The study population consisted of individuals from multiple provinces and cities in the western region of China, representing various ethnic groups. This study relied on the ongoing prospective cohort study WCHAT, the methodology and study design of which has been previously published (16). The Ethics Committee of West China Hospital, Sichuan University, China reviewed and approved this study (reference number: 2017–445), and all participants signed the informed consent form (16). The participants were recruited from four provinces in western China, namely, Sichuan, Xinjiang, Guizhou, and Yunnan, with a focus on Sichuan. The participants represent various ethnic groups, including Han, Tibetan, Qiang, Yi, Hui, Zhuang, and Miao.

Inclusion criteria for participants: living in the region for at least 3 years; age ≥50 years; voluntary participation in the study. Exclusion criteria: expected lifespan of less than 6 months; acute diseases of important organs, such as the heart, liver, and kidneys, and severe diseases such as respiratory failure; refusal to participate in the survey.

A total of 7,536 participants were recruited in the multi-ethnic regions in western China. Bioelectrical impedance analysis (BIA) data were obtained from 4,500 individuals, as well as information on sleep, anxiety, and depression scales, which were ultimately used to analyze individuals with sarcopenia. All data collection personnel involved in this study received rigorous training, and health checks were conducted by relevant professional technicians. This study was approved by relevant committees in china, and every patients provided written consent. All methods used followed relevant regulations.

Sarcopenia is characterized by an accelerated loss of muscle mass and function. For primary health care or community-based health purposes, the Asian Working Group on Sarcopenia (AWGS) defined “possible sarcopenia” as low muscle strength or physical function (15). In this study, we followed the screening methods recommended by the AWGS, using the sarcopenia assessment pathways corresponding to clinical research, categorizing sarcopenia into diagnosed and severe sarcopenia. The primary diagnostic criterion for individuals with diagnosed sarcopenia was a decrease in muscle mass. These individuals also met one of two secondary criteria, namely, a decline in handgrip strength or gait speed. Individuals suffering from severe sarcopenia met both of these secondary criteria. The specific assessment methods and data collection are described below.

Muscle mass was assessed by bioimpedance analysis (BIA) using the INbody770 body composition instrument for data collection. The reliability of this instrument was validated in the relevant Chinese population (17, 18). Following the AWGS2019 recommendations, we used a cutoff value of 7.0 kg/m² for men and 5.7 kg/m² for women for the determination of the skeletal muscle mass index (ASMI) (15).

Handgrip testing is used as a reflection of muscle strength. The handgrip strength of the subjects’ dominant hand was measured using a dynamometer (EH101; Camry, Zhongshan). During the measurement, the subjects were asked to stand with their feet naturally apart, arms hanging down, and to perform the maximum grip strength test on two separate occasions, recording the maximum value. The standard for weak grip strength is <18 kg for females and <28 kg for males (15).

The general gait speed test requires participants to wear flat shoes and may use a walking aid for measuring walking speed. Participants can rest during the measurement but should not sit down. The AWGS recommends a critical value of 1.0 m/s for gait speed in individuals with muscle weakness.

In our study, following the AWGS2019 criteria, sarcopenia was defined as low muscle mass and low handgrip strength or low gait speed. And severe sarcopenia was defined as low muscle mass combined with low handgrip strength and low gait speed.

As an indicator of subjective sleep quality in the past month, the Pittsburgh Sleep Quality Index (PSQI) was used to gauge sleep quality. It consists of 19 items and is commonly used in the diagnosis of sleep disorders in both clinical and research settings, serving as a standardized assessment for patients with sleep difficulties. A PSQI score above 5 indicates poor sleep quality, while a PSQI score below 5 indicates good sleep quality.

The Generalized Anxiety Disorder Questionnaire (GAD-7) was used to measure anxiety. Currently, GAD-7 is one of the most widely used measures for anxiety assessment in clinical practice and research due to its diagnostic reliability and high efficiency (19).

To assess depressive symptoms, we used the 15-item Geriatric Depression Scale, which was developed to evaluate the unique symptoms commonly exhibited by depressed older adults, such as somatic symptoms, anxiety, and cognitive decline. A GDS-15 score above 5 indicates depressed mood (20).

This included demographics (sex, age, ethnicity, marital status, employment status, living arrangements), lifestyle factors (alcohol consumption, smoking status), and health conditions (chronic diseases, such as hypertension, diabetes, heart disease, and COPD).

Data were analyzed using SPSS 22.0. Continuous variables are expressed as mean and standard deviation (X ± SD) and were compared using t-tests. Categorical variables are presented as percentages and were analyzed with χ² tests. Descriptive statistics were used to describe demographic and clinical characteristics, with Chi-square and Kruskal-Wallis tests for analysis. Multivariate logistic regression analyses were performed to evaluate the relationship between sarcopenia with sleep quality, depression and anxiety status with corresponding 95% confidence interval (CI). We contrasted three models as follows: model 1, adjusted for age, gender and ethnics; model 2: adjusted for age, gender, ethnics, marriage status, living alone, life styles (smoking, drinking tea); model 3: adjusted for age, gender, ethnics, marriage status, living alone, life styles (smoking, drinking tea), educational level, and chronic diseases.

The quality of sleep is an important factor in maintaining physical and mental health, and disruptions or changes in circadian rhythms are associated with the development of many chronic diseases, including sarcopenia. Sleep quality is a multidimensional structure that includes sleep latency, awakening after sleep onset, frequency and number of awakenings, as well as subjective reports of feelings and mental state upon waking. Sleep quality is associated with reduced quality of life, increased incidence of disease, and higher mortality rates among older adults (23, 24).

There is research indicating that the sleep–wake cycle is associated with the maintenance of skeletal muscle, playing a crucial role in many physiological activities, muscle structure, and the metabolism of skeletal muscle. Many hormones, such as insulin, glucagon, cortisol, and growth hormone, exhibit circadian oscillations. The activity of certain metabolic enzymes and transport systems involved in the metabolism of cholesterol, glucose, and lipid receptors is also regulated by the circadian system. Therefore, disruption of the sleep–wake cycle may affect skeletal muscle metabolism (25). Sleep disorders have been observed to increase stress hormone levels, such as cortisol, which may trigger muscle breakdown and inhibit muscle protein synthesis, leading to the occurrence or progression of sarcopenia (26). At the same time, sleep disorders may disrupt the balance of growth hormones, potentially leading to sarcopenia (27). Sleep deprivation is also related to inflammatory responses, resulting in exacerbated systemic inflammation (28). Systemic inflammation can accelerate muscle degeneration and hinder muscle function, potentially worsening sarcopenia (29). Research indicates that sleep disorders can also affect neurological function and motor control which may impair neuromuscular coordination and gradually lead to muscle damage. In disrupted circadian rhythm models, the absence of the Bma/1 gene has been observed to lead to sarcopenia and several pathological muscle diseases, including reduced mitochondrial density and altered mitochondrial respiration, fiber type displacement, and impaired muscle segment structure (30, 31). Chronic sleep deprivation may accelerate sarcopenia through disrupted growth hormone signaling and elevated pro-inflammatory cytokines (25). Research has shown an association between sleep initiation and/or maintenance and sarcopenia in older Japanese individuals (32). This study found a significant correlation between sleep quality and severe sarcopenia, but no significant correlation with diagnosed sarcopenia. Thus, in the aging population with sleep disorders, improving sleep quality may slow down muscle loss and prevent or delay the onset of severe sarcopenia.

Anxiety shows strong comorbidity with depression in older adults, and it is also associated with cognitive decline (13). Anxiety and depression thus form a common geriatric syndrome. Both are also related to circadian rhythms, which are closely linked to the function of skeletal muscles (30). Research has shown a close association between anxiety and depression and the fragmentation of the 24-h activity rhythm in individuals middle-aged and older (33). Anxiety, depression, and physical activity are significantly correlated, with lower levels of daily activity being a core feature of mood disorders (34). Currently, there is limited research on anxiety disorders, although some research findings indicate that they can influence depression in terms of psychomotor retardation, lower levels of daily activities, and circadian rhythm disturbances (35). There are many potential mechanisms linking sarcopenia with mental disorders (35). Brain-derived neurotrophic factor, a neurotrophic factor produced by skeletal muscle, is associated with anxiety disorders (36). Research has found that chronic inflammation plays a vital role in the progression of sarcopenia and affects the evolution of anxiety disorders (37–39). Additionally, there are many common lifestyle risk factors for both sarcopenia and anxiety disorders, including physical inactivity, malnutrition, and smoking (35). But in this study, anxiety in the multi-ethnic region of western China was not significantly associated with the different sarcopenia groups, while depression showed significant associations with severe sarcopenia.

Depression, characterized by low mood, slow thinking, disrupted sleep or appetite, and feelings of fatigue, is a common mental disorder in older adults. Some studies have found a relationship between depression and body composition, involving factors such as skeletal muscle mass, strength, and muscle function, all of which are directly related to sarcopenia (40–42). Both sarcopenia and depression are associated with reduced physical activity, upregulation of inflammatory factors, and hormonal dysregulation of the hypothalamic–pituitary–adrenal axis (43). However, no significant association has been found between sarcopenia and depression (44), while there are also reports suggesting a significant association between the two (45). Emerging evidence suggests that poor dietary quality, characterized by low protein and micronutrient intake, may exacerbate sarcopenia progression and comorbid anxiety/depression (46). According to the diagnostic criteria of 2019 AWGS for sarcopenia, we subdivided sarcopenia into different groups and collected data on depression, which further confirmed a significant correlation between depression and both diagnosed and severe sarcopenia.

However, this study also has certain limitations. Although the Pittsburgh Sleep Quality Index is a validated and reliable measure, it cannot perfectly capture sleep parameters compared to the gold standard of polysomnography. Additionally, for participants with anxiety and depression, further discussion is needed to determine if their medication status may have influenced their muscle function.