Characteristics and Associated Factors of Insomnia Among the General Population in the Post-Pandemic Era of COVID-19 in Zhejiang, China: A Cross-Sectional Study.

IF 2.1 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL International Journal of General Medicine Pub Date : 2025-01-15 eCollection Date: 2025-01-01 DOI:10.2147/IJGM.S473269
Miao Da, Shaoqi Mou, Guangwei Hou, Zhongxia Shen
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Abstract

Objective: This study aimed to analyze the changes in insomnia characteristics among the general population and explore associated factors during the COVID-19 pandemic and post-pandemic periods.

Methods: A cross-sectional study was conducted using an anonymous online survey. Questionnaires were administered at two-time points (T1: March 1-31, 2022; T2: March 1-31, 2023), which included an Insomnia Severity Index (ISI) and questions related to sleep risk factors, including the COVID-19 pandemic, familial influences, work and study conditions, social activities, physical health, use of electronic devices before sleep, sleep environment, food intake and exercise before sleep, etc. Insomnia characteristics were compared at two points, with logistic regression testing associations with sociodemographic covariates and risk factors. Six machine learning models were employed to develop a predictive model for insomnia, namely logistic regression, random forest, neural network, support vector machine, CatBoost, and gradient boosting decision tree.

Results: The study obtained 2769 and 1161 valid responses in T1 and T2, respectively. The prevalence of insomnia increased from 23.4% in T1 to 34.83% in T2. Univariate analyses indicated the factors of the COVID-19 pandemic, familial influences, social activity, physical health, food intake, and exercise before sleep significantly differed in T1 (p<0.05) between insomnia and non-insomnia groups. In T2, significant differences (p<0.05) were observed between the two groups, including the factors of the COVID-19 pandemic, family structure, work and study conditions, social activity, and physical health status. The random forest model had the highest prediction accuracy (90.92% correct and 86.59% correct in T1 and T2, respectively), while the pandemic was the most critical variable at both time points.

Conclusion: The prevalence and severity of insomnia have worsened in the post-pandemic period, highlighting an urgent need for effective interventions. Notably, the COVID-19 pandemic and physical health status were identified as significant risk factors for insomnia.

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新冠肺炎大流行后浙江省普通人群失眠特征及相关因素的横断面研究
目的:分析新冠肺炎流行期间及流行后普通人群失眠特征的变化并探讨相关因素。方法:采用匿名在线调查进行横断面研究。在两个时间点进行问卷调查(T1: 2022年3月1日至31日;T2: 2023年3月1日至31日),包括失眠严重程度指数(ISI)和与睡眠危险因素相关的问题,包括COVID-19大流行、家庭影响、工作和学习条件、社交活动、身体健康、睡前电子设备的使用、睡眠环境、食物摄入和睡前运动等。在两点上比较失眠特征,用逻辑回归检验与社会人口学协变量和危险因素的关联。采用logistic回归、随机森林、神经网络、支持向量机、CatBoost、梯度增强决策树等6种机器学习模型构建失眠预测模型。结果:研究在T1和T2分别获得2769和1161个有效应答。失眠患病率由T1期的23.4%上升至T2期的34.83%。单因素分析显示,T1与T1之间存在显著差异的因素有新冠肺炎大流行、家庭影响、社会活动、身体健康、食物摄入和睡前运动(p)。结论:大流行后失眠的患病率和严重程度有所恶化,迫切需要采取有效的干预措施。值得注意的是,COVID-19大流行和身体健康状况被确定为失眠的重要危险因素。
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来源期刊
International Journal of General Medicine
International Journal of General Medicine Medicine-General Medicine
自引率
0.00%
发文量
1113
审稿时长
16 weeks
期刊介绍: The International Journal of General Medicine is an international, peer-reviewed, open access journal that focuses on general and internal medicine, pathogenesis, epidemiology, diagnosis, monitoring and treatment protocols. The journal is characterized by the rapid reporting of reviews, original research and clinical studies across all disease areas. A key focus of the journal is the elucidation of disease processes and management protocols resulting in improved outcomes for the patient. Patient perspectives such as satisfaction, quality of life, health literacy and communication and their role in developing new healthcare programs and optimizing clinical outcomes are major areas of interest for the journal. As of 1st April 2019, the International Journal of General Medicine will no longer consider meta-analyses for publication.
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