22 Apr How the data revolution could transform the way people live with diabetes
Diabetes is a data-intensive disease. For those living with diabetes, managing their condition involves never-ending calculations: How much insulin to take to keep blood sugar in a targeted range, how many grams of carbohydrate are in a sandwich, or how an average monthly blood sugar reading fluctuates with different levels of exercise.
But unlike the math problems in school textbooks, there is often no clear answer to these questions. Given the numerous and complex factors that affect blood sugar – including food, physical activity, and sleep patterns – it’s not always clear what exactly occurs between a good blood sugar reading and a bad one.
To many Americans, this is an important question. Nearly 30 million Americans had diabetes in 2014, according to CDC estimates, though more than a quarter of them were undiagnosed. Another 80 million Americans were classified as “pre-diabetic,” meaning they will likely develop diabetes in the next decade if they don’t change their lifestyles. (Around 5-10 percent of these cases are Type 1 diabetes, in which a person’s body doesn’t produce insulin, and a person must take insulin to survive. The rest are Type 2 diabetes, sometimes called adult onset diabetes, in which a person gradually loses the ability to produce sufficient quantities of insulin.)
In many counties in the U.S., more than 10 percent of the population has been diagnosed as diabetic, as this map shows
Because it is so widespread, diabetes is incredibly expensive, costing the U.S. $176 billion in direct medical bills and $69 billion in indirect costs, including disability, work loss and premature death, in 2012.
Diabetes can’t be cured; it can only be treated. The goal is to keep blood sugar within a certain healthy range: If it dips too low, a person can faint or go into a diabetic coma. But too-high blood sugar results in wear and tear on the body that can lead to eye, nerve or kidney complications.
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