Obesity may improve odds of stroke survival, according to a preliminary study released today that will be presented at the American Academy of Neurology's 71st Annual Meeting in Philadelphia, May 4 to 10, 2019.
Medical experts call such an occurrence the obesity paradox. The obesity paradox is a medical theory that suggests obesity may be protective for some people, such as very old people or those with certain chronic diseases.
"It was first noticed that carrying extra weight may play a role in survival for people who had suffered from kidney and heart disease, so we felt the need to investigate whether it also was tied to improved stroke survival," said study author Zuolu Liu, MD, of University of California Los Angeles and a member of the American Academy of Neurology.
Participants were divided into five categories based on BMI: underweight, normal, overweight, obese and severely obese.
Researchers then monitored patients for three months following their stroke, measuring their levels of disability.
People who were obese were 46 percent less likely to die after a stroke and those who were overweight were 15 percent less likely to die. Conversely, people who were underweight were 67 percent more likely to die after a stroke than people of normal weight. These results were calculated after researchers adjusted for other factors that could affect survival rates, such as having high blood pressure, high cholesterol or smoking.
Of the 95 people who were severely obese, 11 died during the study, compared to 19 of the 192 people who were obese, 58 of the 395 people who were overweight, 55 of the 327 people who were normal weight and six of the 24 people who were underweight.
"One possible explanation is that people who are overweight or obese may have a nutritional reserve that may help them survive during prolonged illness," stated Liu. "More research is needed to investigate the relationship between body mass index and stroke."
One limitation of the study was that all participants were from southern California, which means results may not be the same for other populations. However, the racial/ethnic distribution of the population in this study mirrors that of the national population.