With the increasing life expectancy of women worldwide, the peri- and postmenopausal female population is rapidly growing. It is estimated that by 2050, the number of women aged 50 and above will increase from 1 billion in 2020 to 1.6 billion (1). Menopause, typically occurring around age 51, affects most women, with symptoms lasting an average of seven years (2). Over 35 menopause-related symptoms have been identified, including hot flashes, sweating, sleep disturbances, anxiety, mood swings, and decreased libido (3, 4), but musculoskeletal symptoms are often overlooked. Studies show about 70% of middle-aged women experience musculoskeletal syndromes during peri- and postmenopause (5, 6), leading to muscle mass decline, impaired function, increased fall risk, and reduced quality of life.

The muscle mass of postmenopausal women decreases by approximately 0.6% per year (7), and if not addressed early, this can lead to severe long-term health consequences. Early detection and management of muscle loss and menopausal symptoms are therefore crucial in clinical practice.

Existing studies suggest that menopause-related symptoms may be associated with lean body mass (8). International research has also demonstrated that reduced muscle mass correlates with more severe vasomotor symptoms (9, 10). However, an Indian study reported no significant correlation between quality of life and sarcopenia in postmenopausal women (11), indicating that these associations may vary across populations. Estradiol (E₂), the most biologically active estrogen, affects bones, tendons, muscles, cartilage, ligaments, and adipose tissue (12, 13), suggesting a potential role in the link between menopausal symptoms and muscle mass. However, research on this relationship remains limited, and the specific mechanisms are still unclear.

Therefore, this study investigates the association between menopause-related symptoms and muscle mass in Chinese peri- and postmenopausal women, focusing on the mediating role of hormone levels. The findings aim to provide evidence for the early management of muscle loss and improve health care strategies for perimenopausal women.

Our study explored the relationship between menopausal symptoms and MMI and analyzed the mediating role of E₂ levels. The results showed a significant negative correlation between KMI and MMI, with E₂ playing a partial mediating role between the two. This finding provides new evidence for understanding the relationship between muscle mass decline and menopausal symptoms in women during the perimenopausal and postmenopausal stages.

Menopausal symptoms are complex and influenced by numerous factors. This study is the first to identify a significant negative correlation between KMI and MMI, with MMI being an independent protective factor for moderate to severe menopausal symptoms, regardless of age, education level, menopausal stage, hypertension history, and levels of FSH and E₂. At present, studies on the effects of body composition on menopausal symptoms are scarce. Previous studies have suggested that lean body mass, particularly in the trunk, serves as a protective factor for moderate to severe menopausal symptoms (8). In addition, a study from Korea showed that lower grip strength (a commonly used indicator for diagnosing sarcopenia) is positively correlated with higher KMI scores (9). When assessing menopausal symptoms such as vasomotor symptoms (VMS) alone, some studies have also found a significant correlation between sarcopenia and VMS (10). However, some studies have reported an inverse correlation between the prevalence of sarcopenia and the incidence of VMS, while the paraspinal muscle index shows a positive correlation with the incidence of VMS (20). Moreover, a higher body fat percentage in perimenopausal women is strongly linked to increased severity of menopausal symptoms (2, 21). Notably, in our stratified analysis, this relationship was more pronounced in premenopausal women, where the negative association between KMI and MMI remained significant even after adjusting for confounding variables and hormone levels, suggesting that muscle mass may play a more prominent role in influencing menopausal symptoms prior to the onset of menopause. Although our study provides new evidence on the link between muscle mass and menopausal symptoms, longitudinal data remain limited. Recent cohort studies from Canada and Switzerland indicate that sarcopenia incidence increases with age in postmenopausal women and is influenced by hormone therapy and physical activity (22, 23). These findings highlight the need for future longitudinal research to clarify causal relationships and guide personalized intervention strategies.

In addition, this study found that older women and those with lower educational levels had higher KMI (P<0.05), which is consistent with previous research (24, 25). This may be due to higher-educated women having better access to perimenopausal health information and managing symptoms more effectively through self-regulation.

Notably, this study found that menopausal symptoms were more severe in patients with hypertension, while no significant association was observed between diabetes and KMI. Previous studies have shown that systolic blood pressure, diastolic blood pressure, and dyslipidemia are positively correlated with menopausal quality of life scores, whereas fasting blood glucose and high-density lipoprotein have no significant relationship with total menopausal symptom scores (26). The decline in estrogen levels may lead to metabolic abnormalities, vasomotor dysfunction, and muscle mass loss, thereby exacerbating menopausal symptoms. Additionally, the occurrence of vasomotor symptoms is associated with an increased incidence of cardiovascular events. Studies have indicated that more frequent vasomotor symptoms are correlated with higher blood pressure, and compared to women without vasomotor symptoms, those experiencing vasomotor symptoms may be more susceptible to developing hypertension (27).

Further analysis of the mediating role of E₂ between MMI and KMI revealed that patients with higher FSH levels and lower E₂ levels had lower MMI (P<0.05). Moreover, E₂ played a significant mediating role in the relationship between MMI and KMI (P<0.01). This finding supports the potential mechanism of estrogen in muscle mass changes during the (peri)menopausal period. Estrogen not only acts as an inflammation regulator but also inhibits the release of the inflammatory cytokine TNF-α (28), TNF-α contributes to muscle protein breakdown and impairs the muscle’s capacity for repair (29), additionally, TNF-α is released by adipocytes, promoting fat accumulation and impairing muscle function (30–32). Declining ovarian function may directly adversely affect muscle mass through estrogen receptors in muscle and joint tissues (33). Satellite cells are stem cells located on muscle fibers, responsible for promoting muscle plasticity and regeneration (34). Satellite cells are stem cells located on muscle fibers, responsible for promoting muscle plasticity and regeneration (35).

This study has several strengths, including comprehensive data collection and the inclusion of key hormonal and body composition indicators. The statistical models were rigorously adjusted for major demographic and clinical variables. However, several limitations should be noted. First and foremost, the cross-sectional design of this study inherently limits the ability to establish causal relationships. Consequently, the temporal sequence among menopausal symptoms, hormone levels, and muscle mass cannot be determined, which restricts causal inference. Although confounding variables were considered, residual confounding may persist, particularly from unmeasured factors such as physical activity, dietary intake, sleep quality, and comorbidities, all of which are well-known to influence both muscle mass and menopausal symptoms. The absence of data on these key lifestyle factors represents an important limitation of this study and should be addressed in future research. In addition, while blood samples were collected at standardized times to minimize hormonal variability, a single estradiol measurement may not reflect true baseline levels due to diurnal fluctuations and cycle irregularity, especially in perimenopausal women. This could attenuate observed associations between E2 and muscle mass. Finally, although bioelectrical impedance analysis using the InBody 270 is practical and widely used in field settings, it may overestimate skeletal muscle mass due to its sensitivity to hydration and reliance on predictive equations (36, 37). Future longitudinal or interventional studies with repeated assessments and broader population samples are warranted to validate these findings and explore the underlying mechanisms in more depth. Despite these limitations, our study adds to the growing body of evidence supporting the link between hormonal changes, muscle mass, and menopausal symptoms, and underscores the importance of early monitoring and intervention in perimenopausal women.

This study found a negative correlation between KMI and MMI, with E2 partially mediating this relationship. These findings highlight the potential importance of considering muscle mass changes in perimenopausal health assessments. Early identification of reduced muscle mass can not only inform future intervention strategies such as exercise and hormonal therapy but also emphasizes the need for methods of early detection, such as regular body composition analysis and grip strength testing. Additionally, possible therapeutic measures including tailored exercise programs, nutritional supplementation, and hormone therapy warrant further exploration and application. These data could help promote awareness campaigns that, in the long term, may improve the quality of life for postmenopausal women. Nevertheless, the clinical application of personalized interventions should be interpreted cautiously and requires validation through longitudinal or interventional studies.