The Study Of Subjective Sleep Quality And Polysomnogram In Community-dwelling Older Adults

ObjectiveThis study focused on exploring the sleep quality in community-dwelling older adults,including the subjective sleep quality and polysomnogram.Using GDS and SAS to analyze the correlation between sleep quality and anxiety and depression among the elderly in the community.The SF-36 health scale is used to analyze the correlation between sleep quality and health status of elderly people in community.It would be providing accurate data support for the sleep problem of the elderly in the community,and providing an evidence basis on improving the sleep quality,so as to improve their physical health and mental health among the community-dwelling older adults,to improve the subjective well-being and life satisfaction of the elderly.Materials and MethodsAdopt convenience sampling method,a total of 33 older adults with subjective poor sleep quality and 29 healthy old adults selected as the research objects from the community in Chengdu.In this research,we used SPMSQ,Pittsburgh Sleep Quality Index(PSQI),Insomnia Severity Index(ISI),Geriatric Depression Scale(GDS),Self-rating Anxiety Scale(SAS),Short Form 36 Health Survey Questionnaire(SF-36)to evaluate the subjective sleep quality and portable PSG to assess the objective sleep quality.The sleep physical signs what we recorded included(1)sleep process and continuous signs:time in bed,total sleep time,sleep efficiency,sleep latency,awaking times,wake after sleep onset;(2)sleep architecture signs:rapid eyes movement time,non-rapid eyes movement time.Statistical methods contained one-way ANOVA,chi-square test,independent samplet test and Pearson correlation.Results1.We compared the base line between sleep problem group and healthy group,finding that the there is no statistical significance in gender(c~2=0.961;P>0.05)and age(t=0.939;P>0.05)between these two groups.And there is no statistical significance in PSQI(t=13.091;P<0.05),ISI(t=13.234;P<0.05)between these two groups.In addition,there is statistical significance in GDS(t=4.186;P<0.05)and no statistical significance in SAS(t=1.130;P>0.05).2.We find that there is statistical significance in subjective sleep quality(t=6.097;P<0.05),sleep latency(t=4.661;P<0.05),falling asleep time(t=8.479;P<0.05),sleep efficiency(t=7.924;P<0.05),sleep disorders(t=2.799;P<0.05),daytime dysfunction(t=4.139;P<0.05)between sleep problem group and healthy group.3.Based on the data we find that difference in PSG sleep efficiency(t=-6.323;P<0.05)was statistically significant,while in stage 1(t=-0.084;P>0.05),stage 2(t=0.092;P>0.05),stage 3(t=-0.655;P>0.05)and REM sleep(t=1.357;P>0.05)are not statistically significant between two groups.4.According to the sleep architecture score,difference in total time is statistical significant(t=-6.780;P<0.05),as well as in time in bed(t=-1.640;P>0.05),sleep latency(t=0.054;P>0.05)and REM sleep latency(t=-1.666;P>0.05)are not statistical significant.5.There is statistical significance in waking time after fall asleep(t=4.912;P<0.05),and no statistical significance in micro awakening time(t=1.727;P>0.05)between two groups.6.In sleep problem group,there are 17(51.5%)older adults underestimate their total sleep time and 1(3%)overstate their total sleep,15(45.5%)older adults can accurately evaluate their own total sleep time as well.Evaluating the sleep efficiency,18(54.5%)underestimate it,6(18.2%)overstate it and 9(27.3%)can accurately rate it.In addition,25(75.8%)could underestimate their sleep latency,3(9.1%)overrate it,and5(15.1%)can assess it with consistence degree.In healthy group,there are 1(3.4%)older adults underestimate their total sleep time and 25(86.2%)overstate their total sleep,3(10.4%)older adults can accurately evaluate their own total sleep time as well.Evaluating the sleep efficiency,1(3.4%)underestimate it,16(55.2%)overstate it and12(41.4%)can accurately rate it.In addition,12(41.4%)could underestimate their sleep latency,11(37.9%)overrate of these,and 6(20.7%)can assess it with consistence degree.In addition,there is statistical significance in total sleep time(c~2=44.30;P<0.05)、sleep efficiency(c~2=20.01;P<0.05)and sleep latency(c~2=10.72;P<0.05)between two groups.7.In sleep problem group,GDS is positively associated with total PSQI(r=0.436,P<0.05),subjective sleep quality(r=0.305,P<0.05),falling asleep time(r=0.327,P<0.05),sleep efficiency(r=0.280,P<0.05)and daytime dysfunction(r=0.602,P<0.05).And SAS is positively associated with daytime dysfunction(r=0.511,P<0.05).8.According to the data in sleep problem group,SF-36 PCS score is negatively correlated with daytime dysfunction(r=-0.354,P<0.05).and MCS is negatively correlated with daytime dysfunction(r=-0.410,P<0.05).Conclusion1.Compared with healthy older adults,the elderly who have sleep problem are in inefficiency,less total sleep time,higher awaking time after fall asleep,but in little sleep architecture.Therefore,we should focus on the sleep quality in elderly,encouraging good sleep behavioral habits(especially the sleep efficiency)to ensure the falling-asleep time and sleep quality.2.The majority of the elderly have a mismatch in subjective and objective sleep evaluation.The older adults in sleep problem tend to underestimate or overstate their sleep efficiency,total sleep time and sleep latency.And healthy older adults apt to estimate or overrate their sleep efficiency and falling-asleep time,as well as little elderly state their sleep situation like what portable PSG recorded.So we should attach importance to the cognitive adjustment and cultivate good sleep behavioral habits to reduce the subjective-objective mismatch.3.The daytime dysfunction is positively correlated with depression and anxiety.Thus,focusing on the mental health to improving sleep quality is of importance.4.According to the data,daytime dysfunction is negatively associated with the PCS and MCS.So we should focus on the physical and mental health to improve the daytime function.