Active Lifestyle Is Linked With Proper Sleep Quality in Older Adults Living Nursing Homes

Article information

Sleep Med Res. 2024;15(2):81-88
Publication date (electronic) : 2024 June 27
doi :
1Department of Exercise Physiology, Faculty of Physical Education and Sport Sciences, Allameh Tabataba’i University, Tehran, Iran
2Department of Physical Education, Islamic Azad University, South Tehran Branch, Tehran, Iran
3Department of Exercise Physiology, Islamic Azad University, Tehran North Branch, Tehran, Iran
Corresponding Author Mahsa Moghadassi, MSc Department of Exercise Physiology, Islamic Azad University, Tehran North Branch, Tehran, Iran Tel +1-732-875-95-22 E-mail
Received 2024 January 5; Revised 2024 May 27; Accepted 2024 June 6.


Background and Objective

Sleep disorders are a significant concern among older adults. Study Objective: This research aims to explore the relationship between physical activity and sleep quality among elderly residents of nursing homes.


The study involved 119 individuals aged 65 years and above, residing in nursing homes in Tehran. Demographic information was collected and recorded, followed by measurements of body composition, blood pressure, and anthropometric indices including weight, body mass index, height, waist circumferences, and hip circumferences. Digital scales from OMRON, an OMRON M2 blood pressure monitor, and a measuring tape were used for these measurements. Physical activity and sleep quality were assessed using the Physical Activity Scale for the Elderly and the Pittsburgh Sleep Quality Index, respectively.


Pearson correlation analysis revealed an inverse relationship between age and sleep quality (p = 0.003) as well as its components: subjective (p = 0.017), latency (p = 0.001), disturbance (p = 0.020), and dysfunction (p = 0.026). Conversely, a direct and significant correlation was observed between physical activity levels and sleep quality (p = 0.003), along with its components: subjective (p = 0.001), latency (p = 0.001), and disturbance (p = 0.003). Moreover, a positive and significant connection was found between diastolic blood pressure and subjective sleep quality (p = 0.024).


The study’s results underscore that physical activity serves as a non-pharmacological and cost-effective approach for enhancing sleep quality and averting related complications in elderly individuals.


The process of aging is marked by gradual shifts in metabolic activities and a decline in cellular capacity to maintain equilibrium [1-4]. Consequently, aging can be described as the culmination of diverse cellular and molecular impairments that accumulate over time, leading to a range of disruptions in the body’s physiological processes. According to the World Health Organization, by the year 2030, it is projected that approximately one-sixth of the global population will be aged 60 years or older, with the demographic cohort of individuals in this age group increasing from 1 billion in 2020 to an estimated 1.4 billion. Moreover, by the year 2050, it is anticipated that the global population of individuals aged 60 years and older will double, reaching an estimated 2.1 billion individuals [5]. The rising elderly demographic in Iran has raised significant concerns within the healthcare community. Based on data from the Statistics Center of Iran, around 8 million individuals (approximately 9.9% of the country’s population) were aged 60 or older in 2019. Predictions indicate that this figure will escalate to roughly 26 million individuals (around 26% of the population) by 2050 [6].

Alternatively, in a different context, geriatric syndrome encompasses a range of conditions. These include dementia, falls, diminished sleep quality, and urinary incontinence. Remarkably, it is noted that nearly half of individuals aged 60 or older experience symptoms of geriatric syndrome [7-9]. Concurrently, the emergence and intensity of geriatric syndrome are impacted by diverse elements, including lifestyle factors (such as physical activity and dietary choices), social and economic status, and the living environment [10,11].

Recent research has underscored the pivotal significance of sleep as a fundamental physiological process, intricately linked to both physical and mental well-being [12,13]. Any disruptions in the quantity or quality of sleep can exert substantial adverse effects on the cognitive and physical faculties of individuals. Statistics indicate that approximately 30% to 45% of the global population grapples with sleep disorders, with factors such as age, gender, overall health, occupational demands, and socioeconomic status contributing to their emergence [14,15]. The accumulating body of evidence accentuates that reduced sleep quality stands out as a critical concern among the elderly population. Furthermore, epidemiological investigations reveal that more than 57% of older adults experience compromised sleep quality, while only 12% report a satisfactory sleep experience [16].

Conversely, Ohayon and Lemoine [17] have documented a sleep disorder prevalence exceeding 75% among elderly individuals residing in nursing homes. Diminished sleep quality can entail far-reaching repercussions, including an increased risk of falls, reduced life expectancy, persistent fatigue, cognitive and physical impairment, interpersonal challenges, compromised quality of life, and elevated mortality rates among the elderly [18]. Sleep disorders are additionally linked to diminished immune system efficacy; disruptions in the function of the hypothalamus, pituitary, and adrenal glands; heightened blood pressure; and an augmented susceptibility to cardiovascular diseases [19].

Research highlights that a significant proportion of the elderly population frequently resort to sleeping pills in an attempt to enhance their sleep quality. Nevertheless, owing to the adverse effects and transient nature of these medications’ impact on sleep quality, they do not constitute a secure strategy for the prevention and management of sleep disorders in older individuals [20]. Furthermore, our prior investigations have underscored the substantial role of physical activity and consistent exercise in mitigating and addressing various illnesses, particularly those associated with aging [3,21-24].

Experts in gerontology have articulated that consistent engagement in physical activity can wield a significant, multi-faceted influence on enhancing the quality of life, addressing chronic ailments, and improving sleep quality among the elderly and other demographic groups [3,10]. In fact, contrary to the conventional notion that sleep and physical activity are distinct behaviors regulated by disparate physiological mechanisms with no mutual impact, evidence has demonstrated a positive correlation between physical activity and sleep quality levels [25]. A longitudinal study conducted in 2012 revealed that embracing an active lifestyle and curtailing sedentary behaviors are pivotal factors in ameliorating sleep quality in the elderly [25]. Moreover, a comparative assessment of sleep quality between active and inactive men conducted by Kamrani et al. in 2014 concluded that the active group exhibited significantly higher levels of sleep quality [26].

Given the substantial impact of sleep quality on the cognitive and physical well-being of the elderly, as well as the significance of factors like physical activity and exercise in influencing sleep quality, and recognizing the scarcity of research in this domain within nursing homes in Iran, the primary aim of this study was to examine the correlation between physical activity and sleep quality among residents of nursing homes in the city of Tehran.


Subjects and Study Design

The present study, conducted using a cross-sectional approach, involved the design and administration of questionnaires. The research was carried out between October and December 2018 across ten nursing homes located in Tehran city. To determine the appropriate sample size, Cochran’s formula was employed, resulting in a calculated sample size of 131 individuals with a 95% confidence interval. Subsequently, a total of 131 elderly individuals aged over 60 voluntarily expressed their willingness to participate in the study.

Following a thorough assessment based on predefined inclusion and exclusion criteria, a subset of 119 participants (consisting of 33 men and 86 women) were deemed suitable for inclusion in the study. All necessary research permission were obtained from Iranian Welfare Organization, and explicit and written consent was obtained from all participants. Moreover, participants were assured that their responses would solely be utilized for the research.

Inclusion and Exclusion Criteria

The study established specific inclusion and exclusion criteria to ensure a focused and relevant participant pool. The inclusion criteria encompassed individuals aged 65 years or older, with a residence duration exceeding 90 days in a nursing home. Additionally, participants were required to be free from severe dementia or Alzheimer’s disease. Exclusion criteria encompassed individuals with contagious diseases or infections, a body mass index (BMI) below 17 (kg/m2), and an inability to engage in interviews. These criteria were implemented to create a coherent and suitable participant group for the study.

Data Collection

The initial assessment comprised a comprehensive demographic questionnaire encompassing details on education, marital status, medical history, prevalent diseases, and symptoms. Subsequently, anthropometric and body composition metrics were obtained. This encompassed the measurement and recording of height, waist circumference, pelvic circumference, and weight. Height and weight measurements were conducted using a tape measure and an OMRON digital scale (OMRON Healthcare, Binh Doung, Vietnam), precise to 0.1 kg, with minimal clothing to ensure accuracy. Furthermore, waist circumference and pelvic circumference were measured using a tape measure. The waist-to-hip ratio was computed by dividing waist circumference by pelvic circumference. BMI was also calculated using the formula weight (in kg) divided by height squared (in m2). Additionally, blood pressure measurements were taken and recorded after the subjects had been seated and at rest for ten minutes. An OMRON M2 blood pressure device was used, and measurements were taken from the subject’s left hand.

Sleep Quality Assessment

To evaluate the extent of sleep quality, the Pittsburgh Sleep Quality Index (PSQI) was employed. This questionnaire comprises 18 inquiries, categorically assessing sleep quality across 8 domains: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, daytime dysfunction, and a total score. It is noteworthy that a higher score on this questionnaire corresponds to a lower level of sleep quality among individuals. Scores that are equal to or surpass 5 indicate poor sleep quality. Notably, the PSQI exhibits sound validity and reliability for the Iranian population, with a Cronbach’s alpha coefficient of 0.83 [27].

Physical Activity Assessment

To evaluate the physical activity level of the elderly participants, the Physical Activity Scale for the Elderly (PASE) was employed. This questionnaire comprises 13 items, segmented into four sections that collectively gauge different aspects of physical activity: leisure activity component, housework activity, work-related activity, and a total score. PASE scores were classified into three categories: sedentary (<40), light physical activity (41–89), and moderate to intense physical activity (≥90) [28]. It is worth noting that the validity and reliability of the PASE questionnaire have been established within the Iranian population, with a Cronbach’s alpha coefficient of 0.97 [29].

Blood Pressure Assessment

In the study, participants’ blood pressure was assessed following a 10-minute rest period in a seated position, utilizing an OMRON M2 sphygmomanometer positioned on the upper left arm, with a precision of 3 mm Hg. Blood pressure (BP) classifications for elderly individuals were defined as follows [30]: 1) Normal BP: systolic blood pressure (SBP) < 120 mm Hg and diastolic blood pressure (DBP) < 80 mm Hg; 2) elevated BP: SBP 120–129 mm Hg and DBP < 80 mm Hg; 3) stage 1 hypertension: SBP 130–139 mm Hg and/or DBP 80–89 mm Hg; and 4) stage 2 hypertension: SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg.

Statistical Analysis

The normality of the data was assessed using the Kolmogorov-Smirnov test. The correlation between variables was examined utilizing the Pearson correlation coefficient. Additionally, to discern disparities in the data between groups characterized by low sleep quality and normal sleep quality, the independent t-test was employed. Statistical analyses were conducted using SPSS software version 21 (IBM Corp., Armonk, NY, USA), and significance was determined at a threshold of p < 0.05.


Table 1 presents the characteristics of the study participants. The average age of the subjects was 74.17 ± 8.67 years, with the majority falling within their 70s (37% of the participants). Concerning BMI, only 7% of the participants were underweight, while a notable 58% were categorized as overweight or obese. In terms of physical activity, approximately 68% of the subjects were deemed inactive, while only 10% exhibited high levels of physical activity. Furthermore, a considerable 80% of the elderly participants reported poor sleep quality, with the remainder demonstrating satisfactory sleep quality. Regarding blood pressure, over half of the subjects (57%) were identified as hypertensive, while nearly 30% exhibited normal blood pressure levels.

Demographical and physiological indices of subjects

The attributes of the sleep quality subscales are outlined in Table 2. In a comprehensive overview, fewer than 10% of the participants reported significant subjective sleep problems. Roughly one third of the subjects experienced delays in falling asleep. Regarding sleep duration, approximately 75% of the individuals achieved an appropriate sleep duration. Furthermore, nearly 80% of the subjects maintained satisfactory sleep efficiency, and approximately 43% did not encounter notable sleep dysfunction. Significantly, more than half of the subjects incorporated sleep medication into their regular routine.

Sleep quality’s subscale (PSQI) rate in the subjects (n = 119)

Table 3 illustrates the disparities in sleep quality subscales between individuals with high and low levels of physical activity. Inactive elderly individuals exhibited significantly higher scores in the subjective (p < 0.001), sleep latency (p < 0.001), and sleep disturbance (p = 0.002) scales. However, no noteworthy distinctions were observed in terms of sleep duration (p = 0.133), sleep efficiency (p = 0.599), use of sleep medication (p = 0.958), and daytime dysfunction (p = 0.214) between the active and inactive elderly groups.

The differences in sleep quality’s subscale (PSQI) between active and inactive elderly

The Pearson correlation analysis yielded significant findings. There was a notable inverse correlation observed between age and sleep quality (p = 0.003), as well as its individual subcomponents: subjective (p = 0.017), latency (p = 0.001), disturbance (p = 0.020), and dysfunction (p = 0.026). Conversely, a direct and significant relationship emerged between physical activity levels and sleep quality (p = 0.003), along with its subscales: subjective (p = 0.001), latency (p = 0.001), and disturbance (p = 0.003). Furthermore, a positive and significant correlation was identified between DBP and sleep subjectivity (p = 0.024). These results are summarized in Table 4.

The associations between physiological and physical activity levels with sleep quality and its subunits

Referring to Table 5, the participants were categorized into poor and normal sleep quality groups using the established cutoff point of 5 on the PSQI score [24]. Subsequent t-test outcomes indicated significant distinctions between these two groups. Specifically, the poor sleep quality group exhibited notably higher mean age (p = 0.002) compared to the normal sleep quality group. Additionally, scores across various sleep quality subscales displayed significant differences. In the poor sleep quality group, the scores for subjective (p < 0.001), latency (p < 0.001), disturbance (p < 0.001), medication (p < 0.001), and dysfunction (p < 0.001) were all significantly higher than those in the normal sleep quality group. Furthermore, the poor sleep quality group demonstrated significantly lower physical activity levels compared to the normal sleep quality group (p = 0.014).

Differences between general, physiological, and sleep quality subunits between normal and poor sleep quality groups


The sleep quality of the elderly is influenced by a multitude of factors, resulting in negative biological and physiological consequences [31]. These ramifications encompass fatigue, memory lapses, diminished attention and concentration, and even cardiac dysfunctions like tachycardia [32,33]. Expanding further, sleep disorders are linked to an augmented risk of falls, fatigue, and weakness [32]. Moreover, inadequate sleep or reduced sleep quality contributes to the emergence and progression of deleterious impacts on cognitive function among the elderly [33,34]. Furthermore, there is an established correlation between sleep disorders and conditions such as depression, dementia, and mood fluctuations [34,35]. Concurrently, various factors contribute to sleep disorders, including chronic illnesses like cardiovascular disease, type 2 diabetes, hypertension, stroke, cardiomyopathy, and neurological disorders such as cognitive impairment, depression, and Parkinson’s disease. Factors like medication consumption, circadian rhythm disruptions, skeletal muscle pain, osteoarthritis, and physical inactivity also play roles [36,37]. Notably, a direct connection has been reported between heart disease, obesity, arthritis, diabetes, osteoporosis, and sleep disorders [38]. Recent studies have consistently indicated a higher prevalence of falls, fatigue, disability, hospitalization, and premature mortality among elderly individuals with sleep disorders compared to those with satisfactory sleep [39].

In the current study, a significant and inverse correlation between age and both overall sleep quality and its individual components (subjective sleep quality, sleep latency, sleep disturbances, and daytime dysfunction) was observed. Moreover, the mean age within the poor sleep quality group was notably higher than that of the normal sleep quality group. These findings align with numerous previous studies. For instance, Varrasse et al. [40] reported that insomnia tends to increase with age, albeit with varying levels across different individuals. The underlying factors behind these trends involve alterations in sleep homeostasis, changes in the circadian pacemaker, and degeneration of the suprachiasmatic nucleus, which in turn affects circadian rhythms and leads to reduced melatonin output. Such factors are strongly influenced by the aging process, contributing to the development of sleep disorders and related consequences [40]. Simultaneously, advancing age brings about negative changes in bodily homeostasis and musculoskeletal structures, giving rise to issues such as noncommunicable diseases, disability, and sarcopenia, all of which are linked to decreased sleep quality [8]. However, physical activity and exercise present a non-pharmacological and secure avenue for addressing these concerns. Physical activity diminishes the risk of such diseases by enhancing various physiological and anatomical functions, ultimately leading to an indirect improvement in sleep quality [8,41].

In the current study, a noteworthy and inverse association was uncovered between the level of physical activity and overall sleep quality, along with its specific facets (subjective sleep quality, sleep latency, and sleep disturbances). Furthermore, the mean physical activity levels within the normal sleep quality group were significantly higher compared to the poor sleep quality group. In addressing poor sleep quality among the elderly, two predominant approaches are at hand: pharmacological and non-pharmacological methods, each with its own array of advantages and drawbacks [42]. Pharmacological interventions often entail side effects and may only offer temporary relief [43]. In contrast, non-pharmacological methods like physical activity present an approach that is low in risk, cost-effective, and easily accessible, all while yielding a plethora of health benefits. Engaging in physical activity cultivates a sense of tranquility, optimizes energy expenditure, promotes movement that counters physical fatigue, and ultimately upholds and enhances sleep quality in the elderly [43]. As supported by the Centers for Disease Control and Prevention, exercise and physical activity are acknowledged as safe alternatives to traditional pharmacological approaches in improving sleep quality [44]. Multiple research studies corroborate that sleep disorders heighten the susceptibility to various ailments by undermining the body’s immunity to illnesses and free radicals [45].

Recent discoveries have highlighted the association between exercise and a reduction in oxidative stress and inflammatory cytokines. This cascade of immunological changes ultimately bolsters the function of the immune system and concurrently enhances sleep quality in the elderly [46]. Another study supports the notion that physical activity corresponds with reduced levels of brain-derived neurotrophic factor, interleukin-β1, and hyperglycemia, all of which contribute to an overall improvement in sleep quality [47]. Furthermore, a review study has underscored that physical activities of low to moderate intensity are linked to enhancements in various dimensions of sleep quality, leading to a significant elevation in overall sleep quality. Contrarily, high-intensity physical activities tend to delay sleep onset and consequently degrade sleep quality [48]. Most research within this domain tends to advocate for light to moderate intensity activities as effective means to ameliorate sleep quality among the elderly. However, individual health considerations (comprising physical, mental, emotional, and nutritional aspects) should play a pivotal role in determining the suitable intensity and type of physical activity for elderly individuals. For those constrained by time, experts often suggest home-related tasks such as dishwashing and sweeping, along with light activities like stretching and walking. This strategy not only contributes to an increase in overall physical activity but also helps to enhance sleep quality and avert many of the consequences linked to insomnia and sleep disorders [49].

This investigation was limited to the geographical scope of Tehran, thereby potentially limiting the generalizability of the findings to broader populations. Additionally, the adoption of a cross-sectional design precluded the establishment of causal relationships between variables, as this approach captures data at a single time point. Moreover, the study may not have fully addressed all potential confounding variables that could impact the association between physical activity levels and the outcomes under investigation, including but not limited to socioeconomic status, comorbidities, and medication usage.

Understanding the factors contributing to diminished sleep quality in the elderly is pivotal for devising strategies to prevent, treat, and enhance this condition. Our study yielded promising outcomes, suggesting that augmenting physical activity could effectively ameliorate sleep disorders in the elderly. Thus, physical activity emerges as a potent, secure, easily accessible, and economical approach with extensive advantages for enhancing sleep quality, functional capabilities, and mental well-being among the elderly. Encouraging greater participation in sports and exercise among the elderly becomes imperative to sustain both individual and societal health.


Availability of Data and Material

The datasets generated or analyzed during the study are not publicly available due to the private information of participants and nursing homes in Tehran but are available from the corresponding author upon reasonable request.

Author Contributions

Conceptualization: Mehdi Kushkestani. Data curation: Sohrab Rezaie. Formal analysis: Sohrab Rezaie. Funding acquisition: Mehdi Kushkestani. Investigation: Mehdi Kushkestani, Mohsen Parvani. Methodology: Mohsen Parvani. Project administration: Mohsen Parvani. Resources: Mehdi Kushkestani. Software: Atiyhe Abassi, Sohrab Rezaie. Supervision: Mehdi Kushkestani. Validation: Sohrab Rezaie. Visualization: Mehdi Kushkestani. Writing—original draft: Mahsa Moghadassi, Atiyeh Abassi. Writing—review & editing: Mehdi Kushkestani, Mahsa Moghadassi.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Funding Statement





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Table 1.

Demographical and physiological indices of subjects

Variables Value (n = 119)
Age (yr) 74.17 ± 8.67
 60–69 yrs 40 (33.61)
 70–79 yrs 44 (36.97)
 80> yrs 35 (29.42)
Height (cm) 154.75 ± 10.53
Weight (kg) 62.03 ± 13.23
BMI (kg/m2) 23.94 ± 3.26
 Underweight 8 (6.72)
 Normal 42 (35.29)
 Overweight 49 (41.18)
 Obese 20 (16.81)
 (Female ≥0.85) 0.89 ± 0.08
 Normal 26 (30.23)
 Obese 60 (69.77)
 (Male ≥0.95) 0.93 ± 0.06
 Normal 22 (66.67)
 Obese 11 (33.33)
Physical activity (PASE score) 37.85 ± 49.16
 Low 80 (67.23)
 Moderate 28 (23.53)
 High 11 (9.24)
Sleep quality (PSQI) 7.48 ± 3.40
 Low 95 (79.83)
 Normal 24 (20.17)
SBP (mm Hg) 135.22 ± 24.36
 Normal 34 (28.57)
 Elevated 17 (14.29)
 Stage 1 22 (18.49)
 Stage 2 46 (38.65)
DBP (mm Hg) 82.59 ± 14.72
 Normal 46 (38.66)
 Stage 1 36 (30.25)
 Stage 2 37 (31.09)

Values are presented as n (%) or mean ± standard deviation.

BMI, body mass index; WHR, waist-to-hip ratio; PASE, Physical Activity Scale for the Elderly; PSQI, Pittsburgh Sleep Quality Index; SBP, systolic blood pressure; DBP, diastolic blood pressure.

Table 2.

Sleep quality’s subscale (PSQI) rate in the subjects (n = 119)

PSQI score
0 1 2 3
Subjective 18 (15.1) 65 (54.6) 25 (21.0) 11 (9.2)
Latency 30 (25.2) 17 (14.3) 34 (28.6) 38 (31.9)
Duration 88 (73.9) 12 (10.1) 12 (10.1) 7 (5.9)
Efficiency 95 (79.8) 20 (16.8) 4 (3.4) 0 (0)
Disturbance 22 (18.5) 75 (63.0) 19 (16.0) 3 (2.5)
Medication 33 (27.7) 6 (5.0) 15 (12.6) 65 (54.6)
Dysfunction 51 (42.9) 35 (29.4) 27 (22.7) 6 (5.0)

Values are presented as n (%).

PSQI, Pittsburgh Sleep Quality Index.

Table 3.

The differences in sleep quality’s subscale (PSQI) between active and inactive elderly

Variables Pysical activity
Inactive (n = 40) Active (n = 40)
Subjective 1.60 ± 0.81 0.88 ± 0.76 <0.001**
Latency 2.18 ± 1.01 0.95 ± 1.09 <0.001**
Duration 0.30 ± 0.79 0.53 ± 0.91 0.133
Efficiency 0.23 ± 0.53 0.28 ± 0.56 0.599
Disturbance 1.20 ± 0.52 0.80 ± 0.82 0.002**
Medication 1.90 ± 1.39 2.00 ± 1.22 0.958
Disturbance 0.88 ± 0.85 0.68 ± 0.89 0.214

Values are presented as mean ± standard deviation.


p < 0.01, statistically significant;

Inactive group: lower 33% of PASE score (0.74 ± 1.2); Active group: upper 33% of PASE score (54.43 ± 8.6).

PSQI, Pittsburgh Sleep Quality Index; PASE, Physical Activity Scale for the Elderly.

Table 4.

The associations between physiological and physical activity levels with sleep quality and its subunits

SQ score Subjective Latency Duration Efficiency Disturbance Medication Dysfunction
 r 0.272** 0.218* 0.321** 0.037 0.025 0.214* -0.058 0.204*
 p-value 0.003 0.017 0.001 0.692 0.786 0.020 0.529 0.026
 r 0.041 0.051 0.075 0.056 0.147 0.045 0.031 -0.107
 p-value 0.657 0.579 0.418 0.547 0.111 0.628 0.734 0.246
 r -0.047 0.090 -0.054 0.032 0.114 -0.012 0.035 0.120
 p-value 0.609 0.328 0.560 0.733 0.217 0.899 0.706 0.195
Educational status
 r -0.114 -0.237** -0.159 0.163 -0.020 -0.147 0.055 -0.114
 p-value 0.217 0.009 0.084 0.077 0.831 0.110 0.551 0.217
 r -0.114 -0.133 -0.046 0.031 0.046 -0.103 -0.153 -0.089
 p-value 0.219 0.150 0.619 0.736 0.619 0.266 0.097 0.338
 r -0.135 -0.207* -0.136 0.023 0.019 0.026 0.032 -0.092
 p-value 0.144 0.024 0.140 0.807 0.838 0.783 0.733 0.321
PASE score
 r -0.274** 0.396** -0.468** 0.175 0.054 -0.267** 0.032 -0.116
 p-value 0.003 0.001 0.001 0.057 0.560 0.003 0.733 0.211

p < 0.05;


p < 0.01; statistically significant.

SQ, sleep quality; WHR, waist-to-hip ratio; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; PASE, Physical Activity Scale for Elderly.

Table 5.

Differences between general, physiological, and sleep quality subunits between normal and poor sleep quality groups

Variables Normal sleep quality (PSQI ≥ 5) Poor sleep qulaity (PSQI < 5) p-value
Age (yr) 75.37 ± 8.35 69.42 ± 8.42 0.002**
Height (cm) 154.40 ± 10.43 156.13 ± 11.04 0.476
Weight (kg) 61.59 ± 12.89 63.78 ± 14.66 0.472
WHR 0.902 ± 0.078 0.909 ± 0.068 0.693
BMI (kg/m2) 26.60 ± 6.14 27.70 ± 7.45 0.455
Education levela) 1.43 ± 1.12 1.58 ± 1.02 0.546
SBP (mm Hg) 133.38 ± 24.14 142.50 ± 24.34 0.101
DBP (mm Hg) 81.29 ± 14.25 87.71 ± 15.74 0.056
PASE score 31.13 ± 44.33 64.44 ± 58.67 0.014*

Values are presented as mean ± standard deviation.


p < 0.05;


p < 0.01; statistically significant;


Education level: 1, illiterate; 2, primary school; 3, high school; and 4, university.

PSQI, Pittsburgh Sleep Quality Index; WHR, waist-to-hip ratio; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; PASE, Physical Activity Scale for the Elderly.