Although fat is distributed throughout the body, research indicates that excess fat in the abdominal region, particularly visceral fat surrounding internal organs, is among the most dangerous. High levels of visceral fat are linked to a greater risk of numerous health problems, including Alzheimer’s disease. New research shows that people with greater muscle mass and a lower visceral fat-to-muscle ratio have brains that appear markedly younger than their chronological age.
Elevated visceral fat is the deep abdominal fat surrounding internal organs, which promotes chronic inflammation that can speed up brain aging. In contrast, greater muscle mass appears to have a protective effect. Previous research has already tied visceral fat to Alzheimer’s-related brain changes and neuroinflammation, making it a logical next step to investigate whether this type of fat also drives accelerated brain aging overall.
In this study, researchers enrolled 1,164 healthy adults, with an average age of 55 years, and performed whole-body MRI scans using an advanced protocol optimized to distinguish muscle, visceral fat, subcutaneous fat, and brain tissue. An AI algorithm then calculated each participant’s normalized total muscle volume, visceral fat volume, subcutaneous fat volume, and brain age.
The results showed that participants with greater muscle mass tended to have younger-appearing brains, whereas those with a higher visceral fat-to-muscle ratio had brains that looked significantly older. The findings suggest that the most effective strategy for slowing brain aging and supporting long-term brain health is to reduce visceral fat while maintaining or building muscle mass.
Reducing visceral fat while preserving or increasing muscle mass may help protect brain health and substantially lower the risk of age-related neurodegenerative diseases, including Alzheimer’s. This study confirms long-standing hypotheses linking body composition, specifically muscle mass and visceral fat, to brain health. It also establishes these measurable biomarkers as valuable tools for inclusion in future clinical trials evaluating metabolic therapies and treatments.
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