Biomedical Data Analyses Can Predict Metabolic Risk

Published
  • July 02 2014, 7:27am EDT

Analyses of biomedical data from nearly 37,000 volunteer employees of a large company insured under Aetna shows a success rate of 80 percent to 88 percent in predicting risk of metabolic syndrome, which can cause chronic disease.

Metabolic syndrome means an individual has at least three of five biological characteristics that are out of normal range--waist circumference, blood pressure, elevated triglycerides, low high-density lipoproteins and increased insulin resistance--according to a report on the findings in The American Journal of Managed Care. Research published in 2006 suggests that almost a third of U.S. adults have three of the out-of-range characteristics and another 45 percent have one or two risk factors, the study notes. Individuals with metabolic syndrome are twice as likely to develop cardiovascular disease and five times more likely to get diabetes mellitus.

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