With increasing life expectancy and a rapidly aging population, age-related diseases such as T2DM, OP, and SAC have become major global public health challenges21. These conditions are highly prevalent in older adults and are closely interrelated. A growing body of evidence suggests that patients with T2DM have a significantly higher prevalence of both OP and SAC1,22,23. T2DM is closely linked to oxidative stress and chronic inflammation, which are key contributors to bone and muscle deterioration24,25. Reactive oxygen species (ROS), which increase with aging or inflammatory states, disrupt skeletal homeostasis by inducing apoptosis in osteoblasts and osteocytes through signaling pathways such as MAPK and reducing osteoblast differentiation and mineralization24,25. Additionally, poor glycemic control, long disease duration, and diabetic complications significantly raise the risk of osteoporosis and fractures26,27. SAC is also more common in T2DM patients due to impaired insulin sensitivity, which diminishes insulin’s anabolic effects on muscle, leading to reduced protein synthesis and increased degradation, ultimately causing loss of muscle mass and strength28. Chronic hyperglycemia further contributes to the accumulation of advanced glycation end products (AGEs), which are associated with declines in grip strength, leg strength, and walking speed29. Inflammatory cytokines also increase T2DM, exacerbating muscle wasting and functional decline30. As SAC impairs postural support and increases fall risk, it further contributes to fracture susceptibility in diabetic patients31,32,33.
During the peri- and postmenopausal stages, declining ovarian function causes fluctuating levels of follicle-stimulating hormone (FSH) and a marked decrease in estrogen, leading to reduced bone strength and increased fracture risk34. The rapid decline in estrogen secretion after menopause is strongly associated with accelerated bone loss35. Estrogen plays a critical role in regulating bone and muscle metabolism via its interaction with estrogen receptors, and its deficiency impairs osteoblast function and skeletal muscle maintenance8. Aging also reduces intestinal calcium absorption, resulting in a negative calcium balance that can lead to secondary hyperparathyroidism and enhanced bone resorption36. In addition, age-related decline in renal synthesis of 1,25-(OH)₂D contributes to vitamin D deficiency, further promoting bone loss through increased osteoclast activity36. These metabolic shifts contribute to decreased bone mineral density (BMD) and increased skeletal fragility. At the cellular level, aging alters mesenchymal stem cell differentiation: activation of peroxisome proliferator-activated receptor gamma (PPARγ) favors adipogenesis over osteogenesis, further reducing bone formation potential37. Collectively, these endocrine and metabolic changes with aging significantly heighten the risk of osteoporosis in postmenopausal women.Skeletal muscle plays a vital role in bone health through mechanical and biochemical mechanisms. Muscle contraction generates local mechanical loading on bone, which activates osteoblasts via mechanotransduction, promoting bone formation and survival38. In addition, muscle-derived myokines have anabolic effects on bone, further supporting bone remodeling and structural maintenance. Appendicular lean mass (ALM), which reflects the muscle mass of the limbs, is particularly important for posture, locomotion, and weight-bearing, and has been shown to positively correlate with bone mineral density (BMD) in diverse populations, including African American, Caucasian, and Chinese cohorts39. Low ALM is a core component of sarcopenia, which increases the risk of falls, fractures, and osteoporosis1,40. While absolute ALM exerts protective effects on bone via mechanical loading and myokine secretion, ALM/Ht2—a diagnostic criterion for sarcopenia—reflects relative muscle deficiency. Lower ALM/Ht2 indicates disproportionate muscle loss for height, exacerbating osteoporosis risk despite higher absolute ALM in taller individuals. This aligns with AWGS guidelines where low ALM/Ht2 defines sarcopenia, a known osteoporosis risk factor19. Moreover, skeletal muscle and adipose tissue contribute positively to bone mass through gravitational loading and external mechanical forces, which drive bone modeling and remodeling41. Adipose tissue also secretes estrogen, which enhances osteoblast activity and inhibits osteoclast-mediated resorption, further promoting bone formation42.
Body composition indicators such as ALM and body mass index (BMI) are key predictors of osteoporosis risk. Although low BMI is a recognized risk factor for both OP and SAC43, it fails to distinguish between fat and lean mass, limiting its accuracy. ALM, in contrast, captures functional muscle mass more directly and has been identified as a more precise predictor of bone health. Our study evaluated the relationship between ALM and OP in elderly postmenopausal women with T2DM and found that lower ALM and lower BMI were significantly associated with an increased risk of osteoporosis, suggesting that each is a protective factor when maintained at sufficient levels. These findings are consistent with previous studies showing a negative association between ASMI and osteoporosis in male T2DM patients22. Interestingly, our study also found that T2DM patients with peripheral neuropathy had a lower incidence of osteoporosis, contrasting with earlier meta-analytic findings44. This discrepancy may be attributed to increased clinical attention—once neuropathy is diagnosed, physicians may proactively prescribe calcium and vitamin D supplementation, thereby reducing OP risk. Collectively, these results highlight that both absolute and relative muscle mass and body weight play crucial roles in modulating osteoporosis risk among postmenopausal women with T2DM.
Emerging evidence suggests that the immune system also plays a role in bone homeostasis. In our study, lymphocyte count was identified as a potential protective factor against osteoporosis, aligning with Peng et al.‘s prior findings45. Lower lymphocyte levels in OP patients may reflect chronic inflammation and immune exhaustion, likely caused by sustained exposure to pro-inflammatory cytokines such as TNF-α and IL-646. Conversely, adequate lymphocyte reserves may indicate better immune regulation, indirectly supporting bone anabolism through reduced osteoclastogenic signaling. However, as specific lymphocyte subsets (e.g., CD4+/CD8 + ratios) were not analyzed in this study, this observation requires further validation through studies incorporating detailed immunophenotyping. Additionally, we observed a lower prevalence of osteosarcopenia (9.24%) compared to previous reports from Chinese community-based studies, which documented rates as high as 15.1% in elderly women47. This discrepancy may be partially explained by the younger average age in our cohort (68 years) relative to that of the reference population (74.9 years), as advancing age is a well-established independent risk factor for osteosarcopenia48. Furthermore, an unexpected finding from our model was the paradoxical association between serum 25(OH)D levels and osteoporosis risk, whereby higher vitamin D levels did not appear protective in the nomogram. This counterintuitive result may reflect confounding by indication, as patients already diagnosed with osteoporosis are more likely to receive vitamin D supplementation, thus elevating serum levels without reversing disease status. Crucially, however, our study lacked data on vitamin D, calcium, and anti-osteoporosis medication usage. The absence of this key information prevents a direct verification of the confounding-by-indication hypothesis and represents a significant limitation, as it is a potential unmeasured confounder. Another possible explanation is reverse causation, where individuals at higher fracture risk undergo more frequent monitoring and targeted supplementation. These complexities highlight the importance of interpreting 25(OH)D values in the context of clinical history and treatment exposure. Clinicians using the nomogram should be cautious in over-relying on serum vitamin D as an isolated predictor and instead consider it alongside other musculoskeletal and metabolic markers to avoid misinterpretation and inappropriate decision-making.
Several limitations of this study should be acknowledged. First, the retrospective cross-sectional design limits the ability to establish causal relationships between the variables analyzed. Second, the extended study period (2008–2024) may introduce temporal heterogeneity. While major metabolic parameters were stable, this long timeframe could be subject to unmeasured secular trends, including technological changes such as updates and calibrations of DXA machines, evolution in diabetes and osteoporosis treatment guidelines, and improvements in the average nutritional status of the population. These factors could introduce variability that our study was not designed to fully capture. Third, although our sample size was substantial, the study population was drawn exclusively from inpatient patients at the Department of Endocrinology of a single tertiary medical center (First Affiliated Hospital of Fujian Medical University). This may limit the generalizability of our findings to other clinical settings, particularly outpatient populations or community-dwelling individuals with T2DM who may have different clinical characteristics. Additionally, our cohort comprised patients receiving standardized medical interventions, which may further reduce the generalizability to broader populations, such as those seen in primary care or with lower treatment adherence. Fourth, as noted previously, we lacked critical data on the use of supplements and medications, including calcium, vitamin D, and anti-osteoporosis drugs, which are important potential confounding factors. Finally, the lack of subgroup analyses based on temporal cohorts or socioeconomic factors represents an important limitation that should be addressed in future research. To address these limitations, we propose a multicenter, prospective validation study across three cohorts: (1) treatment-naïve patients, (2) patients with low adherence, and (3) patients receiving optimized standard care. This future study will incorporate systematic collection of socioeconomic data and perform temporal subgroup analyses to account for potential secular trends. This stratified design would enhance the external validity and predictive precision of future diagnostic models and improve their clinical applicability in real-world settings.