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Behavioral Factors Related to Sleep Quality and Duration in Adults

Background The purpose of this study was to measure the sleep quality and duration in healthy adults and to identify any influencing factors. Methods This study was a descriptive research investigation that evaluated 240 healthy adults at least 19 years of age. The data were assessed using the following self-administered questionnaires: the Pittsburgh Sleep Quality Index (PSQI), the Beck Depression Inventory, the State-Trait Anxiety Inventory-Korean YZ, and the Fatigue Severity Scale. Results The PSQI global score was 5.69 ± 3.23, and 59.6% of the participants were classified as having poor quality sleep (PSQI score > 5). The significant risk factors for poor sleep quality were female gender (p = 0.021), number of comorbid conditions (p = 0.003), depression (p < 0.001), fatigue (p < 0.001), and anxiety (p < 0.001). Stepwise multiple regression analyses showed that significant predictors of poor sleep quality were depression (p < 0.001) and fatigue (p < 0.001). Participants slept an average of 6.16 ± 1.36 hours a night. A shorter sleep duration was correlated with older age (p = 0.010), a higher body mass index (BMI) (p = 0.026), a greater depression score (p = 0.002), a higher fatigue score (p = 0.028), and lower sleep quality (p < 0.001). In addition, stepwise multiple regression analyses revealed that factors significantly associated with sleep duration were depression (p = 0.002) and BMI (p = 0.034). Conclusion The number of comorbid conditions and the presence of depression and fatigue were risk factors for both low sleep quality and short sleep duration. Therefore, to improve sleep quality, there is a need for comprehensive interventional programs to manage these and any other factors that disturb sleep.


INTRODUCTION
The Korean National Health Insurance Service reported that the number of patients who have received medical care for sleep disturbances increased from 358,000 in 2010 to 414,000 in 2014, representing a 15.8% rise over this four-year period and an annual increase of 7.6%. In addition, the number of patients per 100,000 who have received medical treatment for sleep problems has increased by 6.4% and is steadily rising [1]. Due to this stable increase in the number of sleep-disturbed patients [2], two of modern society's major health issues are sleep problems and sleep deprivation in adults. Sleep quality includes quantitative aspects, such as the total sleep time, sleep latency, awakening frequency, and subjective and qualitative aspects. People who experience sleep problems are also likely to have poor sleep

Journal of
Lifestyle Medicine quality, which may be an important symptom of medical problems; therefore, more attention should be given to patients' sleep quality [3]. Poor sleep quality has additionally been linked to increased medical expenses, work disturbances and an elevated risk for psychiatric disorders [4]; it has a negative effect on general health and also on quality of life [2].
Sleep takes up a great portion of everyday life as well as time during the human lifespan [5]. A recent study has identified that the average number of hours Korean adults 19 years of age and older spent sleeping was 6 h 53 min [6] per day, which decreased from 7 h 49 min in the 2009 data and was ranked the lowest among all Organization for Economic Cooperation and Development (OECD) countries [5]. One's optimal sleep duration differs depending on the social context and also one's personal characteristics [7].
However, inadequate sleep duration results in daytime sleepiness, fatigue, decreased concentration, irritable behaviors, and anger; prolonged sleep deprivation is linked to cardiovascular diseases and psychiatric disorders [7]. Nurses are in an optimal position to assess and evaluate patients' individual sleep quality and the factors affecting their sleep and also to apply interventions to promote better sleep.
Promoting qualitative sleep has been considered one of the most important nursing care goals since the Nightingale era [8]; therefore, more attention and research should be carried out to resolve sleep disturbances.
Sleep studies have been conducted in a patient population considered likely to develop sleep problems, such as stroke patients [9], chronic epilepsy patients [10], female cancer patients [11], patients with other specific medical conditions, and older adults [12][13][14][15]. However, few sleep studies have focused on healthy adults, which would prove useful in comparisons with specific patient populations because the comparison would determine the degree of sleep disturbances in these specific populations. Therefore, a sleep study on healthy, community-dwelling adults should be a valuable reference.
It is a common issue in modern society to experience short total sleep hours [16], and this problem has drawn attention to the physical, psychological and behavioral problems that are associated with short sleep hours. Several previous studies have identified an association between the amount of sleep and cardiovascular diseases, stroke, coronary calcification, and inflammatory marker changes [17]. Additionally, inadequate sleep is linked to an increased body mass index (BMI), changes in the hormonal levels that regulate hunger, a higher incidence of insulin resistance due to problems with glucose metabolism [16], an elevated risk of diabetes, daytime behavior disorders, and increased mortality [17].

Study design
This study was a descriptive, cross-sectional study conducted to understand the sleep quality and sleep duration of healthy adults and to identify related factors.

Participants
Healthy adults over the age of 19 who visited an electroencephalogram center located in Seoul, Korea, were chosen to participate in this study. Inclusion criteria were as follows: 1) Those who understood the study purpose and had consented to study participation.
2) Those who were able to comprehend and respond to questionnaires with no communication disabilities.
3) Those with no history of psychiatric problems who were able to answer the survey questions.
Sample size was calculated using the G*Power 3.

1) General characteristics
Age, gender, educational level, job status, BMI, comorbidity, depression, fatigue, and anxiety were investigated to determine participant general characteristics.

2) Sleep quality
The Pittsburgh Sleep Quality Index (PSQI) was developed by Buysse et al. [3] and is a self-report assessment tool that

3) Depression
The Beck Depression Inventory (BDI) was developed by Beck et al. [19] and translated by Lee and Song [20]; this questionnaire was used to assess the depression level of each participant. The BDI is a self-report tool that contains 21 questions. Each question is scored on a scale from 0-3 with the total score ranging from 0-63; a higher score denotes a more severe level of depression. Scores are grouped as fol-

4) Anxiety
The translated version of the Spielberger State-Trait Anxiety Inventory (STAI-Y) [21], which is called the State-Trait Anxiety Inventory-Korean YZ (STAI-KYZ, translated by Hahn et al.) [22], was used to assess anxiety.

5) Fatigue
The Fatigue Severity Scale (FSS) was developed by Krupp et al. [23] and is a self-reporting tool with nine items scored on a Likert scale from 1-7. The mean of all scores is considered to be the final score, and a higher score de-

Ethical considerations
Data collection for the current study took place after approval from the Institutional Review Board of Seoul National University (IRB No. 2013-93). The study's pur-pose, method and efforts for protection of privacy were explained to each participant, and the data were collected from those who provided signed informed consent.

Data analysis
The collected data were analyzed using the Statistical Package for the Social Sciences (SPSS), version 23.0, as follows: 1) The frequency, percentage, mean, and standard deviation were calculated using the participants' general characteristics, sleep quality and sleep duration time.
2) Differences in sleep quality, sleep duration and the sub items of sleep quality according to the general characteristics were analyzed with an independent t-test and a one-way analysis of variance (ANOVA). After using a Levene verification of equal variance, the data were analyzed with both a one-way ANOVA and Bonferroni post-hoc comparisons.

3) Correlations between variables were analyzed using
Pearson's correlation.

4) A multiple linear regression model was used to analyze
sleep quality and its predictors.
5) The reliability of the tools used to measure depression, fatigue and anxiety were analyzed with Cronbach's α.
6) The default significance level was set as p ＜ 0.05.

General characteristics
The

Correlations between sleep and different variables
The correlations between different variables and sleep quality and sleep duration are shown in Table 3. Higher scores for age, BMI, depression, and fatigue were correlated with shorter sleep duration.

Sleep-influencing factors
Stepwise multiple regression analyses were used to determine the factors that influence sleep quality and sleep duration. The Durbin-Watson autocorrelation score was 2.045, indicating independence. In addition, the VIF score between independent variables was 1.095, indicating a lack of multicollinearity.
Among factors that were found to be related to sleep, depression and fatigue had a significant influence on sleep quality (p ＜ 0.001). Higher depression (p ＜ 0.001) and fatigue scores (p ＜ 0.001) resulted in a low sleep quality score with a model description power of (R 2 ) = 0.29 (Table 4).

DISCUSSION
This study aimed to investigate the sleep quality and sleep duration of healthy adults and to assess any influencing factors to provide a basis for nursing intervention development to increase patients' sleep quality. The average sleep quality score was 5.69 ± 3.23, which was similar to a previous study's report of 5.7 ± 2.79 [24]. Our study result showed a higher score compared to Sohn and Kim's [25] earlier investigation of the reliability and validity of the Korean PSQI (4.06 ± 2.08) and an Iranian study (5.06) [2].
However, our study respondents displayed a lower average sleep quality score than a previous study that compared healthy adults and obese adults in Korea (6.62 ± 2.45) [26] and another report on middle-aged adults in the United States (6.3 ± 3.4) [27]. These findings may indicate that sleep quality could be affected by various factors, such as ethnicity, geographical location, lifestyle, and culture. Therefore, researchers should consider the characteristics and environmental factors of participants when conducting sleep studies; further research that includes participants with diverse ethnic backgrounds is needed. More than half of our respondents (59.6%) had PSQI scores that were higher than the mid-point, as well as all age groups and the mean PSQI score, indicating poor sleep quality. In all age groups, the average sleep duration was 6.16 ± 1.36, suggesting that many did not exceed seven hours of sleep each night. In the age group ≤51 years, the total number of hours spent sleeping was less than six. In addition, the mean sleep duration of this study was even lower than the national results (6 h and 53 min and 7 and 49 min, respectively) [6]. Our study showed similar results as other previous studies [2,24,28] that women had a lower sleep quality than men. This trend may be due to several factors, including the psychiatric disorder incidence rate, sociocultural factors, gender differences in coping skills [2], menopause [28], bereavement [2], and other cultural lifestyle differences [2]. were similar to those of a previous Japanese study [18] and another study conducted in community-dwelling adults that showed a high incidence of sleep disorders in those with significant prior medical histories [28]. Ancoli-Israel [15] reported that physical and psychological problems, such as cardiovascular and pulmonary disorders, depression and arthritis, were correlated with sleep disturbances; a higher number of comorbid conditions was found to negatively affect sleep quality, and poor sleep quality may lead to an increased mortality rate. Choi and Kim [28] concluded that one of the major problems any patient with any medical condition experiences is disordered sleep and that medical staff members should devote special attention to this matter. Therefore, a careful assessment of sleep should be carried out in patients with medical conditions, and further sleep research on these various conditions should also be established.
Age was also significantly related to sleep duration.
Participants aged ≥51 years had the shortest sleep duration, and those in the 31-40-year-old group had the longest. The latter result was unexpected and may be due to a high (42.9%) proportion of the respondents in this age group being unemployed. Economically inactive people are more likely to have regular life patterns and may have longer sleep hours due to not having to wake up early for work and not experiencing work-related stress. Additionally, this finding could also be related to the low incidence of medical conditions in those in the ＜30 age group (79%) and the 31-40 age group (73%), which leads to fewer sleep disturbances. These medical conditions often cause pain and discomfort or require drugs with unpleasant side effects and can therefore interfere with sleep; the group with more comorbid conditions reported poorer sleep than those with no conditions. Our results also showed that participants older than 51 years had the shortest sleep duration, which was similar to a previous study's results.
Older adults residing in rural areas were more prone to experiencing sleep disturbances as they aged [28]; an Iranian study found that adults who lived in urban areas also had the same problem [2]. These disturbances are related to physiological changes that take place in elderly adults and involve relatively short non-rapid eye movement (NREM) periods [3], the deepest REM sleep stage, and frequently waking from sleep [29]. In addition, physical and psychological disorders and the pain associated with these disorders [12] may also be influencing factors. In this study, the mean BDI score in participants ≥ 60 years of age was 10.05 ± 9.84, indicating that depression may be the biggest risk factor that influences sleep duration. Further analyses indicated that 72.5% of respondents in their 50 s and 81.1% of those in their 60 s had more than one comorbid medical condition; 37.8% of participants older than 60 years reported three or more comorbid conditions, which may have influenced their sleep quality and duration. Therefore, further study should investigate these influencing factors according to various age groups, especially in the elderly population.
Correlation and regression analyses revealed that sleep quality was affected by depression and fatigue, while sleep duration was influenced by depression and BMI. Depression was the predisposing factor that had an effect on both sleep quality and duration, which was a similar to reports from the established literature. Previous studies have shown that depression is correlated with low sleep quality, and elderly patients with depression are more likely to have sleep disturbances than people without depression [12]. Many studies have found a strong correlation between depression and sleep problems, and sleep problems have been implicated to both cause and worsen depression [24]. Studies conducted in stroke victims [9], epilepsy patients [10] and female cancer patients [11] have all shown that depression affects sleep and suggested a careful assessment of depression along with any sleep assessment in these populations. Fatigue also influences sleep quality, which is in accordance with previous studies on epilepsy patients [10] and female cancer patients receiving chemotherapy [11].
Our study showed that a high BMI was related to short sleep duration. A study that compared healthy and obese adults reported that obese adults experienced more severe sleep problems and had shorter sleep duration than their healthy counterparts. A French study conducted in an elderly population also found a correlation between obesity and a shortened sleep duration [14]. Sleep deprivation has been linked to an increased intake of fat and carbohydrates and decreased physical activity, which led to obesity [26]. Short sleep hours decreased leptin and increased ghrelin levels, which resulted in an increased appetite and an elevated BMI [16]. In a meta-analysis of 696 BMI scores and sleep hours, short sleep hours were associated with an increased risk for obesity in both adults and children [30]. However, it was difficult to determine the causal relationship between obesity and sleep problems [30], suggesting the need for further evaluation.
This study investigated sleep quality and sleep duration as well as their influencing factors to provide evidence for optimizing sleep quality and also quality of life in general.
Our study results should encourage broad-spectrum studies that include various variables in different participants to promote better sleep quality and to prevent sleep deprivation. In addition, based on our study results, we sug-