背景：慢性阻塞性肺疾病（慢阻肺）是全球重大的公共卫生问题，具有较高的患病率和沉重的疾病负担。体力活动不足与慢阻肺患者的高死亡率、再入院风险及生活质量下降密切相关，亟需采取有效的干预措施。尽管现有研究提示体力活动对患者的健康有益，但是慢阻肺患者的体力活动水平仍有待进一步提升。明确影响慢阻肺患者体力活动的影响因素可为进一步构建精准干预策略提供科学依据。现有研究探讨的慢阻肺患者体力活动影响因素多聚焦于单一层面，缺乏对多层次因素的综合性研究。社会生态学模型为整合多维度因素提供了理论支持，但是目前尚缺乏基于该理论模型、结合我国文化背景深入探讨慢阻肺体力活动影响因素的研究。

目的：描述慢阻肺患者的体力活动现状；基于社会生态学模型探讨影响慢阻肺患者体力活动水平的多维因素。

方法：本研究为横断面研究，采用便利抽样法，选取2024年3月~2025年2月于北京方庄社区卫生服务中心全科门诊及北京清华长庚医院慢性阻塞性气道疾病个案管理门诊就诊的170例慢阻肺患者作为研究对象。使用老年人体力活动量表评估患者的体力活动水平，并通过一般资料调查表、改良呼吸困难指数、衰弱筛查量表、锻炼动机量表、中文版锻炼自我效能量表、社会支持量表和改编自社区体育环境问卷的三个子问卷，测量个体、人际、组织、社区和政策层面的影响因素。采用单因素分析、多元线性回归分析等方法确定慢阻肺患者体力活动水平的影响因素。

结果：1. 慢阻肺患者体力活动水平得分为84.50（44.29，133.55）。2. 单因素分析结果显示，基于社会生态学模型中个体层面的社会人口学特征、健康状况、锻炼动机和自我效能，人际层面的社会支持，组织层面的社区体育氛围环境和社区体育组织环境，社区层面的社区体育设施环境，政策层面的国家制度和社区制度等不同层面因素进行分组时，慢阻肺患者的体力活动总分在不同组别间的差异均具有统计学意义（P<0.05）。3. 多元线性回归分析结果表明，年龄（β=-0.196, P=0.011）、职业（β=-0.336, P=0.000）、FEV₁（β=-0.157, P=0.047）、衰弱状态（β=-0.171, P=0.040）、锻炼动机（β=0.264, P=0.005）和社区制度（β=-0.253, P=0.021）是体力活动水平的影响因素，共同解释了慢阻肺患者体力活动水平得分总变异的46.0%。

结论：1. 慢阻肺患者的体力活动水平处于中等水平。2. 社会生态学模型各层面在单因素分析中均与慢阻肺患者体力活动显著相关，但多因素分析仅个体及政策层面部分因素保持独立预测作用。个体层面上，年龄小、在职、低FEV₁、衰弱程度轻及强锻炼动机者体力活动水平更高；政策层面上，感知到的社区制度影响越低者体力活动水平越高。提示在制定干预措施时，应考虑患者的年龄、职业、肺功能基础等个体特征对活动水平的影响，同时从衰弱状态管理、锻炼动机激发和社区制度优化等多方面入手，提升慢阻肺患者的体力活动水平。

Background: Chronic obstructive pulmonary disease (COPD) remains a major global health challenge due to its high prevalence and substantial burden on healthcare systems. Low physical activity (PA) levels in COPD patients are strongly associated with increased mortality, higher readmission risks, and reduced quality of life, underscoring the urgent need for effective interventions. Although existing evidence confirms the health benefits of PA, PA levels among COPD patients remain persistently low. Identifying multi-level factors that influence PA is crucial in developing targeted intervention strategies. Current research mainly focuses on single factors influencing PA in COPD patients, with limited exploration of multi-level interactions. The social ecological model (SEM) provides a robust theoretical framework for integrating these multi-level factors. However, few studies have applied SEM to investigate PA influencing factors in COPD patients within China's cultural and healthcare contexts.

Objective: This study aims to describe PA levels among COPD patients and identify multi-level factors influencing PA using the SEM framework.

Method: This cross-sectional study recruited 170 COPD patients through a convenience sampling from the General Outpatient Department of Beijing Fangzhuang Community Health Service Center and Case Management Clinic for Chronic Obstructive Airway Diseases at Beijing Tsinghua Changgung Hospital between March 2024 and February 2025. PA levels were measured using the Physical Activity Scale for the Elderly. A self-designed general information questionnaire, modified Medical Research Council, FRAIL Scale, motives for physical activities measure-revised, self-efficacy for exercise scale, social support scale, and three sub-questionnaires adapted from the community sports environment questionnaire, were used to measure the influencing factors at individual, interpersonal, organizational, community and public policy levels. Univariate analysis and multiple linear regression analysis were used to identify the influencing factors of PA level in COPD patients.

Results: 1. The median PA score among COPD patients was 84.50 (IQR: 44.29-133.55). 2. Univariate analysis showed significant associations between PA and factors across all SEM levels, including individual-level socio-demographic characteristics, health status, exercise motivation and self-efficacy, interpersonal-level social support, organizational-level community sports atmosphere environment and community sports organization environment, and policy-level national system and community system. 3. Multiple linear regression analysis showed that age (β=-0.196, P=0.011), occupation (β=-0.336, P=0.000), FEV₁ (β=-0.157, P=0.047), frailty (β=-0.171, P=0.040), exercise motivation (β=0.264, P=0.005) and community system (β=-0.253, P=0.021) were the influencing factors of PA level, explained 46.0% of the total variation.

Conclusion: 1. The PA level of COPD patients is at a medium level. 2. While factors at all levels of the SEM showed significant associations with PA in COPD patients during univariate analyses, only some individual and policy-level factors retained independent effects in multivariable modeling. At the individual level, younger age, working status, lower FEV₁, less frailty, and higher exercise motivation were associated with higher PA levels. At the policy level, patients who perceived lower impacts of community institutional policies exhibited higher PA levels. It is suggested that when formulating intervention measures, factors such as the patient's age, occupation, and lung function based on activity level should be taken into account. Meanwhile, we should consider various aspects, such as frailty management, exercise motivation stimulation, and community system optimization, to improve the PA level of COPD patients.