Association of sleep quality, pain severity, and depression in patients undergoing maintenance hemodialysis

Study design and site

A cross-sectional study was carried out for a period of 6 months (February 2019–July 2019) in HD center of Justice K. S. Hegde Charitable Hospital, Dakshina Kannada, Mangaluru.

Sample size and study criteria

The present study is a 6–month, time–bound, hospital-based study. The sample size was estimated by taking into consideration the previous records of patients visiting the outpatient HD unit of the hospital in the preceding years. The following formula was used to calculate the sample size: n = Z _1-α² P.Q/d²; n = [(1.96)² × 0.2 × 0.8]/(0.1)² = 61. The required sample for the study is 61. During the study period, only 66 patients visited the outpatient HD unit. The patients were chosen using random sampling method. Out of 66 patients, 60 patients gave their consent for participation in the study.

Patients who are undergoing maintenance HD aged 18 and above of either sex were included in the study. Pregnant women, critically ill patients, and patients who were not willing to give their consent were excluded from the study.

Ethics approval

Approval was obtained from the Institution Ethics Committee (IEC) Ref No: NGSMIPS/IEC/22/2018-19 and Clinical Trials Registry - India (CTRI) registration (CTRI Ref. No: CTRI/2019/02/017378) was done prior to the study.

Study procedure

The aim of the study was explained to all the participants, and the subjects who were voluntarily interested to partake in the study were made to sign the informed consent before participation, and they also were assured about the confidentiality. Patients who met the inclusion criteria, the demographic details such as age, gender, marital status, employment status, comorbidities, frequency, and vintage of HD were collected from the medical records and the patients themselves. Sleep quality, pain severity, and depression in patients undergoing maintenance HD was assessed using the scales mentioned below.

Severity of pain was assessed using a single-item Visual Analog Scale (VAS) and the scores ranged from 0 to 10 (Haefeli and Elfering, 2006; Huskisson, 1974; Jensen et al., 1986; McCormack et al., 1988; Upadhyay et al., 2014). Original Beck Depression Inventory (BDI) questionnaire was used to assess the depression among the subjects, which is 21-item self-reporting questionnaire. The BDI scores ranged from 1 to above 40 (Jackson-Koku, 2016). The sleep quality of patients was assessed using the 10-item Pittsburgh Sleep Quality Index (PSQI). The PSQI scores ranged from 0 to 36 (Mehrabi et al., 2017).

The validated VAS and PSQI questionnaires, of Kannada and Malayalam local languages, were provided by the original developers. The BDI was translated into Kannada and Malayalam local languages by using a 3-step process and it was validated by an expert panel. Cronbach’s alpha value was more than 0.7.

Statistical analysis

Frequency and percentage were used to present categorical data. The association between the categorical variables was assessed by using Chi-square/Fisher’s exact test, with p < 0.05 being considered as statistically significant. Spearman’s correlation was applied to find the association between pain severity, sleep quality, and depression among HD patients. Kruskal–Wallis’ test was applied to find the association between disease scales (pain severity, sleep quality, and depression) among HD patients. Statistical Package for the Social Sciences Statistical software (version 20) was used to analyze the data.

Sociodemographic characteristics

A total of 60 subjects were interviewed over a period of 6 months. Among the 60 patients interviewed, majority were male (80%) and the rest (20%) were females, which is similar to the study findings of Aggarwal et al. (2017), where male subjects were predominant than female subjects. The age of the HD patients ranged from 18 to 83 years, the mean age of the subjects was 53.51 ± 12.06 years, and majority of patients were in the age group of 45–64 years, which is similar to the study findings of Rai et al. (2011) which reported the mean age to be 53.82 ± 8.06 in their study, with majority of the population belonging to the age group of 40–55 years and majority of them are married. With regard to the presence of comorbidities, the most common comorbidity was hypertension, followed by diabetes mellitus. With regard to the sociodemographic parameters observed in the current study, such as male predominance, majority of patients were in the age group of 45–64 years, most of them were married (91.66%), more than half of the subjects were unemployed (60%), and the most common comorbidity was hypertension, followed by diabetes mellitus and ischemic heart disease. These findings were observed to be similar to the demographic parameters in the study conducted by Uzzal et al. (2015) for ESRD patients. In this study, majority of the subjects were undergoing HD twice a week and the vintage HD ranged from 1 to 18 months and 57% of the subjects were unemployed due to the burden of the disease. Detailed demographics of the patients are summarized in Table 1.

Pain, depression, and sleep quality among HD patients

In this study, most of the patients had mild pain (78.33%), followed by 11.66% patients who had moderate pain which is in accordance with the study conducted by Rosa Marques et al. (2016) where mild pain was seen to be more common. It was found that most of the subjects had moderate depression (43.33%), followed by mild mood disturbance (11.66%) and severe depression (11.66%), which was in contrast to the study conducted by Cengic and Resic (2010) where most of the subjects were observed to have mild depression (30%) more commonly followed by moderate depression (8.5%). In this study, it can be seen that majority of patients had low quality sleep (78.33%), which is in line with the study conducted by Masoumi et al. (2013) where majority of the HD patients (86.6%) had poor quality sleep in terms of total PSQI scores. The occurrence of pain, depression, and sleep quality among HD patients are summarized in Table 2.

Association between pain severity, sleep quality, and depression among HD patients

In this study, there is a significant association between pain and depression (p = 0.036) which indicates that there is significant impact of pain severity on developing depression in HD patients and these findings are in accordance with the findings of Davison and Jhangri (2005), which observed that pain was associated with depression.

It was also seen that there is a significant association between depression and sleep, which illustrates that the quality of sleep among HD patients is affected due to the depression that they are going through, which is strongly in line with the findings of the study conducted by Trbojevic-Stankovic et al. (2014), which observed depressed patients to have worst quality of sleep and also the poor sleepers had a significantly high BDI, i.e., there is a correlation between BDI and PSQI. At the same time, there was no association found between the severity of pain and sleep quality of HD patients, which was in agreement with the study conducted by Davison (2003), where it was found that pain is independently associated with insomnia. The association between pain severity, sleep quality, and depression among HD patients are summarized in Table 3. The association between pain severity, sleep quality, and depression, with demographic details among HD patients, are summarized in Table 4 and 5.

Table 1. Demographic details of the patients. [Click here to view]

Table 2. Pain, depression, and sleep quality among hemodialysis patients. [Click here to view]

Table 3. Association between pain severity, sleep quality, and depression among hemodialysis patients. [Click here to view]

Table 4. Association between age and duration of HD with pain severity, sleep quality, and depression. [Click here to view]

Table 5. Association between pain severity, sleep quality, and depression with patients’ demographics. [Click here to view]

This study has some limitations as it is conducted in just one hospital, which diminishes the generalizability of findings, and also there was difficulty in drawing accurate comparison with other studies due to considerable variations in settings, duration, size, and method. Also, the association of other psychosocial and risk factors is not taken into consideration.