Understanding the Link Between Abdominal Muscle Density and Fall Risk Across Ages

Falls are one of the leading causes of injury and death across the globe. While most people associate fall risk with older adults, recent research indicates that physiologic changes in muscle and body composition can affect fall risk much earlier than previously thought. A 2025 study published in Mayo Clinic Proceedings: Digital Health sheds new light on how fat, muscle, and bone measures derived from abdominal computed tomography (CT) scans relate to fall risk in adults aged 20 to 89 years. The findings emphasize the critical role of muscle density, especially during middle age, in predicting future falls.

This article explores the study’s methodology, key findings, and implications for clinical practice and personal health strategies.

Why Fall Risk Matters

Falls are the third leading cause of injury-related mortality across all age groups and represent a significant public health concern. They are also a major contributor to long-term disability and reduced quality of life. The risk of falls increases with age. Research indicates that about 0.7% of individuals aged 18 to 44 experience fall-related injuries within a three-month period, while that rate rises to 2% for those over 65. Approximately 28% of people over 65 report falling each year, and 10% sustain injuries due to these falls.

Understanding what drives fall risk in adults of different ages is essential for developing preventive strategies. Traditionally, risk factors for older adults include gait or balance disorders, cognitive impairment, certain medications, and frailty. For younger populations, risky behaviors and substance use are more relevant, while middle-aged adults often experience falls due to tripping or navigating stairs.

Body Composition and Fall Risk

Body composition, including the distribution of fat, muscle, and bone density, has been studied as a potential contributor to fall risk. For instance:

• Fat: Obesity has been associated with a modest increase in falls among older adults.
• Bone: Lower bone density increases fracture risk but does not necessarily influence the likelihood of a fall itself.
• Muscle: Higher muscle density and strength correlate with improved balance and reduced postural sway, suggesting a protective effect against falls.

Despite this knowledge, most studies focus on individual factors such as muscle mass or bone density. Comprehensive studies examining fat, muscle, and bone together, particularly in younger and middle-aged adults, have been limited. The 2025 Mayo Clinic study fills this gap by using abdominal CT scans to measure these parameters simultaneously.

Using Abdominal CT Scans for Body Composition Analysis

Abdominal CT scans are commonly used in clinical care. Research shows that approximately 35% of adults undergo an abdominal CT over an 11-year period. These scans provide an opportunity to assess body composition without additional testing.

In the study, researchers used a validated deep learning algorithm to analyze abdominal CT images for:

• Subcutaneous fat area
• Visceral fat area
• Skeletal muscle area and density
• Vertebral bone area and density

The algorithm, based on a U-Net Convolutional Neural Network, identifies the axial section at the L3 vertebra and segments fat, muscle, and bone within a 20-centimeter section of the abdomen. Muscle density is measured in Hounsfield units (HU) and reflects the quality of the muscle tissue rather than its size alone.

Study Design

The study utilized the Rochester Epidemiology Project (REP), a collaboration of healthcare providers in a 27-county region of Minnesota and Wisconsin. The REP provides extensive longitudinal medical data for about 60% of the population in the area.

Key aspects of the study design included:

• Population: 3,972 adults aged 20 to 89 with no prior falls.
• Follow-up: Median follow-up was 6.7 years.
• Fall identification: Falls were identified using International Classification of Diseases (ICD) codes and verified through medical record review.
• Analysis: Cox proportional hazards models were used to evaluate associations between body composition measures and fall risk. Models were adjusted for body mass index (BMI) and 18 chronic conditions.

Key Findings

Muscle Density Is Critical

The most striking finding of the study was the role of muscle density in fall risk. Specifically:

• Individuals in the lowest tertile of muscle density were more than twice as likely to experience a fall compared with those in the middle tertile (adjusted hazard ratio [HR], 2.31).
• Those in the highest tertile of muscle density had a reduced risk of falls compared with the middle tertile (HR, 0.63).
• The association was strongest in middle-aged adults (45-64 years), where low muscle density increased fall risk nearly fivefold (HR, 4.98).

Interestingly, muscle area (size) was not significantly associated with fall risk, highlighting the importance of muscle quality over quantity.

Fat and Bone Measures

Contrary to expectations, subcutaneous fat, visceral fat, bone area, and bone density were not significantly associated with fall risk after adjusting for BMI and chronic conditions. While obesity has been linked to fall risk in previous studies, the specific distribution of abdominal fat in this study did not show a significant independent effect. Bone density, as expected, was more relevant to fractures than to the likelihood of falling.

Age-Specific Patterns

The study revealed age-specific patterns in falls:

• Younger adults (20-44 years): Accidents accounted for 85% of falls, while frailty or cognitive issues were rare.
• Middle-aged adults (45-64 years): Falls were more evenly split between accidents and other causes, with muscle density strongly predicting fall risk.
• Older adults (65-89 years): Falls were predominantly due to frailty and cognitive decline (64%), with muscle density contributing but less influential than in middle age.

These results underscore that fall prevention strategies should be tailored by age group and focus on different risk factors across the lifespan.

Implications for Prevention

The study has important implications for both clinical practice and individual health strategies.

For Middle-Aged Adults

Middle age emerges as a critical period for muscle health. Declines in muscle density may go unnoticed because muscle size can remain relatively normal. Low muscle density may compromise strength and balance, increasing fall risk even before older age. Interventions targeting muscle quality, including resistance training, adequate protein intake, and regular physical activity, may prevent falls decades before typical fall risk increases.

For Older Adults

In older adults, muscle density continues to play a role, but falls are influenced by multiple factors, including cognitive decline, visual impairment, and polypharmacy. Strategies in this group may require multifactorial interventions such as:

• Strength and balance training
• Medication review to minimize side effects
• Environmental modifications to reduce fall hazards

While improving muscle function may not completely prevent falls, it can reduce the severity of injuries when falls occur.

Potential Clinical Applications

The use of abdominal CT scans to assess muscle density provides a potential avenue for opportunistic screening. Since these scans are already part of routine clinical care for many patients, healthcare providers could identify individuals at higher fall risk without additional testing. This approach could help:

• Flag middle-aged adults for early interventions
• Track muscle quality changes over time
• Integrate fall prevention into broader wellness programs

Strengths and Limitations

Strengths

• Comprehensive body composition assessment: Fat, muscle, and bone were evaluated simultaneously.
• Representative population: The cohort reflected the general community, enhancing generalizability.
• Longitudinal follow-up: Median of 6.7 years allowed for robust analysis of incident falls.
• Verified outcomes: Falls were confirmed through medical record review, reducing misclassification.

Limitations

• Only falls resulting in medical attention were captured, potentially underestimating less severe falls.
• Muscle function was not directly measured; muscle density serves as a surrogate marker.
• Contrast use in CT scans may slightly affect muscle density readings.
• Data were limited to the abdominal region; muscle quality in legs and hips, which also affects fall risk, was not assessed.
• The population was predominantly from a Midwestern U.S. region with higher socioeconomic status, which may limit generalizability.

Practical Takeaways

1. Muscle density matters more than muscle size: Focus on strength and quality rather than just bulk.
2. Middle age is a critical window: Interventions to improve muscle density may prevent falls later in life.
3. CT scans could serve dual purposes: Routine imaging may identify individuals at risk for falls without additional testing.
4. Comprehensive fall prevention: In older adults, addressing multiple risk factors remains essential.

Conclusion

This study highlights that lower muscle density, measured through abdominal CT scans, is a strong predictor of fall risk, particularly in middle-aged adults. Fat and bone measures, while important for other health outcomes, were not independently associated with falls. These findings suggest that maintaining muscle quality from midlife onward may be a key strategy in fall prevention.

Healthcare providers and individuals alike should consider strategies to improve muscle density, including resistance training, protein-rich diets, and regular physical activity. Opportunistic use of CT scans may help identify at-risk adults earlier, enabling targeted interventions and potentially reducing falls across the lifespan.

Sources

1. St. Sauver JL, Grossardt BR, Weston AD, et al. Associations Between Deep Learning–Derived Fat, Muscle, and Bone Measures From Abdominal Computed Tomography Scans and Fall Risk in Persons Aged 20 Years or Older. Mayo Clinic Proceedings: Digital Health. 2025;3(4):100299.
2. Stevens JA, et al. The Epidemiology of Falls in the United States. Journal of Safety Research. 2006;37(3):273-280.
3. Cruz-Jentoft AJ, et al. Sarcopenia: European consensus on definition and diagnosis. Age and Ageing. 2010;39(4):412-423.
4. Liu P, et al. Muscle, adipose, and bone measures and fall risk in older adults. J Gerontol A Biol Sci Med Sci. 2020;75(12):2340-2347.
5. Anderson D, et al. Abdominal muscle density, postural sway, and fall risk in older adults. J Gerontol A Biol Sci Med Sci. 2017;72(5):703-709.

Disclaimer

This article is for informational purposes only and is not intended as medical advice. Individuals should consult a healthcare professional before starting any new exercise, diet, or medical screening program. Results may vary based on individual health status, age, and other factors.