A mathematical theory reveals why you should ignore diet and exercise fads
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That over-optimization is what statisticians call "overfitting," and it appears again and again when researchers want to build models for their data. In being thorough, they end up generating a lot of noise that makes it much harder to find the signal.Diet fads are prime examples of overfitting because they turn an ongoing process - healthy eating - into an over-simplified mandate.
Typically, fads emerge when a single study finds a food or action helps a small group of people. This is what Christian means by "the thing that you can measure." The study has data that shows, however modestly, that coffee lowers blood pressure or nuts lower cholesterol.That modest finding then gets blown out of proportion, typically through news media, and gets circulated around as gospel. People start going on juice cleanses and detox diets regardless of whether it makes sense for them."You see these extremely violent swings in popular taste," Christian says, pointing to the rise and fall of soy milk during the mid-1990s to late 2000s, before getting dethroned by almond milk around 2013.
In essence, people overfit the dietary advice because they start prioritizing the specific food over the process of eating healthy - similar to how people may exercise to an unhealthy degree to look better instead of trying to be healthier.Christian and Griffiths call this the "idolatry of data."
"Overfitting the signals - adopting an extreme diet to lower body fat and taking steroids to build muscle, perhaps - can make you a picture of good health," they write, "but only the picture."
So do your best to avoid most dietary advice you hear in the news. A lot of it is poorly supported by data.Instead, do this.
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