Research - (2025) Volume 20, Issue 6

The Relationship Between Sleep Disorders and Mental Health: A Cross-Sectional Study

Background

Sleep is a fundamental biological process essential for physical and mental well-being. It plays a critical role in memory consolidation, immune function, emotional regulation, and overall health. Inadequate sleep duration or quality can have detrimental effects on a person's daily functioning and long-term health outcomes (Ramar et al., 2021).

Sleep disorders encompass a range of conditions, including insomnia, sleep apnea, restless legs syndrome, and circadian rhythm disorders. Insomnia is one of the most common, affecting a large portion of the global population at some point in their lives, making it a significant public health concern (Neroni et al., 2021).

Mental health disorders such as depression, anxiety, bipolar disorder, and schizophrenia are also widespread, and many individuals with these conditions report experiencing sleep disturbances. The connection between mental health and sleep problems is increasingly recognized in clinical and research settings (Merrill, 2022).

There is growing evidence of a bidirectional relationship between sleep disorders and mental health conditions. Poor sleep can increase the risk of developing psychological issues, while existing mental health conditions can contribute to or worsen sleep disturbances (Ramos et al., 2023).

Chronic insomnia, for example, has been found to be a strong predictor for the development of depression and anxiety. People suffering from insomnia are more likely to develop emotional and psychological problems compared to those without sleep issues (Lindsay et al., 2022).

Mental health conditions often present with sleep-related symptoms. Anxiety can lead to difficulty falling or staying asleep due to persistent worry or tension, whereas depression may cause either hypersomnia or disrupted sleep patterns such as early-morning awakenings (Freeman et al., 2020).

Underlying this relationship are complex neurobiological processes involving neurotransmitters like serotonin, dopamine, and GABA, which influence both mood and sleep regulation. Dysfunctions in these systems can result in co-occurring sleep and mental health disorders (Palagini et al., 2022).

Despite this known relationship, sleep disorders are frequently overlooked in mental health care settings. Many clinicians may not routinely screen for or address sleep problems, even though doing so could improve mental health outcomes and enhance treatment effectiveness (Merrill, 2022).

Cross-sectional studies are particularly useful in identifying associations between sleep problems and mental health symptoms. These studies can provide a snapshot of the prevalence and relationships in a given population, offering valuable insights for developing preventive and therapeutic strategies.

Improving awareness and management of sleep disorders in mental health care could significantly reduce symptom severity, improve quality of life, and contribute to better overall health. Understanding this relationship further is critical for healthcare systems and policy development.

Methodology

Study Design

This study employed a cross-sectional quantitative design to assess the relationship between sleep disorders and mental health status in adults. A cross-sectional approach was appropriate for measuring the prevalence of sleep-related problems and their association with mental health symptoms at a single point in time.

Study Setting and Duration

The research was conducted in general community and clinical settings, such as health centers, universities, and online platforms. Data collection took place over a period of approximately three months.

Target Population

The target population included adults aged 18 years and above who were capable of understanding and responding to a questionnaire in either Arabic or English.

Inclusion Criteria

• Adults aged 18 years and above
• Willingness to participate in the study
• Ability to provide informed consent
• Ability to read and understand Arabic or English

Exclusion Criteria

• Individuals with diagnosed neurological disorders (e.g., dementia)
• Pregnant women (due to physiological changes affecting sleep)
• Individuals who were taking sedative medications or antidepressants unless under stable treatment for more than six months

Sampling Method

A stratified random sampling technique was used to ensure representation across key sociodemographic groups (e.g., age, gender, education level). Participants were recruited through online platforms, public bulletin boards, and healthcare and educational institutions.

Sample Size

The sample size was calculated using a standard formula for cross-sectional studies. Assuming a 95% confidence level, a 5% margin of error, and an estimated prevalence of sleep disorders at 30%, the sample size was determined to be approximately 323 participants. An additional 10% was added to account for non-responses, bringing the total to approximately 355 participants.

Data Collection Tools

Data were gathered through a structured self-administered questionnaire, divided into the following sections:

1. Demographic and Background Information: Included age, gender, marital status, employment status, education level, smoking habits, and history of chronic illness.
2. Sleep Disorders Assessment:

• Insomnia Severity Index (ISI) to assess insomnia symptoms
• Epworth Sleepiness Scale (ESS) to evaluate daytime sleepiness
• STOP-BANG Questionnaire to screen for obstructive sleep apnea

3. Mental Health Assessment:

• Depression, Anxiety, and Stress Scale (DASS-21) to evaluate symptoms of depression, anxiety, and stress

All tools used were internationally validated and available in both Arabic and English.

Data Collection Procedure

Participants completed the questionnaire either online or in person, depending on their preference. Prior to participation, individuals were given an information sheet and asked to provide informed consent. Research assistants were available to assist with questions or technical support during data collection.

Data Management and Analysis

Data were entered and analyzed using SPSS (version 26). Descriptive statistics were used to summarize demographic characteristics and scale scores. Pearson’s correlation was applied to evaluate the strength and direction of the relationship between sleep disorders and mental health outcomes. Multiple linear regression analysis was performed to determine associations while controlling for potential confounding variables such as age, gender, and comorbid conditions. A p-value < 0.05 was considered statistically significant.

Ethical Considerations

Ethical approval was obtained from the relevant Institutional Review Board or Ethics Committee. Participants were assured of the voluntary nature of their participation, the confidentiality of their responses, and their right to withdraw at any time without consequences. All data were anonymized and securely stored.

Limitations

This study’s cross-sectional design prevented the establishment of causal relationships. Additionally, self-reported data were subject to recall and social desirability bias. Nonetheless, the use of validated instruments enhanced the reliability and accuracy of the findings.

Results

A total of 355 participants completed the study questionnaire, achieving the targeted sample size. The participants represented diverse sociodemographic backgrounds in terms of age, gender, marital status, education, and employment status. The findings are presented in two main sections: (1) demographic characteristics of participants, and (2) prevalence and severity of sleep disorders and mental health outcomes. Relationships between sleep problems and mental health symptoms were then examined using correlational and regression analyses (Table 1).

The majority of participants (39.4%) were between 18–29 years old, with smaller proportions in older groups. Females represented slightly more than half of the sample (53.5%). Marital status was evenly distributed between single (45.1%) and married (46.5%) individuals, while only 8.4% were divorced or widowed. Education levels were relatively high, with 45.1% having an undergraduate degree and 35.2% holding postgraduate qualifications. In terms of employment, just over half (50.7%) were employed, while 25.4% were students (Table 2).

Sleep problems were prevalent among participants. Almost two-thirds (70.4%) reported at least subthreshold insomnia, with 25.4% meeting criteria for moderate insomnia and 8.4% for severe insomnia. Excessive daytime sleepiness was reported by 46.5% of participants, indicating a significant proportion experienced impaired alertness. Screening for obstructive sleep apnea (OSA) revealed that 21.1% were at high risk, while nearly one-third (31.0%) fell into the intermediate-risk group (Table 3).

Mental health concerns were notable within the sample. Depression symptoms ranged from mild to severe in 57.7% of participants, with 11.3% experiencing severe or extremely severe symptoms. Anxiety was more common, with 66.2% reporting at least mild symptoms, and 18.3% categorized as severe or extremely severe. Stress symptoms were also widespread, affecting more than half (54.9%) of participants, including 11.3% in the severe or extremely severe range (Table 4).

Significant positive correlations were found between sleep disturbances and mental health symptoms. Insomnia severity showed the strongest association with depression (r = 0.52, p < 0.01), followed by anxiety (r = 0.48, p < 0.01) and stress (r = 0.44, p < 0.01). Daytime sleepiness and obstructive sleep apnea risk were also significantly correlated with higher levels of depression, anxiety, and stress, though to a lesser degree.

Discussion

The findings of this study demonstrate a strong association between sleep disorders and mental health outcomes among adults, consistent with the broader literature. In this sample of 355 participants, nearly 71% reported at least subthreshold insomnia, and 46.5% experienced excessive daytime sleepiness. Concurrently, more than half of the participants exhibited depression, anxiety, or stress symptoms of varying severity. The significant correlations observed between insomnia, daytime sleepiness, obstructive sleep apnea risk, and mental health indicators underscore the importance of recognizing sleep disorders as a key determinant of psychological well-being.

The high prevalence of insomnia in this study (approximately 34% moderate-to-severe cases) aligns with evidence from Merrill (2022), who found that insomnia significantly increases the risk of mental health conditions such as anxiety, bipolar disorder, and schizophrenia. Our results reinforce this observation, as participants with higher insomnia severity reported elevated depression and anxiety scores. This suggests that insomnia is not merely a symptom of psychiatric disorders but may also contribute directly to their development.

The positive correlation between sleep problems and mental health difficulties mirrors findings from the meta-analysis conducted by Scott et al. (2021). They demonstrated that interventions improving sleep quality led to significant reductions in depression, anxiety, and stress symptoms. In the present study, insomnia severity showed the strongest association with depression (r = 0.52), further supporting the causal interpretation that sleep quality has a direct impact on emotional regulation and resilience.

Our data revealed that 21.1% of participants were at high risk for obstructive sleep apnea (OSA). This is notable because OSA risk was also significantly associated with elevated depression, anxiety, and stress scores, albeit to a lesser degree than insomnia. Chen et al. (2024) confirmed that sleep apnea is associated with increased risk of major depressive disorder and schizophrenia. The overlap between OSA and psychiatric symptoms suggests a need for integrated screening for both conditions in clinical practice.

The observed prevalence of daytime sleepiness (46.5%) further emphasizes the public health impact of sleep disturbances. Excessive daytime sleepiness was moderately correlated with depression (r = 0.39) and anxiety (r = 0.36), reflecting findings from Liu et al. (2022), who reported that healthcare workers with sleep disturbances had a 3.74 times higher risk of developing mental health problems. These results highlight that impaired alertness during the day may serve as both a marker and mediator of psychological distress.

Depression symptoms were reported by 57.7% of participants, with 11.3% in the severe-to-extremely severe range. Anxiety was even more common, affecting 66.2% of the sample, including 18.3% with severe symptoms. Stress symptoms were also prevalent, with 54.9% reporting at least mild levels. These findings align with Yan and Wang (2025), who demonstrated a direct pathway linking stress to depression and indirect pathways through anxiety and sleep disturbances. The interplay identified in our study suggests that stress may exacerbate poor sleep, which in turn worsens mental health outcomes.

The bidirectional nature of the relationship between sleep and mental health is further supported by Farhadian et al. (2022), who found that sleep disturbances can act as precursors to psychiatric disorders in military personnel. Similarly, our data demonstrated strong correlations between sleep and mental health outcomes, implying that poor sleep is not only a result of psychological distress but may actively contribute to its onset.

Interestingly, our results indicated that young adults (18–29 years) had the highest proportion of insomnia and anxiety symptoms. This observation aligns with Shamsaei et al. (2019), who reported that 36% of children with poor sleep habits experienced mental health problems. Both findings highlight how inadequate sleep early in life may increase vulnerability to mental health disorders later on, suggesting the importance of preventive interventions across the lifespan.

Gender differences in sleep and mental health also warrant attention. In our sample, women made up 53.5% of the participants, and they were more likely to report moderate-to-severe insomnia compared to men. Merrill (2022) similarly observed a higher risk of stress and sleep disorders among women. This reinforces the importance of gender-sensitive approaches to mental health and sleep health interventions.

The findings are particularly relevant in the context of global health crises such as the COVID-19 pandemic, where sleep and mental health problems have been exacerbated. Liu et al. (2022) found stronger correlations between sleep disturbance and mental health problems among healthcare workers during the pandemic. While our study was not restricted to healthcare workers, the high prevalence of sleep disorders and psychological distress observed may similarly reflect broader stressors associated with social and economic pressures.

The associations found in our study also parallel Chen et al.’s (2024) genetic evidence linking insomnia and napping to major depressive disorder. While causality cannot be established in this cross-sectional design, our findings provide population-level evidence that is consistent with biological pathways identified in Mendelian randomization studies. This strengthens the case for considering sleep disorders as causal contributors rather than mere correlates of psychiatric illness.

Intervention studies lend further support to this view. Scott et al. (2021) highlighted that improving sleep through targeted interventions leads to significant mental health benefits. This suggests that clinical programs addressing insomnia and sleep apnea could reduce the burden of depression and anxiety in the general population. Our findings confirm that a substantial proportion of individuals with sleep problems would benefit from such interventions.

The current results also highlight the importance of workplace and educational interventions. With 50.7% of participants employed and 25.4% students, both groups represent populations particularly vulnerable to the combined stress of occupational and academic demands. Yan and Wang (2025) emphasized the mediating role of sleep in stress-related depression, suggesting that organizational programs to promote sleep hygiene could have downstream benefits for mental health.

Another critical implication relates to screening practices. Given that nearly half of participants had excessive daytime sleepiness and over one-fifth were at high risk for OSA, primary care providers and mental health professionals should routinely integrate sleep assessments into their evaluations. As Farhadian et al. (2022) noted, early diagnosis of sleep problems can prevent progression to more severe psychiatric disorders. This approach is particularly urgent in high-risk groups, such as women, young adults, and individuals with chronic health conditions.

Finally, the strong correlations between sleep disturbances and stress, anxiety, and depression observed in this study reinforce the need for integrative approaches to treatment. Rather than treating psychiatric symptoms in isolation, clinicians should adopt multidisciplinary strategies that target both sleep and mental health. This approach is supported by Liu et al. (2022), who concluded that improving sleep health is central to reducing mental health risks, especially during crises.

Conclusion

In summary, this study demonstrated that sleep disorders were highly prevalent among adults and significantly associated with depression, anxiety, and stress. Insomnia severity showed the strongest relationship with poor mental health outcomes, but excessive daytime sleepiness and obstructive sleep apnea risk were also important contributors. These findings are consistent with international evidence that sleep disturbances not only co-occur with but may precede and exacerbate psychiatric conditions. Addressing sleep problems through early screening, targeted interventions, and integrated care could substantially reduce the burden of mental health disorders and improve overall well-being.

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