Relationship between sleep quality and fear of progression among partients with chronic kidney disease: A cross-sectional survey

doi:10.21203/rs.3.rs-4817528/v1

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Research Article

Relationship between sleep quality and fear of progression among partients with chronic kidney disease: A cross-sectional survey

https://doi.org/10.21203/rs.3.rs-4817528/v1

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Objectives

The study aims to elucidate the direct correlation between sleep quality and fear of progression (FOP), two significant psychosocial issues that individuals with chronic kidney disease (CKD) encounter.

Methods

A cross-sectional study was conducted among patients with CKD who were recruited from the Second Affiliated Hospital of Anhui Medical University.Clinical and demographic data were collected using a general information questionnaire. The Fear of Progression Questionnaire-Short Form and Pittsburgh Sleep Quality Index were used to measure the level of FOP and evaluate sleep quality over one month. The correlation between sleep quality and FOP was investigated utilizing Pearson correlation and hierarchical regression analysis.

Results

This study comprised 195 people in total, of which 116 (59.5%) suffered from poor sleep quality.Sleep quality and FOP were positively correlated, with higher FOP scores leading to poorer sleep quality. Gender, family financial burden, disease stage, and total FOP score could predict sleep quality. Collectively, these factors combined explained 24.7% of the variation in sleep quality, with FOP independently contributing 6.3% to the explained variance.

Conclusions

Patients with CKD often experience poor sleep quality, an issue that healthcare professionals should take seriously. Interventions focused on reducing FOP could offer a promising approach to enhancing sleep quality.

Chronic kidney disease

Sleep quality

Sleep disturbances

Fear of progression

Psychological nursing

Chronic kidney disease (CKD) is an independent risk factor for cardiovascular disease, cognitive dysfunction, and all-cause mortality, posing a serious public health issue that threatens human health^[1]. By 2040, CKD is predicted to be among the top five causes of death worldwide^[2]. Sleep disturbances affect individuals with CKD at all stages of the disease. Approximately 50% of patients in the early stages of CKD experience sleep disorders, while a substantial 45–80% of those with end-stage kidney disease are affected by such challenges^[3]. These sleep disorders mainly manifest as insomnia, restless legs syndrome, periodic limb movements during sleep, and sleep apnea syndrome^[4]. Sleep disturbances can lead to dysregulation of the hypothalamic-pituitary axis, autonomic nervous system disorders, and increased systemic inflammation, which are closely related to cardiometabolic diseases^[5]. Moreover, they reduce patients' quality of life and adversely affect treatment and prognosis^[6]. Therefore, enhancing sleep quality among CKD is of utmost importance.

Sleep disorders are physiological arousal disturbances linked to elevated levels of stress^[7]. Psychological stress can disrupt sleep by influencing sleep physiology, dream content, dream patterns, and the emotions within a dream^[8]. Stress-related emotions, such as anxiety and depression, are closely related to sleep disorders^[9]. Due to the discomfort of treatment and the chronic nature of the disease, individuals with CKD frequently encounter anxiety, depression, and other emotional disturbances^[10]. Additionally, fear of progression (FOP) is a typical psychological strain caused by the irreversible advancement of CKD^[11]. FOP is defined as a psychological reaction triggered by the presence of an objectively existing disease, manifesting as the patient's concern regarding various biological and psychosocial consequences arising from disease progression or fear of recurrence^[12]. Higher FOP levels can affect the treatment and prognosis of patients, but few studies have investigated FOP in patients with CKD.

It is critical for healthcare practitioners to clarify the direct link between sleep disturbances and FOP, as they can affect the prognosis of patients with CKD. Understanding this link may improve patients' quality of life and lead to more comprehensive care. Although previous research has indicated a positive correlation between FOP and sleep quality in heart failure patients and cancer survivors, this association has not been demonstrated in patients with CKD. Therefore, the study aimed to investigate the relationship between the reported sleep quality and FOP among patients with CKD.

Study design

A cross-sectional study was conducted among patients with CKD who were recruited from the Second Affiliated Hospital of Anhui Medical University between October 2023 and March 2024.

Sample size

The PASS software version 2021 was utilized to calculate the sample size. Based on previous studies, the correlation coefficient was 0.45, and the width of the 95% confidence interval was 0.25^[13]. According to the Pearson correlation coefficient confidence interval method, 159 samples are required. Taking into account a possible dropout rate of 10%, a minimum of 177 samples were ultimately identified. Therefore, the final sample size of 195 study participants included was deemed sufficient.

Participants

Inclusion criteria included patients with CKD aged 18 years or older, who were able to understand and communicate without obstacles and could provide informed consent. CKD was diagnosed according to the KDIGO (Kidney Disease: Improving Global Outcomes) criteria, which state that the estimated glomerular filtration rate (eGFR) is below 60 mL/min/1.73 m^{2 [14]}; Exclusion criteria included individuals with mental illness or cognitive impairment, those with life-threatening diseases, or those who had experienced a major change or severe trauma in the last three months. Kidney transplant recipients were excluded due to the small sample capacity.

Measures

Sociodemographic and clinical data

All participants were interviewed to collect sociodemographic information. Medical records were the foundation of the clinical data. Social demographic data include age, gender, religious affiliation, smoking and drinking habits, educational level, marital status, place of residence, family economic burden, and medical payment methods. Additionally, clinical data such as therapy methods, disease staging, comorbidities, family medical history, and illness duration were also recorded.

Pittsburgh Sleep Quality Index (PSQI)

PSQI was utilized to assess sleep quality in the last month and consists of 9 self-reported questions. The scale contains seven dimensions, including subjective sleep quality, sleep latency, sleep disturbance, sleep duration, habitual sleep efficiency, use of sleep medication, and daytime dysfunction. Scores range from zero to three for each dimension and zero to twenty-one for the overall total. Poor quality of sleep was indicated by a PSQI score higher than seven^[15]. The PSQI's Cronbach's α coefficient in this study was 0.89, indicating the great validity of the questionnaire.

Fear of Progression Questionnaire-Short Form (FOP-Q-SF)

The FOP-Q-SF [16], which was translated into Chinese by Wu et al. ^[17], was utilized to assess FOP. It consists of twelve self-reported items and divided into two dimensions: physical health and social and family aspects. Each item is rated on a scale from one to five, with a higher score corresponds to a higher level of fear. A score of thirty-four or above indicates a dysfunctional FOP^[17]. The Cronbach's alpha of the scale was 0.854 in the current study, indicating the reliability of the tool.

Data collection

The potential participants were provided with the significance and detailed information of the study protocol to guarantee their cooperation and confidentiality. Participants signed an informed consent form prior to the survey. They independently completed the questionnaires based on their own opinions without any external recommendations. The questionnaires were collected and checked by investigators on site. For the answers with doubts, the investigators and participants communicated in time to ensure the completeness and accuracy of responses. All investigators received systematic training and adopted a uniform approach to data collection. The data were entered after double-checking and maintained by a specialized individual.

Statistical analysis

IBM SPSS 26.0 software was employed for data analysis, with statistical significance set at (p < 0.05) for the two-tailed test. Clinical data and sociodemographic characteristics were analyzed using descriptive statistics. For continuous variables, the mean ± standard deviation (SD) was utilized, while for categorical variables, frequency (%) was employed. One-way analysis of variance (ANOVA) with Least Significant Difference(LSD) post hoc tests or independent samples t-tests was used to compare groups. Bivariate correlations between various FOP dimensions and sleep quality were measured using Pearson's correlation coefficient. Covariates from the univariate analysis with (p < 0.05) were considered and included in the multivariate analyses. Hierarchical multiple regression was used to analyze the potential factors affecting sleep quality and explore its relationship with FOP.

Baseline characteristics

Finally, 208 patients with CKD were surveyed, of whom 6 declined to participate and 7 failed to complete the questionnaires. Consequently, 195 valid questionnaires were ultimately collected, representing an effective recovery rate of 93.7%. The study comprised 107 male and 88 female participants, with approximately 18.5% reporting religious affiliation. Participants' ages ranged from 20 to 86, with a mean age of (54.87 ± 12.81) years. The majority had one or more children (91.3%) and resided primarily with family members (82.6%). A significant portion had achieved a secondary school education or below (72.3%), and most were engaged in manual labor occupations (54.9%) or were currently unemployed (84.1%). Furthermore, medical expenses for 97.4% of the patients were covered by insurance. Nevertheless, a substantial number of patients still faced economic burdens (89.2%). In terms of clinical characteristics, the majority of patients enrolled in this study presented with stage 3 or stage 5 disease (80.5%) and lacked familial predisposition to kidney disease (82.6%). Over half of the patients were receiving medication (51.3%), and most suffered from less than three types of comorbidities (90.8%).

Among the sociodemographic and clinical characteristics (Table 1), significant differences were observed in sleep quality based on sex (t = -3.318, p = 0.001), on-the-job status (t = 2.865, p = 0.005), occupation (F = 3.973, p = 0.020), family financial burden (F = 9.628, p < 0.010), stage of disease (F = 7.740, P = 0.001), therapy method (F = 5.460, p = 0.005), number of comorbidities (t = -2.366, p = 0.019).

Table 1

Baseline characteristic and differences in sleep quality (N = 195)
Variables	N(%)	PSQI	t/F	P	post hoc test
		Mean ± SD
Sex
Male	107(54.9)	7.94 ± 3.99	-3.318	0.001
Female	88(45.1)	9.74 ± 3.46	-3.318	0.001
Age, years
≤ 59	122(62.6)	8.46 ± 3.81	0.953	0.387
60–74	68(34.9)	9.25 ± 3.95
75–89	5(2.6)	9.20 ± 3.77
Religious belief
Have no religious belief	159(81.5)	8.85 ± 3.89	0.724	0.470
Have religious belief	36(18.5)	8.33 ± 3.71	0.724	0.470
Education level
Middle school or under	141(72.3)	8.99 ± 4.04	1.068	0.346
Senior high school	30(15.4)	7.93 ± 3.95
College or above	24(12.3)	8.38 ± 2.24
Drink
Never drink	124(63.6)	9.19 ± 3.56	3.011	0.052
Have stopped drinking	60(30.8)	8.25 ± 4.17
Still drinking	11(5.6)	6.64 ± 4.57
Smoke
Never smoke	113(57.9)	9.19 ± 3.56	1.416	0.245
Have stopped smoking	57(29.2)	8.25 ± 3.56
Still smoking	25(12.8)	6.64 ± 4.57
Marital status
Married	168(86.2)	8.81 ± 3.95	0.502	0.616
Unmarried/divorced/widowed	27(13.8)	8.41 ± 3.25	0.502	0.616
Number of children
No children	17(8.7)	8.12 ± 3.24	0.245	0.865
A child	65(33.3)	8.89 ± 3.93
Two children	76(39)	8.88 ± 3.66
≥Three children	37(19)	8.54 ± 4.44
Residence
Urban	99(50.8)	8.55 ± 4.05	-0.766	0.445
Rural	96(49.2)	8.97 ± 3.65	-0.766	0.445
Inhabiting
Living alone	34(17.4)	8.53 ± 3.56	-0.373	0.710
Living with family	161(82.6)	8.80 ± 3.92	-0.373	0.710
On-the-job status
No job	164(84.1)	9.09 ± 3.75	2.865	0.005
On job	31(15.9)	6.97 ± 3.97	2.865	0.005
Occupation
Unemployed ^a	37(19)	10.05 ± 2.73	3.973	0.020	a > c*
Manual labour ^b	107(54.9)	8.79 ± 4.14
Non-manual labour ^c	51(26.2)	7.75 ± 3.70
Medical payment method
Self-paying	5(2.6)	10.60 ± 2.97	1.178	0.279
Medical insurance	190(97.4)	8.71 ± 3.87	1.178	0.279
Family financial burden
Not at all ^a	21(10.8)	6.38 ± 3.41	9.628	< 0.010	a < c* a < d* b < d* c < d*
Little ^b	56(28.7)	7.86 ± 3.88
Some ^c	63(32.3)	8.62 ± 3.39
Heavy ^d	55(28.2)	10.73 ± 3.68
Duration of illness
< 2 years	63(32.3)	7.92 ± 3.75	2.492	0.085
2–4 years	69(35.4)	9.39 ± 4.04
> 4 years	63(32.3)	8.89 ± 3.66
Stage of disease
Ⅲ ^a	62(31.8)	7.27 ± 3.80	7.740	0.001	a < c* a < b*
Ⅳ ^b	38(19.5)	8.89 ± 4.11
Ⅴ ^c	95(48.7)	9.66 ± 3.51
Family history of kidney disease
No	161(82.6)	8.61 ± 3.88	-1.145	0.254
Yes	34(17.4)	9.44 ± 3.69	-1.145	0.254
Therapy method
Medication ^a	100(51.3)	7.89 ± 3.98	5.460	0.005	a < c*
Peritoneal dialysis ^b	29(14.9)	9.44 ± 2.93
Hemodialysis ^c	66(33.8)	9.76 ± 3.76
Number of comorbidities
< 3	177(90.8)	8.55 ± 3.86	-2.366	0.019
≥ 3	18(9.2)	10.78 ± 3.23	-2.366	0.019
Abbreviations: PSQI, Pittsburgh Sleep Quality Index; SD, standard deviation. *p < 0.05.

Current status of sleep quality and FOP in CKD patients

The PSQI score in this research varied from 1 to 17 points, with a mean score of 8.75 ± 3.85. In addition, 59.5% of patients reported poor sleep quality (PSQI > 7) with a mean score of 11.38 ± 2.33. Detailed component scores were provided in Table 2, where daytime dysfunction emerged as the most prevalent issue, followed by prolonged sleep latency. The mean score of FOP was 32.65 ± 8.99, with 45.1% manifesting dysfunctional FOP (FOP ≥ 34) (Table 2).

Table 2

Current status of sleep quality and fear of progression in patients with chronic kidney disease (N = 195)
Scales and dimensions	Mean ± SD	Minimum	Maximum
Total score of PSQI	8.75 ± 3.85	1.00	17.00
Subjective sleep quality	1.48 ± 1.08	0.00	3.00
Sleep latency	1.73 ± 1.14	0.00	3.00
Sleep duration	1.19 ± 0.68	0.00	3.00
Habitual sleep efficiency	1.09 ± 0.61	0.00	3.00
Sleep disturbance	1.38 ± 0.67	0.00	3.00
Use of sleep medication	0.09 ± 0.44	0.00	3.00
Daytime dysfunction	1.80 ± 0.90	0.00	3.00
PSQI ≤ 7 (n = 79,40.5%)	4.9 ± 1.91	1.00	7.00
PSQI > 7 (n = 116, 59.5%)	11.38 ± 2.33	8.00	17.00
Total score of FOP-Q-SF	32.65 ± 8.99	12.00	56.00
Social and family	16.08 ± 4.98	6.00	28.00
Physical health	16.56 ± 5.04	6.00	29.00
FOP ≤ 34 (n = 107, 54.9%)	26.02 ± 5.18	12.00	33.00
FOP ≥ 34 (n = 88, 45.1%)	40.7 ± 5.27	34.00	56.00
Abbreviations:PSQI,Pittsburgh Sleep Quality Index; FOP-Q-SF, fear of progression questionnaire-short form; SD, standard deviation.

Correlation between sleep quality and FOP in CKD patients

Table 3 illustrates that sleep quality was positively associated with FOP (r = 0.382, p < 0.01). Table 3 displayed the correlation coefficients for each dimension. However, the connection between the use of the hypnotic medication dimension of the PSQI scale and the total FOP score, as well as the correlation between the two dimensions, was not statistically significant (p = 0.232; p = 0.264; p = 0.305). This may be due to only 4.6% of patients in the study were taking hypnotics.

Table 3

Correlation between sleep quality and fear of progression in patients with chronic kidney disease (N = 195)
Variables	FOP-Q-SF(r)
	Total score	Physical health	Social and family
PSQI	0.382**	0.391**	0.292**
Subjective sleep quality	0.311**	0.324**	0.232**
Sleep latency	0.240**	0.278**	0.152*
Sleep duration	0.187**	0.186**	0.149*
Habitual sleep efficiency	0.299**	0.245**	0.291**
Sleep disturbance	0.358**	0.387**	0.253**
Use of sleep medication	-0.086	-0.08	-0.074
Daytime dysfunction	0.374**	0.367**	0.304**
Abbreviations: FOP-Q-SF, fear of progression questionnaire-short form; PSQI, Pittsburgh Sleep Quality Index; r, correlation coefficient. p < 0.05; *p < 0.01.

Predictors of sleep quality

Hierarchical regression analyses were conducted with total sleep quality as the dependent variable. Model 1 included covariates with p < 0.05 in univariate analysis (sex, on-the-job status, occupation, family financial burden, stage of disease, therapy method, and number of comorbidities). Covariates and FOP were entered into Model 2. Multiple categorical variables were converted into dummy binary variables. By controlling for the effects of the covariates in Model 2, we found that being female (B = 1.287; p = 0.012), experiencing a heavy family financial burden (B = 2.288; p = 0.02), being at disease stage 3 (B = -1.445; p = 0.023), and the total FOP score (B = 0.121; p < 0.001) showed statistical significance (p < 0.05). Higher FOP levels were associated with poorer sleep quality. In addition, the factors mentioned above accounted for 24.7% of the variance in sleep quality, with FOP independently explaining 6.3% of it (Table 4).

Table 4

Hierarchical regression analysis regarding predictors of sleep quality (N = 195)
	Model 1				Model 2
Variables	B	β	t	p	B	β	t	p
Constant term	8.76	-	6.661	< .001	5.094	-	3.269	0.001
Sex(= female)	1.55	0.201	2.956	0.004	1.287	0.167	2.533	0.012
Family financial burden(have heavy financial burden)	3.064	0.359	3.076	0.002	2.288	0.268	2.343	0.02
Stage of disease (3 stage)	-1.731	-0.21	-2.652	0.009	-1.445	-0.175	-2.289	0.023
FOP-Q-SF total score	-	-	-	-	0.121	0.282	4.022	< 0.001
R²	0.23				0.293
Adjusted R²	0.184				0.247
R² change	-				0.063
F	4.981				16.176
Sig. of model (p)	< 0.001				< 0.001

As far as we know, this is the first study to explore the connection between sleep quality and FOP in Chinese patients suffering from CKD. The findings revealed that 59.5% of CKD patients struggle with sleep issues, primarily manifesting as daytime dysfunction and difficulty falling asleep. These observations align with previous research findings^{[18, 19]}. Studies have shown that inflammatory reactions negatively impact sleep quality^[20]. Patients with CKD often experience reduced renal clearance, elevated levels of pro-inflammatory hormones, accumulation of toxins, and a generalized state of low-grade inflammation in the body^[21]. Additionally, declining renal function can lead to deficiencies in melatonin production and abnormal cortisol levels, further compromising sleep quality^[22].

The results also indicate that women tend to have poorer sleep quality compared to men, echoing previous research. This gender disparity may be attributed to differences in circadian rhythms and hormone secretion between men and women^[23]. Notably, women are more sensitive to circadian rhythms, and perimenopausal women are particularly prone to decreased sleep quality^[24]. This conclusion is bolstered by the fact that the average age of the women in our study was 54.18 years, with most of them being in the perimenopausal phase.

Consistent with other research findings, we discovered that patients with significant family financial burdens were more likely to have lower-quality sleep. Furthermore, univariate analysis revealed a relationship between sleep quality and participants' employment status, as well as their occupations. Previous studies have shown that economic status was associated with sleep behavior and affects other sleep-related outcomes^[25]. Stress levels may rise as a result of low income and trouble paying for healthcare, which may deter people from seeking help. To ameliorate the situation, more resources for healthcare and better insurance plans are required.

The study results showed that patients with advanced stages of the disease have poorer sleep quality than those with earlier stages. The univariate results indicated a relationship between the sleep quality of CKD patients and the type of therapy method, as well as the number of complications. Previous studies have shown that the sleep quality of patients with CKD varies at different stages of the disease^[26]. Patients with advanced CKD experience poorer sleep quality, which may be attributed to both the disease itself and family-related factors. As the disease progresses to an advanced stage, concerns about the illness, the demanding treatment, and escalating complications can disturb sleep quality.

Furthermore, previous research has shown that age independently affects sleep quality in patients with CKD. Sleep quality tends to decline as they become older^[18]. However, this relationship was not observed in the current study, possibly due to the uneven distribution of participant ages, with 62.6% of them being 59 years old or younger.

Most importantly, this study found a positive association between sleep quality and FOP, a relationship that, to our knowledge, has only been explored in cancer survivors and patients with chronic heart failure. The finding align with previous research conclusions. The research found that 45.1% of CKD patients presented dysfunctional FOP, slightly lower than the rate reported by Liu, S. ^[27]. Furthermore, we found that FOP independently accounted for 6.3% of poor sleep quality after adjusting for the covariates. A bidirectional relationship between sleep and mood has been demonstrated^[28]. Conversely, sleep disturbance was more likely to result in mood disorders. Recent studies have proposed a cognitive model of insomnia to explain this relationship^[29]. FOP and sleep quality are influenced by many complex factors, but the underlying mechanism remains unclear. Some interventions such as aromatherapy, acupressure, and health education have been attempted to improve sleep in CKD patients^[3]. However, the available evidence for improving sleep in CKD patients is still limited. Relieving FOP to enhance sleep quality may provide valuable insights for the development of future sleep interventions for patients with CKD.

Nonetheless, this study still has several limitations. Firstly, the cross-sectional design precludes the ability to describe trajectory changes in sleep quality or establish causal relationships between variables. Secondly, our study population was limited to non-transplanted patients with CKD stages 3–5 from a single hospital, limiting the generalizability of our findings. Finally, all variables were measured using self-report questionnaires, lacking an objective measure of sleep quality, which may introduce some reporting bias. Future research could benefit from longitudinal studies and expanded surveys to further explore these issues.

The prominence of sleep problems in CKD patients requires urgent attention from clinicians. Sleep quality was associated with higher levels of FOP, which should be regularly assessed to detect psychological challenges, especially among women, individuals with significant financial burdens, and those with advanced illnesses. In addition, further research could be considered to examine the trajectory of sleep quality and FOP. This research could contribute to the development of personalized sleep therapies for CKD patients.

CKD

chronic kidney disease

FOP

fear of progression

KDIGO

Kidney Disease:Improving Global Outcomes

PSQI

Pittsburgh Sleep Quality Index

FOP-Q-SF

fear of progression questionnaire-short form

standard deviation

ANOVA

analysis of variance

LSD

Least Significant Difference

Ethics approval and consent to participate

Ethics statement

Approval was obtained from the ethics committee of the Anhui Medical University (83242397). The procedure used in this study is consistent with the principles of the Helsinki Declaration. All procedures performed in studies involving human participants were in accordance with the ethical standards of the and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent information

Before the study began, participants were required to provide their informed consent by signing a formal document. During this study, measures were taken to safeguard their personal information and privacy.

Consent for publication

Not applicable.

Availability of data and materials

Due to privacy concerns, the data are available from the corresponding author upon reasonable request.

Competing interests

All authors declare no competing interests.

Funding

No funding was obtained for this study.

Author contribution

Q.Y. and J. W. performed data analysis and wrote the manuscript.

T. S. were involved in data collection, collation, and entry.

X. L. provided critical revisions.

D. W. contributed to supervised, reviewed, revised the manuscript.

Acknowledgments

The authors express their sincere gratitude to the CKD patients who generously volunteered to participate in this study and extend their appreciation to the Department of Nephrology at the Second Affiliated Hospital of Anhui Medical University for providing a venue for this research.

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No competing interests reported.

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Relationship between sleep quality and fear of progression among partients with chronic kidney disease: A cross-sectional survey

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Abstract

Objectives

Methods

Results

Conclusions

Introduction

Methods

Study design

Sample size

Participants

Measures

Sociodemographic and clinical data

Pittsburgh Sleep Quality Index (PSQI)

Fear of Progression Questionnaire-Short Form (FOP-Q-SF)

Data collection

Statistical analysis

Results

Baseline characteristics

Current status of sleep quality and FOP in CKD patients

Correlation between sleep quality and FOP in CKD patients

Predictors of sleep quality

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

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