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Objective this retrospective study aims to compare the prevalence and diagnostic agreement of sarcopenic obesity (SO) using different obesity diagnostic methods among Chinese community-dwelling older adults. Methods SO was diagnosed with sarcopenia and obesity diagnostic methods. Sarcopenia was defined using the Asian Working Group for Sarcopenia criteria 2019 (AWGS2019). Four widely used indicators were used to define obesity: body mass index (BMI), waist circumference (WC), percent of body fat (PBF) and visceral fat area (VFA). Cohen's kappa was used to analyse the diagnosis agreement of SO between different diagnostic methods. Results a total of 1,050 participants were included, including 347 men (71.3 ± 7.4 years) and 703 women (69.9 ± 7.5 years). The prevalence of sarcopenia was 25% in total participants, there was no difference between men (24.2%) and women (25.5%), (P  = 0.705). With different obesity diagnostic methods, the obesity prevalence ranged from 4.1 to 42.2%, the SO prevalence was 0.1–7.9%. The diagnosis agreement of SO was poor-to-moderate (κ ranged from −0.002 to 0.682). Among the four diagnostic methods, AWGS combined with BMI had the poorest agreement (κ = −0.002 with other methods), AWGS combined with VFA had the best agreement (κ = 0.641 and 0.682 with AWGS combined with PBF and with AWGS combined with WC, respectively). Conclusion the prevalence of SO vary considerably and the diagnostic agreement is poor-to-moderate with non-uniform diagnostic methods. BMI has the lowest sensitivity, whereas VFA has the highest sensitivity in diagnosis of SO, and VFA has a relatively good diagnostic agreement with other diagnostic methods. [ABSTRACT FROM AUTHOR]

To establish and validate a nomogram that predicts the risk of sarcopenia for community-dwelling older residents. Retrospective study. A total of 1050 community-dwelling older adults. Data from a survey of community-dwelling older residents (≥60 years old) in Hunan, China, from June to September 2019 were retrospectively analyzed. The survey included general demographic information, diet, and exercise habits. Sarcopenia diagnosis was according to 2019 Asian Working Group for Sarcopenia criteria. Participants were randomly divided into the development group and validation groups. Independent risk factors were screened by multivariate logistic regression analysis. Based on the independent risk factors, a nomogram model was developed to predict the risk of sarcopenia for community-dwelling older adults. Both in the development and validation sets, the discrimination, calibration, and clinical practicability of the nomogram were verified using receiver operating characteristic curve analysis, Hosmer-Lemeshow test, and decision curve analysis, respectively. Sarcopenia was identified in 263 (25.0%) participants. Age, body mass index, marital status, regular physical activity habit, uninterrupted sedentary time, and dietary diversity score were significant contributors to sarcopenia risk. A nomogram for predicting sarcopenia in community-dwelling older adults was developed using these factors. Receiver operating characteristic curve analysis showed that the area under the curve was 0.827 (95% CI 0.792-0.860) and 0.755 (95% CI 0.680-0.837) in the development and validation sets, respectively. The Hosmer-Lemeshow test yielded P values of.609 and.565, respectively, for the 2 sets. The nomogram demonstrated a high net benefit in the clinical decision curve in both sets. This study developed and validated a risk prediction nomogram for sarcopenia among community-dwelling older adults. Sarcopenia risk was classified as low (<11%), moderate (11%-70%), and high (>70%). This nomogram provides an accurate visual tool to medical staff, caregivers, and older adults for prediction, early intervention, and graded management of sarcopenia. [ABSTRACT FROM AUTHOR]