广西医学

目的基于国家健康和营养检查调查（NHANES）数据库探讨多种病毒感染与睡眠障碍之间的关联性。方法选取NHANES数据库2009—2010年的横断面调查数据，根据睡眠障碍发生情况将研究对象分为睡眠障碍组与非睡眠障碍组。采用逆概率处理加权法（IPTW）平衡两组研究对象的基线特征。采用χ 2检验及标准均数差（SMD）评估IPTW分析前后两组基线特征的均衡性；应用非条件Logistic回归（IPTW分析前）和加权Logistic回归（IPTW分析后）分析7种病毒感染与睡眠障碍之间的关联性。针对HAV感染与睡眠障碍之间的关联性进行亚组分析。结果共纳入2 385名研究对象，其中146名纳入睡眠障碍组，2 239名纳入非睡眠障碍组。IPTW分析前，两组的年龄、人群、家庭收入贫困比率（PIR）、吸烟的SMD >0.1，基本特征不均衡；IPTW分析后，两组的基线特征差异无统计学意义（SMD <0.1，P >0.05），基本特征均衡。非条件Logistic回归结果显示，HAV感染、单纯疱疹病毒2型（HSV⁃2）感染与睡眠障碍存在相关性（P<0.05）；加权Logistic回归结果显示，HSV⁃2感染者发生睡眠障碍的风险约为未感染者的1.93倍（P<0.05），而HAV感染与睡眠障碍无相关性（P>0.05）。亚组分析显示，HAV感染与睡眠障碍的关联性受年龄与教育水平等混杂因素显著影响（P交互作用 < 0.05）。结论经IPTW平衡基线特征后，HSV⁃2感染与睡眠障碍存在显著性关联。应对HSV⁃2感染者进行睡眠障碍情况筛查和干预，以提高该人群睡眠质量。

Objective To explore the association between multiple virus infections and sleep disorder based on the National Health and Nutrition Examination Surveys (NHANES) database. Methods The cross⁃sectional investigation data from 2009 to 2010 were selected from the NHANES database, and the research subjects were assigned to sleep disorder group or non⁃sleep disorder group according to the occurrence of sleep disorder. The baseline characteristics of research subjects in both groups were balanced by using the inverse probability of treatment weighting (IPTW). The balance of baseline characteristics of both groups before and after IPTW analysis was evaluated by employing the χ 2 test and standardized mean difference (SMD). The association between 7 virus infections and sleep disorder was analyzed by the application of unconditional Logistic regression (before IPTW analysis) and weighting Logistic regression (after IPTW analysis). A subgroup analysis was performed for the association between HAV infection and sleep disorder. Results A total of 2385 research subjects were enrolled, therein 146 research subjects were enrolled in the sleep disorder group, and 2239 research subjects were enrolled in the non⁃sleep disorder group. Before IPTW analysis, SMD of age, population, household income poverty impact ratio (PIR), and smoking in both groups was larger than 0.1, and the essential characteristics were imbalance. After IPTW analysis, there was no statistically significant difference in baseline characteristics between the two groups (SMD<0.1, P>0.05), and the essential characteristics were balance. The results of unconditional Logistic regression revealed that HAV infection, herpes simplex virus type 2 (HSV⁃2) infection exhibited correlations with sleep disorder (P<0.05). The results of weighting Logistic regression indicated that the occurrence risk of sleep disorder from HSV⁃2 infected person was approximately 1.93 times higher than that of uninfected person (P<0.05), whereas no correlation was found between HAV infection and sleep disorder (P>0.05). The subgroup analysis presented that the association between HAV infection and sleep disorder was significantly affected by age, educational level, and other confounding factors (Pinteraction< 0.05). Conclusion After balancing baseline characteristics by IPTW, there is a significant correlation between HSV⁃2 infection and sleep disorder. It is necessary to screen and intervene sleep disorder of HSV⁃2 infected person to improve its sleep quality.

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