The association of chronotype with sleep quality and mental health in dialysis patients: A cross-sectional study

Abstract

Background

Patients on hemodialysis commonly experience poor sleep quality, fatigue, and depression. Chronotype may influence these outcomes, but its role in this population remains unclear.

Objectives

This study examined associations among chronotype, sleep quality, fatigue, and depression, and tested the mediating role of sleep quality.

Methods

In this cross-sectional study of 157 patients on hemodialysis (mean age, 63.99 years; 58.6% male), chronotype (Morningness–Eveningness Questionnaire), sleep quality (Pittsburgh Sleep Quality Index [PSQI]), fatigue (Fatigue Severity Scale [FSS]), and depression (Beck Depression Inventory [BDI]-II) were assessed. Correlation and mediation analyses were used to examine these relationships.

Results

Evening types (38.2%) had significantly poorer mean ± standard deviation PSQI scores (12.57 ± 3.37) than neither types (53.5%; 9.73 ± 4.23, p < 0.001) and morning types (8.3%; 8.23 ± 4.36, p = 0.001), particularly in terms of sleep duration, efficiency, and medication use. Fatigue (FSS score=4.63 ± 1.17) and depression (BDI-II score=9.07 ± 7.81) did not differ according to chronotype.

Discussion

Evening chronotype was associated with poorer sleep quality, which in turn was linked to increased fatigue and depression. Targeted sleep interventions for evening types may improve outcomes by correcting circadian misalignment and enhancing sleep efficiency. Sleep hygiene education and timed light exposure may offer clinically meaningful benefits in terms of sleep and psychological well-being.

Keywords

Sleep quality chronotype depression fatigue

Introduction

Chronic kidney disease (CKD) represents a growing global public health burden, with an estimated prevalence of 13.4%.¹ Patients with end-stage renal disease (ESRD), particularly those undergoing hemodialysis, encounter substantial physical and psychological challenges that severely diminish their quality of life.² Common symptoms include poor sleep quality, fatigue, and depression, all of which negatively impact health outcomes.² The global prevalence of poor sleep quality in this group is reported as approximately 64.2%, underscoring the magnitude of the problem.³ Furthermore, sleep disturbances frequently co-occur with fatigue and depressive symptoms.^3,4 Evening-type individuals, whose circadian rhythms are misaligned with societal schedules, tend to experience more severe sleep disturbances, greater fatigue, and poorer mood outcomes.^5,6

Research indicates circadian disruption contributes to poor sleep quality and adverse health outcomes.⁷ Chronotype describes an individual's preferred timing for daily activities and is commonly assessed using self-report tools such as the Morningness–Eveningness Questionnaire (MEQ).⁸ This tool is used to evaluate sleep–wake preferences, peak alertness, and circadian phase, classifying individuals as morning-, intermediate-, or evening-type. Morning types (“larks”) tend to wake earlier and perform best in the morning, whereas evening types (“owls”) prefer later sleep times and perform best in the evening. Intermediate types, comprising approximately 60% of adults, exhibit more flexible patterns.⁸ Recently, chronotype has been viewed as multidimensional, including psychological and environmental factors in addition to sleep timing.⁹ Chronotype reflects behavioral manifestations of endogenous circadian rhythms—approximately 24-h biological cycles that regulate physiological processes—but is distinct from the underlying molecular clock. Chronotype influences sleep quality and health by indicating how well internal rhythms align with external demands.⁶ A morning chronotype is associated with lower risks of anxiety, depression, and insomnia,¹⁰ while an evening chronotype is consistently linked to poorer sleep quality¹¹ and poorer mental health.⁶

Sleep disorders are highly prevalent among patients with CKD and substantially contribute to symptom burden, including poor sleep quality, daytime fatigue, excessive sleepiness, and increased morbidity and mortality.¹² Sleep quality is a multidimensional construct commonly assessed using the Pittsburgh Sleep Quality Index (PSQI), which includes components such as sleep efficiency, sleep latency, sleep duration, and sleep disturbances.¹³ Patients with CKD undergoing hemodialysis exhibit a higher prevalence of poor sleep quality compared with those in earlier stages of CKD, and poor sleep quality is closely associated with disease progression and mental health conditions such as anxiety and depression.¹⁴

Fatigue is a prevalent and often debilitating symptom among patients undergoing hemodialysis, with 70% reporting chronic fatigue that significantly impairs daily functioning and quality of life.^2,15 Fatigue in CKD patients is multifactorial, influenced by psychological factors such as depression, behavioral factors including sleep and nutrition, proinflammatory cytokines like Interleukin 6 and C-reactive protein, and the physiological demands of dialysis.¹⁶ Poor sleep quality is a major contributor to fatigue, as disrupted sleep patterns exacerbate exhaustion and perpetuate a cycle that intensifies both fatigue and related symptoms, including depression.^17,18

Depression is common among patients with CKD undergoing hemodialysis, with up to 40% experiencing clinically significant symptoms.² However, these symptoms are often underdiagnosed and undertreated due to the overlap between somatic and psychological manifestations.^2,19 Despite recognition of the interrelationships among sleep quality, fatigue, and depression, the specific mechanisms linking poor sleep quality to both fatigue and depression in this population remain unclear.¹⁷ Therefore, this study aims to investigate the relationships among chronotype, sleep quality, fatigue, and depression in hemodialysis patients with poor sleep quality.

Method

Design

This study employed a cross-sectional, correlational design.

Sampling

A convenience sample of patients with ESRD undergoing hemodialysis was recruited from two hospitals in Northern Taiwan. Inclusion criteria were as follows: (a) a confirmed diagnosis of ESRD with regular hemodialysis for at least three months; (b) age between 20 and 80 years; (c) a PSQI score above 5, indicating poor sleep quality; and (d) willingness to participate. Patients with cognitive or physical impairments were excluded.

Sample size

Sample size was estimated based on Cohen's²⁰ power guidelines. Given the cross-sectional design and expected unequal group sizes reflecting natural population distribution, the required sample size was determined using the average group size approach. For a one-way ANOVA with three groups, a total sample of 159 was required to detect a medium effect size (f = 0.25) with 80% power at α = 0.05.

Data collection

Data were collected between June and December 2023 at two teaching hospitals in northern Taiwan, after approval from the respective institutional review boards (approval nos. 2023003 and B1121023). Participants were recruited during routine hemodialysis sessions in dialysis units. Trained research assistants individually approached eligible patients, explained the study purpose by using a standardized script, and obtained their written informed consent prior to enrollment. Questionnaires were administered during hemodialysis sessions to minimize the participant burden and improve response quality. For participants with limited literacy or no formal education, trained research assistants read each questionnaire item aloud without interpretation and recorded responses as provided to ensure data accuracy and consistency. In total, 157 patients undergoing dialysis participated in the study, with a mean age of 63.99 years; 58.6% were male. Table 1 presents the demographic characteristics of the participants.

Table 1.

Demographic and clinical characteristics of participants (N = 157).

Variable	n (%)	Mean (SD)
Gender
Male	92 (58.60)
Female	65 (41.40)
Age, years		63.99 (11.60)
Creatinine		10.13 (2.27)
Global PSQI
Subjective sleep quality		1.58 (0.90)
Sleep latency		1.96 (1.10)
Sleep duration		1.97 (0.95)
Habitual sleep efficiency		1.72 (1.23)
Sleep disturbances		1.43 (0.64)
Use of sleeping medications		1.38 (1.46)
Daytime dysfunction		0.65 (0.83)
Chronotype
Morning type	13 (8.30)
Neither type	84 (53.50)
Evening type	60 (38.20)
Fatigue
FSS		4.63 (1.17)
Depression
BDI-II		9.07 (7.81)

Note: SD, standard deviation; PSQI, Pittsburgh Sleep Quality Index; FSS, Fatigue Severity Scale; BDI-II, Beck Depression Inventory-II.

Measures

Several validated questionnaires were used to achieve the study objectives, including the PSQI, Horne and Ostberg MEQ, Fatigue Severity Scale (FSS), and Beck Depression Inventory-II (BDI-II).

PSQI

PSQI is a self-administered questionnaire designed to assess sleep quality over the past month. It evaluates seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. The index comprises 19 items, each scored from 0 to 3, yielding a total score between 0 and 21, with higher scores indicating poorer sleep quality.¹³ The Chinese version of the PSQI has demonstrated strong internal consistency (Cronbach's α = 0.82–0.83). A study found that a score greater than 5 detected primary insomnia with 98% sensitivity and 55% specificity.²¹ In this study, Cronbach's α based on the seven PSQI component scores was 0.66.

MEQ

MEQ is a self-report tool designed to assess circadian preference in human rhythms.²² The Chinese version consists of 19 items that identify an individual's most active period within the daily temporal cycle. Most questions are preference-based, such as “When would you prefer to wake up?” The MEQ total score ranges from 16 to 86, with lower scores indicating an evening chronotype. The Chinese MEQ has demonstrated strong internal consistency (Cronbach's α = 0.70) and test-retest reliability (r = 0.71) over one month.²³ In this study, Cronbach's α for the MEQ was 0.74.

FSS

The FSS is a self-report measure assessing fatigue severity and its impact on daily activities over the past week. It consists of nine items, each rated on a 7-point scale, with higher scores indicating greater fatigue.²⁴ The Chinese version has demonstrated strong reliability and validity.²⁵ In this study, Cronbach's α for the FSS was 0.87.

BDI-II

The BDI-II consists of 21 self-report items, each rated on a 0–3 scale, yielding a total score between 0 and 63. Higher scores indicate greater depressive severity, with scores of 0–13 generally considered within the normal range.²⁶ In this study, Cronbach's α was 0.82 for the BDI-II.

Data analysis

Statistical analyses were performed using SPSS version 27.0. Descriptive statistics were used to examine participants’ demographic characteristics. Continuous variables were reported as means and standard deviations (SDs), while categorical variables were expressed as frequencies and percentages. The normality of continuous variables was assessed with the Shapiro–Wilk test and by visual inspection of histograms and Q–Q plots. Potential outliers were identified using box plots and z-scores, with values greater than ±3 considered extreme. An ANOVA was conducted to examine the effects of different chronotypes on sleep quality, depression, and fatigue. Mediation analysis, using the PROCESS macro (version 4.2), tested the hypothesis that chronotype positively affects fatigue and depression, with sleep quality as a mediator. Statistical significance was set at p < 0.05.

Results

PSQI results for patients undergoing dialysis therapy

Sleep characteristics were assessed using the PSQI. Mean scores for each component are presented in Table 1. The mean scores for subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction were 1.58 (SD = 0.90), 1.96 (SD = 1.10), 1.97 (SD = 0.95), 1.72 (SD = 1.23), 1.43 (SD = 0.64), 1.38 (SD = 1.46), and 0.65 (SD = 0.83), respectively.

Participants were classified as morning types (8.3%), neither types (53.5%), or evening types (38.2%). PSQI scores differed significantly among chronotype groups (F = 11.90, p < 0.001). The evening-type group had the highest mean score (12.57 [SD = 3.37]), followed by the neither-type group (9.73 [SD = 4.23]) and the morning-type group (8.23 [SD = 4.36]). Significant group differences were also observed for sleep duration (F = 8.89, p < 0.001), habitual sleep efficiency (F = 15.14, p < 0.001), and use of sleep medication (F = 7.80, p < 0.001; Table 2). Bonferroni post hoc tests showed that the evening-type group had significantly higher global PSQI scores than the morning-type group (mean difference = 4.34, p = 0.001) and the neither-type group (mean difference = 2.84, p < 0.001), whereas the morning-type and neither-type groups did not differ significantly from each other. Regarding sleep duration, the evening-type group differed significantly from the morning-type group (mean difference = 1.01, p = 0.001) and the neither-type group (mean difference = 0.49, p = 0.006), while the morning-type and neither-type groups did not differ significantly from each other. In terms of habitual sleep efficiency, the evening-type group had significantly worse scores than the morning-type group (mean difference = 1.20, p = 0.002) and the neither-type group (mean difference = 0.99, p < 0.001), and the morning-type and neither-type groups did not differ significantly from each other. As for sleep medication use, the evening-type group reported significantly higher scores than the neither-type group (mean difference = 0.92, p < 0.001), while the difference between the evening-type and morning-type groups was not significant. No significant differences were observed for subjective sleep quality, sleep latency, the sleep disturbance component, or daytime dysfunction.

Table 2.

Comparison of sleep quality, depression, and fatigue by chronotype.

Variable	Morning type (n = 13)	Neither type (n = 84)	Evening type (n = 60)	Between-group difference
Variable	Mean (SD)	Mean (SD)	Mean (SD)	p
Sleep Quality	8.23 (4.36)	9.73 (4.23)	12.57 (3.37)	< 0.001
Subjective sleep quality	1.46 (0.97)	1.50 (0.93)	1.72 (0.85)	0.323
Sleep latency	1.46 (1.13)	1.90 (1.07)	2.15 (1.12)	0.097
Sleep duration	1.31 (1.11)	1.83 (0.96)	2.32 (0.77)	< 0.001
Habitual sleep efficiency	1.15 (1.41)	1.36 (1.20)	2.35 (0.97)	< 0.001
Sleep disturbances	1.38 (0.51)	1.43 (0.70)	1.43 (0.59)	0.969
Use of sleeping medications	1.15 (1.52)	1.01 (1.35)	1.93 (1.44)	< 0.001
Daytime dysfunction	0.31 (0.48)	0.69 (0.79)	0.67 (0.93)	0.299
Fatigue	4.17 (1.35)	4.63 (1.20)	4.73 (1.07)	0.283
Depression	5.46 (3.50)	9.65 (7.86)	9.03 (8.29)	0.198

Note: SD, standard deviation.

Depression and fatigue results for patients undergoing dialysis therapy

The mean FSS score was 4.63 (SD = 1.17), and the mean BDI-II score was 9.07 (SD = 7.81). Fatigue and depression scores did not differ significantly among chronotype groups. Fatigue scores showed no significant difference (p = 0.283), and depression scores were also similar among groups (p = 0.198).

Effect of sleep quality on chronotype and fatigue

The mediation analysis showed that sleep quality significantly mediated the association between chronotype and fatigue. The indirect effect was significant (β = 0.18, 95% confidence interval [CI] = 0.05–0.35), as the CI did not include zero. Chronotype was significantly associated with sleep quality, and sleep quality was significantly associated with fatigue. However, the direct effect of chronotype on fatigue was not significant (Figure 1A). These findings suggest that sleep quality may mediate the association between chronotype and fatigue.

Effect of sleep quality on chronotype and depression

The mediation analysis indicated that sleep quality significantly mediated the association between chronotype and depression. The indirect effect was significant (β = 1.01, 95% CI = 0.24–2.05), as the CI did not include zero. Chronotype was significantly associated with sleep quality, and sleep quality was significantly associated with depression. However, the direct effect of chronotype on depression was not statistically significant (Figure 1B). These results suggest that sleep quality may mediate the relationship between chronotype and depression.

Discussion

This study examined the relationships among chronotype, sleep quality, fatigue, and depression in patients undergoing hemodialysis. Evening types exhibited poorer sleep quality, including lower sleep efficiency and greater use of sleep medications, despite longer sleep duration. Sleep quality mediated the associations between chronotype and both fatigue and depression.

Several potential mechanisms may explain the observed relationships among chronotype, sleep quality, fatigue, and depression in hemodialysis patients. First, circadian misalignment may play a central role. Individuals with an evening chronotype are more likely to experience a mismatch between their endogenous biological rhythms and externally imposed schedules. This misalignment can disrupt the regulation of sleep–wake cycles and impair sleep architecture, leading to reduced sleep efficiency and non-restorative sleep despite longer sleep duration.^6,9,27 Second, physiological dysregulation associated with CKD may exacerbate these effects. Prior evidence has shown that patients with chronic renal failure exhibit poorer sleep quality, lower and non-rhythmic melatonin secretion, and higher inflammatory cytokine levels suggesting that disrupted melatonin-inflammation pathways may contribute to sleep disturbance.²⁸ Individuals with an evening chronotype may be particularly vulnerable to these disruptions, as a delayed circadian phase could further aggravate circadian misalignment, increase nocturnal arousal, and contribute to non-restorative sleep. These factors may, in turn, lead to a greater reliance on sleep medications and be associated with increased fatigue and depressive symptoms.^6,28,29

The present findings are consistent with those of previous studies showing that an evening chronotype is associated with poorer sleep quality.¹¹ Prior studies have suggested that a longer sleep duration does not necessarily offset disrupted sleep timing or a reduced sleep efficiency,^30,31 which may explain why evening types in the present study reported poorer sleep efficiency despite sleep for longer. One possible explanation is that a mismatch between circadian preference and external schedules can lead to less restorative sleep,⁸ increasing the likelihood of using sleep medication as a coping strategy. In patients on hemodialysis, this pattern may be more pronounced because disease-related symptoms can further disrupt sleep–wake regulation.³² Therefore, in patients with CKD, sleep quality may serve as a clinically relevant pathway linking chronotype and disease-related burden to daytime fatigue and symptoms of depression. These findings suggest that individualized sleep-focused interventions, along with attention to circadian alignment and the management of underlying uremic symptoms, may be beneficial in this population.

Chronotype was not directly associated with fatigue; however, sleep quality significantly mediated this relationship. Increased fatigue in evening-type individuals was largely explained by poorer sleep quality, consistent with prior evidence.^33,34 Similarly, sleep quality mediated the association between chronotype and depressive symptoms, indicating that chronotype was not directly related to depression. The higher depressive symptoms observed in evening-type individuals were largely explained by poorer sleep quality. Prior research has similarly emphasized that poor sleep quality is a robust predictor of depressive symptoms, especially in individuals with disrupted or irregular sleep-wake patterns.⁶

The findings of this study have important clinical implications, particularly in the management of dialysis patients. The significant association between evening chronotype and poor sleep quality highlights the need for targeted interventions to improve sleep quality in this population. Specifically, non-pharmacological approaches such as Cognitive Behavioral Therapy for Insomnia and chronobiologically-informed strategies (e.g., sleep hygiene education, timed light exposure, and circadian-aligned scheduling) could be implemented. Clinicians should consider incorporating strategies to enhance sleep efficiency into the care plans for evening-type individuals. Improving sleep quality may not only alleviate sleep disturbances but could also reduce fatigue and depressive symptoms, leading to improved overall well-being for dialysis patients.

This study has several limitations. First, its cross-sectional design its cross-sectional design means that interpretations of causality are not as robust as they could be, and future studies of a longitudinal nature would help to confirm causality., necessitating longitudinal studies to establish directional relationships. Second, reliance on self-reported sleep measures may introduce recall bias and subjective misperceptions. Third, data collection during dialysis sessions may have influenced responses, as fatigue may affect perceptions of sleep quality, although questionnaires were administered early in the session, when possible. Additionally, researcher-recorded responses for participants without a formal educational background might have introduced interviewer bias despite verbatim reading and standardized training. In future, researchers should use self-administered digital questionnaires, conduct assessments outside of treatment sessions, and incorporate objective measures such as actigraphy or polysomnography to improve accuracy.

Conclusion

Sleep quality mediated the relationship between chronotype and both fatigue and depression in patients undergoing hemodialysis. Evening types were particularly vulnerable, showing poorer sleep efficiency and greater use of sleep medication. Targeted interventions, including sleep hygiene education, timed light exposure, and circadian-aligned scheduling, may improve sleep and psychological outcomes. Future longitudinal studies are needed to evaluate chronotype-tailored interventions.

Footnotes

ORCID iD

Mei-Yu Lin

Funding

This study was supported by a grant from Mackay Medical University, (grant number MMU-RD-114-1A-P001).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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