Dysmobility Syndrome (DS) is a condition characterized by the accumulation of clinical risk factors for functional disability, including osteoporosis, sarcopenia, and obesity. Additionally, neurological disorders affecting the motor and sensory systems can contribute to DS, leading to gait disturbances, muscle weakness, and an increased risk of falls and fractures. Despite the known impact of body composition on DS, the role of fat distribution in different body regions remains unclear.
This study aimed to investigate the association between regional fat mass distribution and the likelihood of DS in older adults. Conducted as part of the second phase of the Bushehr Elderly Health (BEH) Cohort, this cross-sectional study defined DS based on the presence of at least three criteria associated with the syndrome. Body composition was assessed using dual-energy X-ray absorptiometry (DXA) and anthropometric measurements, while multivariate logistic regression and adjusted univariate linear regression analyses were applied to explore these relationships.
Among 2,359 participants, 1,277 individuals (54.13%) were diagnosed with DS. The final logistic regression model revealed a significant association between DS and both fat mass (FM) and the FM-to-fat-free mass (FFM) ratio in the limbs region, with stronger associations observed in this region compared to the trunk. Specifically, higher fat mass in the limbs, particularly in the legs, was associated with increased odds of DS. Conversely, a higher android-to-gynoid fat mass ratio was linked to a lower risk of DS.
These findings highlight the critical role of regional fat distribution in DS risk among older adults. Our results suggest that monitoring fat mass, particularly in the limbs, may serve as an effective strategy for early DS detection and intervention. By implementing targeted screening and preventive measures, healthcare professionals can reduce disability risks and improve the quality of life in aging populations.