predictors of sleep quality in community-dwelling older ... · predictors of sleep quality in...

Predictors of Sleep Quality inCommunity-Dwelling Older Adults

in Northern Taiwan

Chiu-Yueh Yang1 & Ai-Fu Chiou2*

1PhD, RN, Assistant Professor, School of Nursing, National Yang-Ming University &2PhD, RN, Professor, School of Nursing, National Yang-Ming University.

IntroductionAn aging population increases economic and social demands.Aging societies are a great challenge for most countries, in-

cluding Taiwan. Thus, helping older adults remain healthyand sustain an active lifestyle is important. To achieve thisgoal, good sleep quality is necessary for older adults to re-store both physical and mental health and maintain optimalquality of life (Hoffman, 2003). Sleep disturbance is a majorproblem for older people. The prevalence of self-reported dis-turbed sleep increases with age, ranging from 39.4% to 75%in older persons (Blay, Andreoli, & Gastal, 2008; Wong &Fielding, 2011). Variations in the results obtained by previousstudies were due to the different criteria used to define insom-nia. We defined sleep disturbance in this study as a PittsburghSleep Quality Index (PSQI) score of more than 5. The PSQI isa subjective measure of sleep quality that addresses patternsinvolved in subjective sleep quality, sleep latency, sleep dura-tion, sleep efficiency, frequency of sleep disturbance, use ofsleepmedications, and daytime dysfunction (Buysse, Reynolds,Monk, Berman, & Kupfer, 1989).

Some age-related changes in older adult sleep habits areattributable to normal aging. Older adults may experience anincrease in Stage 1 (the transitional period of drifting to sleep)and a decrease in Stages 3 and 4 (deeper and more restorativeperiods of sleep) in the sleep cycle (Hoffman, 2003). Lighter,more interrupted sleep leads to easier awaking. In addition,older adults may have a phase-advanced sleep cycle due to di-minished body temperature and melatonin production, whichmay lead to earlier bedtimes at night and early awakenings inthe morning (Hoffman, 2003). Age-related sleep changes maylead to poor sleep quality in older adults in the context of phys-ical and psychiatric disorders (Hoffman, 2003).

Common sleep complaints reported by older people in-cluded poor sleep quality, difficulty in falling asleep (failureto fall asleep within 30 minutes), difficulty in maintainingsleep (interruption of sleep at least three times during the

ABSTRACTBackground: Poor sleep quality may have a significant andnegative impact on physical and mental health. Poor sleepquality also increases the risk of all-cause mortality. Fewstudies have explored the sleep quality of community-dwelling older adults in Taiwan.

Purpose: This study examined the prevalence of sleepdisturbance and potential factors of influence in community-dwelling older people in Taiwan.

Methods: We used a cross-sectional design to recruit a totalof 160 individuals 60 years of age or older from an urban areain northern Taiwan. All subjects completed a structuredquestionnaire that included demographic data, physicalhealth status, a social activity/habit survey, as well as theChinese versions of Barthel’s index, Pittsburgh Sleep QualityIndex, short form of the Geriatric Depression Scale, the SF-36Health-Related Quality of Life Survey, and the PhysicalActivity Scale for the Elderly.

Results: Participants reported a rate of sleep disturbance of41.9%. Sleep disturbance was associated with nocturia anddizziness, hypertension, increased use of medications such asantihypertensives and gastric medicines, poor self-reportedfunctional status, depression, and sedentary lifestyle. Logisticregression showed nocturia, sedentary lifestyle, and mentalcomponent summary score as significant predictors of sleepdisturbance.

Conclusions/Implications for Practice: Sleep disturbanceshould be examined within the context of an individual’sphysical, mental, and social status. Symptom managementeducation and an active lifestyle are necessary to promotesleep quality in older people.

KEY WORDS:functional status, older people, sedentary lifestyle, sleep quality.

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Accepted for publication: August 3, 2012*Address correspondence to: Ai-Fu Chiou, No. 155, Li-Nong St. Sec. 2,Taipei City 11221, Taiwan, ROC.Tel: +886 (2) 2826-7000 ext. 7354; Fax: +886 (2) 2820-2487;E-mail: [email protected]

doi:10.1097/jnr.0b013e3182736461

night), and early morning awakening (wake up 2 hours ear-lier than usual; Su, Huang, & Chou, 2004). These sleep prob-lems are often underestimated as older adults, and healthcareproviders may consider them a normal manifestation of theaging process. However, poor sleep quality may have a sig-nificant negative impact on physical and mental health andincrease risk of all-cause mortality (Hoffman, 2003). Olderadults may experience sleep disorders such as sleep-disorderedbreathing. Obstructive sleep apnea is the most common sleep-disordered breathing, which may contribute to an increasedrisk of cardiovascular complications including arrhythmia,myocardial infarction, and stroke (Hoffman, 2003). A pro-spective, observational cohort study also associated poor sleepwith declining functional status, quality of life, and greater in-cidence of depression (Martin, Fiorentino, Jouldjian, Josephson,& Alessi, 2010). Disturbed sleep may also contribute to cogni-tive difficulties including daytime impairments in attentionand memory, which may increase accidental falls risk (Mesas,Lopez-Garcıa,&Rodrıguez-Artalejo, 2011). Many factors maycontribute to disturbed sleep in older adults (Su et al., 2004).Thus, understanding the related factors of sleep quality canhelp develop effective sleep interventions and improve olderadult sleep quality.

Factors associated with disturbed sleep may include de-mographic characteristics, physical health status, and psy-chosocial factors (Ancoli-Israel & Cooke, 2005; Wong &Fielding, 2011). People who were older, female, not married,and lacked education were found to face significantly higherdisturbed sleep risk (Su et al., 2004). Poor sleep quality mayalso be related to poor physical health, including physicalsymptoms such as nocturia or bodily pain; chronic diseasessuch as pulmonary and heart disease; medication use such ashypnotics, antihypertensives, and antihistamines; and other sub-stance use such as caffeine, alcohol, and nicotine (Ancoli-Israel& Cooke, 2005). Psychosocial factors such as depression, so-cial activities, and physical activity have also been associatedwith disturbed sleep in older persons (Morgan, 2003; Wong& Fielding, 2011).

The high prevalence of disturbed sleep and its predic-tors in older adults have been well documented in Westerncountries. Among the few studies that have explored thesleep quality of community-dwelling older adults in Taiwan(Wu, Su, Fang, & Chang Yeh, 2012; Yao, Yu, Cheng, &Chen, 2008), most focused on demographic factors and didnot examine the influences of physical health status and psy-chosocial factors on sleep quality. Previous studies have founda prevalence of disturbed sleep in 25.7%Y49% of Taiwaneseolder adults. However, there were inconsistent findings re-garding the factors associated with disturbed sleep. For exam-ple, although studies have related demographic data such asgender, education, and lifestyle to disturbed sleep (Wu et al.,2012; Yao et al., 2008), another study reported inconclusiveresults (Lin, Pan, & Chang Yeh, 2006). Another study foundthat Taiwanese older adults have relatively lower insomniaprevalence and fewer symptoms such as difficulty in fallingasleep and difficulty in maintaining sleep/early morning wak-

ening than their Western counterparts (Su et al., 2004). Cul-tural differences between Western and Asian countries canaffect the attitude and management of disturbed sleep byolder adults and healthcare providers. Therefore, more stud-ies are needed to explore the related factors of disturbedsleep in Taiwanese older adults. Few sleep studies have exam-ined the influence of physical activity and self-reported func-tional status on sleep quality. Physical activity is especiallybeneficial for healthy aging in terms of physical function andcognitive health, as well as sleep quality (Morgan, 2003). Inaddition, self-reported functional status reflects the impact ofhealth problems on the physical, mental, and social aspectsof an individual’s life (Otero-Rodrıguez et al., 2010).

With an understanding of the potential risk factors asso-ciated with disturbed sleep, healthcare providers can developadequate interventions to improve the sleep quality of olderadults of different ethnicities. The purpose of this study wasto understand the prevalence of disturbed sleep in Taiwaneseolder adults and explore the predictors of sleep quality andtheir association with physical activity, self-reported func-tional status, and other factors. This study was designed todetermine (a) the prevalence rate of disturbed sleep and (b)predictors of disturbed sleep in Taiwanese older people.

Methods

Design and SampleA cross-sectional design and convenience sampling was usedto recruit 185 community-dwelling older people from an ur-ban area of northern Taiwan. The study was conducted insenior activity centers in Linkou District in northern TaiwanbetweenNovember and December 2008.Most of the elderlypopulation in this area was of middle socioeconomic class;most lived in a three-generation family setting.During the study,all older adults at senior activity centers who met the inclusioncriteria were invited to participate. Inclusion criteria were asfollows: (a) age of 60 years or more; (b) ability to speak andread Mandarin; and (c) absence of delirium and disorientationwith regard to time, place, and persons. We selected peopleaged 60 years or older to include more participants in thisstudy. Of the 225 eligible older people invited, 23 refused toparticipate, leaving 202 willing participants. Among thoseparticipants, 17were unable to finish the questionnaire, leaving185 completed questionnaires. To eliminate the effect of hyp-notics on disturbed sleep, the 25 participants currently usinghypnotics were excluded, leaving 160 community-dwellingolder people as valid participants for data analysis. A post hocstatistical power calculator indicated that a sample of 160would have 97% power to detect a medium effect size of 0.15using the multiple regression test with an alpha of .05 for ninepredictive variables.

After receiving institutional reviewboard approval,we askedall subjects who met the inclusion criteria to participate in thestudy. Participantswere interviewed by one of the three researchassistants who were trained by the investigator to standardize

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the data collection process. Written informed consent was ob-tained from participants. Subjects were then interviewed toprovide demographic data and complete the questionnaires.Research assistants read all questions to participants and filledout the answers on the participant’s behalf. Interviews took20Y30 minutes. All information was kept confidential, andanonymity was preserved.

MeasuresAll participants completed a structured questionnaire thatincluded a section on demographic information, physicalhealth status, social activity and habits, and Chinese versionsof Barthel’s index (Dai & Lou, 1996), PSQI (Buysse et al.,1989), short form of the Geriatric Depression Scale (GDS-SF;Sheikh & Yesavage, 1986), SF-36 Health Related Qualityof Life Survey (SF-36; Ware et al., 1998), and Physical Ac-tivity Scale for the Elderly (PASE; Wu et al., 2012). Theseinstruments were chosen based on their wide use and showedvalidity and reliability.

Demographic data included participant age, gender, mari-tal status, education, religion, employment status, and livingarrangement. Physical health status included physical symp-toms (headache, dizziness, back pain, and nocturia), chronicdiseases, and use of medications. Social activity/habits includedattending social activities, nap time, smoking, intake of tea,caffeine, and alcohol. All categorical demographic variableswere recorded as dichotomous in order to perform logisticregression analysis.

The Barthel’s index

The 10-item Barthel’s index was used to measure participantability to independently perform basic activities of daily liv-ing. This study used the Chinese version of Barthel’s indexpreviously translated by Dai and Lou (1996); it includes 10items, namely eating, mobility, hygiene, toileting, bathing,walking, going up and down stairs, dressing, and boweland bladder control. The range of possible scores was be-tween 0 (complete dependence) and 100 (complete indepen-dence). In this study, the Cronbach’s alpha of Barthel’sindex was .91.

The PSQI

We used the Chinese version of PSQI to measure sleep qual-ity (Tsai et al., 2005). The PSQI is a self-administered scalethat contains 19 questions related to subjective sleep quality(Buysse et al., 1989). Subjects were asked to report the timethey went to bed, length of time it took to fall asleep, thetime they arose in the morning, the duration of actual sleep,frequency of disturbed sleep, and subjective sleep quality.The PSQI includes seven domains: subjective sleep quality,sleep latency, sleep duration, sleep efficiency, frequency ofdisturbed sleep, use of sleep medications, and daytime dys-function. Each domain score ranges from 0 (no difficulty)to 3 (severe difficulty). Domain scores are summed to producea global score (range of 0Y21). Because the 25 potential par-

ticipants who used hypnotics were excluded, the score forthe ‘‘use of sleep medications’’ domain was 0. We definedsubjects with a PSQI global score of 95 as having significantdisturbed sleep. The Cronbach’s alpha and testYretest reli-ability for the global PSQI score were .83 and .85, re-spectively. A post hoc cutoff score of 5 on the PSQI hadpreviously produced a sensitivity of 89.6% and a specificityof 86.5% for patients versus control subjects (Buysse et al.,1989). In this study, validity and reliability of the Chineseversion of the PSQI were supported by an index of contentvalidity of .94 and Cronbach’s alpha of .70.

The GDS-SF

Wemeasured depressive symptoms using a 15-item self-ratingGDS-SF with yes/no responses (Sheikh & Yesavage, 1986).Subjects answered questions based on their mood and feel-ings. A score of 0Y5 was defined as no depression, whereasa score of 6Y15 indicated depression. The Chinese versionof the GDS-SF was adopted in the Chinese population, andgood internal consistency (! = .89) was found in Chineseolder people (Mui, 1996). In this study, the Cronbach’s alphaof the Chinese GDS-SF was .84.

The SF-36

We used a Taiwanese version of the SF-36 to assess self-reported functional status. The SF-36 assesses eight domains,including physical functioning, social functioning, role limi-tations due to physical problems, bodily pain, mental health,role limitations due to emotional problems, vitality, and gen-eral health perceptions. Each domain ranges from 0 to 100(Ware et al., 1998). The Taiwanese version of the SF-36 wasshown to have good psychometric properties (Lu, Tseng, &Tsai, 2003) as internal reliability reached an acceptable levelfor all scales (Cronbach’s ! 9 .70), except for social function-ing. In addition, all scales, except for mental health, passedthe tests for item discriminant validity. In this study, theCronbach’s alpha of the Taiwanese version of the SF-36 was.94. To better interpret the SF-36 score, the eight domainswere combined into two separate summary scores, namelyphysical component summary (PCS) and mental componentsummary (MCS) scores (Ware et al., 1998). The PCS consistsof the four domains of physical functioning, role-physical,bodily pain, and general health. The MCS includes the re-maining domains of vitality, social functioning, role-emotional,and mental health (Cleary & Howell, 2006). The PCS andMCS summarize the respondent’s health status from broadphysical and mental health perspectives. The PCS and MCSare usually calculated in three steps. First, standardized scalescores were computed using means and standard deviationsof corresponding scales. Second, Z scores were multipliedby their respective factor score coefficients and then summed.Finally, these aggregated scores were transformed to norm-based scores. The PCS and MCS scores are easier to inter-pret, simpler to analyze statistically in studies, and helpful indetermining whether functional limitations exist in the two

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health components. In addition, we used the general popula-tion as a norm-based reference group, with 50 representing themean score. Lower scores on PCS and MCS scales reflectedmuch worse physical and mental functions (Hagger-Johnson,Whiteman, Wawrzyniak, & Holroyd, 2010). The SF-36 sum-mary scales were found to be valid, reliable, and equivalent ina Chinese population (Lam, Tse, Gandek, & Fong, 2005).

The PASE

The PASE is an age-specific physical activity scale originallydesigned for community-dwelling older adults (Washburn,Smith, Jette, & Janney, 1993). TestYretest reliability was .75(95% CI = 0.69Y0.80) over a 3- to 7-week interval. Con-struct validity was established by correlating PASE scoreswith grip strength, static balance, leg strength, resting heartrate, and perceived health status (Washburn et al., 1993).This study used a 10-item Chinese version of the PASE mod-ified by Wu et al. (2012), which takes cultural diversity intoconsideration. Subjects were asked to report their activitylevels in three categories and 13 activities including (a) lei-sure time activities (sitting activities, walking, light sports,moderate sports, strenuous sports, muscle strength), (b) house-hold activities (light and heavy housework, home repair, yardwork, gardening, caring for others), and (c) work-related ac-tivities (work/volunteer) over the past 7-day period. We com-puted the total PASE score by multiplying the amount of timespent on the 12 activities (except for sitting activities) by theirrespective weights and then summing the 12 results. The PASEhas a total possible score range of 0Y360, with a higher PASEscore indicating greater physical activity. As the PASE scoredid not include sitting activities, such as watching televisionand reading the newspaper, a score of 0 was defined as asedentary lifestyle. A score greater than 0 was defined as anactive lifestyle for purposes of this study. TestYretest reliabilitywas .89 over a 3-week interval. Concurrent validity was sup-ported by correlating PASE scores with a 6-minute walk test(r = .379, p G .01; Wu et al., 2012).

Statistical AnalysisThe SPSS statistical package (version19.0; SPSS, IBM,Armonk,NY, USA) was used to analyze study data. Descriptive statisticsincluding mean, standard deviation, frequency, and percentagedescribed demographic and health status, as well as levels ofsleep quality, physical activity, and quality of life. Chi-squareand t tests examined relationships between sleep quality anddemographics, physical health status, social factors, depression,physical activity, and self-reported functional status.

Multivariate logistic regression identified significant pre-dictors of disturbed sleep, with the selection of independentvariables entered into the model determined based on sig-nificant bivariate association with disturbed sleep. The ninerelated factors entered as independent variables includeddizziness, nocturia, use of antihypertensives, use of gastric med-ications, number ofmedications, sedentary lifestyle, PCS,MCS,and depression. We used multiple linear regression to examine

multicollinearity among variables by calculating variance in-flation factors. Results showed all variable variance inflationfactors as good (G3), indicating multicollinearity was not anissue of concern. We assessed goodness of fit using the signif-icance of chi-square resulting from the Hosmer and Lemeshowtest (p = .409). A level of p G .05 was considered statisticallysignificant.

Results

Subject CharacteristicsA total of 160 older people participated in this study; 67were defined as sleep disturbed (PSQI 9 5), and 93 were iden-tified as not sleep disturbed. Table 1 shows participant demo-graphic characteristics.Mean participant age was 72.56 years(SD = 7.42 years). Most participants were male, married, un-employed, educated at the elementary or lower level, pro-fessed some religious affiliation, and lived with their spouse/children or others.

Table 2 shows participant physical health status and socialfactors. The most common chronic diseases among partici-pants were hypertension and diabetes, and prevalent medicaltreatment regimens included antihypertensives and hypogly-cemics. The mean number of medications used was 1.14 (SD =1.03). Commonly reported physical symptoms included backpain, nocturia, and dizziness. Fewer than half of the partici-pants reported attending social activities, fewer than20%drankalcohol or coffee, and only 13.8%were current smokers. Mostwere completely independent (Barthel’s index score = 100); nineparticipantswere identified as having a sedentary lifestyle (PASEscore = 0).

Prevalence of Disturbed SleepTable 3 shows that 41.9% of participants reported signifi-cant disturbed sleep (PSQI 9 5). The mean PSQI score was5.54 (SD = 3.32). The most common disturbed sleep wassleep latency (i.e., difficulty falling asleep), followed by sub-jective sleep quality, sleep duration, disturbed sleep, sleepefficiency, and daytime dysfunction. Approximately 20% ofparticipants perceived poor or very poor subjective sleep qual-ity. Mean sleep duration and sleep efficiency were 6.33 hours(SD = 1.62 hours) and 84.47%, respectively. About 41% haddaytime dysfunction. Most had trouble sleeping for reasonsincluding ‘‘had to get up to use the bathroom’’ (69.4%),‘‘cannot get to sleep within 30 minutes’’ (50.0%), and ‘‘wokeup in the middle of night or early morning’’ (44.4%).

Levels of Depression, Physical Activity,

and Self-Reported Functional StatusTable 4 describes levels of depression, physical activity, andself-reported functional status. The mean GDS-SF score was3.19 (SD = 3.33). Twenty participants (12.5%) were identifiedas depressive (GDS-SF 9 5). Mean overall PASE score was70.43 (SD = 50.57). The most common leisure activities were


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sedentary activities such as watching television, followed bywalking, and moderate sports such as tai chi. Light houseworksuch as washing dishes was themost common household activ-ity. These findings indicated that most participants performedprimarily sedentary activities. The highest mean score amongthe eight domains of SF-36 was bodily pain (85.47 T 17.37),followed by social functioning, mental health, vitality, role lim-itations due to emotional problems, physical functioning, rolelimitations due to physical problems, and general health. Thisfinding indicates that the participants had a relatively poorself-reported functional status in terms of general health androle limitations due to physical problems. Mean PCS andMCS scores were 50.02 (SD = 5.24) and 50.45 (SD = 6.14).

Comparison Between Sleep Disturbed and

Non-Sleep Disturbed GroupsChi-square and t tests examined the relationship between sleepquality and demographic, physical health status, social factors,depression, physical activity, and self-reported functional statusvariables. Differences in demographic characteristics betweenthe sleep disturbed and non-sleep disturbed groups are pres-ented inTable 1. There were no significant differences betweensleep disturbed and non-sleep disturbed groups in any demo-graphic characteristic.

In terms of physical health status, participantswith disturbedsleep were more likely to have nocturia (#2 = 11.147, p G .001)and dizziness (#2 = 4.033, p G .05), hypertension (#2= 5.087,p G .05), and use more medications including antihypertensives(#2 = 5.358, p G .05) and gastric medications (p G .05). Statis-tical analysis also indicated the sleep disturbed group morelikely to have a sedentary lifestyle (p G .05) than the non-sleepdisturbed group (see Table 2). In other words, disturbed sleepwas found in those who had physical symptoms includingdizziness or nocturia, hypertension, and those taking anti-hypertensives or gastric medications. Those with a sedentarylifestyle were also more likely to have disturbed sleep.

Table 4 shows the significant differences between the twogroups in terms of geriatric depression score (t = -3.32, p G .01),yard work (t = 2.11, p G .05), physical component (t = 2.18, pG .05), and mental component scores (t = 3.83, p G .001).Theseresults indicated that disturbed sleep was more prevalent in par-ticipantswhohadmoredepression, less yardwork, and poor self-reported functional status. However, disturbed sleep was notsignificantly associated with overall physical activity score.

Predictors of Disturbed SleepA multivariate logistic regression model was used to iden-tify significant predictors of disturbed sleep. Table 5 shows

TABLE 1.

Demographic Characteristics of Participants by Group (N = 160)

Variable

All (N = 160)Non-Sleep

Disturbed (n = 93)Sleep Disturbed

(n = 67)

#2 pn % n % n %

Gender 0.375 .540Male 91 56.9 51 54.8 40 59.7Female 69 43.1 42 45.2 27 40.3

Marital status 0.085 .771Single/widowed/divorced 57 35.6 34 36.6 23 34.3Married 103 64.4 59 63.4 44 65.7

Education 1.332 .248Elementary or lower 109 68.1 60 64.5 49 73.1Junior high school or higher 51 31.9 33 35.5 18 26.9

Religion 0.003 .956None 45 28.1 26 28.0 19 28.4Buddhist/Christian/other 115 71.9 67 72.0 48 71.6

Work status .362a

Not employed 148 92.5 84 90.3 64 95.5Employed 12 7.5 9 9.7 3 4.5

Living arrangement .362a

Alone 12 7.5 9 9.7 3 4.5Living with spouse/children/other 148 92.5 84 90.3 64 95.5

M SD M SD M SD t p

Age 72.56 7.42 71.65 7.19 73.84 7.60 j1.86 .065

Note. aFisher’s exact test.


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multivariate logistic regression model results. Nocturia, sed-entary lifestyle, and MCS score were significant predictors ofdisturbed sleep risk. This indicated that those with nocturiafaced a 2.24-fold increase in risk of disturbed sleep (OR =3.24, p G .01) and those with a sedentary lifestyle faced a6.7-fold increase in risk of disturbed sleep (OR = 7.73, p G.05). Participants with relatively poor mental health faced an8% increase in risk of disturbed sleep (OR = 0.92, p G .05).

DiscussionIn this study, 41.9% of participants reported significant dis-turbed sleep (PSQI 9 5). Although the prevalence of disturbedsleep varied among previous studies due to different defini-tions andmeasurements, our results were consistentwith thoseof previous studies of olderChinese persons (Wong & Fielding,2011). The most common sleep complaints for participants

in this study included difficulty in falling asleep, poor sleepquality, and shorter sleep duration. About 50% had prob-lems in falling asleep within 30 minutes. Su et al. (2004) alsoreported 47% of their subjects had difficulty in falling asleepand 25% had difficulty in maintaining sleep or experiencedearly morning awakening. This change in the sleep patternsof older people may be attributed to decreased melatonin pro-duction, which may deteriorate or weaken circadian rhythmsand sleepingYwaking patterns (Manabe et al., 2000).

In terms of physical factors, physical symptoms includingdizziness and nocturia, hypertension, and antihypertensiveand gastric medication use were all significantly associatedwith disturbed sleep. On the other hand, disturbed sleep wasassociated with psychosocial factors including sedentary life-style, less yard work, depression, and poor self-reported func-tional status in both the PCS and MCS. In addition, logisticregression results showed nocturia, sedentary lifestyle, and

TABLE 2.

Physical Health Status and Social Factors of Participants by Group (N = 160)

Variable



(n = 67)

#2 pn % n % n %

Physical symptomsHeadache 22 13.8 9 9.7 13 19.4 3.106 .078Dizziness 27 16.9 11 11.8 16 23.9 4.033 .045Back pain 66 41.3 36 38.7 30 44.8 0.591 .442Nocturia 53 33.1 21 22.6 32 47.8 11.147 .001

Chronic diseasesHypertension 67 41.9 32 34.4 35 52.2 5.087 .024Diabetic mellitus 32 20.0 17 18.3 15 22.4 0.411 .522Heart disease 24 15.0 12 12.9 12 17.9 0.766 .382Gastric disease 20 12.5 11 11.8 9 13.4 0.092 .762Arthritis 19 11.9 9 9.7 10 14.9 1.025 .311Respiratory disease 5 3.1 2 2.2 3 4.5 .650a

Use of medicationsAntihypertensives 62 38.8 29 31.2 33 49.3 5.358 .021Hypoglycemics 29 18.1 16 17.2 13 19.4 0.127 .722Heart medication 25 15.6 15 16.1 10 14.9 0.043 .836Gastric medications 10 6.3 2 2.2 8 11.9 .018a

Social activity/habitsSocial activity 71 44.4 47 50.5 24 35.8 3.417 .065Smoking 22 13.8 11 11.8 11 16.4 0.692 .406Drinking alcohol 18 11.3 11 11.8 7 10.4 0.074 .785Coffee 31 19.4 20 21.5 11 16.4 0.645 .422Tea 65 40.6 37 39.8 28 41.8 0.065 .799Sedentary lifestyle 9 2.2 2 2.2 7 11.4 .035a

M SD M SD M SD t p

Napping time (min) 42.63 48.79 39.57 45.75 46.87 52.78 j0.93 .352Activities of daily living 98.59 7.75 99.73 1.54 97.01 11.71 1.89 .063Number of chronic diseases 2.06 1.49 1.88 1.55 2.31 1.37 j1.82 .071Number of medicine 1.14 1.03 0.99 0.93 1.34 1.14 j2.10 .038

Note. aFisher’s exact test.


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MCS score (mental health) to be significant risk predictors ofdisturbed sleep.

A number of studies have supported the view that dis-turbed sleep is associated with the physical symptoms ofage (Chen et al., 2009; Su et al., 2004). Consistent withprevious studies (Su et al., 2004), we found nocturia to bethe major risk factor for disturbed sleep in older people.Prevalence of nocturia in our study differed significantlybetween sleep disturbed and non-sleep disturbed groups(47.8% vs. 22.6%, p G .01). Participants with nocturia faceda 2.24-fold increase in the risk of disturbed sleep, which maybe attributed to the interruption of sleep due to nocturia andsubsequent difficulty returning to sleep. Disturbed sleep wasalso associated with dizziness, which occurred in 16.9% of par-ticipants. These findings suggest the role of physical symptomsin disturbing sleep. Healthcare professionals should provide

appropriate symptommanagement to improve sleep quality forolder people based on patient need.

Psychosocial factorsmay contribute to disturbed sleep. Con-sistent with other studies, we found disturbed sleep associatedwith depression, sedentary lifestyle, and self-reported functionalstatus (Martin et al., 2010; Shirota, Tamaki, Hayashi, & Hori,2000; Wong & Fielding, 2011). We found that participantswith a sedentary lifestyle faced a 6.7-fold increase in disturbedsleep risk and that relatively poor mental health increased dis-turbed sleep risk by8%.The effect ofmental health ondisturbedsleep was consistent with Wong and Fielding’s (2011) studyreport in Chinese sample. However, logistic regression showedthat depression was not an important predictive factor of dis-turbed sleep in our study. Although previous studies supporteda negative effect of depression on sleep quality (Wu et al.,2012; Yao et al., 2008), our results suggest that the role of

TABLE 3.

Sleep Quality of Participants (N = 160)

Variable M SD Range Frequency %

PSQI score 5.54 3.32 1Y16e5 93 58.195 67 41.9

Subjective sleep quality 1.06 0.58 0Y3Very good 21 13.1Good 110 68.8Poor 28 17.5Very poor 1 0.6

Sleep latency 1.26 1.16 0Y30 54 33.81Y2 48 30.03Y4 20 12.55Y6 38 23.8

Sleep duration (actual hours) 0.98 (6.33) 1.10 (1.62) 0Y3 (2Y10)Q7 hours 74 46.36Y6.9 hours 40 25.05Y5.9 hours 22 13.8e4.9 hours 24 15.0

Sleep efficiency (actual %) 0.76 (84.47) 1.06 (17.70) 0Y3 (23Y120)Q 85 92 57.575Y84 35 21.965Y74 12 7.5e 64 21 13.1

Sleep disturbance 0.86 0.43 0Y20 28 17.51Y9 127 79.410Y18 5 3.119Y27 0 0.0

Daytime dysfunction 0.57 0.77 0Y30 94 58.81Y2 41 25.63Y4 24 15.05Y6 1 0.6

Note. PSQI = Pittsburg Sleep Quality Index. The mean score of ‘‘use of sleep medications’’ domain is zero.


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active lifestyle cannot be neglected and should be given priorityconsideration prior to recommending an intervention programfor depressive symptoms in elderly patients. Inconsistent withother studies (Morgan, 2003), our study did not find overallphysical activity significantly associated with disturbed sleep.This may be attributed to the relatively lower level of physicalactivity and higher standard deviation among participants.Mean PASE score in this study was 70.43 (SD = 50.57). Thisis lower than reported in previous studies (Dinger, Oman,Taylor, Vesely, & Able, 2004), but similar to that reported byWu et al. (2012). Cultural diversity may result in comparisondifficulties due to the use of different language version instru-ments. Although we did not find sleep quality significantlyrelated to overall physical activity, further analysis showedthat older adults with more yard work had better sleep qual-ity. Previous studies had indicated that moderate-intensity

exercise may improve sleep quality (King et al., 2008). Ourparticipants were likely to perform more sedentary activi-ties, such as watching television or walking, and less moderate-intensity exercises. Therefore, overall physical activity may nothave had a significant impact on participant sleep quality.

Disturbed sleep has also been related to chronic diseasesand medications. In this study, disturbed sleep was reportedin older people with hypertension and those who use anti-hypertensives or gastric medications. Hypertension is one ofthe most common chronic diseases among older persons,and many take antihypertensives as a result. In our study,41.9% participants had hypertension and 38.8% used anti-hypertensives. Similar results were reported by a study thatfound that patients with resistant hypertension had shortersleep duration and lower sleep efficiency (Friedman, Bradley,Ruttanaumpawan, & Logan, 2010). In 2011, National Sleep

TABLE 4.

Depression, Physical Activity, and Self-Reported Functional Status ofParticipants by Group (N = 160)

Variable



(n = 67)

t pM SD M SD M T SD SD

Geriatric depression score 3.19 3.33 2.44 2.76 4.24 3.76 j3.32 .001Physical activity 70.43 50.57 76.04 48.19 62.63 53.08 1.66 .098Leisure time activitiesSitting 1.86 1.27 1.78 1.29 1.97 1.25 j0.94 .351Walking 0.56 0.57 0.62 0.56 0.47 0.58 1.64 .103Light sports 0.19 0.55 0.22 0.61 0.16 0.46 0.67 .503Moderate sports 0.31 0.67 0.35 0.75 0.24 0.53 1.12 .264Strenuous sports 0.12 0.48 0.12 0.50 0.12 0.46 j0.06 .951Muscle strength 0.03 0.16 0.02 0.15 0.03 0.17 j0.39 .697

Household activitiesLight housework 0.71 0.46 0.73 0.45 0.67 0.47 0.81 .418Heavy housework 0.44 0.50 0.43 0.50 0.45 0.50 j0.22 .826Home repair 0.01 0.11 0.01 0.10 0.01 0.12 j0.23 .816Yard work 0.12 0.32 0.16 0.37 0.06 0.24 2.11 .037Outdoor gardening 0.17 0.38 0.22 0.41 0.10 0.31 1.94 .054Caring others 0.14 0.35 0.13 0.34 0.16 0.37 j0.62 .535

Work-related activitiesWork/volunteer 0.36 1.80 0.52 2.20 0.14 0.99 1.47 .145

Self-reported functional statusPhysical functioning 65.57 25.45 68.34 25.17 61.72 25.52 1.63 .104Role limitation due tophysical problems 59.38 47.97 65.05 46.50 51.49 49.21 1.76 .081

Role limitations due toemotional problems 70.00 45.67 71.68 45.03 67.66 46.77 0.55 .584

Vitality 71.34 20.36 76.24 18.53 64.55 20.96 3.72 G.001Mental health 73.20 18.12 76.86 15.78 68.12 19.96 2.98 .004Social functioning 81.41 18.81 84.14 17.98 77.61 19.41 2.19 .030Bodily pain 85.47 17.37 88.12 15.38 81.79 19.32 2.22 .028General health 58.44 19.88 64.09 17.27 50.60 20.70 4.35 G.001Physical component 50.02 5.24 50.78 5.20 48.97 6.14 2.18 .031Mental component 50.45 6.14 51.97 5.40 48.35 6.52 3.83 G.001


256

Foundation (2011) reported that certain medications includ-ing antihypertensives can lead to insomnia. Although only7.6% of study participants used gastric medications, adverseeffects such as gastroesophageal reflux and other gastroin-testinal problems during sleep have been reported in previ-ous studies (Ancoli-Israel & Cooke, 2005; Chen et al., 2009).

LimitationsThe limitations of this study relate to the localized nature ofthe sample and our cross-sectional design. We used conve-nience sampling to recruit participants from an urban area ofnorthern Taiwan. Thus, findings cannot be generalized to allolder people in Taiwan. In addition, the cross-sectional de-sign and different instrument characteristics of the Chineseversion of PASE may also limit interpretation of study find-ings. Longitudinal or follow-up studies are needed to identifyevidence of a causal relationship between disturbed sleep andphysicalYpsychosocial factors in community-dwelling olderpeople. Another limitation was the lack of examination of theassociation with disturbed sleep and environmental factors,such as light, noise, and temperature. In addition to insom-nia, other common sleep disorders such as sleep apnea, pe-riodic limb movement disorder, and restless leg syndromecould disturb the sleep patterns of older adults. Thus, futurestudies are needed to evaluate more comprehensively thefactors related to disturbed sleep. In addition, research onmethods used to self-manage disturbed sleep and their effi-cacy is warranted.

ImplicationsNurses play a significant role in the management of dis-turbed sleep in older people. To ensure that older people geta good night’s sleep, it is necessary to enhance nurses’ knowl-edge of older persons’ sleep experiences in order to managetheir different sleeping patterns and needs effectively. Thefindings of our study suggest that nurses should assess sleepquality in elderly people from a comprehensive perspectivethat includes demographic characteristics, physical health sta-

tus, mental health, and social activity. Nurses may then pro-vide comprehensive, adequate interventions to maintain sleepquality based on individual needs. Patient education regard-ing symptom management and an active lifestyle promotemaintenance of sleep quality in older people. The followingstrategies are recommended for nurses.

A comprehensive physicalYpsychosocial assessment ofdisturbed sleep should first be performed to monitor sleepquality and contributing factors so that nurses learn to betterrecognize the sleep problems of older adults. Nurses can usea simple screening tool such as the PSQI to identify olderadults with disturbed sleep (PSQI 9 5) and ask that they keepa sleep diary of sleep patterns and activity habits. Physi-cal health status can be evaluated by asking older adultsabout their chronic diseases, physical symptoms, and useof medications. In addition, mental status can be assessedusing the GDS-SF. A simple checklist would help facilitateimplementation.

It will then be important to eliminate factors contributingto disturbed sleep. For example, older adults who have noc-turia or depression or who use antihypertensives should bereferred to clinics or other health professionals for furthertreatment and advice. Those with a sedentary lifestyle can beencouraged by nurses toward a more active lifestyle, such asparticipating in social activities.

Finally, nurses should implement interventions early toreduce disturbed sleep, maintain physical function, and im-prove patient quality of life. Effective sleep interventionsmayinclude establishing good sleep hygiene including a suitablebedtime routine, regular exercise during the day, and the useof relaxation techniques such as music and guided imageryto promote and maintain restful sleep. For those who expe-rienced severe disturbed sleep, pharmacotherapy may besuggested, although such is not recommended for long-termuse due to negative side effects.

ConclusionsThis study found disturbed sleep to be a common problemamong older adults living in communities in northernTaiwan.

TABLE 5.

Predictors of Disturbed Sleep by Logistic Regression (N = 160)

Variable B OR p

95% CI

Lower Upper

Dizziness 0.92 2.51 .063 0.95 6.59Nocturia 1.18 3.24 .003 1.47 7.13Antihypertensives 0.59 1.81 .221 0.70 4.69Gastric medications 1.22 3.40 .178 0.57 20.19Number of medicine j0.10 0.90 .696 0.54 1.50Sedentary lifestyle 2.05 7.73 .024 1.32 45.39Physical component summary 0.01 1.01 .895 0.93 1.09Mental component summary j0.09 0.92 .027 0.85 0.99Depression 0.03 1.03 .686 0.90 1.18Constant 2.73 15.36 .331


257

Participants with nocturia, dizziness, hypertension, sedentarylifestyle, higher levels of depression, and a poorer self-reportedfunctional status were more likely to experience disturbedsleep. These findings highlight the importance of assessingphysical symptoms and psychosocial factors in older patientsin order to recommend appropriate interventions that effec-tively promote sleep quality.

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北台灣地區社區老年人的睡眠品質預測因子

楊秋月1　邱愛富2*

1國立陽明大學護理學系助理教授　2國立陽明大學護理學系教授

背　景睡眠品質不良會對老年人的身心健康造成負面影響，甚至增加死亡率。然而，在台灣

地區探討老年人睡眠品質的相關研究仍然有限。

目　的本研究目的欲探討北台灣地區社區老年人的睡眠品質情形及其預測因子。

方　法採橫斷式研究設計，以結構式問卷訪談160位六十歲以上的社區老年人，問卷量表包

括：人口學資料、健康狀況、巴氏量表、匹茲堡睡眠量表、短版老年憂鬱量表、短版

健康調查量表及老年身體活動量表。

結　果研究發現41.9%北台灣社區老年人有睡眠不佳的情形。睡眠品質與夜尿、頭暈症狀、高

血壓、使用降壓藥和胃藥、功能狀態不佳、憂鬱、及靜態生活型態有相關性。邏輯式

迴歸顯示，夜尿、靜態生活型態、及心理健康為睡眠品質的最重要預測因子。

結　論／

實務應用

睡眠品質應評估個人的生理、心理、及社會狀況，護理人員應教導老年人如何處理生

理症狀和維持活躍的生活型態以改善睡眠品質。

關鍵詞：功能狀態、老年人、靜態生活型態、睡眠品質。

接受刊載：101年8月3日*通訊作者地址：邱愛富　　11221台北市立農街二段155號電話：（02）28267354　　E-mail: [email protected]

老年人的睡眠品質 The Journal of Nursing Research VOL. 20, NO. 4, DECEMBER 2012

260

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