big data

AI and you: Is the promise of personalized nutrition apps worth the hype?

Personalized nutrition apps could provide valuable data to people trying to eat healthier, though more research must be done to show effectiveness.

As a type 2 diabetic, Michael Snyder has long been interested in how blood sugar levels vary from one person to another in response to the same food, and whether a more personalized approach to nutrition could help tackle the rapidly cascading levels of diabetes and obesity in much of the western world.

Eight years ago, Snyder, who directs the Center for Genomics and Personalized Medicine at Stanford University, decided to put his theories to the test. In the 2000s continuous glucose monitoring, or CGM, had begun to revolutionize the lives of diabetics, both type 1 and type 2. Using spherical sensors which sit on the upper arm or abdomen – with tiny wires that pierce the skin – the technology allowed patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.

It gave Snyder an idea for his research at Stanford. Applying the same technology to a group of apparently healthy people, and looking for ‘spikes’ or sudden surges in blood sugar known as hyperglycemia, could provide a means of observing how their bodies reacted to an array of foods.

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David Cox
David Cox is a science and health writer based in the UK. He has a PhD in neuroscience from the University of Cambridge and has written for newspapers and broadcasters worldwide including BBC News, New York Times, and The Guardian. You can follow him on Twitter @DrDavidACox.
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