Journal of Shandong University (Health Sciences) ›› 2025, Vol. 63 ›› Issue (4): 26-35.doi: 10.6040/j.issn.1671-7554.0.2024.1040

• Nutrition, Gut Microbiota, and Associated Diseases • Previous Articles    

Development and validation of a prediction model for muscle mass loss in office workers

CHEN Yingyi1, YOU Qian1, WANG Yi1, ZHANG Fan2, LI Feng2, JI Shuming3, XU Haoyuan4, RAO Zhiyong1   

  1. 1. Department of Clinical Nutrition, West China Hospital, Sichuan University;
    2. Health Management Center, West China Hospital, Sichuan University;
    3. Clinical Research Management Department, West China Hospital, Sichuan University;
    4. West China School of Medicine, Sichuan University, Chengdu 610041, Sichuan, China
  • Published:2025-04-08

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Abstract: Objective To investigate and analyze the prevalence of muscle mass loss in office workers and the contributing factors, and to construct and validate a risk prediction model to inform the development of an intervention program. Methods Two hundred and eighty-six office workers from institutions and agencies who underwent medical check-ups at the Health Management Center of West China Hospital of Sichuan University from March 2023 to December 2023 were selected and surveyed using food frequency questionnaires, exercise questionnaires, physical examination, body composition analysis, and laboratory tests. Factors influencing muscle mass were analyzed using R software(RStudio,version number 4.4.1), and a risk prediction model was established and validated. Results The prevalence of muscle mass loss was 26.22%; high glucose and low BMI were risk factors for muscle mass loss, high BUN/Cr, high actual daily energy intake/recommended daily energy intake ratio, high fresh fruits intake, high grip strength score and overweight were protective factors for muscle mass loss, and a model was constructed; the area under the ROC curve of the model was verified to be 0.83, and the Youden index was 0.52. The optimal risk threshold was set as 14.40%. The Hosmer-Lemeshow test and calibration curve assessed that the fit of the model was high(χ2=11.98,P=0.152), and predicted that the threshold probability value of the model was in the range of 0.07-0.93. Conclusion The prediction model in this study has a good predictive effect and good fit, which will facilitate medical and technical nurses to assess the risk of developing muscle mass loss and helps to provide a reference for early prevention for office workers at high risk of muscle mass loss.

Key words: Muscle mass loss, Incidence, Influencing factors, Predictive model, Sarcopenia

CLC Number: 

  • R685
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