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Original Article
26 (
1
); 47-53
doi:
10.4103/IJPC.IJPC_141_19

Assessment of Quality of Life among End-Stage Renal Disease Patients Undergoing Maintenance Hemodialysis

Department of Pharmacy Practice, Genesis Hospital, Kannur, Kerala, India
Department of Pharmacy Practice, Government Medical College, Pariyaram, Kerala, India
Department of Nephrology, Kmct Medical College, Manassery, Kerala, India
Department of Community Medicine, Government Medical College, Pariyaram, Kerala, India
Address for correspondence: Dr. Rajesh Penganazhi Kunnath, Flat No 1E, Skyline Crescendo, Chevarambalam, Chevayur PO, Kozhikode - 673 017, Kerala, India. E-mail: rajeshpkunnath@gmail.com
Licence

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Disclaimer:
This article was originally published by Wolters Kluwer - Medknow and was migrated to Scientific Scholar after the change of Publisher; therefore Scientific Scholar has no control over the quality or content of this article.

Abstract

Background:

Renal failure is a chronic disease that can seriously affect quality of life (QOL). Health-Related QOL represents the physical, psychological, and social domains of health that are influenced by a person's experience, beliefs, expectations, and perceptions. The aim of this study is to explore QOL of Stage 5 chronic kidney disease (CKD) patients on maintenance hemodialysis (MHD) in South India.

Materials and Methods:

This was a cross-sectional observational study conducted among patients with CKD undergoing MHD at 11 major centers in South India. Demographic data were collected using a predesigned questionnaire. QOL index was measured using the 26-item WHOQOL-BREF questionnaire, and statistical analysis was carried out using the SPSS version 24 (Academy of Medical Sciences, Kannur, Kerala, India).

Results:

Five hundred and three patients undergoing MHD were enrolled, and the following QOL scores were recorded: social relationship (51.65 ± 21.03), environmental (46.91 ± 19.29), psychological (41.07 ± 20.30), and physical health (40.17 ± 17.05). QOL of patients declined with aging in all four domains. Being male, younger, educated, and unmarried appeared to have a favorable effect on several aspects of patients' QOL.

Conclusion:

The evaluation of QOL in CKD patients undergoing hemodialysis showed that it was relatively compromised. Because the patients had a chronic, progressive irreversible disease, the most affected was physical domain. Age, education, employment, and marital status were found to affect one or more domains of QOL. Age and education are significant independent variables; as the age increases, QOL decreases, and higher the education better the QOL.

Keywords

Chronic kidney disease
maintenance hemodialysis
quality of life

INTRODUCTION

Chronic kidney disease (CKD) has become one of the major medical problems worldwide. According to a study conducted in the 2015 Global Burden of Disease (GBD), CKD ranked the 17th among causes of death globally (age-standardized annual death rate of 192 deaths per 100,000 population). In India, the GBD 2015 ranks CKD as the eighth leading cause of death.[1]

Renal failure is a chronic disease that can seriously affect quality of life (QOL) and specifically their social, financial, and psychological well-being.[234] QOL is defined as “An individual perception of their position in life in the context of culture and value system where they live, and in relation to their goals, expectations, standards, and concerns.” Health-Related QOL (HRQOL) represents the physical, psychological, and social domains of health that are influenced by a person's experience, beliefs, expectations, and perceptions.[5] In this scenario, QOL has become an important indicator of health care, patient experience, and measure of effectiveness in various chronic diseases. The assessment of QOL becomes mandatory as an outcome measure in the evaluation of adverse events and treatment effectiveness in various diseases conditions such as end-stage renal disease (ESRD), cardiovascular disease, malignancy, chronic obstructive pulmonary disease, and human immunodeficiency virus infection.[6] Patients with CKD may experience a negative impact on their QOL, which comes from the anxiety that can appear before and during the treatment.[7] There are various renal replacement therapies available that result in longer survival in Stage 5 CKD patients. Hemodialysis therapy is time-intensive, expensive, and requires fluid and dietary restrictions. Long-term dialysis therapy itself often results in loss of freedom; dependence on caregivers; disruption of marital, family, and social life; and reduced or loss of financial income. Due to these reasons, the physical, psychological, socioeconomic, and environmental aspects of life are negatively affected, leading to compromised QOL.[8] QOL in CKD patients is a unique, personal, nontransferable, and complex concept that is linked to human adaptive mechanisms, and it requires various factors related to psychological, environmental, social, and personal relationship dimensions.[9]

The aim of this study is to explore QOL of patients with Stage 5 CKD undergoing maintenance hemodialysis (MHD) using the WHOQOLBREF questionnaire.

MATERIALS AND METHODS

This is a cross-sectional observational study conducted among patients with CKD undergoing MHD at 11 major centers in India. Data were collected from these hospitals for a total duration of 6 months. Ethical approval for this study was obtained from the Institutional Review Board of Kannur Government Medical College, Kerala (ref no: A1/1839/2017APSC/IEC-07/2017). Patients with ESRD on MHD were included in this study. Demographic data were collected using a predesigned questionnaire. QOL index was measured using 26 items in the WHO-QOL BREF questionnaire. We included patients who had been on regular hemodialysis for at least 3 months.

The following criteria were used to exclude patients after the initial screening:

  • Patients undergoing peritoneal dialysis

  • Incompletely filled questionnaire.

The WHO-BREF questionnaire was translated into local language. Educated participants were encouraged to fill the questionnaire by themselves; however, for patients who were illiterate, questions were read out clearly by an investigator and responses were noted from a primary caretaker if applicable.

Sociodemographic factors such as age, gender, marital status, education, employment, and number of dialysis per week were collected using a structured questionnaire, and QOL was measured using the WHOQOL-BREF questionnaire. After explaining the purpose of this study, 530 patients were evaluated initially, of which 503 met the inclusion criteria and 27 were excluded due to incomplete responses.

The WHOQOL-BREF is a questionnaire that relies on assumption that the QOL is a subjective and multidimensional construct based on individual perception of QOL and is composed of positive and negative dimensions.[10] The WHOQOL-BREF contains 26 questions and is cross-culturally adapted and validated in Malayalam language. The questions are relating to the physical health, psychological, social, and environmental status of patients. Items G1 and G4 assess individual overall perception of QOL and health, respectively, and the remaining 24 questions are divided into four domains. Each item is rated by a 5-point Likert scale. Out of the four domains, one is physical health and others are psychological, social, and environmental domains. All domains have different raw score ranges; for uniformity, all raw scores were transformed to 0–100 scale using transformation formula.[11] A higher score indicates a better QOL. Descriptive statistics were used to analyze the mean domain scores and are presented as mean ± standard deviation (SD). Pearson's correlation coefficient was used to assess the inter-domain correlation between various demographic factors and domain scores.

Statistical analysis

SPSS version 23.0 was used for the analysis of data. Results of descriptive analysis were presented as mean ± SD, and inter-domain correlations between various demographic factors and domain scores were assessed using Pearson's correlation coefficient. Bivariate relationship between sociodemographic factors and QOL scores was analyzed using t-test and one-way analysis of variance. Post hoc analysis was performed for variables with more than two groups. Independent predictors of QOL were analyzed through multiple linear regression analysis. P < 0.05 was considered statistically significant.

RESULTS

Demographic characteristics

After explaining the purpose of the study, total 530 patients were evaluated, of which 503 patients met the inclusion criteria and 27 patients were excluded due to incomplete responses.

Majority of the respondents belong to age group above 60 years (47.91%); 73.76% were male. The male-to-female ratio was found to be 3:1. Among 503 patients on MHD, 55 (10.93%) were illiterate, 379 (75.35) were married, and 447 (88.86%) were unemployed. Patients undergo one, two, or three dialysis sessions per week. Majority of the patients (60.64%) undergo thrice weekly dialysis. The mean domain score was given in Table 1, and the demographic characteristics of the study population (n = 503) are presented in Table 2.

Table 1: Mean domain scores (descriptive statistics)
Domain Mean±SD
Physical health 40.17±17.05
Psychological 41.07±20.30
Social relationship 51.65±21.03
Environmental 46.91±19.29

SD: Standard deviation

Table 2: Characteristics of study population (n=503)
Characteristics n (%)
Age group (years)
 13-34 36 (7.16)
 35-59 226 (44.93)
 ≥60 241 (47.91)
Sex
 Male 371 (73.76)
 Female 132 (26.24)
Marital status
 Married 379 (75.35)
 Unmarried 54 (10.74)
 Widow 70 (13.92)
Education
 Illiterate 55 (10.93)
 Primary 185 (36.78)
 Secondary 205 (40.76)
 Higher/university 58 (11.53)
Employment
 Employed 56 (11.13)
 Unemployed 447 (88.86)
Number of dialysis/week
 Once/week 7 (1.39)
 Twice/week 191 (37.97)
 Thrice/week 305 (60.64)

Association between demographic characteristics and quality of life scores

Various demographic factors and their association with QOL were assessed in Stage 5 CKD patients on MHD [Table 3], which showed a bivariate relationship between demographic characteristics and domain scores (P = 0.005). A statistically significant relationship was observed between various age groups and different domains. The physical and psychological health of patients declined with aging (P = 0.001 and 0.009). Post hoc least significant difference (LSD) showed a significant difference in both mean physical and psychological health scores, as well as mean social relationship scores, between 13–34 years and ≥60 years and also between 35–59 and ≥60 years. Whereas, in the environmental domain, post hoc LSD showed a significant difference in mean scores between 13–34 years and 35–59 years as well as between 13–34 years and ≥60 years' age groups.

Table 3: Comparison of WHO-BREF domain mean scores, standard deviation, and significance based on sociodemographic variables
Variable Physical Psychological Social Environmental G1 G4
Age
 13-34 47.3611±14.89 48.36±18.52 59.67±15.54 54.33±18.09 3±0.99 2.89±1.06
 35-59 41.76991±18.0 42.53±22.47 53.61±23.49 46.99±21.20 2.55±1.13 2.52±1.05
 ≥60 37.60166±15.98 38.61±17.97 48.62±18.73 45.73±17.31 2.58±0.91 2.54±0.94
P 0.001 0.009 0.002 0.044 0.046 0.114
Sex
 Male 40.34±17.14 41.19±20.58 50.89±21.97 46.06±19.34 2.62±1.02 2.59±1.00
 Female 39.70±16.85 40.73±19.58 53.80±18.04 49.28±19.03 2.52±1.03 2.46±1.00
P 0.714 0.825 0.135 0.1 0.336 0.216
Education level
 Illiterate 36.55±16.77 37.64±17.82 45±23.01 43.15±18.84 2.15±0.97 2.24±0.98
 Primary 37.43±15.09 39.57±19.02 49.97±19.86 43.72±18.32 2.52±1.02 2.52±1.02
 Secondary 42.16±18.07 41.33±21.78 53.02±20.55 48.69±20.00 2.63±1.06 2.59±1.00
 Higher 45.33±17.68 48.19±19.83 58.53±22.44 54.33±17.69 3.14±0.71 2.86±0.96
P 0.001 0.02 0.003 0.001 <0.001 0.009
Job
 Working 49.91±17.36 52.35±19.28 60.20±22.48 59.36±19.96 3.27±1.008 3.16±0.898
 No job 38.98±16.65 39.69±20.01 50.60±20.63 45.38±18.67 2.51±0.999 2.47±0.989
P <0.001 <0.001 0.001 <0.001 <0.001 <0.001
Marital status
 Married 39.36±16.77 40.37±20.82 50.74±21.77 45.71±19.67 2.55±1.04 2.50±1.01
 Unmarried 49.11±15.16 49.96±18.60 60.96±18.00 54.30±17.70 3±0.78 3.00±0.89
 Widow 37.67±16.24 38.00±16.85 49.39±17.19 47.71±17.26 2.51±1.03 2.53±0.93
P <0.001 0.002 0.002 0.008 0.009 0.002
Number of dialysis/week
 1 53±17.330 53.857±24.89 58.857±19.0 57.429±18.884 2.286±0.95 3.571±1.13
 2 40.869±17.283 41.445±20.248 50.408±20.03 46.770±19.686 2.2597±1.07 2.513±1.015
 3 39.443±16.820 40.544±20.202 52.262±21.68 46.754±19.049 2.603±0.998 2.557±0.979
P 0.089 0.218 0.419 0.349 0.721 0.022

P significance (using one-way ANOVA); G1: Overall perception of quality of life; G4: Overall perception of general health (range of score 1-5). (P<0.05) indicate significant. ANOVA: Analysis of variance

A significant difference was observed in all the four domains based on the educational status of the patients. Educated patients (tertiary or higher education) had better QOL scores in physical (45.33 ± 17.68), psychological (48.19 ± 19.83), social (58.53 ± 22.44), environmental (54.33 ± 17.67) domains as well as in overall perception of QOL (3.14 ± 0.71) and overall perception of general health (2.86 ± 0.97). Post hoc LSD analysis showed a significant difference in mean physical health scores between illiterate patients and patients with secondary school education as well as illiterate patients and patients with higher education also between primary and secondary as well as primary and higher educated patients with P = 0.001. Moreover, in psychological domain, post hoc analysis revealed a significant difference in mean domain score between tertiary and all other education levels with P = 0.02. The post hoc LSD also showed a significant difference in mean environmental scores between illiterate patients and patients with higher education, between primary and secondary as well as primary and tertiary, between secondary and tertiary education (P = 0.001).

A better QOL was seen in employed patients when compared to unemployed which exhibited a significant difference in all the four domains as well as in overall perception of general health and overall perception of QOL with P < 0.05. QOL in unmarried people is better as compared to married people, which is found to be statistically significant. Comparison of the WHO-BREF domain mean scores, standard deviation, and significance based on sociodemographic variables are given in Table 3.

Further regression analysis was conducted which showed that age, employment, and education were independent predictors of QOL affecting one or more domains of the WHOQOL-BREF. Age was found to be a significant negative predictor physical (P = 0.000), psychological (P = 0.001) and social domain (P = 0.001), whereas employment status was found to be a significant negative predictor affecting physical health (P = 0.003), psychological domain (P = 0.003), and environmental domain (P = 0.001); in contrary, education was found to be a significant positive predictor in social and environmental domain with P = 0.014 and 0.003, respectively. We observed that gender, number of dialysis per week, and marital status were not associated with any of the four domains in multivariate analysis. Multiple linear regression analysis is given in Table 4.

Table 4: Pearson correlation among domain score
Domain Pearson correlation/regression analysis G1 G4 Physical health Psychological health Social relationship Environmental health
G1 r 1
P
G4 r 0.62 1
P <0.001
Physical health r 0.53 0.55 1
P <0.001 <0.001
Psychological health r 0.60 0.62 0.70 1
P <0.001 <0.001 <0.001
Social relationship r 0.49 0.47 0.58 0.61 1
P <0.001 <0.001 <0.001 <0.001
Environmental health r 0.58 0.53 0.68 0.67 0.63
P <0.001 <0.001 <0.001 <0.001 <0.001 1

r: Pearson correlation; P: Significance (two-tailed); G1: Overall perception of QOL (range of score: 1-5); G2: Overall perception of general health (range score: 1-5); Domain 1: Physical domain; Domain 2: Psychological domain; Domain 3: Social domain; Domain 4: Environmental domain. QOL: Quality of life

Quality of life scores and correlations among various domains of WHO Quality of Life-BREF

Bivariate Pearson correlation (two-tailed) was carried out, wherein a significant correlation among physical, psychological, social, and environmental domains was observed (P< 0.05). Furthermore, a statistically significant correlation was found to exist between overall perception of QOL and general health and scores obtained from different domains (P< 0.05). The strength of correlation among various domains was analyzed, a moderate correlation was observed between social domain with overall perception of QOL (G1) and overall perception of general health (G4) with a person's r = >0.3 and <0.5, and a strong inter-domain correlation was found in between rest of the domains. The details of Pearson correlation among various domains are given in Table 4.

Multiple linear regression analysis

In this study, there is a significant relationship between age and different domains such as physical, psychological, and environment with P = 0.006, 0.035, and 0.007, respectively. In physical health, an increase in age by 1 year causes a decrease in physical QOL by 0.179 units, whereas in psychological health and social relationship of patients, it declines by 0.166 units and 0.007 units, respectively [Table 5].

Table 5: Multiple linear regression analysis
QOL domain Unstandardized coefficients Standardized coefficient (β) t Significance
B SE
Physical health
 Age −0.179 0.065 −0.136 −2.748 0.006
 Education
  Illiterate −2.120 3.353 −0.039 −0.632 0.528
  Primary −2.642 2.639 −0.075 −1.001 0.317
  Secondary −0.566 2.537 0.016 0.223 0.824
 Job 9.882 2.495 0.181 3.961 <0.001
 Marital status
  Married −0.364 2.162 −0.009 −0.169 0.866
  Unmarried 5.846 3.222 0.108 1.815 0.070
Psychological health
 Age −0.166 0.079 −0.106 −2.111 0.035
 Education
  Illiterate −2.644 4.052 −0.041 −0.652 0.514
  Primary −2.358 3.188 −0.056 −0.739 0.460
  Secondary −2.086 3.066 −0.051 0.680 0.497
 Job 11.61 3.015 0.179 3.854 <0.001
 Marital status
  Married 0.447 2.613 0.009 0.171 0.864
  Unmarried 6.680 3.893 0.103 1.716 0.087
Social relationship
 Age −0.220 0.082 −0.135 −2.687 0.007
 Education
  Illiterate −7.557 4.206 −0.112 −1.797 0.073
  Primary −3.684 3.310 −0.085 −1.113 0.266
  Secondary −1.987 3.182 −0.046 −0.624 0.533
 Job 7.676 3.129 0.114 2.453 0.015
 Marital status
  Married −1.840 2.712 −0.038 −0.679 0.498
  Unmarried 3.552 4.041 0.053 0.879 0.380
Environment
 Age −0.096 0.074 −0.064 −1.288 0.198
 Education
  Illiterate −5.616 3.814 −0.091 −1.473 0.142
  Primary −5.254 3.001 −0.131 −1.751 0.081
  Secondary −1.491 2.886 −0.038 −0.517 0.606
 Job 12.279 2.837 0.199 4.328 <0.001
 Marital status
  Married −3.916 2.459 −0.088 −1.592 0.112
  Unmarried 2.832 3.664 0.046 0.773 0.440
G1 −0.001 0.004 −0.010 −0.203 0.839
 Age
 Education −0.692 0.202 −0.211 −3.427 0.001
  Illiterate −0.327 0.159 −0.154 −2.060 0.040
  Primary −0.260 0.153 −0.125 −1.706 0.089
  Secondary 0.614 0.150 0.187 4.097 <0.001
 Job
 Marital status
  Married −0.121 0.130 −0.051 −0.927 0.357
  Unmarried 0.275 0.194 0.084 1.420 0.156
G4
 Age −0.343 0.196 −0.107 −1.745 0.082
 Education
  Illiterate −0.069 0.156 −0.033 −0.445 0.656
  Primary −0.047 0.151 −0.023 −0.312 0.755
  Secondary 0.649 0.148 0.203 4.388 <0.001
 Job −0.146 0.128 −0.063 −1.141 0.254
 Marital status
  Married 0.350 0.175 0.110 2.003 0.046
  Unmarried −0.073 0.084 −0.038 −0.880 0.379

SE: Standard error, QOL: Quality of life

In categorical variables, the category unemployment is compared with the reference (working category), which showed a significant relationship between employment and domains such as physical, psychological, environmental, G1, and G2 with P < 0.05. Employed patients showed better QOL, greater psychological health, and social relationship by 11.617 and 7.676 units as compared to unemployed patients. Age and education are significant independent variables; as the age increases, QOL decreases, and higher the education better the QOL.

DISCUSSION

CKD patients undergoing MHD have to cope with the fact of having an incurable disease that requires painful treatment and causes limitations to life. They often end up having poor QOL. In this study, it was noticed that the best QOL domain was social relationship, with an average of 51.65 ± 21.03, followed by environmental (46.91 ± 19.29) and psychological (41.07 ± 20.30). It was found that psychological was the second most affected domain. Dialysis treatment is a repetitive and exhausting routine for CKD patients were as changes in lifestyle and occupational inactivity causes mood swings and emotional stress that affect mental and physical health of patients. Other factors such as dependence and restrictions imposed by treatment, fear of death, and alterations in bodily appearance may add a negative result in this scenario. The domain affected most adversely was physical health. The low scores clearly demonstrate that daily activities such as sleep and capacity to work were disrupted in ESRD patients due to physical pain and dependence on medical treatment.

Overall QOL is correlated with age. A common trend exists within all the domains and age ≥60, i.e., a negative correlation can be observed with respect to older age and physical, psychological, social, and environmental domains. This decline in scores for older age can be attributed to the fact that with increasing age, there is deterioration in physical status of the patient, i.e., energy, work capacity, and quality of sleep, and with increasing age, there is a decrease in scores of psychological domain. This may be due to various comorbidities, poor support from the family and society, financial burden which in turn drives them up in a state of solitude, blue mood, anxiety, and depression. Our findings also indicate that older patients had significantly lower QOL scores than younger patients in the social domain. This may be due to lack of solid personal relationships and dissatisfied sexual life. The environmental domain assesses the influence of factors such as environment, financial resources, health-related information, transport facilities, and insurance schemes. The decline in scores may be due to unhealthy living conditions, lack of adequate transport facilities, and absence of social support groups for the elderly unlike in developed countries. Although a number of government schemes exist (like Karunya, employees' state insurance), most of the patients are unable to avail these because they do not fulfill the inclusion criteria. Similarly, Mandoorah et al.[12] showed that patients older than 60 years had a worst report of QOL. In contrary, the study done by Joshi et al.[13] revealed that older patients had better QOL than younger patients in social domain.

This study claimed that a better educational background positively impacted the patient's QOL. They are directly proportional. The level of education has been identified as a predictor of good health because more the academic qualifications, greater the chances of being employed and hence a reliable income and better socioeconomic conditions. Literate patients have a better understanding of the disease and awareness regarding its treatment and lifestyle modifications. Hence, in this study, higher scores in all the domains are observed in participants who have received tertiary education and in those who are employed. In this study, only 11.13% of the patients were employed and the remaining were not working either due to being retired or unable to work due to physical limitations. This is in line with the study conducted by Theofilou[2] and Gerasimoula et al.[14] Whereas, the study by Joshi et al.[13] did not come across any significant association between QOL and educational status.

While we expected gender to affect QOL in CKD patients, we did not come across any significant results on comparing scores in both the sexes. In contrast, the study conducted by Sathvik et al.[8] revealed that females have a lower score in psychological and environmental domains compared to males.

Marital status significantly affects QOL in all domains. Unmarried people had better scores, whereas married people scored lower. This may be because married people have to run the family which increases financial stress and dependence and finally affects QOL. In India, due to extended family structure, even unmarried people get adequate emotional and financial support from their families. While many previous studies have indicated that married people have higher QOL,[2] a study carried out in Nepal[13] is in line with our findings.

Although we expected the QOL to improve in patients undergoing thrice weekly dialysis, it was found to decline. This may be owing to the fact that as the number of dialysis increases, the patient has to spare more time and resources. Furthermore, since many of them stay far off from the dialysis centers, they have to spend extra money to meet their travel expenses and also the medication costs. Apart from this, the surplus charges also include the cost of replacing the dialyzer after the definite time interval.

Limitations

First, the absence of control group limits the interpretation of the comorbidities on HRQOL. Since the questionnaire was filled by the patients themselves, the responses may be based on their personal perceptions and understanding of the questions. We did not include the duration on MHD and also information on diet.

CONCLUSION

The evaluation of the QOL in CKD patients undergoing hemodialysis showed that it was relatively compromised. Because the patients had a chronic, progressive irreversible disease, the most affected was physical domain. Age, education, employment, and marital status were found to affect one or more domains of QOL. Age and education are significant independent variables; as the age increases, QOL decreases, and higher the education better the QOL. It was found that studies on QOL offer strategies to health workers that allow them to measure physical, psychological, and environmental necessities in order to meet the real needs of patients undergoing renal therapy. To our knowledge, no such study has been conducted in Kerala, and this study provides an insight on how dialysis affects various dimensions of life.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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