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J Gerontol Nurs. Author manuscript; available in PMC 2025 January 01.
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Published in final edited form as:

J Gerontol Nurs. 2024 July ; 50(7): 12–18. doi:10.3928/00989134-20240618-03.

Comparing Sleep Quality, Duration, and Efficiency Among Low-

Income Community-Dwelling Older Adults With and Without
Physical Disabilities
James D. Brightman, PhD, CRC,
College of Nursing, University of Central Florida, Orlando

Kworweinski Lafontant, MS,

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College of Nursing, University of Central Florida, Orlando; Institute of Exercise Physiology and
Rehabilitation Sciences, University of Central Florida, Orlando

Jethro Raphael M. Suarez, MS,

College of Nursing, University of Central Florida, Orlando

Jennifer M. Crook, PhD, RN,

College of Nursing, University of Central Florida, Orlando; Department of Mechanical and
Aerospace Engineering, University of Central Florida, Orlando; Minority Health and Health Equity
Research Support Services, Mayo Clinic Florida, Jacksonville, Florida

Ladda Thiamwong, PhD, RN, FAAN

College of Nursing, University of Central Florida, Orlando; Disability, Aging, and Technology
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Cluster, University of Central Florida, Orlando

Abstract
PURPOSE: Physical disabilities may exacerbate the natural decline in sleep quality that occurs
with aging. In the current study, we assessed sleep quality and medicinal sleep aid use among 87
community-dwelling older adults with (n = 24) and without (n = 63) physical disabilities.

METHOD: Sleep quality, duration, and efficiency were assessed subjectively with the Pittsburgh
Sleep Quality Index. Sleep duration and efficiency were objectively measured with actigraphy.
Participants self-reported medicinal sleep aid use.

RESULTS: Significant group differences were observed in sleep duration measured objectively (p
= 0.01) and subjectively (p = 0.04). No other group differences were observed for sleep factors (p
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> 0.05) or medicinal sleep aid use (p = 0.41).

CONCLUSION: Findings show that physical disability may be a factor in sleep duration;
however, physical disability was not found to be associated with worsened sleep perception
or greater reliance on medicinal sleep aids. Future research should consider longer objective
actigraphy assessment windows and explore potential subgroup differences in sex and race/
ethnicity.

Address correspondence to James D. Brightman, PhD, CRC, College of Nursing, University of Central Florida, 12201 Research
Parkway, Orlando, FL 32826-2210; jbright007@gmail.com.
Disclosure: The authors have disclosed no potential conflicts of interest, financial or otherwise.
 Brightman et al. Page 2

Seventy million Americans experience chronic sleep disorders (Soares de Almeida

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Ciquinato et al., 2023) and older adults are more likely than younger adults to have problems
sleeping (Chen, 2019). Sleep quality changes as a function of normal aging (Borges et
al., 2019; Landry et al., 2015); however, the experience of aging and difficulty sleeping is
multifactorial (Li et al., 2022). Income and disability status can also impact sleep quality
among older adults (Campanini et al., 2019; Li et al., 2022). Sleep is a critical part of
the circadian rhythm of older adults, and the prevalence of dysregulated sleep may lead to
increased use of over-the-counter or prescribed medicinal sleep aids to attempt to alleviate
the issue (Landry et al., 2015; St George et al., 2009). Chronic use of sleep aids, however,
may not be beneficial for alleviating sleep complaints (Schroeck et al., 2016).

Dysregulated sleep encompasses several factors, such as decreased sleep duration,

efficiency, and overall quality (St George et al., 2009; Stone et al., 2008). An increase
in fall risk, as well as a decrease in physical function and overall quality of life, have
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been linked to sleep dysregulation (St George et al., 2009). Moreover, cellular repair occurs
during sleep, and this cellular repair aids in combatting age-related disorders, such as
sarcopenia (Choi et al., 2020). Sarcopenia is a progressive and generalized skeletal muscle
disorder that is associated with an increased likelihood of adverse outcomes, including
falls, fractures, physical disability, and mortality (Cruz-Jentoft et al., 2010). Although sleep
quality is important for all older adults to combat age-related disorders, individuals with
low income and a physical disability may be at a disadvantage. Income status is considered
a social determinant of health, with individuals at a lower income level experiencing a
greater prevalence of chronic poor sleep (Jean-Louis et al., 2022). Physical disabilities are
characterized by difficulties in performing activities of daily living and diminished physical
function (Chien & Chen, 2015). Previous research has also shown a connection in older
adults between dysregulated sleep and physical disability (Campanini et al., 2019; Chien
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& Chen, 2015). However, those researchers recommend further largescale, well-controlled
studies to verify the connection.

Historically, sleep quality has been assessed either subjectively, with assessments such
as the Pittsburgh Sleep Quality Index (PSQI), or objectively, with assessments such as
polysomnography or with an ActiGraph (Landry et al., 2015). Researchers recommend
that sleep quality in older adults be measured subjectively and objectively. Subjective
assessments rely on an individual’s memory of sleep and sleeping habits, whereas the
combination of objective and subjective assessments may provide unique insights into sleep
quality that only one measure cannot provide.

Despite recommendations, previous research that established a connection between

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disability and sleep has done so largely with subjective measurements alone (Campanini et
al., 2019; Chien & Chen, 2015). Considering that older adults are at high risk for developing
a disability (Chien & Chen, 2015), understanding how living with a physical disability
might impact older adults’ sleep quality is important. The current investigation aimed to
compare objectively and subjectively assessed sleep quality, efficiency, and duration among
older adults living with and without physical disabilities. In addition, we sought to compare
medicinal sleep aid use between those living with and without physical disabilities. We
hypothesized that low-income community-dwelling older adults with a physical disability

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would exhibit poorer sleep quality, efficiency, and duration, as well as greater medicinal
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sleep aid use, compared to those without a physical disability.

METHOD
Design
The current study was a cross-sectional study with primary data analysis and part of a
federally funded study (NIH Grant #R01MD018025) of which protocols were pre-registered
on ClinicalTrials.gov (NCT05778604) and published elsewhere (Thiamwong et al., 2023).
All study protocols were approved by the University of Central Florida Institutional Review
Board (STUDY00003206) and conducted in accordance with the Declaration of Helsinki.
All participants gave written informed consent prior to participation.

Participants
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We recruited 121 older adults, comprising 13 men and 108 women, using flyer
distribution, word-of-mouth, and community partners that facilitated introductions to
potential participants. Participants all resided in older adult living communities within the
greater Orlando, Florida metropolitan region, which has a diverse population. Participants
were screened for inclusion and exclusion criteria prior to participation. Participants were
included in the study if they were aged ≥60 years, lived independently in their own homes
or apartments, had low-income status based on the 2019 poverty thresholds relative to
family size (U.S. Census Bureau, 2020), and if their ActiGraph registered data for at least
five nights during the week-long data collection period. Participants were excluded from
the study if they were actively receiving treatment from a rehabilitation facility or were
cognitively impaired, determined by a score ≤4 on the Memory Impairment Screening test
or a score ≤22 on the Rowland Universal Dementia Assessment Scale (Buschke et al., 1999;
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Nielsen et al., 2019), two assessments used as part of a larger research study.

Measures
Physical Disability and Medicinal Sleep Aid.—Physical disability and medicinal
sleep aid use were classified using a self-report checklist from the Centers for Disease
Control and Prevention (CDC; 2019) Stopping Elderly Accidents and Deaths Initiative
(STEADI) algorithm. Participants completed the STEADI checklist in person. The checklist
includes yes or no questions about physical ability and sleep aid use. Participants were
classified as having a physical disability if they answered yes to the statement, “I use or
have been advised to use a cane or walker to get around safely” (CDC, 2019). Participants
were classified as using medicinal sleep aids if they answered yes to the statement, “I take
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medicine to help me sleep or improve my mood” (CDC, 2019).

Subjective Sleep Assessment.—On the same day, after self-reporting physical

disability status and medicinal sleep aid use, participants completed the PSQI in person.
The PSQI (Buysse et al., 1989) was originally developed to categorize individuals as
either “good” or “poor” sleepers. This 19-item questionnaire assesses sleep quality using
subjective ratings for seven different components: sleep quality, sleep latency, sleep duration,
sleep efficiency, sleep disturbance, use of sleeping medication, and daytime dysfunction.

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Some items are open ended, whereas others are scored on a Likert-type scale ranging from
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0 to 3, with higher scores indicating a greater degree of sleep disturbances. Respondents are
asked to answer the questionnaire retrospectively, surveying sleep components spanning the
previous month. The PSQI is quick and easy to administer and score, making it an effective
tool for sleep quality assessments. It has also been validated as a measure of sleep quality
and sleep efficiency in various populations, with an internal consistency of α = 0.72 in older
women (Beaudreau et al., 2012) and α = 0.69 in older men (Spira et al., 2012).

Objective Sleep Assessment.—Immediately after completing the PSQI, participants

were instructed to wear the ActiGraph GT9X Link on their non-dominant wrist for 7
consecutive days. Participants were considered noncompliant and excluded if <5 days
of ActiGraph data were recorded. The GT9X Link uses a tri-axial accelerometer and
photoplethysmography sensor to collect data regarding sleep duration and efficiency.
ActiGraph data were extracted using ActiLife software (version 6.13.5) and processed
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using R statistical software (version 4.3.1) using pre-existing built-in raw accelerometer
data analysis functions and code (Migueles et al., 2019; van Hees et al., 2015; van
Hees et al., 2018). Wrist-worn actigraphy has demonstrated good concurrent validity with
polysomnography, which is considered a gold standard for sleep assessments (Weiss et al.,
2010). The GT9X does not provide a global sleep quality score like the PSQI; therefore, no
direct comparison could be made for that variable.

Data Analysis
All statistical analyses were conducted using jamovi version 2.4.1. Levene’s test (used
to assess the assumption of equal variances between dependent variables) revealed non-
heteroscedastic sleep data (ActiGraph sleep efficiency and PSQI sleep duration), and a
Kolmogorov-Smirnov test (used to assess the assumption of a normal distribution pattern for
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each dependent variable) revealed that sleep efficiency data from the PSQI and ActiGraph
were not normally distributed. However, results did not differ between nonparametric and
parametric assessments, so parametric assessments adjusting for unequal variances are
reported within. A one-way Welch’s analysis of variance (ANOVA) was used to compare
sleep duration and efficiency between groups using Games-Howell adjustments for post-hoc
analyses. Welch’s ANOVA and Games-Howell post-hoc assessments account for unequal
variances. A chi-square test of association was used to compare pharmaceutical sleep/mood
aid use between groups. Data are presented as mean (standard deviation) unless otherwise
noted. The threshold for statistical significance was set to p < 0.05.

RESULTS
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Participants
Of 121 participants recruited for this study, only 87 participants completed all required
assessments. Therefore, 87 participants were included in the analysis. Table 1 details
participant characteristics.

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Sleep Quality, Duration, and Efficiency

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Table 2 details results of between-group comparisons of sleep quality and medicinal

sleep aid use. A significant between-group difference was identified in the category of
objective ActiGraph sleep duration (p = 0.01), with respondents without physical disability
reporting longer sleep duration (mean = 7 hours, SD = 1.7 hours) compared to those with
physical disability (mean = 6 hours, SD = 1.9 hours). A similar significant difference was
observed between groups for subjective sleep duration (p = 0.04). Global sleep quality
score (measured subjectively) identified lower sleep quality scores in participants with
physical disability (mean = 8.3, SD = 3.9) compared to those without physical disability
(mean = 6.9, SD = 4.3), although findings were not statistically significant (p = 0.21).
Likewise, objective measurement of sleep efficiency via actigraphy revealed non-statistically
significant differences between groups of 78.3% (SD = 15.5%) and 83.1% (SD = 11.8%)
in respondents without and with physical disability, respectively. No statistically significant
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differences in subjective sleep efficiency (p = 0.09) were observed either.

Medicinal Sleep Aid Use

No significant difference in sleep aid use was identified between participants with or without
physical disabilities (χ2 = 1.14, p = 0.29). Of 63 participants without a physical disability,
14 (22%) reported using a pharmaceutical sleep/mood aid. Of 24 participants with a physical
disability, eight (33%) reported using a pharmaceutical sleep/mood aid.

DISCUSSION
In the current study, using subjective and objective sleep assessments, we analyzed sleep
quality and medicinal sleep aid use among community-dwelling low-income older adults
with and without physical disabilities. We hypothesized that those living with a physical
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disability would exhibit poorer sleep quality, efficiency, and duration, as well as greater
medicinal sleep aid use compared to those without a physical disability and these results
partially support our hypothesis.

Many differences were not significant; however, we were able to identify a statistically
significant difference of longer sleep duration in participants without disability when
measured objectively via actigraphy and subjectively via the PSQI. There were no
significant differences identified in subjective sleep quality or efficiency, objective
efficiency, or medicinal sleep aid use.

One plausible explanation may be found in understanding the different temporal foci of
the PSQI and actigraphy. Whereas the PSQI measures quality and habits for the previous
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30 days of sleep, actigraphy measures present sleep duration and efficiency. Landry et al.
(2015) demonstrated that global PSQI scores did not correlate significantly with ActiGraph
data in younger or older adults but correlated with Consensus Sleep Diary (CSD) entries.
This finding suggests that subjective measures may be influenced by a Hawthorne effect,
where sleep is rated differently retrospectively compared to when it is rated presently.
Although our results did not indicate subjective differences in sleep quality between
those with and without a physical disability, future research should seek to validate our

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results using actigraphy and a different concurrent subjective assessment, such as the CSD.
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Furthermore, a longer assessment window of ≥14 days may help account for potential sleep
variances by increasing the number of observations with enough data collection to capture
trends (Landry et al., 2015).

Using subjective and objective assessments, those with a physical disability demonstrated
significantly lower sleep duration than those without a physical disability. Furthermore,
accounting for standard deviations, both groups are on the cusp of the recommended amount
of sleep for older adults (Hirshkowitz et al., 2015). Previous research is equivocal on the
impact of sleep duration, with some studies indicating negative consequences to prolonged
sleep duration and others indicating negative consequences to short sleep duration (Devore
et al., 2016; Fu et al., 2017; Goldman et al., 2007). It is likely that prolonged and short
sleep duration are maladaptive for older adults; however, it is not clear if the statistically
significant difference in sleep duration observed in the current study represents a clinically
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significant difference. Actigraphy is limited in its ability to produce a measure of overall

sleep quality like the PSQI, so future research may benefit from using a prospective study
design to assess consequences to short and prolonged sleep duration over time in individuals
with a physical disability.

Other studies have examined sleep quality with similar instruments in the subpopulations
of race/ethnicity and sex. Carnethon et al. (2016) identified that Black participants were
more likely to have shorter sleep duration and poorer subjective and objective sleep
quality compared to their White counterparts. Hispanic participants were also identified
to display poorer sleep quality patterns (Chen et al., 2015; Patel et al., 2010), although
research shows conflicting results on participants of Hispanic origin (George et al.,
2020). Multiple meta-analyses have corroborated sleep disparities among impoverished
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racial/ethnic minoritized individuals (Ruiter et al., 2011; Sosso et al., 2021; Sosso et al.,
2023). Likewise, sex and gender play a role in sleep quality and duration, which may
be explained by hormonal differences, gender differences in reporting, and environmental,
social, and cultural influences (Mallampalli & Carter, 2014). Evidence for sex/gender sleep
differences include women reporting better sleep quality, efficiency, and duration, but higher
sleep-related complaints (Dietch et al., 2017; Kocevska et al., 2020; Krishnan & Collop,
2006) and others observing poorer overall sleep quality in female participants (Zeng et
al., 2020). When further explored by race/ethnicity, Black/African American and Hispanic/
Latino women report poorer sleep quality due to a complexity of factors, including greater
prevalence of obstructive sleep apnea (Chen et al., 2016; Jackson et al., 2020; Meetze et al.,
2002), life stressors, increased body mass index, and financial hardships (Matthews et al.,
2019).
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One indication of poor sleep quality may be medicinal sleep aid use, as those
pharmaceuticals are designed to improve sleep. No significant difference in medicinal sleep
aid use was observed between individuals with and without a physical disability. This
finding supports the assertion that there may not be a meaningful difference in sleep quality
between individuals with and without a physical disability. However, we did not assess
specific details of sleep aid use, such as frequencies, dosages, and drug classes. These are
important details that should be investigated further, as older adults often turn to medicinal

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sleep aids (Albert et al., 2017). Furthermore, there is the potential for medications targeting
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symptoms of a disability to also influence sleep (Pagel & Parnes, 2001), so consideration is
needed in categorizing all medications used.

LIMITATIONS
The current study has some limitations. Factors that were not assessed included whether
participants had a preexisting medical or mental health condition, and their living
arrangements inside their home. Moreover, disability status typically results in function loss
or functional impairment, and each disability is unique and affects individuals differently.
Variations in physical function among individuals with a physical disability can largely
be attributed to how physical disability is defined and categorized. The current study
relied on the use or recommended use of a mobility aid for defining physical disability
and self-report for categorizing individuals. It is possible that observed results might have
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changed if a different definition of physical disability were adopted. Similarly, our study
relied on self-report to account for medicinal sleep aid use. When self-identifying, it
is possible that participants may have overlooked medications used for other issues that
simultaneously impact sleep. However, although use of self-report can be limiting, this study
used validated and common instruments, such as the PSQI and STEADI checklist, which
aided in consistently guiding participants in their self-report.

Due to the limited numbers of male and racial and ethnically diverse participants, we did
not stratify results by sex or race/ethnicity. Future research may benefit from investigating
potential differences in how physical disability impacts sleep quality, as both sex (Kocevska
et al., 2021; Krishnan & Collop, 2006; Wang & Boros, 2021) and race/ethnicity (Chen et
al., 2015; Dietch et al., 2017; George et al., 2020; Ruiter et al., 2011) differences have been
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observed in sleep quality retrospectively via the PSQI and presently via the CSD, while still
concurrently measuring sleep objectively. In addition, there are countless other factors that
could potentially influence sleep and cannot reasonably be controlled for in a single study,
so current results should be interpreted within the context of variables that were accounted
for. Results of this study can reasonably be generalized to low-income, community-dwelling,
older adult men and women with and without physical disabilities.

CONCLUSION
Despite no difference in perceived sleep quality and sleep efficiency, sleep duration is
lower in those with a physical disability than those without a physical disability. Moreover,
medicinal sleep aid use does not differ in individuals with and without a physical disability.
Health care professionals should be cognizant of the reduced sleep duration that individuals
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with physical disabilities experience and not disregard their subjective reporting. Individuals
with physical disabilities may benefit from targeted interventions to increase sleep duration.
Further research is needed to validate these results, particularly using subjective and
objective sleep assessments, a larger male sample, and more detailed reporting in medication
use.

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TABLE 1

Participant Characteristics (N = 87)

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n (%)

Characteristic Without Physical Disability (n = 63) With Physical Disability (n = 24)

Age (years), mean (SD) (range) 72.8 (6.36) (61.1 to 87.9) 75.1 (7) (62.3 to 87.3)

Sex

Female 55 (87) 21 (88)

Male 8 (13) 3 (12)

Race/ethnicity

African American 32 (51) 16 (67)

Asian 2 (3) 0 (0)

Hispanic 22 (35) 3 (12)

Non-Hispanic White 7 (11) 5 (21)

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Educational level

Lower than high school 5 (8) 2 (8)

High school 32 (51) 12 (50)

College or higher 26 (41) 10 (42)

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TABLE 2

Comparison of Sleep Quality, Duration, and Efficiency Using Subjective and Objective Sleep Assessments (N
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= 87)

Mean (SD) (Range)

Without Physical With Physical

Disability Disability
Variable (n = 63) (n = 24) F p

PSQIa sleep quality 7.2 (4.3) (0 to 16) 8.5 (4.1) (2 to 16) 1.6 0.21

PSQI sleep duration (hours) 8.5 (1.6) (4 to 12) 7.3 (2.5) (2 to 10.5) 4.5 0.04
ActiGraph sleep duration (hours) 7.2 (1.7) (3.19 to 12.3) 5.9 (2) (2.78 to 9.57) 7.2 0.01

PSQI sleep efficiency (%) 82.8 (24.4) (45.5 to 225) 88.8 (32) (50 to 200) 0.7 0.41

ActiGraph sleep efficiency (%) 77.7 (16.1) (20.7 to 94.8) 83.4 (12.9) (28.2 to 95.7) 3 0.09

Note. PSQI = Pittsburgh Sleep Quality Index.

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a
Comprises 19 items that generate seven component scores. Some items are open-ended and others are scored on a Likert-type scale ranging from 0
to 3, with higher scores indicating a higher degree of sleep disturbances.
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