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老年睡眠障碍患者焦虑状况及影响因素的logistic回归分析 被引量:2

Anxiety status and logistic regression analysis of the influencing factors in elderly patients with insomnia
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摘要 目的调查老年睡眠障碍患者的焦虑状况,并分析其影响因素。方法选取2018年9月至2019年5月到南昌大学第一附属医院心身医学科就诊的老年睡眠障碍患者155例,运用汉密尔顿焦虑量表(HAMA)、艾森克人格问卷神经质分问卷(EPQ-N)、多伦多述情障碍量表(TAS-20)对患者进行调查。结果老年睡眠障碍患者中有82%(127/150)存在不同程度的焦虑症状,患者HAMA得分为(17.06±9.68)分。Logistic回归分析结果表明,男性、受教育程度高、家庭收入高是老年睡眠障碍患者焦虑症状的保护因素(P<0.05);不稳定型神经质人格、述情障碍是出现焦虑症状的危险因素(P<0.05)。结论绝大多数老年睡眠障碍患者存在不同程度焦虑症状,且受性别、受教育程度、家庭收入、神经质人格类型以及述情障碍的影响。 Objective To investigate the anxiety status of elderly patients with sleep disorder and analyze its influencing factors.Methods Totally 155 elderly patients with sleep disorders who were admitted to the Department of Psychosomatic Medicine of the First Affiliated Hospital of Nanchang University from September 2018 to May 2019 were selected,and the patients were investigated with Hamilton anxiety scale(HAMA),Eysenck personality questionnaire(EPQ-N)and Toronto alexithymia scale(TAS-20).Results Eighty-two percent(127/150)of the elderly patients with sleep disorder had anxiety symptoms in varying degrees,and the HAMA score was(17.06±9.68).The results of Logistic regression analysis showed that male,high educational level and high family income were the protective factors of anxiety symptoms in elderly patients with sleep disorder(P<0.05).Unstable neurotic personality and alexithymia were the risk factors of anxiety symptoms(P<0.05).Conclusion Most elderly patients with sleep disorders had different degrees of anxiety symptoms.And it was affected by gender,education,family income,neurotic personality type and alexithymia.
作者 杨肇熙 万爱兰 刘利丹 吴国江 徐梦霞 田洋丽 Yang Zhao-xi;Wan Ailan;Liu Lidan;Wu Guojiang;Xu Mengxia;Tian Yangli(Department of Psychosomatic Medicine, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China;School of Public Administration, Nanchang University, Nanchang 330031, China)
出处 《中国医院统计》 2020年第4期308-310,314,共4页 Chinese Journal of Hospital Statistics
关键词 睡眠障碍 老年人 焦虑 影响因素 insomnia elderly anxiety influencing factor
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