las

Welcome all seeking refuge from low carb dogma!

“To kill an error is as good a service as, and sometimes even better than, the establishing of a new truth or fact”
~ Charles Darwin (it's evolutionary baybeee!)

Sunday, December 9, 2018

The $12M NuSI/Ludwig Study ~ Part III: Some "Early" Lessons


SUMMARY




Continuing on with discussion of:
Effects of a low carbohydrate diet on energy expenditure during weight loss maintenance: randomized trial

In Part I, I discussed some issues with methodology, mostly focusing on the reduced Run-In Phase that likely compromised the outcomes irreparably.

In Part II, I highlighted a serious issue with the Run-In Phase, the purpose of which was to produce a somewhat homogeneous "reduced weight state" to test various diets in maintenance of that state.

Ultimately, since randomization to the various test diets occurred after weight loss (PWL) randomization to maintenance test diet would not influence the impact of various BSL (pre-weight loss baseline) measures on the Run-In outcome -- target = 12% ± 2% weight loss -- on a standard composition diet for all:  45% Carb / 30% Fat / 25% Protein. 

The researchers appear to have made minimal adjustments, if any, during the Run-In Weight Loss so as to produce a more uniform result.  Rather, the result was a wide range of weight loss (5.6 to 16.0%, roughly 10.5% ± 5%) . 

Thus we have an "accidental" test-within-a-test of the CIH/TWICHOO from these "early" results.

In the end, I offer these scatter plots for all 105 subjects who successfully completed the study, for whom complete data for insulin measures and energy expenditure were available at all time points. 


The Carb-Insulin Hypothesis (aka TWICHOO) predicts that weight loss will vary inversely with insulin levels:  The higher the insulin levels, the lesser the weight loss.  The Run-In Phase data supports no such relationship (indeed, if anything, absolute weight loss was greater for those with higher baseline insulin measures.

Meanwhile, differences in weight loss are easily explained by variation in caloric deficit during the calorie restricted Run-In due to coarse estimation of baseline energy expenditure (vs. rigorous measure). 

This post expands on some relationships of baseline (BSL) and post-weight loss (PWL) measures as observed during the weight loss portion of the Run-In Phase.

Bottom Line:  Baseline insulin status seems to be irrelevant to weight loss on a "high carb" calorie-restricted diet.  





The study in question had two phases, a weight loss Run-In Phase, and a dietary intervention weight maintenance Test Phase.  As such, there are four major time points for data collection, involving two different "baseline" measures.  In the data files from which I obtained the data for the plots in this and other posts, these are:
  • BSL = Baseline = Pre-Run-In.  As the doubly labeled water assessment of total energy expenditure began on "Day 1", it is fair to say that these measures are of the subjects "off the street".  
  • PWL = Post Weight Loss = last two weeks of Run-In.   Following 10 weeks on a calorie restricted (60% of estimated energy requirements)  45%C/30%F/25%P composition diet, subject intakes were increased to stabilize the reduced weight.  DLW and other measures were made during these two weeks.
The Test Phase involved 20 weeks consuming weight-maintaining caloric levels of one of three test diets, 20% protein and varying in carb from 20% to 40% to 60%.  Data was collected at:
  • MID = Midpoint = 10 weeks.  DLW-TEE data was gathered in weeks 9 and 10.
  • END = End (grin) = 20 weeks.  DLW-TEE data was gathered in weeks 19 and 20.
The major "finding" of the study was a reported average increase of ~210-280 cal/day in total energy expenditure (TEE), depending on whether intent-to-treat (ITT) or per-protocol analysis.  In a late hour change, these findings use PWL as "baseline" instead of the originally slated BSL measures.  When subjects were divided into tertiles (thirds) of the BSL measure of Ins-30 (described later in this post), a comparison between the LOW and HIGH carb diet groups in the highest tertile of Ins-30 produced a "metabolic advantage" of some ~310-480 cal/day.   That latter figure being most *unbelievable*! 

So let's take a look at some of these tertiles -- both at true baseline, BSL, and the post-weight loss, PWL, test phase start point.





A note about all plots in this post


Subjects:   My analyses are for only those subjects who completed the trial successfully (maintained weight to within ± 2 kg of PWL weight) for whom there is complete 4 time point data for all energy and insulin measures.  This involves:  105 Total , 40 LOW carb, 35 MOD carb, 30 HIGH carb.  

Colors:    Gold = LOW , Blue = MOD , Green = HIGH , Gray = All
Diamonds are means, Turquoise diamond lines represent mean of all subjects

Tertiles:  (split to balance high and low for uneven sized tertiles)

T1 = Tertile 1 = Lowest Third:  lowest 13 for LOW, 12 for MOD,10 for HIGH , lowest 35 for ALL
T2 = Tertile 2 = Middle Third:  middle 14 for LOW, 11 for MOD,10 for HIGH , middle 35 for ALL 
T3 = Tertile 3 = Lowest Third:  highest 13 for LOW, 12 for MOD,10 for HIGH , highest 35 for ALL 

There are two plots side-by-side.  

  • Left displays tertiles within diet intervention groups, each grouping is T1, T2, T3 and ALL for each diet.
  • Right compares each tertile between diet interventions, groupings are T1, T2, T3 and ALL 


A note about statistical significance


As one can imagine, this endeavor has already been rather time consuming, and at this time I am not in a position to assess the statistical significance of any of the trends in the various plots I'm sharing.  In many cases, the lack of trend supporting TWICHOO  (Taubes Wrong Carb-Insulin Hypothesis Of Obesity) is more than sufficient, there is no need to statistically quantify it!





It's The Insulin, Stupid?


The remainder of this post will deal with the "I" part of the original hypothesis.  Insulin regulates fat mass, and higher insulin, as stimulated by carbohydrates, traps fat in the fat cells so that the rest of your cells are starved of energy and cannot burn the fat.  

At baseline, the investigators measured insulin in two contexts:
1.  Fasted insulin levels -- basal insulin levels.
2. Insulin-30 (Ins-30):  insulin response at 30 minutes after a standard oral glucose tolerance test (OGTT). --measure of insulin secretion in response to dietary carbohydrate.

As the hypothesis goes, repeatedly raising insulin with dietary carb results in elevated insulin virtually around the clock -- your fat is locked up and can never get out.   Eliminate the carbs and your insulin levels will finally drop low enough for your fat cells to give up their stores.  Atkins even once described this lipolysis to be "as delightful as sex and sunshine"!  

The increased energy expenditure being touted more of late is hypothesized to be in response to this glut of fat available to burn!   So isn't it odd that, for everything measured ...
Neither fasting insulin levels, nor Ins-30 are measured at any point after BSL baseline.
At LEAST fasting insulin should have been measured, especially considering that the hormones ghrelin and leptin WERE measured.



Tertiles of Baseline Insulin-30



Below are the Ins-30 levels (BSL) plotted according to the tertiles of those same Ins-30 levels.  The mean Ins-30 for the highest tertile of all subjects was roughly four times that of the lowest tertile.  Also of note, there is a far wider range of Ins-30 levels within the highest tertile than within the lowest two tertiles, either individually or combined. 

BSL Ins-30 levels by Tertile of BSL Ins-30 levels

While it is unlikely that differences of the means rise to statistical significance, given that most comparisons in the analysis are between LOW (gold) and HIGH (green), there are some distribution differences worth noting.  By the way, at any time you can click on images to zoom in and take a closer look.   Some in the middle tertile of the LOW group have higher than all-mean Ins-30 levels, while all of the middle tertile of the HIGH group are "safely" below this mean.  Further, some of the highest tertile HIGH group are still below all-mean Ins-30 levels.    While these two groups have comparable hyperinsulinemic outliers, it is fair to note that the subjects randomized to the LOW carb intervention were more metabolically "damaged" than those randomized to the HIGH carb intervention. 

It would have been nice to have this measure as a post weight loss "baseline", as most would agree that weight loss will have the greatest effect on insulin dynamics in those who have some degree of metabolic dysregulation.  Ludwig has now argued strongly for why the pre-weight loss BSL energy expenditures are less appropriate as an "anchor" with which to compare the responses to test diets, and indeed his analysis uses the post weight loss (PWL) values.  I would argue that whether you agree or not, one can't have it both ways.  If PWL energy expenditures are a more appropriate baseline anchor, then so too would be PWL Ins-30 levels.  Only we don't have those!  [snarkasm] So much for that meticulous study design? [/snarkasm]

TWICHOO, or the Carbohydrate-Insulin Hypothesis, as even put forth in Ludwig's 2016 mass media diet book Always Hungry, predicts that carb-spiked insulin will sweep energy out of circulation and shuttle it off to the fat cells, leaving other cells starving for energy.  This cellular starvation -- sometimes called "internal starvation" -- will cause a person to become hungry and eat more.  Sounds somewhat plausible, but as such, TWICHOO predicts that those in the highest tertile of carb-stimulated insulin production would have the most trouble adhering to a calorie restricted, high carb diet, and would thus lose the least weight.   Let's see how that shook out, shall we?

Below are the plots of absolute weight lost (in kg) during the 10 week Run-In according to BSL Ins-30 tertiles. 

Weight loss (kg) during Run-In by Tertiles of BSL Ins-30

Despite secreting roughly four times the insulin in response to carbohydrates, there is a trend towards increased absolute weight loss in the higher tertiles compared to the lowest ones.  For whatever reason, this randomly shook out to be most profound in those who were randomized to the LOW carb group.  This does not seem to persist, however, when weight loss is expressed as a percentage of initial body weight as shown below. 

Weight loss as percent initial bodyweight during Run-In by Tertiles of BSL Ins-30
It is fair to say that there is no favorable trend in Ins-30 between highest and lowest tertiles that supports TWICHOO.  Meanwhile the fact they all lost weight on a high-ish carb reduced calorie diet regardless of insulin status provides evidence against it.   Both the biggest loser (16.0%) and the the smallest loser (only 5.6%) had Ins-30 responses near the median for all subjects.




Tertiles of Baseline Insulin-30 & Fasting Insulin (Ins-Fast)



Critical to TWICHOO is not only an exaggerated insulin response to dietary carbohydrate, but that somehow this leads to chronically elevated insulin levels -- basal insulin secretion measured in the fasted state.  Again, the idea here is that not only do postprandial insulin spikes lock away fat, but insulin remains elevated virtually 24/7 making it practically impossible to burn stored body fat for fuel. 

I have repeated the above graphical analyses for the tertiles of BSL Ins-Fast, but to segue to that, I have compiled two sets of plots illustrating the relationship between BSL Ins-30 and BSL Ins-Fast for the subjects in this study.   First, below, are Fasting Insulin levels for the tertiles of BSL Ins-30.


BSL Ins-Fast levels by Tertiles of BSL Ins-30

As expected, there is a trend towards higher mean fasting insulin from lowest-to-highest tertile, but there is also wide overlap between Ins-Fast levels across the three tertiles of BSL Ins-30, particularly at lower levels.  This is consistent with the etiology of both fasting and postprandial Ins-30 having related but causes but great individual variation in the manifestation of basal vs. postprandial hyperinsulinemia. 

I would note that, again by random "luck", this relationship appears to be strongest in the LOW carb group and is dominated by what is seen in the highest tertile of BSL Ins-30.   While the BSL Ins-30 distributions seem to indicate more metabolically dysregulated subjects among the LOW carb group, the elevated  BSL Ins-Fast in the third BSL Ins-30 tertile are a stronger indication that the LOW carb group has more metabolically dysregulated subjects.  What effect this had on the primary outcome (total energy expenditure in reduced-weight maintenance) is a topic for a future post.

And now, I flipped the insulin measures.  Below are the BSL Ins-30 levels grouped by tertiles of BSL Ins-Fast.

BSL Ins-30 levels by Tertiles of BSL Ins-Fast
I'm not sure there is much to add with this "flip", similar trends can be seen from lowest-to-highest tertiles, but again, there is wide overlap at the lower levels of BSL Ins-30 across the tertiles. 

Perhaps the best way to put a bow on this are the scatter plots below of Fasting Insulin vs. Insulin-30 at baseline.  The plots are for each diet group separately, and all subjects.  Horizontal and vertical dashed lines are means for all data, and diagonal dotted line is the linear regression fit line for all data.

Scatter plots of BSL Fasting Insulin vs. BSL Insulin-30
By diet group and all subjects , Mean and Fit lines are for all subjects in each plot



Tertiles of Baseline Fasting Insulin



I'm going to round out this presentation of insulin-related plots by presenting the same plots using tertiles for BSL Ins-Fast = Baseline Fasting Insulin, in the same manner as I did previously with BSL Ins-30. 

Below are the Fasting Insulin levels (BSL) plotted according to the tertiles of those same Ins-Fast levels.  Here there is an even wider range of Ins-Fast levels within the highest tertile than within the lowest two tertiles, either individually or combined, where the range of Ins-Fast levels is strikingly narrow.  Despite the greater variation, the highest tertile mean is not quite double that of the mean of all values.


BSL Fasting Insulin levels by Tertile of BSL Fasting Insulin levels

We again see a trend where those randomized to the LOW Carb group have a more pronounced difference in Fasting Insulin levels in the third tertile compared to other diet groups, and a higher third tertile mean Ins-Fast level.

So how did weight loss on a high carb diet shake out vs. these baseline values and tertiles?  Below are the plots of absolute weight lost (in kg) during the 10 week Run-In according to BSL Fasting Insulin tertiles. 

Weight loss (kg) during Run-In by Tertiles of BSL Ins-Fast
Despite the higher basal insulin levels trapping fat hopelessly away, there's an even more pronounced trend of increased liberation and oxidation of fat as across the tertiles from lowest to highest.   And for weight loss as a percentage of initial weight ...

Weight loss as percent initial bodyweight during Run-In by Tertiles of BSL Ins-Fast

Once again, any trend tends to be ameliorated when measuring weight loss as a percentage of initial weight, however the lack of effect is still evidence against TWICHOO.  The wide ranging elevations in fasting insulin seen in the third (highest) tertiles should have been sufficient to limit weight loss.  Rather, it was a caloric deficit that produced weight loss.




A Final Smattering of Scatterings



Since randomization to maintenance test diet occurred after weight loss on a common diet, we can look simply at various  PWL "baselines" vs. true baseline, BSL values for all subjects.  Plotting weight loss on the y-axis (as absolute kg or percent) vs. insulin on the x-axis (as fasting or 30 min post OGTT), I generate the following. 



Once again I repeat and reiterate ... The Carb-Insulin Hypothesis (aka TWICHOO) predicts that weight loss will vary inversely with insulin levels:  The higher the insulin levels, the lesser the weight loss. 

I titled this blog post "Early" Lessons, because there was an early test of the CIH / TWICHOO that goes unaddressed by the researchers.  That is, early in the game ... during Run-In.  They fed (to improve compliance) a reduced calorie, constant macro composition diet to ALL participants during this Run-In phase.  As discussed in my last post, the researchers apparently did not adjust these diets much following baseline estimates. so that rather than producing a narrow range of weight loss by percentage (target 12% ± 2%) a rather wider range was achieved:  10.5% ± 5%.  While this introduced possibly fatal error into the Test Phase of the study (stay tuned!) , it still provided an unintentional test of CIH/TWICHOO. 

There is NO relationship between baseline insulin measures -- INS-30 or INS-Fast -- and weight loss -- either as a percent or absolute amount -- during the Run-In/Weight Loss Phase of this current study that supports the Carb-Insulin Hypothesis (aka TWICHOO).  If anything, in absolute weight loss amounts, a slight correlation exists between higher insulin and greater absolute weight loss (statistical significance not determined).


Thank you NuSI, for putting some final nails in the coffin of a hypthesis that was never viable once your organization was formulated.  At least if we can further cement the basic lessons, the $12 MILLION dollars (not including the cuts for NuSI officers, employees and consultants) will not be for naught.


Monday, December 3, 2018

The $12M NuSI/ Ludwig Study ~ Part II: $12 Million for 12% Weight Loss?

SUMMARY


This post focuses on a critical issue with the Run-In phase of the recently released $12 million dollar NuSI funded study led by David S. Ludwig MD, PhD: Effects of a low carbohydrate diet on energy expenditure during weight loss maintenance: randomized trial. On occasion I reference the 2012 predecessor: Effects of Dietary Composition on Energy Expenditure During Weight-Loss Maintenance.

Virtually every stipulation leading up to the study, the Abstract and Full Text of the journal article, and continuing through to Ludwig's November 28, 2018 response to Kevin Hall in BMJ,  has stated that the MAIN purpose of the Run-In phase was to achieve 12%  ± 2% weight loss.  The study was intended to test the so-called Carb-Insulin Hypothesis during 20 weeks of weight-stable maintenance on diets of varying carbohydrate content.


OUTCOME:
With only 10 weeks of 60% calorie restriction during Run-In, the subjects who completed this phase averaged 10.5% weight loss (std.dev. 1.7%), ranging from only 5.6% up to 16.7% weight loss.  This doesn't change much for analyses of just those completers for whom complete energy data are available (same mean, SD = 1.5%, range 5.9% to 16.0%).

This indicates an unacceptable variation in the post-weight loss (PWL) "biological state", and to use this as the baseline "anchor" for diet comparisons is negated by either Study Design and/or execution thereof.





Wednesday, November 28, 2018

The $12M NuSI/Ludwig Study: Part I: Critique of the Study Design


SUMMARY


The results of the $12 Million Dollar NuSI-sponsored study, headed up by Dr. David S. Ludwig, are finally out.  
Effects of a low carbohydrate diet on energy expenditure during weight loss maintenance: randomized trial
While the good doctor is making the rounds touting them as evidence in support of the Carb-Insulin Hypothesis (TWICHOO in these parts), a review of the raw data made available to the public casts grave doubts on his victory lap.  This study built upon the "promising" results of the 2012 study:  
Effects of Dietary Composition on Energy Expenditure During Weight-Loss Maintenance  

This post focuses on comparisons of Study Design between these two studies, some improvements, and the ultimate failure that renders the primary outcome data suspect, if not outright useless.  (And I don't say that lightly!)


Improvements:


  • Study size
  • Length of time on one test diet (20 weeks) vs. 4 weeks crossover on each diet w/o washout
  • Protein held constant between test diets
  • Macro extremes the same -- e.g. LCHF = 20% carb/60% fat , HCLF = 60% carb / 20% fat
  • Post weight loss (PWL) assessment of TEE
  • Intake adjusted to maintain weight

Detrimental Changes:

  • Drastically altered run-in phase 
    • Shorter in total:  16 weeks vs. 20 weeks
    • No monitoring period before gathering baseline data.
    • No baseline intake assessment
    • Shorter weight loss phase:  10 weeks vs. 12 weeks
    • More varied weight loss and no minimum loss established to be included in the test phase.  In previous study, all subjects had to achieve at least 10% loss, averaged 13.5%.  Current study, losses ranged from 5.6% to 16.0%
    • Only 2 weeks for weight stabilization vs. 4 weeks.
  • Added ad libitum snacks for those who needed to increase caloric intake in maintenance but could not tolerate the larger meals necessary.
  • Assessing post weight loss DLW-TEE during the same two weeks immediately following weight loss that are designated for stabilizing reduced weight.
  • Changing protocol to anchor TEE changes to this flawed PWL measure of TEE instead of baseline per original protocol.

Monday, November 12, 2018

Why Aren't We Taking Anti-Obesity Drugs?



This post was prompted by the following article on Medscape


It is written by Caroline M. Apovian, MD 

I'd encourage you to read this whole thing first, as I'm genuinely interested in that response. Additionally I'm curious as to whether or not your response changes after reading this blog post (or other sources I'm about to link to).

Friday, November 2, 2018

"Real Food Keto" Quips


Rather than formally reviewing Real Food Keto -- an abomination of a book written by Jimmy Moore and his "Nutritional Therapy Practitioner" wife Christine Moore -- I've decided to compile a collection of my tweets here in a blog post.  I'll sort from most recent, with the newest before the "page break" after each update.  Feel free to comment here, but I'm also embedding tweets if you wish to go respond on Twitter.   Some may include additional commentary, others just the tweet. Enjoy!




This book is littered with nonsense about how low stomach acid causes everything from ass itching  to zygomycosis.   No doubt there will be more of these tweets coming!






Thursday, August 9, 2018

Swan Song


[no I'm not retiring the blog]



TLDR:  Rather than dragging things on by dismissing more black swans, Gary Taubes could eat crow and go quietly into the night.

After a long hiatus from any meaningful new content, and monumental blows to TWICHOO (Taubes Wrong Insulin Carbohydrate Hypothesis Of Obesity -- c'mon, it has a much better ring to it than the Ludwigian version),, Gary Taubes has gotten back to blogging a bit.*

He has apparently been reading (in fits and starts, in other words, probably not really reading) obscure books about obscure cultures from long, long ago.  Mind you, that in five years plus of arduous and comprehensive research put forth in Good Calories, Bad Calories, there was no mention of the Yahgan people he's about to discuss.   One wonders why not.  Heck, this is right in his time period of excellence for nutritional research and reporting!  (Uttermost Parts of the Earth, this is to a 2007 version of a book Taubes states was published in 1948).  But alas, no Yahgan (I also checked Wikipedia's alternate spellings), among the conventional-wisdom-challenging by Taubes circa 2007.

It's OK really, nobody expects you to track down every obscure culture, especially one that counters your hypotheses.  Shhh... look away ... no paradoxes to be found here!

Fast forward to 2018.  Currently, Gary Taubes has been  thinking about black swans as he engages in a bit of light Summer reading.  Perhaps no longer needing to devote so much time to NuSI has opened up a lot of free time for such endeavors.


(*something I still hold out hope of doing more of myself)





Tuesday, August 7, 2018

Where did the fat in this blood come from? ~ An Ead-iotic Analysis


NOTE  (8/7/2018):    So I've edited this post, originally written/published 5/5/2011, to omit the no longer relevant back story and defunct links.  I refer to a discussion on Jimmy Moore's now-long-defunct LLVLC Discussion Board that made me aware of the Eades' post discussed.

I'm bumping this for reasons that should become obvious soon.

SUMMARY:  Fat in the blood following a fatty meal is almost entirely due to the fat in the meal. 


~~~~~

Several years ago, Dr. Michael Eades wrote the following post:  ABC’s big meal propaganda.  Sadly, the video is no longer available.  It involved subjects consuming a GIGANTIC meal of 6000 calories, after which blood was drawn two hours later.  This "after" blood was very cloudy, and the technician holds this up and identifies the source of the cloudiness as fat.  The meal was deep fat fried mac&cheese, a bacon cheese burger quesadilla and fries and an ice cream smothered giant cookie.  Yes, high in fat and carbs, but favoring the starches.  While they pointed finger at just the saturated fat -- it was 187g of saturated fat == it's not too much of a stretch to estimate this meal contained around 300-350g total fat or more.


Friday, June 22, 2018

Quotable Quotes: Taubes the Radical!

Due to a recent article in Wired, I think this (6/30/14) post could use a hearty bump.  These words were uttered just over a decade ago by Gary Taubes. 

THE COLLAPSE OF A $40 MILLION NUTRITION SCIENCE CRUSADE





Seth Roberts:  But you'd seen Nobel-Prize-winning physicists get it very wrong.

Gary Taubes:  But what they were getting wrong were subtle; yes, they'd believe incorrectly that they'd discovered elementary particles, but what they were doing was a real subtle game. What they were misinterpreting were extraordinarily subtle aspects of the data.  


This obesity screw-up is fundamental; it’s like a grade school error in the interpretation of the laws of thermodynamics.  

And I made it as well, up until five years ago. I never thought differently. 

But what radicalized me is that they don't care.  If they successfully ward off my threat to their beliefs, then I'm in a very dangerous place.  Then it's, like I said, where I end up a bitter demented old man, one of those guys who's muttering to himself all the time that they, the establishment, didn't listen to him…



I don't mean to wish ill on a person, but if he doesn't end up a muttering demented old man, it means that fantasy wins out over fact, and sensationalism over science.  

Thursday, May 17, 2018

Thoughts on Obesity as "Disease" or Choice ~ Part 1: Smoking & Lung Cancer Analogy


Recently (May 2018) comments about obesity at a Pediatric conference have made the rounds. Specifically: Obesity Is a Disease, Not a Choice, Experts Advise.  Here is link to the full text in  "print version".


The AMA classified Obesity as a disease in 2013. Five years later we've made little to no progress, likely because we've got "experts" pontificating and arguing over semantics and false dichotomies.  The false dichotomy of Disease vs. Choice is right out of whatever master playbook teaches that if you keep the "masses" arguing, they might not notice you're full of it.  It's really the only explanation I can think of for the circular arguments made with nary a tinge of irony on board straight faces.

I have a bunch of stuff in the draft pile here on this topic, but cannot seem to organize it. I decided to start a series.  In no particular order.  

This installment deals with the following statement from the 2013 Resolution by the AMA:

Whereas, Progress in the development of lifestyle modification therapy, pharmacotherapy, and bariatric surgery options has now enabled a more robust medical model for the management of obesity as a chronic disease utilizing data-driven evidenced-based algorithms that optimize the benefit/risk ratio and patient outcomes; and

Whereas, The suggestion that obesity is not a disease but rather a consequence of a chosen lifestyle exemplified by overeating and/or inactivity is equivalent to suggesting that lung cancer is not a disease because it was brought about by individual choice to smoke cigarettes; and

Whereas, The Council on Science and Public Health has prepared a report that provides a thorough examination of the major factors that impact this issue, the Council’s report would  receive much more of the recognition and dissemination it deserves by identifying the enormous humanitarian and economic impact of obesity as requiring the medical care, research and education attention of other major global medical diseases; therefore be it 

Wednesday, May 9, 2018

Mind over Milkshakes!


This post was prompted by yet another discussion on Facebook involving cravings and hunger and the supposed magic of keto/LC in fixing this aspect.   As the thought process goes:  it's not about calories (even if they count), it's about how the food impacts us that causes us to eat too much (or just enough).   A hat-tip to Melanie (Mac Smiley) who sent me this study almost three years ago! 


TL,DR Summary:  Same people, different days, same shake, different labels.  Hormonal response differed based on expectations.