Quality of life in hemodialysis diabetic patients: a multicenter cross-sectional study from Palestine

We performed this multicenter cross-sectional study in the period between November 2016 and August 2017.

The study was conducted in six dialysis centers in the North of West Bank, Palestine. These included the dialysis centers in Nablus, Tulkarem, Jenin, Qalqelia, Tubas and Salfeet. Five of them are centers at the government hospital in each city; only the center at Nablus is at a teaching hospital. We used annual health records of the Palestinian Ministry of Health to gather information regarding the numbers and distribution of diabetic and dialysis patients [16].

At the time of our study, the total number of dialysis patients in these six cities was 507 patients; furthermore, the total number of hemodialysis machines was 92 machines. The distribution of patients and hemodialysis machines for each city was as follows: Nablus 210 patients (33 machines), Tulkarem 78 patients (13 machines), Jenin 113 patients (16 machines), Qalqelia 47 patients (10 machines), Tubas 27 patients (12 machines), Salfeet 32 patients (8 machines). Zyoud et al [19] found that 45% of hemodialysis patients in Palestine are diabetic, so the population of our study was estimated to be 230 patients.

We used a web-based calculator (Raosoft sample size calculator) to calculate our sample size, which was 141 patients. We increased our sample size by 7% to cover patients not responding to our study.

One hundred and forty one patients were recruited by a reliable quota sampling method proportional to the number of patients in each dialysis center. We set five inclusion criteria for patients participating in our study, which were: (1) patients who have confirmed diagnosis of end-stage renal disease according to their medical files; (2) Patients who reported having type 2 DM; (3) Patients aged 18 years or more; (4) Patients who have been on regular hemodialysis for more than six months; (5) Patients with a history of DM for more than one year. We excluded patients with cognitive restrictions that made independent responses to the questionnaire impossible.

The questionnaire we used to gather data from patients contained two sections, one for clinical history and socio-demographic information and the other for the validated Arabic version of HRQOL [20]. In the first section, we included the following socio-demographic characteristics: patient’s gender, age, weight and height (for calculating body mass index (BMI)), residency (village, city or Palestinian refugee camp) [6], educational level, living arrangements (living alone or with family), marital status, occupation, monthly household income, and whether the patient was a smoker or not. The clinical factors included in our study were: total number of chronic medications, total number of chronic diseases, time since DM was diagnosis, average duration of dialysis session, months on dialysis, history of kidney transplantation, and glycated haemoglobin (HbA1c) level. We categorized monthly household income as low (less than 400 Jordanian dinner (JD)), moderate (400–1000 JD) or high (more than 1000 JD) [17]. We also categorized HbA1c level as controlled (HbA1c ≤ 7%) or uncontrolled (HbA1c more than 7%) [21, 22]. We used the 5-level EuroQoL Group’s 5-dimension (EQ-5D-5L) questionnaire to estimate the health status and quality of life (QOL) for diabetic dialysis patients. EQ-5D is a standardized instrument for use as a measure of health outcome [23]. This questionnaire is a five-item scale assessing five separate dimensions of health: (MOBILITY, SELF-CARE, USUAL ACTIVITIES, PAIN/DISCOMFORT and ANXIETY/DEPRESSION). Each dimension has to be answered on a five–level scale (no problems, slight problems, moderate problems, severe problems and extreme problems). We also used the EQ visual analogue scale (EQ-VAS), which measures the subjects' perspectives on their QOL using a 100-point scale [23]. We used the Arabic version of EQ-5D [17, 19, 24] according to Euro QOL guidelines. We also registered our study with Euro quality of life and obtained permission for its use (ID: 20964). An additional file was supplied to illustrate detailed description of the study both in English and Arabic (Additional file 1). Cronbachs’ alpha for our study indicated acceptable internal consistency for EQ-5D-5L scale (α= 0.79). EQ-5D was scored using United Kingdom general population scoring algorithm (i.e. EQ-5D-5L Crosswalk Index Value Calculator) to calculate the index value using the value sets (weights) [25].

After obtaining permission from the education department at Ministry of Health (MOH), we got access to patients’ medical records at each dialysis center to determine diabetic patients among those on hemodialysis. We also identified patients who met our inclusion criteria and invited them to participate in the study. We interviewed one hundred and forty one patients, we chose to meet them face-to-face to make the interview very comfortable for both patients and interviewers, and also to allow patients who aren’t able to read to have the chance to participate in our study. Interviews were carried out by qualified medical students from An Najah National University. After interviewing each patient, a blood sample was withdrawn from each patient by a qualified registered nurse at each dialysis center and these samples were sent to the laboratory department at An Najah National University Hospital to test the patients’ HbA1c level.

The Institutional Review Board (IRB) at An-Najah National University and Palestinian MOH approved our study protocol. We also obtained verbal consent from each patient before including him/her in our study. Approval for blood sample withdrawal was obtained from the MOH and from each patient.

We entered our data and analyzed it using SPSS (IBM SPSS Statistic, version 21: IBM, Armonk, NY, USA) program. Data were expressed as mean (standard deviation) or median (interquartile range) or frequency (percentage). HRQOL was the dependent variable. Socio-demographic and hemodialysis related clinical factors were the independent factors. We used the Kruskal-Wallis or Mann-Whitney U test for data that were not normally distributed. We also assessed the normality of distribution of data using the Kolmogorov-Smirnov test. Median (interquartile range) was used to describe non-normally distributed variables. Internal consistency was assessed using Cronbach's α. The significance level was set at P < 0.05. We entered the independent variables such as gender, marital status, education level, occupational status, and total chronic diseases as dummy coding of 0 and 1. We tested associations between clinical and socio-demographic factors and HRQOL score with multiple linear regression to control for potential confounding factors.

A total of 141 diabetic patients undergoing hemodialysis participated in this cross sectional study out of 150 recruited, giving a response rate of 94%. Overall, 52.5% of them (74 patients) were males while 47.5% (67 patients) were females. Studied patients had a mean age of 60.32 with 52.5% of them aged below 60.The majority of our patients (44%) were obese with BMI above 30. Most of the recruited sample (81 patients) were living in a village, and 95.7% of patients in our sample were living with their family. The sample had a poor educational level, as only 28 (19.9%) graduated from school. The vast majority of patients were unemployed (89.4%), and so 71 out of 141 patients reported having low household income monthly. Regarding dialysis sessions, 87 patients (61.7%) had been having regular hemodialysis for less than four years and 123 patients (87.2%) were having 3 or more dialysis sessions weekly. Only 3 patients reported having a history of kidney transplant. 22.7% of patients were smokers and only 40 (28.4%) had three or more chronic diseases. Ninety-two patients (65.2%) were taking fewer than eight chronic medications. Other clinical and socio-demographic features are shown in Table 1.

In Palestinian diabetic patients undergoing hemodialysis in the North West Bank, we found that the mean EQ-5D-5L index value was 0.314, with median of 0.31 ± 0.4. The mean (± standard deviation) EQ-VAS score was 50.85 (±22.43). The number (percentile) of patients who answered “severe problems” for the five items of QOL was as follows: mobility 25 (17), usual activities 56 (38.1), self-care 46 (31.3), pain/discomfort 9 (6.1) and anxiety/depression 29(19.7) Fig. 1.

The variables that displayed a statistically significant association with the EQ-5D were: patient’s gender, education level, marital status, occupational status, and total chronic diseases (all P values were less than 0.05). On the other side, patient’s age, BMI, residency, living status, household income, smoking, dialysis time, DM time, dialysis frequency, dialysis duration, kidney transplant, total chronic medications, and HbA1c level were not significantly associated with HRQOL (all P values were more than 0.05). For more details regarding the association between clinical and socio-demographic variables and EQ-5D total score, see Table 2.

Table 3 presents the multivariate associations between HRQOL scores and patients’ gender, education level, marital status, occupational status, and total chronic diseases. As shown in Table 3, marital status and occupational status were significantly (p < 0.05) associated with the QOL score. More specifically, married status and being employed were positively associated with QOL score (β = 0.22; p = 0.016 and β = 0.27; p = 0.013, respectively).

Notwithstanding the relatively limited sample, this work had many positive points. For example, it was the first study of our knowledge to use EQ-5D-5L among diabetic patients undergoing hemodialysis. Moreover, this was the first study in Palestine to assess HRQOL in diabetic dialysis patients. In addition, we included patients from both urban and rural areas because of the multi-center design of the study. On the other hand, there were some limitations we have to mention. First of all, we can’t identify a cause-effect relationship because of the cross-sectional nature of the study. Secondly, we didn’t include a generalized sample, as we included only six dialysis centers out of 11 dialysis centers in West Bank. Thirdly, the absence of control groups (i.e. diabetic patients not on maintenance dialysis and non-diabetic patients on maintenance dialysis) limits the interpretation of the disease burden on HRQOL. Lastly, there were some clinical and social factors that might affect patients’ QOL that we didn’t include in our study, such as diet, and some laboratory values.