The study was based on the data of 1,164 healthy subjects, whose average age was 55.17 years. About 52 percent of the participants were women and about 39 percent belonged to non-white populations. All participants underwent a comprehensive MRI examination that included imaging of the brain, assessment of muscle mass and measurement of visceral fat, the deep fat surrounding the abdominal organs. At the same time, the biological brain age of each participant was estimated using an algorithm built on the basis of 5,500 MRI examinations of adults aged 18 to 89.
The data analysis found that the average brain age was 56.04 years, slightly higher than the average chronological age. Comparing the indices showed that a low ratio between visceral fat and muscle and a high muscle mass were associated with a younger brain age. Conversely, a low level of muscle with a high level of visceral fat was associated with an older brain age. The average difference between brain age and chronological age was 0.69 years, but was not statistically significant.
Visceral fat is considered the most dangerous fat in the body. It accumulates deep in the abdominal cavity, around organs such as the liver, pancreas and intestines, and may release inflammatory substances that affect metabolic processes and the functioning of various systems. In contrast to the subcutaneous fat that is found under the skin and plays the role of an energy reservoir, the visceral fat is associated with an increased risk of diabetes, excess blood lipids, heart disease and chronic inflammatory processes. In the current study it was found that only the visceral fat, and not the subcutaneous fat, was linked to brain aging.
The researchers emphasize that “visceral fat is the most problematic fat. It is associated with a high rate of diabetes, insulin resistance, pre-diabetic conditions and high cholesterol. All of these increase the level of inflammation in the body, and ultimately affect the brain. This is the main mechanism by which we believe obesity affects the risk of Alzheimer’s,” said Dr. Raji.
The working method combined accurate imaging with multivariate computer analysis. The muscle and fat volumes were calculated from the simulations, and the algorithm estimated the biological brain age and compared it to the real age. The combination made it possible to examine the cumulative effect of body structure on the processes of neurological aging.
One of the conclusions of the study is that common indices such as BMI do not distinguish between the types of fat and do not reflect the condition of the muscles. Dr. Raji points out that “a low BMI can be misleading. Those who have more visceral fat and less muscle mass can present a brain that looks older, regardless of the BMI index.”