A nomogram to predict sarcopenia in middle-aged and older women: a nationally representative survey in China.

Abstract

Background: Sarcopenia is a disease characterized by losing muscle mass, strength, and function with age. Studies have shown that sarcopenia is generally higher in women than in men. Therefore, this study used the 2015 China Health and Retirement Longitudinal Study (CHARLS) data to explore further the risk factors associated with sarcopenia in middle-aged and older Chinese women.

Methods: In this study, data from the 2015 CHARLS database were analyzed, comprising 7,805 eligible participants. Participants were categorized into either the sarcopenia group (n = 2,160) or the non-sarcopenia group (n = 5,645) based on the presence or absence of sarcopenia. Through the utilization of logistic regression analysis, multiple risk factors were identified. Additionally, the predictive value of these risk factors was assessed by applying receiver operating characteristic (ROC) curve analysis. Subsequently, a visual nomogram prediction model was developed by incorporating the identified risk factors into R4.1.2 software.

Results: Age, area, education, marriage, waist circumference, stroke, body pain, depression, and region may be closely related to Chinese women with sarcopenia. In addition, this study integrated these sarcopenia-related variables into a comprehensive index, and ROC analysis results showed that the AUC of the composite index was 0.738.

Conclusions: This study found that sarcopenia in Chinese women may be closely related to age, waist, education, marriage, area, stroke, physical pain, depression, and region. In addition, this study constructs a nomogram to help clinicians better screen potential female patients with sarcopenia.