Abstract
Purpose
The aims of the study are to explore the prevalence and risk factors of anxiety and depression in hemodialysis (HD) patients and to study their relationship with quality of life (QOL).
Methods
This cross-sectional study involved 298 HD patients. Sociodemographic, clinical, and laboratory data of the patients were obtained from their records. Anxiety and depression were assessed by utilizing Hospital Anxiety and Depression Scale (HADS). In addition, QOL of the patients were evaluated by fulfilling the Kidney Disease Quality of Life-36.
Results
This study included 298 HD patients (male 59.1%) with a median age of 49 years. Abnormal and borderline cases of anxiety were recognized in 49.6%, 26.2% of the patients, respectively, while depression cases and borderline cases were identified in 55 and 28.2% of the patients, respectively. Percentages of females (41 and 48% vs 26.4%, respectively), and patients who were not working (92.3 and 93.9% vs 72.2%, respectively) increased significantly in borderline and abnormal anxiety groups. Patients who did not work, led an inactive lifestyle, and smoked had considerably greater percentages in the borderline and abnormal HADS-depression categories than normal patients. Abnormal cases of depression and anxiety had significantly longer duration of HD than other two groups. Abnormal and borderline cases of anxiety and depression had worse QOL components than the normal patients.
Conclusion
Anxiety and depression are prevalent among HD patients in Egypt, and several sociodemographic and clinical risk factors are associated. In addition, these mental disorders are associated with poor QOL.
Keywords: Anxiety, Depression, Hemodialysis, Quality of life, Mental disorders
Introduction
End stage kidney disease (ESKD) is a global public health problem since the patients must live on hemodialysis (HD) for the remainder of their lives unless they have a successful kidney transplant [1]. In comparison to the general population, HD patients had a higher mortality rate due to several factors that might negatively affect these patients' health [2]. Psychiatric disorders are common in patients with chronic illnesses including ESKD and HD patients. Anxiety and depression are two of these conditions [3–6], with estimates ranging from 20 to 45% [7–9] and 25 to 50% [3, 5, 8, 10] in HD patients, respectively.
These diseases can lead to poor dialysis adherence and disruptive attitudes, such as missed HD treatments and shorter HD session duration [11–13]. Furthermore, these mental problems are linked to an increase in suicide, hospitalization, and death [12, 14]. Moreover, psychological, physical, and lifestyle problems have been shown to have an impact on HD patients' health-related quality of life (HRQOL) [15, 16]. Depression has been linked to demographic, socioeconomic, and clinical risk variables such as younger age, female gender, lower educational level, unemployment, hypertension, smoking status, and diabetes in HD patients [17, 18].
The Hospital Anxiety and Depression Scale (HADS) questionnaire is used to assess anxiety and depression in patients with various medical disorders. The HADS self-assessment tool is designed for early detection of potential mental disease that may improve with therapy [19].
To best of our knowledge, there are few studies which addressed prevalence and determinants of anxiety and depression in HD patients in Egypt. Thus, the aims of the current study were to explore the prevalence and risk factors of these psychiatric disorders in Egyptian HD patients and to discover the relationship between these disorders and HRQOL in those patients.
Patients and methods
This multi-center cross-sectional study comprised 298 HD patients recruited from three different HD units in Egypt's Dakahlia and Gharbia governorates between January and May 2021. Adult patients who have been on HD for more than 3 months met the inclusion criteria. Patients with cognitive dysfunction, terminal cancer, severe organ dysfunction, hearing or visual impairments were not eligible for the trial. The sample size was selected as a convenience sample; all patients who met the inclusion criteria were invited to participate in the study, unless they were excluded by any of the exclusion criteria or declined to participate. Informed written consent was obtained from all participants prior to their enrollment in the study. The study was approved by the Mansoura Faulty of Medicine Institutional Research Board (Approval number R.22.07.1767).
Patients' sociodemographic data, such as age, gender, marital status, residence, level of education, job position, socioeconomic status (SES), and smoking behaviors, were collected. In addition, clinical characteristics such as hemodialysis duration, the existence of any comorbidities, and medication history were documented.
Blood sampling and laboratory tests
Just before starting the first HD session of the week, blood samples were taken from the arteriovenous fistula. An automated analyzer was used to perform routine laboratory tests on the same day of blood sampling.
Hospital anxiety and depression scale (HADS)
The patients completed an Arabic-language version of the HADS questionnaire. The HADS questionnaire is a tool that uses two separate subscales to assess anxiety and depression. The HADS has proven to be a valid instrument for use in general population [20], patients with different diseases [21–23] and patients with kidney disease [24, 25]. All the questions are graded on a four-point Likert scale (from 0 to 3). Patients with a score of 7 or less are deemed normal for depression and anxiety, those with a score of 8–10 are considered borderline for depression and anxiety (borderline cases), and those with a score of 11–21 are considered abnormal for depression and anxiety (cases) [26].
The Kidney Disease Quality of Life-36 (KDQOL-36™)
KDQOL-36 was used to assess HRQOL of the studied patients. The original version included the Medical Outcomes Study 36 as a generic chronic illness core, as well as items specific to kidney disease patients. It consisted of 36 questions, with questions 1–12, 13–16, 17–28, and 29–36 yielding the mental health composite (MHC), physical health composite (PHC), burden of renal disease, symptom/problem list, and effect of kidney disease components of QOL, respectively. The average values for these five KDQOL-36 components range from 0 to 100, with higher scores suggesting better HRQOL. [27].
Statistical analysis
Parametric and non-parametric continuous data were expressed as mean ± SD and median (minimum–maximum), respectively. Categorical data were expressed as number (percentage). Kolmogorov–Smirnov test was used to test for normality. Chi-square test was used to compare categorical variables. Analysis of Variance (ANOVA) test was used to compare parametric variables, while Kruskal–Wallis one-way analysis of variance was used to compare non-parametric variables between 3 subgroups of anxiety and depression. Univariate and multivariate linear regression analysis were used to discover the most significant associated factors of anxiety, depression and HRQOL in this study. P value less than 0.05 was considered to be significant. The tests were performed using SPSS 25 for personal computers.
Results
In the current study, 298 HD patients were included, with a median age of 51 years and a male preponderance (59.1%). Table 1 shows the sociodemographic, clinical, therapeutic, and laboratory features of the individuals investigated. The bulk of the patients (71.8%) were married, and almost one-quarter were illiterate. Less than half of the patients (47%) were from low-income families. HD lasted an average of 5 years. The majority of patients (61.4%) had hypertension, 14.4% had diabetes, and 13.4% had no comorbidities. Calcium and iron supplements were given to the great majority of patients (78.9% and 73.2%, respectively). Patients' hemoglobin levels averaged 10.47 gm/dl, while their serum calcium, phosphorus, and albumin levels were all within normal limits. TSAT was lower than expected, although serum ferritin and iPTH were higher (Table 1).
Table 1.
Sociodemographic, clinical, therapeutic and laboratory data of the studied patients (n = 298)
| Variable | All (n = 298) |
|---|---|
| Sociodemographic data | |
| Age (years) | 51(19–90) |
| Gender | |
| Male | 176(59.1%) |
| Female | 122(40.9%) |
| Married | 214(71.8%) |
| Live alone | 51(17.1%) |
| Residence | |
| Urban | 140(46.9%) |
| Rural | 158(53.1%) |
| Educational level | |
| Non-educated | 73(24.5%) |
| Low school | 33(11.1%) |
| Middle school | 42(14.1%) |
| High school | 109(36.6%) |
| College degree | 37(12.4%) |
| Post-graduate | 4(1.3%) |
| Occupational status | |
| Working | 35(11.7%) |
| Not working | 263(88.3%) |
| Active lifestyle | 53(17.8%) |
| Socioeconomic status | |
| Low | 140(47%) |
| Average | 153(51.3%) |
| High | 5(1.7%) |
| Smoking | |
| Non-smoker | 255(85.6%) |
| Smoker | 43(14.4%) |
| Clinical data | |
| Time since starting HD (years) | 5(0.1–30) |
| Associated comorbidities | |
| No comorbidities | 40(13.4%) |
| Diabetes | 43(14.4%) |
| Hypertension | 183(61.4%) |
| Psychiatric | 9(3%) |
| COPD | 4(1.3%) |
| IHD | 16(5.4%) |
| Therapeutic data | |
| No medications | 2(0.7%) |
| Erythropoietin stimulating agents | 155(52%) |
| Calcium supplements | 235(78.9%) |
| Iron supplements | 218(73.2%) |
| Antihypertensives | 188(63.1%) |
| Antidiabetics | 59(19.8%) |
| Laboratory data | |
| Blood hemoglobin (gm/dl) | 10.47 ± 1.3 |
| Serum albumin (gm/dl) | 4(3–4.5) |
| Serum calcium (mg/dl) | 8.5(5.2–13) |
| Serum phosphorus (mg/dl) | 4.6(1.9–10.6) |
| iPTH (pg/ml) | 324.5(4–1991) |
| TSAT (%) | 21(5–59) |
| Serum ferritin (ng/ml) | 281.3(12.6–1375.9) |
HD hemodialysis, COPD chronic obstructive pulmonary disease, IHD ischemic heart disease, iPTH intact parathyroid hormone, TSAT transferrin saturation
The data represented as median (min–max), mean ± SD or number (percentage)
Regarding HADS-anxiety, the median score was 11, and nearly half of the patients were anxious (49.6%), 26.2% of patients were borderline anxious, and 24.2% were normal. The median HADS-depression score was 10, with normal, borderline, and abnormal cases accounting for 16.8, 28.2, and 55% of the patients, respectively. Table 2 also included data on the patients' HRQOL.
Table 2.
HADS score and HRQOL in the studied patients
| Variable | The patients (n = 298) |
|---|---|
| HADS-Anxiety: median (min–max) | 11(0–21) |
| Normal | 72(24.2%) |
| Borderline | 78(26.2%) |
| Abnormal | 148(49.6%) |
| HADS-Depression: median (min–max) | 10(0–20) |
| Normal | 50(16.8%) |
| Borderline | 84(28.2%) |
| Abnormal | 164(55%) |
| HRQOL domains | |
| Symptom/problem list | 70.83(0–100) |
| Effect of kidney disease | 65.63(0–100) |
| Burden of kidney disease | 15.62(0–100) |
| Physical health composite | 32.64(16.2–57.90) |
| Mental health composite | 36.59(12.8–60.7) |
HADS hospital anxiety and depression scale, HRQOL health-related quality of life, MHD maintenance hemodialysis
The data presented as number (percentage) or median (min–max)
As regard HADS-anxiety subgroups, female percentages increased significantly in borderline and abnormal groups (41 and 48% vs 26.4%, respectively). Patients who were not working (92.3 and 93.9% vs 72.2%, respectively) and had an inactive lifestyle (87.2 and 88.5% vs 63.9%, respectively) were considerably more borderline and abnormal than normal patients. Smokers were substantially more common in the borderline and abnormal groups than in the normal group (20.5 and 16.9% vs 2.8%). The duration of HD in borderline and abnormal cases was much longer than in normal people (median was 6 and 6 vs 3 years). However, there were no statistically significant variations in age, marital status, living alone, residence, educational level, or socioeconomic status amongst the groupings. Serum phosphorus levels in normal people were substantially higher than in borderline and abnormal patients (5.1 vs 4.5 and 4.4 mg/dl, respectively). The remaining laboratory data, however, showed no significant variance (Table 3).
Table 3.
Comparison between anxiety and depression subgroups regarding socio-demographic, medical and laboratory data
| HADS-anxiety | HADS-depression | |||||||
|---|---|---|---|---|---|---|---|---|
| Normal (n = 72) | Borderline (n = 78) | Abnormal (n = 148) | P | Normal (n = 50) | Borderline (n = 84) | Abnormal (n = 164) | P | |
| Sociodemographic data | ||||||||
| Age | 51(19–77) | 49(27–83) | 52(23–90) | 0.975 | 45(21–71) | 54(12–81) | 48(7–90) | 0.164 |
| Gender | ||||||||
| Male | 53(73.6%) | 46(59%) | 77(52%) | 0.009 | 35(70%) | 46(54.8%) | 95(57.9%) | 0.202 |
| Female | 19(26.4%) | 32(41%) | 71(48%) | 15(30%) | 38(45.2) | 69(42.1%) | ||
| Married | 58(80.5%) | 52(66.7%) | 104(70.3%) | 0.252 | 39(78%) | 61(72.6%) | 114(69.5%) | 0.619 |
| Live alone | 11(15.2%) | 13(16.6%) | 27(18.2%) | 0.857 | 5(10%) | 14(16.7%) | 32(19.5%) | 0.358 |
| Residence | ||||||||
| Urban | 36(50%) | 38(48.7%) | 66(44.6%) | 0.845 | 24(48%) | 37(44%) | 79(48.2%) | 0.829 |
| Rural | 36(50%) | 40(51.3%) | 82(55.4%) | 26(52%) | 47(56%) | 85(51.8%) | ||
| Education | ||||||||
| Non-educated | 14(19.4%) | 16(20.5%) | 43(29.1%) | 0.194 | 7(14%) | 25(29.8%) | 41(25%) | 0.128 |
| Low school | 7(9.7%) | 6(7.7%) | 20(13.5%) | 3(6%) | 12(14.3%) | 18(11%) | ||
| Middle school | 11(15.3%) | 9(11.5%) | 22(14.9%) | 8(16%) | 6(7.1%) | 28(17.1%) | ||
| High school | 24(33.3%) | 35(44.9%) | 50(33.8%) | 21(42%) | 27(32.1%) | 61(37.2%) | ||
| College degree | 14(19.4%) | 11(14.1%) | 12(8.1%) | 10(20%) | 13(15.5%) | 14(8.5%) | ||
| Post-graduate | 2(2.8%) | 1(1.3%) | 1(0.7%) | 1(2%) | 1(1.2%) | 2(1.2%) | ||
| Occupational status | ||||||||
| Working | 20(27.8%) | 6(7.7%) | 9(6.1%) | < 0.001 | 12(24%) | 5(6%) | 18(11%) | 0.007 |
| Not working | 52(72.2%) | 72(92.3%) | 139(93.9%) | 38(76%) | 79(94%) | 146(89%) | ||
| Active lifestyle | 26(36.1%) | 10(12.8%) | 17(11.5%) | < 0.001 | 26(52%) | 9(10.7%) | 18(11%) | < 0.001 |
| Socioeconomic status | ||||||||
| Low | 36(50%) | 38(48.7%) | 66(44.6%) | 0.636 | 24(48%) | 42(50%) | 74(45.1%) | 0.682 |
| Average | 34(47.2%) | 40(51.3%) | 79(53.4%) | 25(50%) | 42(50%) | 86(52.4%) | ||
| High | 2(2.8%) | 0 | 3(2%) | 1(2%) | 0 | 4(2.4%) | ||
| Smoking | ||||||||
| Non-smoker | 70(97.2%) | 62(79.5%) | 123(83.1%) | 0.004 | 49(98%) | 73(86.9%) | 133(81.1%) | 0.011 |
| Smoker | 2(2.8%) | 16(20.5%) | 25(16.9%) | 1(2%) | 11(13.1%) | 31(18.9%) | ||
| Clinical data | ||||||||
| Time since starting HD | 3(0.25–21) | 6(0.5–24) | 6(0.1–30) | 0.001 | 3.5(0.25–25) | 5(0.5–21) | 6(0.1–30) | 0.013 |
| Associated comorbidities | ||||||||
| No comorbidities | 10(13.9%) | 8(10.3%) | 22(14.9%) | 0.621 | 5(10%) | 14(16.7%) | 21(12.8%) | 0.517 |
| Diabetes | 12(16.7%) | 13(16.7%) | 18(12.1%) | 0.612 | 7(14%) | 13(15.4%) | 23(14%) | 0.872 |
| Hypertension | 41(56.9%) | 48(61.5) | 94(63.5%) | 0.643 | 32(64%) | 56(66.7%) | 95(57.9%) | 0.375 |
| Psychiatric | 0 | 5(6.4%) | 4(2.7%) | 0.065 | 1(2%) | 2(2.4%) | 6(3.7%) | 0.739 |
| COPD | 2(2.8%) | 1(1.3%) | 1(0.7%) | 0.456 | 2(4%) | 0 | 2(1.2%) | 0.148 |
| Therapeutic data | ||||||||
| No medications | 0 | 1(1.3%) | 1(0.7%) | 1 | 0 | 0 | 2(1.2%) | 0.693 |
| Erythropoietin | 40(55.6%) | 33(42.3%) | 82(55.4%) | 0.136 | 29(58%) | 42(50%) | 84(51.2%) | 0.639 |
| Calcium supplements | 48(66.7%) | 69(88.5%) | 118(79.7%) | 0.005 | 29(58%) | 74(88.1%) | 132(80.5%) | < 0.001 |
| Iron supplements | 42(58.3%) | 61(78.2%) | 115(77.7%) | 0.005 | 22(44%) | 65(77.4%) | 131(79.9%) | < 0.001 |
| Antihypertensives | 41(56.9%) | 49(62.8%) | 98(66.2%) | 0.408 | 32(64%) | 61(72.6%) | 95(57.9%) | 0.075 |
| Antidiabetics | 12(16.7%) | 17(21.8%) | 30(20.3%) | 0.718 | 8(16%) | 19(22.6%) | 32(19.5%) | 0.643 |
| Laboratory data | ||||||||
| Blood hemoglobin (gm/dl) | 10.67 ± 1.4 | 10.55 ± 1.2 | 10.35 ± 1.3 | 0.272 | 10.39 ± 1.2 | 10.24 ± 1.1 | 10.59 ± 1.4 | 0.187 |
| Serum albumin (gm/dl) | 4(3–4.4) | 4(3.6–4.3) | 3.8(3.1–4.5) | 0.148 | 4(3–4.4) | 4(3.1–4.4) | 3.9(3.4–4.5) | 0.315 |
| Serum calcium (mg/dl) | 8.25(5.8–9.7) | 8.55(6.6–10.1) | 8.5 (5.2–13) | 0.394 | 8.3(6.2–9.7) | 8.3(6–9.8) | 8.5(5.2–13) | 0.059 |
| Serum phosphorus (mg/dl) | 5.1(2.6–10.6) | 4.5(2–10.2) | 4.4(1.9–10.6) | < 0.001 | 5.1(2.1–10.2) | 4.6(2.4–9.5) | 4.4(1.9–10.6) | 0.034 |
| iPTH (pg/ml) | 257(36.9–1559) | 375(44.6–1991) | 324.5(4–1978) | 0.950 | 398.5(36.9–1991) | 327.5(4.6–1149) | 304.1(4–1978) | 0.279 |
| TSAT (%) | 22(8–45) | 21(5–39) | 21(7–59) | 0.575 | 22(5–45) | 21(12–59) | 21(7–39) | 0.776 |
| Serum ferritin (ng/ml) | 364.3(13.5–797.3) | 251(12.6–1375.9) | 353.28(53.8–1139.7) | 0.884 | 316.3(12.6–1375.9) | 280(71.4–848.4) | 282.6(13.5–1139.7) | 0.783 |
The data represented as median (min–max), mean ± SD or number (percentage)
The bold P values mean that they were statistically significant
HD hemodialysis, COPD chronic obstructive pulmonary disease, IHD ischemic heart disease, iPTH intact parathyroid hormone, TSAT transferrin saturation
Patients who did not work, led an inactive lifestyle, and smoked had considerably greater percentages in the borderline and abnormal HADS-depression categories than normal patients. Age, gender, marital status, living alone, residence, educational level, and socioeconomic status, on the other hand, did not show statistically significant variations. The duration of HD in borderline and abnormal cases was much longer than in normal people (median was 5 and 6 vs 3.5 years). Serum phosphorus levels in normal people were significantly higher than in borderline and abnormal patients (5.1 vs 4.6 and 4.4 mg/dl, respectively). However, there was no significant variation in the remaining laboratory results (Table 3).
When the significant socioeconomic, clinical, and laboratory variables from the HADS-anxiety and depression subgroups were entered into a multiple linear regression analysis equation, the female gender and cigarette smokers were the most significant predictors of anxiety (Beta = − 0.270 and 0.134, P = < 0.001 and 0.043, respectively). While inactive life style, female gender, and cigarette smokers were the most significant predictors of depression (Beta = − 0.227, − 0.169, and 0.135, P = < 0.001, 0.009, and 0.041, respectively) Table 4.
Table 4.
Univariate and multivariate linear regression analysis of HADS-anxiety and HADS-depression
| HADS-anxiety | HADS-depression | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | Univariate analysis | Multivariate analysis | |||||||||
| Beta | P value | Beta | P value | Confidence interval | Beta | P value | Beta | P value | Confidence interval | |||
| Lower bound | Higher bound | Lower bound | Higher bound | |||||||||
| Female gender | − 0.174 | 0.003 | − 0.270 | < 0.001 | − 3.084 | − 1.112 | − 0.119 | 0.040 | − 0.169 | 0.009 | − 2.037 | − 0.301 |
| Cigarette smoker | 0.152 | 0.009 | 0.134 | 0.043 | 0.046 | 2.780 | 0.140 | 0.016 | 0.135 | 0.041 | 0.053 | 2.504 |
| Inactive lifestyle | − 0.241 | < 0.001 | − 0.123 | 0.056 | − 2.609 | 0.081 | − 0.277 | < 0.001 | − 0.227 | < 0.001 | − 3.337 | − 0.968 |
| Duration of hemodialysis | 0.135 | 0.021 | 0.086 | 0.189 | − 0.033 | 0.164 | 0.161 | 0.006 | 0.105 | 0.107 | − 0.016 | 0.161 |
| Occupational status | 0.084 | 0.146 | − 0.070 | 0.272 | − 2.633 | 0.744 | 0.029 | 0.619 | 0.049 | 0.439 | − 0.919 | 2.109 |
| Serum phosphorus | − 0.199 | 0.001 | − 0.032 | 0.624 | − 0.444 | 0.267 | − 0.119 | 0.059 | − 0.080 | 0.219 | − 0.518 | 0.120 |
The bold P values mean that they were statistically significant
When the five KDQOL-36 components were examined across the HADS-anxiety and depression subgroups, the HRQOL component scores were considerably higher in normal patients compared to borderline and abnormal cases, indicating that normal patients have a better quality of life (Tables 5, 6). Univariate linear regression analysis were performed for all variables regarding HRQOL and showed that male gender, living alone, active lifestyle, anxiety, and depression were significant associates with HROL (Beta = 0.168, − 0.125, 0.173, − 0.459, and − 0.379, respectively, P = 0.004, 0.041, 0.003, < 0.001, and < 0.001, respectively). Entering these variables into multilinear regression analysis equation to identify the most significant associates of HRQOL resulted in exclusion of male gender, living alone and active lifestyle from being significant associates. Anxiety was the most significant associate of HRQOL (Beta = − 0.381, P = < 0.001) followed by depression (Beta = − 0.142, P = 0.25) [Table 7].
Table 5.
Health-related quality of life data of studied patients across HADS-anxiety subgroups
| Normal (n = 72) | Borderline (n = 78) | Abnormal (n = 148) | P | |
|---|---|---|---|---|
| Symptom/problem list | 81.25(25–100) | 70.83(14.5–100) | 64.58(0–100) | < 0.001 |
| Effect of kidney disease | 75(0–100) | 64(12.5–100) | 57.81(0–100) | < 0.001 |
| Burden of kidney disease | 25(0–87.5) | 12.5(0–75) | 12.5(0–75) | < 0.001 |
| Physical health composite | 35.71(16.2–56.5) | 30.74(21.1–47.1) | 32.13(18.6–57.9) | 0.007 |
| Mental health composite | 45.37(24.6–60.7) | 36.26(21.3–49.9) | 35.04(12.8–49.5) | < 0.001 |
The data represented as median (min–max)
The bold P values mean that they were statistically significant
Table 6.
Health-related quality of life data of studied patients across HADS-depression subgroups
| Normal (n = 50) | Borderline (n = 84) | Abnormal (n = 164) | P | |
|---|---|---|---|---|
| Symptom/problem list | 79.17(14.5–100) | 66.67(4.1–100) | 70.83(0–100) | 0.027 |
| Effect of kidney disease | 75(0–100) | 65.63(12.5–100) | 59.38(0–100) | 0.001 |
| Burden of kidney disease | 25(0–81.2) | 12.5(0–81.2) | 12.5(0–100) | < 0.001 |
| Physical health composite | 38.27(21.2–57.9) | 32.48(18.6–51) | 31.56(16.2–51.6) | < 0.001 |
| Mental health composite | 46.8(24.6–60.7) | 36.72(21.3–58) | 35.54(12.8–59.7) | < 0.001 |
The data represented as median (min–max)
The bold P values mean that they were statistically significant
Table 7.
Univariate and multivariate linear regression analysis of total score of QOL
| Univariate analysis | Multivariate analysis | |||||||
|---|---|---|---|---|---|---|---|---|
| Beta | P value | Confidence interval | Beta | P value | Confidence interval | |||
| Lower bound | Higher bound | Lower bound | Higher bound | |||||
| Gender (Male) | 0.168 | 0.004 | 5.401 | 27.827 | 0.043 | 0.433 | − 6.344 | 14.775 |
| Live alone | − 0.125 | 0.041 | − 31.518 | − 0.657 | − 0.078 | 0.144 | − 23.511 | 3.455 |
| Active lifestyle | 0.173 | 0.003 | 7.795 | 36.959 | 0.083 | 0.134 | − 3.652 | 27.156 |
| Anxiety | − 0.495 | < 0.001 | − 7.415 | − 4.931 | − 0.381 | < 0.001 | − 6.203 | − 3.181 |
| Depression | -0.379 | < 0.001 | − 6.771 | − 3.801 | − 0.142 | 0.025 | − 3.695 | − 0.254 |
The bold P values mean that they were statistically significant
Discussion
Anxiety and depression are common among HD patients [3, 5], and they have been linked to worse HRQOL [16]. Furthermore, certain recognized risk factors for these illnesses exist [17]. However, these disorders are understudied, with minimal research focusing on them in Egypt. As a result, the current study sought to determine the prevalence of anxiety and depression in Egyptian HD patients, as well as their determinants and links to HRQOL.
Anxiety was common among the patients in this study, with abnormal cases having a frequency of 49.6% and borderline cases having a frequency of 26.2%. Furthermore, depression was common, accounting for 55% of abnormal and 28.2% of borderline cases, respectively. The current study's prevalence of anxiety and depression is comparable to that of Kamel et al. [28] on 524 Egyptian HD patients. However, this finding is significantly higher than that obtained by Turkistani et al. [29], who evaluated 286 Saudi HD patients and discovered that 21.1 and 23.3% of patients, respectively, had elevated anxiety and depression scores. Furthermore, Mosleh et al. [30] showed that 19.7 and 24.6% of 122 HD patients, respectively, had abnormal anxiety and depression symptoms, which is much lower than our findings. Furthermore, the current prevalence is somewhat higher than that reported by Yoong et al. [8]. The aforementioned studies used HADS as a tool to assess anxiety and depression in dialysis patients. The difference in prevalence of these disorders between the studies might be due to different geographic areas and thence differences in socioeconomic statuses. Our prevalence is comparable to the prevalence mentioned by another Egyptian study but differs with other non-Egyptian studies.
In the current study, females reported significantly higher levels of anxiety than males. This finding is congruent with those of Gerogianni et al. [31], as well as Delgado-Domínguez et al. [32]. However, this finding contradicts the findings of Kamel et al. [28], Kao et al. [33] and Yoong et al. [8], who found no significant differences in anxiety levels between men and women in respective investigations. Several cognitive and physiological activities associated with anxiety have shown significant gender variations [34]. Estrogen and progesterone appear to have a significant impact on the activities of anxiety-related neurotransmitter systems and fear extinction [34], whereas testosterone has anxiolytic properties [35]. Females may be more prone to anxiety disorders than males due to variations in occupational level, socioeconomic situations, cultural restraints, and social responsibilities [36]. In addition, females in Arabic countries have more restrictions in lifestyle and more responsibilities than females. Thus, they might be more prone to anxiety disorders. Asher et al. concluded in their review that females report more social anxiety than men. They explained this conclusion by self-construal theory, and greater personal interaction and greater reduction in daily life satisfaction in women than men [37].
In the current study, smokers had significantly higher percentages of borderline and abnormal anxiety cases than nonsmokers. This conclusion contrasts the findings of Kamel et al., who discovered no changes in anxiety levels between smokers and nonsmokers [28]. Neurotransmitter systems, inflammation, oxidative and nitrosative stress, mitochondrial dysfunction, neurotrophins and neurogenesis, and epigenetic changes are thought to contribute to anxiety. Cigarette smoke components like as nicotine and free radicals have an impact on all of these pathways [38]. Another explanation of association of cigarette smoking with anxiety is that anxiety could lead to the urge to smoke.
Patients who were not working were more anxious than those who were, supporting the findings of Gerogianni et al. [31]. This finding, however, contradicts those of Kamel et al. [28], Kao et al. [33], Turkistani et al. [29], Delgado-Domínguez et al. [32], and Yoong et al. [8]. Non-work in working-age patients may be associated with a lack of financial means and, as a result, a loss of self-esteem. There may also be psychological concerns and anxiousness. In addition, it is possible that considerable anxiety makes it difficult for patients to work. Furthermore, time consuming in hemodialysis sessions could cause both anxiety and inability to work.
Patients with higher degrees of anxiety and depression (abnormal and borderline cases) had a significantly longer duration of HD in the current research. The findings of Kamel et al.'s [28] are consistent with ours. Our findings, on the other hand, contradict the findings of Gerogianni et al. [31], Delgado-Domínguez et al. [32], and Yoong et al. [8], who discovered no significant differences in HD duration among persons with varied levels of anxiety. Elkheir et al. [39] reported that individuals with HD who had it for less than a year were more depressed than those who had it for more than three years. HD is associated with negative concerns, such as fear of access and HD-related repercussions, which can create stress and worry in patients. Furthermore, frequent commuting and spending extended periods of time away from home may contribute to their stress levels.
The present study discovered that smokers had higher levels of depression than nonsmokers. This result differs from what Kamel et al. [28]. It is unclear if smoking causes depression or whether depression pushes people to start smoking. The relationship between the two is most likely troublesome. Nicotine causes the release of dopamine in the brain. Dopamine is responsible for happy feelings. It has been found repeatedly to be low among depressed persons, who may then turn to smoking to temporarily increase their dopamine levels. Smoking, on the other hand, causes the brain's natural dopamine-producing process to shut down, lowering the availability of dopamine in the brain over time and encouraging smokers to smoke more [40].
In the current study, non-workers had greater levels of depression than employees. This finding contradicts the findings of Kamel et al. [28], Donia et al. [41], Kao et al. [33], Delgado-Domínguez et al. [32] and Yoong et al. [8]. As mentioned before, unemployment may be related with financial difficulties, loss of self-esteem, and consequently depression.
Poor HRQOL was described in patients on HD [42–44]. In the current study, anxiety and depression were the most significant associated variables with HRQOL in multivariate linear regression analysis. Anxiety and depression have been associated to low HRQOL in several studies [15, 16, 41, 45, 46]. In the current study, both anxiety and depression had a negative influence on many parameters of HRQOL. Dialysis has a major and occasionally negative impact on patients' physical and mental health, impairing quality of life and causing psychological issues [46]. Low treatment adherence is thought to be one of the factors that contribute to the link between high levels of anxiety or depression and low quality of life [45]. The foregoing evidence suggests that HD patients who effectively avoid or treat anxiety and depression may improve significantly in terms of both HRQOL and regular physical activity [47].
The present results put an emphasis of evaluating mental disorders in HD patients in addition to searching for the underlying risk factors as a trial to address them because of the affliction of these disorders on HRQOL and health status of these patients. However, we recommend other studies to stratify the study cohort according to presence/absence of depression/anxiety.
Limitations of the current study included that anxiety and depression were assessed depending on self-report not on established clinical diagnosis. Additionally, convenience sampling is not representative of all population undergoing HD in Egypt and it could be the reason for the different prevalence of the disease from other studies. In addition, activity of lifestyle was collected from the patients’ own words so it might be inaccurate. Furthermore, the limited range of collected variables that might have impacts on the multivariable linear regression model of both anxiety and depression. Moreover, selection bias was one of the study limitations due to exclusion of patients who did not want to participate in the study which could be due to having some degree of anxiety/depression.
Conclusion
Anxiety and depression are prevalent among Egyptian HD patients, and many sociodemographic and clinical risk factors, such as female gender, sedentary lifestyle, smoking, and longer HD duration, are associated with them. In addition, these mental disorders are associated with poor HRQOL in those patients.
Funding
Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).
Data availability
The dataset generated and analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest in this work.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Eman Nagy, Email: emannagy@mans.edu.eg.
Samar Tharwat, Email: samartharwat2000@mans.edu.eg.
Abdelrahman Mohamed Elsayed, Email: abdorezk588@gmail.com.
Shimaa Abd El-Galeel Shabaka, Email: shimaashabaka@mans.edu.eg.
Mohammed Kamal Nassar, Email: m_kamal@mans.edu.eg.
References
- 1.Mills KT, Xu Y, Zhang W, Bundy JD, Chen C-S, Kelly TN, et al. A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010. Kidney Int. 2015;88(5):950–957. doi: 10.1038/ki.2015.230. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Robinson BM, Zhang J, Morgenstern H, Bradbury BD, Ng LJ, McCullough KP, et al. Worldwide, mortality risk is high soon after initiation of hemodialysis. Kidney Int. 2014;85(1):158–165. doi: 10.1038/ki.2013.252. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Shirazian S, Grant CD, Aina O, Mattana J, Khorassani F, Ricardo ACJKIR. Depression in chronic kidney disease and end-stage renal disease: similarities and differences in diagnosis, epidemiology, and management. Kidney inter rep. 2017;2(1):94–107. doi: 10.1016/j.ekir.2016.09.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Cukor D, Coplan J, Brown C, Friedman S, Cromwell-Smith A, Peterson RA, et al. Depression and anxiety in urban hemodialysis patients. Clin J Am Soc Nephrol. 2007;2(3):484–490. doi: 10.2215/CJN.00040107. [DOI] [PubMed] [Google Scholar]
- 5.Palmer S, Vecchio M, Craig JC, Tonelli M, Johnson DW, Nicolucci A, et al. Prevalence of depression in chronic kidney disease: systematic review and meta-analysis of observational studies. Kidney Int. 2013;84(1):179–191. doi: 10.1038/ki.2013.77. [DOI] [PubMed] [Google Scholar]
- 6.Theofilou PJIJON. Depression and anxiety in patients with chronic renal failure: the effect of sociodemographic characteristics. Int j nephrol. 2011;2011:6. doi: 10.4061/2011/514070. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Ma TKW, Li PKTJN. Depression in dialysis patients. Nephrology. 2016;21(8):639–646. doi: 10.1111/nep.12742. [DOI] [PubMed] [Google Scholar]
- 8.Yoong RK, Mooppil N, Khoo EY, Newman SP, Lee VY, Kang AW, et al. Prevalence and determinants of anxiety and depression in end stage renal disease (ESRD). A comparison between ESRD patients with and without coexisting diabetes mellitus. J psycho res. 2017;94:68–72. doi: 10.1016/j.jpsychores.2017.01.009. [DOI] [PubMed] [Google Scholar]
- 9.Schouten RW, Haverkamp GL, Loosman WL, Shaw PKC, van Ittersum FJ, Smets YF, et al. Anxiety symptoms, mortality, and hospitalization in patients receiving maintenance dialysis: a cohort study. Am J Kidney Dis. 2019;74(2):158–166. doi: 10.1053/j.ajkd.2019.02.017. [DOI] [PubMed] [Google Scholar]
- 10.Cirillo L, Cutruzzulà R, Somma C, Gregori M, Cestone G, Pizzarelli C, et al. Depressive symptoms in dialysis: prevalence and relationship with uremia-related biochemical parameters. Blood Purif. 2018;46(4):286–291. doi: 10.1159/000491014. [DOI] [PubMed] [Google Scholar]
- 11.Cohen SD, Cukor D, Kimmel PLJCJOTASON. Anxiety in patients treated with hemodialysis. Clin J Amer Soci Nephrol. 2016;11(12):2250–2255. doi: 10.2215/CJN.02590316. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Eyler RF, Unruh ML, Quinn DK, Mary Vilay A. editors Psychotherapeutic agents in end-stage renal disease. Semi dialysis. 2015;28:417. doi: 10.1111/sdi.12370. [DOI] [PubMed] [Google Scholar]
- 13.Weisbord SD, Mor MK, Sevick MA, Shields AM, Rollman BL, Palevsky PM, et al. Associations of depressive symptoms and pain with dialysis adherence, health resource utilization, and mortality in patients receiving chronic hemodialysis. Clin J Am Soc Nephrol. 2014;9(9):1594–1602. doi: 10.2215/CJN.00220114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Kimmel PL, Fwu C-W, Abbott KC, Moxey-Mims MM, Mendley S, Norton JM, et al. Psychiatric illness and mortality in hospitalized ESKD dialysis patients. Clin J Am Soc Nephrol. 2019;14(9):1363–1371. doi: 10.2215/CJN.14191218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Cukor D, Coplan J, Brown C, Friedman S, Newville H, Safier M, et al. Anxiety disorders in adults treated by hemodialysis: a single-center study. Am J Kidney Dis. 2008;52(1):128–136. doi: 10.1053/j.ajkd.2008.02.300. [DOI] [PubMed] [Google Scholar]
- 16.Kao TW, Lai MS, Tsai TJ, Jan CF, Chie WC, Chen WYJAO. Economic, social, and psychological factors associated with health-related quality of life of chronic hemodialysis patients in Northern Taiwan: a multicenter study. Artif Organs. 2009;33(1):61–68. doi: 10.1111/j.1525-1594.2008.00675.x. [DOI] [PubMed] [Google Scholar]
- 17.Fischer MJ, Xie D, Jordan N, Kop WJ, Krousel-Wood M, Tamura MK, et al. Factors associated with depressive symptoms and use of antidepressant medications among participants in the Chronic Renal Insufficiency Cohort (CRIC) and Hispanic-CRIC Studies. Am J Kidney Dis. 2012;60(1):27–38. doi: 10.1053/j.ajkd.2011.12.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kop WJ, Seliger SL, Fink JC, Katz R, Odden MC, Fried LF, et al. Longitudinal association of depressive symptoms with rapid kidney function decline and adverse clinical renal disease outcomes. Clin J Am Soc Nephrol. 2011;6(4):834–844. doi: 10.2215/CJN.03840510. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Barczak P, Kane N, Andrews S, Congdon A, Clay J, Betts TJTBJOP. Patterns of psychiatric morbidity in a genito-urinary clinic: a validation of the Hospital Anxiety Depression scale (HAD) British J Psychiat. 1988;152(5):698–700. doi: 10.1192/bjp.152.5.698. [DOI] [PubMed] [Google Scholar]
- 20.Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the Hospital Anxiety and Depression Scale: an updated literature review. J Psychosom Res. 2002;52(2):69–77. doi: 10.1016/S0022-3999(01)00296-3. [DOI] [PubMed] [Google Scholar]
- 21.Aben I, Verhey F, Lousberg R, Lodder J, Honig A. Validity of the beck depression inventory, hospital anxiety and depression scale, SCL-90, and Hamilton depression rating scale as screening instruments for depression in stroke patients. Psychosomatics. 2002;43(5):386–393. doi: 10.1176/appi.psy.43.5.386. [DOI] [PubMed] [Google Scholar]
- 22.Kuijpers PM, Denollet J, Lousberg R, Wellens HJ, Crijns H, Honig A. Validity of the hospital anxiety and depression scale for use with patients with noncardiac chest pain. Psychosomatics. 2003;44(4):329–335. doi: 10.1176/appi.psy.44.4.329. [DOI] [PubMed] [Google Scholar]
- 23.Stafford L, Berk M, Jackson HJ. Validity of the Hospital Anxiety and Depression Scale and Patient Health Questionnaire-9 to screen for depression in patients with coronary artery disease. Gen Hosp Psychiatry. 2007;29(5):417–424. doi: 10.1016/j.genhosppsych.2007.06.005. [DOI] [PubMed] [Google Scholar]
- 24.Martin CR, Thompson DR. The hospital anxiety and depression scale in patients undergoing peritoneal dialysis: internal and test–retest reliability. Clin Eff Nurs. 2002;6(2):78–80. doi: 10.1016/S1361-9004(02)00029-8. [DOI] [Google Scholar]
- 25.Loosman W, Siegert C, Korzec A, Honig A. Validity of the Hospital Anxiety and Depression Scale and the Beck Depression Inventory for use in end-stage renal disease patients. Br J Clin Psychol. 2010;49(4):507–516. doi: 10.1348/014466509X477827. [DOI] [PubMed] [Google Scholar]
- 26.Terkawi AS, Tsang S, AlKahtani GJ, Al-Mousa SH, Al Musaed S, AlZoraigi US, et al. Development and validation of Arabic version of the Hospital Anxiety and Depression Scale. Saudi J Anaesth. 2017;11(1):S11. doi: 10.4103/sja.SJA_43_17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Da Schatell W. Beth Measuring dialysis patients’ health-related Quality of life with the KDQOL-36™. Med Educ Inst. 2008;608:833–8033. [Google Scholar]
- 28.Reda A, Kamel MF, Goda TM. Anxiety and depression among hemodialysis patients in Egypt. Zagazig Univer Med J. 2022;28(3):594–604. [Google Scholar]
- 29.Turkistani I, Nuqali A, Badawi M, Taibah O, Alserihy O, Morad M, et al. The prevalence of anxiety and depression among end-stage renal disease patients on hemodialysis in Saudi Arabia. Ren Fail. 2014;36(10):1510–1515. doi: 10.3109/0886022X.2014.949761. [DOI] [PubMed] [Google Scholar]
- 30.Mosleh H, Alenezi M, Alsani A, Fairaq G, Bedaiwi R. Prevalence and factors of anxiety and depression in chronic kidney disease patients undergoing hemodialysis: a cross-sectional single-center study in Saudi Arabia. Cureus. 2020 doi: 10.7759/cureus.6668. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Gerogianni G, Lianos E, Kouzoupis A, Polikandrioti M, Grapsa EJIu. nephrology The role of socio-demographic factors in depression and anxiety of patients on hemodialysis: an observational cross-sectional study. Inter urol nephrol. 2018;50(1):143–154. doi: 10.1007/s11255-017-1738-0. [DOI] [PubMed] [Google Scholar]
- 32.Delgado-Domínguez CJ, Sanz-Gómez S, López-Herradón A, Díaz Espejo B, Lamas González O, et al. Influence of depression and anxiety on hemodialysis patients: the value of multidisciplinary care. Inter J Environm Res Public Health. 2021;18(7):3544. doi: 10.3390/ijerph18073544. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Kao Y-Y, Lee W-C, Wang R-H, Chen J-BJRF. Correlation of sociodemographic profiles with psychological problems among hospitalized patients receiving unplanned hemodialysis. Ren Fail. 2020;42(1):255–262. doi: 10.1080/0886022X.2020.1736097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Lebron-Milad K, Milad MRJBOM. Disorders a Sex differences, gonadal hormones and the fear extinction network: implications for anxiety disorders. Biol mood anxiety disord. 2012;2(1):1–12. doi: 10.1186/2045-5380-2-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.McHenry J, Carrier N, Hull E, Kabbaj MJFIN. Sex differences in anxiety and depression: role of testosterone. Front neuroendocrinol. 2014;35(1):42–57. doi: 10.1016/j.yfrne.2013.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Bekker MH, van Mens-Verhulst JJGM. Anxiety disorders: sex differences in prevalence, degree and background, but gender-neutral treatment. Gender med. 2007;4:S178–S193. doi: 10.1016/S1550-8579(07)80057-X. [DOI] [PubMed] [Google Scholar]
- 37.Asher M, Asnaani A, Aderka IM. Gender differences in social anxiety disorder: A review. Clin Psychol Rev. 2017;56:1–12. doi: 10.1016/j.cpr.2017.05.004. [DOI] [PubMed] [Google Scholar]
- 38.Moylan S, Jacka FN, Pasco JA, Berk MJB. behavior How cigarette smoking may increase the risk of anxiety symptoms and anxiety disorders: a critical review of biological pathways. Brain behav. 2013;3(3):302–326. doi: 10.1002/brb3.137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Elkheir HK, Wagaella AS, Badi S, Khalil A, Elzubair TH, Khalil A, et al. Prevalence and risk factors of depressive symptoms among dialysis patients with end-stage renal disease (ESRD) in Khartoum, Sudan: A cross-sectional study. J Family Med Primary Care. 2020;9(7):3639. doi: 10.4103/jfmpc.jfmpc_1229_19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Smoking and mental health Mental health foundation. Available from: https://www.mentalhealth.org.uk/a-to-z/s/smoking-and-mental-health. Accessed 1 May 2022
- 41.Donia AF, Zaki NF, Elassy M, Elbahaey WJIU. Nephrology Study of depression and quality of life among hemodialysis patients: an Egyptian experience. Inter urol nephrol. 2015;47(11):1855–1862. doi: 10.1007/s11255-015-1091-0. [DOI] [PubMed] [Google Scholar]
- 42.Nagy E, Mahmoud M, El-kannishy G, Sayed-Ahmed N. Impact of malnutrition on health-related quality of life in patients on maintenance hemodialysis. Ther Apher Dial. 2021;25(4):467–474. doi: 10.1111/1744-9987.13588. [DOI] [PubMed] [Google Scholar]
- 43.Al Salmi I, Kamble P, Lazarus ER, D’Souza MS, Al Maimani Y, Hannawi S. Kidney disease-specific quality of life among patients on hemodialysis. Inter j nephrol. 2021;2021:8. doi: 10.1155/2021/8876559. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Dembowska E, Jaroń A, Gabrysz-Trybek E, Bladowska J, Gacek S, Trybek G. Quality of life in patients with end-stage renal disease undergoing hemodialysis. J Clin Med. 2022;11(6):1584. doi: 10.3390/jcm11061584. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Vasilopoulou C, Bourtsi E, Giaple S, Koutelekos I, Theofilou P, Polikandrioti MJGJOHS. The impact of anxiety and depression on the quality of life of hemodialysis patients. Global j health sci. 2016;8(1):45. doi: 10.5539/gjhs.v8n1p45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Bujang MA, Musa R, Liu WJ, Chew TF, Lim CT, Morad ZJAJOP. Depression, anxiety and stress among patients with dialysis and the association with quality of life. Asian j psychiat. 2015;18:49–52. doi: 10.1016/j.ajp.2015.10.004. [DOI] [PubMed] [Google Scholar]
- 47.Li Y-N, Shapiro B, Kim JC, Zhang M, Porszasz J, Bross R, et al. Association between quality of life and anxiety, depression, physical activity and physical performance in maintenance hemodialysis patients. Chronic dis translat med. 2016;2(02):110–119. doi: 10.1016/j.cdtm.2016.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The dataset generated and analysed during the current study are available from the corresponding author on reasonable request.