without thinking about it. This is because a low-carb diet tends to reduce hunger, so you don't want as much food.
Simply losing weight (not that the process itself is simple) improves blood pressure and blood glucose levels in most people. So if you reduce the carbs and don't replace them with a lot of other calories, you're apt to lose weight.
If not replacing the carbs with anything means that you're hungry, you can eat a little extra protein. Or even have a little extra fat. Just don't make a big effort to replace those 1000 calories a day you were eating in the form of bread, mashed potatoes, and doughnuts with something else.
I don't know why, when the press keeps blathering about the "obesity epidemic" the nutrition researchers hone in on replacing fat calories with something else. Do they want to keep people fat?
Come on, people. Let's stop bickering and use our brains and figure out how to make us all as healthy as we can be.
You pick your favorite diet, and then you defend that diet come heck or high water. When a scientific paper supporting your diet choice is published, you crow. When a scientific paper supporting some other diet is published, you ignore it.
A couple of recent papers concerning the impact of saturated fat on heart disease illustrate this unscientific approach by some people in the science-discussing community.
In January, a study titled Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease was published online ahead of print publication. The study concluded that "there is no significant evidence for concluding that dietary saturated fat is associated with an increased risk of CHD or CVD."
The study was pretty much ignored by the mainstream science press, which tends to support the official American Heart Association low-fat approach to heart health. The New York Times didn't mention it. The various popular science summary services like Science Daily and EurekAlert also didn't report on it.
As diabetes blogger David Mendosa wrote, "I couldn't find any mainstream articles about it today. Not one of the four sources that I rely on heavily for leads to new studies has carried a word about this one."
But response in the low-carb community was immediate. People on low-carb diets tend to eat a lot of fat, often including a lot of saturated fat. Blog after blog reported on this study, and some of the bloggers made fun of the "low fatters" and patted each other on the back for following the "correct" diet.
More recently, another paper, titled Effects on Coronary Heart Disease of Increasing Polyunsaturated Fat in Place of Saturated Fat: A Systematic Review and Meta-Analysis of Randomized Controlled Trials was published online. This paper concluded that replacing saturated fat with unsaturated fat could reduce the risk of having a coronary heart disease "event" almost 20%.
This study was picked up by the science reporting services like Science Daily, but to date, I haven't seen a single one of the sites or blogs that publicized the "no effect of saturated fat" study mention this other study, and I've been looking.
To be fair, I get the URLs of some lipid blogs from the links in other blogs, and because people tend to link to blogs that agree with them, they do tend to read each other's posts and come to similar conclusions. But I find this business of ignoring the studies you don't agree with sad.
This isn't science. This is religion, or politics . . . or sports. When I was a child, I was a big supporter of the Washington Senators, the team that ended up in the basement year after year. The big excitement was whether they'd end up last, as usual, or perhaps claw their way up to next-to-last. So I know what it's like to root for a loser. You grasp at straws.
For example, Dean Ornish, who advocates an extremely low fat diet to prevent heart disease, was once asked about the fact that when your fat intake is low, your HDL cholesterol, the "good" cholesterol, goes down as well as your LDL, the "bad" cholesterol, so the ratio remains the same or even gets worse.
He said well, maybe when you're not eating fat, you don't need HDL.
But finding the best diet for people with diabetes shouldn't be pursued like this. We need to look at all the evidence, whether it supports our preconceived notions or not.
In fact, these two studies are not that far apart in their conclusions. What the first study said was that there was no significant evidence for linking saturated fat with heart disease. But they hinted at the results of the second study: "More data are needed to elucidate whether CVD risks are likely to be influenced by the specific nutrients used to replace saturated fat."
And the second study concluded that yes, it does matter what you replace the saturated fat with. Replace it with carbohydrate, and people's risk goes up. Replace it with unsaturated fat, and people's risk goes down.
Both studies were meta-analyses, and like many people, I'm not a big fan of meta-analyses, as I discussed here. Nevertheless, they hint at possible relationships.
And I don't think we should sit around throwing darts and this study or that study and maintaining the ideas we've had for decades. What we need to do is to look at all the evidence and try to interpret it in the best way we can given today's scientific and statistical tools. We need to try to find out why different studies seem to give different results and figure out how we can apply those findings to individual patients.
When I was in graduate school, forced to read a little in the history of biology, one thing that struck me was that often when there were two different schools of thought on some topic, it turned out they were both wrong. The answer turned out to be something else, which they couldn't have known because the technology for testing for that thing had not yet been developed.
So it's possible that a similar thing applies to research on dietary fats. Maybe it's not the saturation/unsaturation of the fats that is important but how fresh they are. Maybe it's the degree to which the fats are oxidized, or glycated because of high blood glucose, or modified in some other way that makes the most difference in heart disease.
Maybe the type of fat depends on what you're doing with that fat. Unsaturated fats, expecially the omega-3 fats found in fish, are easily oxidized when warm. This is what causes the "fishy" smell when fish sit around before you cook them. Using fish oil for frying would be a bad idea. The best fats for frying are the saturated fats. But most studies don't ask about how the various fats were used, or how fresh they were.
Maybe we can tolerate any kind of fat when it's not modified by food additives or the many chemical pollutants in our environment. Even organic food and bottled water are not free from contaminants, especially when the water is bottled in plastic.
Maybe we can tolerate almost any kind of fat in limited quantities, but when we overwhelm our metabolism with huge amounts of any kind of fat we'll see our heart health decline.
If it turns out that any type of food does, indeed, affect heart disease, we need to study why that food has that effect. We need to determine if it's eating any of the suspect food or eating a tremendous amount of that food that is important.
We need to abandon more studies designed to prove some preconceived notion (fat is bad, or fat is good) and instead encourage studies that show why different studies appear to give different results. Was it study design? Poor use of statistics? Poor choice of patient populations? Poor choice of endpoints?
You can look at short-term effects or long-term effects. You can lump together all cardiovascular events, including mortality, or you can study only mortality, or you can separate strokes from heart attacks, or you can try to study them all. In the latter case you need gargantuan overall sample sizes to have statistical significance in all the groups. And that means very expensive studies, especially if it's a long-term study.
You can study saturated fat from meat, butter, chicken, and coconut oil or you can study saturated fat from fast-food burgers, luncheon meats, hot dogs, french fries, potato chips, and southern fried chicken. The latter sources are apt to be associated with other behaviors such as eating a lot of processed convenience foods and drinking lots of sodas. So is it the effect of saturated fat that you're measuring or an overall unhealthy eating pattern?
So until we find the best possible diet, what do I think is the best diet for both preventing heart disease and controlling diabetes?
A l0w-carb diet. I've been following a low-carb diet for about 14 years.
But if you start out on a "standard American diet" that is high in both carbs and fats, I think the best approach is to drastically reduce the carbs and not replace them with anything. This way, your percentage of fat will increase; a typical low-carb diet includes about 60% fat. But your calories will go down.
In fact, studies have shown that when most people switch from a typical American diet to a low-carb diet, they reduce calories without thinking about it. This is because a low-carb diet tends to reduce hunger, so you don't want as much food.
Simply losing weight (not that the process itself is simple) improves blood pressure and blood glucose levels in most people. So if you reduce the carbs and don't replace them with a lot of other calories, you're apt to lose weight.
If not replacing the carbs with anything means that you're hungry, you can eat a little extra protein. Or even have a little extra fat. Just don't make a big effort to replace those 1000 calories a day you were eating in the form of bread, mashed potatoes, and doughnuts with something else.
I don't know why, when the press keeps blathering about the "obesity epidemic" the nutrition researchers hone in on replacing fat calories with something else. Do they want to keep people fat?
Come on, people. Let's stop bickering and use our brains and figure out how to make us all as healthy as we can be.
Monday, March 15, 2010
ADVANCE and NAVIGATOR
The Internet is abuzz with the latest results from a couple of those massive trials that physicians who practice "evidence-based medicine" require before they'll believe in any treatment.
Although I understand why such studies are needed, I hate them, because they're studying a huge, diverse population of patients who may differ a lot in their baseline characteristics, even though the mean is usually all you can see.
Unless the outcome is black and white, for example, 100% of the patients who took the new drug dropped dead within 2 weeks, you need statistics to evaluate the study. Quite often, individual patients may be harmed or helped, but the published conclusion refers only to the average impact, as I noted here. Then physicians apply these average results to everyone.
A good example of this is the blood glucose (BG) arm of the ACCORD study, which was stopped early a couple of years ago because it appeared that the patients who used intensive treatment with a lot of drugs and lowered their A1cs to a mean of 6.5% had higher mortality than those who used standard treatment and had A1cs of about 7.3%.
This was despite the fact that patients in both groups had mortality rates lower than those of most people with diabetes.
In fact, the patients in the ACCORD study were older, had had type 2 for at least 10 years, had other risk factors for heart disease, and started with mean A1cs of 8.3. This means they had probably had poor control for years. Yet doctors are applying the conclusions to everyone.
Many patients are now reporting that their doctors tell them that their excellent A1c levels in the 5s are too low and they should increase them until they're over 7!
Furthermore, like most patients, the ACCORD patients were told to follow an ADA-type diet with less than 30% total fat and less than 10% saturated fat. This means they undoubtedly increased their consumption of carbohydrates, most likely the kind most Americans eat: potatoes, rice, white bread, processed fat-free foods. Yet a recent meta-analysis showed that there is no significant evidence to conclude that saturated fat causes heart disease. Some studies showed an increase when saturated fat was reduced, and others showed an increase. This averaged out to no effect.
The authors suggested that it might depend on what you substitute for the saturated fat, as studies with substitution of unsaturated fat tended to reduce heart disease and mortality and studies with substitution of carbohydrate tended to increase it, although no studies have been done that would actually prove this.
Yet replacing saturated fat with carbohydrate is undoubtedly what people in ACCORD were told to do, and those in the intensive treatment arm of the study got more intensive nutritional counseling and hence probably ate more carbohydrate.
Now the other two arms of the ACCORD study have been published. The blood pressure arm showed that reducing the systolic blood pressure below 120 resulted in no better cardiovascular outcomes than using fewer drugs to keep the systolic blood pressure below 140. The lower blood pressures did result in fewer strokes.
This is the same patient population as the BG arm of the study, and the same caveats apply: longstanding diabetes in an elderly population with coexisting medical problems (34% had already had a cardiovascular event), relatively high starting A1cs and fasting BG levels over 170, and multiple blood pressure drugs given to reach the goal. Also, twice as many of the intensively treated patients gained more than 10 kg during the study.
The final arm of the study was designed to see whether adding a fibrate drug to the treatment of patients already taking a statin would reduce cardiovascular events. The fibrates (they used fenofibrate) reduce triglycerides and increase HDL levels.
Again, they found no significant effect but a suggestion that the drug might help in patients who began with triglyceride levels over 204 and HDL levels under 34. Men appeared to do better and women appeared to do worse on the fibrate. Such studies can show differences that appear to be real but aren't statistically significant.
Again: same population and same caveats.
Another study, the NAVIGATOR study, was reported at the same time. This study started with patients who had prediabetes, with mean A1cs of 5.8 and also either preexisting heart disease or cardiovascular risk factors. They tested whether using valsartan (Diovan), an angiotensin-receptor inhibitor that lowers blood pressure, would reduce progression from prediabetes to diabetes. Similar drugs had been shown in the past to do so.
Again, all the patients were given "lifestyle modification" advice, although the papers don't specify exactly what that was other than the usual ADA line of reducing total and saturated fat and increasing exercise. You have to go to an Appendix, which most people won't read, and then to a reference to a Finnish study they cite to see what type of dietary advice was given.
It turns out to be the usual low fat with "lots of whole grains, fruits and vegetable." Many Americans told to eat lots of whole grains are apt to eat whole-wheat bread (which isn't whole grain) and to drink more orange juice and eat more apples and bananas, and maybe more peas and corn. Very few will up their intake of kale and broccoli and other low-carb veggies.
It turned out that the low-fat high-carb diet plus increased exercise plus the drug reduced the progression to type 2 diabetes from 36.8% to 33.1%, which they calculate is a 13% reduction in the "absolute hazard difference using an exponential model," but a pretty small absolute reduction. It didn't affect the rate of cardiovascular events.
The second arm of the NAVIGATOR trial involved the same patient population and the drug nateglinide (Starlix), which is a sulfonylurea-type drug that increases insulin secretion by the beta cells but for a shorter period than the traditional sulfs.
The rationale was that high postprandial BG levels are said to lead to beta cell deterioration, and higher A1cs are associated with increased heart disease. They tested whether or not this drug would reduce progression from prediabetes to diabetes and whether it would affect cardiovascular events.
They found it did neither.
Do these studies mean there's no point in trying to control our diabetes?
Not at all. What they really show is that you can't give people with longstanding diabetes or even a diabetic tendency and either preexisting heart disease or a lot of heart disease risk factors a low fat, and hence very high carbohydrate, diet, try to control the resulting high BG levels with a lot of drugs, and expect the heart disease to go away.
Furthermore, even though you tell people to eat lots of vegetables and whole grains, you know that in the general population, most of them -- if they modify their diet at all -- will eat high-glycemic foods, low-fat processed convenience foods, and sugary fruits. If they show the dietician that their fat consumption is down, the dietician will probably tell them they're doing great.
No one has tested whether or not trying to control diabetes with lower-carb diets and fewer drugs would reduce heart disease rates.
But I'm afraid that the results of these trials will make a lot of people simply throw up their hands and give up, figuring that heart attacks are inevitable, no matter what they do.
Even if the results from a lower-carb study showed fewer cardiovascular events, I'm afraid most Americans wouldn't make significant changes in their diets. An intelligent woman with type 2 once told me she had trouble eating just a couple of potato chips. I asked why she bought potato chips (she lived alone). She said, "Because I like potato chips."
Well, who doesn't. I also used to like blueberry pie (I probably wouldn't like it now, because it would seem overwhelmingly sweet with relatively little taste) and homemade bread slathered with butter and homemade jam. But I don't eat those things now.
What we need to learn to do is to become gourmets, seeking out foods with a lot of taste and not a lot of carbohydrate, like berries, or exotic fresh vegetables from a farmers market. This is a lot more fun and cheaper than paying $500 a month for a lot of pills to try to cover the damage from eating ho-hum potato chips and packaged snack cakes.
The intelligent people who read this blog will understand this. I worry about the other millions of people in the country who don't have access to good information. I worry about the overworked GPs who don't have time to slog through long statistical studies and try to figure out what an "absolute hazard difference using an exponential model" is.
Many of the details, like the actual dietary advice, in these papers are difficult, if not impossible, to find. If you make an effort to download the full study protocol of the ACCORD study, you find that patients were taught carb counting but it doesn't say how many carbs they were supposed to eat. They were taught self-monitoring of BG, and how to titrate their drugs according to the results. They were apparently not taught how to "titrate" their carb consumption according to the results.
And the authors are often sloppy. For example, sometimes they give both mean and median A1c. Sometimes they give only one. Sometimes they don't indicate which one they calculated.
I worry that the busy physicians will just read the headlines in medical magazines and the New York Times ("Diabetes Heart Treatments May Cause Harm") and conclude that they shouldn't try to treat diabetic patients with high blood pressure, high BG levels, or high lipid levels. Why bother, because they might be sued if they caused harm.
As studies become old, people who write about them tend to simplify, ignoring the many caveats that apply to the studies. For example, Gina Kolata wrote in the recent New York Times story, "It was discovered 2 years ago that rigorously controlling blood sugar did not prevent heart disease or deaths in people with type 2 diabetes." What that study actually showed was that "rigorously controlling blood sugar with a lot of drugs to cover a high-carb diet did not prevent heart disease or death in elderly patients with preexisting heart disease or at least two cardiovascular risk factors and long-standing poorly controlled diabetes."
But how many physicians have retained Kolata's interpretation? I suspect a lot. I've mentioned the many patients whose doctors told them that their diet-controlled A1cs of 5.6 were too low and they should try to get them up to 7!
I would agree that if someone had an A1c of 5.6 only because they were on 7 different expensive medications with a lot of potential side effects, it would make sense to stop several of the drugs and let the A1c go up a bit, especially if the patient was elderly with several other medical problems treated with even more drugs.
But if someone has an A1c of 4.8 because of strict diet control and a lot of exercise, and if that person doesn't go low (after all, nondiabetics don't go low when they have low A1cs), there's absolutely no reason to tell that person to increase the A1c.
Applying a "rule" for the wrong reasons is the type of faulty logic that has caused harm in a lot of diabetic patients. I know some who have been told by registered dieticians that they should put raisins in their oatmeal "to get the carb counts up."
The reason for the high-carb ADA diet is not to eat a lot of carbohydrate; it's to eat less fat. The idea is that when you eat more carbohydrate, you'll eat less fat. But adding carbohydrate to a meal instead of substituting carbohydrate for fat won't reach the ADA goals (which many people today don't agree with anyway). It will just add calories, increase insulin levels, and promote even more fat gain.
So will patients with type 2 diabetes soon be told to get their blood pressure up, not worry about lipid levels, and pay no attention to postprandial BG levels?
I certainly hope not.
The full texts of the New England Journal of Medicine articles cited are available free here.
Although I understand why such studies are needed, I hate them, because they're studying a huge, diverse population of patients who may differ a lot in their baseline characteristics, even though the mean is usually all you can see.
Unless the outcome is black and white, for example, 100% of the patients who took the new drug dropped dead within 2 weeks, you need statistics to evaluate the study. Quite often, individual patients may be harmed or helped, but the published conclusion refers only to the average impact, as I noted here. Then physicians apply these average results to everyone.
A good example of this is the blood glucose (BG) arm of the ACCORD study, which was stopped early a couple of years ago because it appeared that the patients who used intensive treatment with a lot of drugs and lowered their A1cs to a mean of 6.5% had higher mortality than those who used standard treatment and had A1cs of about 7.3%.
This was despite the fact that patients in both groups had mortality rates lower than those of most people with diabetes.
In fact, the patients in the ACCORD study were older, had had type 2 for at least 10 years, had other risk factors for heart disease, and started with mean A1cs of 8.3. This means they had probably had poor control for years. Yet doctors are applying the conclusions to everyone.
Many patients are now reporting that their doctors tell them that their excellent A1c levels in the 5s are too low and they should increase them until they're over 7!
Furthermore, like most patients, the ACCORD patients were told to follow an ADA-type diet with less than 30% total fat and less than 10% saturated fat. This means they undoubtedly increased their consumption of carbohydrates, most likely the kind most Americans eat: potatoes, rice, white bread, processed fat-free foods. Yet a recent meta-analysis showed that there is no significant evidence to conclude that saturated fat causes heart disease. Some studies showed an increase when saturated fat was reduced, and others showed an increase. This averaged out to no effect.
The authors suggested that it might depend on what you substitute for the saturated fat, as studies with substitution of unsaturated fat tended to reduce heart disease and mortality and studies with substitution of carbohydrate tended to increase it, although no studies have been done that would actually prove this.
Yet replacing saturated fat with carbohydrate is undoubtedly what people in ACCORD were told to do, and those in the intensive treatment arm of the study got more intensive nutritional counseling and hence probably ate more carbohydrate.
Now the other two arms of the ACCORD study have been published. The blood pressure arm showed that reducing the systolic blood pressure below 120 resulted in no better cardiovascular outcomes than using fewer drugs to keep the systolic blood pressure below 140. The lower blood pressures did result in fewer strokes.
This is the same patient population as the BG arm of the study, and the same caveats apply: longstanding diabetes in an elderly population with coexisting medical problems (34% had already had a cardiovascular event), relatively high starting A1cs and fasting BG levels over 170, and multiple blood pressure drugs given to reach the goal. Also, twice as many of the intensively treated patients gained more than 10 kg during the study.
The final arm of the study was designed to see whether adding a fibrate drug to the treatment of patients already taking a statin would reduce cardiovascular events. The fibrates (they used fenofibrate) reduce triglycerides and increase HDL levels.
Again, they found no significant effect but a suggestion that the drug might help in patients who began with triglyceride levels over 204 and HDL levels under 34. Men appeared to do better and women appeared to do worse on the fibrate. Such studies can show differences that appear to be real but aren't statistically significant.
Again: same population and same caveats.
Another study, the NAVIGATOR study, was reported at the same time. This study started with patients who had prediabetes, with mean A1cs of 5.8 and also either preexisting heart disease or cardiovascular risk factors. They tested whether using valsartan (Diovan), an angiotensin-receptor inhibitor that lowers blood pressure, would reduce progression from prediabetes to diabetes. Similar drugs had been shown in the past to do so.
Again, all the patients were given "lifestyle modification" advice, although the papers don't specify exactly what that was other than the usual ADA line of reducing total and saturated fat and increasing exercise. You have to go to an Appendix, which most people won't read, and then to a reference to a Finnish study they cite to see what type of dietary advice was given.
It turns out to be the usual low fat with "lots of whole grains, fruits and vegetable." Many Americans told to eat lots of whole grains are apt to eat whole-wheat bread (which isn't whole grain) and to drink more orange juice and eat more apples and bananas, and maybe more peas and corn. Very few will up their intake of kale and broccoli and other low-carb veggies.
It turned out that the low-fat high-carb diet plus increased exercise plus the drug reduced the progression to type 2 diabetes from 36.8% to 33.1%, which they calculate is a 13% reduction in the "absolute hazard difference using an exponential model," but a pretty small absolute reduction. It didn't affect the rate of cardiovascular events.
The second arm of the NAVIGATOR trial involved the same patient population and the drug nateglinide (Starlix), which is a sulfonylurea-type drug that increases insulin secretion by the beta cells but for a shorter period than the traditional sulfs.
The rationale was that high postprandial BG levels are said to lead to beta cell deterioration, and higher A1cs are associated with increased heart disease. They tested whether or not this drug would reduce progression from prediabetes to diabetes and whether it would affect cardiovascular events.
They found it did neither.
Do these studies mean there's no point in trying to control our diabetes?
Not at all. What they really show is that you can't give people with longstanding diabetes or even a diabetic tendency and either preexisting heart disease or a lot of heart disease risk factors a low fat, and hence very high carbohydrate, diet, try to control the resulting high BG levels with a lot of drugs, and expect the heart disease to go away.
Furthermore, even though you tell people to eat lots of vegetables and whole grains, you know that in the general population, most of them -- if they modify their diet at all -- will eat high-glycemic foods, low-fat processed convenience foods, and sugary fruits. If they show the dietician that their fat consumption is down, the dietician will probably tell them they're doing great.
No one has tested whether or not trying to control diabetes with lower-carb diets and fewer drugs would reduce heart disease rates.
But I'm afraid that the results of these trials will make a lot of people simply throw up their hands and give up, figuring that heart attacks are inevitable, no matter what they do.
Even if the results from a lower-carb study showed fewer cardiovascular events, I'm afraid most Americans wouldn't make significant changes in their diets. An intelligent woman with type 2 once told me she had trouble eating just a couple of potato chips. I asked why she bought potato chips (she lived alone). She said, "Because I like potato chips."
Well, who doesn't. I also used to like blueberry pie (I probably wouldn't like it now, because it would seem overwhelmingly sweet with relatively little taste) and homemade bread slathered with butter and homemade jam. But I don't eat those things now.
What we need to learn to do is to become gourmets, seeking out foods with a lot of taste and not a lot of carbohydrate, like berries, or exotic fresh vegetables from a farmers market. This is a lot more fun and cheaper than paying $500 a month for a lot of pills to try to cover the damage from eating ho-hum potato chips and packaged snack cakes.
The intelligent people who read this blog will understand this. I worry about the other millions of people in the country who don't have access to good information. I worry about the overworked GPs who don't have time to slog through long statistical studies and try to figure out what an "absolute hazard difference using an exponential model" is.
Many of the details, like the actual dietary advice, in these papers are difficult, if not impossible, to find. If you make an effort to download the full study protocol of the ACCORD study, you find that patients were taught carb counting but it doesn't say how many carbs they were supposed to eat. They were taught self-monitoring of BG, and how to titrate their drugs according to the results. They were apparently not taught how to "titrate" their carb consumption according to the results.
And the authors are often sloppy. For example, sometimes they give both mean and median A1c. Sometimes they give only one. Sometimes they don't indicate which one they calculated.
I worry that the busy physicians will just read the headlines in medical magazines and the New York Times ("Diabetes Heart Treatments May Cause Harm") and conclude that they shouldn't try to treat diabetic patients with high blood pressure, high BG levels, or high lipid levels. Why bother, because they might be sued if they caused harm.
As studies become old, people who write about them tend to simplify, ignoring the many caveats that apply to the studies. For example, Gina Kolata wrote in the recent New York Times story, "It was discovered 2 years ago that rigorously controlling blood sugar did not prevent heart disease or deaths in people with type 2 diabetes." What that study actually showed was that "rigorously controlling blood sugar with a lot of drugs to cover a high-carb diet did not prevent heart disease or death in elderly patients with preexisting heart disease or at least two cardiovascular risk factors and long-standing poorly controlled diabetes."
But how many physicians have retained Kolata's interpretation? I suspect a lot. I've mentioned the many patients whose doctors told them that their diet-controlled A1cs of 5.6 were too low and they should try to get them up to 7!
I would agree that if someone had an A1c of 5.6 only because they were on 7 different expensive medications with a lot of potential side effects, it would make sense to stop several of the drugs and let the A1c go up a bit, especially if the patient was elderly with several other medical problems treated with even more drugs.
But if someone has an A1c of 4.8 because of strict diet control and a lot of exercise, and if that person doesn't go low (after all, nondiabetics don't go low when they have low A1cs), there's absolutely no reason to tell that person to increase the A1c.
Applying a "rule" for the wrong reasons is the type of faulty logic that has caused harm in a lot of diabetic patients. I know some who have been told by registered dieticians that they should put raisins in their oatmeal "to get the carb counts up."
The reason for the high-carb ADA diet is not to eat a lot of carbohydrate; it's to eat less fat. The idea is that when you eat more carbohydrate, you'll eat less fat. But adding carbohydrate to a meal instead of substituting carbohydrate for fat won't reach the ADA goals (which many people today don't agree with anyway). It will just add calories, increase insulin levels, and promote even more fat gain.
So will patients with type 2 diabetes soon be told to get their blood pressure up, not worry about lipid levels, and pay no attention to postprandial BG levels?
I certainly hope not.
The full texts of the New England Journal of Medicine articles cited are available free here.
Friday, March 5, 2010
Ancient Bacteria
It's generally agreed that low-grade chronic inflammation is related to metabolic syndrome, cardiovascular disease, and type 2 diabetes. But no one knows what causes this generalized inflammation.
Acute, localized inflammation is a good thing. It's what walls off an infection, "eats" the offending organism, and then digests it with the help of heavy-duty oxidants. Then, when things are working right, the body repairs the damage, and the cells that have been doing all this leave the scene.
Chronic inflammation, on the other hand, is not a good thing, and the more scientists can find out about it, the better.
Hence I was intrigued by a recent paper in Nature that proposed a totally new idea and confirmed an old idea. You can read a popularized description here, or a link to the original paper here.
When we are invaded by pathogens, the body mounts what is called the innate immune response. This is a nonspecific response triggered by certain chemicals on the surface of many organisms that are unique to them and are not found on our own cells. The body sends out cells called macrophages to engulf the offending organisms and sends chemical signals to recruit other cell types to help rid the body of the organisms and then repair any damage that occurred.
This response is more primitive than the adaptive immune response that uses antibodies and is more specific than the innate immune response.
Usually, the cause of the response is clear, as bacteria or viruses or other pathogens can be found in the blood. But sometimes people seem to have such a response when no pathogens can be found. This puzzled scientists for a long time.
But Carl Hauser and colleagues, the authors of the Nature paper, came up with a fascinating hypothesis. It is generally accepted that mitochondria, known as the "powerhouses of the cell" because they are where most of the cell's energy is produced, were originally bacteria that invaded the cells of other organisms and adapted to the benefit of both.
Mitochondria have their own DNA, which comes only from the mother.
Hauser and colleagues wondered if perhaps trauma that destroys cells could release mitochondria from the damaged cells into the bloodstream. Then, because the mitochondria are descended from bacteria, they might have surface molecules that our bodies would interpret as foreign, so we would mount an innate immune response, just as we do to other bacteria.
His researched suggested that this does indeed happen.
It explains why severe trauma patients sometimes get reactions that look like severe infections when no signs of infecting organisms can be found.
And I wonder if less severe chronic trauma could cause just enough of an innate immune response to trigger chronic disease. For example, we know that chronic gum disease can increase blood glucose levels, along with various signs if inflammation. Could this be because the gum disease is causing gum cells to break down and release mitochondria?
Could other hidden infections be doing the same? By reducing various chronic infections, could we reduce people's chance of getting type 2 diabetes?
I find this research exciting, not because it offers an immediate chance for a cure of type 2 diabetes, but because it's a new idea and I find new paradigm-shifting ideas much more fascinating than huge studies of drugs that rely on statistics to prove anything. Even then, although the statistics can show that the drug worked on average, it can never show whether or not it will help you in particular, as I discussed here.
Creative new ideas can suggest new research paths that may some day lead to real cures.
.
Acute, localized inflammation is a good thing. It's what walls off an infection, "eats" the offending organism, and then digests it with the help of heavy-duty oxidants. Then, when things are working right, the body repairs the damage, and the cells that have been doing all this leave the scene.
Chronic inflammation, on the other hand, is not a good thing, and the more scientists can find out about it, the better.
Hence I was intrigued by a recent paper in Nature that proposed a totally new idea and confirmed an old idea. You can read a popularized description here, or a link to the original paper here.
When we are invaded by pathogens, the body mounts what is called the innate immune response. This is a nonspecific response triggered by certain chemicals on the surface of many organisms that are unique to them and are not found on our own cells. The body sends out cells called macrophages to engulf the offending organisms and sends chemical signals to recruit other cell types to help rid the body of the organisms and then repair any damage that occurred.
This response is more primitive than the adaptive immune response that uses antibodies and is more specific than the innate immune response.
Usually, the cause of the response is clear, as bacteria or viruses or other pathogens can be found in the blood. But sometimes people seem to have such a response when no pathogens can be found. This puzzled scientists for a long time.
But Carl Hauser and colleagues, the authors of the Nature paper, came up with a fascinating hypothesis. It is generally accepted that mitochondria, known as the "powerhouses of the cell" because they are where most of the cell's energy is produced, were originally bacteria that invaded the cells of other organisms and adapted to the benefit of both.
Mitochondria have their own DNA, which comes only from the mother.
Hauser and colleagues wondered if perhaps trauma that destroys cells could release mitochondria from the damaged cells into the bloodstream. Then, because the mitochondria are descended from bacteria, they might have surface molecules that our bodies would interpret as foreign, so we would mount an innate immune response, just as we do to other bacteria.
His researched suggested that this does indeed happen.
It explains why severe trauma patients sometimes get reactions that look like severe infections when no signs of infecting organisms can be found.
And I wonder if less severe chronic trauma could cause just enough of an innate immune response to trigger chronic disease. For example, we know that chronic gum disease can increase blood glucose levels, along with various signs if inflammation. Could this be because the gum disease is causing gum cells to break down and release mitochondria?
Could other hidden infections be doing the same? By reducing various chronic infections, could we reduce people's chance of getting type 2 diabetes?
I find this research exciting, not because it offers an immediate chance for a cure of type 2 diabetes, but because it's a new idea and I find new paradigm-shifting ideas much more fascinating than huge studies of drugs that rely on statistics to prove anything. Even then, although the statistics can show that the drug worked on average, it can never show whether or not it will help you in particular, as I discussed here.
Creative new ideas can suggest new research paths that may some day lead to real cures.
.
Monday, March 1, 2010
Slow Progress
One thing that annoys me is how long it takes for new ideas and new research results to filter down to practitioners. At this rate I will have died of old age before they figure out a better way to treat type 2 diabetes.
When I was first diagnosed in 1996, because I had been a biology major and had done some research in biochemistry, I wanted to learn more about the science of type 2 diabetes.
I was puzzled because the nurse practitioner who diagnosed me told me to follow the American Diabetes Association (ADA) diet, which was chock-a-block full of carbohydrates. I knew that diabetes was caused by an inability to process carbohydrates. So why were they telling me to eat more of them? It made no sense.
So I went to the library. Remember libraries? They were places with books and preceded Internet searches and Google and all that. The library didn't have much of interest, so I searched the interlibrary loan catalogs and found and ordered a book called Insulin, edited by F. M. and S. J. H. Ashcroft. It was published in 1992, which means it was probably written around 1990, as the publishing process does take time.
The book was very interesting. A chapter author named Erol Cerasi said he and others had done a study of a large group of obese and nonobese subects both with and without diabetes and studied insulin resistance (IR) and insulin secretion.
They found that only beta-cell responsiveness could distinguish the diabetic from nondiabetic subjects. The IR could only distinguish obese from nonobese subjects.
In other words, if you're obese, you'll have IR, but you won't necessarily have diabetes. If you have diabetes, your beta cells won't secrete enough insulin, whether or not you're overweight.
They concluded that "the diabetic state is much more closely related to a failure of the secretion of insulin than to diminished efficiency of the circulating hormone level," that is, beta cell defects are more important than IR in causing type 2.
Another group did a similar study and found that those who progressed from prediabetes to diabetes had decreased insulin responses to glucose at the beginning of the study.
Yet people with type 2 diabetes continued to be told that their obesity had caused IR and the IR had caused the diabetes.
Recently, 23 years after the research published by Cerasi and others, there was a report of a study of 13 new genes increasing the risk of type 2 diabetes. The authors of the study said they were "intrigued" by the finding that most of these genes affect beta cell secretion rather than insulin resistance.
"Beta cell impairment may play a larger role in type 2 diabetes than previously recognized," the authors said, as if this was a totally new idea.
It is true that there's so much diabetes research published that no researcher can have read all of it. One report or one person's opinion isn't considered proof of anything, but it should suggest something, so researchers shouldn't be stunned 23 years later to discover the same thing.
Why is it that an amateur researcher, a newly diagnosed patient, can find information a professional apparently cannot? I'm sure the Cerasi papers were not the only ones to come to the same conclusion, and the other researchers had 23 years in which to look.
Cerasi also recommended using insulin in type 2 patients right from the beginning, to normalize blood glucose levels and reduce glucotoxicity, which he felt contributed to the IR. "Present therapeutic approaches based on initial dietary restriction followed after a period of up to several months by oral diabetic agents, seem rather unsuited" for returning the patient to mild diabetes or prediabetes.
"I propose initial, short-term (one to a few weeks) intensified insulin treatment aimed at achieving euglycemia very rapidly, in order to block down-regulation of glucose transport and inprove beta-cell function." He showed in a pilot study that when patients in whom the oral drugs had stopped working were given insulin to maintain normal BG levels for two weeks, they could then maintain good control on oral agents alone after the insulin was stopped.
Again, a recent proposal suggests essentially the same thing. Ralph DeFronzo proposed starting newly diagnosed patients with type 2 on an intensive drug regimen of metformin, a TZD, and exenatide. And he and 15 other diabetes experts proposed the same at the 2008 ADA meeting.
The ADA's response: Prove it. They just now started a 3-year study to see if early normalization of BG levels with drugs helps. But what is taking them so long? And why use drugs instead of insulin?
Other research has shown that early intensive insulin treatment is more effective than drugs in maintenance of beta cell function. So why mess around with expensive drugs that can have serious side effects when a simpler, cheaper treatment has already been shown to work?
It boggles the mind.
Another example is a 2007 paper by Frank Q. Nuttall and Mary C. Gannon. They showed in 1996 that fasting caused normalization of BG levels in people with type 2 diabetes and wondered, "Could merely a reduction in carbohydrate mimic the effect of a reduced fuel-energy diet or short-term starvation on blood glucose in people with type 2 diabetes mellitus?"
They published the results of using l0w-carb diets (20 and 30% carbohydrate), showing that BG levels and HbA1c levels were much lower. However, their request for further funding was rejected by the National Institutes of Health, which said their sample sizes were too low to show anything and "it is difficult to conceive of the diet as producing larger improvements than metformin or rosiglitazone, for example, especially if the subjects are maintaining their body weight."
"So much for open mindedness," wrote Nuttall and Gannon. The health authorities cling to their old views even in the face of new evidence. They seem to have made up their minds, and there's no more room in their tiny minds to consider alternatives.
But wait a minute. For decades, Richard K. Bernstein has been proposing low-carbohydrate diets for both type 1 and type 2 patients. His first book was published in 1984. But almost no one in the professional world listened to him either. Why did Nuttall and Gannon have to "wonder" in 1996 if the idea of reducing carbohyrate would work?
Research has been done, and it has been published, but other researchers don't seem to pay a lot of attention.
Why must the patients be the ones to ferret out the facts?
When I was first diagnosed in 1996, because I had been a biology major and had done some research in biochemistry, I wanted to learn more about the science of type 2 diabetes.
I was puzzled because the nurse practitioner who diagnosed me told me to follow the American Diabetes Association (ADA) diet, which was chock-a-block full of carbohydrates. I knew that diabetes was caused by an inability to process carbohydrates. So why were they telling me to eat more of them? It made no sense.
So I went to the library. Remember libraries? They were places with books and preceded Internet searches and Google and all that. The library didn't have much of interest, so I searched the interlibrary loan catalogs and found and ordered a book called Insulin, edited by F. M. and S. J. H. Ashcroft. It was published in 1992, which means it was probably written around 1990, as the publishing process does take time.
The book was very interesting. A chapter author named Erol Cerasi said he and others had done a study of a large group of obese and nonobese subects both with and without diabetes and studied insulin resistance (IR) and insulin secretion.
They found that only beta-cell responsiveness could distinguish the diabetic from nondiabetic subjects. The IR could only distinguish obese from nonobese subjects.
In other words, if you're obese, you'll have IR, but you won't necessarily have diabetes. If you have diabetes, your beta cells won't secrete enough insulin, whether or not you're overweight.
They concluded that "the diabetic state is much more closely related to a failure of the secretion of insulin than to diminished efficiency of the circulating hormone level," that is, beta cell defects are more important than IR in causing type 2.
Another group did a similar study and found that those who progressed from prediabetes to diabetes had decreased insulin responses to glucose at the beginning of the study.
Yet people with type 2 diabetes continued to be told that their obesity had caused IR and the IR had caused the diabetes.
Recently, 23 years after the research published by Cerasi and others, there was a report of a study of 13 new genes increasing the risk of type 2 diabetes. The authors of the study said they were "intrigued" by the finding that most of these genes affect beta cell secretion rather than insulin resistance.
"Beta cell impairment may play a larger role in type 2 diabetes than previously recognized," the authors said, as if this was a totally new idea.
It is true that there's so much diabetes research published that no researcher can have read all of it. One report or one person's opinion isn't considered proof of anything, but it should suggest something, so researchers shouldn't be stunned 23 years later to discover the same thing.
Why is it that an amateur researcher, a newly diagnosed patient, can find information a professional apparently cannot? I'm sure the Cerasi papers were not the only ones to come to the same conclusion, and the other researchers had 23 years in which to look.
Cerasi also recommended using insulin in type 2 patients right from the beginning, to normalize blood glucose levels and reduce glucotoxicity, which he felt contributed to the IR. "Present therapeutic approaches based on initial dietary restriction followed after a period of up to several months by oral diabetic agents, seem rather unsuited" for returning the patient to mild diabetes or prediabetes.
"I propose initial, short-term (one to a few weeks) intensified insulin treatment aimed at achieving euglycemia very rapidly, in order to block down-regulation of glucose transport and inprove beta-cell function." He showed in a pilot study that when patients in whom the oral drugs had stopped working were given insulin to maintain normal BG levels for two weeks, they could then maintain good control on oral agents alone after the insulin was stopped.
Again, a recent proposal suggests essentially the same thing. Ralph DeFronzo proposed starting newly diagnosed patients with type 2 on an intensive drug regimen of metformin, a TZD, and exenatide. And he and 15 other diabetes experts proposed the same at the 2008 ADA meeting.
The ADA's response: Prove it. They just now started a 3-year study to see if early normalization of BG levels with drugs helps. But what is taking them so long? And why use drugs instead of insulin?
Other research has shown that early intensive insulin treatment is more effective than drugs in maintenance of beta cell function. So why mess around with expensive drugs that can have serious side effects when a simpler, cheaper treatment has already been shown to work?
It boggles the mind.
Another example is a 2007 paper by Frank Q. Nuttall and Mary C. Gannon. They showed in 1996 that fasting caused normalization of BG levels in people with type 2 diabetes and wondered, "Could merely a reduction in carbohydrate mimic the effect of a reduced fuel-energy diet or short-term starvation on blood glucose in people with type 2 diabetes mellitus?"
They published the results of using l0w-carb diets (20 and 30% carbohydrate), showing that BG levels and HbA1c levels were much lower. However, their request for further funding was rejected by the National Institutes of Health, which said their sample sizes were too low to show anything and "it is difficult to conceive of the diet as producing larger improvements than metformin or rosiglitazone, for example, especially if the subjects are maintaining their body weight."
"So much for open mindedness," wrote Nuttall and Gannon. The health authorities cling to their old views even in the face of new evidence. They seem to have made up their minds, and there's no more room in their tiny minds to consider alternatives.
But wait a minute. For decades, Richard K. Bernstein has been proposing low-carbohydrate diets for both type 1 and type 2 patients. His first book was published in 1984. But almost no one in the professional world listened to him either. Why did Nuttall and Gannon have to "wonder" in 1996 if the idea of reducing carbohyrate would work?
Research has been done, and it has been published, but other researchers don't seem to pay a lot of attention.
Why must the patients be the ones to ferret out the facts?
Saturday, January 30, 2010
Fuzzy Fats
Fats have been in the news lately, with publication of a meta-analysis mentioned in a previous blogpost showing that there's no statistical evidence that saturated fat is associated with deaths from cardiovascular disease (CVD).
Well, let me qualify that statement. Fats have been in the low-carb news lately. I haven't seen much discussion of this study by people like Dean Ornish who support very low fat diets.
Note that the study showed that they found no evidence that saturated fat intake was associated with CVD mortality. They didn't study whether or not eating other fats were associated with CVD mortality.
But what does saturated fat intake mean? Does it mean the amount of saturated fat you eat? Or does it mean what percentage of your diet consists of saturated fat? These two things can be quite different. Yet many research reports, written by scientists who should be precise about such things, don't make it clear.
Fat intake is often reported as a percentage. For example, low fatters want us to keep our dietary fat under 30% and saturated fat under 10%. But I don't know anyone who goes into a restaurant and sits down with a calculator and a scale to make sure they don't eat more than 30% fat at that meal. (Actually, people with type 1 diabetes used to have to do just that.) Trying to calculate total fat and also saturated fat is even more difficult.
I once bought a little hand-held gizmo that allowed you to punch in your menu and it would, indeed, calculate the macronutrients in the meal. If you ate the same meals over and over again, it might have been useful. But if you ate the same meals over and over again it would have been equally useful to do the calculations on a real computer or even by hand with the aid of a book and then write them down to refer to when you had that meal.
When you ate something different at each meal, you had to locate that food among thousands of foods, decide what description best fit it and how much it weighed, and then input that.
I don't eat the same meal over and over again. I think variety is the spice of eating as well as the spice of life. When it's mealtime, I go to the fridge to see what's there and then try to make something interesting from it.
And the biggest problem I had with any nutritional gizmo was trying to decide which of the myriad choices to input for various foods. Let's say I roast a leg of lamb.
Do I want "Lamb, Australian, imported, fresh, leg, center slice, bone in, separable lean and fat, trimmed to 1/8 inch fat, raw" or do I want "Lamb, domestic, leg, shank half, separable lean and fat, trimmed to 1/4 inch fat, Choice, cooked, roasted, USDA"? I counted 44 different versions of leg of lamb in the nutrition program I have on my computer: Computer Planned Nutrition.
And how do I know how the nutritional information from lambs raised by my neighbors are closer to those of the Australian, New Zealand, or domestic lamb in this program? The lamb I eat comes from free-range animals. Do the animals used in the nutritional program? I don't know.
So even assuming I have time to comb through all 44 choices every time I sit down to eat a slice of lamb (which would probably be cold by the time I figured out the best one), I have no confidence that the lamb I'm eating has the same nutritional composition as the lamb in the program.
Some lambs are fatter than others. Of course I could trim them all evenly. But I could trim the lamb to 1/4 inch or 1/8 inch and then eat or not eat the remaining fat. Or I could leave some of the lamb and a lot of the fat that oozed out of the lamb on my plate.
I see some of the precise calculations some people do with nutritional programs as GIGO: garbage in, garbage out. The computational ability of the computer programs exceeds the accuracy of the data you put in.
The same is true of other foods. Foods have different nutritional compositions depending not only on the particular variety and size but on the condition of the soil, fertilizer, growing season, and so forth.
Furthermore, most nutritional studies rely on people's recollection of what they ate last week or last month or last year. I often can't remember what I had for breakfast, much less last week.
But I digress. I was talking about fat.
Most people don't estimate the percentage of fat in every meal they eat. You can get an estimate of what you need every day by calculating the number of calories you need every day to keep your weight stable, or to lose weight if that's what you're trying to do. Then you can calculate how many calories or grams of a food you should eat each day to reach that percentage.
For example, let's say you're trying to eat about 2000 calories a day with 30% fat. That would be 600 calories of fat. Because there are about 9 calories per gram of fat, that would be 66 grams of fat. Divide that by 28.35 (1 ounce = 28.35 grams), and you get about 2.35 ounces of fat per day, or 1.175 tablespoons (1 oz = 2 Tb). That includes the fat in your meat as well as the oil you cook in or pour on your salad.
But how do you really know how much fat is in the meat you eat?
What if you're eating a lot more or a lot less than 2000 calories a day? What if you're a large man and you're very athletic and you eat 5000 calories a day. Then you could eat 1000 calories of fat (111 grams) of day and still say you were eating a very low fat diet, only 20%.
What if you're a small woman trying to lose weight? You might eat only 1000 calories a day. Then the same amount of fat (1000 calories, or 111 grams) would constitute 100% of your diet, obviously not a likely choice for anyone. If you ate only 400 calories of fat (44 grams), you'd still be eating 40% fat, considered a high-fat diet.
You could get your fat percentage down by eating more carbohydrate calories. Let's say you increased your total calories to 2000. Then you'd be on a "nice healthy 20% fat diet." But does that many any sense? Not to me.
Now let's look at what often happens when people go on a low carb diet. Let's say your previous lunch every day was a hamburger on a bun with french fries and a regular soda. I chose ground beef and a large hamburger bun (this had less fat than a fast-food burger, but I wanted to be able to compare it with a burger without the bun), a "serving" of Burger King fries, and a 32-ounce soda. Most people would probably also add catsup, or the fast-food burger would come with a sweet sauce, but I'm ignoring that. According to my nutritional program, without those extras, you have a meal with 1358 calories, 38 grams of fat, 10 grams of saturated fat, and 200 grams of carbohydrate.
Now let's say you go on a low-carb diet. You still eat at the hamburger place because all your friends do, but now you get a large burger without the bun. In place of the bun, you order a salad of mixed greens (I used 2 cups), with ranch dressing, and water or a sugarfree soda. This meal results in 324 calories, 15 grams of fat, 3 grams of saturated fat, and 4 grams of carbohydrate.
The first meal results in 25% fat (38 grams of fat x 9, divided by 1358), because of all the calories in the soda and the potato. The second meal results in 42% fat (15 x 9, divided by 324), because the total calories are so much lower that the fat makes up a larger proportion of the meal.
But would anyone claim that a meal that included french fries and a large soda (25% fat) was healthier than a meal that included salad greens and ranch dressing (42% fat)?
I don't think so.
This is why measuring a diet by the percentage of fat can be so misleading. This is why worrying about the fat content of low-carb diets can be so misleading.
Although my current low-carb diet includes about 60% fat, I don't think I'm eating any more fat than I used to eat. What I'm not eating is all the carbohydrate I used to put underneath that pat of butter or tablespoon of oil.
Biochemist Richard Feinman said all this in a more concise and more academic way when he wrote here, ". . . it is important to recognize that percentages are misleading. There are really three degrees of freedom in design or analysis of a weight loss experiment: two of the three macronutrients and the total calorie intake. It is unlikely that the percentage rather than the absolute amount of macronutrients is the controlling variable and at least three published studies show that carbohydrate reduction is not necessarily accompanied by replacement with either fat or protein but rather caloric reduction due to the carbohydrate removed."
In trying to unravel the very complex picture of the role of fat in human health, and for us its role in diabetes control, remember to scrutinize any research articles you read to see if the reseachers were measuring absolute amounts of nutrients or their percentages.
If only percentages, take the results with a grain of salt . . . or maybe a piece of cheese.
Also see how they determined the various nutritional intakes. Did they isoloate people in a ward and feed them carefully controlled meals? Or did they provide all the food on a take-out basis and trust that the participants weren't eating anything else? Or did they just provide "guidance" by a nutritionist who told them what kinds of foods they should be eating? Or did they just ask people to fill out food questionnaires after the fact?
You also need to see how the researchers defined their terms. They can differ a lot. For example, some people call a diet that has 45% carbohydrate (225 grams on a 2000-calorie diet) instead of 55 or 60% a low-carb diet and then claim that low-carb diets do this or that. Often this information cannot be found in the abstract of the article. You have to obtain and read the whole thing.
If you're reading an article about the effects of fat, you need to determine what other foods the subjects were eating. If you're on a low-carb diet, you'll burn a lot more fat than if you're eating both fats and carbs.
Unfortunately, the news media can't deal with these subtleties. They want interesting stories. And simplistic interpretations make for better stories. A story headlined "Whortleberries cure cancer" would get more readers than a story headlined "When fed a diet of 98% whortleberry, small percentage of highly inbred white mice see improvements in obscure cancer type that never affects humans ."
But you're smarter than the average reporter. So reader beware. Read and learn. But don't take any nutritional study as the last word. And especially, don't accept fuzzy fat words like "fat intake."
Well, let me qualify that statement. Fats have been in the low-carb news lately. I haven't seen much discussion of this study by people like Dean Ornish who support very low fat diets.
Note that the study showed that they found no evidence that saturated fat intake was associated with CVD mortality. They didn't study whether or not eating other fats were associated with CVD mortality.
But what does saturated fat intake mean? Does it mean the amount of saturated fat you eat? Or does it mean what percentage of your diet consists of saturated fat? These two things can be quite different. Yet many research reports, written by scientists who should be precise about such things, don't make it clear.
Fat intake is often reported as a percentage. For example, low fatters want us to keep our dietary fat under 30% and saturated fat under 10%. But I don't know anyone who goes into a restaurant and sits down with a calculator and a scale to make sure they don't eat more than 30% fat at that meal. (Actually, people with type 1 diabetes used to have to do just that.) Trying to calculate total fat and also saturated fat is even more difficult.
I once bought a little hand-held gizmo that allowed you to punch in your menu and it would, indeed, calculate the macronutrients in the meal. If you ate the same meals over and over again, it might have been useful. But if you ate the same meals over and over again it would have been equally useful to do the calculations on a real computer or even by hand with the aid of a book and then write them down to refer to when you had that meal.
When you ate something different at each meal, you had to locate that food among thousands of foods, decide what description best fit it and how much it weighed, and then input that.
I don't eat the same meal over and over again. I think variety is the spice of eating as well as the spice of life. When it's mealtime, I go to the fridge to see what's there and then try to make something interesting from it.
And the biggest problem I had with any nutritional gizmo was trying to decide which of the myriad choices to input for various foods. Let's say I roast a leg of lamb.
Do I want "Lamb, Australian, imported, fresh, leg, center slice, bone in, separable lean and fat, trimmed to 1/8 inch fat, raw" or do I want "Lamb, domestic, leg, shank half, separable lean and fat, trimmed to 1/4 inch fat, Choice, cooked, roasted, USDA"? I counted 44 different versions of leg of lamb in the nutrition program I have on my computer: Computer Planned Nutrition.
And how do I know how the nutritional information from lambs raised by my neighbors are closer to those of the Australian, New Zealand, or domestic lamb in this program? The lamb I eat comes from free-range animals. Do the animals used in the nutritional program? I don't know.
So even assuming I have time to comb through all 44 choices every time I sit down to eat a slice of lamb (which would probably be cold by the time I figured out the best one), I have no confidence that the lamb I'm eating has the same nutritional composition as the lamb in the program.
Some lambs are fatter than others. Of course I could trim them all evenly. But I could trim the lamb to 1/4 inch or 1/8 inch and then eat or not eat the remaining fat. Or I could leave some of the lamb and a lot of the fat that oozed out of the lamb on my plate.
I see some of the precise calculations some people do with nutritional programs as GIGO: garbage in, garbage out. The computational ability of the computer programs exceeds the accuracy of the data you put in.
The same is true of other foods. Foods have different nutritional compositions depending not only on the particular variety and size but on the condition of the soil, fertilizer, growing season, and so forth.
Furthermore, most nutritional studies rely on people's recollection of what they ate last week or last month or last year. I often can't remember what I had for breakfast, much less last week.
But I digress. I was talking about fat.
Most people don't estimate the percentage of fat in every meal they eat. You can get an estimate of what you need every day by calculating the number of calories you need every day to keep your weight stable, or to lose weight if that's what you're trying to do. Then you can calculate how many calories or grams of a food you should eat each day to reach that percentage.
For example, let's say you're trying to eat about 2000 calories a day with 30% fat. That would be 600 calories of fat. Because there are about 9 calories per gram of fat, that would be 66 grams of fat. Divide that by 28.35 (1 ounce = 28.35 grams), and you get about 2.35 ounces of fat per day, or 1.175 tablespoons (1 oz = 2 Tb). That includes the fat in your meat as well as the oil you cook in or pour on your salad.
But how do you really know how much fat is in the meat you eat?
What if you're eating a lot more or a lot less than 2000 calories a day? What if you're a large man and you're very athletic and you eat 5000 calories a day. Then you could eat 1000 calories of fat (111 grams) of day and still say you were eating a very low fat diet, only 20%.
What if you're a small woman trying to lose weight? You might eat only 1000 calories a day. Then the same amount of fat (1000 calories, or 111 grams) would constitute 100% of your diet, obviously not a likely choice for anyone. If you ate only 400 calories of fat (44 grams), you'd still be eating 40% fat, considered a high-fat diet.
You could get your fat percentage down by eating more carbohydrate calories. Let's say you increased your total calories to 2000. Then you'd be on a "nice healthy 20% fat diet." But does that many any sense? Not to me.
Now let's look at what often happens when people go on a low carb diet. Let's say your previous lunch every day was a hamburger on a bun with french fries and a regular soda. I chose ground beef and a large hamburger bun (this had less fat than a fast-food burger, but I wanted to be able to compare it with a burger without the bun), a "serving" of Burger King fries, and a 32-ounce soda. Most people would probably also add catsup, or the fast-food burger would come with a sweet sauce, but I'm ignoring that. According to my nutritional program, without those extras, you have a meal with 1358 calories, 38 grams of fat, 10 grams of saturated fat, and 200 grams of carbohydrate.
Now let's say you go on a low-carb diet. You still eat at the hamburger place because all your friends do, but now you get a large burger without the bun. In place of the bun, you order a salad of mixed greens (I used 2 cups), with ranch dressing, and water or a sugarfree soda. This meal results in 324 calories, 15 grams of fat, 3 grams of saturated fat, and 4 grams of carbohydrate.
The first meal results in 25% fat (38 grams of fat x 9, divided by 1358), because of all the calories in the soda and the potato. The second meal results in 42% fat (15 x 9, divided by 324), because the total calories are so much lower that the fat makes up a larger proportion of the meal.
But would anyone claim that a meal that included french fries and a large soda (25% fat) was healthier than a meal that included salad greens and ranch dressing (42% fat)?
I don't think so.
This is why measuring a diet by the percentage of fat can be so misleading. This is why worrying about the fat content of low-carb diets can be so misleading.
Although my current low-carb diet includes about 60% fat, I don't think I'm eating any more fat than I used to eat. What I'm not eating is all the carbohydrate I used to put underneath that pat of butter or tablespoon of oil.
Biochemist Richard Feinman said all this in a more concise and more academic way when he wrote here, ". . . it is important to recognize that percentages are misleading. There are really three degrees of freedom in design or analysis of a weight loss experiment: two of the three macronutrients and the total calorie intake. It is unlikely that the percentage rather than the absolute amount of macronutrients is the controlling variable and at least three published studies show that carbohydrate reduction is not necessarily accompanied by replacement with either fat or protein but rather caloric reduction due to the carbohydrate removed."
In trying to unravel the very complex picture of the role of fat in human health, and for us its role in diabetes control, remember to scrutinize any research articles you read to see if the reseachers were measuring absolute amounts of nutrients or their percentages.
If only percentages, take the results with a grain of salt . . . or maybe a piece of cheese.
Also see how they determined the various nutritional intakes. Did they isoloate people in a ward and feed them carefully controlled meals? Or did they provide all the food on a take-out basis and trust that the participants weren't eating anything else? Or did they just provide "guidance" by a nutritionist who told them what kinds of foods they should be eating? Or did they just ask people to fill out food questionnaires after the fact?
You also need to see how the researchers defined their terms. They can differ a lot. For example, some people call a diet that has 45% carbohydrate (225 grams on a 2000-calorie diet) instead of 55 or 60% a low-carb diet and then claim that low-carb diets do this or that. Often this information cannot be found in the abstract of the article. You have to obtain and read the whole thing.
If you're reading an article about the effects of fat, you need to determine what other foods the subjects were eating. If you're on a low-carb diet, you'll burn a lot more fat than if you're eating both fats and carbs.
Unfortunately, the news media can't deal with these subtleties. They want interesting stories. And simplistic interpretations make for better stories. A story headlined "Whortleberries cure cancer" would get more readers than a story headlined "When fed a diet of 98% whortleberry, small percentage of highly inbred white mice see improvements in obscure cancer type that never affects humans ."
But you're smarter than the average reporter. So reader beware. Read and learn. But don't take any nutritional study as the last word. And especially, don't accept fuzzy fat words like "fat intake."
Friday, January 29, 2010
Banana Cream
I've always loved custard of any kind, and banana cream pie was a real treat.
Alas, I don't eat custard anymore, except for custard sauce I make with low-carb milk in the summer when my raspberry bushes are producing. They don't raise my BG very much.
I recently invented a banana cream substitute when I was trying to use up some ricotta cheese I'd bought for another recipe.
Basically, you stir some DaVinci sugarfree banana flavoring into full-fat ricotta cheese. (I find the Maggio brand is the creamiest I can get here.) Top with sugarfree whipped cream. And that's it. Pretty simple.
The ricotta has a smooth texture somewhat like custard, and when topped with sugarfree whipped cream, it really gave me the feeling I was eating banana cream.
I like the sugarfree whipped cream that comes in a can, made by Land O'Lakes, because I can use just a little at a time. You can get it at Walmart superstores. When I buy heavy cream and whip it, then I have to use up the rest of the cream or it will go bad. So I end up eating more heavy cream than I really want.
You do have to be careful with ricotta cheese, as it does contain some carbs, so small portions are in order. It was so good I went overboard, and my BG levels did reflect that.
But it made a nice change for me, and next time I'll be more careful.
Alas, I don't eat custard anymore, except for custard sauce I make with low-carb milk in the summer when my raspberry bushes are producing. They don't raise my BG very much.
I recently invented a banana cream substitute when I was trying to use up some ricotta cheese I'd bought for another recipe.
Basically, you stir some DaVinci sugarfree banana flavoring into full-fat ricotta cheese. (I find the Maggio brand is the creamiest I can get here.) Top with sugarfree whipped cream. And that's it. Pretty simple.
The ricotta has a smooth texture somewhat like custard, and when topped with sugarfree whipped cream, it really gave me the feeling I was eating banana cream.
I like the sugarfree whipped cream that comes in a can, made by Land O'Lakes, because I can use just a little at a time. You can get it at Walmart superstores. When I buy heavy cream and whip it, then I have to use up the rest of the cream or it will go bad. So I end up eating more heavy cream than I really want.
You do have to be careful with ricotta cheese, as it does contain some carbs, so small portions are in order. It was so good I went overboard, and my BG levels did reflect that.
But it made a nice change for me, and next time I'll be more careful.
Monday, January 18, 2010
Saturated Fat and Heart Disease
I'm on a low-carb diet. I believe in LC diets for people with diabetes.
However, I also have an open mind. It's possible that new evidence will show that LC diets, although they improve blood glucose (BG) levels in people with diabetes, also make something else worse.
Richard Bernstein, the physician and author of LC diet book The Diabetes Solution, has lived with type 1 diabetes for many decades, most of those years on a LC diet. And the fact that he is in excellent health in his 70s argues against this possibility. However, Bernstein has type 1 diabetes, and very little insulin resistance. There's some evidence that fat increases insulin resistance. Hence, for those of us for whom insulin resistance is a big problem, perhaps fat of any kind, or maybe only certain kinds of fat, is not a great idea.
So, I have an open mind. But unfortunately, many people in the LC community seem not to. Many of them don't have diabetes, and they have gotten great results losing a lot of weight with LC diets. So they think the LC diet with a lot of fat is the answer for everyone.
And unfortunately, the LC world is just as guilty of spinning the news as the popular science writers who blame red meat for all our problems when some study showed that people eating red meat, hot dogs, french fries, no vegetables, and sweet desserts don't fare so well on some health factor.
A good example is the blogosphere response to this recent study, a meta-analysis of the association between saturated fat and cardiovascular disease (CVD). A meta-analysis is a study in which researchers combine the results from a lot of studies, some of which aren't statistically significant because of their small size, so that the overall results are statistically significant because of the larger populations in the combined studies.
Meta-analyses are notoriously questionable, because the researchers have to decide which studies to include. If you did a meta-analysis of the percentage of the population that watched the Super Bowl (assuming lots of people had studied this fascinating question) but excluded everyone who shaved every morning, the results wouldn't be very accurate.
Nevertheless, sometimes meta-analyses can suggest possible conclusions that other scientists can then investigate more thoroughly.
And that is what this study, titled Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease, did.
The authors' conclusion was that "there is no significant evidence for concluding that dietary saturated fat is associated with an increased risk of CHD [coronary heart disease] or CVD. More data are needed to elucidate whether CVD risks are likely to be influenced by the specific nutrients used to replace saturated fat."
Two things are important here.
First, the fact that there's no significant evidence for something doesn't mean it's not true. It just means no one has proved that it's true. Several studies have concluded that there's no significant evidence that BG testing in people with type 2 diabetes results in lower A1c's, but most of us know that it does when patients are educated about how to use the results from their meters to change their diets and their exercise patterns. But no one has done the study that would show this.
And second, this study was about association, not cause. Something can be associated with something else but not be the cause of it. For example, coffee drinking is often associated with smoking, but drinking coffee doesn't make you smoke, and vice versa.
The types of studies this meta-analysis looked at were not the types of studies that can show cause.
What the authors found was that some studies showed that saturated fat consumption was associated with higher rates of CVD (heart attacks and strokes), and other studies showed that saturated fat consumption was associated with lower rates of CVD. When you combined the higher rates and the lower rates, you got rates that weren't significantly different.
However, they also noted another recent study that showed that when saturated fat was replaced by polyunsaturated fat, CVD rates went down. When saturated fat was replaced by carbohydrates (what dieticians have been recommending that we all do), CVD rates went up. They said there was some evidence that the ratio of unsaturated to saturated fats was more important than the amount of saturated fat. Hence they suggest that studies are needed that would investigate whether the other elements of the diet have more effect on CVD than the saturated fat.
The authors of Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease never say that saturated fat definitely doesn't cause CVD. They also say that "the available data were not adequate for determining whether there are CHD or stroke associations with saturated fat in specific age and sex subgroups." In other words, the jury is still out.
Nevertheless, the Internet is awash in blogs with titles like "Two major studies conclude that saturated fat does NOT cause heart disease" and "Saturated Fats Are Not Harmful."
The following are just my opinions, and I won't cite studies to back them up. I suspect that saturated fat is fine in moderation. If you want to put a couple of teaspoons of something on your vegetables, I suspect it doesn't matter if it's butter or olive oil. People on LC diets can probably eat more saturated fat because they're burning fats instead of carbohydrates for energy. I don't think eating a lot of polyunsaturated fats (vegetable oils), which are easily oxidized (damaged), is healthy.
But I don't think eating gargantuan amounts of fat of any kind is healthy, even on a LC diet. I once measured my triglyceride levels after eating an extremely high fat breakfast. You can see the results here. The triglyceride levels were astronomical.
People with diabetes probably have a disturbed lipid metabolism, so it's possible that nondiabetics would not have such astronomical triglyceride levels after pigging out on fats (for example, eating half a pizza). But headlines proclaiming that saturated fat isn't harmful will be interpreted by many people to mean that fat isn't harmful. They won't stop eating all those carbohydrates, the doughnuts and french fries and white bread. They'll just add more fat because they remember that they saw headlines saying fat doesn't cause heart disease.
The study showing no association between saturated fat consumption and CVD, despite its many limitations, is important. It should lead to more studies that will attempt to show causation or lack thereof.
I just hope the misinterpretations don't result in more unhealthy eating.
However, I also have an open mind. It's possible that new evidence will show that LC diets, although they improve blood glucose (BG) levels in people with diabetes, also make something else worse.
Richard Bernstein, the physician and author of LC diet book The Diabetes Solution, has lived with type 1 diabetes for many decades, most of those years on a LC diet. And the fact that he is in excellent health in his 70s argues against this possibility. However, Bernstein has type 1 diabetes, and very little insulin resistance. There's some evidence that fat increases insulin resistance. Hence, for those of us for whom insulin resistance is a big problem, perhaps fat of any kind, or maybe only certain kinds of fat, is not a great idea.
So, I have an open mind. But unfortunately, many people in the LC community seem not to. Many of them don't have diabetes, and they have gotten great results losing a lot of weight with LC diets. So they think the LC diet with a lot of fat is the answer for everyone.
And unfortunately, the LC world is just as guilty of spinning the news as the popular science writers who blame red meat for all our problems when some study showed that people eating red meat, hot dogs, french fries, no vegetables, and sweet desserts don't fare so well on some health factor.
A good example is the blogosphere response to this recent study, a meta-analysis of the association between saturated fat and cardiovascular disease (CVD). A meta-analysis is a study in which researchers combine the results from a lot of studies, some of which aren't statistically significant because of their small size, so that the overall results are statistically significant because of the larger populations in the combined studies.
Meta-analyses are notoriously questionable, because the researchers have to decide which studies to include. If you did a meta-analysis of the percentage of the population that watched the Super Bowl (assuming lots of people had studied this fascinating question) but excluded everyone who shaved every morning, the results wouldn't be very accurate.
Nevertheless, sometimes meta-analyses can suggest possible conclusions that other scientists can then investigate more thoroughly.
And that is what this study, titled Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease, did.
The authors' conclusion was that "there is no significant evidence for concluding that dietary saturated fat is associated with an increased risk of CHD [coronary heart disease] or CVD. More data are needed to elucidate whether CVD risks are likely to be influenced by the specific nutrients used to replace saturated fat."
Two things are important here.
First, the fact that there's no significant evidence for something doesn't mean it's not true. It just means no one has proved that it's true. Several studies have concluded that there's no significant evidence that BG testing in people with type 2 diabetes results in lower A1c's, but most of us know that it does when patients are educated about how to use the results from their meters to change their diets and their exercise patterns. But no one has done the study that would show this.
And second, this study was about association, not cause. Something can be associated with something else but not be the cause of it. For example, coffee drinking is often associated with smoking, but drinking coffee doesn't make you smoke, and vice versa.
The types of studies this meta-analysis looked at were not the types of studies that can show cause.
What the authors found was that some studies showed that saturated fat consumption was associated with higher rates of CVD (heart attacks and strokes), and other studies showed that saturated fat consumption was associated with lower rates of CVD. When you combined the higher rates and the lower rates, you got rates that weren't significantly different.
However, they also noted another recent study that showed that when saturated fat was replaced by polyunsaturated fat, CVD rates went down. When saturated fat was replaced by carbohydrates (what dieticians have been recommending that we all do), CVD rates went up. They said there was some evidence that the ratio of unsaturated to saturated fats was more important than the amount of saturated fat. Hence they suggest that studies are needed that would investigate whether the other elements of the diet have more effect on CVD than the saturated fat.
The authors of Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease never say that saturated fat definitely doesn't cause CVD. They also say that "the available data were not adequate for determining whether there are CHD or stroke associations with saturated fat in specific age and sex subgroups." In other words, the jury is still out.
Nevertheless, the Internet is awash in blogs with titles like "Two major studies conclude that saturated fat does NOT cause heart disease" and "Saturated Fats Are Not Harmful."
The following are just my opinions, and I won't cite studies to back them up. I suspect that saturated fat is fine in moderation. If you want to put a couple of teaspoons of something on your vegetables, I suspect it doesn't matter if it's butter or olive oil. People on LC diets can probably eat more saturated fat because they're burning fats instead of carbohydrates for energy. I don't think eating a lot of polyunsaturated fats (vegetable oils), which are easily oxidized (damaged), is healthy.
But I don't think eating gargantuan amounts of fat of any kind is healthy, even on a LC diet. I once measured my triglyceride levels after eating an extremely high fat breakfast. You can see the results here. The triglyceride levels were astronomical.
People with diabetes probably have a disturbed lipid metabolism, so it's possible that nondiabetics would not have such astronomical triglyceride levels after pigging out on fats (for example, eating half a pizza). But headlines proclaiming that saturated fat isn't harmful will be interpreted by many people to mean that fat isn't harmful. They won't stop eating all those carbohydrates, the doughnuts and french fries and white bread. They'll just add more fat because they remember that they saw headlines saying fat doesn't cause heart disease.
The study showing no association between saturated fat consumption and CVD, despite its many limitations, is important. It should lead to more studies that will attempt to show causation or lack thereof.
I just hope the misinterpretations don't result in more unhealthy eating.
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