“Dangerous than belly fat”… Which fat increases the risk of death by 15%?

It is well known that the accumulation of belly fat around the abdominal organs is not good for health. But even more insidious than that, a new study suggests that there is a type of fat that deserves to be dubbed the ‘silent killer’. This is the content reported on the 18th (local time) by the health medicine webzine ‘Health Day’ based on a thesis by a researcher at the University of Wisconsin, USA recently published in 《Radiology》.

The culprit is myosteatosis, caused by fat infiltrating the muscles. In a group of healthy adults, the researchers found that obesity increased the absolute risk of death by 7.6%, while muscular fat increased the absolute risk of death by 15.5%. Fatty liver disease was found in 8.5% and muscle wasting in 9.7%. The accumulation of fat in the muscles was investigated as the most dangerous.

“The signal[of the risk of muscle fat]was more pronounced in people who would be classified as healthy without muscle fat,” said lead author Perry Pickhart, director of the Department of Gastrointestinal Imaging at the University of Wisconsin School of Public Health. Muscle fat appears to be a greater risk factor than body fat (BMI) or fatty liver (visceral fat), which are considered biomarkers of obesity risk, he explained.

Muscle fat is a topic of growing interest in obesity and diabetes, said Steven Hemesfield, a professor of metabolism and body composition at Louisiana State University’s Pennington Center for Biomedical Research, who reviewed the paper. According to him, inside each muscle cell there is naturally a small amount of healthy fat that can be used to generate energy. Problematic fat is excess fat that accumulates outside cells and around muscle fibers and muscle bundles.

Consider the marbling of steaks, he explains. The average person has several kilograms of muscle fat spread throughout the body, but muscle fat is more likely to be concentrated in the legs than in other parts of the body.

Professor Parkhart’s research team gained an insight while conducting a study on a group of about 9,000 healthy patients who underwent low-dose computed tomography (CT) scans for colorectal cancer between 2004 and 2016. Visceral fat and muscle mass, aortic calcium, liver fat, and bone marrow density can be checked through CT scans, but usually only one or two figures are looked at and the rest are discarded. Therefore, it came to the idea that it could be used as virtual physical examination data to predict other potential health problems.

So, the researchers extracted body composition measurements from abdominal CT scans and trained an artificial intelligence tool to specifically assess each individual’s abdominal fat, muscle fat, liver fat, and muscle consumption. Automated software streamlined the process. “With previous methods, it would have taken a lifetime to do this,” said Hemesfield.

The researchers then followed the participants for an average of nine years to determine if these measures were associated with major health problems or premature death. As a result, muscle fat was found to be the highest risk factor for death. Even after taking into account each individual’s BMI, which is the best way to measure obesity, these associations were maintained.

“BMI is actually a very poor predictor,” said Professor Pickhart. Even if you are fat on the BMI, if your muscle fat is low, there are cases where you are relatively healthy, and if you look thin on the BMI but have a high muscle fat, the risk of death increases.

However, this study cannot draw a clear causal relationship between muscle fat and risk of death, says Angela Tong, a professor of radiology at New York University School of Medicine. Dr. Tong, who co-authored an editorial published with the study, stated that her muscle fat build-up could be due to other health issues. “Muscular fat can be a sign that other problems are developing, or that other health problems are causing inactivity,” he said. “You should look out for heart problems or diabetes.”

The paper can be found at the following link (https://pubs.rsna.org/doi/10.1148/radiol.222008).