Kidney Res Clin Pract > Epub ahead of print
Jeon, Lim, Jeon, Chung, Kim, Kang, Yang, Kim, Jung, Choi, Park, Kim, Kim, and Cho: The impact of severe depression on the survival of older patients with end-stage kidney disease



Incidence of depression increases in patients with end-stage kidney disease (ESKD). We evaluated the association between depression and mortality among older patients with ESKD, which has not been studied previously.


This nationwide prospective cohort study included 487 patients with ESKD aged >65 years, who were categorized into minimal, mild-to-moderate, and severe depression groups based on their Beck Depression Inventory-II (BDI-II) scores. Predisposing factors for high BDI-II scores and the association between the scores and survival were analyzed.


The severe depression group showed a higher modified Charlson comorbidity index value and lower serum albumin, phosphate, and uric acid levels than the other depression groups. The Kaplan-Meier curve revealed a significantly lower survival in the severe depression group than in the minimal and mild-to-moderate depression groups (p = 0.011). Multivariate Cox regression analysis confirmed that severe depression was an independent risk factor for mortality in the study cohort (hazard ratio, 1.39; 95% confidence interval, 1.01–1.91; p = 0.041). Additionally, BDI-II scores were associated with modified Charlson comorbidity index (p = 0.009) and serum albumin level (p = 0.004) in multivariate linear regression. Among the three depressive symptoms, higher somatic symptom scores were associated with increased mortality.


Severe depression among older patients with ESKD increases mortality compared with minimal or mild-to-moderate depression, and patients with concomitant somatic symptoms require careful management of their comorbidities and nutritional status.


Major depressive disorder is the most common psychiatric disorder among patients with end-stage kidney disease (ESKD) [13]. Upon initiating dialysis, patients with incident ESKD suffer from stress and various dialysis-related somatic symptoms. Furthermore, regular dialysis restricts social and occupational activities [46]. Concurrent presence of physical symptoms and mental stress may cause depression in patients with ESKD [4,7,8].
Depression in patients on maintenance dialysis is associated with adverse outcomes, such as mortality and hospitalization [3,911]. In a study from the United States, the rates of hospitalization due to depression were significantly higher in elderly patients with ESKD than those in non-ESKD elderly patients with chronic medical conditions, such as ischemic heart disease, cerebrovascular disease, and peptic ulcer disease [12]. While the mean age of patients initiating dialysis is steadily increasing [13,14], the prevalence and impact of depression on survival rates of older patients with ESKD remain unclear.
Depression and frailty were identified to have reciprocal interactions in the elderly population [15]. Depression is associated with an increased prevalence and incidence of frailty, and frailty at dialysis initiation is associated with higher mortality in patients initiating dialysis [16].
The Beck Depression Inventory-II (BDI-II) score was first introduced by Beck et al. [17] in 1996 and has been widely used as a screening instrument for depression. It is a 21-item self-questionnaire consisting of three depressive symptom domains. Affective domain is composed of emotional symptoms such as sadness, anxiety, and irritability. Cognitive domain consists of cognitive symptoms such as indecisiveness, sense of failure and guilt. Physical symptoms, such as fatigue, loss of energy, weight loss, and sleep disturbance are included in somatic domain.
This study aimed to investigate the factors predisposing to depressive disorders and the association between depression severity and long-term mortality in older patients with ESKD using nationwide prospective ESKD cohort data. Furthermore, we compared the impact of the three depressive symptom domains on patient survival.


Study population

This study enrolled patients from the Clinical Research Center for End-Stage Renal Disease (CRC for ESRD) in Korea. The CRC for ESRD included a multicenter prospective cohort of patients undergoing dialysis at nationwide 31 participating hospitals in South Korea (NCT00931970). Between July 2009 and May 2018, 487 patients aged >65 years and newly diagnosed with ESKD on maintenance dialysis for >3 months were included in the analysis (Supplementary Fig. 1, available online). The details of the cohort are described in a previous report [18].

Ethics approval and consent to participate

The Institutional Review Boards (IRBs) of all participating centers approved the study protocol before patient enrollment. The names of the IRBs are as follows: The Catholic University of Korea, Bucheon St. Mary’s Hospital; The Catholic University of Korea, Incheon St. Mary’s Hospital; The Catholic University of Korea, Seoul St. Mary’s Hospital; The Catholic University of Korea, St. Mary’s Hospital; The Catholic University of Korea, St. Vincent’s Hospital; The Catholic University of Korea, Uijeongbu St. Mary’s Hospital; Cheju Halla General Hospital; Chonbuk National University Hospital; Chonnam National University Hospital; Chung-Ang University Medical Center; Chungbuk National University Hospital; Chungnam National University Hospital; Dong-A University Medical Center; Ehwa Womans University Medical Center; Daegu Fatima Hospital; Gachon University Gil Medical Center; Inje University Pusan Paik Hospital; Kyungpook National University Hospital; Kwandong University College of Medicine, Myongji Hospital; National Health Insurance Service Ilsan Hospital; National Medical Center; Pusan National University Hospital; Samsung Medical Center; Seoul Metropolitan Government, Seoul National University, Boramae Medical Center; Seoul National University Hospital; Seoul National University Bundang Hospital; Yeungnam University Medical Center; Yonsei University Severance Hospital; Yonsei University Gangnam Severance Hospital; Ulsan University Hospital; and Wonju Christian Hospital (in alphabetical order). Written informed consent was obtained from all patients prior to inclusion. This study was performed in accordance with the 2013 Declaration of Helsinki.

Data collection

The requisite data were extracted from the web-based CRC for ESRD database. Baseline patient information was collected at enrollment, including demographics, history of primary renal disease, dialysis modality, comorbidities, and laboratory values. The modified Charlson comorbidity index (mCCI) was calculated for each patient at the time of dialysis [19,20].

Assessment of depression

Depression was evaluated using the BDI-II questionnaire at the time of enrollment. The BDI-II is a 21-item questionnaire that assesses the severity of depressive symptoms [17]. Each symptom is rated between 0 and 3, with a greater score indicating increased severity. The BDI-II score was divided into tertiles: minimal (0–10), mild-to-moderate (11–19), and severe depression (≥20). Additionally, BDI-II scores were separated into three symptom domains: affective, cognitive, and somatic depressive symptoms [21].


The main study outcome was all-cause mortality after initiation of dialysis during the study period. Mortality data of the cohort patients were obtained from Statistics Korea until December 2019. Patients were censored at the time of loss of follow-up or kidney transplantation.

Statistical analysis

Continuous and categorical variables are presented as mean ± standard deviation and numbers (percentage), respectively. Analysis of variance was used to compare continuous variables, and Pearson chi-square or Fisher exact test was used for categorical variable comparisons. The Kaplan-Meier curve with the log-rank test was used to compare the differences in mortality among the three depression groups. A Cox proportional hazards regression model was used to calculate the adjusted hazard ratios (HRs) for all-cause mortality in the tertiles. Association between the BDI-II score and mortality was evaluated using multivariate Cox regression analysis, for which clinically important baseline characteristics, including age, sex, mCCI, and serum albumin, phosphate, and uric acid levels, were selected as adjustment values; the univariate analysis determined the values that were significantly different at baseline, which were subsequently included in the multivariate analysis along with age and sex. Factors associated with the BDI-II score were evaluated using logistic regression analysis. The associations among the three depressive symptom domains and mortality were analyzed using multivariate Cox proportional hazard regression models. The Kaplan-Meier method was used to analyze the differences in mortality among tertiles of depressive symptom domains. The cut-off values for the tertiles of depressive symptom scores were as follows: affective: <1, 1–5, ≥5; cognitive: <3, 3–7, ≥7; and somatic symptom: <5, 5–8, ≥8. To analyze the BDI-II or somatic symptom score as a quantitative variable, the relationship between each score and mortality was evaluated using a Cox proportional hazard model with restricted cubic spline functions to capture potential nonlinear effects. Statistical analyses were performed using the IBM SPSS version 22.0 (IBM Corp.) and R version 3.6.2 (The R Foundation for Statistical Computing). Statistical significance was set at p < 0.05.


Baseline characteristics

Of 487 older patients with newly diagnosed ESKD on dialysis, 305 (62.6%) were male and the mean age was 74.2 ± 6.7 years. The mean BDI-II score was 16.5 ± 10.9, and patients were followed up for a median of 69.3 months. The proportion of patients with hemodialysis was higher than that of patients with peritoneal dialysis (76.8% vs. 23.0%, respectively). Until December 2019, 245 patients died and 96 (56.5%) of deceased patients had severe depression. Table 1 summarizes the baseline demographic characteristics and laboratory values of the depression groups stratified by the BDI-II scores. The severe depression group had a higher mCCI, more comorbidities, such as cerebrovascular diseases, chronic lung disease, and malignancy, and lower serum albumin, phosphate, and uric acid levels than the other depression groups.

Predictors of severe depression

Univariate analysis showed a positive association between BDI-II and mCCI and negative associations between BDI-II and serum albumin, phosphate, and uric acid levels (Table 2). In the multivariate linear regression model, BDI-II score displayed a positive association with mCCI and a negative association with serum albumin level (p = 0.009 and p = 0.04, respectively).

Association between Beck Depression Inventory-II score and mortality

Higher BDI-II and somatic symptom scores were both associated with increased mortality in older patients with ESKD (Fig. 1). In the Kaplan-Meier survival curve, the severe depression group showed significantly lower survival than the minimal and mild-to-moderate depression groups (log-rank p = 0.01) (Fig. 2). In the Cox proportional hazards model, severe depression was an independent risk factor for mortality in older patients with ESKD (model 4: HR, 1.39; 95% confidence interval [CI], 1.01–1.91; p = 0.04) (Table 3). However, mortality risk was comparable between mild-to-moderate and minimal depression.

Analysis of depressive symptom domains

When comparing depressive symptoms among the tertiles, the differences in the three depressive symptom scores were similar to that of the BDI-II scores, with the highest scores in the severe depression group (Supplementary Table 1, available online). To analyze the factors related to survival among depressive symptom domains, each depressive symptom score (affective, cognitive, and somatic symptom scores) was divided into tertile groups. The Kaplan-Meier survival curves revealed that only somatic symptom scores were associated with mortality among the tertiles (log-rank p < 0.001) (Fig. 3). The third tertile group of the somatic symptom domain showed poor survival compared to the first tertile and second tertile groups (p = 0.003 and p = 0.02, respectively) (Fig. 3C). Among the three depressive-symptom scores, only a high somatic symptom score was an independent risk factor for mortality (model 4: HR, 2.45; 95% CI, 1.25–4.79; p = 0.009) (Table 4). In the multivariate linear regression analysis, somatic symptoms negatively correlated with age and albumin level and positively with the male sex among older patients with ESKD (all p < 0.05) (Table 5).


This Korean nationwide prospective cohort study revealed that severe depression increased the mortality risk in older patients with ESKD, whereas minimal and mild-to-moderate depression showed similar survival outcomes. The negative effect of severe depression on survival remained significant after adjusting for confounding factors. Among the three depressive symptom domains, only somatic symptoms were associated with mortality in the study cohort. In addition, older patients with a higher comorbidity index or lower albumin level had an increased risk of severe depression.
Over the decades, many studies have demonstrated an association between depression and mortality in patients with ESKD [2,3,9,11,22]. The cut-off values of BDI-II score for discriminating depression may change depending on the patient group and a definite cut-off value that could be applied consistently has not yet been determined. A study of hemodialysis patients aged 65 years and older showed that a BDI score of ≥10 had a diagnostic value of depression with a sensitivity of 68% and specificity of 77% [23]. In this background, a cut-off of 10 for the minimal depression group was acceptable as a value to discriminate depression. In addition, we referred to another study that reported the association between the severity of depression and patient survival. The study investigating hemodialysis patients with a mean age of 64 years showed that only moderate depression (BDI-II score, ≥20) was significantly associated with all-cause mortality [24]. Therefore, dividing patients into BDI-II tertile groups (minimal, 0–10; mild-to-moderate, 11–19; severe, ≥20) was considered appropriate to investigate outcomes of interest based on previous studies from a similar population.
With the progressive establishment of aging societies, evaluating the relationship between depression and mortality among older patients is important [25]. Among the screening tools for depression, the BDI-II is the most widely used for the chronic kidney disease population [1,23,26]. Depression increases the mortality risk in patients with ESKD [2,3,911,22]; however, the behavioral and biological mechanisms that fully explain the link between the two remain unclear [27]. Our results showed that the risk of severe depression increased in older patients with higher mCCI values. The presence of multiple comorbidities increases the burden of illness, such as selfcare demands and functional impairment, causing depression and poor therapeutic adherence [2831]. The close association between depression, frailty, and mortality has been demonstrated in several studies [15,32]. In addition, hypoalbuminemia is linked to severe depression; therefore, depression may reflect a poor nutritional status. These depression-related factors may result in poor outcomes for older patients with ESKD.
Several studies have demonstrated a relationship between the BDI score and mortality in patients with ESKD, but not among older patients. Kimmel et al. [9] reported that higher time-varying BDI scores were associated with increased mortality in 295 patients with a mean age of 54.6 years on hemodialysis. However, a cumulative survival analysis showed a similar increase in mortality in the mild and moderate-to-severe depression groups compared with the minimal depression group, with no differences in the mortality risk between the mild and moderate-severe depression group [9]. A European multinational cohort study, using a sensitivity analysis, revealed that self-reported severe depression was significantly associated with all-cause mortality during the 11-month follow-up period among 3,086 patients with a mean age of 63.6 years undergoing hemodialysis [24]. Unlike previous studies, our study included a cohort of older patients with ESKD with a mean age of 74.2 years and showed that severe depression negatively impacted mortality compared with minimal or mild-to-moderate depression. To the best of our knowledge, this is the first study to investigate the association between depression and mortality among older patients with ESKD.
Few studies have investigated depression among Korean patients with ESKD. Recently, a nationwide cohort study analyzed psychiatric problems in patients with ESKD based on the code of International Classification of Disease, 10th revision; the hemodialysis and peritoneal dialysis groups had a greater depression risk than the kidney transplantation group [33]. In addition, patients with ESKD aged >60 years reportedly have a higher depression risk than those aged 18–39 years [33]. Contrary to our results, Jeon et al. [34] found no association between depression, as measured by the BDI, and all-cause mortality among 166 patients on hemodialysis. However, the mean age of patients was 57.9 years, which was younger than that in our study, and the 31.2-month follow-up period was much shorter than that in our study; therefore, their reports of the effects of depression among older patients with ESKD were limited [34].
Interestingly, our results demonstrated that each depressive symptom domain had a different relationship with mortality. Among the three domains, patients with higher scores for somatic, but not affective or cognitive, depression had higher mortality. This is consistent with a previous prospective study conducted in the Netherlands, which reported that only BDI-II score-derived somatic depressive symptoms affected mortality in 687 patients on dialysis [35]. Most patients on dialysis with depression have somatic symptoms; somatic and psychiatric symptoms are reportedly associated in patients on dialysis [36]. In our study, somatic symptoms negatively correlated with age among older patients. In other words, younger subsets of older patients with better physical capacity are more likely to experience physical and sexual dysfunctions compared with the older subsets. In a cross-sectional study, somatic symptoms were associated with low physical activity levels, measured using pedometry, in patients with ESKD [37]. Although our study did not measure the physical activity levels of patients, a higher somatic symptom score among younger subsets of older patients may reflect their discouragement due to discrepancies between their physical activity levels and expectations. These causal relationships should be further investigated.
This study had some limitations. First, this was an observational study; therefore, potential prognostic factors could not be considered, such as history of psychiatric disorder and antidepressants. Additionally, the causal relationship and pathophysiological mechanisms between depression and mortality could not be explained. Second, the depressive symptoms were similar to those observed in uremia. However, we did not investigate dialysis adequacy and prescription, which may have affected the symptoms. Third, since this study focused on the association between baseline depression and mortality in older patients with ESKD, no evidence regarding the effect of depression treatment and changes in the degree of depression on patient outcomes was generated.
In conclusion, we found that severe depression increases mortality in older patients with ESKD. Older patients with somatic depressive symptoms are a particularly vulnerable population and may require meticulous management of comorbidities and nutritional status to improve their outcomes.

Supplementary Materials

Supplementary data are available at Kidney Research and Clinical Practice online (


Conflicts of interest

All authors have no conflicts of interest to declare.


This work was supported by a grant from Biomedical Research Institute, Kyungpook National University Hospital (2022).

Data sharing statement

The data presented in this study are available on request from the corresponding author.

Authors’ contributions

Conceptualization, Investigation: JHL, YLK, JHC

Data curation: YSK, SWK, CWY, NHK, HYJ, JYC, SHP, CDK

Statistical analysis, Visualization: JHL, YJ

Funding acquisition, Supervision: YKC, JHC

Methodology: JHL, HYJ, JYC, SHP, CDK, YLK, JHC

Writing–original draft: YHJ, JHL

Writing–review & editing: YHJ, JHL, YLK, JHC

All authors read and approved the final manuscript.

Figure 1.

Relationship between the mortality hazard ratio and depressive symptom scores.

RBoth (A) the Beck Depression Inventory-II (BDI-II) and (B) somatic symptom scores are positively associated with mortality hazard ratio (HR). The reference values are 1.0.
Figure 2.

Kaplan-Meier curve for mortality in depression groups.

Figure 3.

Kaplan-Meier curves for mortality according to three depressive symptom scores in tertile groups.

(A) Affective symptom domain. (B) Cognitive symptom domain. (C) Somatic symptom domain.
Table 1.
Baseline characteristics
Characteristic Depression group
Minimal Mild-to-moderate Severe
No. of patients 152 165 170
Age (yr) 65.9 ± 7.2 66.0 ± 6.6 67.1 ± 7.1 0.24
Male sex 102 (67.1) 96 (58.2) 107 (62.9) 0.26
BMI (kg/m2) 23.3 ± 3.4 23.4 ± 3.5 22.8 ± 3.4 0.27
BDI-II score 5.2 ± 3.3 14.7 ± 2.5 24.9 ± 7.9 <0.001
Primary renal disease 0.20
 Diabetes 86 (56.6) 108 (65.5) 104 (61.2)
 Hypertension 32 (21.1) 20 (12.1) 21 (12.4)
 Glomerulonephritis 13 (8.6) 13 (7.9) 12 (7.1)
 Others 21 (13.8) 24 (14.6) 33 (19.4)
Comorbid conditions
 Diabetes 91 (59.9) 116 (70.3) 113 (66.5) 0.14
 Congestive heart failure 19 (12.5) 32 (19.4) 32 (18.8) 0.20
 Peripheral vascular disease 7 (4.6) 24 (14.6) 22 (12.9) 0.01
 Cerebrovascular disease 12 (7.9) 17 (10.3) 29 (17.1) 0.03
 Chronic lung disease 14 (9.2) 7 (4.2) 18 (10.6) 0.08
 Malignancy 13 (8.6) 13 (7.9) 15 (8.8) 0.95
mCCI 6.0 ± 1.9 6.5 ± 2.0 6.5 ± 2.1 0.02
Smoker  0.65
 Nonsmoker 79 (52.7) 88 (54.3) 93 (55.4)
 Smoker 9 (6.0) 16 (9.9) 15 (8.9)
 Exsmoker 62 (41.3) 58 (35.8) 60 (35.7)
Systolic pressure (mmHg) 143.0 ± 21.2 142.8 ± 22.6 143.5 ± 21.9 0.96
Diastolic pressure (mmHg) 75.6 ± 12.3 75.1 ± 12.6 74.8 ± 12.3 0.83
Residual urine volumea, ≥100 mL/day 76 (85.4) 88 (83.8) 85 (85.9) 0.91
Laboratory data
 Hemoglobin (g/dL) 9.2 ± 1.5 9.1 ± 1.5 9.2 ± 1.6 0.62
 Albumin (g/dL) 3.5 ± 0.5 3.4 ± 0.7 3.3 ± 0.6 0.04
 Creatinine (mg/dL) 7.8 ± 3.0 7.8 ± 3.1 7.4 ± 3.0 0.34
 CRP (mg/dL) 3.2 ± 12.2 3.2 ± 10.5 5.4 ± 13.2 0.22
 Ferritin (ng/dL) 268.9 ± 274.4 295.1 ± 268.5 311.5 ± 314.0 0.46
 Calcium (mg/dL) 8.0 ± 1.0 8.1 ± 0.9 8.0 ± 0.9 0.53
 Phosphate (mg/dL) 5.3 ± 1.6 5.4 ± 1.5 5.0 ± 1.7 0.04
 Uric acid (mg/dL) 8.0 ± 2.4 8.0 ± 2.4 7.4 ± 2.7 0.04
 Intact PTH (mg/dL) 250.8 ± 195.8 221.7 ± 147.9 217.5 ± 192.4 0.26

Data are expressed as mean ± standard deviation or number (%).

BDI-II, Beck Depression Inventory-II; BMI, body mass index; CRP, C-reactive protein; mCCI, modified Charlson comorbidity index; PTH, parathyroid hormone.

a The analysis included 293 patients with available data.

Table 2.
Factors associated with BDI-II scores in the linear regression model
Variable Univariate
B (SE) β p-value B (SE) β p-value
Age 0.08 (0.07) 0.05 0.29 –0.04 (0.08) –0.03 0.61
Sex (reference, female) –0.13 (1.02) –0.01 0.90 –0.08 (1.03) –0.00 0.94
BMI –0.26 (0.14) –0.08 0.07
mCCI 0.81 (0.24) 0.15 0.001 0.70 (0.27) 0.13 0.009
Albumin –2.39 (0.83) –0.13 0.004 –1.72 (0.85) –0.09 0.04
Creatinine –0.29 (0.16) –0.08 0.07
Phosphate –0.69 (0.31) –0.10 0.03 –0.41 (0.33) –0.06 0.22
Uric acid –0.44 (0.20) –0.10 0.02 –0.31 (0.21) –0.07 0.13

B, unstandardized regression coefficient; β, standardized coefficient; BDI-II, Beck Depression Inventory-II; BMI, body mass index; mCCI, modified Charlson comorbidity index; SE, standard error.

Table 3.
Associations of depression and mortality in the Cox proportional hazard regression model
Depression group Model 1
Model 2
Model 3
Model 4
HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value
Minimal Reference Reference Reference Reference
Mild-to-moderate 1.07 (0.78–1.48) 0.67 1.12 (0.81–1.55) 0.50 0.98 (0.71–1.37) 0.92 0.98 (0.70–1.38) 0.92
Severe 1.53 (1.13–2.09) 0.007 1.49 (1.09–2.03) 0.01 1.39 (1.02–1.90) 0.04 1.39 (1.01–1.91) 0.04

Model 1: unadjusted. Model 2: adjusted for age and sex. Model 3: adjusted for age, sex, and mCCI. Model 4: adjusted for age, sex, mCCI, albumin, phosphate, and uric acid.

CI, confidence interval; HR, hazard ratio; mCCI, modified Charlson comorbidity index.

Table 4.
Associations of depressive symptom domains and mortality in the Cox proportional hazard regression model
Depressive symptom domian Model 1
Model 2
Model 3
Model 4
HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value
 Tertile 1 Reference Reference Reference Reference
 Tertile 2 1.15 (0.83–1.59) 0.40 1.28 (0.59–2.77) 0.54 1.22 (0.56–2.66) 0.61 1.20 (0.55–2.62) 0.65
 Tertile 3 1.15 (0.86–1.53) 0.35 1.08 (0.54–2.18) 0.83 1.07 (0.54–2.16) 0.84 1.09 (0.54–2.18) 0.82
 Tertile 1 Reference Reference Reference Reference
 Tertile 2 1.08 (0.77–1.53) 0.65 1.35 (0.62–2.94) 0.45 1.29 (0.59–2.81) 0.52 1.29 (0.59–2.83) 0.52
 Tertile 3 1.31 (0.98–1.74) 0.07 1.06 (0.53–2.11) 0.88 1.04 (0.52–2.08) 0.92 1.03 (0.51–2.09) 0.93
 Tertile 1 Reference Reference Reference Reference
 Tertile 2 1.25 (0.88–1.75) 0.21 0.60 (0.20–1.83) 0.37 0.58 (0.19–1.77) 0.34 0.59 (0.19–1.82) 0.36
 Tertile 3 1.71 (1.29–2.28) <0.001 2.57 (1.33–4.98) 0.005 2.43 (1.25–4.73) 0.009 2.45 (1.25–4.79) 0.009

Model 1: unadjusted. Model 2: adjusted for age and sex. Model 3: adjusted for age, sex, and mCCI. Model 4: adjusted for age, sex, mCCI, albumin, phosphate, and uric acid.

HR, hazard ratio; CI, confidence interval; mCCI, modified Charlson comorbidity index.

Table 5.
Factors associated with somatic symptom scores in the linear regression model
Factor Univariate
B (SE) β p-value B (SE) β p-value
Age 0.06 (0.10) 0.10 0.03 –0.02 (0.01) –0.05 0.003
Sex (reference, female) 0.31 (0.03) 0.88 <0.001 0.26 (0.01) 0.92 <0.001
BMI 1.25 (0.43) 0.13 0.004 0.06 (0.11) 0.01 0.54
mCCI 0.39 (0.08) 0.21 <0.001 –0.16 (0.17) –0.02 0.35
Albumin –0.94 (0.48) –0.15 0.001 –0.06 (0.04) –0.03 0.08
Creatinine –0.10 (0.06) –0.08 0.08
Phosphate –0.13 (0.11) –0.05 0.24
Uric acid –0.08 (0.07) –0.06 0.23

B, unstandardized regression coefficient; β, standardized coefficient; BMI, body mass index; mCCI, modified Charlson comorbidity index; SE, standard error.


1. Hedayati SS, Bosworth HB, Kuchibhatla M, Kimmel PL, Szczech LA. The predictive value of self-report scales compared with physician diagnosis of depression in hemodialysis patients. Kidney Int 2006;69:1662–1668.
crossref pmid
2. Lopes AA, Bragg J, Young E, et al. Depression as a predictor of mortality and hospitalization among hemodialysis patients in the United States and Europe. Kidney Int 2002;62:199–207.
crossref pmid
3. Boulware LE, Liu Y, Fink NE, et al. Temporal relation among depression symptoms, cardiovascular disease events, and mortality in end-stage renal disease: contribution of reverse causality. Clin J Am Soc Nephrol 2006;1:496–504.
4. King-Wing Ma T, Kam-Tao Li P. Depression in dialysis patients. Nephrology (Carlton) 2016;21:639–646.
crossref pmid pdf
5. Murtagh FE, Addington-Hall J, Higginson IJ. The prevalence of symptoms in end-stage renal disease: a systematic review. Adv Chronic Kidney Dis 2007;14:82–99.
crossref pmid
6. Purnell TS, Auguste P, Crews DC, et al. Comparison of life participation activities among adults treated by hemodialysis, peritoneal dialysis, and kidney transplantation: a systematic review. Am J Kidney Dis 2013;62:953–973.
crossref pmid
7. Kimmel PL, Patel SS. Quality of life in patients with chronic kidney disease: focus on end-stage renal disease treated with hemodialysis. Semin Nephrol 2006;26:68–79.
crossref pmid
8. Kimmel PL, Emont SL, Newmann JM, Danko H, Moss AH. ESRD patient quality of life: symptoms, spiritual beliefs, psychosocial factors, and ethnicity. Am J Kidney Dis 2003;42:713–721.
crossref pmid
9. Kimmel PL, Peterson RA, Weihs KL, et al. Multiple measurements of depression predict mortality in a longitudinal study of chronic hemodialysis outpatients. Kidney Int 2000;57:2093–2098.
crossref pmid
10. Hedayati SS, Bosworth HB, Briley LP, et al. Death or hospitalization of patients on chronic hemodialysis is associated with a physician-based diagnosis of depression. Kidney Int 2008;74:930–936.
crossref pmid
11. Hedayati SS, Grambow SC, Szczech LA, Stechuchak KM, Allen AS, Bosworth HB. Physician-diagnosed depression as a correlate of hospitalizations in patients receiving long-term hemodialysis. Am J Kidney Dis 2005;46:642–649.
crossref pmid
12. Kimmel PL, Thamer M, Richard CM, Ray NF. Psychiatric illness in patients with end-stage renal disease. Am J Med 1998;105:214–221.
crossref pmid
13. Ye X, Rastogi A, Nissenson AR. Renal replacement therapy in the elderly. Clin Geriatr Med 2009;25:529–542.
crossref pmid
14. Berger JR, Hedayati SS. Renal replacement therapy in the elderly population. Clin J Am Soc Nephrol 2012;7:1039–1046.
crossref pmid pmc
15. Soysal P, Veronese N, Thompson T, et al. Relationship between depression and frailty in older adults: a systematic review and meta-analysis. Ageing Res Rev 2017;36:78–87.
crossref pmid
16. Alfaadhel TA, Soroka SD, Kiberd BA, Landry D, Moorhouse P, Tennankore KK. Frailty and mortality in dialysis: evaluation of a clinical frailty scale. Clin J Am Soc Nephrol 2015;10:832–840.
pmid pmc
17. Beck AT, Steer RA, Brown GK. Manual for the beck depression inventory-II. Psychological Corporation; 1996.
18. Kwon E, Cho JH, Jang HM, et al. Differential effect of viral hepatitis infection on mortality among Korean maintenance dialysis patients: a prospective multicenter cohort study. PLoS One 2015;10:e0135476.
crossref pmid pmc
19. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–383.
crossref pmid
20. Chae JW, Song CS, Kim H, Lee KB, Seo BS, Kim DI. Prediction of mortality in patients undergoing maintenance hemodialysis by Charlson Comorbidity Index using ICD-10 database. Nephron Clin Pract 2011;117:c379–c384.
crossref pmid pdf
21. García-Batista ZE, Guerra-Peña K, Cano-Vindel A, Herrera-Martínez SX, Medrano LA. Validity and reliability of the Beck Depression Inventory (BDI-II) in general and hospital population of Dominican Republic. PLoS One 2018;13:e0199750.
crossref pmid pmc
22. Kimmel PL, Weihs K, Peterson RA. Survival in hemodialysis patients: the role of depression. J Am Soc Nephrol 1993;4:12–27.
23. Balogun RA, Turgut F, Balogun SA, Holroyd S, Abdel-Rahman EM. Screening for depression in elderly hemodialysis patients. Nephron Clin Pract 2011;118:c72–c77.
crossref pmid pdf
24. Saglimbene V, Palmer S, Scardapane M, et al. Depression and all-cause and cardiovascular mortality in patients on haemodialysis: a multinational cohort study. Nephrol Dial Transplant 2017;32:377–384.
crossref pmid
25. Wei J, Hou R, Zhang X, et al. The association of late-life depression with all-cause and cardiovascular mortality among community-dwelling older adults: systematic review and meta-analysis. Br J Psychiatry 2019;215:449–455.
crossref pmid
26. Grant D, Almond MK, Newnham A, Roberts P, Hutchings A. The Beck Depression Inventory requires modification in scoring before use in a haemodialysis population in the UK. Nephron Clin Pract 2008;110:c33–c38.
crossref pmid pdf
27. Tuot DS, Lin F, Norris K, Gassman J, Smogorzewski M, Ku E. Depressive symptoms associate with race and all-cause mortality in patients with CKD. Kidney Int Rep 2019;4:222–230.
crossref pmid
28. Shirazian S. Depression in CKD: understanding the mechanisms of disease. Kidney Int Rep 2019;4:189–190.
crossref pmid
29. Hammer-Helmich L, Haro JM, Jönsson B, et al. Functional impairment in patients with major depressive disorder: the 2-year PERFORM study. Neuropsychiatr Dis Treat 2018;14:239–249.
crossref pmid pmc pdf
30. Jiang W, Alexander J, Christopher E, et al. Relationship of depression to increased risk of mortality and rehospitalization in patients with congestive heart failure. Arch Intern Med 2001;161:1849–1856.
crossref pmid
31. Richardson JL, Marks G, Johnson CA, et al. Path model of multidimensional compliance with cancer therapy. Health Psychol 1987;6:183–207.
crossref pmid
32. Vaughan L, Corbin AL, Goveas JS. Depression and frailty in later life: a systematic review. Clin Interv Aging 2015;10:1947–1958.
crossref pmid pmc
33. Lee MJ, Lee E, Park B, Park I. Mental illness in patients with end-stage kidney disease in South Korea: a nationwide cohort study. Kidney Res Clin Pract 2022;41:231–241.
crossref pmid pdf
34. Jeon HJ, Park HC, Park JI, et al. The effect of depression and health-related quality of life on the outcome of hemodialysis patients. Kidney Res Clin Pract 2012;31:54–61.
crossref pmid pmc
35. Schouten RW, Harmse VJ, Dekker FW, van Ballegooijen W, Siegert CE, Honig A. Dimensions of depressive symptoms and their association with mortality, hospitalization, and quality of life in dialysis patients: a cohort study. Psychosom Med 2019;81:649–658.
crossref pmid pmc
36. Nadort E, Schouten RW, Luijkx X, et al. Symptom dimensions of anxiety and depression in patients receiving peritoneal dialysis compared to haemodialysis. Perit Dial Int 2022;42:259–269.
crossref pmid pdf
37. Lou X, Li Y, Shen H, Juan J, He Q. Physical activity and somatic symptoms among hemodialysis patients: a multi-center study in Zhejiang, China. BMC Nephrol 2019;20:477.
crossref pmid pmc pdf
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You Hyun Jeon

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Yena Jeon

Yu-Kyung Chung

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Shin-Wook Kang

Chul Woo Yang

Nam-Ho Kim

Hee-Yeon Jung

Ji-Young Choi

Sun-Hee Park

Chan-Duck Kim

Yong-Lim Kim

Jang-Hee Cho

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