Proposal for a N=1 Experimentation Online Community

INTRODUCTION

There is a paradox when it comes to optimizing ones health through diet.  All indications are that individual characteristics, circumstances and history are tremendously important as far as fine-tuning choices of nutrition and exercise.  This leads many people to try N=1 experimentation in order to evaluate exactly how their body will respond to changes and find what's right for them.   The trouble with this approach is that these experiments are difficult to to conduct, interpret and use for future decision making.  What to do?  

An idea has been floating around to develop an online community -- the larger the better -- of N=1 experimenters to

• provide support, new ideas and discussion
• structure and conduct experiments across a variety of nutritional (and other factors)
• share results and allow analysis of both pooled and specifically relevant community members
• develop tools allowing one to interpret the community results in their individual context, make predictions and forward looking decisions

This community could even ultimately become a useful scientific complement to the traditional approaches of large scale epidemiological studies and small targeted controlled trials.

WHY IS N=1 DIFFICULT?

Truly informative N=1 nutritional studies are difficult because of 

* The self-discipline, consistency and time (and possibly cost) required

* The intrinsic 'high dimensionality' of the problem.  (By high dimensionality we mean that there are many, certainly tens maybe hundreds of variables necessary to describe ones food intake and relevant circumstances.  Of course not all of these are equally important but from a statistical modeling standpoint, if one reduces this dimensionality in an ad-hoc fashion -- e.g. by just ignoring some of them -- it will almost always introduces systematic biases in the results.)  These attributes of food intake might include total calories, macronutrient breakdown, types of fats, vitamins, glycemic index, etc.  Timing of feedings, combinations of macro-nutrients eaten, are other obvious potential considerations.  And when one considers the background factors: observable individual characteristics like age, weight, body fat, activity level and type, sleep, supplementation and history thereof, the picture is further complicated.

So a) there are many many compelling experiments to try out and only one lifetime to do it in, b) it may be  tempting to prematurely move to the next experiment because something seems 'not to be working', c) interpreting results even after a lot of data has been collected can be difficult because the other variables are not adequately controlled or accounted for, d) extrapolating from other's N=1 results is exceedingly problematic.

* It is difficult to know what can be objectively measured and tracked and with what averaging and what lags.  For instance, if I add some starches on top of a   low carb diet, conjectured to accelerate weight loss, how long until it starts working, should I look at instantaneous weight or averaged over some period?

* There are few available to help predict outcomes and analyze realizations against these to figure out what went wrong (or right).  This can emotionally be quite important and for certain types of individuals will help them persevere with the programs.  For example one would like to be able to say:  given my current state of health and personal history, if I eat a 15%/25%/60% carb/prot/fat diet for 1 month, I would expect might weight change over that period to be in the following range.   

What are we proposing?

The vision is to have a way to explore many hypotheses with large populations that cover the high-dimensional space of characteristics  with the necessary emotional and intellectual support of the participants, effective monitoring and reporting tools and ongoing analysis and interpretation.

The community would consist of

* A handful of interested researchers willing to design/program and oversee experiments

* A large number of individual N=1 experimenters who would participate in these and report their results to some level of granularity

* Possibly, funding permitting, some number of self-identified but screened guinea-pigs willing to follow a baseline diet with proscribed tweaks and larger (instantaneous and secular) changes and put up with continual tests and diagnostics.

* Statistical modelers and tool builders who would create open source analytical and predictive tools that would be continually updated using the results.  Machine learning techniques are ideal for coping with the large dimensionality and (hopefully) large data -- inferring the right conditional distribution of outcomes for an individual and not losing sight of the error-bars 

A website would  provide background on the experiments (including summaries of relevant traditional studies), forums for discussion and Q&A, tools for reporting/tracking, statistics on the trials underway and summary results from completed ones, analytic and modeling tools that would provide statistics and machine-learning based predictive capability.

Please contact us if you have interest in participating either as an organizer, researcher or participant.

Calories-in-calories-out: dangerous tautology or just a model needing improvement

It seems that the battlelines about very low-carb vs moderate/pragmatic lower-carb diets have been drawn around the question of whether or not calories count or whether there is a macronutrient ratio silver bullet that allows one to 'eat as much as one wants'.   Personal experience seems to dictate which side of of this divide one falls.  To us the salient questions is whether the CICO model has predictive power. If it does, it has an important role in addressing the obesity problem; if it doesn't, it is at best a confusing factor and possibly can be a harmful behavioral influence.

(By 'predictive power' we mean that if one specifies intake in terms of total calories and estimates energy expenditure one could anticipate expected weight change over some defined period.  Note that we are not even requiring that caloric requirements must be 'theoretically derived; it is fair game to estimate these from idiosyncatic past experience; if there is a reliable way to do this that identifies, say, the right lookback period for estimation for a given predictive horizon, that would be valuable.) 

There are plenty of obvious reasons that the predictive power of the CICO model may be limited  in practical application. 
1. measurement error ( you may simply be unable to record accurately your energy intake and output) eg:
a) the reference data may be poor or hard to apply in reality (how exactly to quantify the marbled-ness of a  steak)?
b) there may be metabolic advantages to certain foods that are not captured in the caloric estimates. (This would mean that the inputs would need to be corrected or else the CICO model would be dimensionally over-reduced)
c) there might be metabolic advantages/disadvantages associated with consuming foods in different combinations-- or there may be other conditionality, ex hormonal levels, that complicate the picture.
d) difficulties in accurately measuring your energy content of your exercise both deliberate and background

2. timescale effects, for instance:
a) water retention (and maybe other effects) can dominate weight changes over short periods of time(days)  and these would not be predicted by CICO. Of course if one could measure WIWO from all sources then the CICO predictions could be corrected and still be useful for these short timescales.
b) over somewhat longer horizons, adjustment of base metabolic rate due to changes in body mass, composition, etc... occur and make it (much) more complicated to connect activity level with true energy expenditure.
c) other changes may occur (such as the oft-discussed keto-adaptation) that might exploit effects such as 1b in a time dependent fashion.
d) 'behavioral' impact or feedback that make it improbable that the model user will realize the initially specified inputs (e.g. 'I am going to eat 1200 calories and walk 10km/day for the next 21 days').

Of course these practical problems are irrelevant under metabolic ward conditions where, in principle, total intake and expediture may be measurable.  Those may studies may be the only way to properly isolate and resolve the existence and magnitude of 1b & 1c although other approaches may also be possible (see below).  But even armed with those answers, another very interesting challenge exists: whether the CICO model can be improved to be more useful, i.e. more predictive and with more true explanatory power for people living in the real world.

The CICO model would seem to have some validity in boundary cases: e.g. zero food intake, forced feeding. Personal experience indicates that predictability is possible when one has a very large weight surplus and intake is severely restricted. As one reaches more of an equilibrium measurement noise is harder to smooth over.  Thus it is compelling to think that a systematic approach to collecting a large amount of data from n=1 experimentation, with the right clustering of participants to span the space of personal attributes,
could lead to a more practical model where the user would:
Provide inputs:
0. input personal attributes and possibly history thereof
1. specify a time period
2. specify planned food intake (the dimensionality of this specification is a critical output of the study above)
3. specify exercise plan
Get outputs:
0. expected weight change
1.  uncertainty band.
(2. these outputs would provide some rigor to the concepts of 'overfeeding' and 'energy excess' for the desired time period.)

This may seem like a technocratic fantasy but if even incremental improvements to CICO can be achieved, rather than being a lightning rod for disagreement about dietary approach amongst the afficionados,  the model could be a constructive vehicle for improving nutritional guidance to a mass audience.

Red meat scare

There have been a number of refutations published of the recent "red meat and mortality" study that has garnered so much attention in the press, e.g.
http://www.nytimes.com/2012/03/13/health/research/red-meat-linked-to-cancer-and-heart-disease.html?scp=2&sq=red%20%20meat&st=cse

Most of these analyses have focused on the difficultly, even absurdity, of learning much from observational studies in contrast to real experiments. They emphasize the pitfalls of self-reported dietary data, the small size of the claimed effect, and question the ability of the researchers to control for confounding variables.  A more substantive post by Ned Kock, excerpted below,  reaches some very interesting, tentative, conclusions from some of the same data:

Here are the correlations calculated by WarpPLS, which refer to the graphs above: 0.030 for red meat intake and mortality; 0.607 for diabetes and mortality; and 0.910 for food intake and diabetes. Yes, you read it right, the correlation between red meat intake and mortality is a very low and non-significant 0.030 in this dataset. Not a big surprise when you look at the related HCE graph, with the line going up and down almost at random. Note that I included the quintiles data from both the Health Professionals and Nurses Health samples in one dataset.
Those folks in Q5 had a much higher incidence of diabetes, and yet the increase in mortality for them was significantly lower, in percentage terms. A key difference between Q5 and Q1 being what? The Q5 folks ate a lot more red meat. This looks suspiciously suggestive of a finding that I came across before, based on an analysis of the China Study II data (5). The finding was that animal food consumption (and red meat is an animal food) was protective, actually reducing the negative effect of wheat flour consumption on mortality. That analysis actually suggested that wheat flour consumption may not be so bad if you eat 221 g or more of animal food daily.

http://healthcorrelator.blogspot.com/2012/03/2012-red-meat-mortality-study-arch.html

In Search of the Perfect Human Diet

Mark Sisson has an excellent preview of this movie being released in the next few days:

The most moving scenes take place at the dig site and with the Max Planck geneticist. I talk about this stuff all the time, and I and many others write about how meat eating shaped our evolution, but there’s always a sense of distance and abstraction. Links to journal articles are helpful and all, but there’s really nothing like seeing the dig site with the layers of animal bones and tools, hearing the anthropologist with dirty knees from kneeling in the ancient, ancient earth say that the diet of the humans who lived there was “primarily reindeer,” or listening to Prof. Michael Richards discuss how his team has yet to find evidence of a vegan human via isotope analysis. These are the people who actually do the hard labor, write the papers, and run tests talking directly about the implications of their work. Rather than me or Robb or whoever else writing blogs or books about our interpretations of the work, the people who produce the work are stepping out from academia and giving their honest summation of the evidence for ancestral eating. If they’re coming to similar conclusions as us, that’s huge.

Professor Loren Cordain has a great scene where he uses a football field to illustrate just how far we’ve come as a species, how long we were eating wild plants and animals exclusively, and how recently – in the big picture – our lifestyles have drastically changed. It’s a great visual that will resonate with a lot of people.

Overall, “In Search of the Perfect Human Diet” presents a great introduction to and justification for ancestral eating. It’s hard to get someone to read a book or even check out a blog, but if they can sit reasonably still for an hour and a half while an entertaining, engaging movie plays, they’ll get the general idea behind this stuff and want to learn more. It presents a compelling case for the evolutionary foundation of the diet we prescribe.

The movie has been made and released to DVD, but the battle doesn’t stop there. The more copies they sell and the more people watch it, the larger our community will grow. If you want to support a great movie, a great cause, and (in my opinion) the answer to the obesity epidemic that’s showing no signs of reversing, pick up a copy of “In Search of the Perfect Human Diet.” Copies begin shipping tomorrow.

Read more: http://www.marksdailyapple.com/in-search-of-the-perfect-human-diet/#ixzz1nhU65xw7

Constrained Carbohydrate Common Denominators: Pt 2 The Zone

In the first part of this series, "Constrained Carbohydrate Common Denominators", we introduced the goal of finding some "low-carb" nutritional guidance that can be syndicated to the broadest possible audience. To review, this message is not intended for people who are already following paleo or primal lifestyles, sophisticated self-quantifiers and nutrition geeks, or Cross-fit super-people, and it is meant to have relevance across the socioeconomic and educational achievement spectrum. We accept the view that everyone falls somewhere on the more-or-less continuous spectrum of perfectly regulated blood sugar to extreme cases of metabolic syndrome and diabetes. The goal of this exercise is to find a dietary prescription, which combined with the sort of physical activities anyone can incorporate into their regular life, moves one down this curve, towards a functioning metabolism and a normal weight. In some cases, weight loss will be an important side-effect but it is general well-being and avoidance of the diseases of modern society that is the primary success criterion. Although we don't view food 'addiction' as a root cause of the obesity epidemic; it seems to be an important part of the phenomenology of metabolic damage and it seems plausible that it has an important nonlinear feedback effect on this condition. An ancillary goal of this exercise would be to shift societal resources away from intensifying and fueling this behavior. It is important that the nutritional messages that are distilled are reasonably straightforward and require only basic background in food groups, macro-nutrients and reading nutritional information on labels. The guidelines cannot be overly precise or fiddly, and shouldn't require too much fine tuning. We are quite sympathetic to the view articulated by S. Andrei Ostric

...what I believe in regards to a philosophy regarding health and nutrition. You have to keep a lot of plates spinning to make it work ie low carb, avoid grains and sugars, avoid gluten, avoid processed foods, eat whole foods, eat your vegetables, get sleep, get exercise, get rest, control your stress, avoid fructose, don’t overeat, enjoy meals with family and friends. All those things are the plates, and you have to keep them spinning. Sometimes the plates break, and you have to start over, sometimes you need help get the plate spinning, sometimes you still break the plate and yo have to find a new way to do it. But most important is have fun (that is passion, involvement, and awareness) during the process, and remember its the whole that counts not just one plate.

Nevertheless, we are looking for some time-homogeneous solutions that are stable to perturbations. We start this survey with The Zone diet, created by Dr. Barry Sears. Our rationale is that The Zone has been around since the mid-90s, longer than most diets that would qualify as carb-constrained; it is very well known and has spawned a mini-industry of books, educational resources and products; most importantly, it is actually moderate in carbohydrates (suggested macro-nutrient ratio of 30-30-40 fat/protein/carb) so is closest to the 'Standard American Diet' and presumably would be a less severe modification for most people. The diet removes sugar and most simple carbs and replaces them with 'healthy' fats and moderate amounts of protein. An interesting differentiation of the Zone approach is the direct focus on avoiding systemic low-level inflammation rather than trying to influence fat metabolism. Of course, we are not attempting a comprehensive exploration of his diet here but are touching on a few key aspects. To fully appreciate the perspective, please see his website or Dr. Sears' interesting books, including "Toxic Fat" which we found refreshingly different in its perspective though obviously speculative in aspects.

 Dr Sears was gracious enough to respond to a couple of questions we sent him which, though, specific, to us strike at the essential differences between established low-carb dietary frameworks; we reproduce his answers here. (Please note that Thought-Fuel Company has no affiliation or business relationship with Dr. Sears or his company.)

Many low-carb diets focus on control of insulin and, more recent, leptin. When we asked if it was more important to optimize insulin or leptin he responded:

It's not optimal hormonal levels of either insulin or leptin that is the goal, but reduction of cellular inflammation in their target cells that compromises their signaling to the interior of the cell . Thus you are looking for an optimal anti-inflammatory diet that makes both insulin and leptin work more effectively. The best anti-inflammatory diet remains the Zone diet coupled with high dose fish oil and very low in omega-6 fatty acids. As you reduce cellular inflammation, the levels of insulin and leptin will begin to fall.

Putting aside all the fundamental questions about underlying biochemical mechanisms and how they interplay in the complex system of human metabolic health, there have been some critiques of the Zone diet approach. Here we mention a few of the more frequent ones: 1. The Zone diet is really calorie restricted, due to the caloric intake being calibrated to the 30% protein component -- which for most people equates to 300-500 calories. This doesn't strike us as a severe defect; There are a number of studies connecting calorie restriction with longevity and disease avoidance. Dr Rosedale's diet, which is much more 'severely' low carb, also emphasizes reducing food intake and lowering body temperature. 2. Unlike many of the currently vogue Primal and Paleo low-carb diets (though not all, eg De Vany), The Zone steers strongly away from the consumption of saturated animal fats. We asked Dr. Sears about this:

Saturated fats have a slight inflammatory effect because of their ability to bind to toll-like receptors and initiate an inflammatory response. However, omega-6 fatty acids are more inflammatory because they generate arachidonic acid. Both should be kept to a minimum by replacing them with monounsaturated fats (non-inflammatory) and omega-3 fats (anti-inflammatory).

Other more controversial aspects of the approach include the inclusion of soy as a protein source and the prescriptive macro-nutrient ratios for each meal. We view each of these as potentially positive in the 'common denominator' context. For many people without sufficient access to beef or dairy sources, even if soy protein is not optimal, it may be better than eating carbs. And as long as they don't need to be exactly adhered to on every occasion, a uniform macro-nutrient ratio per meal may be the easiest long-term rule to follow.

In future installments we hope to look at other low-carb diets through this same lens.
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