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The Relationship between Skeletal Muscle Mass and Bone Mass at Different Sites in Older Adults
Lingyan Chen1, Jiayu Wu1, Weiying Ren1
1Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China.
Introduction:
It has been well recognized that sarcopenia is closely related with osteoporosis, while the relationship between bone mass at different sites and muscle mass remains largely unexplored. This study aims to explore the relationship between bone mass at different sites and skeletal muscle mass in older adults.
Methods:
A total of 228 patients over 65 years old were enrolled in this study, and then 180 valid participants with accessible dual-energy X-ray absorptiometry (DXA) scanning data and absence of malignant tumors, mobility disorders, serious liver and kidney disease, and cardiac insufficiency were selected (138 male and 42 female). These individuals were further divided into control group and low skeletal muscle mass index (SMI) group. DXA scanning was used to access skeletal muscle mass and bone mass. SMI or body mass index was defined as appendicular muscle mass or weight divided by squared height, respectively. Low SMI <7.0 kg/m2 in male or <5.4 kg/m2 in female was defined as low SMI; while the bone density score at or below 2.5 standard deviations (T-score) below normal peak bone values, was regarded as osteoporosis.
Results:
The average age of enrolled patients was 82.72 years; the ratios of osteoporosis, low SMI, and low SMI with osteoporosis were 48.8%, 23.3%, and 15.0%, respectively. Compared with the control group, the prevalence of osteoporosis was higher, and the total bone mass and bone mass at various sites including limbs, spine, and pelvis, were all lower in low SMI group. Correlation analysis showed that SMI was positively related with total bone mass and bone mass at various sites. Covariance analysis showed that only total bone mass and appendicular bone mass decreased with decreasing SMI. After multiple adjustment, osteoporosis was positively related with the prevalence of low SMI, as evidenced by logistic regression analysis (odds ratio = 1.33, 95% confidential interval: 1.04-3.24, p = 0.045). Furthermore, compared with the highest quartile of appendicular bone mass, the lowest quartile was related with the increasing prevalence of low SMI (odds ratio = 7.29, 95% confidential interval: 1.21-67.45, p = 0.042).
Conclusion:
Compared with the other sites, the bone mass reduction at limbs of older adults was positively associated with skeletal muscle loss. It may be more beneficial to increase bone mass at the limbs for improved sarcopenia prevention and therapy. Further investigations are needed to explore the effects of other confounders (e.g., energy, calcium and vitamin D intake, and physical activity) on the osteoporosis and sarcopenia in older adults.
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