Sarcopenia has become a heavy disease burden among the elderly. Lipid metabolism was reported to be involved in many degenerative diseases. This study aims to investigate the association between dysregulated lipid metabolism and sarcopenia in geriatric inpatients. This cross-sectional study included 303 patients aged ≥ 60, of which 151 were diagnosed with sarcopenia. The level of total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY), BMI, and fat percentage, were compared between sarcopenia and non-sarcopenia patients. The Spearman correlation coefficient was used to estimate the association between sarcopenia and the level of lipid metabolism. To determine risk factors related to sarcopenia, a multivariate logistic regression analysis was carried out. Risk prediction models were constructed based on all possible data through principal component analysis (PCA), Logistic Regression (LR), Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and eXtreme Gradient Boosting (XGboost). We observed rising prevalence of sarcopenia with increasing age, decreasing BMI, and fat percentage (p < 0.001, Cochran Armitage test). Multivariate logistic regression analysis revealed sarcopenia’s risk factors, including older age, male sex, lower levels of BMI, TC, and TG, and higher levels of LDL and HCY (p < 0.05). The sarcopenia risk prediction model showed the risk prediction value of sarcopenia, with the highest area under the receiver operating curve (AUC) of 0.775. Our study provided thorough insight into the risk factors associated with sarcopenia. It demonstrated that an increase in lipid metabolism-related parameters (BMI, TG, TC), within normal reference ranges, may be protective against sarcopenia. The present study can illuminate the direction and significance of lipid metabolism-related factors in preventing sarcopenia.

The C-reactive protein-albumin-lymphocyte (CALLY) index, which integrates albumin, lymphocytes, and C-reactive protein levels, has emerged as a novel method to assess nutritional and inflammatory statuses in patients. This study examined the correlation between the CALLY index and sarcopenia risk using two cohorts: 1804 community dwellers from the NHANES database in the United States and 139 patients from the Department of Gerontology at Kunshan Hospital, China. In the US community cohort, RCS curve analysis was used to examine the non-linear relationship between inflammatory/nutritional markers and sarcopenia, subgroup analysis was also conducted. Logistic regression was employed to evaluate the association between the CALLY index and the risk of sarcopenia in both cohorts. Results demonstrated a significant non-linear relationship between the CALLY index and the risk of sarcopenia (P < 0.001). Elevated levels of the CALLY index are independently linked to a decreased risk of sarcopenia in both community residents (OR = 0.35, 95% CI 0.20–0.57, Q3 CALLY index and OR = 0.26, 95% CI 0.11–0.56, Q4 CALLY index) and hospitalized patients (OR = 0.35, 95% CI 0.12–0.96). This finding identified low CALLY index as a conveniently measurable parameter, serving as a nutritional and inflammatory risk factor for sarcopenia.

Sarcopenia greatly reduces the quality of life of the elderly, and iron metabolism plays an important role in muscle loss. This study aimed to investigate the association between iron status and sarcopenia. A total of 286 adult patients hospitalized between 2019 and 2021 were included in this study, of which 117 were diagnosed with sarcopenia. Serum iron, total iron binding capacity (TIBC), transferrin, and transferrin saturation levels were compared between groups with and without sarcopenia and were included in the logistic analyses, with significant variables further included in the logistic regression model for the prediction of sarcopenia. Serum iron, TIBC, and transferrin levels decreased significantly in the sarcopenia group (p < 0.05), and were negatively associated with handgrip strength, relative skeletal muscle index, and multiple test performances (p < 0.05). Multivariate logistic analysis showed that sex, age, body mass index (BMI), and serum iron level were independent risk factors for sarcopenia. In the final logistic regression model, male sex (odds ratio [OR] 3.65, 95% confidence interval [CI] 1.67–7.98), age > 65 years (OR 5.40, 95% CI 2.25–12.95), BMI < 24 kg/m² (OR 0.17, 95% CI 0.08–0.36), and serum iron < 10.95 μmol/L (OR 0.39, 95% CI 0.16–0.93) were included. Our study supported the impact of iron metabolism on muscle strength and performance.

Background: The Controlled Nutritional Status (CONUT) metric has demonstrated effectiveness as a prognostic indicator for acute and chronic diseases in addition to other wasting conditions. However, its association with sarcopenia in elderly hospitalized patients remains insufficiently explored. Our study objectives included the assessment of the potential of CONUT score to predict sarcopenia onset. Methods: Our study was a single center retrospective cohort study. Patients from the Department of Geriatrics of the First People’s Hospital of Kunshan were recruited for this study. Multiple indicators related to nutrition and sarcopenia, including CONUT, Prognostic Nutritional Index (PNI), triglyceride–total cholesterol–body weight index (TCBI), Geriatric Nutritional Risk Index (GNRI), and handgrip strength (HGS). Spearman’s and Pearson’s correlation were calculated to assess the associations between nutritional indices and sarcopenia-related indicators. The demographic characteristics, physical examination findings and laboratory parameters were included in univariate logistic regression. Based on the results of univariate logistic regression and theoretical analysis, variables were selected for multivariate logistic regression in order to identify risk factors for sarcopenia. Results: A total of 236 elderly hospitalized patients were included. Malnutrition was prevalent in patients with sarcopenia. The optimal CONUT cut-off values were defined as >4 for males and >3 for females, dividing patients into high CONUT ( n = 140, 59.32%) and low CONUT ( n = 96, 40.58%) groups. Patients in the high CONUT group had lower levels of albumin, prealbumin, hemoglobin, and total lymphocyte count. Multivariate logistic regression analysis showed that a high CONUT score was an independent risk factor for sarcopenia ( OR:1.814, 95% CI: 1.019–3.255, p = 0.044 ). Male sex and low iron level were also demonstrated to be associated with sarcopenia. Conclusion: CONUT score is an independent risk factor for sarcopenia and may serve as a practical indicator for sarcopenia risk screening in elderly hospitalized patients.

Background: Sarcopenia has become a heavy disease burden among the elderly. Lipid metabolism was reported to be involved in many degenerative diseases. This study aims to investigate the association between dysregulated lipid metabolism and sarcopenia in geriatric inpatients. Methods: This retrospective cohort study included 303 patients aged ≥ 60, of which 151 were diagnosed with sarcopenia. The level of total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY), BMI, and fat percentage, were compared between sarcopenia and non-sarcopenia patients. The Spearman correlation coefficient was used to estimate the association between sarcopenia and the level of lipid metabolism. To determine risk factors related to sarcopenia, a multivariate logistic regression analysis was carried out, and a risk prediction logistic model was derived based on significant risk factors in multivariate logistic analysis. Results: We observed a trend of rising sarcopenia prevalence with increasing age, decreasing BMI, and fat percentage (p < 0.001, Cochran Armitage test). Multivariate logistic regression analysis revealed sarcopenia’s risk factors, including older age, male sex, lower levels of BMI, TC, and TG, and higher levels of LDL and HCY (p < 0.05). The multivariate logistic regression model showed the risk prediction value of sarcopenia, with an area under the receiver operating curve (AUC) of 0.7466. Conclusions: Our study provided thorough insight into the risk factors associated with sarcopenia. It demonstrated that an increase of lipid metabolism-related parameters (BMI, TG, TC), within normal reference ranges, may be protective against sarcopenia. The present study can illuminate the direction and significance of lipid metabolism-related factors in preventing sarcopenia.