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Sabtu, 30 Juni 2012

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Hat tip to Colby Vorland (@nutsci) via Twitter: New fuel for the calorie debate

This is the blog of one Carson Chow -- half of the dynamic duo who set one Mr. Gary Taubes straight for once and for all about glycerol-3-phosphate -- and routinely puts the man to shame. Oh ... but let it never escape your mind that Chow is *young* ... I hear he's even more *young* than I am *female*!!

In any case, Chow picked up on something that I missed in my obsession with the statistics. The average TEE's measured by doubly labeled water were: LF / LGI / LC = 2812 / 2937 / 3137 (by FQ) and = 2767 / 2926 / 3013 (by RQ). The average caloric intake was 2626 calories per day. This was less than each of the average TEE's for each diet by either measure. By a minimum of 140 calories per day, to over 500 calories per day. On average, everyone would have been in caloric deficit and lost something over 12 weeks, yet they didn't lose weight. Heck, I suppose that's something for the CDS sufferers to hang their hats on. Chow seems to attribute this more to error in TEE measurement, and I'll add that cheating cannot be ruled out either.

Oh ... interestingly enough, they reported energy intake as is customary, Mean (SD) -- 2626(686). But no such transparency for EE's which are reported Mean [95% CI Range]. Sigh.

And oh again ... re-reading, it was the other half, (rumor has it he's still young too), Kevin Hall, that picked up on this.

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This started out as a comment on my last post, but got a bit lengthy so I decided to make it a full post. I also addressed some issues with this study in another post those only interested in this study might have missed based on the non-descript title. Let me start by saying that I did a fair amount of updating on my last post after reading the supplemental materials, and as a result I have some new criticisms of this article, and most of my original concerns remain. So we're all on the same page, here's the study, and here's the Supplemental PDF.

Many are treating the results of this study as if it were conducted in a metabolic ward. This is not true, it was a free-living study except for 3-day hospitalizations for analyses. Now it wasn't your usual free-living study in many ways: Participants were paid and had all food prepared for them for the duration of the study (added all up, a little over 7 months!). Monday through Friday they ate one meal a day at the facility. Daily diaries were filled out documenting any "cheats" or foods left uneaten. They received counseling if they had difficulty complying with the diet. It is unclear, but it seems they were weighed daily, at least during the various 4-week weight stablizing/stable legs. Body composition by DEXA was only assessed before and after the weight loss phase. TEE (by doubly labeled water method) was assessed over the last two weeks of the 4-week pre-weight loss and test maintenance diet legs, activity was assessed by accelerometer for 7 days (it is unclear which week, I'm guessing the 4th week) for each test maintenance diet. REE was measured by indirect calorimetry. Intake was ramped up during the first 4 days of the stabilizing phase and subjects were weighed daily and caloric intake adjusted accordingly. Here's an important little piece of information in this regard from the supplemental materials: "We allowed the duration of the run-in phase to vary among participants, to account for individual differences in the rate of weight loss." And: "The energy intake required for weight stabilization at the end of the run-in phase was established as the energy intake for the entire test phase, with no further adjustments regardless of any weight fluctuation with the test diets."

A Friday JAMA-lama Ding Dong!

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Well ... I wasn't really going to weigh in further past using that recent JAMA article (EDIT: full text no longer free at JAMA, see link below) as an example of where statistics can lead us astray. But ... as is probably expected, this study has kicked up some dust in the community. I'm sure I'll miss a few, but here's the weighing in so far:

That's just the blog posts, not the tweets, FB postings or other social media buzz ... and I'm happy to edit in more, just drop the hint in comments. And here's the full text of the study: Effects of Dietary Composition on Energy Expenditure During Weight-Loss Maintenance

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In this installment, we reunite with our old friend C3KO mouse to learn a little bit more about the role of acylation stimulating protein, ASP, in the regulation of fat tissue (and muscle) from this study: Differential regulation of fatty acid trapping in mouse adipose tissue and muscle by ASP. The C3KO mouse was discussed in Part II of this series. This mouse lacks the gene to produce a protein called C3 (short for Complement 3) which is a precursor for the formation of ASP. Thus C3KO mice are ASP deficient. The C3KO is to ASP as a type1 diabetic is to insulin. These mice are also resistant to obesity. BTW, hyperASPemia accompanies the hyperinsulinemia and hyperleptinemia of obesity when it's measured.

ASP-deficient mice have delayed postprandial triglyceride (TG) clearance and reduced WAT mass. The objective of this study was to examine the mechanism(s) by which ASP deficiency induces differences in postprandial TG clearance and body composition in male KO mice.

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A new study in JAMA led by Dr. Cara B. Ebbeling and colleagues purports to challenge the idea that all calories are equally fattening (1). Let's have a look. When thinking about the role of calorie intake in body fatness, there are basically three camps:

1.    Calories don’t matter at all, only diet composition matters.
2.    Calories are the only thing that matters, and diet composition is irrelevant.
3.    Calories matter, but diet composition may also play a role.

The first one is an odd position that is not very well populated. The second one has a lot of adherents in the research world, and there’s enough evidence to make a good case for it. It’s represented by the phrase ‘a calorie is a calorie’, i.e. all calories are equally fattening. #1 and #2 are both extreme positions, and as such they get a lot of attention. But the third group, although less vocal, may be closest to the truth.
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With the advent of, and inexpensive nature of online sharing of information, I propose that all peer-review research should include (anonymous) raw data for each subject. At the very least, there should be scatter plots presented for the individual data points for the main outcomes.

I frequently teach statistics, and one of the first things we discuss in that class is sort of the "first purpose" of it all. Because before we can analyze data, first we must summarize and present the data in such a way that the "consumer" can readily glean information. In one classic stats text -- Triola -- this part is given the acronym CVDOT. C = Center, V = Variation, D = Distribution, O = Outliers and T = Time. So we go through the various ways we can convey the center of a data set, it's variability, distribution, etc. In most of the studies we discuss here, data is presented as a mean value +/- either the standard deviation or standard error (C +/- V in the acronym). And further statistical analysis compares these means between groups for statistically significant differences. If I have 20 subjects in a study, I can provide you with a table of all results sorted by subject number assigned randomly. This tells you very little. If all I do is sort the data ascending or descending, you can now readily pick out the range and "center" of the data. Perhaps if data is of a more rounded nature, you might be able to pick out the most frequent or common values. Outliers will jump off the page.

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This may seem like sour grapes, but... Numerous media reports say that the US Supreme Court has upheld the massive US health care "reform" law (look here for Reuters coverage today, and here, for the Los Angeles Times, for example). In my humble opinion, the law will likely increase acess to commercial health care insurance, although will likely not reduce the expense of such insurance, or address the misbehavior of many large insurance companies (for example, see our series of posts on Aetna, UnitedHealth, WellPoint, and the insurance industry in general, etc, etc).

The law, as we summarized here, does contain a few provisions relevant to the concerns we raise on Health Care Renewal. These include measures to improve disclosure of certain kinds of conflicts of interest affecting individual physicians and health care academics, and improved funding for comparative effectiveness research. We hoped that the law would lead to a more rational way to fix payments to physicians that might supplant the secretive, procedure-happy RUC, but so far that hope remains unfulfilled.

However, as we wrote in 2010, the legislation will leave most of the other problems we discuss on Health Care Renewal untouched. We thus have one or two small steps for mankind in the US, but no reason for complacency.

The news is not bad. We are probably on balance somewhat better off with some health care insurance reform than none. However, we are still a long way from meaningfully addressing concentration and abuse of power in health care. There will be no rest for the weary bloggers of Health Care Renewal.