Prevalence of excessive daytime sleepiness (EDS) and its association with quality of life in patients with obstructive sleep apnea (OSA): data from a sleep-center in Shenzhen, a single-center cross-sectional study

Introduction

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder affecting approximately 1 billion adults aged 30–69 years worldwide (1). Excessive daytime sleepiness (EDS) is the primary symptom and main complaint of patients with OSA (2,3), and approximately 20–50% of patients with OSA have reported EDS (4,5). Study has shown that 176 million people in China have OSA, ranking first in the world in terms of OSA prevalence (1). In addition, the prevalence of EDS in patients with OSA ranges from 34% to 55.9% (6-9), suggesting that China has many patients with EDS (approximately 59–98 million). EDS can have a negative impact on functioning, work productivity, mood, cognition, and quality of life (3). For example, patients with OSA presenting with EDS had increased comorbidities (depression, insomnia, and post-traumatic stress disorder), impaired health status, more work impairment and driving impairment (2,10-12). Therefore, addressing EDS in patients with OSA is crucial for improving their overall health and well-being.

Notably, many studies have focused on the overall impact of OSA, whereas only a few have explored the impact of EDS on the quality of life of patients with OSA. The impact of EDS on the quality of life of patients with OSA has been investigated in some studies in European and American countries (2,10-12). However, there are a few limitations to the existing research in this field. In a cohort study conducted in the United States, an online survey that relied on patients to provide subjective data, which may have limited reliability, was used; however, EDS severity was not assessed (2). In a retrospective observational study conducted in the European Union 5, the effect of EDS severity on the quality of life of OSA was analyzed; however, the overall quality of life of patients with or without EDS was not compared (10). A cross-sectional study in Australia included only an older population (11). The impact of OSA on the quality of life could not be determined using the US National Health and Wellness Survey because it lacked a grading of OSA severity (12). However, these studies involved European and American populations, and no data on Chinese populations exist. Considering that there are significant differences in obesity rate and craniofacial structure between the European and American populations and the Chinese population (13,14), which may have an impact on the clinical characteristics of OSA (15), the OSA-related study in the Chinese population is strongly needed.

To date, studies on the impact and burden of EDS in patients with OSA have been very limited, and most previous studies have focused on methods for predicting OSA and the impact of OSA on the quality of life rather than on OSA-related EDS problems (12,16,17). Therefore, it is necessary to explore the EDS-related epidemiological characteristics and the impact of EDS on the quality of life of Chinese patients. With the increasing urgency for the diagnosis and treatment of OSA, it is necessary to determine the impact of EDS on the quality of life of Chinese patients with OSA. In the present cross-sectional study, we aimed to explore the prevalence of EDS and its association with quality of life among patients with OSA at the sleep center of Shenzhen People’s Hospital. In addition, we aimed to achieve a better understanding of the impact of pathological sleepiness on health and well-being and provide a scientific basis for public health policymaking. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1322/rc).

Methods

Study population

In this cross-sectional study, we enrolled patients diagnosed with OSA at Shenzhen People’s Hospital in China between May 21, 2023 and November 30, 2023. The inclusion criteria were: (I) age of >18 years; (II) adherence to the criteria of the Third Edition of the International Classification of Sleep Disorders (ICSD-3); and (III) completion of the electronic questionnaire. Patients with serious medical or mental illnesses (except OSA) that affected their sleep or quality of life were excluded. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of Shenzhen People’s Hospital (LL-KY-2023079-02). Informed consent was taken from all individuals.

Data collection

A pre-designed electronic self-assessment survey was used to collect information on demographics (sex, age, occupation, height, weight, and race/ethnicity), comorbidities, OSA diagnosis, and treatment history. Patient-reported outcomes and health-related quality of life (HRQoL) outcome measures, including Epworth Sleepiness Scale (ESS) (18), Functional Outcomes of Sleep Questionnaire Short Version (FOSQ-10) (19), Work Productivity and Activity Impairment Questionnaire: Specific Health Problem Questionnaire (WPAI:SHP; V2.0) (2), World Health Organization Quality of Life-Brief (WHOQOL-BREF) Scale (20), Hospital Anxiety and Depression Scale (HADS) (21), and self-made driving questionnaire were used to evaluate the quality of life of patients. The Chinese versions of all scales have previously been tested for reliability and validity (22-25). All the scales were authorized, and administered as electronic questionnaires. To ensure quality and consistency, all score grading was performed by trained physicians or full-time investigators.

Regarding the ESS, participants were asked to rate their likelihood of falling asleep in various situations, with higher scores indicating greater severity of sleepiness. The FOSQ-10 is an important index for evaluating patients’ functional outcomes and can be used to reflect the impact of EDS on various activities of daily life. Higher scores indicated better daily functioning. The WHOQOL-BREF consists of 26 items and four domains: physical, psychological, social, and environmental. In WPAI: SHP, four outcomes are graded, including (I) work time missed due to problem “sleep disorder”; (II) impairment while working due to problem “sleep disorder”; (III) overall work impairment due to problem “sleep disorder”; (IV) activity impairment due to problem “sleep disorder”. Scores were presented as percentages, with higher numbers indicating worse outcomes. Patients who had driven within the past 6 months were asked to answer the driving questionnaire, which included questions on whether they had “a motor vehicle accident due to falling asleep while driving” or “a near miss while driving due to falling asleep” and how many times they had “dozed off at the wheel while driving”. The HADS is used to screen for anxiety and depression. Higher scores indicated greater anxiety and depressive symptoms.

Outcomes

Data on the prevalence, baseline characteristics, and treatments of EDS in patients with OSA were collected and evaluated. OSA severity was determined using the apnea-hypopnea index (AHI) (26). The absence of OSA, mild OSA, moderate OSA, and severe OSA were defined as AHI <5, 5≤ AHI <15, 15≤ AHI <30, and AHI ≥30, respectively. By current criteria, OSA is defined by the number of respiratory events per hour on sleep testing. Patients with an AHI of only 5 or more can meet diagnostic criteria if they also have supportive symptoms or medical conditions associated with OSA, like snoring, witnessed apneas, fatigue, somnolence, mood/cognitive disorder, hypertension, type 2 diabetes, stroke or cardiac disease. Sleep disorders are defined in seven major categories according to ICSD-3, including insomnia disorders, sleep-related breathing disorders, central disorders of hypersomnolence, circadian rhythm sleep-wake disorders, sleep-related movement disorders, parasomnias, and other sleep disorders (27). The ESS rates each person individually from 0 to 3 in eight distinct daytime scenarios to determine the overall degree of daytime sleepiness. The scores were defined as follows: 0= would never nod off, 1= slight chance of nodding off, 2= moderate chance of nodding off, and 3= high chance of nodding off. Patients with ESS score ≥10 were considered to have EDS (5,6,28-31). Patients with EDS were further divided into mild (ESS: 10–12), moderate (ESS: 13–15) and severe (ESS ≥16) categories. The prevalence of EDS was defined as the proportion of patients with OSA presenting with EDS. The correlation between the EDS scores and quality of life was also explored.

Statistical analysis

Data analysis was performed using R Studio (version 4.3.1) and SPSS (version 25.0). For continuous data, normality was assessed using the Shapiro-Wilk method. Normally distributed data were presented as mean ± standard deviation, whereas non-normally distributed data were presented as medians (interquartile range). The independent sample t-test, nonparametric Mann-Whitney U test, or Kruskal-Wallis test was used to compare quantitative data between groups. Categorical data were presented as percentages (%) and frequencies and were compared using the Chi-squared or Fisher’s exact test. The Clopper-Pearson method was used to estimate the prevalence of EDS and its exact 95% confidence intervals (CIs).

The correlation coefficient (r) was calculated using Spearman’s correlation, Pearson’s correlation, Kendall’s tau-b, and point-biserial correlation. Furthermore, we examined the associations of EDS (ESS ≥10) with motor vehicle driving accidents, quality of life, and functional outcomes using logistic regression models. Model 1 showed the results for each variable separately, unadjusted for other factors. Model 2 was adjusted for sex, age, alcohol consumption, and sleep disorders (all of which are associated with OSA severity and symptoms) (32). Unless otherwise stated, missing values were not considered in the percentage calculations. All statistical tests were bilateral tests, and statistical significance was set at P<0.05.

Results

Baseline demographic and clinical characteristics of patients with OSA with and without EDS

A total of 334 patients with OSA were enrolled in this study, including 283 males (84.7%), with an average age and body mass index (BMI) of 38.1±8.6 years and 28.3±8.1 kg/m², respectively. Notably, most patients [323 (96.7%)] were of the Han nationality. A total of 295 (88.3%) patients were paid workers, and most [307 (91.9%)] did not work shifts. Furthermore, over half of the patients [213 (63.8%)] had sleep disorders, of which 189 (88.7%) had sleep disordered breathing. Seventy (21.0%) patients had a history of OSA treatment, and 25 of 38 patients who had been treated with continuous positive airway pressure (CPAP) had discontinued the treatment. The baseline characteristics are presented in Table 1.

Among the 334 patients, 104 were classified as having EDS (ESS ≥10), whereas 230 were classified as not having EDS (ESS <10). Patients in the EDS group were younger (36.4 vs. 38.9 years, P=0.02). The two groups were similar in sex (P=0.34), BMI (P=0.99), race/ethnicity (P=0.75), occupation (P>0.99), shift work (P=0.86), alcohol consumption (P=0.95), and history of OSA treatment (P=0.13) (Table 1). Patients with EDS had more sleep disorders than those without EDS (75.0% vs. 58.7%, P=0.004), whereas both patient groups had similar prevalence of other comorbidities. Parents of patients with EDS consistently went to bed later than expected (18.3% vs. 8.3%, P=0.008).

Quality of life and functional outcomes of patients with OSA presenting with EDS according to EDS status

Patients with EDS had lower FOSQ-10 and WHOQOL-BREF scores but higher WPAI:SHP and HADS scores than those without EDS (P<0.05). Furthermore, patients with EDS had more motor vehicle accidents within the past 6 months than those without EDS, and the higher occurrence of motor vehicle accidents among patients with EDS was due to falling asleep while driving (7 vs. 2, P=0.001) and drowsiness while driving (51 vs. 45, P<0.001). Overall, patients with OSA presenting with EDS had a worse quality of life than those without EDS (Table 2).

Among the 104 patients with OSA presenting with EDS, 42, 35, and 27 had mild, moderate, and severe EDS, respectively (Table 2). There was a significant difference in the FOSQ-10 scores among the three groups (P=0.03), and patients with moderate and severe EDS had lower scores, indicating poor activities of daily living. Similarly, patients with severe EDS had lower WHOQOL-BREF scores in the physical domain (P=0.02) and environmental domain (P=0.03), indicating more barriers in the physical and environmental domains. In addition, there were differences in absenteeism (P=0.01), presenteeism (P=0.03), and work productivity impairment (P=0.005) according to WPAI:SHP scores among the three groups, and patients with severe EDS had worse work performance. Regarding the occurrence of motor vehicle accidents within the past 6 months, patients with severe EDS were more likely to doze off while driving (P=0.04) and have a near-accident experience due to falling asleep (P=0.02). Generally, there were differences in some quality of life indicators among patients with different categories of EDS, and patients with severe EDS showed poor quality of life.

The prevalence of EDS among patients with OSA

Among the 334 patients, the prevalence of EDS was 31.1% (95% CI: 26.2–36.4%). A subgroup analysis was performed to explore the prevalence of EDS among patients with OSA based on different age groups and grades. There were no significant differences in the prevalence of EDS among the different age groups (P=0.17) or OSA grades (P=0.08) (Table 3 and Figure 1).

Figure 1 The prevalence of EDS among patients with OSA. EDS, excessive daytime sleepiness; OSA, obstructive sleep apnea; CI, confidence interval.

Correlation analysis between EDS and variables of interest

Correlation analysis showed that EDS was significantly associated with sex (P=0.03), age (P=0.002), sleep disorders (P<0.001), and high-risk motor vehicle accidents (P≤0.001). In addition, EDS was associated with worse sleep function (as indicated by FOSQ-10 scores) (r=−0.32, P<0.001), worse quality of life (as indicated by WHOQOL-BREF scores) (P<0.01), and more severe work impairment (as indicated by WPAI:SHP scores) (P<0.01), anxiety (r=0.22, P<0.001), and depression (r=0.20, P<0.001) (Table 4). A heat map of the correlation coefficients between EDS and the variables of interest is shown in Figure 2.

Figure 2 Heat map of the correlation coefficients between EDS and variables of interest. The circle size corresponded to the absolute value of the correlation coefficient, with red (blue) color indicating a positive (negative) correlation. EDS, excessive daytime sleepiness; FOSQ-10, Functional Outcomes of Sleep Questionnaire Short Version; WHOQOL, World Health Organization Quality of Life; WPAI, Work Productivity and Activity Impairment Questionnaire; HADS, Hospital Anxiety and Depression Scale.

Association of EDS with quality of life and functional outcomes

Logistic regression models were used to estimate the associations between EDS and motor vehicle accidents, functional outcomes, and quality of life (Table 5). After adjusting for factors such as sex, age, alcohol consumption, and sleep disorders, motor vehicle accidents were found to be associated with a higher prevalence of EDS. Regarding the functional outcome index, for every 1-point increase in the FOSQ-10 score, the likelihood of developing EDS decreased by 11%. The primary quality of life outcome indicators included WHOQOL-BREF, WPAI:SHP, and HADS scores. Lower WHOQOL-BREF scores in physical [odds ratio (OR): 0.83, 95% CI: 0.75–0.92], psychological (OR: 0.90, 95% CI: 0.82–0.99), and social (OR: 0.88, 95% CI: 0.79–0.98) domains were associated with higher prevalence of EDS. EDS was significantly associated with the percentage scores of WPAI: SHP for presentation (OR: 1.03, 95% CI: 1.02–1.04), work productivity impairment (OR: 1.02, 95% CI: 1.01–1.03), and activity impairment (OR: 1.03, 95% CI: 1.02–1.04) but not absenteeism. In addition, the HADS scores for anxiety (OR: 1.08, 95% CI: 1.01–1.17) and depression (OR: 1.09, 95% CI: 1.01–1.17) were associated with a higher prevalence of EDS.

Discussion

The present study is the first to investigate the impact of OSA-related EDS on the quality of life of Chinese patients. In this study, we primarily aimed to assess the prevalence of EDS and its association with quality of life among patients with OSA using a cross-sectional study with real-world data from the Shenzhen People’s Hospital. In the present study, the prevalence of EDS among patients with OSA was 31.1%. Age, sex, and sleep disorders may influence EDS in patients with OSA. In addition, patients with OSA presenting with EDS had worse functional status (as indicated by FOSQ-10 scores), more severe work impairment (as indicated by WPAI:SHP scores), worse quality of life and general health (as indicated by WHOQOL-BREF scores), more severe anxiety and depression (as indicated by HADS scores), and more severe driving impairment. Furthermore, patients with severe EDS had a worse quality of life than those with mild EDS. The findings of the present study contribute to further understanding of the impact of OSA-related EDS on the quality of life of Chinese patients and provide valuable information for evaluating prevention and control measures.

The present study showed that EDS greatly affected the quality of life of patients with OSA patients, as evidenced by a more severe driving impairment in patients with OSA presenting with EDS than in those without EDS. In an Australian study, EDS increased the risk of motor vehicle accidents, regardless of OSA severity (33). In addition to driving problems, OSA-related EDS can place tremendous physical and mental burdens on patients, affecting their functioning, emotions, work efficiency, quality of life, and interpersonal relationships (34,35). In particular, EDS has been significantly associated with more severe work and activity impairments (2). Similar results were observed in the present study. EDS severity was strongly correlated with FOSQ-10, WHOQOL-BREF (physical health domain, psychological domain, and social relationships), WPAI:SHP (attendance, work efficiency, and activity impairments), and HADS (anxiety and depression), even after adjusting for sex, age, alcohol consumption, and sleep disorders. We also found that EDS severity was correlated with quality of life, consistent with the findings of a cross-sectional study in Turkey and the European Union 5 (10,20). These results indicate the importance of EDS as a contributor to poor quality of life, work impairment, and risk of motor vehicle accidents in patients with OSA.

As mentioned earlier, the prevalence of EDS among patients with OSA was 31.1% in the present study, consistent with findings of an online study in the United States and a large-sample study in China (2,6). The results of the present study showed a significant correlation of EDS with age and sex, which is in line with the findings of previous studies (11,36). However, the prevalence of EDS did not vary significantly across the various age groups in the present study due to the sample consisted mainly of middle-aged patients. The study on American and the Saudi population also showed no difference in the prevalence of EDS among different age groups (2,37). The results of the present study showed that the prevalence of EDS was slightly higher among young patients than among middle-aged patients. The lack of statistical significance may be due to the uneven distribution of patients across age groups, with fewer patients aged >55 years, which may be due to the younger urban population in Shenzhen. In particular, the prevalence of EDS was 100% among patients aged >65 years, which was not of reference significance since only one person was included in the population. Exploring the relationship between EDS prevalence and age requires additional research in the future. Furthermore, several reports have also indicated a higher incidence of EDS in males than in females (11). However, contrary reports exist on the relationship between EDS and sex and indicate a higher incidence of EDS in females (38,39), possibly due to a combination of other factors, such as hours of sleep per night and the lifestyle of both sexes.

The results of the present study clearly indicated no association between the prevalence of EDS and OSA severity, consistent with the results of studies showing a lack of significant contribution of OSA severity indices to the prevalence of EDS (40,41). Clinically, some patients with mild OSA experience severe sleepiness, whereas some with severe OSA do not (42). Notably, different reports have indicated an association between EDS and OSA severity and a higher prevalence of EDS among patients with severe OSA (42,43). However, the correlation between EDS and OSA severity remains inconclusive and may be influenced by confounding factors in different studies. Compared with previous study in the United States (2), the present study included more patients with newly diagnosed OSA. Only 38 patients had a history of CPAP treatment, of whom 25 had discontinued it; therefore, the sample size was too small to further analyze the influence of CPAP adherence on EDS.

By grading EDS, we found that improving EDS severity by one tier may significantly affect an individual’s quality of life. Previous studies have shown that HRQoL deteriorates with increasing EDS severity, which significantly affects HRQoL, as assessed using EQ-5D utility scores (44,45). These results highlight the importance of the state characteristics of EDS severity and the treatment and management of OSA-related EDS. Therefore, it is important to know the extent of change in the ESS score that is required to demonstrate a clinically meaningful improvement. A clinical trial evaluating the association between wake-promoting drugs and ESS showed that a 25% decrease in ESS score from baseline may be the optimal threshold for identifying patients with narcolepsy demonstrating clinical significance for treatment (46). An analysis of subgroups adherent or non-adherent to OSA treatment suggested that ESS scores reduced by 4.3–8.9 points from baseline scores after taking wake-promoting drugs, which was considered a clinically meaningful change (47). An American Academy of Sleep Medicine systematic review indicated that a 2-point reduction in ESS score is clinically significant (48). These data can provide the necessary information for patients, healthcare workers, and public policy.

The findings of the present study suggest that the Chinese public and related policies should pay more attention to EDS in patients with OSA. Notably, CPAP, which is the primary treatment method for OSA, but is also limited by suboptimal adherence (49). In addition, there is a lack of alternative treatments for OSA-related EDS, such as scarce novel wake-promoting drugs, and a lack of experience in the pharmacological treatment of EDS (50). The present study showed that EDS seriously affects the quality of life, which needs to be addressed, and we expect the public and policymakers to focus on improving treatment options and developing more individualized treatment of OSA-related EDS.

Anatomical factors are key risk factors for OSA, obesity and abnormal craniofacial morphology can cause upper airway stenosis to various degrees. It is noteworthy that the relative importance of these factors to OSA risk may vary between ethnicities (13,14,51,52). The prevalence of OSA in the European and American populations is greatly affected by obesity, while in Chinese population, it is greatly affected by craniofacial structure (13,14). Therefore, it is necessary to conduct a study in the Chinese population to analyze the prevalence of EDS and its association with quality of life in patients with OSA.

In the present study, we evaluated the prevalence of EDS and its association with quality of life among patients with OSA in China, thus addressing a knowledge gap in the existing literature. In addition, the sample size of this study was relatively large, and the dimensions of quality of life assessment were comprehensive. However, there are some limitations in this study. First, this was a single-center study with samples from the sleep center of Shenzhen People’s Hospital, which may not be representative of the entire Chinese population. The data collection time was short (6 months). Second, the included patients were younger, with most being newly diagnosed, and the influence of CPAP adherence on EDS could not be analyzed owing to fewer patients using CPAP. Third, although the ESS is a common tool for assessing EDS, it is subjective. Objective tools such as the maintenance of wakefulness test may be required to further assess EDS and analyze the relevance of polysomnography data to EDS and quality of life. Despite these limitations, this study is the first to assess EDS in patients with OSA in China. In addition, this study used several proven quality-of-life tools and corrected for confounding factors that influenced the risk of EDS. In the future, there is a need to expand the sample of respondents, conduct multicenter research, and further validate our results using cohort studies.

Conclusions

This single-center cross-sectional study is the first to examine the impact of OSA-related EDS on the quality of life in patients from a sleep center in Shenzhen. The results of this study showed a high prevalence of EDS among patients with OSA, and EDS, especially severe EDS, was correlated with a worse quality of life, worse functional status, and more severe driving impairment.

Acknowledgments

Funding: This work was supported by the Shenzhen Science and Technology Program (Nos. JCYJ20210324113612032, JCYJ20220530152414032, and JCYJ20210324142207019), the Science and Technology Development Special Fund of Shenzhen Longgang District (No. LGKCYLWS2022014).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1322/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1322/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1322/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1322/coif). W.Z. and H.Y. are current employees of Ignis Therapeutics. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of Shenzhen People’s Hospital (LL-KY-2023079-02). Informed consent was taken from all individuals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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