Introduction
Maintenance hemodialysis (MHD) serves as a life-sustaining treatment for individuals with end-stage renal disease (ESRD). Although the survival rate of ESRD has improved over time, patients undergoing MHD have a lower quality of life compared to the general population (1). Health-related quality of life (HRQoL) reflects the impact of disease and healthcare on patients’ functional status and their subjective perception of life (2), and it is affected by factors such as psychological health, physical state, level of independence, and social relations (3). In MHD patients, studies have shown that HRQoL is a strong and independent predictor of mortality and hospitalization (4–8). Evaluating and analyzing HRQoL in MHD patients is an important objective. Various generic and disease-specific questionnaires have been utilized to evaluate the quality of life in patients with renal disease (9). The Medical Outcomes Study Short Form 36 Health Survey (SF-36) is a widely recognized generic instrument for assessing HRQoL in ESRD patients (2, 10). There are differences in the HRQoL of hemodialysis patients across different countries and regions (11).
As renal function deteriorates, MHD patients experience physical inactivity, malnutrition and muscle wasting, which together make them more prone to sarcopenia (12). Sarcopenia, characterized by a combination of low muscle mass, strength and function, (13) is a condition related to aging with adverse clinical outcomes, including increased mortality rates, diminished mobility, and an elevated risk of falls and fractures (14, 15). Previous studies on older individuals have suggested that muscle strength, rather than muscle mass, influences factors such as quality of life, mortality risk and physical performance (16–18). While sarcopenia has been linked to reduced HRQoL in community-dwelling older adults (19, 20), the impact of sarcopenia and its components, such as muscle strength and muscle mass, on HRQoL in patients undergoing MHD remains underexplored (21–23).
The objective of this cross-sectional study was to examine the relationship between HRQoL and sarcopenic parameters, with a specific focus on muscle strength, in Chinese patients undergoing MHD.
Methods
Study design and participants
A single-center cross-sectional study was conducted. Patients were recruited from March 2021 to December 2021 in the hemodialysis center of our hospital. This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Ethics Committee of Guangzhou Red Cross Hospital, Jinan University (No.2021–066-01). The study was registered on the Chinese Clinical Trial Registry (ChiCTR2100053790).1 Informed consent was obtained from each participant before enrollment.
The inclusion criteria were as follows: (a) dialysis vintage more than 3 months, three times a week, 4 h each session, (b) age 18 years or older, (c) informed consent. The exclusion criteria were: (a) patients with pacemakers, (b) a history of severe infections, trauma or surgery within the past 3 months, (c) patients with diabetic feet, or amputations, (d) those with physical disabilities or who could not cooperate with the study for other reasons, (e) patients with malignant tumors.
Health-related quality of life
HRQoL was assessed using the 36-item Short-Form Health Survey (SF-36) (24). This tool is a patient-related questionnaire that generates scores across eight subscales: physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE), mental health (MH). Each scale is scored from 0 to 100. Two health component summary measures, the Physical Component Summary (PCS) and Mental Component Summary (MCS), were calculated from eight domain subscales for easier and simpler interpretation and analysis (25, 26). A higher score on these summaries indicates better HRQoL. The SF-36 scores use norm-based scoring in which the scale and component summary scores have a mean of 50 and standard deviation of 10 in the US general population. For better international comparability, patients in this study were allocated into two groups based on the mean of 50, which originated from the U.S. population. In each summary component, scores ≥50 were designated as the high-PCS or high-MCS (better HRQoL) group, and the scores <50 was designated as the low-PCS or low MCS (poorer HRQoL) group.
Handgrip strength
Handgrip strength (HGS) was measured using the BASELINE digital Grip Force Tester (12–0091, Fabrication Enterprises Inc., United States). Measurements were performed on the non-fistula hand before the hemodialysis session. Participants were seated in a straight-backed chair with their feet flat on the floor, their shoulders adducted, and their elbow flexed at 90°. The forearm was kept in a neutral position. The arm should not be supported by the patient, examiner, or by an armrest. The dynamometer was held vertically in line with the forearm. The hand was positioned with the thumb around one side of the handle and the four fingers around the other side. For each patient, measurements were repeated three times and the highest score was used in our analysis. The interval between the three measurements was at least 1 min. Grip strength was read in kilograms (kg) from the outside dial and recorded to the nearest 1 kg on the data entry form. According to the consensus of the Asian Working Group for Sarcopenia (AWGS) (13), low hand grip strength (low-HGS) was defined as HGS <28 kg for men and < 18 kg for women.
Demographic, clinical and laboratory parameters
Demographic (age, gender), clinical data (dialysis duration, history of diabetes, primary disease) were collected by retrieving medical records and asking the patient directly. Blood samples were collected before dialysis sessions for serum dosages of blood urea nitrogen (BUN), creatinine, phosphorus, hemoglobin, albumin, prealbumin, total cholesterol (TC), triglyceride, high-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β). The Kt/V was calculated according to Daugirda’s formula (27).
Anthropometric measurement
Dry body weight and height were measured to the nearest 0.01 kg/0.1 cm, and body mass index (BMI) was calculated as dry body weight divided by squared height (kg/m2). We also assessed triceps skinfold thick ness (TSF) and mid-upper arm circumference (MAC) after the hemodialysis sessions with the skinfold caliper (Guangdong Xiangshanweihua Corporation Ltd., EH101, China) and a flexible plastic, non-stretchable tape. Mid-arm muscle circumference (MAMC) was calculated using the following equation: (28).
MAMC
cm
=
M
A
C
cm
−
T
S
F
cm
×
π
.
Body composition measurement
Whole-body composition was measured using a body composition analyzer (Multiscan 5,000; Bodystat, Isle of Man, United Kingdom) by bioimpedance spectroscopy analysis (BIS). Body fat mass and lean body mass were measured. The equations for calculating appendicular skeletal muscle (ASM) and appendicular skeletal muscle index (ASMI) are according to Adrian’s formula (29).
Sarcopenia criteria
Sarcopenia was diagnosed as low HGS and low ASMI on the basis of the criteria proposed by AWGS (2019): (13) (1) ASMI <7.0 kg/m2 for men and < 5.7 kg/m2 for women; (2) HGS <28 kg for men and < 18 kg for women.
Statistical analysis
Statistical analyses were performed using SPSS version 22.0 statistical software (IBM Corp., Armonk, NY). All variables were tested for normality using the Shapiro–Wilk normality test. Continuous variables with a normal distribution were presented as the mean ± standard deviation, and those with non-normal distribution were described as median (25–75% interquartile range). Categorical variables were presented using percentages. Participants were divided into high-PCS/MCS and low-PCS/MCS groups. Differences between the 2 groups were assessed using a student’s t-test, Mann–Whitney U test, or chi-squared test, as appropriate. Normally distributed variables were compared using the t-test. For variables that did not exhibit a normal distribution, the Mann–Whitney U test was utilized. Associations between categorical variables were estimated using the chi-squared test. The two-tailed Fisher exact test was used for dichotomous variables. Variables with p-values <0.05 on comparison between the groups were subsequently analyzed using multivariate logistic regression to identify the independent factors of low-PCS/MCS by using a forward-stepwise method. A two-tailed p-value <0.05 was considered to indicate statistical significance.
Discussion
To our knowledge, this study is the first to investigate the relationship between HRQoL and sarcopenic parameters, with a specific emphasis on muscle strength, within the Chinese hemodialysis patient. Our findings suggest that HGS was independently associated with a better quality of life, predominantly reflected in the PCS score of the SF-36. However, no significant correlation was found in the MCS domain.
In our study, the mean SF-36 PCS was 43.8 and the mean SF-36 MCS was 57.3, which closely aligns with previous study’s findings of PCS 46.3 and MCS 55.1 in Romania (30). However, our study exhibits substantial discrepancies when compared to research conducted in Russia (31). Studies from different countries have shown that there are differences in HRQoL among ESRD patients treated with hemodialysis. A study involving MHD patients from three continents demonstrated significant variations in HRQoL across various countries and regions (11). Patients in the United States had the highest MCS scores, and Japanese patients reported better physical functioning than those in the United States or Europe. PCS scores across various studies ranged from 33.1 to 46.3, while MCS scores ranged from 43.2 to 55.1 (11, 30, 31). The possible reasons for the existence of these differences are potentially due to variations in sample size, demographic characteristics, comorbidities, social support, and dialysis duration.
In the present study, the low PCS group was associated with lower values for parameters related to muscle strength, such as HGS, older age, and lower creatinine levels, as well as with higher levels of inflammation, such as hsCRP and IL-6, and higher levels of TC and body fat mass. The low-PCS group exhibited a significantly higher mean age compared to the high-PCS group. It may be due to a decrease in physical activity levels with aging, and a reduction in social activities as well. Fat mass in the high-PCS groups was lower than the low-PCS group. One possible explanation is that individuals in the high-PCS group tend to participate in more social activities and exhibit a higher level of physical activity. Increasing physical activity levels has been shown to be advantageous for promoting an increase in lean body mass and a decrease in body fat mass. Compared to the high-PCS group, the low-PCS group had higher inflammatory markers (IL-6 and hsCRP). This phenomenon may be mediated by the change in body fat composition. As mentioned above, MHD patients in the low-PCS group had higher fat mass, which is associated with a redistribution of fat depots, shifting from subcutaneous locations to more harmful ectopic locations (32–35). This redistribution results in obesity, particularly visceral fat deposits, and lipid spillover into muscle (36–38). This fat deposition shifts fat into infiltrating skeletal muscle as intermuscular adipose tissue, which releases a host of proinflammatory cytokines, such as interleukin-6 (IL-6), onto muscle fibers, resulting in local inflammation within the muscle (39). Our findings indicated that body fat mass, hsCRP and IL-6 may also serve as one of the indicators for assessing HRQoL in hemodialysis patients. In addition, the results showed that the high-PCS group had lower TC levels. Possible explanations include the fact that, for people in the high-PCS group, they tend to be more active and socially inclined, which may contribute to keep better body composition and blood lipid levels. The research by Lonardo et al. suggested that changes in skeletal muscle mass could have a role in worsening lipid profile (40).
As for the MCS groups, the high-MCS group exhibited higher TC levels. The differences in TC levels between the groups remain unclear. However, one study conducted in Chinese centenarians found that lipid profile was positively associated with the HRQoL (41). These findings warrant further investigation to elucidate the relationship between MCS and TC levels in MHD patient.
In this study, the mean HGS measurement was 19.3 ± 9.50 kg, consistent with other studies on dialysis patients (42, 43). The multivariate logistic regression model revealed that only HGS was significantly associated with the SF-36 PCS scores, indicating that muscle strength determined by handgrip, rather than body composition (fat mass and ASMI), could be an independent factor that lowers physical health of the HRQoL in MHD patients. In previous studies on hemodialysis patients, Maria et al. found that there was no association between sarcopenia and HRQoL, but the components of sarcopenia (handgrip strength and gait speed) showed a correlation with the physical domain of HRQoL (22). Giglio et al. demonstrated that the group with low muscle strength had lower scores in the SF-36 domains, a finding not observed in the group of low muscle mass (23). Similarly, Tsekoura et al. suggested that HGS was significantly correlated with quality of life in hemodialysis patients (42). The associations between muscle strength and HRQoL have also been reported in other populations, such as healthy adults, patients with osteoporosis, cancer survivors, systemic lupus erythematosus patients and spinal disorders patients, suggesting that muscle strength rather than skeletal muscle mass might affect HRQoL (44–48). The mechanism underlying the positive association between muscle strength and HRQoL reported in the aforementioned studies is hypothesized to be mediated by physical activity. Physical inactivity in MHD patients can cause muscle weakness, declines in physical functioning and reduction of atrophic fiber number. The loss of motor neurons leads to an increase in the size of remaining motor units, concurrent with a greater preservation of type I muscle fibers. This results in the preservation of muscle mass with a relatively smaller proportion of type II fibers, thereby contributing to reduced muscle strength (49). Chen et al. conducted a randomized controlled trial in which MHD patients underwent intradialytic low-intensity strength training or stretching exercises (control group) (50). The results showed that compared with the control group, the strength training group showed significant improvements in knee extensor strength and HRQoL domains such as leisure time, physical activity, and self-reported physical function and disability in activities of daily living. Silva et al. also found that supervised physical therapy during hemodialysis sessions improved knee extensor muscle strength, leading to benefits in activities of daily living and HRQoL (51). The current findings suggest that even at lower training intensities, most MHD patients increase muscle strength, minimizing the negative impact of a sedentary lifestyle (23, 51, 52). Maintaining or promoting muscle strength through exercise is crucial for the HRQoL of patients undergoing MHD.
Our results indicated that high HGS was independently correlated with a better quality of life, primarily in the PCS domain. However, no significant correlation was found in the MCS domain. These results align with some prior studies conducted on older populations, (53, 54) but only partially agree with other investigations. In MHD patients and community-dwelling nonagenarians, several studies have substantiated the correlation between HGS and both physical and mental health (23). Sayer et al. reported a correlation between reduced grip strength and a higher prevalence of poor SF-36 score in general health, physical activity and mental health among younger individuals (20). In contrast, Wang et al.’s study did not demonstrate a correlation between muscle strength and PCS or MCS domain scores in MHD patients (55). The discrepancies observed in these studies could be attributed to several factors: (a) Variations in muscle strength measurement methods, such as focusing on ankle dorsiflexion strength (reflecting lower limb muscle strength) or grip strength (primarily reflecting upper limb muscle strength); (b) Inconsistencies in the scales used to measure HRQoL, including the SF-36, EuroQol-5 Dimensions, and disease-specific scales; (c) Diversity in study populations, encompassing age, race, comorbidities, and other demographic factors, which may contribute to differing outcomes. Therefore, further research is necessary to explore the relationship between upper and lower limb muscle strength and HRQoL in hemodialysis patients, with a specific focus on prospective and interventional studies.
In summary, this study found that HGS, body fat mass, IL-6, hsCRP and TC were associated with HRQoL in a univariate analysis. Multivariate logistic regression model suggested that HGS may serve as a robust predictor of HRQoL in patients undergoing MHD. However, further research is warranted to validate these findings. The major strength of our study is that it firstly analyzed the relationship between HGS and HRQoL in Chinese patients undergoing MHD. Moreover, prior research has suggested that multiple factors may impact HRQoL scores and muscle health in MHD patients (43, 56–58). We considered potential confounders—age, sex, fat mass, ASMI, creatinine and TC levels, as well as inflammatory markers such as hsCRP and nutritional indicators such as albumin—thus bolstering the reliability of our results. The study faced several limitations. Firstly, due to its cross-sectional design, the study cannot establish any cause-effect relationships between muscle strength and HRQoL. Secondly, the analysis excluded certain sociodemographic variables such as education level, marital status, and living arrangements, as well as factors like depression and sleep quality. These omissions may have affected the potential for robust correlations between muscle strength and HRQoL, including dietary intake and nutritional status, which are also known to affect the quality of life of MHD patients (18, 56, 59). Furthermore, the participants of this study were selected from a single hemodialysis center using a convenience sampling approach. Future research aims to enhance the robustness of the findings by increasing the sample size, adopting more rigorous sampling methods, and conducting multi-center studies to explore the relationship between muscle strength and quality of life.