酒精使用障碍人群睡眠、心理健康的 状况及其在发病中的作用——基于山东省流行病学调查的分析

Sleep and Mental Health Status among Individuals with Alcohol Use Disorder and Their Role in Disease Onset—An Analysis Based on an Epidemiological Survey in Shandong Province

摘要: 目的：调查山东省酒精使用障碍(AUD)人群的睡眠质量与心理健康状况，并分析二者在AUD发病中的风险作用。方法：于2015年10月至2016年3月，采用多阶段分层整群随机抽样方法，在山东省49个县(市、区)抽取18岁及以上常住居民进行流行病学调查。采用修订版一般健康问卷(GHQ-12)进行筛查，并由精神科医师依据DSM-IV标准进行疾病诊断。选取其中符合诊断标准的1269例酒精使用障碍(AUD)患者及17,725名普通健康人群作为研究对象。通过PSQI量表评估其睡眠质量；运用t检验进行组间差异比较，并构建二元多因素Logistic回归模型识别AUD群体睡眠、心理健康状况受损的特征及全人群AUD发病的核心风险因子。结果：完成调查27,489人，选取诊断符合酒精使用障碍DSM-IV标准者共1269例，普通健康人群17,725例进行数据分析。睡眠、心理健康状况分析：AUD组GHQ-12及PSQI总分均显著高于对照组(P < 0.001)，提示该人群心理与睡眠状况普遍较差。人群异质性特征：AUD群体内部回归显示，中青年(18~44岁)患者心理健康受损风险最高，老年(≥60岁)风险显著降低(aOR = 0.42)；低教育程度(≤6年)是AUD患者发生睡眠障碍的危险因素。发病核心风险因子：多因素回归显示，“感到有压力”(OR = 23.636)、“因担忧而失眠”(OR = 13.164)是AUD发病最强的心理健康预测因子；主观睡眠质量差、睡眠障碍及日间功能障碍均显著增加发病风险(P < 0.05)结论：AUD人群心理健康与睡眠状况存在显著年龄及教育背景异质性；心理应激与担忧性失眠是诱发AUD发病的核心机制。临床干预应重点关注中青年高压群体及低教育程度者的睡眠管理。

Abstract: Objective: To investigate the sleep quality and mental health status of individuals with alcohol use disorder (AUD) in Shandong Province and analyze the risk roles of both factors in AUD onset. Methods: From October 2015 to March 2016, a multi-stage stratified cluster random sampling method was employed to survey permanent residents aged 18 years and above across 49 counties (cities, districts) in Shandong Province. The 12-item General Health Questionnaire (GHQ-12) was used for screening, followed by diagnostic confirmation by psychiatrists according to DSM-IV criteria. A total of 1269 patients met diagnostic criteria for AUD and 17,725 healthy individuals from the general population were selected as study subjects. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Between-group differences were compared using t-tests, and binary multivariable logistic regression models were constructed to identify characteristics of impaired sleep and mental health status in the AUD population and core risk factors for AUD onset in the general population. Results: A total of 27,489 individuals completed the survey. Among them, 1269 cases met DSM-IV diagnostic criteria for AUD and 17,725 healthy individuals were selected for data analysis. Sleep and mental health status analysis: The AUD group showed significantly higher GHQ-12 and PSQI total scores compared to the control group (P < 0.001), indicating generally poorer mental health and sleep status in this population. Population heterogeneity characteristics: Internal regression analysis within the AUD population revealed that young and middle-aged patients (18~44 years) had the highest risk of mental health impairment, while risk was significantly reduced in the elderly (≥60 years) (aOR = 0.42); low educational attainment (≤6 years) was a risk factor for sleep disturbance among AUD patients. Core risk factors for disease onset: Multivariable regression showed that “feeling under strain” (OR = 23.636) and “losing sleep over worry” (OR = 13.164) were the strongest mental health predictors of AUD onset; poor subjective sleep quality, sleep disturbance, and daytime dysfunction all significantly increased disease risk (P < 0.05). Conclusion: Significant age- and education-related heterogeneity exists in mental health and sleep status among the AUD population. Psychological stress and worry-induced insomnia are core mechanisms triggering AUD onset. Clinical interventions should prioritize sleep management for high-stress young and middle-aged populations and individuals with low educational attainment.