An analytical cross-sectional study design was selected for this study with a quantitative approach that allowed for objectivity and accuracy of findings.

The study was conducted in 2020 to 2021 at University Teaching Hospitals. The University Teaching Hospital is an 1800-bed capacity specialized hospital and the largest centre for various specialist referrals from across the country whose population stands at 18 million [18].

The population under study was Chronic Kidney Disease patients above 18 years on permanent dialysis at UTH Dialysis Unit.

A census sampling technique was used to select CKD patients on dialysis at the Unit. The selected population of 104 patients was grouped into two according to the days they came for dialysis, that is group one (52 patients) attended dialysis on Monday and Wednesday and group two (55) attended dialysis on Tuesday and Thursday.

The Unit provided dialysis sessions in three (3) blocks per day lasting three to four (3 - 4) hours for each patient, with 19 functioning dialysis machines. Each patient had two (2) sessions per week and a permanent time slot on each given day. Interviews were conducted on Monday and Tuesday at 07 hours and 14 hours; Wednesday and Thursday at 10 hours and 17 hours, approximately 26 patients were being interviewed each day.

The inclusion criteria were as follows:

1) Patients commenced on dialysis for two months and longer.

2) Consenting participants.

The exclusion criteria were as follows:

1) Patients on dialysis for other conditions other than CKD.

2) Critically illness patients on dialysis.

The tool was adapted from the validated Kidney Disease Quality of Life Short form (KDQOL-SF 36) item score and Quality of Life Questionnaire for Dialysis Patients. These instruments were chosen for this study because they reflected central components of HRQoL that were under study, namely biological, functional, psychological and sociological wellbeing.

The collection of data was done at the UTH Renal Unit as eligible patients come for dialysis. The interview process commenced by giving a self-introduction after which the purpose of the interaction was elaborated. Consent from the participants and Renal Unit Manager was obtained to collect data on haemoglobin levels done within the last three months. After assurance of confidentiality, written consent was obtained. For those who were unable to write, a thumbprint was obtained. During the interview process, the researcher read out the questions and clarified for those who had difficulties in understanding the questions. At the end of each interview, the researcher thanked each participant. The interviews lasted 15 to 20 minutes with each participant.

Ethical clearance was obtained from the University of Zambia Biomedical Research Ethical Committee (UNZAREC, ref no. 1159-2020) and written permission from University Teaching Hospital and the National Health Research Authority (Ref no. NHRA 00004/15/10/2020). Information sheets explaining the study and expected benefits were given to participants, thereafter-informed written consent was obtained.

Participants were assured that dialysis would not be withheld should they opt-out of the study. It was anticipated that participants would experience distress and embarrassment discussing intimate details of the illness and the impact of the illness on their lives. Participants were assured that they could stop the interview at any point when it becomes too distressful; a counsellor was available in case a participant required one during the interview.

The collected data coded, entered and analysed using Stata® version 13. Analysis using a Chi-square tests was employed to establish the statistical significance of variables. The multivariate analysis of data was carried out using binary logistic regression and adjusted for confounders to elucidate associations of HRQoL. A confidence interval of 95% was set, and p-value of <0.05.

This study showed that the majority (60.6%) of the patients were male. Three-quarters (68.3%) of the participants were married and 31.7% were single. Almost half (49%) of the patients had secondary education, with 59.6% being unemployed. The mean duration period from dialysis initiation was two years with a standard deviation of 1.9 while the mean age was 43.9 years with a standard deviation of 1.3 (Table 1).

This study found that majority of the patients had low scores in three HRQoL domains that is functional well-being (68.3%), sociological well-being (73.1%), and psychological well-being (64.4%) (Table 2). All the patients scored 100% in the biological wellbeing as most patients reported minimal symptoms resulting from CKD and dialysis at the time of data collection. Composite scores revealed above average mean scores (Functional—57.4, Sociological—54.5, Psychological—57.3 and Biological Wellbeing—87) of the HRQoL domains (Table 3). As a result of the high biological scores, an aggregation of the composite scores of all four domains found that the majority (65.4%) of the participants had good HRQoL.

Adequacy of dialysis as measured by Kt/v and URR was optimal with 96.2% and 83.7% respectively of patients achieving acceptable dosing (Table 4).

Clinical determinants (Table 5) of CKD and dialysis that influence HRQoL were

*SD = Standard deviation.

*Kt/V = Adequacy of dialysis.

evaluated using haemoglobin levels, presence of comorbidity, and Karnofsky function scale. The study found low haemoglobin levels in two-thirds (73.1%) of the patients with a reading below 10 grams per decilitre only about 26.9% of patients exhibited normal HB levels. Almost all (99%) the patients had pre-existing or acquired comorbidities. Hypertension (89.4%) was the most prevalent followed by Diabetes mellitus (7.7%) and cardiovascular disease (2.9%). Karnofsky function scale showed that half (51%) of the patients had some limitation in physical function. The majority (95.2%) of patients were receiving haemodialysis with only 4.8% being on peritoneal dialysis.

The relationship between demographic variables and HRQoL (Table 6) showed that male patients (66.7%) had poor HRQoL than female patients. Unemployment (69.4%) and having tertiary education (47.2%) were associated with poor HRQoL outcomes. Poor HRQoL (75%) was revealed in married patients than the single patients. Similarly, mature age (SD 11.5) and longer duration on dialysis (SD 2.4) treatment showed an increase the prevalence of poor HRQoL among participants.

Low Haemoglobin levels (77.8%) and comorbid states (100%) were associated with poor HRQoL. Additionally, the study found that with optimal adequacy of dialysis good HRQoL was seen in almost all the patients (97.1% and 85.3%); on the other hand, poor HRQoL was seen in participants who had inadequate urea reduction ratios (13.9%). However, none of the results was statistically significant (Table 7).

*SD = Standard deviation.

Performance of logistic regression revealed factors that influenced HRQoL (Table 8). Literature review guided the decision to conduct logistic regression.

*OR = Odds ratio; CI = Confidence interval; Ref = Reference category.

Therefore, the selection of age, sex, educational level, haemoglobin level, employment status, marital status, residence, functional category (KFS), and duration on dialysis was made as these were observed to influence HRQoL. In the analysis, one represented poor HRQoL and zero good HRQoL.

The binary logistic regression model analysis revealed that unemployed patients were 90% less likely to attain good HRQoL. A clinically significant finding showed that low HB levels increased the odds of poor HRQoL by 31%, while the male sex and being married resulted in 33% and 36% respectively, less probability of a good HRQoL. However, regression did not yield any statistical significance.

This study (Table 1) revealed that the majority (60.3%) of participants were male. Generally, CKD is higher in females than males though this male predominance noted in studies can be attributed to a lack of the protective function that is seen in females due to the presence of oestrogens. Males progress rapidly to end-stage kidney disease and are consequently initiated on renal replacement therapy earlier than females [19]. Further, males tend to have morbid lifestyles, thereby leading to a higher risk for kidney failure.

In addition, this study found a mean age of 43.9 years (SD = 1.3) among participants. These findings reflect those of a study done in Ghana whose patients exhibited a mean age of 46.7 years (SD = 16.2). Contrary to this finding other studies have [20] found the mean age much higher at 80.7 years (SD = 6.8). The findings confirm the notion that disease patterns vary greatly between developing and developed countries. The mean age of patients on dialysis in developing countries is lower than in developed countries perhaps due to the lack of advanced medical interventions that help in reducing the progression of CKD leading to the initiation of dialysis at a much-advanced age.

The present study revealed that 49.0% of the patients had secondary education with 44.3% having tertiary education. This finding reflects that educational levels may influence health-seeking behaviours; populations with minimal education are likely to end up with more chronic diseases than literate population that may have information and access to disease prevent services. The high prevalence of this population among CKD patients on dialysis is due to unhealthy modifiable behaviours such as smoking [21].

The study demonstrated high unemployment rates among patients on dialysis (59.6%); this echoes the finding in South African [22]. From the results, it is clear that patients on dialysis experience barriers to employment, these barriers may result from an inability to cope with occupational stress, time constraints related to dialysis sessions, and limited physical functionality.

In response to determining the HRQoL of patients on dialysis, results revealed that the majority (65.4%) of CKD patients receiving dialysis at UTH-Adult hospital have a good health-related quality of life. This finding is broadly similar to a study in Nepal that reported that CKD patients on dialysis treatments had better QOL than those not on dialysis [23]. The findings of the current study could be attributed to high scores noted in biological wellbeing, as for most patients the absence of serious symptoms and optimal adequacy of dialysis gave a positive perspective of quality of health. However, these findings suggest that patients’ perception of the determinants of HRQoL may be related to the presence or absence of signs and symptoms, but also other factors that exist outside variables covered in this study.

The results revealed that scores were generally low across three HRQoL domains that is the psychological, sociological and functional wellbeing. The study found that patients with poor HRQoL (34.6%) particularly had average to low scores in the psychological (70%) and functional (61%) well-being. Similar studies have found that decreased functionality and psychological stress diminishes HRQoL [24] [25]. The physical function of CKD patients is attributed to anaemia and uremic myopathy, further patients may also experience chronic fatigue due to their inactive state, experience loss of self-esteem, and feeling disabled. The effect of poor physical function results in the inability to work and low financial coverage resulting in mental anguish, anxiety, and depression.

In this study being male increased the incidence (67%) of poor HRQoL than for females (33%). This could be attributed to the fact that men exhibited greater levels of perceived stress related to CKD and dialysis. Moreover, the impact of stress on HRQoL is higher in males than females, as the utilization of adaptive stress coping mechanisms is more effective among females. While males tend to use maladaptive strategies, such as excessive alcohol consumption that can further lower their HRQoL [26]. Contrary to these findings, an Emirati study found females to have poor HRQoL than males a finding attributed to females exhibiting more symptoms and problems [27]. However, the results observed were not statistically significant as p-value was greater than 0.05.

In this study, an increase in age was associated with the incidence of poor outcomes in HRQoL. Although not statistically significant (p > 0.05), this finding is important clinically to note when caring for patients that are elderly. Research findings show that younger patients generally have significantly good HRQoL [23]; further findings highlighted that with each one-year increase in age, the risk of poor outcomes increased by 3%. In assenting to this finding, a Chinese study confirmed that higher age was related to low functional scores particularly [28]. Higher age is associated with increased risk of other non-communicable conditions that lead to commodities identified in older patients on dialysis hence poor HRQoL as the outcome.

Educational level is a plausible predictive factor of quality of life, it may have been assumed that higher levels of education should result in better HrQoL, however, this study revealed that the incidence of poor HRQoL was higher (47%) in tertiary education, a finding consistent with research [11]. Even though patients with tertiary education may have a broad understanding of the disease and self-management, the knowledge about probable prognosis and complications of dialysis and CKD may contribute to a poor perception of health. Further, the added stress of maintaining full-time employment and a restrictive dialysis schedule may worsen the situation.

Health-related quality of life was found to be affected by employment status of the patients. The risk of poor HRQoL increased by 69.4% in unemployed participants, while being employed increased the outcome of good HRQoL by 45.6%. This has been seen as a common occurrence in studies [29] [30], it is reported that an increase in the social-economic gradient promotes good HRQoL, and vice vasa poor social-economic situations lead to poor HRQoL [31]. An unanticipated finding was the lack of statistically significant association between unemployment and HRQoL (p > 0.137), as a lack of regular income, demanding dialysis and CKD-related costs are burdensome and likely to cause poor HRQoL.

The study revealed that the majority (73.1%) of the participants were found to have low HB levels. Cross-tabulation of HB levels and HRQoL revealed that in patients with low HB, the incidence of poor HRQoL increased from 22.2% to 77.8%, and equally with a normal HB the occurrence of good HRQoL increased from 29.4% to 70.6%. These findings are consistent with previous research showing that reduced HB levels worsen the impact of Chronic Kidney Disease on HRQoL [32]. It is important to highlight the fact that previous studies confirm that low HB levels are prevalent among dialysis patients because CKD causes dysfunctional synthesis of erythropoietin by the kidneys causing a reduction in erythrocyte production [32] [33] [34].

The results of this study showed that adequacy of dialysis was optimal in 90% of the patients, with Kt/V and URR being found to be above 1.2% and 65% respectively. From the cross-tabulation, it was observed that with optimal adequacy of dialysis HRQoL increased from 11.8% to 85.3% when measured by URR, and when measured by Kt/V HRQoL increased from 0% to 97.1%. These findings support the notion that strict adherence to Kidney disease treatment guidelines that are in use at UTH-Adult hospital. Additionally, UTH may have more specialized care providers and newer machines that can provide higher blood flow rates to achieve optimal adequacy of dialysis.

Almost all (99%) of the participants were found to have comorbid states, hypertension (89%) was found to be prominent, increasing the occurrence of poor HRQoL (100%). Other studies have shown that multiple comorbidities produce a tenfold outcome to already existing problems. Comorbidities have been associated with higher degrees of poorer HRQoL such as all-cause mortality, hospitalization, and increased length of hospital admissions [16] [27]. The occurrence of comorbidities in the majority of the patients was found to be present pre-dialysis, which most likely lead to CKD as a complication. However, they may also result from complications related to CKD and dialysis.

In binary logistic regression analysis of independent variables (adequacy of dialysis and HB levels) and the dependent (HRQoL), the results obtained were not statistically significant with p-values ranging from 0.140 to 1.000. However, clinical significance was noted in that the study highlighted that low HB levels increased the odds of having poor HRQoL by 31%. Age was found to influence the occurrence of poor HRQoL as older patients were 1.03 times more likely to have poor HRQoL than younger patients on dialysis.

Further the study highlighted that unemployment increased the odds of poor HRQoL by 9% than in employed patients or those who were engaged in any occupation [95% Cl (0.81 - 4.48) p-value 0.140]. An increase in the duration of dialysis was 1.04 times more likely to cause poor HRQoL in patients, therefore newly initiated patients on dialysis may have a relatively good HRQoL however it has been seen to gradually diminishes over time [35].