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中国全科医学 ›› 2025, Vol. 28 ›› Issue (12): 1486-1493.DOI: 10.12114/j.issn.1007-9572.2024.0236

所属专题： 心房颤动最新文章合辑

• 论著·心房颤动管理专题研究 • 上一篇    下一篇

心房颤动患者身体活动的潜在剖面分析及影响因素研究

游展鸿1, 孙国珍1,*(), 卢静1, 汤志杰1, 王洁2, 王琴3, 王琳2   

  1. 1．211100　江苏省南京市，南京医科大学护理学院
    2．210029　江苏省南京市，南京医科大学第一附属医院心血管内科
    3．210029　江苏省南京市，南京医科大学第一附属医院护理部
  • 收稿日期:2024-05-15 修回日期:2024-10-11 出版日期:2025-04-20 发布日期:2025-02-06
  • 通讯作者: 孙国珍


  • 作者贡献：

    游展鸿负责设计研究方案、发放调查问卷及数据分析、绘制图表，最终完成论文撰写；孙国珍、王洁提出研究命题及思路；卢静负责数据分析及论文撰写；汤志杰、王琴、王琳负责发放调查问卷并回收；孙国珍负责研究过程中的质量控制监督、稿件校审，对本文负责。

  • 基金资助:
    国家自然科学基金资助项目(72074124); 江苏高校优势学科建设工程项目(JX10631804)

Latent Profile Analysis and Its Influencing Factors of Physical Activity in Patients with Atrial Fibrillation

YOU Zhanhong1, SUN Guozhen1,*(), LU Jing1, TANG Zhijie1, WANG Jie2, WANG Qin3, WANG Lin2   

  1. 1. School of Nursing, Nanjing Medical University, Nanjing 211100, China
    2. Department of Cardiology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China
    3. Department of Nursing, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China
  • Received:2024-05-15 Revised:2024-10-11 Published:2025-04-20 Online:2025-02-06
  • Contact: SUN Guozhen

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摘要： 背景 身体活动是心房颤动（AF）患者自我管理的聚焦点，不同类型及强度身体活动对患者健康状况产生不同影响，然而当前AF患者身体活动类型分布特征并未明晰。 目的 探究AF患者身体活动能量消耗潜在剖面特征及其影响因素。 方法 选取2023年7—12月在南京医科大学第一附属医院心血管内科新入院300例择期行导管消融术的AF患者作为研究对象。收集患者一般资料，采用国际身体活动问卷长版（IPAQ-L）评估患者身体活动水平，采用恐惧疾病进展简化量表（FoP-Q-SF）评估患者恐惧疾病进展水平，采用感知控制量表（CAS-R）评估患者感知控制力，采用家庭关怀度指数（FAI）评估患者家庭关怀度。对AF患者各类型身体活动能量消耗进行潜在剖面分析，从单类别模型开始逐步增加类别数量，确定拟合数据最好的模型为最终模型。采用多因素Logistic回归分析探究各因素对不同潜在剖面的影响。 结果 依据IPAQ-L评分，身体活动低、中、高水平的AF患者分别为80例（26.7%）、63例（21.0%）和157例（52.3%），依据患者身体活动水平潜在剖面分析结果将患者分为低能量消耗-久坐为主型（n=198）和高能量消耗-职业性身体活动为主型（n=102）2个剖面。单因素分析结果示，低能量消耗-久坐为主型与高能量消耗-职业性身体活动为主型患者年龄、文化程度、职业、家庭人均月收入水平及FoP-Q-SF、CAS-R、FAI评分比较，差异有统计学意义（P<0.05）。多因素Logistic回归分析结果示年龄40~59岁（OR=0.280，95%CI=0.087~0.899，P=0.017）、本科/大专及以上（OR=0.331，95%CI=0.124~0.883，P=0.027）、脑力劳动（OR=0.315，95%CI=0.121~0.817，P=0.032）、退休（OR=0.151，95%CI=0.050~0.452，P<0.001）、FoP-Q-SF评分（OR=1.086，95%CI=1.036~1.139，P<0.001）、CAS-R评分（OR=0.899，95%CI=0.820~0.985，P=0.022）、FAI评分（OR=0.828，95%CI=0.707~0.969，P=0.018）是身体活动能量消耗潜在剖面的影响因素（P<0.05）。 结论 AF患者身体活动能量消耗状况存在不同潜在剖面，且各剖面能量消耗分布特征存在异质性，40~59岁、本科/大专及以上、脑力劳动、退休、感知控制力强、家庭关怀度高患者更易归类至低能量消耗-久坐为主型，可针对不同身体活动能量消耗剖面特征并结合影响因素制订干预方案，以促进恰当且科学的身体活动。

关键词: 心房颤动, 身体活动, 恐惧疾病进展, 感知控制, 家庭关怀度, 潜在剖面分析

Abstract:

Background

Physical activity is the focus of disease management in patients with atrial fibrillation (AF), and different types and intensities of physical activity have different impacts on the health status of patients; however, the current distribution of physical activity types in patients with AF is not clearly characterized.

Objective

To explore differences in the distribution of the daily physical activity energy expenditure in patients with AF and the influencing factors.

Methods

A total of 300 AF patients newly admitted to the Department of Cardiology Medicine at the First Affiliated Hospital with Nanjing Medical University for elective catheter ablation from July to December 2023 were enrolled. General patient information was collected. The International Physical Activity Questionnaire-Long Form (IPAQ-L) was used to assess the level of physical activity, the Fear of Progression Questionnaire-Short Form (FoP-Q-SF) to evaluate fear of disease progression, the Cancer Acceptance Scale-Revised (CAS-R) to assess perceived control, and the Family Apathy Index (FAI) to gauge family care. A latent profile analysis was conducted on energy expenditure from various types of physical activity among AF patients. Starting from a one-class model, the number of classes was incrementally increased to determine the best-fitting model. Multivariate Logistic regression analysis was employed to investigate the impact of various factors on different latent profiles.

Results

Based on IPAQ-L scores, 80 patients (26.7%) had low, 63 (21.0%) had moderate, and 157 (52.3%) had high levels of physical activity. The latent profile analysis of patients' physical activity energy expenditure categorized them into two profiles: low energy expenditure-primarily sedentary (n=198) and high energy expenditure-primarily occupational physical activity (n=102). Univariate analysis revealed statistically significant differences in age, education level, occupation, family monthly income per capita, and scores on the FoP-Q-SF, CAS-R, and FAI between the two profiles (P<0.05). Multivariate Logistic regression analysis indicated that age 40-59 years (OR=0.280, 95%CI=0.087-0.899, P=0.017), bachelor's degree or higher (OR=0.331, 95%CI=0.124-0.883, P=0.027), mental labor (OR=0.315, 95%CI=0.121-0.817, P=0.032), retirement (OR=0.151, 95%CI=0.050-0.452, P<0.001), FoP-Q-SF score (OR=1.086, 95%CI=1.036-1.139, P<0.001), CAS-R score (OR=0.899, 95%CI=0.820-0.985, P=0.022), and FAI score (OR=0.828, 95%CI=0.707-0.969, P=0.018) were influencing factors of the latent profiles of physical activity (PA) energy expenditure (P<0.05) .

Conclusion

There are different latent profiles of physical activity energy expenditure among AF patients, with heterogeneous distribution characteristics across profiles. Patients aged 40-59, with bachelor's degree or higher, engaged in mental labor, retired, possessing strong perceived control, and receiving high family care are more likely to be classified as low energy expenditure-primarily sedentary. Interventions can be tailored based on the characteristics of different physical activity energy expenditure profiles and influencing factors to promote appropriate and scientific physical activity.

Key words: Atrial fibrillation, Physical activity, Fear of progression, Control attitude, Family apgar index, Latent profile analysis

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