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“Healthy Obesity” - Misnomer or Actual Physiological State?


“Healthy Obesity” - Misnomer or Actual Physiological State?
  Nov. 30, 2015


Australian researchers recently defined some key characteristics of the “metabolically healthy obese” – at term for obese individuals who remain free from type 2 diabetes, hypertension, dyslipidemia and other pathologies that are usually associated with obesity. Due to the increased prevalence of the metabolically healthy obese, a study led by Dr. Jerry Greenfield was recently published in the Journal of Clinical Endocrinology and Metabolism seeking to define metabolically healthy obesity.

Their findings have implications for the treatment of type 2 diabetes, insulin resistance and obesity because understanding what is different about these individuals could help clarify the mechanisms that cause type 2 diabetes; ultimately leading to more precise treatment plans. “Our own approach is to define metabolically healthy obesity in clearly measurable terms,” explained Greenfield. The team specifically focused on insulin resistance, with obese individuals who are not insulin-resistant being considered “metabolically healthy.”

Using a cutting edge technique that is able to measure insulin sensitivity in muscle and liver tissue, the research team identified that some of the 64 obese participants had varying levels of insulin resistance or sensitivity in muscles compared to the liver. It appeared that those who were resistant to insulin in only one area were much more metabolically healthy than those resistant at both sites. Those individuals also tended to have lower blood pressure, less visceral fat and less fatty tissue within their liver. The authors noted that this sheds light on the complexity of insulin resistance among humans, and that different drivers of insulin action at different tissues exist, which may be determined by genetic variables. Greenfield proposes that this identification of varying levels of insulin sensitivity between the liver and muscles could improve early detection and individualized treatment in the future.

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