Mayo Clinic Is Developing Genius New Way To Balance Blood Sugar
Have you ever wondered why we react differently to certain foods? Some of us can eat gluten without a problem while others end up sleepy, bloated, and generally miserable after just one slice of bread. Some of us can fill our diets with healthy carbs like sweet potatoes and quinoa for extra energy—and some of us feel much more stable on a low-carb keto diet. The same applies to blood sugar; certain foods cause unhealthy blood sugar spikes in some people but not in others.
So what explains this? The reasons for our very individualized responses to foods aren't simple; we have to factor in our age, gender, BMI, stress levels, sleep patterns, and even the makeup of our gut microbiome. The good news is that that's exactly what the Mayo Clinic is doing—and they're using that information to help combat diabetes. In a new study, published in the American Journal of Clinical Nutrition, Mayo Clinic researchers proved that a specific test can predict an individual's post-meal blood sugar response for unique foods and food combinations.
If you're wondering how, exactly, they figured that out, you're not alone. And it wasn't easy! Researchers started by recruiting about 325 participants and having them report on their lifestyle habits. Then, they had them wear a blood glucose monitor for six days, which collected data on how their blood sugar responded to certain meals. They compared this data to the predictions made by a method developed by company Day Two. The results showed that Day Two was able to accurately predict an individual's blood sugar response to foods much better than the approaches that are currently used.
This is good news for patients and clinicians alike, as more than 100 million Americans are currently living with diabetes or prediabetes, according to the CDC. Rolling out this tool in a clinical setting could give patients the ability to tailor their nutrition plan to how they individually respond to certain foods, which would be a much more efficient approach than telling all diabetics and prediabetics to avoid all carb- and sugar-heavy foods altogether.
According to Professor Eran Segal, who first used this method in a study published in 2015, "By using models that can better predict how your body will respond to different foods and meal combinations, this approach aims to provide food recommendations that will help you better maintain normal glycemic levels." In the future, all diabetics could use this individualized method as a food-as-medicine approach to help them manage their diabetes, or potentially even reverse it.
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