Health-Related Quality of Life among Hemodialysis Patients and Its Associated Factors in Betong and Sarikei Divisions, Sarawak

• Main Authors: Bujang Zaharuddin, Ramdzan Abdul Rahman, Pang Tze Ping Nicholas, Hidrus Aizuddin
• Format: Proceedings
• Language: English; English
• Published: Penerbit UMS 2024
• Subjects: R5-920 Medicine (General); R858-859.7 Computer applications to medicine. Medical informatics
• Online Access: https://eprints.ums.edu.my/id/eprint/39235/1/ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/39235/2/FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/39235/; https://jurcon.ums.edu.my/ojums/index.php/bjms/article/view/5046
• Institution: Universiti Malaysia Sabah

Chronic kidney disease (CKD) is a significant worldwide health issue that is associated with high rates of morbidity, death, and health care expenses. The prevalence of CKD in Malaysia is around 9.07 percent, with 0.36 percent of the population affected by CKD stage 5. Since there is no study yet in Sarawak to measure the Health-Related Quality of Life (HRQoL) of hemodialysis patients, this is the primary reason for conducting this study. Thus, the HRQoL of hemodialysis patients can be improved if factors affecting their HRQoL can be identified through this study. This study was conducted using a cross-sectional approach. The data was collected from 153 respondents by visiting 4 dialysis centres from September until November 2022. Factors investigated in the study are socio-demographic, clinical, hemodialysis adequacy and medical cost support. HRQoL was assessed using the EQ-5D 5L questionnaire that was given to those who meet the requirements. The obtained utility score varied from “0” which indicates worse HRQoL to “1” represent good HRQoL. Descriptive statistics were conducted based on sociodemographic data. Mann-Whitney test, Kruskal Wallis test and Spearman correlation were performed to identify the relationship between variables. Data analysis was done based on numerical outcomes. Overall this study shows that HRQoL among hemodialysis patients is generally good with a mean utility score result of 0.95. The main socio-demographic factors associated with HRQoL were educational background (p = .001) and employment status (p = .001). While only haemoglobin level affected overall HRQoL in clinical characteristics (p = .003). Last but not least, medical cost support does affect the overall HRQoL among hemodialysis patients in this study (p = .019). Our results suggest that the patient's quality of life can be improved if the patient undergoing hemodialysis treatment has a steady source of income and a good educational background. Furthermore, a haemoglobin level between 10-12g/dL is suggested to improve their quality of life. Finally, this study suggests that medical cost support can help patients ease their financial burden and further improve their quality of life.