`I quite agree with you,’ said the Duchess; `and the moral of that is–Be what you would seem to be–or if you’d like it put more simply–Never imagine yourself not to be otherwise than what it might appear to others that what you were or might have been was not otherwise than what you had been would have appeared to them to be otherwise.’
`I think I should understand that better,’ Alice said very politely, `if I had it written down: but I can’t quite follow it as you say it.’
Lewis Carroll
If you tell a lie big enough and keep repeating it, people will eventually come to believe it.
Dr. Joseph Goebbels, Nazi minister of propaganda
I’m starting this post with two apropos quotes. The first, from Alice in Wonderland, because the post will be a little difficult to understand; the second because I just read for the umpteenth time the Big Lie about low-carb diets and wanted to blog about it but couldn’t until I wrote this post first.
Intention-to-treat analysis (ITT) has become the de rigueur way of looking at experimental results that more often than not gives erroneous results. These erroneous results are then reported as gospel, when in reality they are simply erroneous. When unbiased, intelligent people (the readers of this blog, for example) consider ITT, they cannot understand how it can be used by scientist trying to make sense out of their data, but, unfortunately, it is in almost every experiment. Here is how it works.
Let’s say were going to do an experiment comparing two different diets. We round up 100 subjects and randomize them into two groups of 50. We put one group, Group A, on one diet, Diet A, and we put the other, Group B, on a different diet, Diet B. We keep both groups on their respective diets for 8 weeks to see what happens.
At the end of the 8 weeks we find that 30 members of Group A dropped out, but those who hung in there lost an average of 3 pounds per week for a total of 24 pounds each over the course of the study. We look at Group B and find that no one dropped out of the study and that all the subjects lost an average of 1.2 pounds per week.
What does this data tell us? It’s pretty simple. It tells us that Diet A is much more effective, but is more difficult to follow. It tells us that Diet B is less effective but easier to follow. Right? All intelligent people could agree on that. So that’s how this study would be presented if it were published in a journal, right? Uh, no.
No?
No. If published, the conclusion would be that both diets are exactly the same.
Say what?!?!?
Yep. That’s what the authors would conclude. Why? Because they would use an intention-to-treat analysis. In fact, the peer-review process would probably demand it.
An intention-to-treat analysis demands that all subjects remain in the data pool, even if some have dropped out. The intention was to treat all the subjects, so the analysis should contain all the subjects, even if some left the study after the first day. In an ITT, researchers pretend that subjects who chose to abandon the study really didn’t and include them in their final data. Sounds like something from Through the Looking Glass, doesn’t it?
Let’s look at how this would work in our dietary study above. The 20 subjects in Group A who followed Diet A lost 24 pounds each. Multiply this 24 pounds times the 20 subjects who stayed in the study and you find that the group lost 480 pounds over the course of the 8 weeks. Now divide this 480 pounds by the 50 subjects who started the study, and you get a weight loss of 9.6 pounds for the 8 weeks. Dividing by 8 gives us an average weight loss of 1.2 pounds per week for all 50 subjects in Group A. Which is exactly the same as the weight loss in the subjects in Group B. So, according to the dictates of ITT, the study would show that both diets were equally effective. But, as we’ve seen, they’re not.
If a doctor were recommending a diet to his/her patients based on the actual findings of the study, he/she could reasonably say: Diet A is very effective but tough to follow, so if you think you can do it, Diet A is definitely the fastest way to lose weight. If you want something that will help you lose a little weight and is easy to stick to, then try Diet B.
If the same doctor recommends a diet to his/her patients based on the ITT results, he/she would say: Follow whichever diet you want – they’re both the same.
Why, you may ask, could seemingly intelligent people do something so stupid as use ITT to evaluate data? There is a reason, although it has its own problems.
We all know from experience and from talking to a lot of people who have lost weight that a lot of different diets work. People lose weight on the Ornish diet and they lose weight on the infinitely preferable Protein Power diet. And many other diets as well. So, we can reasonably assume that almost any diet will help some people lose weight. But we want to compare two diets to see which one is really the best. So, let’s do another experiment.
Let’s take another 100 people and randomize them into two groups of 50, Group C and Group D. Those subjects in Group C go on Diet C and all of them do well. They lose an average of 2 pounds per week and all of them stay on the diet. The subjects in Group D go on Diet D, and most don’t do very well. As we all know from experience, it’s tough to stay motivated to stay on a diet if you’re not losing weight. So, 30 of the subjects in Group D drop out because they’re not losing. We know that any diet will work for some people, and Diet D is no different. The 20 who stay in the study are those who are losing on Diet D. And those 20 Group D subjects lose an average of 2 pounds per week.
In analyzing our data, if we remove from the pool of subjects all those who dropped out of the study, we are left with all 50 people in Group C, who lost an average of 2 pounds per week and only 20 people in Group D, who lost an average of 2 pounds per week. We would then find that both diets are exactly the same. Subjects in both groups lost 2 pounds per week. Therefore both diets are equally effective.
But is that true? Clearly not. And that is the problem that ITT was designed to deal with. But, as we’ve seen above, it brings its own errors.
So, how do we deal with the issue honestly and effectively? Easy. By explaining the data in two ways. Most people – researchers included – want to boil an issue down to a single answer, when two answers are required. ITT allows one answer – often incorrect – to two different questions. ITT is like the old TV show in which the clown Bozo always asked the little kids he interviewed something like this:
So, Bobby, tell me: Do you walk to school or carry your lunch?
Were Bozo adamant on an ITT-type analysis of the question, he could get only one answer.
Going back to our Group A/Group B diet study we can look at the data in two ways:
1. Diet A is extremely effective for those who stick with it. (Called the adherence effect.)
2. Only 40 percent of those attempting Diet A achieve the desired effect. (Called the assignment effect.)
Both of these statements are true. Both contain valuable information. But they answer two different questions. The first answers the question: what happens to people who stick to the diet? The second answers the question: What happens to people who are placed on the diet?
As Dr. Gerard Dallal writes about ITT
The fraud occurs when the answer to the question of assignment is given as though it were the answer to the question of adherence!
Instead of the conclusion that both Diet A and Diet B show the same results (when, clearly, they don’t), which would be the way it would be presented in a scientific paper demanding ITT, why not present it this way?:
The adherence effect: Subjects following Diet A for 8 weeks lost an average of 3 pounds per week whereas those following Diet B lost 1.2 pounds per week.
The assignment effect: 40 percent of those attempting Diet A remained in the study whereas 100 percent of those following Diet B remained in the study.
Conclusion: Diet A is significantly more effective (3 pounds per week vs 1.2 pounds per week) for those able to remain on the diet. Diet B is less effective but significantly less difficult to follow than Diet A. (100 percent of subjects on Diet B remained on the diet throughout the study whereas 60 percent of those on Diet A dropped out).
It just ain’t that hard to present it that way. It provides much more information than the ITT, which attempts to answer two questions with one answer.
Now, let’s look at the big low-carb lie that launched me into this post. I was reading a book that I intended to review for this blog and came across the following statement:
There is evidence from a variety of sources that [low-carb diets] work for short-term weight loss. One year after starting a diet, however, there appears to be no significant difference in success rate than that seen on any other common diet plan.
Have you heard that one before? It’s a specific variant of the old: Studies show that while effective in the short term low-carb diets show no difference in weight loss after one year than do low-fat diets. It’s the Big Lie.
It’s the last refuge argument of low-fat advocates who are getting hammered with all the data showing low-carb diets to be more effective. Yeah, well, they say, Protein Power may work in the short term, but over a year studies show it’s no better than low-fat. It’s like a cross thrust in a vampire’s face.
But is it true? It is if you believe in intention-to-treat analysis. But what if you believe in a more accurate way of presenting the data?
Let’s briefly look at a few studies published that confirm the idea that there is no difference between low-carb diets and low-fat diets after one year.
The first was published in the Annals of Internal Medicine in 2004. The conclusion of the authors was that after one year subjects
had more favorable triglyceride and high-density lipoprotein cholesterol levels on the low-carbohydrate diet than on the conventional diet. However, weight loss and the other metabolic parameters were similar in the 2 diet groups.
In the body of the paper, however, one can read the following:
The final 1-year weight change (mean ± SD) was -5.1 ± 8.7 kg in the low-carbohydrate group and -3.1 ± 8.4 kg in the conventional diet group (Figure). The difference in weight loss between the 2 diet groups was not significant (-2.0 kg [CI, -4.9 kg to 1.0 kg]; P = 0.195 before and P > 0.2 after adjustment for baseline variables). The difference in weight loss between the 2 diet groups between 6 months and 1 year was not statistically significant (P = 0.063).
But that’s all ITT blather. Let’s read the next couple of sentences:
Persons on the low-carbohydrate diet who dropped out lost less weight than those who completed the study (change, -0.2 ± 7.6 kg vs. -7.3 ± 8.3 kg, respectively; mean difference, -7.1 kg [CI, -11.6 kg to -2.8 kg]; P = 0.003). In contrast, weight loss was not significantly different for those on the conventional diet, whether they dropped out or completed the study (change, -2.2 ± 9.5 kg vs. -3.7 ± 7.7, respectively; mean difference, -1.5 kg [CI, -5.7 kg to 2.7 kg]; P > 0.2).
Let’s translate. Those who dropped out of the low-carb diet but were counted as if they hadn’t lost 0.2 kg (about 0.4 pounds) whereas those who completed the study lost 7.3 kg (about 16 pounds). Do you think the dropouts skewed the numbers? I guess so. And look at the next astounding sentence. “In contrast, weight loss was not significantly different for those on the conventional diet, whether they dropped out or completed the study…” So, there was no difference in the results of those following the low-fat diet whether they dropped out or stayed in. Had the subjects who dropped from the low-fat arm not been included, the results for that diet would have been the same. Including the subjects who dropped from the low-carb arm, however, dramatically lowered the overall weight loss of the subjects as a group, making them equal to those in the low-fat arm.
It could be accurately stated that those who remained on the low-carb diet for one year lost significantly more weight than those who remained on the low-fat diet. which, of course, refutes the Big Lie that low-carb and low-fat diets provide equal weight loss at one year.
The two other studies used to perpetrate the Big Lie that low-carb diets show no difference in weight loss after one year are the ones by Foster et al and Samaha et al in the May 2003 New England Journal of Medicine.
When analyzed by ITT, both of these studies show no significant difference between low-carb and low-fat diets after a year. But when looked at from the perspective of those subjects remaining in the study, we see a big difference between the low-carb and the low-fat arms.
In the Foster et al study using a modified version of the Atkins diet, we find a statistically insignificant 1.9 kg difference in weight loss between the two groups by ITT. But when we eliminate the drop outs and look instead at the data from those subjects who remained on the diets for the entire one year, we find a statistically significant 2.8 kg (over 6 pounds) greater weight loss in those following the low-carb diet.
In the Samaha et al study using the diet from the Protein Power LifePlan, those following the low-carb diet lost a statistically insignificant 2 kg more weight than those following the low-fat diet by ITT. Eliminating the dropouts, however, gives us a statistically significant 3.6 kg (almost 8 pounds) greater weight loss on the low-carb verses the high-carb diet after one year.**
Intention-to-treat analysis gives us the Big Lie: Low-carb diets are no more effective than low-fat diets after one year. Dr. Goebbels would have been proud.
The truth, however, is a little different and can be stated thus:
Those who follow low-carb diets for a year lose significantly greater weight than those who follow low-fat diets for a year.
After reading this post you should know more about intention-to-treat analysis than 99.9 percent of the physicians and dietitians practicing in the world today. Don’t let this knowledge go to waste. Next time you hear the Big Lie, point out the truth.
** Thanks to Richard Feinman, Ph.D. for the tabulation of these data and for our many conversations on this subject.
Great tutorial Dr. Eades. How did ITT become the standard for these trials? Was there something sinister happening, or are these people just morons?
They’re not really morons. They tried to get rid of the bias inherent in one way of doing a study and ended up adding bias in a different way.
That’s a very interesting description of what, I myself, have seen from real world experience. Thanks! But you left out the very important information on WHY the ITT skewed the low carb results.
It seems that either more people dropped out of the low carb study than the low fat study, or the dropouts of the low carb study regained more weight than the dropouts of the low fat study. Did I interpret that right?
If so, that’s an interesting observation that you should discuss and one I instinctively see in the real world. It IS harder to stay on the low carb diet, not necessarily because of the diet itself, but because of the social pressures and conveniences involved with the diet.
Try eating low carb on an airplane, or at 90% of all restaurants. Try deciphering the hidden carbs in so-called low carb salads and other meals in restaurants that contain invisible sugar. Try finding very many good low carb snacks. I remember 5 years ago during the “low carb” renaissance, when stores started stocking tons of low carb choices. Those days are gone. I miss my low carb, high fiber, bread choices from five years ago.
This social stigma issue goes back, of course, to your original point: the bias of the industry and the resulting effect on product availability. And to me, the biggest REASON for the anti-low carb bias is because of industry pressure. It’s no secret that the food industry makes FAR MORE profit off of high carb, grain based foods and “food-like substances” that can sit on a shelf for a year or more and have more cost invested in the packaging than in the contents.
Sigh!
ITT is the gold standard for clinical trials because clinical trials grew out of testing pharmaceuticals and medical devices. Ideally you would first give everyone the meds in a controlled environment and see how they worked when you knew for sure everyone took every pill and then do a second study under real world conditions and see how people would do following the regimen on their own. The first is an efficacy trial and the second is an effectiveness trial. It is kind of important to know if the medicine won’t work because people won’t take it due to outrageous side effects or too complex a schedule which is one reason for doing the effectiveness trial.
To me, if an effectiveness trial didn’t pan out the researchers job is not done. He/she or someone (science) needs to find out why and fix the treatment so it will work in the real world. That may be a matter of making a pill you only have to take one time a day instead of 5 or that may be a matter of providing supports for adherence. My guess is very few people-even people enrolling in clinical trials of diets go into them intending to restrict their eating for a whole year anyway. You wouldn’t say a blood pressure med worked less well than doing nothing if you only gave the blood pressure med for 6 months and 6 months later treatment and controls both had high blood pressure. You would say at the end of treatment we had X and then after treatment was discontinued the problem returned (duh!).
There are problems with using an ITT for many long term behavioral approaches. Ideally you could simply put 2 groups of patients on a 2 different diets under controlled conditions for a year and have your answer. Unfortunately that’s not possible so you do a study with free ranging people & monitor their adherence as best as you can. It gets even more dodgy because alot of times the novel treatments and controls produce differential attrition/loss to follow-up which can really foul up statistics. Many studies of behavioral interventions present ITT and a “completers” analysis but completers analysis suffers when one therapy or intervention results in a grossly shrunken sample at the end of the study.
As I see it, the only thing one could say about a trial of low-carb verses low-fat if analyzed by ITT is that if you are a subject randomized into the low-carb arm you don’t stand any better chance of losing weight after one year than if you are randomized into the low-fat arm. It says nothing about the effectiveness of either regimen for those who follow them for the entire year.
This is so disconcerting Dr. Eades. There seems to be no end to this crap. I guess reality is only what you perceive it to be. Thank goodness there are people like you and Taubes with the calling and determination to set the record straight. I just hope you don’t tire of it for a while. Thanks again.
Also I must say there’s “fraud” if a program (whatever it is-bootcamp, fatcamp, drug rehab) holds itself out to the public as a great program and bases this soley on data provided by completers.
You really need a randomized trial to control for personal preference and other biases people have that might make a treatment appealing to some people and not others. Then you can look at mediators of outcome like individual differences or personal preferences or other factors that might predispose some people to do well and others poorly. For example, I love this WOE but it would be very hard to do if I was being supported by public assistance given that the foods available through programs like WIC tend not to be low carb…I have a feeling that alot of lower income people would have to be very creative to pull this off for a whole year. Finances might be one of the reasons for the lack of long term adherence by some people.
Point taken, but I don’t believe it’s fraud if you can show that people who stick with the low-carb program are more successful than those who hang in there with low-fat.
I believe you’re wrong about welfare based on what my mom and my daughter told me. Mom used food stamps for a couple years while my dad was trying to get his degree, and my daughter used them while she was working on HER degree.
both told me that for a person who was well versed in cooking and serving whole homemade foods, food stamps provides so much that you could either buy steak for at least twice a week as well as other meats during the rest of the week (daughter) or (back when you had to pay a percentage of the food stamps to receive them {Mom}) only purchase them only once every two months and stretch them to last two months.
A thinking person who was educated in cooking and eating whole foods could eat low carb on welfare, they’d just have to plan it and work it.
And those of us that must live and die by peer reviewed and evidence based and provide appropriate patient care are in a word ….
The good news is that education is the absolute key. If we don’t keep telling the truth about the risks and benefits of all or nothing solutions, groups like ours, won’t exist. Thank you for being willing/able to “put it out there.”
Another great explanation of all the shenanigans that go on in the medical study industry. This an your others posts on similar subjects have been invaluable. Very easy to follow.
Thanks so much!
It seems like the researchers are aiming for a nice concise one or two sentence conclusion that they can release to the press. That way, they can get their name in the paper and have a nice little quote for their next grant application.
However, I think an ITT analysis should be included because it raises another question. Why did the study participants drop out? The authors never discuss this. I could design a very effective diet that no one would ever follow…
Nor do they seem to discuss any of the other beneficial effects of the low carb diets, only weight loss. Even then they mention how low carb diets encourage fat loss, not lean muscle mass loss.
Thanks for the ammunition! It’s becoming more and more valuable to me personally. I just had my 3 month checkup at the endo this last week. Not a single complaint about my diet and in fact compliments on how well I am managing this 800 lb gorilla aka diabetes with this as expensive as a small car insulin pump.
I share alot of your information with the docs and they are asking for books now….
Just a side note. The drug rep was in the office waiting to see the doc with new samples of the combined statin and some other drug pills. I struck up a conversation with her and eventually told her that I wouldn’t touch that stuff again for a million bucks. I told her all about the memory loss and other side effects I suffered. There was a obese man sitting close by who said he wished they would work for him but they don’t. I got to talk a bit about low carb diet and the benefits. The drug rep then started taking notes and I asked why…she said she had to report everytime someone had an adverse reaction to the drug even if she just heard about it in the waiting room….
I should talk to more drug reps….lots of them…on a daily basis….
Ressy
Not so sweet today Evil Fabric Queen
Thanks, great explanation!
While you’re on a roll debunking studies, what about this one that’s getting headlines today claiming that the Western diet causes more heart attacks? My intuition tells me there’s something fishy about the study but I can only get the Abstract, not the whole paper.
Dietary Patterns and the Risk of Acute Myocardial Infarction in 52 Countries. Results of the INTERHEART Study
Circulation, Oct 2008;
That’s an easy one. It’s an observational study, and it’s impossible to determine causality from observational studies. Everyone does it when it suits their interest, but the fact is that causality can’t be determined. Even if it could in this study (which it can’t), the correlation still isn’t very strong.
This is an extremely useful post, Dr. Eades. Thank you. It would be nice to see it published again as a chapter of a book or article in a mainstream science magazine.
You are very good at explaining things in a way that “regular” people can understand. Your talent for this reminds me very much of Isaac Asimov’s, which is the highest praise I know for this type of writing.
Just a little nitpick (I haven’t read the post entirely yet). It is spelled ‘de rigueur’ with a u before and after the e. The first u is for “hardening” the g and doesn’t give a sound from itself. The second u is part of the diphtongue ‘eu’ which sounds like the ‘ea’ in ‘I heard what you said’
Thanks for the heads up. It didn’t look right when I wrote it. I’ve made the change.
I would have no problem with an effectiveness study for lo-carb vs. low-fat except that in the real world, the patients are constantly bombarded by advertising, news, friends, and colleagues all warning them of the dire consequences of being on a Low carbohydrate diet. Those on a low fat diet would receive the opposite — reinforcement from all directions. Hardly an unbiased test environment.
Also, in this Canadian study they group people in three categories: those who eat soy and tofu, those who eat fruit and vegetables and those who eat fried foods, salty snacks, eggs and meat. Talk about bias!
I wouldn’t be surprised if the whole thing was underwritten by the soy producers. The bottom line of study is the ‘healthfulness’ of replacing eggs and meat with soy products, because you gotta have protein, don’t you? The fruit and veg thing is a no-brainer (well, more or less).
Why don’t they compare people who eat a lot of soy, fried foods and salty snacks to people who eat a lot of eggs, meat and vegetables?
Perhaps they would be afraid of what they would find.
The low fatties just can’t admit that their diet is less effective that low carb. They have to resort to statistical manipulations to “show” that low carb is no more effective than low fat.
I don’t think they resorted to statistical manipulations – they simply went with what is required now days for determining the outcomes of studies. It’s the ITT form of analysis that is idiotic. The fact that researchers are virtually required to use it is even more idiotic.
No wonder I dropped out of college statistics. I’m glad I’ve stuck with the diet, though. It’s been over a year and I’m approaching goal. How’s that for efficacy and effectiveness?
Good job! Congrats.
Here’s a quote feom a media article on the InterHeart study that found a diet high in red meat and fried foods caused more heart attacks.
“Those who scored high on the “Western” diet were 35 per cent more likely to have a heart attack versus those who ate little or no fried foods and meat.
“Most people in North America would think of french fries, pizza and potato chips as the big offenders here,” says co-author Dr. Sonia Anand, professor of medicine at McMaster.
“That’s true, but we also include into that things like samosas and pakoras and fried won ton so that this message applies generally to people from India, people from China – that deep frying is not good for you.”
It’s probably due to the type of fat used for frying and salty snacks, the researchers report in Circulation: Journal of the American Heart Association. Saturated fats can raise blood cholesterol.”
Say what? The article lists off a bunch of foods that are fried in toxic vegetable oils and then caps it off by implying that they are fried in saturated fat!
Yep, thanks to the saturated fat phobes almost everyone fries stuff in vegetable fats/trans fats, yet saturated fats get the blame.
More reason to ignore all those “studies show blah blah blah” that turn up everywhere in the media these days.
You got it.
Thanks for the disambiguation, Dr Eades.
In my opinion, adherence to a program is perhaps more important than the effectiveness of the program yet effectiveness is also a factor in its adherence.
For people to adhere, the program must be easy to do, easy to understand and must fit existing environment. The environment isn’t conducive to low carb so that makes outcasts of us. We don’t want to be outcasts. Social interaction is a strong incentive to do or to not do something. The environment doesn’t limit itself to social interaction however. It also includes the media which is shock full of ads for carbohydrates of all kinds. There’s would be gurus pushing high carb healthy stuff all day long. There’s a contradiction between the healthful benefit of a low carb diet and a high carb diet. Without knowing which is true, I’d go with the most popular. At this time, the most popular is low fat high carb.
Then there’s the addictive qualities of carbohydrates. Then there’s the abundance of carbohydrates everywhere we go. All of these combined is a recipe for continued failure. Failure to maintain weight. Failure to adhere to low carb. Failure to return to good health. I would not be surprised to learn that low carb diets are the most difficult to adhere to.
But the point I was going with is that if at first we don’t succeed (in making people stick with the program) try again until we succeed. It’s naive to think that a single trial can give us the answer we seek in that matter. Especially considering all the variables that affect adherence.
Wasn’t ITT a response to the problem of investigators’ introduction of bias through their exclusions of study individuals (either before, during, or after the study, either accidental or not)?
I think getting rid of ITT would potentially corrupt and bias things even further.
I think using ITT often increases bias. What’s wrong with simply answering both questions – effectiveness and adherence – rather than trying to shoehorn two questions into one answer? That’s what has been done with the BMI in an effort to simplify things.
Thanks for the hundreth time for a great blog post! As one of the average joes who used to get my health news from the today show I am so glad to have found your blog and other sources of health information. ITT is useless to me. When i research a diet all I need to know is how much weight will I lose if i stick with it. I know da**ed well if i stop I won’t lose. ack
I enjoyed your blog here Dr.Eades. I know I’m a litle off-topic here .I don’t know who or how you upset somebody recently ……..but I want to inform you that your Protein Power website was banned from at least one corporate multinational oil company servers(company firewall),I believe by company medical staff.I also believe that it is something personal ……as I can access any other low carb sites without problem(Atkins…etc.) ……and happened recently(september ,before was ok)
Regards
I haven’t got a clue as to what happened or why? Maybe you should ask them.
Hi Dr. Eades:
I was wondering if you read the paper posted in Medscape this week entitled
“Low-Carb/High-Fat or High-Carb/Low-Fat Diet Improves Weight Loss, Mood” in which they found that a low carb diet was superior to a low fat diet in terms of weight loss, but that the low fat diet was associated with a greater improvement in speed of cognitive processing. I find this interesting, because my ability to focus greatly improved on a low carb diet as compared to high carb. Thanks for the post.
Olga
Haven’t read it yet. I saw the Medscape piece, but haven’t had a chance to look at the actual study. I find it hard to believe, however, just as you do.
Thanks a ton for bringing us another excellent post. You have a very good knack of explaining technical jargon in a way that non-medicos can easily understand.
Esp the protein power life plan book and these blog posts – wonderful and excellent.
I cannot believe a process like this will be used to mess up the results. Simply put – remove ITT and provide 2 answers as you have suggested.
Thanks once again for your service.
I’m glad you’ve enjoyed the information.
Hi Michael,
I’m sure you’re busy on your new big thing… if you have 2 minutes would you be so kind as to fill in my understanding on these two things please:
1. When one has depleted glycogen stores (such as when on a low-carb diet for an extended period)… what happens if you suddenly ingest a big quantity of carbs? Does excess blood glucose go first to glycogen? Or is it possible to gain fat (shift in the equilibrium of fat into and out of cells) even with depleted glycogen.
2. What happens to excess dietary protein? It obviously does not necessarily get stored as muscle mass as otherwise ingesting high amounts of dietary protein would lead to muscle gain without resistance training. And I presume every after resistance training, there is a maximum amount of protein used in protein syntehis… some used for gluconeogensis if blood glucose levels are getting low and glycogen are low… where does the surplus go? Do it get converted to FAs and glycerol?
I’ve looked for these answers everywhere and can’t find a good overview of glycogen storage that covers this aspect. Would you be able to point me in the right direction please?
Many thanks Michael. I really appreciate it,
Michael
The intake of excess carbs in your first example (those beyond the amount used for energy productiob) would go first to glycogen, then to fat. And probably would do some of both simultaneously.
Excess dietary protein can be converted to sugar (if the body needs it due to low-carb intake) and can be used as a source for other nitrogen-containing body substances (of the three macronutreints only protein contains nitrogen). Any excess is deaminated ( a process whereby the NH3 is removed), leaving a carbon skeleton that can then be treated just like a fat or carbohydrate and burned for energy.
Hello Dr. Eades: I have a question: are carbohydrates really necessary? I mean is it possible to eat a diet real low in carbohydrates like 10 to 20 grams a day? or should do we need more carbohydrates than 20 grams a day? like 40 to 50 grams a day? I mean can we get our glucose and energies straight from the protein and fat we eat? Because some people state that a diet real low in carbohydrates leads to sluggishness and tiredness.
Thanks, and i would like your comments on this
low-carber
We don’t need any carbohydrates for life. There are no carbohydrate deficiency diseases. The same can’t be said for fat or protein.
So walking burns 400 calories an hour. While stationary-bike 500 per hour
Hi Dr. Eades:, i found out that stationary-bicycling or regular bicycling burns a lot more calories than walking. But some people claim that walking burns more than bicycling, because when you ride a bicycle or stationary bicycle you are sitting down, and walking is standing up. I really don’t understand why then most exercise calorie calculators state that bicycling burns more than walking.
Here is the link of the calories-burned calculator for each sport activity:
http://www.healthstatus.com/calculate/cbc
Hey Doc,
Off subject but I know you are interested in the Laws of Thermodynamics. Here’s an article from Scientific American on it, not sure how accurate it may be but looked interesting. http://www.sciam.com/article.cfm?id=how-nature-breaks-the-second-law
I read it on the plane a few days ago. It was pretty interesting, but didn’t apply much to diet.
Mike
Even using the unusually high standards for quality we’ve come to expect from your blogs, this one is a standout.
Jonny Bowden, PhD, CNS
Hey Jonny–
Thanks for the compliment. Realizing this goes on sure makes a difference when you’re trying to analyze medical papers.
Best–
M
Thanks for the ITT explanation! Like so many, I read medical abstracts (ahh, this strange hobby I’ve developed since my health starting going ‘south’) and often find the ‘conclusions’ at seeming odds with what little methodology is described — now it will likely make sense…that is, if anyone can say that interpreting results a la ITT makes any sense at all *G*. Thanks for the heads up on this bizarre ‘reasoning.’
You should never take what the abstract of a medical paper says to be a summary of what the actual body of the paper shows. You might be interested in reading a post I wrote a few years ago called Baboon Business about the art if dissecting medical studies.
First one must determine WHY the subjects withdrew from the study. Your assumption was that one diet was more difficult to follow than the other. This may be true, or maybe there was another reason. In clinical drug trials, side effects and tolerance are two factors which impact compliance greatly and as suggested earlier those factors should be assessed early on. Next, I’m not convinced that an ITT was appropriate for the diet study to begin with. Most ITT studies are clinical drug based studies where compliance is not necessarily based upon the subject/patients self motivation. Any study which includes ‘psycological’ factors is very limited in terms of ITT. ITT studies are quite suited for ‘objective’ treatments such as dose response studies but not so for more ‘subjective’ studies. Let’s not throw the baby out with the bath water but rather let’s use the tool in an appropriate manner. Rather than bashing let’s educate researchers on the appropriate way to use the tool.
I’m all for that. If it truly is a valuable tool. I’m just not yet convinced that it is.
When I went to the original study, it spent much more time looking at the model used for anticipating data than the actual (or actual plus manipulated) data itself. The model they used based on prior studies, I assume, understated the difference between the diets and understated the amount of weight lost especially at the earlier time points of the study (when the low carb group was actually on a weight loss diet.) Using the “minimum trajectory” of that model for the dropouts definitely understated the effect of the two diets.
And that is before considering that most of the low carb group which was instructed to add 5 carbs daily eachr week after week 12, were on maintenance or a weight-gaining diet for three quarters of the study.
I have an analysis of the study with a link to the actual study at http://www.acupuncturebrooklyn.com/alternative-health/two-year-low-callow-carb-diet-study-misleading