摘要
目的:基于倾向性评分(PSM)探讨我国老年哮喘病人抑郁症状的影响因素。方法:基于中国健康与养老追踪调查(CHARLS)数据,通过倾向性评分匹配法对哮喘病人一般资料进行匹配后,采用Logistic回归分析探讨我国老年哮喘病人抑郁症状的影响因素。结果:匹配前,无哮喘病人抑郁症状发生率为32.4%(1780/5500),哮喘病人抑郁症状发生率为42.3%(116/274),两组比较差异有统计学意义(P<0.001);共272对完成匹配,匹配后,无哮喘病人与哮喘病人抑郁症状发生率比较差异无统计学意义(P>0.05);Logistic回归分析结果显示,生活自理能力、夜间睡眠时长、共病情况是老年哮喘病人抑郁症状的影响因素(P<0.05)。结论:生活自理能力、夜间睡眠时长和共病情况对老年哮喘病人抑郁症状有影响,可采取针对性措施对老年哮喘病人进行干预,以缓解老年哮喘病人的抑郁症状。
Objective:To explore the influencing factors of depressive symptoms in older asthma patients in China based on propensity score matching(PSM).Methods:Using data from the China Health and Retirement Longitudinal Study(CHARLS),propensity score matching was applied to match general information,and Logistic regression analysis was conducted to identify factors associated with depressive symptoms in older asthma patients.Results:The occurance rate of depressive symptoms was 32.4%(1780/5500)in the non-asthma group and 42.3%(116/274)in the asthma group,with statistically significant difference between the two groups(P<0.001).A total of 272 matched pairs were successfully established.Post-matching analysis showed no statistically significant difference in the occurance rate of depressive symptoms between non-asthma patients and asthma patients(P>0.05).Logistic regression analysis revealed that self-care ability,nighttime sleep duration,and comorbidities were influencing factors for depressive symptoms in older asthm a patients.Conclusions:Asthma could increase occurrence risk of depression in older adults.Furthermore,self-care ability,nighttime sleep duration,and comorbidities significantly influence depressive symptoms in older asthma patients.Targeted interventions should be implemented to alleviate depressive symptoms in this population.
作者
韩文娟
张素琴
HAN Wenjuan;ZHANG Suqin(The First People′s Hospital of Changzhou,Jiangsu 213000 China)
出处
《护理研究》
北大核心
2025年第17期2889-2893,共5页
Chinese Nursing Research
关键词
老年人
哮喘
抑郁
自理能力
睡眠障碍
慢性病
倾向性评分
older patients
asthma
depression
self-care ability
sleep disorders
chronic diseases
propensity score matching
