18 Months on the Shangri-La Diet
March 29, 2011
Alex Chernavsky has kindly given me several years of weight data he collected by weighing himself daily. He read about the Shangri-La Diet in 2005 and several years later decided to try it. The graph above shows what happened: Starting at 222 pounds (BMI = 32), over 11 months he lost 31 pounds, reaching a BMI of 27. Since then — while continuing the diet — his weight has increased at roughly the same rate it was increasing before he started the diet.
He started by drinking olive oil and sugar water, switched to olive oil alone, and then, finally, to flaxseed oil alone of which he drinks 3.5 tablespoons/day (= 420 calories/day). He does not clip his nose shut when he drinks it but he washes his mouth with water afterwards. More about his method here.
Almost all weight-control experts would say these results are impossible: 1. Alex lost weight because he ate more fat. Fat is fattening say most nutrition experts. 2. Atkins dieters, who don’t say that, think the secret of weight loss is to reduce carbohydrate. Alex didn’t do that (and eats plenty of carbohydrate). 3. He didn’t restrict what he ate in any way. 4. He didn’t change how much he exercised.
Quite apart from how it contradicts mainstream beliefs, including Atkins, the data are remarkable because the change was so simple, small, and sustainable, the weight loss so large, the rebound so minimal, and data period so long.
An ordinary clinical trial has obvious advantages over such one-person data, such as more subjects and more data per subject. Less obvious are the advantages of this sort of data over clinical trials:
1. Long pre-diet baseline. Clinical trials never have this. It allows one to judge if weight increase post-diet, often called “regain”, is due to the weight loss or other factors. In this case the rising pre-diet baseline shows that other factors are causing slow weight gain over time.
2. Motivation. In a clinical trial, the motivations of the researchers and the subjects are different. The researchers want to measure the effect of an intervention; the subjects want to lose weight. If paid, they may want to make money. The difference in motivations causes problems. How closely the subjects obey the researchers and how truthful they are is usually hard to know. This data does not have that clash of motivations and incentive to lie.
3. Realism — what methodologists call ecological validity. These data, unlike clinical trial data, come from the situation to which everyone wants to generalize: people trying a diet by themselves at home without professional support or guidance.
4. Level of detail available. You (the reader) have access to something resembling raw data. In clinical trial reports, the data available is heavily filtered (e.g., shortened, simplified) and the nature of the filtering rarely described. For example, you rarely learn in any detail what the subjects ate. With this sort of data, but not clinical trial data, you can get a better sense of whether the results are likely to apply to you.
Seth Roberts, Ph.D., is a professor of psychology at Tsinghua University in Beijing and a professor emeritus of psychology at the University of California at Berkeley. He is a regular contributor to Quantified Self and will be leading a session on “How to Do Self-Experiments” at the upcoming QS Conference – more details on this session soon.