The Association Between Low Muscle Mass and the Risk of Depressive Symptoms: A Cross-Sectional Study Based on the Chinese Longitudinal Health Longevity Survey (CLHLS).
Аннотация
BACKGROUND
Many studies have shown a strong link between sarcopenia and depression, and low muscle mass (LMM) is an important component in the diagnosis of sarcopenia; however, there have been no studies on the relationship between LMM and depressive symptoms in the Chinese elderly population. To estimate the potential relationship between LMM and depressive symptoms among older adults, a cross-sectional analysis was conducted utilizing data from the Chinese Longitudinal Health Longevity Survey (CLHLS).
METHOD: The study sample comprised 11,711 individuals aged 65 years or older (mean age 83.0 ± 10.9) from the CLHLS database in 2018. We used the corrected appendicular skeletal muscle mass (ASM) prediction formula to assess muscle mass and the 10-item Center for Epidemiological Studies-Depression Scale (CES-D-10) to assess depressive symptoms. A multivariate logistic regression model and restricted cubic spline (RCS) curves were employed to investigate the association between LMM and depressive symptoms.
RESULTS
The study findings revealed a 1.16-fold higher risk of depressive symptoms in the LMM group compared to the control group (adjusted odds ratio [aOR]: 1.16, 95% confidence intervals [95% CI]: 1.05-1.29, p < 0.001). Furthermore, for every one-point decrease in LMM score below 7.87, the risk of depressive symptoms increased by 8%, with statistical significance. However, when the LMM score was greater than or equal to 7.87, the decrease in the LMM score did not significantly increase the risk of depressive symptoms.
CONCLUSION
Our study suggests LMM is a risk factor for depressive symptoms in the elderly Chinese population, and within a certain range, the risk of depressive symptoms increases as the LMM score decreases. Physical exercise may be an effective strategy to maintain optimal muscle mass and help the mental health of the elderly.
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