Activity data from wearables could help monitor blood sugar levels, study indicates
Activity data from a Fitbit can predict changes in blood sugar control for adults with prediabetes, a condition that affects around one in three adults in the United States, a new study shows. The findings point to a strategy that tech companies might use in their rumored efforts to build diabetes technology into wearable products.
“It kind of makes sense intuitively — more movement, more physical activity leads to overall better health, and better health is one of the factors behind improved glycemic control,” says Jessilyn Dunn, an assistant professor of biomedical engineering at Duke University who wasn’t involved with this study but has also done work on wearables and glucose monitoring.
People with prediabetes have elevated blood sugar levels, placing them at risk of developing diabetes. But most tools that predict whether someone with prediabetes will progress to develop diabetes look years in the future, says study author Mitesh Patel, an associate professor of medicine at the University of Pennsylvania and vice president for Clinical Transformation at hospital group Ascension.
“There were no good near-term models to say, in the next six months, whose blood sugar is going to increase and get worse versus whose is going to get better,” Patel says.
In the new study, published in NPJ Digital Medicine, Patel’s team built models that would use activity data collected from either wrist- or waist-worn Fitbits to predict both changes in average blood sugar and 5 percent improved or worsened blood sugar levels. Over the course of the six-month study, they found that they were able to make accurate predictions, and that predictions were more accurate using data collected from the wrist-worn devices.
“We know that people who are generally more active have better control of their blood sugar, and people who are less active have worse control,” Patel says. “But there are other hidden patterns in the daily information we’re getting — how many steps are fast steps versus slow steps, and other nuances — that we can get from this information.” Because the wearable can capture that additional data, it can give a more granular look at how activity drives changes in blood sugar.