|Year : 2018 | Volume
| Issue : 4 | Page : 1414-1421
Assessment of health-related quality of life of hemodialysis patients in Benha City, Qalyubia Governorate
Ossama M Wassef, Mahmoud F El-Gendy, Rabaa M El-Anwar, Sherif M El-Taher, Basma M Hani
Department of Public Health and Community Medicine, Faculty of Medicine, Benha University, Benha, Egypt
|Date of Submission||21-Dec-2015|
|Date of Acceptance||11-Feb-2016|
|Date of Web Publication||14-Feb-2019|
Basma M Hani
Department of Public Health and Community Medicine, Faculty of Medicine, Benha, Qalyubia 13111
Source of Support: None, Conflict of Interest: None
The first was to assess health-related quality of life (HRQOL) of hemodialysis patients attending dialysis unit in Benha University and Teaching Hospitals, and the second was to determine the factors and predictors affecting HROOL of hemodialysis patients.
Hemodialysis results in a significant change in daily living, physical and psychological impairments, and disruption of marital, family, and social life. HRQOL assessment helps to plan individual management strategies and determine the efficacy and quality of medical and social care provided.
Patients and methods
This was a cross-sectional study that included 228 hemodialysis patients, with 144 males and 84 females, and their mean age was 46.62 ± 14.59 years. Data were collected by a questionnaire that included demographic, social, and medical questions. Kidney Disease Quality of Life short form questionnaire 36 was used as a tool for assessment of HRQOL. The collected data were presented and analyzed by using statistical package for the social sciences, version 20, software. The significance was tested by independent t test, analysis of variance, and multiple linear regression analysis.
HRQOL in the studied hemodialysis patients was relatively low. The mean score for physical component summary was 39.3 ± 10.98, and the mean score for mental component summary was 47.59 ± 12.21. Better HRQOL was revealed in less than 60 years old, males, single patients, those with higher educational level, and in patients on maintenance hemodialysis of less than 6 years. Hepatitis C virus (HCV) positive, diabetic, and anemic patients had the lowest HRQOL scores for comorbidities. Age, duration of dialysis, anemia, and HCV positivity were statistically significant predictors of physical component summary; diabetes was a statistically significant predictor of mental component summary.
The most important sociodemographic factors affecting HRQOL were age, sex, education, occupation, and marital status. The most important comorbidities affecting quality of life were anemia, HCV infection, and diabetes.
Keywords: Benha University, end-stage renal disease, hemodialysis, health-related quality of life, quality of life
|How to cite this article:|
Wassef OM, El-Gendy MF, El-Anwar RM, El-Taher SM, Hani BM. Assessment of health-related quality of life of hemodialysis patients in Benha City, Qalyubia Governorate. Menoufia Med J 2018;31:1414-21
|How to cite this URL:|
Wassef OM, El-Gendy MF, El-Anwar RM, El-Taher SM, Hani BM. Assessment of health-related quality of life of hemodialysis patients in Benha City, Qalyubia Governorate. Menoufia Med J [serial online] 2018 [cited 2023 Jun 1];31:1414-21. Available from: http://www.mmj.eg.net/text.asp?2018/31/4/1414/252064
| Introduction|| |
Over the past few decades, quality-of-life (QOL) research studies have emerged as valuable tools in assessing the outcome of therapeutic intervention in chronic diseases. End-stage renal disease (ESRD) is one such chronic disease that causes a high level of disability in different domains of the patients' lives, leading to impaired QOL. Hemodialysis therapy is time intensive, expensive, and requires fluid and dietary restrictions. Long-term dialysis therapy itself often results in a loss of freedom; dependence on caregivers; disruption of marital, family, and social life; and reduced or loss of financial income.
Hemodialysis alters the lifestyle of the patient and family and interferes with their lives. The major areas of life affected by ESRD and its treatment include employment, eating habits, vacation activities, sense of security, self-esteem, social relationships, and the ability to enjoy life. Owing to these reasons, the physical, psychological, socioeconomic, and environmental aspects of life are negatively affected, leading to compromised QOL.
Survival of patients with ESRD has been largely improved nowadays because of medical progress, advanced technology, and better patient care. Accumulated data in the recent decade show that health-related quality of life (HRQOL) markedly influences dialysis outcomes. Attention thus needs to be focused not only on how long but also on how well patients with ESRD live. Compared with the general population, patients with ESRD treated with hemodialysis have significantly impaired HRQOL.
Evaluation of HRQOL in patients with chronic diseases is becoming paramount. HRQOL assessment helps to plan the individual strategy of treatment, to determine the efficacy of medical intervention, and to evaluate the quality of medical care. In comparison with HRQOL of the general population, it provides the opportunity to evaluate the psychological burden of chronic disease, and the effect of specific treatment.
An increasing number of professionals feel that HRQOL assessment is essential for evaluating quality and effectiveness of care among patients with ESRD, comparing alternative treatments and renal replacement therapy modalities, improving clinical outcomes, facilitating complex rehabilitation of patients with ESRD, and enhancing patient satisfaction. Several authors have suggested that regular HRQOL monitoring has become a part of regular assessment of patients with ESRD and needs to be incorporated into the continuous quality assurance and quality improvement systems.
| Patients and Methods|| |
This is a cross-sectional study conducted to assess the QOL of hemodialysis patients and determine factors and predictors affecting HRQOL among them. The study was carried out in the dialysis unit of both Benha University Hospital and Benha Teaching Hospital. The field work was carried out during the period from January 1 to July 31, 2015 (7 months).
An approval from the Research Ethics Committee in Benha Faculty of Medicine was obtained to conduct this study. An informed written consent in Arabic language was obtained from all participants. The consent form included complete details about the study (title, objectives, methods, expected benefits, and confidentiality of data). An official permission was obtained from hospital administrators to carry out the work.
The study was conducted among 288 hemodialysis patients (all hemodialysis patients attending the dialysis unit of both Benha University and Benha Teaching Hospitals), aged 18 years or more, on maintenance hemodialysis not less than 6 months, had two or three hemodialysis sessions per weak, and agreed to be interviewed and participate in the study.
Tool of data collection
Data were collected using a well-structured questionnaire translated into Arabic language (modified). Every participant in the study was interviewed in the dialysis unit by the researchers who explained the aim of the study and then took their answers. The questionnaire included the following sections.
The participants were asked about their age, sex, residence, marital status, occupation, smoking habit, and social score.
Social score: it is used to assess the socioeconomic status of included patients. The final scale included seven domains with a total score of 84, with a higher score indicating better socioeconomic status.
Kidney Disease Quality of Life short form questionnaire, version 1.3
The Kidney Disease Quality of Life short form questionnaire (KDQOL-SF) is a self-reported measure that assesses the functioning and well-being of people with kidney disease who are on dialysis. The questionnaire consists of 80 items divided into 19 domains. The SF health survey (SF-36) is a generic core with 8 domains/36 items: physical functioning (10 items), role limitations caused by physical problems (four items), role limitations caused by emotional problems (three items), pain (two items), general health perceptions (five items), social functioning (two items), emotional well-being (five items), energy/fatigue (four items), and one item about health status compared with 1 year ago. The 43 kidney disease-specific items (11 domains/43 items) are as follows: symptom/problem list (12 items), effects of kidney disease (eight items), burden of kidney disease (four items), cognitive function (three items), quality of social interaction (three items), sexual function (two items), sleep (four items), social support (two items), work status (two items), overall health rating (one item scored separately), patient satisfaction (one item), and dialysis staff encouragement (two items). Overall health rating has one item that is scored separately. Results of the 36-item health survey instrument are further summarized into a physical component summary (PCS) score and a mental component summary (MCS) score. Meanwhile, kidney disease targeted items are summarized into kidney disease component summary (KDCS) score.
Scoring of Kidney Disease Quality of Life short form questionnaire
The scoring procedure of the KDQOL-SF transforms the raw precoded numeric values of items to a 0–100 possible range, with higher transformed scores always reflecting better QOL.
It includes patients' medical history. It consists of questions covering the following items: duration of illness, causes of renal failure, information on other diseases, duration of dialysis, number of hemodialysis session/week, time schedule of session, and type of vascular access.
The collected data were tabulated and analyzed using statistical package for the social sciences, version 20, software (SPSS 20, IBM, Armonk, NY, United State of America). Categorical data were presented as number and percentages, whereas quantitative data were expressed as mean and SD. Independent t test and analysis of variance (F) test were used as tests of significance. Multiple linear regression analysis was used to detect the significant predictors of QOL scores among the studied sample. The accepted level of significance in this work was stated at 0.05 (P < 0.05 was considered significant).
| Results|| |
The study showed that the mean scores for PCS and MCS were 39.3 ± 10.98 and 47.59 ± 12.21, respectively, showing that the kidney disease had a greater effect on physical health than on mental health. For PCS, physical role, which referred to the limitations owing to physical health problems such as limitations in the kind of work that could be performed or in other activities, scored the lowest (34.4 ± 10.69). Conversely, physical function, which referred to the ability to perform moderate activities such as moving a table or climbing stairs, scored the highest (45.9 ± 11.16).
For MCS, emotional role, which is referred to the limitations owing to emotional health problems such as the patient accomplished less than he or she would have liked and was not able to work or do other activities as carefully as usual, scored the lowest (41.1 ± 10.89). Conversely, the highest score (59.9 ± 12.15) was attributed to emotional well-being, which included feeling peaceful, calm, downhearted, or depressed [Table 1].
|Table 1: The scores of the Kidney Disease Quality of Life short form questionnaire 36 of the study group|
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The mean for KDCS was 64.29 ± 11.71. For KDCS, burden of kidney disease, which assessed perception of frustration and interference of the kidney disease in one's life, scored the lowest (35.21 ± 11.75). Conversely, the highest score was attributed to dialysis staff encouragement, which assessed the extent to which staff encourages patients to be independent and lead a normal life as possible [Table 1].
The results showed that patients of age group less than 60 years had significantly higher PCS and MCS scores than those of age group more than or equal to 60 years; moreover, male patients had higher physical QOL score (33.30 ± 7.11) than female patients (30.33 ± 5.79). Duration of hemodialysis treatment negatively affected physical QOL as patients with a longer duration of hemodialysis (≥6 years) had a significant lower PCS score than those with a shorter duration of hemodialysis (29.83 ± 6.78 and 32.86 ± 5.18, respectively). Patients who came from rural areas had significantly lower PCS scores [Table 2]. Illiterate patients and those who can read and write have significantly lower score regarding the physical and mental QOL than the more educated patients. Unemployed patients had the lowest PCS score (25.23 ± 9.86). Meanwhile, professional job patients have the highest mental component score. There was a statistically significant association between social score and physical and mental component of QOL [Table 2] and [Table 3].
|Table 2: Mean scores of physical component summary of the study group regarding sociodemographic characteristics and comorbidities|
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|Table 3: Mean scores of mental component summary of the study group regarding sociodemographic characteristics and comorbidities|
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Regarding comorbidities, there was a significant difference in mean score of PCS regarding the presence of diabetes, anemia, and ischemic heart disease, whereas hepatitis C and hypertension showed insignificant difference [Table 2]. There was a significant difference in mean score of MCS regarding the presence of diabetes, hepatitis C virus (HCV), and anemia, whereas hypertension and ischemic heart disease showed insignificance [Table 3].
Regarding KDCS, patients younger than 60 years old and male patients had statistically significant higher KDCS scores than those more than or equal to 60 years old and female patients. Patients on hemodialysis for less than 6 years had significant higher KDCS scores than those on dialysis for more than or equal to 6 years. This study illustrated that educational level, residence, and social score significantly affected the KDCS mean scores. Professional job patients had the highest KDCS score (73.50 ± 12.94). Anemic patients had highly significant lower scores regarding the kidney disease component than nonanemic patients. In addition, diabetic, hypertensive, and hepatitis C-positive patients had significantly lower kidney disease components scores than nondiabetics, nonhypertensive, and hepatitis C-negative patients [Table 4].
|Table 4: Mean scores of kidney disease component summary of the study group regarding sociodemographic characteristics and comorbidities|
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Multiple liner regression showed that, among sociodemographic factors, age and duration of dialysis were significant risk factors that affect the score of physical component of QOL. Regarding history of diseases, positive histories of anemia and HCV were significant risk factors affecting physical component score [Table 5]. Diabetes was a significant risk factor that affected the score of mental component of QOL [Table 6]. Regarding KDCS, the most contributing sociodemographic characteristics and comorbidities affecting KDCS scores among the studied hemodialysis patients were anemia and diabetes [Table 7].
|Table 5: Multiple regression analysis of sociodemographic and comorbidities affecting physical component of quality of life among hemodialysis patients attending Benha dialysis units|
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|Table 6: Multiple regression analysis of sociodemographic and comorbidities affecting mental component of quality of life among hemodialysis patients attending Benha dialysis units|
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|Table 7: Multiple regression analysis of sociodemographic and comorbidities affecting kidney disease component among hemodialysis patients attending Benha dialysis units|
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| Discussion|| |
This is a cross-sectional study performed to assess HRQOL in hemodialysis patients. The study was carried out at both Benha University and Benha Teaching Hospitals. It was conducted on patients on maintenance hemodialysis who accepted to participate in the study.
Assessment of health-related quality of life
This study demonstrated that PCS scores of HRQOL of the study group were lower than MCS scores; in other words, despite the worsening of the physical health status, the mental health of dialysis patients is relatively preserved. These results were supported by that of Kim et al., who carried out a cross-sectional study on 237 hemodialysis patients and concluded that hemodialysis patients showed higher scores in MCS (44.6 ± 7.0) than in PCS (39.3 ± 9.7). This may be explained by the psychological adjustment or adaptation of patients to the physical difficulties encountered with advanced age or disability.
Regarding KDCS, the domain of burden of kidney disease, in which patients were asked whether their kidney disease interfered with life, took too much of their time, made them feel frustrated, or made them feel like a burden on their families, scored the lowest (35.21 ± 11.75). This agrees with the study conducted by Shunichi et al., who stated that patients with ESRD treated by hemodialysis in Japan reported a much greater burden of kidney disease than did those in the United States or Europe. Similarly, the study carried out by Nashwa et al., in El-Minia Governorate illustrated a great burden of kidney disease reported by Egyptian hemodialysis patients.
Factors affecting health-related quality of life in the study group
Regarding the relation between QOL scores and sociodemographic characteristics and comorbidities, it was observed from this study that age had a significant influence on physical and mental QOL, as patients in age group less than 60 years had higher PCS, MCS, and KDCS scores than older patients (≥60 years). This is in agreement with Lessan-Pezeshki and Rostami, who studied contributing factors in HRQOL of patients with ESRD in Iran using KDQOL-SF and found that there was a significant negative effect of old age on each of PCS, MCS, and KDCS.
Furthermore, lower physical and mental QOL scores in women were observed in this study. This sex-related difference was also found in the study conducted by Vazquez et al.. The probable reasons for the poorer HRQOL in female patients appear to be more linked to the higher prevalence of depression and anxiety disorder among women in addition to women's multiple domestic tasks and responsibilities that, unlike men, cannot be circumvented.
Duration of dialysis treatment plays an important role in affecting HRQOL of hemodialysis patients. This study found that long duration on hemodialysis treatment (≥6 years) was significantly associated with lower physical QOL scores but had no significant effects on both mental and kidney-disease related aspects of QOL, which is in agreement with Bohlke et al. who found that higher scores in the physical QOL occurred among patients who had been on dialysis for shorter lengths of time. This can be explained by more exposure to disease complication and dialysis adverse effects.
A higher educational level was associated with higher PCS, MCS, and KDCS scores, which is in agreement with the study conducted by Assal et al.. This can be explained by the role of higher education in raising the awareness of the patients about the nature of their disease and providing better coping ability regarding problems of hemodialysis treatment. However, this finding is in contrary to the study by Al-Jumaih et al. who found that QOL scores were not significantly affected by level of education, possibly owing to highly educated patients always hope for better QOL and state of health, which makes them unsatisfied with their physical and mental health.
This study found that rural patients had lower PCS scores than urban patients. These results are in agreement with another study performed by Sathvik et al.. These results may be explained by the fact that rural residents in Egyptian community depend on their physical strength to do indoor and outdoor activities and hemodialysis markedly impairs their physical function.
The study results showed that there is a highly significant association between the social class and the physical and mental QOL scores. This agrees with Sesso et al., who found that QOL domains are remarkably low in the lower socioeconomic classes. This could be explained by a lower social status characterized by lower education, worse financial situation, or lack of employment, as well as the relation of the income and the ability to buy the required supportive treatment and the required healthy food.
Diabetic patients, in this study, had lower PCS and KDCS than nondiabetic patients, which is in agreement with the results of Seica et al., who found that the presence of diabetes was a significant factor for worsening the physical functioning. Furthermore, the study performed by Anees et al., in Pakistan found that nondiabetic patients on hemodialysis had better QOL in physical health as compared with diabetic patients.
Regarding mental component of QOL, the present study showed that the absence of diabetes mellitus is associated with better mental QOL. Similarly, a study done by Wee et al., reported that nondiabetic patients had better MCS compared with diabetic patients. This can be explained by diabetic patients on hemodialysis have a higher burden of morbidity owing to the risk of microvascular and macrovascular disorders associated with diabetes, such as cardiovascular diseases, cerebrovascular events, and peripheral vascular disease, than nondiabetic patients.
The current study found that anemic patients had lower scores regarding physical and kidney disease components than nonanemic patients, which is in agreement with Arogundade et al., who found a positive correlation between HRQOL and hemoglobin concentration. This can be explained by the hypoxic condition caused by anemia may not only negatively affect physical function but also the cognitive performance, mood, and QOL of the hemodialysis patient.
Hepatitis C-positive patients had significantly higher scores in physical, mental, and kidney disease components of QOL than negative patients. This finding is in agreement with Afsar et al., who studied QOL of hemodialysis patients using SF-36 in Turkey and found that HCV-positive patients had lower PCS and MCS scores than negative patients. This could be owing to the complications of hepatitis C infection and the social limitations imposed by the illness, as the patient considers himself/herself infectious, hence cannot get married or live a normal marital life.
Determining predictors affecting health-related quality of life components
Using multivariable regression analyses of sociodemographic and comorbidities affecting the PCS and MCS among hemodialysis patients, this study found that age, duration of dialysis, anemia, and hepatitis C infection are negative predictors of physical QOL score, whereas diabetes is a negative predictor of mental QOL. This can be supported be multivariable regression analyses performed by Kao et al., who showed that older age was significantly inversely associated with PCS but not with MCS. Moreover, in the study conducted byBayoumi et al., to detect predictors of QOL in hemodialysis patients, multiple regression analysis demonstrated that age, dialysis duration, and male sex were negative predictors of QOL score.
| Conclusion|| |
From the present study, it can be concluded that HRQOL of hemodialysis patients is impaired. The most important sociodemographic factors affecting HRQOL were age, sex, education, occupation, and marital status. The most important comorbidities affecting QOL were anemia, HCV infection, and diabetes. The development and implementation of multidisciplinary interventions consisting of psychosocial and specific medical and dietetic strategies that focus on factors associated with mental and physical QOL are warranted to prevent further health complications and to improve QOL of hemodialysis patients.
This study revealed that ESRD is a major public health problem that disturbs patients' QOL. So, comprehensive programs, including a health education program in Benha University Hospital and Benha Teaching Hospital, are recommended followed by performing further interventional research studies to assess the effect of this educational QOL program.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]