Obesity paradox
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 | edit source]
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 | edit source]
Several medical conditions have been associated with the obesity paradox. These include:
- Heart disease: Several studies have found that obese patients with heart disease have better survival rates than their normal-weight counterparts. This has been observed in conditions such as heart failure, coronary artery disease, and hypertension.
- Cancer: Some studies have found that obese cancer patients have better survival rates than normal-weight patients. This has been observed in a variety of cancers, including breast cancer, prostate cancer, and colorectal cancer.
- 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 | edit source]
Several explanations have been proposed for the obesity paradox. These include:
- Biological mechanisms: Some researchers have suggested that certain biological mechanisms associated with obesity, such as increased adipose tissue and insulin resistance, may have protective effects in certain situations.
- 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 | edit source]
References[edit | edit source]
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Contributors: Prab R. Tumpati, MD