Over 30 million people in the US have diabetes, and millions more don’t even know it.
How is that possible?
Type 2 diabetes does not have an acute onset with glaringly obvious symptoms in the beginning. Instead, it develops slowly over years of poor lifestyle choices. Only at the point where the symptoms are problematic, such as tingling in the toes, do many people discover that they’re living with diabetes.
Type 2 diabetes is growing especially fast among millennials, those who are between the ages of 18 and 34. In fact, rates of obesity for teenagers are currently over 30 percent.
Rates of both obesity and diabetes are expected to rise in the coming years. Given that diabetes comes with an increased risk of mortality, it is imperative that the epidemic is stopped.
Luckily, University of Warwick may have discovered one way to do so.
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Diabetes May be Predicted Through Google Searches
A group of researchers in the UK wanted to know if a person’s Google searches lead to a diabetes diagnosis.
First, they reviewed the key indicators of a diabetes diagnosis such as lifestyle habits and a family history of the disease. Then, they set out to find hints of these key indicators in social media sites and Google searches.
So, an individual who posts about weight loss and searches for healthy smoothie recipes may be more likely to develop diabetes than those who do not. The researchers claim that this is a modern version of “self-diagnosing” the disease, where patients turn to the internet to understand and treat their symptoms.
This trend isn’t new. Since the emergence of the internet, people have been using this immediate availability of knowledge to self-diagnose. The common cold, flu, and even pregnancy can all be self-diagnosed with a few quick clicks and careful observation.
The researchers of this study are arguing that the same can be said for diabetes related searches.
This information is still a bit broad but certainly sheds light on new ways to reach people that are at risk for developing diabetes. Perhaps we can implement a system that uses this information to identify those at most risk. All of this would be, of course, in hopes of treating the disease before it advances too far.
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[expand title=”References“]
Science Daily. URL Link. Retrieved August 11, 2017.
Fortune. URL Link. Retrieved August 11, 2017.
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