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Group-based trajectory modeling for sarcopenia risk assessment and analysis of influencing factors in chronic respiratory diseases
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Chuan ZHAO1, Lan-ying PEI1, Ya-jing HE2, Jian-sheng LI2
Modern Preventive Medicine | 2025, 52(23) : 4230 - 4235
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Modern Preventive Medicine | 2025, 52(23): 4230-4235
• Epidemiology and Statistical Methods •
Group-based trajectory modeling for sarcopenia risk assessment and analysis of influencing factors in chronic respiratory diseases
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Chuan ZHAO1, Lan-ying PEI1, Ya-jing HE2, Jian-sheng LI2
Affiliations
  • Department of Preventive Medicine, School of Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan 450046,China
Published: 2025-12-10 doi: 10.20043/j.cnki.MPM.202504565
Outline
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Objective

To explore the developmental trajectories of sarcopenia and its influencing factors in patients with chronic respiratory diseases.

Methods

The data from three waves (2011, 2013, and 2015) of the China Health and Retirement Longitudinal Study (CHARLS) were used to screen patients with chronic respiratory diseases who had sarcopenia-related information. Group-based trajectory modeling was employed to fit the developmental trajectories of sarcopenia in these patients,and multinomial logistic regression was used to analyze the influencing factors.

Results

A total of 1 138 chronic respiratory diseases patients with sarcopenia-related information were included in the study. Four developmental trajectories were identified:the low-risk stable group (38.66%, n=440), the high-risk declining group (15.29%, n=174), the U-shaped risk group (23.46%, n=267), and the high-risk stable group (22.58%, n=257). Multinomial logistic regression analysis indicated that age, gender,education level, body mass index (BMI), disease type, and hypertension were the influencing factors for the developmental trajectories of sarcopenia in patients with chronic respiratory diseases.

Conclusion

The progression of sarcopenia in patients with chronic respiratory diseases is characterized by dynamism and reversibility. Intervention should be preferentially carried out for the elderly, females, individuals with low education levels, low BMI, respiratory system comorbidities, and hypertension to improve muscle function and overall prognosis in patients with chronic respiratory diseases.

Chronic respiratory diseases  /  Sarcopenia  /  Group-based trajectory modeling  /  Influencing factors
赵川, 裴兰英, 贺亚静, 李建生. 基于组轨迹模型的慢性呼吸系统疾病并发肌少症风险评估及影响因素分析. 现代预防医学, 2025 , 52 (23) : 4230 -4235 . DOI: 10.20043/j.cnki.MPM.202504565
Chuan ZHAO, Lan-ying PEI, Ya-jing HE, Jian-sheng LI. Group-based trajectory modeling for sarcopenia risk assessment and analysis of influencing factors in chronic respiratory diseases[J]. Modern Preventive Medicine, 2025 , 52 (23) : 4230 -4235 . DOI: 10.20043/j.cnki.MPM.202504565
Year 2025 volume 52 Issue 23
33
16
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Article Info
doi: 10.20043/j.cnki.MPM.202504565
  • Receive Date:2025-04-29
  • Online Date:2026-11-02
  • Published:2025-12-10
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  • Received:2025-04-29
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    Department of Preventive Medicine, School of Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan 450046,China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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