Susan Mathai1, Dency Sebastian2, Anju Mary George3, Ann Maria S3, Ann Maria Sony3,
Ann Mariya Sajeev3, Ansa Sabu3
1Associate Professor, Department of Medical Surgical Nursing, M.O.S.C College of Nursing, Kolenchery.
2Assistant Professor, Department of Mental Health Nursing, M.O.S.C College of Nursing, Kolenchery.
3Fourth Year B.Sc. Nursing Students, M.O.S.C College of Nursing, Kolenchery.
*Corresponding Author E-mail: susanriju@gmail.com, denseb.06@gmail.com
ABSTRACT:
A correlational study was done to assess the degree of lifestyle modifications and its relationship with quality of life among patients undergoing hemodialysis in a tertiary care hospital in Central Kerala. The objectives of the study were to assess the relationship between lifestyle modifications and quality of life among patients undergoing hemodialysis, to assess the association of lifestyle modifications with the selected socio-demographic variables and to assess the association of quality of life with the selected socio-demographic variables. The study design used is correlational study design. The study was conducted in M.O.S. CMedical Mission Hospital, Kolenchery, using convenient sampling, 90 hemodialysis patients were enrolled in the study. Socio-demographic performa, a self-structured questionnaire on lifestyle modifications and a standardized questionnaire of KDQOL-36 Quality of Life Assessment were used to collect the data. The data analysis was done using descriptive and inferential statistics like percentage, frequency, mean and standard deviation. The study results showed that, there is a statistically significant weak negative correlation between lifestyle modifications and the domain of symptom or problem affecting the quality-of-life ina hemodialysis patient (p=0.043). There is a significant association between lifestyle modifications and selected socio-demographic variables such as age, marital status, occupation and income (p=0.005, p=0.010, p=0.023, p=0.028 respectively). Also, there is a significant association between the quality of life and the socio-demographic variable of burden of medical expenses (p=0.034).
KEYWORDS: Lifestyle modifications, Quality of Life, Hemodialysis.
INTRODUCTION:
Hemodialysis is the choice of renal replacement therapy for patients who need dialysis acutely and for many patients as maintenance therapy. It is a process of purifying the blood of a person whose kidneys are not working normally. This type of dialysis achieves the extra corporeal removal of waste products such as creatinine and urea and free water from the blood when the kidneys are in a state of kidney failure. Routine hemodialysis is conducted in a dialysis outpatient facility, either a purpose-built room in a hospital or a dedicated, stand-alone clinic. Less frequently hemodialysis is done at home. Removing too much fluid or removing fluids too rapidly causes low blood pressure, fatigue, chest pain, leg cramps, nausea and headache1. A healthy renal system is essential for the proper functioning of the body. So, diseases associated with the renal system should be early diagnosed and treated effectively, otherwise, it can lead to fatal conditions. Chronic Kidney Disease (CKD) is a debilitating condition which has emerged as one of the leading causes of mortality worldwide. Chronic kidney disease (CKD) is a type of kidney disease in which a gradual loss of kidney function occurs over a period of months to years. The presence of Glomerular Filtration Rate [GFR] less than 60mL/min and albumin greater than 30mg per gram of creatinine, along with 3 abnormalities of kidney structure or function for greater than three months signifies chronic kidney disease. End-stage renal disease is defined as a GFR of less than15mL/min2. A kidney transplant is often the best option for people who have end-stage kidney disease, but it’s not always possible. In that case, dialysis makes it possible to continue living with end-stage kidney disease for many years or even decades by providing a renal.
replacement therapy3. In India, it is reported that the progression of chronic kidney disease (CKD) to ESRD is rapid due to the factors such as lack of medical facilities, poor control of risk factors and delayed referral to nephrologists4. The reported prevalence of CKD in different regions ranges from 1% to 13%, and recently, data from the International Society of Nephrology’s Kidney Disease Data Center Study reported a prevalence of 17%5. Over 3/4th of the people suffering from ESRD, especially from rural area, are not treated at all. Chronic renal failure has mutual effects on physical, psychological and functional status of individuals which causes types of deprivation and lifestyle changes including financial problems, unemployment, restriction in fluid intake and diet, change in familial roles and tasks and reduction in achieving long term goals. Health status and quality of life are very important concepts for patients with chronic kidney disease (CKD) and those undergoing hemodialysis6. At the end of the next decade, the number of patients with end-stage renal disease, who need dialysis therapy, may be doubled. Thus, there is an increasing need to assess the quality of life of hemodialysis patients according to their lifestyle.
Data was gathered using three questionnaires. Tool 1, consists of two sections socio demographic variables and standardized KDQOL- 36 quality of life assessment, consists of 36 items; self reporting questionnaire designed to assess a person’s quality of life in five domains- symptoms or problems, effect of kidney disease, burden of kidney disease, physical health composite, mental health composite.
Tool 2 is a self structured questionnaire on lifestyle modifications. The tool was developed by the researchers and validated by five experts from the medical and nursing fields.
Research Approach:
Quantitative research design was adopted for the study.
Research Design:
Correlational study design was used for this study.
Variables:
Outcome variables: Lifestyle modifications, Quality of life.
Selected Demographic Variables:
Age, Gender, Marital status, Education, Occupation, Income, Alcohol intake, Smoking, Diet, Number of dialysis in a week, Duration, Health insurance, Burden on medical expenses, Co-morbidities.
Research Setting:
The setting of the present study was a selected dialysis unit of a tertiary care hospital in Central Kerala.
Population:
Population refers to patients with AV fistula undergoing hemodialysis in Ernakulam district Kerala.
Sample:
The sample selected for the study was hemodialysis patients admitted in the dialysis unit of M.O.S.C Medical College Hospital, Kolenchery.
Sample size:
Ninety hemodialysis patients admitted in the dialysis unit of M.O.S.C Medical College Hospital, Kolenchery.
Based on the pilot study, sample size was estimated using following equation,
n=Z²1-α/2σ²(μd) ²
The anticipated standard deviation = 8.7 Anticipated mean = 93 Precision = 0.02 Statistical table value = 1.96 By this equation, estimated sample size is 84 A total of 90 participants were included in the current study.
Sampling Technique:
Convenient sampling technique was used for the study.
Sampling criteria:
Inclusion Criteria:
Age group above 20 years, patients who are able to read Malayalam.
Exclusion Criteria:
Critically ill patients, mentally challenged patients.
Relationship between lifestyle modifications and quality of life:
Table 1: Relationship Between Lifestyle Modifications and Quality of Life in the Five Domains
|
Variables |
Pearson’s Correlation Coefficient |
p value |
|
Symptoms/ProblemList |
-0.214 |
0.043 |
|
EffectofKidneyDisease |
-0.001 |
0.991 |
|
BurdenofKidneyDisease |
-0.146 |
0.171 |
|
PhysicalHealth Composit |
-0.102 |
0.337 |
|
MentalHealth Composit |
0.028 |
0.792 |
p value<0.05 is significant
Table 1. shows weak negative correlation between the lifestyle modifications and the domain of symptom/problem affecting the quality of life of hemodialysis patients.
Table 2: Relationship Between Lifestyle Modifications And Socio-Demographic Variables
|
Socio |
Lifestyle Modifications |
ChiSquare |
p value |
||
|
Demographic Variables |
Poor |
Average |
Good |
Fisher’s Exact |
|
|
Age in years |
|
|
|
|
|
|
20-30 |
0 |
3 |
2 |
|
|
|
31-40 |
0 |
0 |
3 |
Fisher’s |
0.005 |
|
41-50 |
0 |
11 |
1 |
Exact |
|
|
51and above |
0 |
59 |
11 |
Fisher’s |
1.00 |
|
Gender |
|
|
|
|
|
|
Male |
0 |
55 |
13 |
Exact |
|
|
Female |
0 |
18 |
4 |
|
|
|
Marital Status |
|
|
|
|
|
|
Married |
0 |
70 |
13 |
Fisher’s |
0.010 |
|
Single |
0 |
2 |
4 |
Exact |
|
|
Separate |
0 |
1 |
0 |
|
|
|
Widow |
0 |
0 |
0 |
|
|
|
Education |
|
|
|
|
|
|
PrimarySchool |
0 |
28 |
5 |
Fisher’s |
0.080 |
|
High school |
0 |
13 |
8 |
Exact |
|
|
Diploma |
0 |
5 |
1 |
|
|
|
Degree |
0 |
27 |
3 |
|
|
|
Occupation |
|
|
|
|
|
|
Employed |
0 |
12 |
2 |
Fisher’s |
0.023 |
|
Unemployed |
0 |
26 |
12 |
Exact |
|
|
Retired |
0 |
35 |
3 |
|
|
|
Income |
|
|
|
|
|
|
<50,000 |
0 |
48 |
17 |
Fisher’s |
0.028 |
|
50,000-79,000 |
0 |
21 |
0 |
Exact |
|
|
80,000-1,00,000 |
0 |
2 |
0 |
|
|
|
>1,00,000 |
0 |
2 |
0 |
|
|
|
Alcohol intake |
|
|
|
Fisher’s |
1 |
|
Yes |
0 |
6 |
1 |
Exact |
|
|
No |
0 |
67 |
16 |
Fisher’s |
|
|
Smoking |
|
|
|
|
|
|
Yes |
0 |
2 |
1 |
Exact |
0.470 |
|
No |
0 |
71 |
16 |
|
|
|
Diet |
|
|
|
|
|
|
Vegetarian |
0 |
5 |
0 |
Fisher’s |
0.142 |
|
Non-vegetarian |
0 |
12 |
0 |
Exact |
|
|
Mixed |
0 |
56 |
17 |
Fisher’s |
|
|
Number of dialysis in a week |
|
|
|
|
|
|
Once |
0 |
0 |
0 |
Exact |
|
|
Twice |
0 |
42 |
11 |
|
|
|
Thrice |
0 |
31 |
6 |
|
0785 |
|
Duration |
|
|
|
|
|
|
<6months |
0 |
8 |
1 |
Fisher’s |
|
|
6months-1 year |
0 |
7 |
2 |
Exact |
1 |
|
>1 year |
0 |
58 |
14 |
Fisher’s |
0.908 |
|
Health insurance |
|
|
|
|
|
|
Yes |
0 |
28 |
8 |
Exact |
|
|
No |
0 |
45 |
9 |
|
|
|
Burden on medical expenses |
|
|
|
|
|
|
Self |
0 |
5 |
3 |
Fisher’s |
0.287 |
|
Parents |
0 |
8 |
2 |
Exact |
|
|
Lifepartner |
0 |
16 |
|
|
|
|
Children |
0 |
39 |
6 |
|
|
|
Others |
0 |
5 |
0 |
|
|
|
Comorbidities |
|
|
|
|
|
|
Diabetes mellitus |
0 |
22 |
7 |
|
|
|
Hypertension |
0 |
33 |
4 |
|
|
|
Cardiovasular diseases |
0 |
2 |
0 |
Fisher’s |
0.374 |
|
Hyperlipidemia |
0 |
4 |
1 |
Exact |
|
|
Others |
0 |
12 |
5 |
|
|
p value<0.05 is significant
Fisher’s exact test was used to determine whether there is any relationship between lifestyle modifications and socio-demographic variables. It is found that among the socio- demographicvariables,significantassociationwithlifestylemodificationswerefoundforage (p=0.005), marital status (p=0.010), occupation (p=0.023), income (p=0.028).
Relationship between quality of life and socio-Demographic Variables:
Table 3: Relationshipbetween qualityoflifeandsocio-demographic variables
|
Sociodemographic variables Quality of life |
|
Chi- Square/Fischer’s |
|
Pvalue |
|
Agein years |
Lowrisk |
High risk |
Exact |
|
|
20-30 |
4 |
1 |
|
|
|
31-40 |
1 |
2 |
2.466 |
0.481 |
|
41-50 |
5 |
7 |
|
|
|
51and above |
35 |
35 |
|
|
|
Gender |
|
|
|
|
|
Male |
30 |
38 |
2.948 |
0.085 |
|
Female |
15 |
7 |
|
|
|
Marital status |
|
|
|
|
|
Married |
41 |
42 |
1.6787 |
0.432 |
|
Single |
4 |
2 |
|
|
|
Separate |
0 |
0 |
|
|
|
Widow |
0 |
1 |
|
|
|
Education |
|
|
|
|
|
Primaryschool |
14 |
19 |
|
|
|
High school |
13 |
8 |
1.948 |
0.583 |
|
Diploma |
3 |
3 |
|
|
|
Degree |
15 |
15 |
|
|
|
Occupation |
|
|
|
|
|
Employed |
4 |
10 |
|
|
|
Unemployed |
20 |
18 |
3.097 |
0.212 |
|
Retired |
21 |
17 |
|
|
|
Income (Rs) |
|
|
|
|
|
<50,000 |
32 |
33 |
||
|
50,000-79,000 |
10 |
11 |
2.063 |
0.5590 |
|
80,000-1,00,000 |
2 |
0 |
|
|
|
>1,00,000 |
1 |
1 |
|
|
|
Alcohol intake |
|
|
|
|
|
Yes |
3 |
4 |
0 |
1 |
|
No |
42 |
41 |
|
|
|
Smoking |
|
|
|
|
|
Yes |
0 |
3 |
1.379 |
0.240 |
|
No |
45 |
42 |
|
|
|
Diet |
|
|
|
|
|
Vegetarian |
3 |
2 |
0.214 |
0.898 |
|
NonVegetarian |
6 |
6 |
|
|
|
Mixed |
36 |
37 |
|
|
|
Number of dialysis in |
|
|
|
|
|
a week |
|
|
0 |
1 |
|
Once |
0 |
0 |
|
|
|
Twice |
26 |
27 |
|
|
|
Thrice |
19 |
18 |
|
|
|
Duration |
|
|
|
|
|
<6months |
4 |
5 |
3.389 |
0.183 |
|
6months-1 year |
2 |
7 |
|
|
|
>1year |
39 |
33 |
|
|
|
Health insurance |
|
|
|
|
|
Yes |
18 |
18 |
4.32 |
0.364 |
|
No |
21 |
33 |
|
|
|
Burden on medical |
|
|
|
|
|
expenses |
|
|
|
|
|
Self |
5 |
3 |
|
|
|
Parents |
6 |
4 |
10.383 |
0.034 |
|
Lifepartner |
13 |
9 |
|
|
|
Children |
16 |
29 |
|
|
|
Others |
5 |
0 |
|
|
|
Co-morbidities |
|
|
|
|
|
Diabetes mellitus |
14 |
15 |
|
|
|
Hypertension |
20 |
17 |
|
|
|
Cardiovascular |
1 |
1 |
1.007 |
0.908 |
|
diseases |
|
|
|
|
|
Hyperlipidemia |
3 |
2 |
|
|
|
others |
7 |
10 |
|
|
p value<0.05 is significant
Chi square and fisher’s exact test was performed to assess whether there is a any significant relationship between quality of life and socio-demographic variables. Among these socio- demographic variables, burden of medical expenses was found to be significantly associated with quality of life (p=0.034).
The present study was intended to assess the degree of lifestyle modifications and its relationship with quality of life among patients undergoing hemodialysis in a tertiary care hospital in central Kerala.
Section A: Major study finding showed a significant weak negative correlation between lifestyle modifications and the domains of symptoms affecting the quality of life in a hemodialysis patient,where the p value is 0.043. A cross sectional study was conducted in Greece onthetopicquality oflife inhemodialysis patient and itwas found that theincreasing duration of hemodialysis session entailed poorer quality of life. Socio-demographic and clinical characteristics seems to influence the quality of life in hemodialysis patients.
Section B: The present study found that there is a significant relation in quality of life and burden on medical expenses for which the p value is 0.034.A descriptive study in Nanchong on the topic economic burden of maintenance hemodialysis patient’s family and its influencing factors. Various medical insurance system can effectively reduce the economic burden of hemodialysis patients, but patients must still bear the significant financial hardship.
The conclusion drawn from the study is that there is a significant association between lifestyle modification and quality of life in the domains of symptom or problem (p=0.043).There is a significant association between lifestyle modifications and selected socio-demographic variables such as age( p=0.005), marital status (p=0.010),occupation (p=0.023) and income (p=0.028).Also there is a significant association between the demographic variables of burden on medical expenses and quality of life (p=0.034).
ACKNOWLEDGEMENT:
Here we extend our sincere thanks to all the heamodialysis patients who participated in the study.
CONFLICT OF INTEREST:
The authors declare no conflict of interest in the study
1. Kidney Failure: Choosing a Treatment That's Right for You". National Kidney and Urologic Diseases Information Clearing house guidance. Archived from the origin alon. 2010: 09-16.
2. Scott IA, Scuffham P, Gupta D, Harch TM, Borchi J, Richards B. Going digital: a narrative overview of the effects, quality and utility of mobile app sinchronic disease self- management. Aust Health Rev. 2020 Feb; 44(1): 62-82.
3. BaillieJ, Lankshear A. Patient and family perspectives on peritoneal dialysis at home: findings from an ethnographic study. J Clin Nurs 2015; 24(1-2): 222-234.
4. Ballal HS. The burden of chronic kidney disease in adeveloping country, India. Ouest. 2007; 9:12–9.
5. Ene-Iordache Betal G: Chronic kidney disease and cardio vascular risk in six regions of theworld (ISN-KDDC): Across-sectionalstudy. Lancet Global Health. 2016; 4: e307–e319.
6. Yaghmayi F, Khalfi E, Khost N, Alavi A. The relationship between self- concept dimensions of heal the status in patients treated with hemodialysis in medical science hospital in 2004. Pajoohandeh Journal. 2005; 1(6): 9–15.
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Received on 22.05.2025 Revised on 19.06.2025 Accepted on 14.07.2025 Published on 14.08.2025 Available online from August 23, 2025 Int. J. of Advances in Nursing Management. 2025;13(3):169-173. DOI: 10.52711/2454-2652.2025.00033 ©A and V Publications All right reserved
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