Depression and quality of life among Chronic Kidney
Disease Patients on Hemodialysis at selected Stand-alone Renal Facilities in
Manila: a cross-sectional study
John Rommel P.
Cunanan, Christian R. Navarro, Peter Angelo J. Robles, Danielle Mary B. Sanchez,
Gerard Josef H. Tuazon, Gil P. Soriano
College of
Nursing, San Beda University, Manila, Philippines
*Corresponding Author Email:
gil.p.soriano@gmail.com
ABSTRACT:
Background: Chronic Kidney Disease (CKD) is a progressive disease that causes a
gradual impairment of the renal function and has risen in the past years. As
its prevalence increase, its impact on the emotional aspect of the patient may
also be escalated in a negative way which can lead to the various types of
depression. Objective: This research examined the relationships of
personal profile, level of depression, Physical Composite Score (PCS), Mental
Composite Score (MCS) and Kidney Disease Component Score (KDCS) among chronic
kidney disease patients in stand-alone renal facilities. Methods: A
descriptive cross-sectional method was used as the design of the study and a
convenience sample of 220 participants with chronic kidney disease were
included in the study. The Filipino version of Kidney Disease Quality of Life
Short Form-36 (KDQOL SF-36) and Beck’s Depression Inventory (BDI) were used to assess
the quality of life and level of depression. Data were analyzed using
descriptive and inferential statistics. Results: The findings revealed a
significant negative correlation between the respondent’s age and physical
composite score. On the other hand, a significant negative correlation was
noted between the kidney disease component and mental composite score with the
level of depression. Conclusions: The study concluded that CKD patients
with a higher quality of life have a lower level of depression.
KEYWORDS: Chronic kidney
disease, depression, quality of life.
INTRODUCTION:
According to the International
Society of Nephrology1, Chronic Kidney Disease (CKD) is a public
health problem affecting 10% of the world’s population. In 2013, the
Philippines, experienced an increase of incidence of CKD annually in comparison
to 2004 and at present it accounts to an estimated 20% of the Philippine
population2-3. Concurrently, the Department of Health (DOH)
conducted a census on the number of Filipinos undergoing dialysis which
likewise increased from 4000 cases per year in 2004 to 23,000 cases in 20134.
Since CKD affects an individual’s overall health, symptoms such as high blood
pressure, anemia, weak bones, poor nutritional health and nerve damage may
develop, just to name a few5. According to Malindretos6,
CKD especially end-stage renal disease (ESRD) have a detrimental effect on both
patients’ life expectancy, and health related quality of life.
Health-related quality of life
(HRQOL) is an essential indicator of disease problem and effectively used to
treat and determine the risks for adverse outcomes7. HRQOL has the
notion that quality of life is a highly individual construct that must
contemplate the expectations and attainments of individual8.
Understanding the abstract model of HRQOL enables the clinician to decide if
HRQOL evaluation will be helpful being taken care of by an individual patient 8.
The frailty and burden of CKD symptoms and comorbidities greatly affect the
psychological status of patients which may lead to depression9.
Depression is known to
influence adults with ESRD and ascribed to psychosocial and biologic changes
that compliment with dialysis. Recent examination has demonstrated that patients with
CKD who are not receiving dialysis have rates of depression up to three times
higher than those in the local community10. As a rule, depressed
patients are at higher risk for suicide and resistance with treatment. They
additionally have higher morbidity and mortality caused by renal disease.
Chronic kidney disease is an
arduous process wherein the patient will take time, commitment and compliance
to medical treatment in order to prevent the progression of the disease.
Quality of life has been very significant to a chronically ill individual,
considering and knowing the level of their quality of life will help the
healthcare providers to determine their basic and most important needs. Through
this study, the researchers aim to fulfill the answer the relation between
quality of life and the coping mechanisms among CKD patients and other
chronically ill individuals1. The casual pathways of depression in
CKD and ESRD together with the evaluation of interventions to prevent and treat
depression10.
These are the realities that
prompted the researchers to conduct the study of quality of life and depression
among patient with CKD in selected stand-alone renal facilities. It is hoped
that the relationship between the HRQOL and level of depression would be
understood.
Purpose:
The objectives of the study
were to:
1. Determine the demographic
profile, quality of life and the level of depression among chronic kidney
disease patients.
2. Correlate the demographic
profile of the respondents with the quality of life and level of depression.
3. Determine the relationship
between the quality of life and depression among chronic kidney disease
patients.
METHODS:
Design
overview and sampling technique:
The study utilized a
descriptive cross-sectional research as the design of the study and convenience
sampling for the selection of participants. The minimum sample size for the
study were 220 patients diagnosed with chronic kidney disease (CKD) on
hemodialysis which was computed based on the total population of patients with
CKD in Manila (1,780 individuals) It was computed using the formula for
estimating the population proportion based on the following information: (1)
confidence level is set at 95%; (2) expected population of CKD patients with
depression at 23.7% (Amira, 2011); and (3) a margin of error of 5%. Open Epi
website was utilized in this sample size calculation.
Setting of the Study:
The study was conducted in six
(6) standalone renal facilities in Manila. This were chosen setting due to the
proximity of the area to the researchers. According to the Philippine Society
of Nephrology11, there were 8 accredited renal facilities in Manila.
Standalone dialysis centers were able to provide the best and accurate data
collection among CKD patients.
Instrumentation:
The researchers were able to
utilized two instrumental tools which include Kidney-Disease Quality of Life-36
SF (KDQOL) Filipino Version to determine the health related
quality of life and Beck’s Depression Inventory-Filipino Version to determine
the level of depression among patients with CKD.
Data
Collection Procedures:
Prior to
the collection of data, a letter of approval to conduct the study were obtained
from the selected stand-alone renal facilities. After approval of ethics and
from the standalone renal facilities the researchers screened the participants
following the inclusion and exclusion criteria set in the study.
Before administering the
questionnaire to the participants, scheduled were arranged with the respective
standalone renal facilities for data gathering. A facilitated questionnaire was
given to the participants and was given 30 minutes to answer the BDI and KDQOL
Filipino version questionnaire.
Data
Analysis:
The data gathered were
analyzed using IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM
Corp. with a p-value of 0.05 was considered statistically significant.
Specifically, frequency, percentage, mean and standard deviation Pearson’s r
correlation.
FINDINGS:
Demographic Profile of the
Respondents:
A total of 220 CKD respondents
completed the Filipino version of KDQOL-SF questionnaire from different
stand-alone renal facilities. The majority of these respondents have age
ranging from 49-58 years old (28.63%) followed by 19-28 years old (8.21%),
29-38 years old (17.27%), 39-48 years old (20.45%), 59-68 years old (17.27%),
69-78 years old (6.36%) and 79 years old and above (1.81%).
Table 1. Demographic Profiles
of the Respondents
|
Profile (n=220) |
Descriptor |
n |
% |
|
Age |
19-28 29-38 39-48 49-58 59-68 69-78 79-Above |
18 38 45 63 38 14 4 |
8.21 17.27 20.45 28.63 17.27 6.36 1.81 |
|
Gender |
Male Female |
109 111 |
49.5 50.5 |
|
Level of education |
Elementary Undergraduate High School Undergraduate High School Graduate Vocational/College Undergraduate College Graduate Post-Graduate |
7 13 56 58 73 13 |
3.2 5.9 25.5 26.4 33.2 5.9 |
|
Civil Status |
Single Married |
58 162 |
26.4 73.6 |
In terms of their civil
status, 162 were married respondents (73.6%) while 58 (26.4%) were single.
There were also 109 male respondents (49.5%) and 111 female respondents
(50.5%).
Majority of the respondents
received formal education (73 or 33.2%) while 7 (3.3%) reached elementary, 13
(5.9%) were high school undergraduate, 56 (25.5%) were high school graduate, 58
(26.4%) were vocational/ college undergraduate while 13 (5.9%) have
post-graduate degree.
Quality of Life and Level of
Depression among Chronic Kidney Disease Patients:
Table 2 shows the mean scores of BDI and subscales of
KDQOL. Results revealed that the KDCS has the highest mean score of 53.10 among
the three components of KDQOL followed by MCS (M=51.93, SD= 16.18) and PCS
(M=40.90, SD=17.03).
Table 2. Mean Scores of
BDI and Domain and subscales of KDQOL
|
|
Mean |
SD |
|
Kidney disease component Score (KDCS) |
53.10 |
8.02 |
|
SF-12 Mental Composite Score (MCS) |
51.93 |
16.18 |
|
SF-12 Physical Composite Score (PCS) Beck’s Depression Inventory |
40.90 16.94 |
17.03 10.1 |
In terms of the level of depression, results revealed
that there was a low depression among the participants based on the mean score
of 16.94. In summary, BDI has an overall score of 63 and this means the lower
the score of BDI, the lower the level of depression among CKD patients.
Relationship of the Demographic
Profiles with the Level of Depression and Subscales of KDQOL:
Table 3 shows the relationship
of demographic profiles with the level of depression and subscales of KDQOL. A
Pearson product-moment correlation coefficient was calculated to assess the
relationship between the variables. Results revealed that there was significant
negative correlation between the age and the PCS (r= -0.169, n=220, p= 0.012).
This means that the lower the age of the respondents, the higher the level of
physical functioning. However, no significant correlation was noted with the
other demographic profiles with regards to MCS, KDCS, and BDI.
Relationship of subscales of
KDQOL with level of depression:
Table 4 shows the relationship
of subscales of KDQOL with level of depression. Out of the three components of
KDQOL, significant negative correlation in the subscales of KDCS and MCS with
the level of depression were noted as proven by p value of <0.05. This means
that the higher the score of KDCS and MCS, the lower the level of depression.
Table 3. Relationship of
Demographic Profiles with Level of Depression and Subscales of KDQOL
|
Profiles
|
PCS |
MCS |
KDCS |
BDI |
||||
|
r |
p |
r |
p |
r |
p |
r |
p |
|
|
Age |
-0.169 |
0.012* |
-0.051 |
0.454 |
0.032 |
0.633 |
0.027 |
0.695 |
|
Gender |
0.014 |
0.835 |
0.068 |
0.316 |
0.126 |
0.061 |
-0.007 |
0.915 |
|
Level of Education |
0.092 |
0.175 |
0.126 |
0.062 |
0.022 |
0.744 |
-0.027 |
0.691 |
|
Civil Status |
-0.028 |
0.678 |
0.001 |
0.988 |
0.031 |
0.651 |
0.015 |
0.124 |
*p value is significant at <0.05 level
Table 4 Relationship of
subscales of KDQOL with level of depression
|
|
R |
p |
|
Kidney disease component Score (KDCS) |
-0.178 |
0.008* |
|
SF-12 Mental Composite Score (MCS) |
-0.212 |
0.002* |
|
SF-12 Physical Composite Score (PCS) |
-0.123 |
0.069 |
*p value is significant at
<0.05 level
DISCUSSION:
The study aims to determine
the relationship of the demographic profile with the quality of life and level
of depression among CKD patients. Health-related quality of life (HRQOL) plays
an important role as a marker on treating chronic diseases. Its evaluation
allows measuring the disease consequences according to the subjective
perception of CKD patients.
Based on the overall KDQOL of
the respondents, it was found that KDCS has the highest score, followed by MCS
while PCS has the lowest score. According to Mujais
et al.9, PCS was the most affected sub-scale in KDQOL among CKD
patients which results to the need for assistance in performing normal daily
routines. The findings were further supported by Masina,
Chimeral, Kampondal and
Dreyer12 which stated that the scores for the PCS were lower as
compared to scores in the KDCS and MCS domains. The low scores of the study
recorded in the domains of energy/fatigue and role physical are likely to be
multi-factorial but may specifically reflect untreated anemia. Failure of a
patient’s kidneys also limits their physical functioning and energy since their
bodies would accumulate toxins that would have been excreted with normal kidney
function. This greatly diminishes their functioning the longer their interval
of hemodialysis, hence the low scores as reflected in the study.
In the study the level of
depression falls under mild depression, this can be attributed to the culture
of Filipinos as family-centered and all around
positivism. According to Medina (2001) and Miralao
(1994) as cited by Morillo, Capuno
and Mendoza13 familism is embedded in the Filipino culture,
translating its relational quality outside the family. Being family-centered,
child-centric, having close ties, and a large family size some basic elements
of families in the Philippines. This provides social support wherein Filipinos
tend to deviate their depressive symptoms because of the inherent support and
availability of family members. Furthermore, according to Salikha14
the Philippines ranked 4th out of 9 countries in a survey related to
the happiest countries in South East Asia and ranked 71st out of 156
countries.
In terms of the relationship
of the demographic profiles with the sub-scales of KDQOL, it was found that the
age showed a significant negative correlation with PCS which means the lower
the age of the respondents, the higher their level of physical functioning.
This finding was supported by Soni et al.15
which found that older patients (>65 years) had a poor physical performance
thus having a lower PCS score.
The study also revealed that
the level of education, as well as civil status, were not relatively significant
in determining their coping function to their situation. This finding was also
supported by Ottaviani et al. (2016) which stated that civil status and level
of education did not have any significant relationship to the occurrence of the
disease.
In KDQOL it shows that the
lower the KDCS and MCS leads to a higher level of depression among CKD
patients. These patients are more expected to report burden symptoms, physical
limitation, and diminished quality of life and they were also more like to report
fair or poor overall health. These findings were supported by Piriano et al16 which stated that a strong
correlation between depression and poor health-related quality of life.
Depression was associated with decrements in multiple domains, including but
not limited to kidney-disease-related symptoms, the perception of kidney
disease as a burden and patients’ self-rated health.
KDQOL is a critical predictor
in depression since KDQOL sums up an individuals’ perception of mental,
physical and social health. Perception of a patient may change over time and
may suggest a critical predictor in the overall wellness and how it will or
will not affect the quality of life of an individual.
Similar to other studies, the
dimension of quality of life which has the lowest score was the occupational
status, whereas the majority of the respondents have higher scores in the
cognitive function and quality of social interaction. In the current study, the
effects of daily life, social support satisfaction, sleep, sexual function,
staff encouragement and satisfaction were higher in women; however, gender had
no effect on HRQOL as cited by Rostami17.
CONCLUSIONS:
The study concluded that
younger patients with CKD have a higher level of physical functioning as
compared to older patients. Furthermore, CKD patients with a higher quality of
life have a lower level of depression.
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Doi: 10.5812/numonthly.12485.
Received on 18.01.2019
Modified on 15.02.2019
Accepted on 06.03.2019
©A&V Publications All right reserved
Asian J. Nursing Education and
Research. 2019; 9(2):251-255.
DOI:
10.5958/2349-2996.2019.00053.3