Obesity paradox

From WikiMD's WELLNESSPEDIA

Obesity paradox

The Obesity paradox refers to the medical observation that, contrary to the established understanding that obesity is generally harmful to health, there are certain situations where it appears to have a protective effect. This phenomenon has been observed in a number of different medical conditions, including heart disease, cancer, and diabetes.

Overview[edit]

The term "obesity paradox" was first used in the medical literature in 2005, although the phenomenon it describes has been observed for much longer. It refers to the counterintuitive observation that, while obesity is generally associated with an increased risk of developing and dying from many diseases, in certain situations it appears to be protective.

Conditions associated with the obesity paradox[edit]

Several medical conditions have been associated with the obesity paradox. These include:

  • Diabetes: Some studies have found that obese patients with diabetes have better survival rates than normal-weight patients. This has been observed in both type 1 and type 2 diabetes.

Possible explanations[edit]

Several explanations have been proposed for the obesity paradox. These include:

  • Statistical artifacts: Some researchers have suggested that the obesity paradox may be a statistical artifact, resulting from biases in the way that obesity and disease outcomes are measured and analyzed.

See also[edit]

References[edit]


Medical Disclaimer: WikiMD is for informational purposes only and is not a substitute for professional medical advice. Content may be inaccurate or outdated and should not be used for diagnosis or treatment. Always consult your healthcare provider for medical decisions. Verify information with trusted sources such as CDC.gov and NIH.gov. By using this site, you agree that WikiMD is not liable for any outcomes related to its content. See full disclaimer.
Credits:Most images are courtesy of Wikimedia commons, and templates, categories Wikipedia, licensed under CC BY SA or similar.