The Impact of Anxiety and Depression on the Quality of Life of Hemodialysis Patients

Material and Methods: The sample studied consisted of 395 hemodialysis patients. Data was collected by the completion of a specially designed questionnaire for the needs of the present study which apart from socio-demographic and clinical, it also included HADS scale to assess the level of anxiety and depression as well as the scale Missoula-VITAS Quality of Life Index (MVQOLI) to assess patients’ quality of life. Results: The results of this study showed that 47.8% had high anxiety levels and 38.2% had high levels of depression. The average total score of quality of life was found to be 17.14. It was also shown that the total score of quality of life presented statistically significant association with family status (p=0.007), educational level (p<0.001), the number of children (p=0.001), patients’ adherence to doctors’ orders (p=0.003) and proposed diet (p=0.002) and the relations of patients with healthcare professionals and the other patients (p<0.001). The multiple linear regression showed that the overall quality of life score was statistically associated with the levels of depression after adjusted for possible confounders. More specifically, it was found that total score of quality of life was 2.5 and 4.4 points lower for patients with moderate and high levels of depression, respectively, compared to patients with low levels of depression (p<0.001). Conclusions: Evaluation of anxiety and depression in conjunction with quality of life in hemodialysis patients should be an integral part of the therapeutic regimen.


Introduction
It is widely accepted that end stage renal disease patients experience various problems due to medical illness as well as psychological problems that exert a negative influence on the outcome of the disease. Anxiety and depression are the most common psychiatric disorders that goes in parallel with renal failure (Turkistani, Nuqali, Badawi, Taibah, Alserihy, Morad, & Kalantan, 2014;Feroze, Martin, Reina-Patton, Kalantar-Zadeh, & Kopple, 2010;Stein, Cox, Afifi, Belik, & Sareen, 2006). underestimate symptoms from mental dimension. This effort becomes highly confounded since symptoms of anxiety and depression usually overlap with the clinical symptomology of kidney disease, mainly uremic state. For instance, components of depression such as anorexia, fatigue, sexual and sleep disturbances share common characteristics with uremic state. Consequently, anxiety and depression extend the physical and cognitive impairment that experience hemodialysis patients and contribute significantly to the increase of hospitalization rate and use of health care services. According to estimates, 20-30% of dialysis patients experience depression, thus making an imperative need, the evaluation of depression in clinical routine (Chilcot et al., 2008;Cukor et al., 2007;Theofilou, 2013;McCann & Boore, 2000;Watnick et al., 2005;Cohen, Norris, Acquaviva, Peterson, & Kimmel, 2007). Anxiety and depression affect negatively the quality of hemodialysis patients' life (Unruh & Hess, 2007;Avramovic & Stefanovic, 2012).
The aim of the present study was to explore the impact of anxiety and depression on the quality of life of hemodialysis patients.

Study Design
The sample studied consisted of 395 patients (222 men and 173 women) undergoing hemodialysis. This sample was a convenience sample.
The study included all patients who met the inclusion criteria during the study period June 2014 to December 2014 and participated in the study after they had been orally informed and given consent. Criteria for enrolling a patient in the study were: comprehension of Greek language and being under hemodialysis.
The data collected for each patient included: a) socio-demographic characteristics: gender, age, marital status, education level, place of residence and number of children, b) clinical characteristics: if the patient was suffering from any other illness, the level of awareness of the health status, the years undergoing hemodialysis, the frequency and duration of hemodialysis, as well as information on how strictly they comply with treatment guidelines and the proposed diet and c) other variables such as the relation with the physicians and nurses, the relations with the social and family environment, whether they concealed the problem from the community, if they reported themselves as anxious and if they had help at home.

Mental Health Assessment
For the evaluation of the mental health of the patients, the scale that was used was "The Hospital Anxiety And Depression Scale (HADS)". This scale was proposed in 1983 by Zigmond AS & Snaith RP (Zigmond & Snaith, 1983). The HADS scale consists of 14 questions, of which seven evaluate the level of depression (questions 2, 4, 6, 8, 10, 12 and 14) and the other seven evaluate the anxiety level (questions 1, 3, 5 , 7, 9, 11 and 13) of the respondents. The range of the total score of anxiety and depression level is between 0 and 21. In addition, for both scores it has been proposed and the widely used in the literature following classification: 0-7 indicating no anxiety or depression, respectively, score 8-10 indicating moderate levels of anxiety or depression, respectively, and score> 11 indicates high levels of anxiety / depression. The HADs had high reliability and validity in Greek population by Mystakidou et al. in cancer patients (Mstakidou, Tsilika, Parpa, Katsouda, Galanos, & Vlahos, 2004) and by Michopoulos et al. (2008) in general hospital sample.

Quality of Life Assessment
To evaluate the quality of life of the patients the scale Missoula-VITAS Quality of Life Index (MVQOLI) was used. This scale has been translated and it was culturally adapted to the Greek data by Mrs. Theofilou et al. (Theofilou, Kapsalis, & Panagiotaki, 2012). Although there are two versions of the scale, one with 25 and a second one with 15 questions, in this survey the one with the 15 questions was used. This scale assesses five dimensions of quality of patients' life, the symptoms, functioning, interpersonal relationships, well-being and transcendent. For each dimension, three types of information are collected: (a) assessment (subjective measurement of the actual situation), (b) evaluation (degree of acceptance of the real situation) and (c) importance (the extent to which this dimension affects the actual quality of life).
The questions of each dimension expressing the "assessment" were graded in a 5-degree Likert scale from -2 to 2. Questions expressing "evaluation" were graded from -4 to 4, and the questions that express the "importance" were graded from 1 to 5. To calculate the total score of each dimension of quality of life, the scores of "appreciation" and "evaluation" were added and then multiplied this sum by the degree of "importance" ((estimate + evaluation) x importance). The total score of each dimension reflects the extent that this dimension affects the quality of life of patients. Higher scores indicate better quality of life. The average score of total quality of life ranged from 0 to 30.

Statistical Analysis
Normality tests of continuous variables were performed, using the Kolmogorov-Smirnov test and histograms. Nominal variables are presented using frequencies and percentages, whereas the continuous variables are presented with means and standard deviation or medians and interquartile range.
One-way ANOVA or Kruskal-Wallis test was used to test the existence of correlation between a quantitative continuous variable following the normal distribution or not, respectively, and a nominal variable with more than two categories. Also, independent samples t-test and the Mann-Whitney test was used to check the existence of correlation between a quantitative continuous variable following the normal distribution or not, respectively, and a nominal variable with 2 categories.
Multivariate linear regression was performed to explore the impact of anxiety and depression on patients quality of life after controlling for potential confounders such as socio-demographic factors, data on the underlying disease and the current state of health of participants. The results are presented with beta coefficients and 95% confidence interval (95% CI).
As statistically significant was the observed significance level of 5%. All statistical analyzes were performed with version 20 of SPSS program (SPSS Inc, Chicago, Il, USA). Other person at home. who helps in everyday tasks (Yes) 300 75,9

Anxiety and Depression
Figure 1 illustrates that the majority of participants experienced high levels of anxiety (47.8%), while in terms of depression, the majority was found to experience low levels of depression (41.8%) although high was the percentage of patients suffering from high level of depression (38.2%), too.

Quality of Life
The average total score of quality of life was found to be 17.14. Means or medians of all five dimensions are presented in Table 2 also. Table 3 shows the association of the total score of quality of life with various characteristics. It is observed that the total score of quality of life presents statistically significant association with family status, educational level and number of children. Specifically, the average total score of quality of life was higher in married people (p=0.007). Also, the average total score of quality of life of patients studied in university was higher than the others (p < 0.001). Moreover, a lower quality of life scores were found in patients that do not have children (p=0.001). Additionally, there is a statistically significant correlation between the total score of quality of life and patient information about the problem of health (p < 0.001). The mean total score of quality of life of patients who were not aware of the problem of health, was less than the patients who were very informed. A statistically significant correlation was found between the total score of quality of life and how strictly the patients followed the doctors' orders and proposed diet (p=0.003 & p=0.002, respectively). Specifically, the quality of life of patients who did not follow at all or they followed a little the instructions and the proposed diet was lower than in other patients. Statistically significant association was shown between the total score of quality of life and the relation of patients with medical/nursing staff and the other patients (p < 0.001). More specifically, the average total score of quality of life for patients who had very good relation with the medical and nursing staff and other patients was greater than in other patients. Moreover, there was a statistically significant correlation between the total score of quality of life and social issues such as the difficulties in the relations with social and family environment, hiding the problem from their social environment and the existence of home assistance for everyday activities. In more details, the average quality of life was greater for patients who did not have any difficulties in their family or social environment (p < 0.001), for those who did not hide their health problems from the community (p < 0.001) and for those who had home help for handling everyday (p < 0.001).   Table 4 represents the association between the levels of anxiety or depression and patients' quality of life. It was found that there was statistically significant association (p<0.001 respectively). More specifically patients with low levels of anxiety or depression had better quality of life compared to those with moderate or high levels of anxiety or depression.

Multivariate Linear Regression
The multiple linear regression (Table 5) showed that the overall quality of life score is statistically associated with the levels of depression after adjusted for possible confounders. More specifically quality of life is 2.5 and 4.4 points lower for patients with moderate and high levels of depression respectively than patients with low levels of depression (p < 0.001 respectively).

Discussion
The results of the present study showed that 47.8% of the participants experienced high level of anxiety while 38.2% experienced high level of depression. The average total score of quality of life was found to be 17.14.
Regarding anxiety, depression and quality of life, it was found that patients with low levels of anxiety or depression had better quality of life. The multiple linear regression showed that the overall quality of life score was statistically associated with the levels of depression after adjusted for possible confounders. More specifically quality of life is 2.5 and 4.4 points lower for patients with moderate and high levels of depression respectively when compared to other patients.
According to the literature, mainly depression is common to hemodialysis patients. Furthermore, decreased health related of life and increased levels of depression share common socio-demographic and clinical characteristics (Preljevic et al., 2013;Lee et al., 2013;Birmelé et al., 2012;Park et al., 2010;Kimmel & Patel, 2006). Park et al. (2010) showed that 31.9% of 160 hemodialysis patients experienced depression. The same researchers also showed inverse linear relation between depression and health related quality. Moreover, it was also shown that clinical and socio-demographic characteristics were associated with depression and health related quality of life. More in detail, advanced age (>60 years old), low hemoglobin level (<10g/dl) and low economic status were associated with depression whereas advanced age, female gender, diabetes mellitus, high comorbidity and hypoalbuminemia were associated with decreased health related quality of life. Drayer et al. (2006) who interviewed 62 hemodialysis outpatients showed that patients of younger age were depressed and reported lower quality of life. Cruz et al. (Cruz, Fleck, & Polanczyk, 2010) claimed that depression is a predictor index for low quality of life. Olaqunju et al. (Olaqunju, Campbell, & Adeyemi, 2015) who explored the association between anxiety/depression an the quality of life in 100 endstage renal disease patients showed that employment, married status, young age, and cost of treatment were related positively with quality of life. Moreover, anxiety/depression were independently related to quality of life. The results by Olaqunju et al. (2015) are similar with the present study which showed that the overall quality of life score was statistically associated with the levels of depression.  (Hmwe, Subramanian, Tan, & Chong, 2015) supported that early recognition and treatment of depression is a matter of high importance in hemodialysis patients.
Feroze et al. (Feroze, Martin, Reina-Patton, Kalantar-Zadeh, & Kopple, 2010) claimed that the psychiatric burden experienced end stage renal disease patients exert a negative effect on both quality of life and treatment.
A possibly responsible factor for the association between high levels of anxiety or depression and poor quality of life is attributed to poor compliance to therapy. More in detail, according to Ossareh et al., (Ossareh, Tabrizian, Zebarjadi, & Joodat, 2014) who explored depression in 150 hemodialysis patients claimed that a possible explanation for high levels of depression in hemodialysis patients was non adherence to medication while adherence or non-adherence to the therapeutic regimen was not significantly related to quality of life. However, treatment with antidepressants improved both quality of life and depression. Akman et al. (Akman, Uyar, Afsar, Sezer, Ozdemir, & Haberal, 2007) suggested that early diagnosis of depression in patients waiting for renal transplant contributes to the improvement of their quality of life.
Iyasere et al. (Iyasere, & Brown, 2014) showed that depression is a non-renal determinant of quality of life in older end stage renal disease patients, thus coming to similar conclusions with the present study which highlight the impact of anxiety and depression in hemodialysis patients.

Conclusions
Quality of life score was associated with the levels of depression after adjusted for possible confounders. More specifically, quality of life was 2.5 and 4.4 points lower for patients with moderate and high levels of depression, Measurement of quality of life should incorporate assessment of psychosocial variables in clinical practice and planning of interventional strategies to reduce the burden of illness.
Early intervention in the treatment of depression would have a positive effect on outcome of the disease.

Limitations of the Study
The study sample was not representative of hemodialysis patients in Greece, but a convenience sample. The relevant sampling method limits the generalizability of results. Also, the fact that the study was cross-sectional is not allowing the emergence of a causal relation between quality of life and socio-demographic and clinical variables.