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Saudi Journal of Kidney Diseases and Transplantation
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ORIGINAL ARTICLE  
Year : 2020  |  Volume : 31  |  Issue : 6  |  Page : 1225-1233
A study of quality of life among hemodialysis patients and its associated factors using kidney disease quality of life instrument-SF36 in Riyadh, Saudi Arabia


1 College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
2 Department of Medical Education, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
3 Department of Medical Education, College of Medicine, King Saud bin Abdulaziz University for Health Sciences; Department of Medicine, Division of Nephrology, King Abdulaziz Medical City, Riyadh, Saudi Arabia

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Date of Web Publication29-Jan-2021
 

   Abstract 


We aimed in this study to assess the quality of life for kidney-ill patients using Kidney Disease Quality of Life Instrument-SF36 (KDQOL-SF36) and the impact of other demographic, clinical, and social factors on patients’ QOL. The quality of life was assessed using an Arabic version of KDQOL-36. The KDQOL-36 subscales Physical Component Summary (PCS), Mental Component Summary (MCS), Burden of Kidney Disease, and Effects of Kidney Disease were calculated. The effect of sex, diabetic status, diabetes mellitus, marital and status employment status, etc. on these subscales was evaluated. Reliability was determined by calculating Cronbach’s alpha. A total of 254 patients were enrolled. The mean age was 58.2 (standard deviation 18.2) years; 61% were male, 56.7% diabetic and 20.1% were employed. The mean domain scores on the PCS, MCS, burden of kidney disease, and effects of kidney disease subscales were 49.4, 38.7, 52.6, and 37.2, respectively. Afternoon shift patients score highest among all shifts in MCS and PCS (P = 0.0001). The MCS score (38.7 ± 28.7) was significantly lower than PCS (49.4 ± 16.5) (P = 0.0001). The “effect of kidney disease” subscale was higher in males (P = 0.02), employed patients (P = 0.02), in the afternoon dialysis shift (0.0001). For PCS higher scores were seen in males (P = 0.0001), in non-diabetics (compared to diabetics) (P = 0,006), in the employed patients (P = 0.02). The highest score was seen in the “burden of kidney disease” subscale and the lowest in the “effects of kidney disease” subscale. Higher scores were seen in males, in nondiabetics, in the employed patients.

How to cite this article:
Ajeebi A, Saeed A, Aljamaan A, Alshehri M, Nasradeen M, Alharbi N, Omair A, Al-Sayyari AA. A study of quality of life among hemodialysis patients and its associated factors using kidney disease quality of life instrument-SF36 in Riyadh, Saudi Arabia. Saudi J Kidney Dis Transpl 2020;31:1225-33

How to cite this URL:
Ajeebi A, Saeed A, Aljamaan A, Alshehri M, Nasradeen M, Alharbi N, Omair A, Al-Sayyari AA. A study of quality of life among hemodialysis patients and its associated factors using kidney disease quality of life instrument-SF36 in Riyadh, Saudi Arabia. Saudi J Kidney Dis Transpl [serial online] 2020 [cited 2021 Apr 21];31:1225-33. Available from: https://www.sjkdt.org/text.asp?2020/31/6/1225/308331



   Introduction Top


Chronic kidney disease (CKD) is a severe disease that affects the kidney and has a negative impact on its function. It is defined as a glomerular filtration rate lower than 1.5 mL/min. There are approximately 700,000, 120,000, and 135,000 patients with CKD stage 5 in the United States, United Kingdom, and Europe, respectively.[1] Noticeable increase in CKD cases in the world are likely due to an increase in civilized diseases such as hypertension, diabetes, and obesity. This led to the development of renal replacement therapy, which can be delivered through hemodialysis (HD), peritoneal dialysis, or kidney transplant.[1],[2] Treatment with dialysis is available worldwide but differs from country to country depending on each country’s financial resources.[1] There are approximately 1.9 million patients on dialysis around the world, and the majority of them are on HD rather than peritoneal dialysis, especially in developed countries.[2]

Although dialysis is the major management plan, it could have complications that affect patients’ daily activities and thus affect their quality of life. World Health Organization (WHO) defines quality of life (QOL) as individual’s perception of their position in the context of culture and is affected by each person’s physical and psychological health.[3] Patients on dialysis may often complain of symptoms such as tiredness, exhaustion, fatigue, sleep disorders, or depression.[4] Moreover, dialysis treatment involves limitations in drinking, eating, and some physical activities including work and hobbies. As a response to patients’ complaints and limitations, QOL assessment forms were developed to assess the patient’s status alongside morbidity and mortality. In other words, higher scores indicate better QOL and decrease both morbidity and mortality.[5]

Many tools have been used to assess QOL in patients, and some of them were modified for certain diseases and translated into multiple languages to include many patients worldwide. Kidney Disease Quality of Life Instrument (KDQOL-36) has been extensively used as a tool for the assessment of QOL in patients with kidney disease on dialysis.KDQOL-36 is a self-reported questionnaire derived from the original (KDQOL™) that had eight subscales and 43 kidney-related items.[6] The new short-form KDQOL-36 includes the generic SF-12 Health Survey instrument plus 24 kidney-related items to assess the QoL in patients with kidney disease.[6] Multiple studies were published using KDQOL-36 to assess QOL in dialysis patients.[5]

A study in Mexico suggested that KDQOL-36 can be used by researchers interested in measuring the health-related quality of life in Mexican hemodialytic patients.[7] Another study done in Malaysia using KDQOL-36 concluded that general health, sleep, cognitive function, and role emotional in patients on HD had lower scores.[8] Locally, there was an only single study which was done in 2011 in Riyadh that assessed the quality of life among patients on HD. Authors concluded that scores were higher in “patient satisfaction,” “dialysis staff encouragement,” and “quality of social interaction” domains.[5] Due to lack of studies published in Saudi Arabia except for that single study, and increasing cases of CKD patients, this study aimed to assess the quality of life for patients on HD using KDQOL-36 and the impact of other demographic, clinical, and social factors on patients’ QOL among patient in King Abdulaziz Medical City (KAMC), Riyadh, Saudi Arabia.


   Methods Top


Study design and setting

This was a cross-sectional study, and data were collected from July to October 2019 in KAMC in Riyadh, Saudi Arabia. The KAMC dialysis center has a main unit in the east of Riyadh and three satellites. These satellites are located as the following: Alyasmin district (north), Alyarmok (east), and Derab, (west-south). The main unit at KAMC has 40 dialysis machines, two of them for emergency cases only. Each unit of Derab and Alyasmin has approximately 70 machines, while Alyarmok has 20 machines. At KAMC’s main dialysis unit, dialysis is delivered in four shifts: morning, afternoon, evening, and night, each shift takes 6 h duration. The other satellites dialyze only in the morning and afternoon.

Inclusion and exclusion

Inclusion criteria included all patients who dialyze at KAMC or its satellites, patients should be on dialysis for at least 12 months, and willing to participate in the study. Exclusion criteria included dialysis duration <12 months, diagnosis of dementia, presence of acute infection, active cancer or active cancer treatment, patients who do not have a file at the health-care system of KAMC or refused to participate in the study.

Material/instrument

Three questionnaires have been used in the study. First was demographic data and the status of the patients regarding dialysis, which included age, gender, weight, height, body mass index, marital and employment status, number of dialysis sessions a week and duration, dialysis vintage in years, vascular access, shifts of the dialysis session, the mean of intradialytic weight gain in each session for the last month, mean of Kt/V for the last month, and the last results of sodium, potassium, hemoglobin, and creatinine. The second questionnaire was about the quality of life using KDQOL-36. This questionnaire developed by RAND and the University of Arizona which validated to measure the quality of life for kidney-ill patients.[9],[10] This questionnaire consists of 36 items divided into two categories: SF-12 and 24 kidney-related items. Physical Component Summary (PCS) and Mental Component Summary (MCS) were assessed by SF-12 items, and burden of kidney disease, symptoms and problems of kidney disease, and effect of kidney disease were assessed by 24 kidney-related items. The answers were scored from 0 to 100, and high scores reflect better quality of life. The last questionnaire was assessing the physical activity of patients using the Rapid Assessment of Physical Activity (RAPA) questionnaire.[11]

Sampling technique

Lists of all patients who are dialyzing at KAMC units were provided to data collectors. A total of 819 patients are dialyzing in the four units. After exclusion, 462 patients remained. Then, patients were given the KDQOL-36 and RAPA questionnaires by data collectors. Data collectors did not influence the patients to participate, and patients were free to answer the questions. Data collectors were available instantly if patients want to ask or clarify something. Then informed consent was taken from the patients to extract data from BestCare, health care system, for our demographics. After excluding uncompleted data, which is defined as not answering one question from SF-12 items from KDQOL-SF36 or missing a total of five questions from all questionnaires, a total of 254 patients were included in the study.

Ethical approval

Ethical approval (RC19/219/R) was taken from the Institutional Review Board of King Abdullah International Medical Research Center. Written informed consent was attained from patients. All patients were noted that all data will be kept in confidentiality, and participation is voluntary.


   Statistical Analysis Top


Data analysis was performed using statistical software JMP®, Version 13. SAS Institute Inc., Cary, NC, USA, 1989–2007. Categorical data were presented by frequency and percentage, while numerical data were presented as median, mean, and standard deviation. Simple and multiple logistic regression were used to find any association between recovery time after the dialysis session and all other items of questionnaires. The confidence interval is 95%, and P-value will be considered significant if it is equal to or less than 0.05.


   Results Top


Demographic data for our patients are shown in [Table 1]. The mean age for our patients was 58.2 [standard deviation (SD) 18.2] years. There were 155 males (61%) and 99 females (39%), and 70% of participants were married. The mean weight was 71.7 (SD 18) kg and height was 160 (SD 11.5) cm were. The mean BMI of our patients was 28.1 (SD 7.2) kg/m2. Most of the patients were diabetic (56.7%). More than half (57.1%) were unemployed, while 20.1% were employed, and 22.8% were retired.
Table 1: Demographics and dialysis details for patients (n = 254)

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For the dialysis profile, the mean dialysis time for each patient a week was 11 h (SD 1.3). The Mean dialysis vintage of our patients was 4.9 (SD 4.9) years. More than 70% of the patients dialyze at daytime (morning and afternoon), while the others dialyze in the evening (16.5%) and night (11.4%), respectively. About dialysis types, 50.4% of the patients were on HD, while 49.6% were on hemodiafiltration; 48.8% of the patient had permanent catheter access to draw blood, while 47.6% of patients were on arterio-venous fistula, and few (3.5%) were on arterio-venous graft. Inter-dialytic weight-gain for the longest period between sessions was 2 kg (SD 1.1). The mean score of Kt/V 1.3 (SD 0.37), serum albumin 38 g/L (SD 5.6), serum creatinine 752 μmol/L (SD 265). Serum sodium 135 μmol/L (SD 9), and Serum potassium 5 μmol/L (SD 2.4). [Table 2] shows Cronbach’s alpha analysis and the results showed that the internal reliability of the subscales was consistent.
Table 2: Cronbach's alpha with standardized variables.

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[Table 3] shows the mean results of KDQOL-36 domains. The mean score MCS scale was 38.7 (SD 28.6), with Social Functioning being the highest subscale 46.0 (SD 33.6) and Role emotional being the lowest subscale 30.7 (SD 27.3). The mean score of PCS was 49.4 (SD 16.5); the highest score of its subscale was Physical Functioning 61.5 (SD 22.3), and the lowest score was Bodily Pain 40.3 (SD 35.4). The mean scores of the Effect of Kidney Disease and Burden of Kidney Disease were 37.2 (SD 31.3) and 52.6 (SD 26.9), respectively.
Table 3: Mean values of KDQOL-36 scales.

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[Table 4] shows the association between MCS, PCS, Effect of Kidney Disease, and Burden of Kidney Disease with demographic and dialysis details. Females had lower PCS (P = 0.0001) and Effect of Kidney Disease (P = 0.002). Regarding the diabetes status, patients who are not diabetic had higher PCS (P = 0.006). In addition, diabetic patients had lower MCS and Effect of Kidney Disease, with borderline insignificant P-value of 0.09 for both. PCS (P = 0.02) and Effect of Kidney Disease (P = 0.04) were significantly affected by the employment status in which patients who were employed had better scores MCS and Burden of Kidney Disease were affected by the exercise intensity, where patients who do slight to vigorous activities had better score (P = 0.03 and 0.02, respectively). Patients dialyzing during daytime shifts had better MCS (P = 0.0001), PCS (P = 0.0001), and Effect of Kidney Disease (P <0.001) compared to nighttime shifts. MCS and PCS were moderately positively correlated (r = 0.67), with a slight increase of MCS at the beginning, as illustrated in [Figure 1].
Figure 1: Correlation between mental component summary and physical component summary.
Correlation coefficient r = 0.67, Significance level = P <0.0001, 95% confidence interval for r = 0.60 to 0.74. MCS: Mental component summary, PCS: Physical component summary.


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Table 4: The association between mental component score and physical component score with demographic data and dialysis details.

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   Discussion Top


The significance of KDQOL has been widely getting the attention of health-care providers and researchers, also its scores were associated with increased mortality among end-stage renal disease (ESRD) patients.[12] We studied the quality of life in patients who dialyze at KAMC, one of the largest medical cities in the middle east. The mean scores of MCS, PCS, Effect of Kidney Disease and Burden of Kidney Disease were 38.7, 49.4, 37.2, and 52.6, respectively, which is consistent with previous studies.[13],[14] In addition, patients who dialyze at the afternoon shift had better PCS and MCS compared to other shifts. Besides, diabetic patients had lower MCS and PCS, equivalent to a study which concluded that patients with diabetes and CKD have lower QOL because of the augmentation of comorbidities.[15]

Our results showed that MCS and PCS are correlated, with a slight increase of MCS at the beginning. In addition, patients who do slight to vigorous activities had better MCS. These findings were also reported by other studies that not only physical health but also mental well-being was improved from increased physical activities even with low to moderate forms.[16],[17],[18] Moreover, Markowitz et al suggested that through specific types of high-intensity physical activity, patients could benefit directly or indirectly from vigorous activities for better physical and psychological QOL and less depressive symptoms.[19]

A study found that even though patients with chronic diseases have poorer physical functioning, they would still have a stable mental status.[20] Stewart et al had noted that patients with chronic diseases had poor QOL in all domains of SF-36 except for mental well-being.[21] Furthermore, a study measured the QOL on patients aged 57 years and above with chronic diseases, they found that mental health was the least affected domain by the presence of chronic conditions, while physical functioning was the most affected one along with other domains.[22] It may be that patients with chronic diseases undergo a process of mental and psychological adaptation with age while physical well-being gets limited with time.[20]

In this study, females had worse PCS, MCS, and Effect of Kidney Disease compared to males. These results support the findings of many previous studies that found females had worse QOL in several parameters.[15],[23],[24],[25],[26],[27],[28] Females having a lower QOL is not unique to kidney diseases, yet medical approaches do not address this adequately.[15] These observations tell us that females should have more attention regarding the effect of kidney diseases on their QOL.[15]

Among demographic data in our study, PCS and Effect of Kidney Disease were strongly affected by employment status. These findings are consistent with other studies stated that patients could continue their education and employment during the presence of CKD.[29],[30] In the Saudi population, males are still seeing themselves as the main financial source of their families, and being unemployed increases the effect of kidney disease on their life. Moreover, it was stated that patients with ESRD, even after kidney transplantation, are highly unemployed, and individuals who are in a state of unemployment are often exposed to family struggles.[31],[32],[33] As defined by the WHO, social and relationship is an important aspect; therefore, social counseling and rehabilitation had been studied for these patients and were successful.[32],[33]

Our results showed that KDQOL-SF36 is a reliable questionnaire, with Cronbach-alpha of 0.9 suggesting internal reliability. When we tried to drop some items of MCS and PCS, the Cronbach-alpha still exceeded 0.65, as shown in [Table 4].

The study had some limitations that should be raised. The response rate was low (54%). We think that this low response rate was because of the plenty of questions. We might consider in the future using electronic surveys for such patients so we can easily detect missed items.[34] Second, not all patients in KAMC were eligible to participate in this study because they do not have a database in the system, so we could not gather all their data. Finally, because we did not want the data collectors, by any means, to influence the participants, we could not distinguish what questions answered by patients themselves or by the family members or assistants. Some questions depend on patients’ feelings and perception, thus might affect the results.

Conflict of interest: None declared.



 
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Correspondence Address:
Abdulaziz Ajeebi
College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Riyadh
Saudi Arabia
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DOI: 10.4103/1319-2442.308331

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