中国成年人吸烟相关睡眠特征的网络分析

IF 4.3
Annals of medicine Pub Date : 2024-12-01 Epub Date: 2024-03-25 DOI:10.1080/07853890.2024.2332424
Yuting Xie, Peiyuan Sun, Huang Huang, Jianjun Wu, Yue Ba, Guoyu Zhou, Fangfang Yu, Daming Zhang, Yaqun Zhang, Ranran Qie, Zhuolun Hu, Kaiyong Zou, Yawei Zhang
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引用次数: 0

摘要

多种睡眠特征与吸烟行为之间的关系并不一致,目前尚不清楚哪些睡眠特征对预防吸烟最为关键。本研究旨在探讨吸烟状态/强度与多种睡眠特征之间的关联,并利用网络分析法确定吸烟相关睡眠的潜在核心领域。数据来源于一项中国成年人癌症相关风险因素调查。采用逻辑回归模型量化睡眠特征与吸烟状况/强度之间的关联。网络分析用于确定核心睡眠特征。研究共纳入了 5228 名参与者,中位年龄为 44 岁。目前吸烟与午睡时间长、入睡困难、晚睡、早上 7 点后起床和比预期早醒呈显著正相关。在 45 岁以下的年轻人中,目前吸烟与睡眠时间短呈明显正相关。晚睡和早上 7 点后起床只与当前大量吸烟有关,而与当前少量吸烟无关。网络分析显示,多种与吸烟有关的睡眠特征相互关联,入睡困难和晚睡是网络中的核心特征。研究发现,睡眠特征与吸烟之间的关系因年龄和吸烟强度而异,并强调了促进睡眠健康对戒烟的潜在益处,尤其关注入睡困难和晚睡问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Network analysis of smoking-related sleep characteristics in Chinese adults.

Network analysis of smoking-related sleep characteristics in Chinese adults.

The associations between multiple sleep characteristics and smoking behavior are inconsistent, and it is unclear which sleep characteristics are most crucial for tobacco prevention. This study aimed to explore the associations between smoking status/intensity and multiple sleep characteristics and to identify the potential core domain of smoking-related sleep using network analysis. Data were obtained from a survey of cancer-related risk factors among Chinese adults. Logistic regression models were used to quantify the associations between sleep characteristics and smoking status/intensity. Network analyses were employed to identify the core sleep characteristics. A total of 5,228 participants with a median age of 44 years old were included in the study. Current smoking was significantly positively associated with long nap time, difficulty falling asleep, late bedtime, getting up after 7 am, and waking up earlier than expected. There was significant positive association between current smoking and short sleep duration in young adults under 45 years old. Late bedtime and getting up after 7 am were only associated with current heavy smoking, but not current light smoking. Network analyses showed that multiple smoking-related sleep characteristics were interconnected, with difficulty falling asleep and late bedtime as central characteristics in the network. The study found that the associations between sleep characteristics and smoking varied by age and smoking intensity and highlights the potential benefits of sleep health promotion in smoking cessation, with a particular focus on difficulty falling asleep and late bedtime.

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