Many people believe that it should be relatively easy for medical professionals to spot a person with type 2 diabetes or one who is at risk for the condition. However, short of conducting extensive blood testing, diagnosing the condition may actually be more difficult than commonly thought. The most obvious risk factor for type 2 diabetes is obesity. However, numerous studies have shown that obesity alone is not a very good indicator of the presence of the condition. A large percentage of overweight individuals never develop metabolic problems. Furthermore, there is disagreement about whether body mass index or body fat percentage should be used to diagnose obesity. This lack of clear and simple diagnostic criteria may allow many people with type 2 diabetes to go undiagnosed, which increases their risk of experiencing health complications that result from poorly managed blood sugar. The Centers for disease Control and Prevention estimates that there are more than 7 million people in the U.S. with undiagnosed diabetes.

In order to address this problem, a team of researchers recently reported at the Annual Meeting of the Obesity Society that three simple questions may help doctors identify individuals who are most likely to have type 2 diabetes, allowing the medical professionals to recommend further testing and lifestyle improvements that may help them reduce their risk, according to MedPage Today. The team said that age, family history and BMI taken together may provide the strongest evidence of diabetes risk. Their study showed that 20 percent of individuals over the age of 55 who had family members with diabetes and a BMI over 30 had type 2 diabetes. Findings from the investigation could provide physicians with a simple and relatively accurate tool for predicting type 2 diabetes in their patients, the researchers told the news source. This may help increase rates of diagnosis and allow more individuals to start appropriate treatments, reducing their chances of experiencing health complications.

Courtesy: OntrackDiabetes

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