The present study demonstrated that an increase in hydration and fat tissue indices was negatively related to HRQOL scores in PD patients. These associations were significant after multivariable adjustment and were consistent throughout subgroup analysis stratified by sex, age, and daily urine. These findings indicate that interventions to improve hydration and fat tissue may potentially improve HRQOL in PD patients.
HRQOL is an important aspect of patient health status and should be considered when monitoring patients with chronic illness 16. In particular, kidney diseases have negatively impacted the HRQOL of ESKD patients mainly due to the accompanying impairment or the imposed limitations in almost all aspects of their lives. Poor HRQOL is associated with increased morbidity and mortality 6; thus, enhancing HRQOL is a priority in the area of kidney disease research 17,18. There have been several studies on HRQOL and its implications among chronic kidney disease 19, hemodialysis 6, and transplanted patients 20–22, but fewer studies have focused on PD patients 23. In particular, to date, no study has reported the association of body composition and HRQOL in PD patients.
The body composition of PD patients differs from that of the general population 24. Protein energy wasting and overhydration, which are common in PD patients, may affect changes in body composition. High glucose in dialysis fluid and a loss of proteins into the dialysate may contribute to a progressive decrease in skeletal muscle mass and increase in adipose tissue 25,26. Although adverse changes in body composition are associated with morbidity and mortality in PD patients, there is no consensus on the relationship between body composition and HRQOL in PD patients. With an easy and noninvasive device to measure body composition, we tried to assess the association between body composition and HRQOL in PD patients.
In this study, we showed that R△TH and ECW/ICW had significant negative associations with PCS after adjustments for multiple variables. The negative association between fluid overload and PCS showed robust relationships in multiple subgroup analyses stratified by sex, age, and dialysis urine. This result was consistent with a previous report 23. As PCS is closely related with physical function, several reasons can be postulated. First, fluid overload in PD is not only related with cardiovascular burden but also non-cardiovascular risk factors such as malnutrition and inflammation 27,28. Second, target weight may not always be reached due to an increase in intradialytic symptoms in fluid overload status, and fluid overloaded patients require more effort to adjust to their target weight 29.
We also showed that FTI had a negative association with PCS after adjustments for multiple variables. PD patients are more susceptible to central obesity due to exposure to glucose-containing dialysate fluid 30. However, in this analysis, when comparing subjects with Z-FTI <0 and those with Z-FTI ≥0, the glucose exposure load was not significantly different between both groups (Supplement Table S2). The mechanism of negative association between PCS and Z-FTI has not been completely clarified, although several hypotheses could be inferred by considering the characteristics of the two groups classified as FTI (Supplement Table S2). First, patients with obese or high fat tissue secrete numerous proinflammatory cytokines, including C-reactive protein (CRP), tumor necrosis factor-α, and interleukin (IL)-6. Our study also showed that the lower Z-FTI group showed statistically significantly higher CRP than the higher Z-FTI group. These cytokines modulate lipid and carbohydrate metabolism and orchestrate the inflammatory pathway 31. With this mechanism, a previous study showed that elevated CRP and IL-6 levels predict 2-year mortality, cardiovascular events, and technique survival in PD patients 26,32. Second, a decline in nutritional status appears to have an impact on the physical domain of HRQOL in higher FTI groups. In our study, groups with Z-FTI ≥ 0 showed statistically significantly lower scores in SGA. Lower SGA has a vulnerability that is characterized by reduced functional reserve and a higher susceptibility to adverse health outcomes 33. On the other hand, sarcopenic obesity may develop, where muscles decrease and fat increases in PD patients. In our subgroup analysis, it was confirmed that FTI and PCS had a significant negative association in subjects with higher Z-LTI, but not in those with lower Z-LTI. This association shows that the increased fat tissue itself, independent from the decrease in lean tissue mass, had a negative effect on PCS.
In contrast to the relationship between FTI and PCS, LTI did not show any relationship with HRQOL. This finding was different from a previous study reporting that a reduction of lean body mass was associated with an increased mortality 34. Even though LTI did not show a significant association with HRQOL in our study, it should be interpreted with caution. Progressive loss of muscle mass and strength has frequently been observed in ESKD patients. Although this study did not prove any relationship between LTI and HRQOL, it is well known that LTI is an independent predictor of survival in PD 35. From a long-term perspective, it is warranted to monitor the overall body composition of PD patients.
There was no association between KDCS and any of the body composition parameters in our study. Because the KDCS combines information from a heterogeneous set of scales 36, each component has a different meaning to each of the body components. Even though MCS was weakly related with ECW/ICW and FTI, there was no linear trend between any of the body composition parameters and MCS. This finding was different from a previous study that found that severity of nutritional markers was related not only with PCS, but also with KDCS and MCS 37. However, the nutritional status in the above study was evaluated based on a quantitative version of 24-hour dietary recall and BMI, which have limitations in the accurate assessment of the body composition.
Our study had several limitations. First, this study was an observational study, and there were inherent limitations such as hidden confounding factors. Second, a causal relationship could not be ascertained due to the cross-sectional nature of the study. Further longitudinal or interventional studies are needed to better understand and determine the existence of a causal relationship. Third, the sample size of about 200 subjects may be insufficient to verify robust statistical significance. Nevertheless, this is the first study from PD patients evaluating the association between body composition and HRQOL. Moreover, we analyzed the body composition with Z-FTI and Z-LTI from Korean PD patients, using reference values from the Asian general population rather than the absolute values of FTI or LTI itself. This allowed us to investigate more accurately the association between body composition and HRQOL.
Based on the results of this study, it could be suggested that the implementation of strategies for the prevention and management of overhydration and obesity in PD patients could improve quality of life. Multidisciplinary strategies such as nutritional intervention, physical training, and psychological support for the HRQOL would be needed. Lifestyle and therapeutic adherence of PD patients who are overhydrated or obese could be considered in further investigations.