Impact of Work Status on Quality of Life in Patients with End-stage Renal Disease During the First Year of Hemodialysis

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Bodessova, N. Sagandykova, K. Danebek, B. Sultanova, M. Baurzhan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4574063/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction. Compared with the general population, end-stage renal disease (ESRD) patients have impaired health-related quality of life due to the combined effects of disease and hemodialysis therapy. As a result, poor quality of life increases the risk of mortality and hospitalization and affects general well-being. Although existing rehabilitation programs aim to improve physical activity in hemodialysis patients, the impact of work status, particularly within the first year of treatment, on quality of life (QoL) remains unclear. This study investigated and compared the QoL of working and nonworking patients with end-stage renal disease (ESRD) during their first year on hemodialysis, focusing on two subscales of the SF-36. Materials and methods. The study involved 120 patients with ESRD at the hemodialysis center during their first year of hemodialysis. There were two groups: sixty working patients and sixty nonworking patients. Patients were administered the SF-36 survey to determine their physical and mental health status. Results. It was found that working status was significantly associated with improved quality of life for working patients who reported lower physical function but significantly greater mental health scores (p = 0.009) than for nonworking participants. Conclusion. This study revealed that working ESRD patients who were undergoing hemodialysis during their first year reported better physical and mental health than nonworking patients. These findings suggest that light work during hemodialysis may have a positive impact on patients' quality of life. Further research is warranted to explore the optimal work modalities and their integration into comprehensive rehabilitation programs for ESRD patients. End-stage renal disease Quality of life Haemodialysis therapy Rehabilitation programmes Working patients Figures Figure 1 Introduction As one of the forms of psychosocial interaction and physical activity in society, work can be used as a tool for rehabilitating and improving the quality of life of patients with chronic pathologies, including end-stage renal disease (ESRD). ESRD often leads to a significant decrease in the workability and quality of life of patients during hemodialysis (HD) [1]. Rehabilitation measures include both medical and psychosocial actions. The patients’ lifestyle directly depends on the disease severity, its morphofunctional specialties, the treatment program, and particularly on their social activity. It is hard to say what comes first: the patient’s physical condition or his mental status. However, his mental foundation, preparedness, and involvement in public life have no small importance for well-being or physical health. In our study, we compared the quality of life of working and nonworking patients with ERSD in the first year of HD. Since these patients belong to a vulnerable category, the applicability of different types of rehabilitation is relevant during hemodialysis treatment. Background Chronic kidney disease (CKD) permanently impairs kidney function, leading to a significant decline in health. Notably, two percent of CKD patients progress to terminal kidney failure [ 2 ]. The essential treatment for end-stage chronic renal disease (ESRD) is replacement therapy, which includes hemodialysis, peritoneal dialysis, and kidney transplantation [ 3 , 4 ]. Kidney transplantation provides better quality of life than other treatment methods [ 5 ]. Factors such as financial costs [ 6 ], organizational barriers [ 7 ], surgical risks [ 8 ], and other reasons [ 9 , 10 ] limit patient access to donor kidneys, therefore limiting this treatment modality to many patients. Continuous renal replacement therapy is the most common treatment available for chronic renal failure [ 11 ]. It is primarily a blood purification procedure and can replace the main renal functions, but it has some side effects, especially hemodialysis (HM) versus peritoneal dialysis (PD) [ 12 ], which may considerably worsen the patient’s quality of life. It can have psychological impacts on patients; frequent dialysis center visits, the procedure itself, treatment dependence, and interactions with other patients contribute to increased anxiety, fear of life, and potential mental health disorders [ 13 , 14 ]. Other symptoms after HM may affect patients (hypertension, pain, nausea, anorexia, shortness of breath, insomnia) [ 15 , 16 ]. A key goal of renal replacement therapy is to restore and enhance physical well-being and psychological balance in ESRD patients. To prevent complications during dialysis, various guidelines offer a range of options, including pain management [ 17 , 18 ], cardiovascular complication prophylaxis [ 19 ], and other pathologies linked with HM [ 20 ]. The psychosocial impacts of HM [ 21 ] must also be addressed as a significant factor in rehabilitation. Improving physical activity is an efficacious way to improve mental health in patients with ESRD. An interview study of patients with ESRD during COVID-19 quarantine in the UK revealed the impact of prescribing home exercise on quality of life. This analysis showed that daily exercise during dialysis significantly improved the patient’s mood and mental state [ 22 ]. In addition, some authors [ 23 , 24 ] have indicated the effectiveness of sports exercises in improving daily physical health in patients with ESRD. However, exercise between dialysis periods does not improve patient well-being, as summarized by a randomized clinical trial involving five hemodialysis centers [ 25 ]. Psychosocial support also helps to understand the possible posthaemodialysis outcomes for patients, leading to a decrease in anxiety and depression levels [ 26 , 27 ]. One study revealed that [ 28 ] resistance training significantly improved the mood of patients with ESRD, and these patients became motivated to find work and improve their personal lives. Some hemodialysis centers have introduced psychosocial care rooms and psychologists’ navigation during treatment [ 29 ]. Despite all the proposed methods of patient rehabilitation for patients with ESRD, quality of life after dialysis remains one of the lowest among other nosology. End-stage renal disease (ESRD) can significantly decrease the workability and quality of life of patients undergoing hemodialysis (HD), and a decrease in daily physical activity, which is typical for patients on hemodialysis, reduces their performance and endurance [ 30 ]. Existing efforts to improve the quality of life of hemodialysis patients have focused on specialized rehabilitation programs, counselling, staff training, and optimization. However, the impact of work status during dialysis remains unexplored, particularly given the high prevalence of disabled people receiving hemodialysis in Kazakhstan. Light physical or mental work at a partial load may be feasible for some ESRD patients in their first year of hemodialysis. Work, a source of social interaction and physical activity, can be a rehabilitation tool for chronic illness patients, such as those with end-stage renal disease (ESRD), potentially improving their quality of life [ 31 ]. Therefore, this study compared the quality of life between working and nonworking ESRD patients in their first year of hemodialysis. Given their vulnerability, exploring the applicability of different rehabilitation approaches during treatment is crucial. Objective The purpose of this study was to compare the quality of life of working and nonworking patients with ESRD in the first year of hemodialysis. Hypotheses Working patients with end-stage renal disease in the first year of HD have better physical and mental health than nonworking patients with ESRD. Methods Study design A comparative cross-sectional study was used to compare health-related quality of life among working and nonworking patients with ESRD undergoing haemodialysis during their first year of treatment. Study setting The study was conducted in two clinics of a large renal haemodialysis centre, DIAVERUM KAZAKHSTAN DISTRIBUTION, in Kazakhstan from January to February 2024. Participants The study included 120 patients with ESRD who were undergoing haemodialysis treatment in their first year at two clinics of a large renal haemodialysis centre in Kazakhstan. The inclusion criteria were patients with confirmed ESRD, who were receiving first-year haemodialysis therapy, who were older than 18 years, who were receiving internet access, and who provided written informed consent. We excluded patients currently enrolled in other rehabilitation programs, such as psychotherapy. Since peritoneal dialysis has not yet been widely introduced into treatment programs for patients with ESRD in Kazakhstan, our study included only hemodialysis patients. Study tool We used the SF-36 questionnaire to determine the quality of life of the participants with ESRD [ 32 ]. This questionnaire consists of physical (physical functioning, role physical functioning, and body pain) and mental health (common health, vitality, social functioning, and role emotional, mental health) scales. The answers given in the sections are summarized as points (0-100); the higher the scores are, the better the quality of life. The result is points for the physical component of health (physical health – PH) and the psychological component of health (mental health – MH). Sample size A total of 330 patients visited the hemodialysis centres between January and February 2024. Of these, 120 patients met the inclusion criterion of being in their first year of hemodialysis treatment. We recruited 120 patients who were undergoing first-year haemodialysis at clinics during the study period. Variables The study collected data on participants' age, sex, physical and mental health indicators from the SF-36 questionnaire, and employment status. One hundred twenty patients were divided into two groups based on their work status. Statistical analysis The data were analysed using the Statistical Package for the Social Sciences (SPSS) version 22 (IBM Corp., Armonk, NY). Information regarding gender, age, and questionnaire scores was treated as descriptive statistics (means, standard deviations). The PF, MH, and age variables were treated via Spearman correlation analysis due to the nonparametric origin of the data. The Mann‒Whitney test was applied to determine the significant differences between the working and nonworking groups regarding PF and MH values due to the nonparametric origin of the data. Several potential confounders must not be considered in the context of this study examining the impact of work status on the quality of life of ESRD patients during their first year of hemodialysis. Further research is recommended to control for additional potential confounders, such as socioeconomic status, comorbidities, and baseline quality of life, to ensure the generalizability of the findings. We suggest stratifying the analysis by age, sex, and other significant variables to isolate the effects of these factors. Additionally, potential confounders need to be considered as covariates in a regression model for adjustment of their effects. Notably, matching working and nonworking patients based on similar subscale scores for the likelihood of being employed can reduce confounding factors. Results Overview of the distribution of the variables PF, MH, and age Out of 120 recruited patients, there were 62 males and 58 females. Age within the sample varied from 21 years to 84 years, while the mean age of the sample was 54.3 years, as shown in Table 2 . Regarding employment status, we had an equal number of working and nonworking individuals. Finally, in terms of the subscales from the SF-36, the mean physical functioning (PF) score across the sample was 36.3, which is less than the mean mental health (MH) score of 43.3. Table 1 Demographic characteristics of the participants N Minimum Maximum Mean Std. Deviation PF 120 14.27 63.53 36.2825 9.37974 MH 120 23.8 62.74 43.3367 8.22876 Age 120 21 84 54.2917 14.02483 Valid N (listwise) 120 Table 2 Working status and age distributions by subgroup Working status Total (N) Variable Working (n) Nonworking (n) Gender Male 28 34 62 Female 32 26 58 Age 18–30 0 4 4 31–40 9 11 20 > 40 51 45 96 Distribution of PF and MH subscales across working status and gender The dataset describes variables from the SF-36 survey, categorized by employment status and gender for two specific subscales, i.e., PF and MH. The following statistical results revealed that working individuals reported higher mean PF (M = 42.0) and MH (M = 46.6) scores than did nonworking individuals (M = 30.6; M = 40.1), indicating potentially better health status. The sex differences in the PF and MH scores were minimal, suggesting similar health outcomes between males and females (Table 3 ). Table 3 PH and MH scores among the participants by working status and gender Working Status N Mean Std. Deviation Std. Error Mean PF Non-Working 60 30.6148 5.94766 0.76784 Working 60 41.9502 8.76024 1.13094 MH Non-Working 60 40.0945 5.93851 0.76666 Working 60 46.5788 8.94019 1.15417 PF Male 62 35.8458 9.27013 1.17731 Female 58 36.7493 9.55414 1.25452 MH Male 62 43.4668 8.38319 1.06467 Female 58 43.1976 8.13123 1.06768 Correlation analysis The correlation analysis between work status and various SF-36 subscales and age are detailed below, using Spearman's rho correlation coefficients. Overall, the only significant correlation found in this analysis was between PF and MH (rho = 0.286, p = 0.002), suggesting that these two aspects of health are positively related. Age did not show a significant correlation with either PF or MH in this dataset. Table 4 Correlation Analysis between Work Status and SF-36 Subscales Correlations SF-36 Subscale PF MH Age Spearman's rho PF Correlation Coefficient 1 0.286** 0.119 Sig. (2-tailed) . 0.002 0.196 N 120 120 120 MH Correlation Coefficient 0.286** 1 0.052 Sig. (2-tailed) 0.002 . 0.571 N 120 120 120 Age Correlation Coefficient 0.119 0.052 1 Sig. (2-tailed) 0.196 0.571 . N 120 120 120 ** Correlation is significant at the 0.01 level (2-tailed). Statistical Differences in the Mean Scores of Working and Nonworking Individuals The results from the Mann‒Whitney U test, presented in Table 5 , were used to assess the differences in the mean ranks of PF and MH between two groups: working and nonworking. In terms of the PF subscale, the working group had a significantly greater mean rank (M = 82.4) than did the nonworking group (M = 38.6). This indicates that individuals in the working group reported better physical functioning than did those in the nonworking group. Similarly, for the MH subscale, the working group had a greater mean rank (M = 74.3) than did the nonworking group (M = 46.7), suggesting that working individuals tend to report better mental health than nonworking individuals. The disparity in mean ranks was further supported by the presence of a statistically significant difference. The data from Table 6 provide the statistical test results from the Mann‒Whitney U test evaluating differences in PF and MH between the working and nonworking groups. There was a significant difference in the average PF and MH scores between the groups: PF of -6.888 (p = 0.000) and MH of -4.358 (p = 0.000). This confirms that the working group has significantly greater physical functioning scores than the nonworking group. The p value in MH is again near zero, strongly indicating that these results are statistically significant and not due to random chance. Thus, the results of the Mann‒Whitney U test support the proposition that workers and nonworkers have significantly different PF and MH results. Table 5 Mann‒Whitney test for differences in the mean scores Ranks WorkStatus N Mean Rank Sum of Ranks PF Nonworking 60 38.63 2318 Working 60 82.37 4942 Total 120 MH Nonworking 60 46.67 2800 Working 60 74.33 4460 Total 120 Table 6 Mann‒Whitney test for statistically significant differences Test Statistics a PF MH Mann‒Whitney U 488 970 Wilcoxon W 2318 2800 Z -6.888 -4.358 Asymp. Sig. (2-tailed) 0 0 a Grouping Variable: WorkStatus Discussion ESRD is the terminal stage of chronic renal pathology and is accompanied by a significant decrease in quality of life [ 33 ]. This factor is an important predictor of mortality during hemodialysis [ 34 ] and even during the interdialytic period [ 35 ]. This study aimed to assess the quality of life of working and nonworking patients with ESRD using the SF-36 questionnaire. The results from this study showed that working patients with ESRD in the first year of hemodialysis had a better quality of life than nonworking patients, with the mean PH (36.28) being slightly lower than the mean MH (43.33) for all studied patients. These findings align with those reported by Kraus et al. [ 36 ], who also employed the SF-36 questionnaire. They reported average physical and mental health scores of 32.7 and 42.1, respectively, for ESRD patients. Our findings revealed no statistically significant differences in SF-36 scores between genders. While females had slightly higher PF scores, males had better MH scores, although the difference was not statistically significant. The most striking result was that the physical and mental health scores of the working group were much greater than those of nonworking patients. Before this study, the variability in quality-of-life indicators for ESRD patients across studies could be attributed to the lack of comparisons between working and nonworking groups. However, existing research consistently highlights the positive impact of physical activity on both physical and mental health in ESRD patients [ 37 , 38 ]. Our working ESRD patients' mental health scores approached preexercise levels reported in another SF-36 study [ 39 ]. Pérez-Domínguez et al. noted that the mean preexercise level of individuals with MH was greater than that of individuals without MH in terms of mental health and quality of life. The study also revealed significant improvements in both physical and mental health after exercise rehabilitation. A possible explanation for this phenomenon could be the positive effect of both physical exercise and employment on the physical well-being of patients with ERSD. The importance of integrating employment-based social rehabilitation was also suggested to improve self-rated physical and mental health among people living with mental disorders [ 40 ]. Unemployed respondents noted the same positive attitude toward health after finding a job [ 41 ]. Patients with ESRD, in addition to physical problems, often experience mental disorders such as depression [ 42 ] and cognitive function impairment [ 43 ]. Thus, the psychological rehabilitation of patients receiving long-term replacement therapy is also important because social support plays a crucial role [ 44 ]. Employment goes beyond physical activity; it involves social interaction, requiring contact with others and fostering responsibility. The good quality of life observed in working ESRD patients might be explained by this multifaceted impact—physical and psychosocial—of employment during dialysis. Since the role of work in ESRD management remains unexplored, a shift in rehabilitation protocols for ESRD patients is warranted. A key strength of this research is the consideration of ESRD patients' work status as a factor in hemodialysis rehabilitation, which has not been well explored in other studies. Limitations A potential limitation of cross-sectional studies is the possibility of incomplete data due to participant responses. Another bias is the respondents’ size, with a reported low Cronbach’s alpha, which was less than 0.7, indicating that further research with a larger sample size is needed. This study included a limited number of confounders for further analysis. In addition, the enrolment of patients with ESRD in the 60 + group is a potential bias indicator for the key question of employability. There is a potential limitation in the findings because of the presence of other chronic illnesses affecting both quality of life and the ability to work. The researchers acknowledge the nature of confirmation bias to the data interpretation influenced by preexisting beliefs, leading to partial outcomes. Patients may overreport positive experiences or feelings towards their treatment, which would not demonstrate an accurate representation of their actual quality of life. Conclusion Our study revealed that working patients with ESRD in the first year of hemodialysis were more satisfied with their physical and mental quality of life than nonworking patients were. Given the prevalence of disability and unemployment among ESRD patients, exploring social rehabilitation strategies to enhance replacement therapy outcomes is important. Overall, our findings suggest that employment status is significantly associated with both physical and mental health, with working individuals reporting better health outcomes on both SF-36 subscales. We encourage the consideration of employment during hemodialysis as a method to improve quality of life. Further research with a larger sample size and utilization of entire SF-36 subscales is recommended. Declarations Acknowledgements The work was carried out in collaboration with the .*, “University Medical Center” Corporate Fund, the Kazakh National Medical University after S. D. Asfendyarov, and the “DIAVERUM KAZAKHSTAN DISTRIBUTION” hemodialysis clinic. The results presented in this paper have not been published previously in whole or in part, except in abstract format. Funding The authors declare that no funds, grants, or other support was received during the preparation of this manuscript. Disclosures The authors declare no conflicts of interest. Ethical approval This study was conducted in accordance with the Helsinki Declaration principles. The study was approved by the ethics committee of Kazakh National University after S.D. Asfendiyarov on January 15, 2024 (approval no. 1). Informed consent Verbal informed consent was obtained prior to the interview. 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Nefrologia. 2020;40(3):237–52. https://doi.org/10.1016/j.nefro.2020.01.002 . Pei G, Tang Y, Tan L, Tan J, Ge L, Qin W. Aerobic exercise in adults with chronic kidney disease (CKD): a meta-analysis. Int Urol Nephrol. 2019;51(10):1787–95. https://doi.org/10.1007/s11255-019-02234-x . Perez-Dominguez B, Casaña-Granell J, Garcia-Maset R, Garcia-Testal A, Melendez-Oliva E, Segura-Orti E. Effects of exercise programs on physical function and activity levels in patients undergoing hemodialysis: a randomized controlled trial. Eur J Phys Rehabil Med. 2021;57(6):994–1001. https://doi.org/10.23736/S1973-9087.21.06694-6 . Schuring M, Robroek SJ, Burdorf A. The benefits of paid employment among persons with common mental health problems: evidence for the selection and causation mechanism. Scand J Work Environ Health. 2017;43(6):540–9. https://doi.org/10.5271/sjweh.3675 . Carlier BE, Schuring M, Lötters FJ, Bakker B, Borgers N, Burdorf A. The influence of re-employment on quality of life and self-rated health, a longitudinal study among unemployed persons in the Netherlands. BMC Public Health. 2013;13:503. https://doi.org/10.1186/1471-2458-13-503 . Kondo K, Ayers C, Chopra P, Antick J, Kansagara D. End-stage Renal Disease and Depression: A Systematic Review.. Department of Veterans Affairs (US); 2020. Drew DA, Weiner DE, Sarnak MJ. Cognitive Impairment in CKD: Pathophysiology, Management, and Prevention. Am J Kidney Dis. 2019;74(6):782–90. https://doi.org/10.1053/j.ajkd.2019.05.017 . Fuertes J, Rubinstein S, Yarandi N, Cohen SD. Social Support, Caregivers, and Chronic Kidney Disease. Semin Nephrol. 2021;41(6):574–9. https://doi.org/10.1016/j.semnephrol.2021.10.009 . Additional Declarations No competing interests reported. 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Sagandykova","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDCCA8icBww2QJKx8QBWpQgtjA1gBhsQJzCkgbQ0kKTlMKbV6IDvePPzBx/3MMiZyzcwfkjMOW+3tv0w0JYam2hcWiTPHDNsnPGMwdiyjYFZInHb7eRtZxKBWo6l5Tbg0GJwI4exmecAQ+KGYwwMYC1mB4BaGBsOE9RSD9TC/CNx27lks/MPidOSYHCMgQ1oywE7sxsEbAH5ZeaMAxKGG44ltlkkbktOMLsBtCUBj1+AIfbgw4cDNvIGhw8fvvFxm5292fn0hw8+1Njg1AIFEgwM0PhJBJMJ+JWjAntSFI+CUTAKRsHIAAB+nmflERbEJAAAAABJRU5ErkJggg==","orcid":"","institution":"“University Medical Center” Corporate Fund","correspondingAuthor":true,"prefix":"","firstName":"N.","middleName":"","lastName":"Sagandykova","suffix":""},{"id":321217519,"identity":"96bd5592-b08e-40cd-9b30-9a388c58016e","order_by":2,"name":"K. Danebek","email":"","orcid":"","institution":"Nazarbayev University","correspondingAuthor":false,"prefix":"","firstName":"K.","middleName":"","lastName":"Danebek","suffix":""},{"id":321217520,"identity":"83f7fae8-d010-4505-817c-2e540df69ca8","order_by":3,"name":"B. Sultanova","email":"","orcid":"","institution":"PF \"National Kidney Fund of the Republic of Kazakhstan","correspondingAuthor":false,"prefix":"","firstName":"B.","middleName":"","lastName":"Sultanova","suffix":""},{"id":321217521,"identity":"aabab116-9b33-4074-8a74-c905de2a9271","order_by":4,"name":"M. Baurzhan","email":"","orcid":"","institution":"Academy of Physical Education and Mass Sports","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"","lastName":"Baurzhan","suffix":""}],"badges":[],"createdAt":"2024-06-13 06:47:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4574063/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4574063/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61181059,"identity":"2bfcdb01-49ae-4c6d-b49f-4050c2285cff","added_by":"auto","created_at":"2024-07-26 16:45:27","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":323909,"visible":true,"origin":"","legend":"\u003cp\u003eBarchart showing the difference in the mean SF-36 score between working and nonworkingpatients\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4574063/v1/2a9c15c49f17289f1adc837a.jpg"},{"id":61306472,"identity":"de140118-e663-439c-8491-88b235fc73cb","added_by":"auto","created_at":"2024-07-29 10:10:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":894472,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4574063/v1/2bdf322c-71f6-4455-9f27-25b68f5798ac.pdf"},{"id":61182001,"identity":"f0b2387e-5b06-45be-83aa-50e09502fc00","added_by":"auto","created_at":"2024-07-26 16:53:27","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":13844,"visible":true,"origin":"","legend":"","description":"","filename":"agegendis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4574063/v1/1046b5cdeea381996981ec2a.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Work Status on Quality of Life in Patients with End-stage Renal Disease During the First Year of Hemodialysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs one of the forms of psychosocial interaction and physical activity in society, work can be used as a tool for rehabilitating and improving the quality of life of patients with chronic pathologies, including end-stage renal disease (ESRD). ESRD often leads to a significant decrease in the workability and quality of life of patients during hemodialysis (HD) [1]. Rehabilitation measures include both medical and psychosocial actions. The patients\u0026rsquo; lifestyle directly depends on the disease severity, its morphofunctional specialties, the treatment program, and particularly on their social activity. It is hard to say what comes first: the patient\u0026rsquo;s physical condition or his mental status. However, his mental foundation, preparedness, and involvement in public life have no small importance for well-being or physical health. In our study, we compared the quality of life of working and nonworking patients with ERSD in the first year of HD. Since these patients belong to a vulnerable category, the applicability of different types of rehabilitation is relevant during hemodialysis treatment.\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eChronic kidney disease (CKD) permanently impairs kidney function, leading to a significant decline in health. Notably, two percent of CKD patients progress to terminal kidney failure [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The essential treatment for end-stage chronic renal disease (ESRD) is replacement therapy, which includes hemodialysis, peritoneal dialysis, and kidney transplantation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Kidney transplantation provides better quality of life than other treatment methods [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Factors such as financial costs [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], organizational barriers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], surgical risks [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and other reasons [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] limit patient access to donor kidneys, therefore limiting this treatment modality to many patients. Continuous renal replacement therapy is the most common treatment available for chronic renal failure [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It is primarily a blood purification procedure and can replace the main renal functions, but it has some side effects, especially hemodialysis (HM) versus peritoneal dialysis (PD) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which may considerably worsen the patient\u0026rsquo;s quality of life. It can have psychological impacts on patients; frequent dialysis center visits, the procedure itself, treatment dependence, and interactions with other patients contribute to increased anxiety, fear of life, and potential mental health disorders [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Other symptoms after HM may affect patients (hypertension, pain, nausea, anorexia, shortness of breath, insomnia) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA key goal of renal replacement therapy is to restore and enhance physical well-being and psychological balance in ESRD patients. To prevent complications during dialysis, various guidelines offer a range of options, including pain management [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], cardiovascular complication prophylaxis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and other pathologies linked with HM [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe psychosocial impacts of HM [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] must also be addressed as a significant factor in rehabilitation. Improving physical activity is an efficacious way to improve mental health in patients with ESRD. An interview study of patients with ESRD during COVID-19 quarantine in the UK revealed the impact of prescribing home exercise on quality of life. This analysis showed that daily exercise during dialysis significantly improved the patient\u0026rsquo;s mood and mental state [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In addition, some authors [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] have indicated the effectiveness of sports exercises in improving daily physical health in patients with ESRD. However, exercise between dialysis periods does not improve patient well-being, as summarized by a randomized clinical trial involving five hemodialysis centers [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Psychosocial support also helps to understand the possible posthaemodialysis outcomes for patients, leading to a decrease in anxiety and depression levels [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. One study revealed that [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] resistance training significantly improved the mood of patients with ESRD, and these patients became motivated to find work and improve their personal lives. Some hemodialysis centers have introduced psychosocial care rooms and psychologists\u0026rsquo; navigation during treatment [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite all the proposed methods of patient rehabilitation for patients with ESRD, quality of life after dialysis remains one of the lowest among other nosology. End-stage renal disease (ESRD) can significantly decrease the workability and quality of life of patients undergoing hemodialysis (HD), and a decrease in daily physical activity, which is typical for patients on hemodialysis, reduces their performance and endurance [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Existing efforts to improve the quality of life of hemodialysis patients have focused on specialized rehabilitation programs, counselling, staff training, and optimization. However, the impact of work status during dialysis remains unexplored, particularly given the high prevalence of disabled people receiving hemodialysis in Kazakhstan. Light physical or mental work at a partial load may be feasible for some ESRD patients in their first year of hemodialysis. Work, a source of social interaction and physical activity, can be a rehabilitation tool for chronic illness patients, such as those with end-stage renal disease (ESRD), potentially improving their quality of life [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, this study compared the quality of life between working and nonworking ESRD patients in their first year of hemodialysis. Given their vulnerability, exploring the applicability of different rehabilitation approaches during treatment is crucial.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThe purpose of this study was to compare the quality of life of working and nonworking patients with ESRD in the first year of hemodialysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHypotheses\u003c/h2\u003e \u003cp\u003eWorking patients with end-stage renal disease in the first year of HD have better physical and mental health than nonworking patients with ESRD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA comparative cross-sectional study was used to compare health-related quality of life among working and nonworking patients with ESRD undergoing haemodialysis during their first year of treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting\u003c/h2\u003e \u003cp\u003eThe study was conducted in two clinics of a large renal haemodialysis centre, DIAVERUM KAZAKHSTAN DISTRIBUTION, in Kazakhstan from January to February 2024.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe study included 120 patients with ESRD who were undergoing haemodialysis treatment in their first year at two clinics of a large renal haemodialysis centre in Kazakhstan. The inclusion criteria were patients with confirmed ESRD, who were receiving first-year haemodialysis therapy, who were older than 18 years, who were receiving internet access, and who provided written informed consent. We excluded patients currently enrolled in other rehabilitation programs, such as psychotherapy.\u003c/p\u003e \u003cp\u003eSince peritoneal dialysis has not yet been widely introduced into treatment programs for patients with ESRD in Kazakhstan, our study included only hemodialysis patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStudy tool\u003c/h2\u003e \u003cp\u003eWe used the SF-36 questionnaire to determine the quality of life of the participants with ESRD [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This questionnaire consists of physical (physical functioning, role physical functioning, and body pain) and mental health (common health, vitality, social functioning, and role emotional, mental health) scales. The answers given in the sections are summarized as points (0-100); the higher the scores are, the better the quality of life. The result is points for the physical component of health (physical health \u0026ndash; PH) and the psychological component of health (mental health \u0026ndash; MH).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample size\u003c/h2\u003e \u003cp\u003eA total of 330 patients visited the hemodialysis centres between January and February 2024. Of these, 120 patients met the inclusion criterion of being in their first year of hemodialysis treatment. We recruited 120 patients who were undergoing first-year haemodialysis at clinics during the study period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eVariables\u003c/h2\u003e \u003cp\u003eThe study collected data on participants' age, sex, physical and mental health indicators from the SF-36 questionnaire, and employment status. One hundred twenty patients were divided into two groups based on their work status.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data were analysed using the Statistical Package for the Social Sciences (SPSS) version 22 (IBM Corp., Armonk, NY). Information regarding gender, age, and questionnaire scores was treated as descriptive statistics (means, standard deviations). The PF, MH, and age variables were treated via Spearman correlation analysis due to the nonparametric origin of the data. The Mann‒Whitney test was applied to determine the significant differences between the working and nonworking groups regarding PF and MH values due to the nonparametric origin of the data.\u003c/p\u003e \u003cp\u003eSeveral potential confounders must not be considered in the context of this study examining the impact of work status on the quality of life of ESRD patients during their first year of hemodialysis. Further research is recommended to control for additional potential confounders, such as socioeconomic status, comorbidities, and baseline quality of life, to ensure the generalizability of the findings. We suggest stratifying the analysis by age, sex, and other significant variables to isolate the effects of these factors. Additionally, potential confounders need to be considered as covariates in a regression model for adjustment of their effects. Notably, matching working and nonworking patients based on similar subscale scores for the likelihood of being employed can reduce confounding factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOverview of the distribution of the variables PF, MH, and age\u003c/h2\u003e \u003cp\u003eOut of 120 recruited patients, there were 62 males and 58 females. Age within the sample varied from 21 years to 84 years, while the mean age of the sample was 54.3 years, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Regarding employment status, we had an equal number of working and nonworking individuals. Finally, in terms of the subscales from the SF-36, the mean physical functioning (PF) score across the sample was 36.3, which is less than the mean mental health (MH) score of 43.3.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.2825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.37974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.3367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.22876\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.2917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.02483\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValid N (listwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWorking status and age distributions by subgroup\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWorking status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal (N)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorking (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNonworking (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of PF and MH subscales across working status and gender\u003c/h2\u003e \u003cp\u003eThe dataset describes variables from the SF-36 survey, categorized by employment status and gender for two specific subscales, i.e., PF and MH. The following statistical results revealed that working individuals reported higher mean PF (M\u0026thinsp;=\u0026thinsp;42.0) and MH (M\u0026thinsp;=\u0026thinsp;46.6) scores than did nonworking individuals (M\u0026thinsp;=\u0026thinsp;30.6; M\u0026thinsp;=\u0026thinsp;40.1), indicating potentially better health status. The sex differences in the PF and MH scores were minimal, suggesting similar health outcomes between males and females (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePH and MH scores among the participants by working status and gender\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorking Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Error Mean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.6148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.94766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.9502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.76024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.13094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.0945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.93851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.5788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.94019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.15417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.8458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.27013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.17731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.7493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.55414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.25452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.4668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.38319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.06467\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.1976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.13123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.06768\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis\u003c/h2\u003e \u003cp\u003eThe correlation analysis between work status and various SF-36 subscales and age are detailed below, using Spearman's rho correlation coefficients. Overall, the only significant correlation found in this analysis was between PF and MH (rho\u0026thinsp;=\u0026thinsp;0.286, p\u0026thinsp;=\u0026thinsp;0.002), suggesting that these two aspects of health are positively related. Age did not show a significant correlation with either PF or MH in this dataset.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Analysis between Work Status and SF-36 Subscales\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorrelations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSF-36 Subscale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpearman's rho\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorrelation Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.286**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorrelation Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.286**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorrelation Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e** Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Differences in the Mean Scores of Working and Nonworking Individuals\u003c/h2\u003e \u003cp\u003eThe results from the Mann‒Whitney U test, presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, were used to assess the differences in the mean ranks of PF and MH between two groups: working and nonworking. In terms of the PF subscale, the working group had a significantly greater mean rank (M\u0026thinsp;=\u0026thinsp;82.4) than did the nonworking group (M\u0026thinsp;=\u0026thinsp;38.6). This indicates that individuals in the working group reported better physical functioning than did those in the nonworking group. Similarly, for the MH subscale, the working group had a greater mean rank (M\u0026thinsp;=\u0026thinsp;74.3) than did the nonworking group (M\u0026thinsp;=\u0026thinsp;46.7), suggesting that working individuals tend to report better mental health than nonworking individuals. The disparity in mean ranks was further supported by the presence of a statistically significant difference.\u003c/p\u003e \u003cp\u003eThe data from Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e provide the statistical test results from the Mann‒Whitney U test evaluating differences in PF and MH between the working and nonworking groups. There was a significant difference in the average PF and MH scores between the groups: PF of -6.888 (p\u0026thinsp;=\u0026thinsp;0.000) and MH of -4.358 (p\u0026thinsp;=\u0026thinsp;0.000). This confirms that the working group has significantly greater physical functioning scores than the nonworking group. The p value in MH is again near zero, strongly indicating that these results are statistically significant and not due to random chance. Thus, the results of the Mann‒Whitney U test support the proposition that workers and nonworkers have significantly different PF and MH results.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMann‒Whitney test for differences in the mean scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanks\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorkStatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Rank\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSum of Ranks\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonworking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonworking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMann‒Whitney test for statistically significant differences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest Statistics\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMann‒Whitney U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e970\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWilcoxon W\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsymp. Sig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ea Grouping Variable: WorkStatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eESRD is the terminal stage of chronic renal pathology and is accompanied by a significant decrease in quality of life [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This factor is an important predictor of mortality during hemodialysis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and even during the interdialytic period [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This study aimed to assess the quality of life of working and nonworking patients with ESRD using the SF-36 questionnaire.\u003c/p\u003e \u003cp\u003eThe results from this study showed that working patients with ESRD in the first year of hemodialysis had a better quality of life than nonworking patients, with the mean PH (36.28) being slightly lower than the mean MH (43.33) for all studied patients. These findings align with those reported by Kraus et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], who also employed the SF-36 questionnaire. They reported average physical and mental health scores of 32.7 and 42.1, respectively, for ESRD patients. Our findings revealed no statistically significant differences in SF-36 scores between genders. While females had slightly higher PF scores, males had better MH scores, although the difference was not statistically significant.\u003c/p\u003e \u003cp\u003eThe most striking result was that the physical and mental health scores of the working group were much greater than those of nonworking patients. Before this study, the variability in quality-of-life indicators for ESRD patients across studies could be attributed to the lack of comparisons between working and nonworking groups. However, existing research consistently highlights the positive impact of physical activity on both physical and mental health in ESRD patients [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur working ESRD patients' mental health scores approached preexercise levels reported in another SF-36 study [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. P\u0026eacute;rez-Dom\u0026iacute;nguez et al. noted that the mean preexercise level of individuals with MH was greater than that of individuals without MH in terms of mental health and quality of life. The study also revealed significant improvements in both physical and mental health after exercise rehabilitation. A possible explanation for this phenomenon could be the positive effect of both physical exercise and employment on the physical well-being of patients with ERSD. The importance of integrating employment-based social rehabilitation was also suggested to improve self-rated physical and mental health among people living with mental disorders [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Unemployed respondents noted the same positive attitude toward health after finding a job [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients with ESRD, in addition to physical problems, often experience mental disorders such as depression [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and cognitive function impairment [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Thus, the psychological rehabilitation of patients receiving long-term replacement therapy is also important because social support plays a crucial role [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Employment goes beyond physical activity; it involves social interaction, requiring contact with others and fostering responsibility.\u003c/p\u003e \u003cp\u003eThe good quality of life observed in working ESRD patients might be explained by this multifaceted impact\u0026mdash;physical and psychosocial\u0026mdash;of employment during dialysis. Since the role of work in ESRD management remains unexplored, a shift in rehabilitation protocols for ESRD patients is warranted. A key strength of this research is the consideration of ESRD patients' work status as a factor in hemodialysis rehabilitation, which has not been well explored in other studies.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eA potential limitation of cross-sectional studies is the possibility of incomplete data due to participant responses. Another bias is the respondents\u0026rsquo; size, with a reported low Cronbach\u0026rsquo;s alpha, which was less than 0.7, indicating that further research with a larger sample size is needed. This study included a limited number of confounders for further analysis. In addition, the enrolment of patients with ESRD in the 60\u0026thinsp;+\u0026thinsp;group is a potential bias indicator for the key question of employability. There is a potential limitation in the findings because of the presence of other chronic illnesses affecting both quality of life and the ability to work. The researchers acknowledge the nature of confirmation bias to the data interpretation influenced by preexisting beliefs, leading to partial outcomes. Patients may overreport positive experiences or feelings towards their treatment, which would not demonstrate an accurate representation of their actual quality of life.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study revealed that working patients with ESRD in the first year of hemodialysis were more satisfied with their physical and mental quality of life than nonworking patients were. Given the prevalence of disability and unemployment among ESRD patients, exploring social rehabilitation strategies to enhance replacement therapy outcomes is important. Overall, our findings suggest that employment status is significantly associated with both physical and mental health, with working individuals reporting better health outcomes on both SF-36 subscales. We encourage the consideration of employment during hemodialysis as a method to improve quality of life. Further research with a larger sample size and utilization of entire SF-36 subscales is recommended.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe work was carried out in collaboration with the .*, \u0026ldquo;University Medical Center\u0026rdquo; Corporate Fund, the Kazakh National Medical University after S. D. Asfendyarov, and the \u0026ldquo;DIAVERUM KAZAKHSTAN DISTRIBUTION\u0026rdquo; hemodialysis clinic. The results presented in this paper have not been published previously in whole or\u0026nbsp;in\u0026nbsp;part, except in abstract format.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support\u0026nbsp;was\u0026nbsp;received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003eDisclosures\u003c/p\u003e\n\u003cp\u003eThe authors declare no\u0026nbsp;conflicts\u0026nbsp;of interest.\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study was conducted in accordance with the Helsinki Declaration principles. The study was approved by the ethics committee of Kazakh National University after S.D. Asfendiyarov on January 15, 2024 (approval no. 1).\u003c/p\u003e\n\u003cp\u003eInformed consent\u003c/p\u003e\n\u003cp\u003eVerbal informed consent was obtained prior to the interview.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBello AK, Okpechi IG, Osman MA, Cho Y, Htay H, Jha V, Wainstein M, Johnson DW. Epidemiology of haemodialysis outcomes. Nat Rev Nephrol. 2022;18(6):378\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41581-022-00542-7\u003c/span\u003e\u003cspan address=\"10.1038/s41581-022-00542-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta R, Woo K, Yi JA. Epidemiology of end-stage kidney disease. 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Semin Nephrol. 2021;41(6):574\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.semnephrol.2021.10.009\u003c/span\u003e\u003cspan address=\"10.1016/j.semnephrol.2021.10.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"End-stage renal disease, Quality of life, Haemodialysis therapy, Rehabilitation programmes, Working patients","lastPublishedDoi":"10.21203/rs.3.rs-4574063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4574063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction. Compared with the general population, end-stage renal disease (ESRD) patients have impaired health-related quality of life due to the combined effects of disease and hemodialysis therapy. As a result, poor quality of life increases the risk of mortality and hospitalization and affects general well-being. Although existing rehabilitation programs aim to improve physical activity in hemodialysis patients, the impact of work status, particularly within the first year of treatment, on quality of life (QoL) remains unclear. This study investigated and compared the QoL of working and nonworking patients with end-stage renal disease (ESRD) during their first year on hemodialysis, focusing on two subscales of the SF-36.\u003c/p\u003e \u003cp\u003eMaterials and methods. The study involved 120 patients with ESRD at the hemodialysis center during their first year of hemodialysis. There were two groups: sixty working patients and sixty nonworking patients. Patients were administered the SF-36 survey to determine their physical and mental health status.\u003c/p\u003e \u003cp\u003eResults. It was found that working status was significantly associated with improved quality of life for working patients who reported lower physical function but significantly greater mental health scores (p\u0026thinsp;=\u0026thinsp;0.009) than for nonworking participants.\u003c/p\u003e \u003cp\u003eConclusion. This study revealed that working ESRD patients who were undergoing hemodialysis during their first year reported better physical and mental health than nonworking patients. These findings suggest that light work during hemodialysis may have a positive impact on patients' quality of life. Further research is warranted to explore the optimal work modalities and their integration into comprehensive rehabilitation programs for ESRD patients.\u003c/p\u003e","manuscriptTitle":"Impact of Work Status on Quality of Life in Patients with End-stage Renal Disease During the First Year of Hemodialysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-26 16:45:23","doi":"10.21203/rs.3.rs-4574063/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"efc1491d-c2f7-43c9-ac25-c23538117387","owner":[],"postedDate":"July 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-29T10:02:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-26 16:45:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4574063","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4574063","identity":"rs-4574063","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}