Sex differences in the association between muscle mass or strength and nutrition status in chronic hemodialysis patients

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However, there are few reports examining whether differences exist between sexes in the association between muscle mass, muscle strength, and nutritional status. This study aimed to investigate the association between muscle mass, muscle strength, and nutrition in dialysis patients, with a specific focus on sex differences. Methods This single-center, retrospective, cross-sectional, and observational study was conducted from October 2018 to February 2019. We enrolled 89 patients undergoing regular hemodialysis (HD) at a single dialysis center (Imus Fujimi General Hospital, Saitama, Japan). The relationship between skeletal muscle index (SMI) measured by bioelectrical impedance analysis (BIA), handgrip strength, and nutritional status as assessed by the geriatric nutritional risk index (GNRI), along with other biochemical parameters, was analyzed separately for men and women. Results A positive associations was observed between SMI and GNRI (P-for-GNRI < 0.001). In women, the relationship was nonlinear, presenting a U-shaped pattern, although this was not statistically significant (P-for-nonlinear = 0.085). No association was found between SMI and nPCR (P-for-nPCR = 0.628). SMI and CRP showed a significant nonlinear U-shaped relationship (P-for-nonlinear = 0.001). Although a negative associations could not be confirmed, a significant association was observed (P-for-CRP = 0.001). In women, SMI was maintained even at higher CRP levels. GNRI and CRP also exhibited a significant nonlinear U-shaped relationship (P-for-nonlinear = 0.012), with a notable association despite the absence of a clear negative correlation (P-for-CRP = 0.002). In women, GNRI remained preserved even when CRP levels were elevated. Conclusion An association was found between muscle mass, muscle strength, and nutrition. Women exhibited a nonlinear relationship, distinct from men, suggesting that women may require more robust nutritional management compared to men. Furthermore, the direct association between inflammation and nutrition appeared more prominent in men, whereas the association in women was less distinct. However, the influence of the small sample size of female participants in this study cannot be ruled out, and larger-scale clinical studies are needed. hemodialysis sex differences SMI GNRI grip strength CRP Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The importance of nutrition in kidney disease care has long been recognized, and this holds true in dialysis treatment as well. In particular, sarcopenia and frailty have gained increasing awareness among healthcare professionals and are becoming more widely understood in the general public. In the field of kidney disease care, including dialysis, there has been a shift from a restrictive approach to dietary guidance to a more evidence-based evaluation of the scientific benefits and risks of dietary restrictions. In Japan, guidelines for dietary therapy have been revised frequently to reflect these advancements. On the other hand, research on sex differences in medicine as a whole remains significantly insufficient. In particular, despite the expectation of substantial differences in nutritional aspects, approaches considering sex differences have rarely been undertaken. In the field of chronic kidney disease (CKD), it is reported that the prevalence of CKD diagnosis is higher in women. However, the progression to dialysis is slower, and the proportion of women initiating dialysis is lower ( 1 ). In the nutritional domain, it has been reported that, regardless of renal function (normal or CKD), the incidence of arterial sclerosis and cardiovascular events caused by hyperphosphatemia significantly increases only in men ( 2 , 3 ). This suggests that men and women should not be considered equivalent in terms of nutritional management. In recent years, studies focusing on sex differences have finally begun to appear in the field of dialysis ( 1 , 4 ). Reports have examined sex differences in mortality rates among dialysis patients ( 5 ) and in the incidence of dialysis initiation ( 6 ). It has also been shown that the proportion of female dialysis patients increases as the duration of dialysis lengthens ( 7 ). However, most of these reports primarily address disease incidence, and few studies have investigated the differences in the relationship between muscle mass, muscle strength, and nutrition by sex among dialysis patients. In general, women have a higher body fat percentage and lower muscle mass compared to men ( 8 ). Peter et al. also reported sex differences in dialysis patients, noting disparities in lean body mass and body fat mass ( 9 ). Previous studies on the relationship between muscle mass, muscle strength, and nutrition in CKD and dialysis patients, which did not consider sex differences, have consistently demonstrated an association between muscle mass and nutritional indicators. Furthermore, muscle mass and strength (including gait speed) and malnutrition have each been shown to be associated with survival prognosis ( 10 , 11 , 12 , 13 ). Indicators of muscle mass in dialysis patients commonly include measurements by dual-energy X-ray absorptiometry (DEXA) or skeletal muscle index (SMI) assessed using bioelectrical impedance analysis (BIA) ( 14 , 15 ). Handgrip strength is used as an indicator of muscle strength and is also utilized for the diagnosis of sarcopenia ( 15 ). For assessing the nutritional status of dialysis patients, tools such as subjective global assessment (SGA), malnutrition inflammation score (MIS), albumin, pre-albumin, and transferrin are commonly employed. However, the geriatric nutritional risk index (GNRI) has been reported to be an effective and convenient indicator ( 16 ). As mentioned earlier, there are few studies in Japan focusing on the relationship between muscle mass, muscle strength, and nutrition in dialysis patients with an emphasis on sex differences. Additionally, no studies were found that evaluated the relationship using skeletal muscle index (SMI), handgrip strength, and geriatric nutritional risk index (GNRI) as indicators, while considering sex differences. This study aims to investigate the relationship between muscle mass, muscle strength, and nutrition in dialysis patients, with a specific focus on sex differences. PATIENTS AND METHODS Study Patient This study was a single center, cross-sectional, and observational investigation during October 2018 to February 2019. We enrolled 89 patients who had been undergoing regular HD in a single dialysis center (IMS Fujimi General Hospital, Saitama, Japan). All patients had been subjected to regular HD for 4–5 h three times per week at a blood flow rate of 180–300 mL/min and dialysate flow rate was 500–650 mL/min. No bacteria or pyrogen was detected in the dialysate fluid obtained by reverse osmosis. During the observation period, the patient sample received nutritional and exercise counseling interventions as appropriate. Blood Sampling and Laboratory Examinations Blood samples were drawn from the arterial site of the arteriovenous fistula at the start of each dialysis session after a 2-day interval. Serum electrolytes, urea nitrogen, creatinine, albumin, cholesterol, triglycerides, and C-reactive protein (CRP) were measured using standard laboratory techniques with an autoanalyzer. Whole parathyroid hormone (wPTH) levels were determined by immunoradiometric assay. Body mass index (BMI) was calculated as ideal body weight (IBW, kg) divided by the square of body height (m). To evaluate dialysis efficiency, single-pool Kt/V (standardized dialysis dose) was calculated. Nutritional status was assessed using the normalized protein catabolic rate (nPCR) and the Geriatric Nutritional Risk Index (GNRI), calculated using the following equation: GNRI = {14.89 × Albumin (g/dL)} + {41.7 × (Body Weight / Ideal Body Weight)} ( 16 ) nPCR was calculated using the formula provided in the JRDR database ( 17 ). Body composition analysis. Body muscle volume was evaluated using bioimpedance analysis (BIA) with the InBody S10 body composition analyzer (InBody Japan Inc., Tokyo, Japan), which is a multifrequency bioimpedance device. The BIA measurement of dialysis patients was conducted by the same operator after a hemodialysis session by the standard procedure. Briefly, all the subjects were in a lying posture with legs set apart and arms not touching the torso. The eight surface electrodes are placed on the thumbs, middle fingers, and either side of the ankles of the patients using multiple operating frequencies of 1, 5, 50, 250, 500, and 1,000 kHz. The parameters assessed by BIA measurement were intracellular water (ICW), extracellular water (ECW), total body water (TBW), bone mineral content (BMC), fat mass (FM) and skeletal muscle mass (SMM). SMI was determined as the sum of the limb skeletal muscle mass and normalized for the square of body height (m). Grip strength on Non-shunt side Hand grip strength (HGS) was measured using a GRIP-D® (TAKEI co., Nigata, Japan) after the dialysis session. HGS was measured in the arm without the arterio-venous fistula, regardless of whether it was the dominant arm. The HGS measurement was repeated thrice in a sitting position using the dynamometer, in kilogram units. The maximum grip strength value among all measurements was used in the study. ethics This study complied with the Declaration of Helsinki (seventh revision, 2013) on medical protocol and ethics. This was a cross-sectional observational study. Since we collected the data from physicians’ charts filled out by the patients, the Institutional Review Boards at each hospital waived the requirement of written informed consent but requested patients be given the opportunity to refuse enrollment by leaflets or the hospital website. statistical analysis In order to summarize baseline patients, demographical and clinical characteristics, means and standard deviations were used for continuous variables. Regarding the continuous variables, comparisons between sex were performed using Student ’ s t-test. For the categorical variables, comparisons were performed using the chi-squared test. Statistical analysis was performed using multiple nonlinear regression analysis to examine the relationships among muscle mass, nutrition, and sex. The objective variables were SMI and grip strength, and their association with GNRI, sex, and some clinical characteristics was analyzed after the data were adjusted for age, diabetes, and dialysis history. Gender and diabetes were categorical variables, and all other variables were continuous variables. Nonlinearity of the associations between those variables was assessed by including restricted cubic splines with three knots in the regression models. Statistical tests were considered significant at P < 0.05, and all p values were two-sided. We used R (Version 3.6.0, patched, http://www.r-project.org ; The R Foundation, Vienna, Austria) for all statistical analyses. RESULTS The background characteristics of the patients are summarized in Table 1. Categorical variables are presented as percentages (number of cases), and continuous variables are expressed as mean values (standard deviation). The average age of the patients was close to the mean age of dialysis patients in Japan, but many had relatively short dialysis durations. Diabetic nephropathy accounted for approximately 40% of the underlying diseases. No significant sex differences were observed in obesity rates. However, muscle mass (SMI) and handgrip strength were significantly higher in men, while body fat percentage was significantly higher in women. The mean GNRI was 99.1, indicating good nutritional status in both men and women. Total cholesterol (T-cho) levels were significantly higher in women. No significant sex differences were observed in other biochemical parameters, including CRP and single-pool Kt/V. Figure 1 shows the associations SMI and GNRI, nPCR, CRP, and albumin (Alb). P-for-interaction indicates the p-value for interaction, and P-for-nonlinear represents the p-value for nonlinearity. The analysis was adjusted for age (median: 71 years), sex (majority: male), dialysis duration (median: 30 months), and diabetes status (majority: non-diabetic). The results were illustrated using restricted cubic spline regression with three knots. The variables related to SMI showed a significant P-for-sex, reflecting differences in muscle mass between men and women. A positive associations was observed between SMI and GNRI (P-for-GNRI < 0.001). In women, the relationship was nonlinear and presented a U-shaped pattern, although it was not statistically significant (P-for-nonlinear = 0.085). In female patients, SMI tended to increase only when GNRI exceeded 100. No associations was observed between SMI and nPCR (P-for-nPCR = 0.628). The relationship between SMI and CRP showed a statistically significant nonlinear U-shaped curve (P-for-nonlinear = 0.001), indicating an association without a clear negative associations (P-for-CRP = 0.001). In women, SMI was preserved even at higher CRP levels. No association was observed between SMI and Alb (P-for-Alb = 0.663). Figure 2 shows the associations between handgrip strength (HGS) and GNRI, nPCR, and CRP. P-for-interaction indicates the p-value for interaction, and P-for-nonlinear represents the p-value for nonlinearity. The analysis was adjusted for age (median: 71 years), sex (majority: male), dialysis duration (median: 30 months), and diabetes status (majority: non-diabetic). The associations were illustrated using restricted cubic spline regression with three knots. The relationships between HGS and GNRI, nPCR, and CRP showed trends similar to those observed with SMI, but none reached statistical significance (P-for-GNRI = 0.195, P-for-nPCR = 0.651, P-for-CRP = 0.057). Figure 3 shows the associations between GNRI and nPCR, CRP, triglycerides (TG), and total cholesterol (T-cho). P-for-interaction indicates the p-value for interaction, and P-for-nonlinear represents the p-value for nonlinearity. The analysis was adjusted for age (median: 71 years), sex (majority: male), dialysis duration (median: 30 months), and diabetes status (majority: non-diabetic). The associations were illustrated using restricted cubic spline regression with three knots. No associations were found between GNRI and nPCR, TG, or T-cho (P-for-nPCR = 0.364, P-for-TG = 0.336, P-for-T-cho = 0.411). GNRI and CRP exhibited a significant nonlinear U-shaped relationship (P-for-nonlinear = 0.012), indicating an association despite the absence of a clear negative associations (P-for-CRP = 0.002). In women, GNRI remained preserved even at elevated CRP levels. DISCUSSION Consistent with previous reports, GNRI (nutritional status) showed a positive correlation with SMI (muscle mass). In women, a nonlinear relationship was observed, with muscle mass starting to increase when GNRI exceeded 100. Additionally, the relationship between CRP and SMI was linear and negative in men, whereas in women, a nonlinear relationship was observed. Notably, SMI was maintained in women even at high CRP levels. No correlation was found between nPCR and SMI or handgrip strength. Previous studies have demonstrated correlations between muscle mass, muscle strength, and nutrition in dialysis patients. However, few reports have considered these relationships separately by sex ( 10 , 11 , 12 , 13 ). In this study, sex differences were observed in the relationships between muscle mass, handgrip strength, and nutrition. The novelty of this study lies in the observation that, while GNRI and SMI, as well as CRP and SMI, showed linear relationships in men, a U-shaped nonlinear relationship was found in women. The nonlinear relationship between GNRI and SMI in women may be attributed to physiological differences, where women prioritize energy storage as fat before initiating muscle synthesis. It is well known that as women reach adulthood, an increase in estrogen leads to a reduction in lean body mass, whereas in men, lean body mass increases due to the influence of testosterone. The effects of hormones cause men to have a higher muscle mass, while women prioritize increasing fat tissue and essential fat levels ( 18 ). These phenomena are not limited to dialysis patients but are observed universally, and similar trends were demonstrated among dialysis patients in this study. In this analysis, the nonlinear relationship observed in women is thought to result from their physiological tendency to prioritize fat synthesis before initiating muscle synthesis. In other words, sufficient nutrition is likely required to increase muscle strength in women compared to men. It has already been established that elevated CRP levels negatively affect muscle mass and nutrition ( 19 , 20 ). The fact that SMI and GNRI were maintained in women despite high CRP levels suggests that women may be less affected by inflammation than men. Two potential mechanisms, outlined below, may explain this phenomenon : 【1】In septic conditions (elevated CRP levels), female sex hormones have been shown to support immune function, providing an advantage over men in managing inflammation ( 21 ). Peter et al. also reported that female dialysis patients demonstrated higher survival rates despite elevated CRP levels ( 9 ). 【2】As observed in this study, women have a higher body fat percentage compared to men. Reports indicate that adiponectin concentrations, which are secreted by adipocytes, are higher in women. Adiponectin is known to exhibit anti-inflammatory effects ( 22 ). Additionally, adipocytes synthesize and secrete soluble TNF-α receptors, which bind to TNF-α and suppress its inflammatory activity ( 23 ). Based on these mechanisms【1,2】, it can be inferred that women may better respond to inflammation due to the effects of sex hormones, higher fat mass, and the anti-inflammatory actions of adiponectin and TNF-α inhibition. The U-shaped relationship between GNRI and CRP observed in women may be attributed to higher fat mass and stronger anti-inflammatory effects in female patients with elevated CRP, which could have contributed to relatively higher GNRI values. Regardless of sex differences, the association between CRP and nutritional status has been previously described as part of the malnutrition–inflammation–atherosclerosis (MIA) syndrome, as noted in reference 19. In summary, as suggested by previous studies, the relationship between inflammation and nutritional status aligns more directly with established patterns in men. However, in women, this relationship may not be as clear or straightforward. In this study, no correlation was observed between nPCR (an indicator of protein intake) and SMI, handgrip strength, or GNRI. It has been reported that nPCR may be underestimated in dialysis patients if residual renal function is preserved and renal urea clearance is not included in the evaluation ( 24 ). In the present cases, the lack of evaluation of residual renal urea clearance may have resulted in underestimated nPCR values. This study has several limitations : It is a single-center, cross-sectional study. The total sample size is small. The proportion of men and women is unequal, with fewer women included. The possibility cannot be ruled out that the observed nonlinear associations in women were due to the small number of female participants. Additionally, since all subjects were outpatients from a single hospital, the possibility of sampling bias cannot be excluded, and it remains unclear whether these findings are generalizable to other ethnicities or age groups. Furthermore, due to the limited sample size, adjustments could only be made for age, diabetes status, and dialysis duration, and residual confounding may remain. Because of the observational study design, causal relationships between SMI, GNRI, and related variables cannot be established. Regarding the correction method for SMI as an indicator of muscle mass, there are reports discussing the utility of correcting for body weight or BMI rather than the commonly used height correction. However, in this study, we adopted height correction, as utilized by the Asian Working Group for Sarcopenia (AWGS) ( 15 ). Although height-corrected SMI has been reported to potentially underestimate sarcopenia, these findings are generally based on populations with overweight or obese patients. This does not apply to the patient population examined in this study ( 25 ). Conclusion An relationship was observed between muscle mass, muscle strength, and nutrition. In women, unlike in men, a nonlinear relationship was demonstrated, suggesting that women may require more robust nutritional management compared to men. Additionally, the direct relationship between inflammation and nutrition appears to be more applicable to men, whereas in women, this relationship may not be as clear or straightforward. However, the influence of the small sample size of female participants in this study cannot be excluded, and larger-scale clinical studies are needed. Declarations Conflict of interest The authors have no conflicts of interest to declare. - Ethical Approval and Consent to participate This study complied with the Declaration of Helsinki (seventh revision, 2013) on medical protocol and ethics. This was a cross-sectional observational study. Since we collected the data from physicians ’ charts filled out by the patients, the Institutional Review Boards at each hospital waived the requirement of written informed consent but requested patients be given the opportunity to refuse enrollment by leaflets or the hospital website. - Consent for publication Applicable - Availability of supporting data All the data for this manuscript have been included in this article. Further enquiries can be provided upon reasonable request from the corresponding author. - Competing interests Not applicable - Funding Not applicable - Authors' contributions Not applicable - Acknowledgements The authors are grateful to all the medical staff who participated in this study. - Authors' information (Optional) Y.T and Y.K wrote the main manuscript text, and K.T and K.F prepared Figures 1–3. T.O, A.S, and H.H provided guidance on manuscript preparation. Y.T and T.O supervised the work. References Cobo G, Hecking M, Port FK, Exner I, Lindholm B, Stenvinkel P: Sex and gender differences in chronic kidney disease: progression to end-stage renal disease and hemodialysis. Clin Sci (Lond). 2016 Jul 1;130(14):1147-63. Martín M, Valls J, Betriu A, Fernández E, Valdivielso JM: Association of serum phosphorus with subclinical atherosclerosis in chronic kidney disease. Sex makes a difference. Atherosclerosis. 2015 Jul;241(1):264-70. Yoo KD, Kang S, Choi Y, Yang SH, Heo NJ, Chin HJ: Sex, Age, and the Association of Serum Phosphorus With All-Cause Mortality in Adults With Normal Kidney Function. Am J Kidney Dis. 2016 Jan;67(1):79-88. Artan AS, Kircelli F, Ok E, Yilmaz M, Asci G, Dogan C: Dialyzing women and men: does it matter? An observational study. Clin Kidney J. 2016 Jun;9(3):486-93. Carrero JJ, de Jager DJ, Verduijn M, Ravani P, De Meester J, Heaf JG: Cardiovascular and noncardiovascular mortality among men and women starting dialysis. Clin J Am Soc Nephrol. 2011 Jul;6(7):1722-30. Iseki K, Nakai S, Shinzato T, Nagura Y, Akiba T: Patient Registration Committee of the Japanese Society for Dialysis Therapy. Increasing gender difference in the incidence of chronic dialysis therapy in Japan. Ther Apher Dial. 2005 Oct;9(5):407-11. Japanese society for dialysis therapy renal data registry 2016. Bredella MA: Sex Differences in Body Composition. Adv Exp Med Biol.2017;1043:9-27. 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Table 1 【Table 1】 female male all cases p-value n 23 66 89 Age (years) 71.9 (10.9) 69.3 (11.7) 69.9 (11.5) 0.35 Diabetes (%) No 60.9 (14) 59.1 (39) 59.6 (53) 0.88 Yes 39.1 ( 9) 40.9 (27) 40.4 (36) GNRI 98.0 (8.2) 99.4 (9.7) 99.1 (9.3) 0.54 Height (m) 1.51 (0.08) 1.63 (0.07) 1.60 (0.09) <0.001 Dry Weight (kg) 50.6 (11.1) 61.0 (12.9) 58.3 (13.2) 0.001 BMI 22.0 (3.3) 22.9 (4.3) 22.7 (4.1) 0.37 grip power (kg) 7.7 (6.0) 15.7 (8.0) 13.6 (8.3) <0.001 ECW/TBW 0.40 (0.01) 0.39 (0.01) 0.40 (0.01) <0.001 SMI (kg/m 2 ) 5.3 (1.0) 6.7 (1.0) 6.3 (1.2) <0.001 fat mass 17.7 (7.5) 18.0 (8.21) 17.9 (8.0) 0.89 body fat (%) 34.2 (9.8) 28.4 (8.0) 29.9 (8.8) 0.006 duration of dialysis (month) 53.3 (80.2) 43.6 (37.4) 46.11 (51.6) 0.44 CRP (mg/dL) 0.3 (0.5) 0.6 (2.0) 0.5 (1.7) 0.35 nPCR (g/kg/day) 0.8 (0.1) 0.8 (0.2) 0.8 (0.1) 0.78 Alb (mg/dL) 3.8 (0.3) 3.8 (0.3) 3.8 (0.3) 0.68 Mg (mg/dL) 2.7 (0.3) 2.5 (0.4) 2.6 (0.4) 0.09 corrected Ca (mg/dL) 8.8 (0.5) 8.6 (0.5) 8.6 (0.5) 0.09 P (mg/dl) 5.2 (1.2) 5.4 (1.3) 5.3 (1.3) 0.49 Ca×P 45.2 (11.7) 45.7 (10.8) 45.6 (11.0) 0.85 Whole-PTH (pg/mL) 113.6 (61.7) 141.1 (79.8) 134.0 (76.1) 0.14 Kt/V 1.15 (0.33) 1.09 (0.28) 1.11 (0.29) 0.40 TG (mg/dL) 136.0 (80.3) 128.4 (93.5) 130.4 (89.9) 0.73 Tcho (mg/dL) 175.6 (31.9) 150.9 (31.8) 157.3 (33.5) 0.002 GNRI: geriatric nutritional risk index BMI: body mass index ECW: extracellular water TBW: total body water SMI: skeletal muscle index nPCR: normalized protein catabolic rate Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Jun, 2025 Read the published version in Renal Replacement Therapy → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6093481","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":443567305,"identity":"eb3b3a9b-4e76-4fee-833e-55e35f8bd4c0","order_by":0,"name":"Yosuke Tayama","email":"","orcid":"","institution":"Department of Nephlorogy, Imusu Fujimi General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yosuke","middleName":"","lastName":"Tayama","suffix":""},{"id":443567307,"identity":"e0f21408-f5a1-4816-bcaa-da978c3575c9","order_by":1,"name":"Tomonari Ogawa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYPACGwYGZjgnAUSw4VTLA6HSgFrgeojTcpgByZoE/C6yZ2+/+Jmn5rw9fzv/wU83ahii+dkTGD/8YODLw2kLz5liaZ5jtxNnHGZmls45xpA7s+cBs2QPA1sxTi0SOQnSOWy3ExgOMzMAGf9zN9xIYJAG+iWxAbeW5N85/87ZywNtATIYcvffSGD+jV9L+jHp3LYDjBsOM7MBGQy5GyQS2PDbcuYMm/XfvuTEjYeZzaxz+xhyZ5x52GbZY4DbL+zt7Y9vzvhmZy93/uDj2znfGHL725MP3/hRcQxniAHtMUAXYQQ6yeBYAm4t7A+wCtfg0TIKRsEoGAUjDAAAk49ThU8FtP8AAAAASUVORK5CYII=","orcid":"","institution":"Department of Nephlorogy, Hypertension, Bloodpurification, Saitama Medical Center, Saitama Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tomonari","middleName":"","lastName":"Ogawa","suffix":""},{"id":443567309,"identity":"fd9ba9ee-9bf2-4c6d-b88a-9279339d9ae3","order_by":2,"name":"Yoshimi Konishi","email":"","orcid":"","institution":"Department of Nephlorogy, Imusu Fujimi General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yoshimi","middleName":"","lastName":"Konishi","suffix":""},{"id":443567310,"identity":"2e4a3d1c-9e6f-45a6-bd24-cc525364be22","order_by":3,"name":"Kanae Takahashi","email":"","orcid":"","institution":"Medical Statistics, Osaka Metropolitan University","correspondingAuthor":false,"prefix":"","firstName":"Kanae","middleName":"","lastName":"Takahashi","suffix":""},{"id":443567312,"identity":"4a6f9e8c-cc8c-4498-856f-86500569d8f3","order_by":4,"name":"Koichiro Fujii","email":"","orcid":"","institution":"Pediatric medical center, Osaka City General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Koichiro","middleName":"","lastName":"Fujii","suffix":""},{"id":443567314,"identity":"a5c05ad5-ce60-4899-a319-e9c014ac1593","order_by":5,"name":"Ayumi Shintani","email":"","orcid":"","institution":"Medical Statistics, Osaka Metropolitan University","correspondingAuthor":false,"prefix":"","firstName":"Ayumi","middleName":"","lastName":"Shintani","suffix":""},{"id":443567316,"identity":"004c73af-1210-41d8-907f-d058c63e9762","order_by":6,"name":"Hajime Hasegawa","email":"","orcid":"","institution":"Department of Nephlorogy, Hypertension, Bloodpurification, Saitama Medical Center, Saitama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hajime","middleName":"","lastName":"Hasegawa","suffix":""}],"badges":[],"createdAt":"2025-02-24 05:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6093481/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6093481/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s41100-025-00636-5","type":"published","date":"2025-06-15T15:56:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81009669,"identity":"1ca50879-2650-4f6b-be3b-6a4d37a6c42e","added_by":"auto","created_at":"2025-04-21 08:09:08","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":113277,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6093481/v1/6c21d7ad897204a6a240c18e.jpg"},{"id":81009673,"identity":"6df5e361-2700-47c7-b9c9-db8399a3f4d5","added_by":"auto","created_at":"2025-04-21 08:09:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98040,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6093481/v1/97c93159eee26efc2a375b05.jpg"},{"id":81009671,"identity":"ba60b075-4153-45ec-a644-26f1efad7b9b","added_by":"auto","created_at":"2025-04-21 08:09:08","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":116127,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6093481/v1/802b1a3eabfcafe08de3e28e.jpg"},{"id":84726414,"identity":"f2b0a935-bc0e-490f-acc0-5e7396bb86db","added_by":"auto","created_at":"2025-06-16 15:59:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":840050,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6093481/v1/1f7a7b68-a35f-49a2-b81f-24cd37bbbbbc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sex differences in the association between muscle mass or strength and nutrition status in chronic hemodialysis patients","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe importance of nutrition in kidney disease care has long been recognized, and this holds true in dialysis treatment as well. In particular, sarcopenia and frailty have gained increasing awareness among healthcare professionals and are becoming more widely understood in the general public. In the field of kidney disease care, including dialysis, there has been a shift from a restrictive approach to dietary guidance to a more evidence-based evaluation of the scientific benefits and risks of dietary restrictions. In Japan, guidelines for dietary therapy have been revised frequently to reflect these advancements.\u003c/p\u003e \u003cp\u003eOn the other hand, research on sex differences in medicine as a whole remains significantly insufficient. In particular, despite the expectation of substantial differences in nutritional aspects, approaches considering sex differences have rarely been undertaken. In the field of chronic kidney disease (CKD), it is reported that the prevalence of CKD diagnosis is higher in women. However, the progression to dialysis is slower, and the proportion of women initiating dialysis is lower (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In the nutritional domain, it has been reported that, regardless of renal function (normal or CKD), the incidence of arterial sclerosis and cardiovascular events caused by hyperphosphatemia significantly increases only in men (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). This suggests that men and women should not be considered equivalent in terms of nutritional management.\u003c/p\u003e \u003cp\u003eIn recent years, studies focusing on sex differences have finally begun to appear in the field of dialysis (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Reports have examined sex differences in mortality rates among dialysis patients (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and in the incidence of dialysis initiation (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). It has also been shown that the proportion of female dialysis patients increases as the duration of dialysis lengthens (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, most of these reports primarily address disease incidence, and few studies have investigated the differences in the relationship between muscle mass, muscle strength, and nutrition by sex among dialysis patients. In general, women have a higher body fat percentage and lower muscle mass compared to men (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Peter et al. also reported sex differences in dialysis patients, noting disparities in lean body mass and body fat mass (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious studies on the relationship between muscle mass, muscle strength, and nutrition in CKD and dialysis patients, which did not consider sex differences, have consistently demonstrated an association between muscle mass and nutritional indicators. Furthermore, muscle mass and strength (including gait speed) and malnutrition have each been shown to be associated with survival prognosis (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Indicators of muscle mass in dialysis patients commonly include measurements by dual-energy X-ray absorptiometry (DEXA) or skeletal muscle index (SMI) assessed using bioelectrical impedance analysis (BIA) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Handgrip strength is used as an indicator of muscle strength and is also utilized for the diagnosis of sarcopenia (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). For assessing the nutritional status of dialysis patients, tools such as subjective global assessment (SGA), malnutrition inflammation score (MIS), albumin, pre-albumin, and transferrin are commonly employed. However, the geriatric nutritional risk index (GNRI) has been reported to be an effective and convenient indicator (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs mentioned earlier, there are few studies in Japan focusing on the relationship between muscle mass, muscle strength, and nutrition in dialysis patients with an emphasis on sex differences. Additionally, no studies were found that evaluated the relationship using skeletal muscle index (SMI), handgrip strength, and geriatric nutritional risk index (GNRI) as indicators, while considering sex differences. This study aims to investigate the relationship between muscle mass, muscle strength, and nutrition in dialysis patients, with a specific focus on sex differences.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Patient\u003c/h2\u003e \u003cp\u003eThis study was a single center, cross-sectional, and observational investigation during October 2018 to February 2019. We enrolled 89 patients who had been undergoing regular HD in a single dialysis center (IMS Fujimi General Hospital, Saitama, Japan). All patients had been subjected to regular HD for 4\u0026ndash;5 h three times per week at a blood flow rate of 180\u0026ndash;300 mL/min and dialysate flow rate was 500\u0026ndash;650 mL/min. No bacteria or pyrogen was detected in the dialysate fluid obtained by reverse osmosis. During the observation period, the patient sample received nutritional and exercise counseling interventions as appropriate.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBlood Sampling and Laboratory Examinations\u003c/h3\u003e\n\u003cp\u003eBlood samples were drawn from the arterial site of the arteriovenous fistula at the start of each dialysis session after a 2-day interval. Serum electrolytes, urea nitrogen, creatinine, albumin, cholesterol, triglycerides, and C-reactive protein (CRP) were measured using standard laboratory techniques with an autoanalyzer. Whole parathyroid hormone (wPTH) levels were determined by immunoradiometric assay. Body mass index (BMI) was calculated as ideal body weight (IBW, kg) divided by the square of body height (m). To evaluate dialysis efficiency, single-pool Kt/V (standardized dialysis dose) was calculated. Nutritional status was assessed using the normalized protein catabolic rate (nPCR) and the Geriatric Nutritional Risk Index (GNRI), calculated using the following equation:\u003c/p\u003e \u003cp\u003eGNRI = {14.89 \u0026times; Albumin (g/dL)} + {41.7 \u0026times; (Body Weight / Ideal Body Weight)} (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003cp\u003enPCR was calculated using the formula provided in the JRDR database (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eBody composition analysis.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eBody muscle volume was evaluated using bioimpedance analysis (BIA) with the InBody S10 body composition analyzer (InBody Japan Inc., Tokyo, Japan), which is a multifrequency bioimpedance device. The BIA measurement of dialysis patients was conducted by the same operator after a hemodialysis session by the standard procedure. Briefly, all the subjects were in a lying posture with legs set apart and arms not touching the torso. The eight surface electrodes are placed on the thumbs, middle fingers, and either side of the ankles of the patients using multiple operating frequencies of 1, 5, 50, 250, 500, and 1,000 kHz. The parameters assessed by BIA measurement were intracellular water (ICW), extracellular water (ECW), total body water (TBW), bone mineral content (BMC), fat mass (FM) and skeletal muscle mass (SMM). SMI was determined as the sum of the limb skeletal muscle mass and normalized for the square of body height (m).\u003c/p\u003e\n\u003ch3\u003eGrip strength on Non-shunt side\u003c/h3\u003e\n\u003cp\u003eHand grip strength (HGS) was measured using a GRIP-D\u0026reg; (TAKEI co., Nigata, Japan) after the dialysis session. HGS was measured in the arm without the arterio-venous fistula, regardless of whether it was the dominant arm. The HGS measurement was repeated thrice in a sitting position using the dynamometer, in kilogram units. The maximum grip strength value among all measurements was used in the study.\u003c/p\u003e\n\u003ch3\u003eethics\u003c/h3\u003e\n\u003cp\u003e This study complied with the Declaration of Helsinki (seventh revision, 2013) on medical protocol and ethics. This was a cross-sectional observational study. Since we collected the data from physicians\u0026rsquo; charts filled out by the patients, the Institutional Review Boards at each hospital waived the requirement of written informed consent but requested patients be given the opportunity to refuse enrollment by leaflets or the hospital website.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003estatistical analysis\u003c/h2\u003e \u003cp\u003eIn order to summarize baseline patients, demographical and clinical characteristics, means and standard deviations were used for continuous variables. Regarding the continuous variables, comparisons between sex were performed using Student\u003csup\u003e\u0026rsquo;\u003c/sup\u003es t-test. For the categorical variables, comparisons were performed using the chi-squared test. Statistical analysis was performed using multiple nonlinear regression analysis to examine the relationships among muscle mass, nutrition, and sex. The objective variables were SMI and grip strength, and their association with GNRI, sex, and some clinical characteristics was analyzed after the data were adjusted for age, diabetes, and dialysis history. Gender and diabetes were categorical variables, and all other variables were continuous variables. Nonlinearity of the associations between those variables was assessed by including restricted cubic splines with three knots in the regression models. Statistical tests were considered significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and all p values were two-sided. We used R (Version 3.6.0, patched, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; The R Foundation, Vienna, Austria) for all statistical analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe background characteristics of the patients are summarized in Table\u0026nbsp;1. Categorical variables are presented as percentages (number of cases), and continuous variables are expressed as mean values (standard deviation).\u003c/p\u003e \u003cp\u003eThe average age of the patients was close to the mean age of dialysis patients in Japan, but many had relatively short dialysis durations. Diabetic nephropathy accounted for approximately 40% of the underlying diseases. No significant sex differences were observed in obesity rates. However, muscle mass (SMI) and handgrip strength were significantly higher in men, while body fat percentage was significantly higher in women. The mean GNRI was 99.1, indicating good nutritional status in both men and women. Total cholesterol (T-cho) levels were significantly higher in women. No significant sex differences were observed in other biochemical parameters, including CRP and single-pool Kt/V.\u003c/p\u003e \u003cp\u003eFigure 1 shows the associations SMI and GNRI, nPCR, CRP, and albumin (Alb).\u003c/p\u003e \u003cp\u003eP-for-interaction indicates the p-value for interaction, and P-for-nonlinear represents the p-value for nonlinearity. The analysis was adjusted for age (median: 71 years), sex (majority: male), dialysis duration (median: 30 months), and diabetes status (majority: non-diabetic). The results were illustrated using restricted cubic spline regression with three knots.\u003c/p\u003e \u003cp\u003eThe variables related to SMI showed a significant P-for-sex, reflecting differences in muscle mass between men and women. A positive associations was observed between SMI and GNRI (P-for-GNRI\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In women, the relationship was nonlinear and presented a U-shaped pattern, although it was not statistically significant (P-for-nonlinear\u0026thinsp;=\u0026thinsp;0.085). In female patients, SMI tended to increase only when GNRI exceeded 100. No associations was observed between SMI and nPCR (P-for-nPCR\u0026thinsp;=\u0026thinsp;0.628).\u003c/p\u003e \u003cp\u003eThe relationship between SMI and CRP showed a statistically significant nonlinear U-shaped curve (P-for-nonlinear\u0026thinsp;=\u0026thinsp;0.001), indicating an association without a clear negative associations (P-for-CRP\u0026thinsp;=\u0026thinsp;0.001). In women, SMI was preserved even at higher CRP levels. No association was observed between SMI and Alb (P-for-Alb\u0026thinsp;=\u0026thinsp;0.663).\u003c/p\u003e \u003cp\u003eFigure 2 shows the associations between handgrip strength (HGS) and GNRI, nPCR, and CRP.\u003c/p\u003e \u003cp\u003eP-for-interaction indicates the p-value for interaction, and P-for-nonlinear represents the p-value for nonlinearity. The analysis was adjusted for age (median: 71 years), sex (majority: male), dialysis duration (median: 30 months), and diabetes status (majority: non-diabetic). The associations were illustrated using restricted cubic spline regression with three knots.\u003c/p\u003e \u003cp\u003eThe relationships between HGS and GNRI, nPCR, and CRP showed trends similar to those observed with SMI, but none reached statistical significance (P-for-GNRI\u0026thinsp;=\u0026thinsp;0.195, P-for-nPCR\u0026thinsp;=\u0026thinsp;0.651, P-for-CRP\u0026thinsp;=\u0026thinsp;0.057).\u003c/p\u003e \u003cp\u003eFigure 3 shows the associations between GNRI and nPCR, CRP, triglycerides (TG), and total cholesterol (T-cho). P-for-interaction indicates the p-value for interaction, and P-for-nonlinear represents the p-value for nonlinearity. The analysis was adjusted for age (median: 71 years), sex (majority: male), dialysis duration (median: 30 months), and diabetes status (majority: non-diabetic). The associations were illustrated using restricted cubic spline regression with three knots.\u003c/p\u003e \u003cp\u003eNo associations were found between GNRI and nPCR, TG, or T-cho (P-for-nPCR\u0026thinsp;=\u0026thinsp;0.364, P-for-TG\u0026thinsp;=\u0026thinsp;0.336, P-for-T-cho\u0026thinsp;=\u0026thinsp;0.411). GNRI and CRP exhibited a significant nonlinear U-shaped relationship (P-for-nonlinear\u0026thinsp;=\u0026thinsp;0.012), indicating an association despite the absence of a clear negative associations (P-for-CRP\u0026thinsp;=\u0026thinsp;0.002). In women, GNRI remained preserved even at elevated CRP levels.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eConsistent with previous reports, GNRI (nutritional status) showed a positive correlation with SMI (muscle mass). In women, a nonlinear relationship was observed, with muscle mass starting to increase when GNRI exceeded 100. Additionally, the relationship between CRP and SMI was linear and negative in men, whereas in women, a nonlinear relationship was observed. Notably, SMI was maintained in women even at high CRP levels. No correlation was found between nPCR and SMI or handgrip strength. Previous studies have demonstrated correlations between muscle mass, muscle strength, and nutrition in dialysis patients. However, few reports have considered these relationships separately by sex (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In this study, sex differences were observed in the relationships between muscle mass, handgrip strength, and nutrition. The novelty of this study lies in the observation that, while GNRI and SMI, as well as CRP and SMI, showed linear relationships in men, a U-shaped nonlinear relationship was found in women.\u003c/p\u003e \u003cp\u003eThe nonlinear relationship between GNRI and SMI in women may be attributed to physiological differences, where women prioritize energy storage as fat before initiating muscle synthesis. It is well known that as women reach adulthood, an increase in estrogen leads to a reduction in lean body mass, whereas in men, lean body mass increases due to the influence of testosterone. The effects of hormones cause men to have a higher muscle mass, while women prioritize increasing fat tissue and essential fat levels (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). These phenomena are not limited to dialysis patients but are observed universally, and similar trends were demonstrated among dialysis patients in this study. In this analysis, the nonlinear relationship observed in women is thought to result from their physiological tendency to prioritize fat synthesis before initiating muscle synthesis.\u003c/p\u003e \u003cp\u003eIn other words, sufficient nutrition is likely required to increase muscle strength in women compared to men.\u003c/p\u003e \u003cp\u003eIt has already been established that elevated CRP levels negatively affect muscle mass and nutrition (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The fact that SMI and GNRI were maintained in women despite high CRP levels suggests that women may be less affected by inflammation than men. Two potential mechanisms, outlined below, may explain this phenomenon : 【1】In septic conditions (elevated CRP levels), female sex hormones have been shown to support immune function, providing an advantage over men in managing inflammation (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Peter et al. also reported that female dialysis patients demonstrated higher survival rates despite elevated CRP levels (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). 【2】As observed in this study, women have a higher body fat percentage compared to men. Reports indicate that adiponectin concentrations, which are secreted by adipocytes, are higher in women. Adiponectin is known to exhibit anti-inflammatory effects (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Additionally, adipocytes synthesize and secrete soluble TNF-α receptors, which bind to TNF-α and suppress its inflammatory activity (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Based on these mechanisms【1,2】, it can be inferred that women may better respond to inflammation due to the effects of sex hormones, higher fat mass, and the anti-inflammatory actions of adiponectin and TNF-α inhibition. The U-shaped relationship between GNRI and CRP observed in women may be attributed to higher fat mass and stronger anti-inflammatory effects in female patients with elevated CRP, which could have contributed to relatively higher GNRI values.\u003c/p\u003e \u003cp\u003eRegardless of sex differences, the association between CRP and nutritional status has been previously described as part of the malnutrition\u0026ndash;inflammation\u0026ndash;atherosclerosis (MIA) syndrome, as noted in reference 19. In summary, as suggested by previous studies, the relationship between inflammation and nutritional status aligns more directly with established patterns in men. However, in women, this relationship may not be as clear or straightforward.\u003c/p\u003e \u003cp\u003eIn this study, no correlation was observed between nPCR (an indicator of protein intake) and SMI, handgrip strength, or GNRI. It has been reported that nPCR may be underestimated in dialysis patients if residual renal function is preserved and renal urea clearance is not included in the evaluation (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In the present cases, the lack of evaluation of residual renal urea clearance may have resulted in underestimated nPCR values.\u003c/p\u003e \u003cp\u003eThis study has several limitations : It is a single-center, cross-sectional study. The total sample size is small. The proportion of men and women is unequal, with fewer women included. The possibility cannot be ruled out that the observed nonlinear associations in women were due to the small number of female participants. Additionally, since all subjects were outpatients from a single hospital, the possibility of sampling bias cannot be excluded, and it remains unclear whether these findings are generalizable to other ethnicities or age groups. Furthermore, due to the limited sample size, adjustments could only be made for age, diabetes status, and dialysis duration, and residual confounding may remain. Because of the observational study design, causal relationships between SMI, GNRI, and related variables cannot be established. Regarding the correction method for SMI as an indicator of muscle mass, there are reports discussing the utility of correcting for body weight or BMI rather than the commonly used height correction. However, in this study, we adopted height correction, as utilized by the Asian Working Group for Sarcopenia (AWGS) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Although height-corrected SMI has been reported to potentially underestimate sarcopenia, these findings are generally based on populations with overweight or obese patients. This does not apply to the patient population examined in this study (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAn relationship was observed between muscle mass, muscle strength, and nutrition. In women, unlike in men, a nonlinear relationship was demonstrated, suggesting that women may require more robust nutritional management compared to men. Additionally, the direct relationship between inflammation and nutrition appears to be more applicable to men, whereas in women, this relationship may not be as clear or straightforward. However, the influence of the small sample size of female participants in this study cannot be excluded, and larger-scale clinical studies are needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e- Ethical Approval and Consent to participate\u003cbr\u003eThis study complied with the Declaration of Helsinki (seventh revision, 2013) on medical protocol and ethics. This was a cross-sectional observational study. Since we collected the data from physicians\u003cspan dir=\"RTL\"\u003e\u0026rsquo;\u0026nbsp;\u003c/span\u003echarts filled out by the patients, the Institutional Review Boards at each hospital waived the requirement of written informed consent but requested patients be given the opportunity to refuse enrollment by leaflets or the hospital website.\u003c/p\u003e\n\u003cp\u003e- Consent for publication\u003cbr\u003eApplicable\u003c/p\u003e\n\u003cp\u003e- Availability of supporting data\u003cbr\u003eAll the data for this \u0026nbsp;manuscript have been included in this article. Further enquiries can be provided upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e- Competing interests\u003cbr\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e- Funding\u003cbr\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e- Authors\u0026apos; contributions\u003cbr\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e- Acknowledgements\u003cbr\u003eThe authors are grateful to all the medical staff who participated in this study.\u003c/p\u003e\n\u003cp\u003e- Authors\u0026apos; information (Optional)\u003cbr\u003eY.T and Y.K wrote the main manuscript text, and K.T and K.F prepared Figures 1\u0026ndash;3. T.O, A.S, and H.H provided guidance on manuscript preparation. Y.T and T.O supervised the work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCobo G, Hecking M, Port FK, Exner I, Lindholm B, Stenvinkel P: Sex and gender differences in chronic kidney disease: progression to end-stage renal disease and hemodialysis. Clin Sci (Lond). 2016 Jul 1;130(14):1147-63.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;n M, Valls J, Betriu A, Fern\u0026aacute;ndez E, Valdivielso JM: Association of serum phosphorus with subclinical atherosclerosis in chronic kidney disease. Sex makes a difference. Atherosclerosis. 2015 Jul;241(1):264-70.\u003c/li\u003e\n\u003cli\u003eYoo KD, Kang S, Choi Y, Yang SH, Heo NJ, Chin HJ: Sex, Age, and the Association of Serum Phosphorus With All-Cause Mortality in Adults With Normal Kidney Function. Am J Kidney Dis. 2016 Jan;67(1):79-88.\u003c/li\u003e\n\u003cli\u003eArtan AS, Kircelli F, Ok E, Yilmaz M, Asci G, Dogan C: Dialyzing women and men: does it matter? An observational study. Clin Kidney J. 2016 Jun;9(3):486-93.\u003c/li\u003e\n\u003cli\u003eCarrero JJ, de Jager DJ, Verduijn M, Ravani P, De Meester J, Heaf JG: Cardiovascular and noncardiovascular mortality among men and women starting dialysis. Clin J Am Soc Nephrol. 2011 Jul;6(7):1722-30.\u003c/li\u003e\n\u003cli\u003eIseki K, Nakai S, Shinzato T, Nagura Y, Akiba T: Patient Registration Committee of the Japanese Society for Dialysis Therapy. Increasing gender difference in the incidence of chronic dialysis therapy in Japan. Ther Apher Dial. 2005 Oct;9(5):407-11.\u003c/li\u003e\n\u003cli\u003eJapanese society for dialysis therapy renal data registry 2016.\u003c/li\u003e\n\u003cli\u003eBredella MA: Sex Differences in Body Composition. Adv Exp Med Biol.2017;1043:9-27. \u003c/li\u003e\n\u003cli\u003eStenvinkel P, Barany P, Chung SH, Lindholm B, Heimb\u0026uuml;rger O: A comparative analysis of nutritional parameters as predictors of outcome in male and female ESRD patients. Nephrol Dial Transplant. 2002 Jul;17(7):1266-74.\u003c/li\u003e\n\u003cli\u003eGiglio J, Kamimura MA, Lamarca F, Rodrigues J, Santin F, Avesani CM: Association of Sarcopenia With Nutritional Parameters, Quality of Life, Hospitalization, and Mortality Rates of Elderly Patients on Hemodialysis. J Ren Nutr. 2018 May;28(3):197-207.\u003c/li\u003e\n\u003cli\u003eVettoretti S, Caldiroli L, Armelloni S, Ferrari C, Cesari M, Messa P: Sarcopenia is Associated with Malnutrition but Not with Systemic Inflammation in Older Persons with Advanced CKD. Nutrients. 2019 Jun 19;11(6).\u003c/li\u003e\n\u003cli\u003eHara H, Nakamura Y, Hatano M, Iwashita T, Shimizu T, Ogawa T: Protein Energy Wasting and Sarcopenia in Dialysis Patients. Contrib Nephrol. 2018;196:243-249. \u003c/li\u003e\n\u003cli\u003eIsoyama N, Qureshi AR, Avesani CM, Lindholm B, B\u0026agrave;r\u0026agrave;ny P, Heimb\u0026uuml;rger O: Comparative associations of muscle mass and muscle strength with mortality in dialysis patients. Clin J Am Soc Nephrol. 2014 Oct 7;9(10):1720-8.\u003c/li\u003e\n\u003cli\u003eYajima T, Arao M, Yajima K, Takahashi H, Yasuda K: The associations of fat tissue and muscle mass indices with all-cause mortality in patients undergoing hemodialysis. PLoS One. 2019 Feb 13;14(2).\u003c/li\u003e\n\u003cli\u003eChen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS: Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014 Feb;15(2):95-101.\u003c/li\u003e\n\u003cli\u003eBouillanne O, Morineau G, Dupont C, Coulombel I, Vincent JP, Nicolas I: Geriatric Nutritional Risk Index: a new index for evaluating at-risk elderly medical patients. Am J Clin Nutr. 2005 Oct;82(4):777-83.\u003c/li\u003e\n\u003cli\u003eShinzato T, Nakai S, Fujita Y: Determination of Kt/V and protein catabolic rate using pre‒ and post- dialysis blood urea nitrogen concentrations. Nephron 1994; 67: 280‒90.\u003c/li\u003e\n\u003cli\u003eWells JC: Sexual dimorphism of body composition. Best Pract Res Clin Endocrinol Metab. 2007 Sep;21(3):415-30.\u003c/li\u003e\n\u003cli\u003eAllawi AAD: Malnutrition, inflamation and atherosclerosis (MIA syndrome) in patients with end stage renal disease on maintenance hemodialysis (a single centre experience). Diabetes Metab Syndr. 2018 Apr - Jun;12(2):91-97.\u003c/li\u003e\n\u003cli\u003eSchaap LA, Pluijm SM, Deeg DJ, Visser M: Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med. 2006 Jun;119(6):526.e9-17.\u003c/li\u003e\n\u003cli\u003eDiodato MD, Kn\u0026ouml;ferl MW, Schwacha MG, Bland KI, Chaudry IH: Gender differences in the inflammatory response and survival following haemorrhage and subsequent sepsis. Cytokine. 2001 May 7;14(3):162-9.\u003c/li\u003e\n\u003cli\u003eZhang Y, Zitsman JL, Hou J, Fennoy I, Guo K, Feinberg J: Fat cell size and adipokine expression in relation to gender, depot, and metabolic risk factors in morbidly obese adolescents. Obesity (Silver Spring). 2014 Mar;22(3):691-7.\u003c/li\u003e\n\u003cli\u003eMohamed-Ali V, Goodrick S, Bulmer K, Holly JM, Yudkin JS, Coppack SW: Production of soluble tumor necrosis factor receptors by human subcutaneous adipose tissue in vivo. Am J Physiol. 1999 Dec;277(6):E971-5.\u003c/li\u003e\n\u003cli\u003eEriguchi R, Obi Y, Streja E, Tortorici AR, Rhee CM, Soohoo M: Longitudinal Associations among Renal UreaClearance-Corrected Normalized Protein Catabolic Rate, Serum Albumin, and Mortality in Patients on Hemodialysis. Clin J Am Soc Nephrol. 2017 Jul7;12(7):1109-1117. \u003c/li\u003e\n\u003cli\u003eKittiskulnam P, Carrero JJ, Chertow GM, Kaysen GA, Delgado C, Johansen KL: Sarcopenia among patients receiving hemodialysis: weighing the evidence. J Cachexia Sarcopenia Muscle. 2017 Feb;8(1):57-68.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e【Table 1】\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"728\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16.8724%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003eall cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e71.9 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e69.3 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e69.9 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e60.9 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e59.1 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e59.6 (53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e39.1 ( 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e40.9 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e40.4 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eGNRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e98.0 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e99.4 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e99.1 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eHeight (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e1.51 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e1.63 (0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e1.60 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eDry Weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e50.6 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e61.0 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e58.3 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e22.0 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e22.9 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e22.7 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003egrip power (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e7.7 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e15.7 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e13.6 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eECW/TBW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e0.40 (0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e0.39 (0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e0.40 (0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eSMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e5.3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e6.7 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e6.3 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003efat mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e17.7 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e18.0 (8.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e17.9 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003ebody fat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e34.2 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e28.4 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e29.9 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eduration of dialysis (month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e53.3 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e43.6 (37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e46.11 (51.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eCRP (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e0.3 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e0.6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e0.5 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003enPCR (g/kg/day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e0.8 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e0.8 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e0.8 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eAlb (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e3.8 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e3.8 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e3.8 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eMg (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e2.7 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e2.5 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e2.6 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003ecorrected Ca (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e8.8 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e8.6 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e8.6 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eP (mg/dl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e5.2 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e5.4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e5.3 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eCa\u0026times;P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e45.2 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e45.7 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e45.6 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eWhole-PTH (pg/mL)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e113.6 (61.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e141.1 (79.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e134.0 (76.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eKt/V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e1.15 (0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e1.09 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e1.11 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eTG (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e136.0 (80.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e128.4 (93.5)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e130.4 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8724%;\"\u003e\n \u003cp\u003eTcho (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.21262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e175.6 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.085%;\"\u003e\n \u003cp\u003e150.9 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3196%;\"\u003e\n \u003cp\u003e157.3 (33.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4252%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eGNRI: geriatric nutritional risk index\u003c/p\u003e\n\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eECW: extracellular water\u003c/p\u003e\n\u003cp\u003eTBW: total body water\u003c/p\u003e\n\u003cp\u003eSMI: skeletal muscle index\u003c/p\u003e\n\u003cp\u003enPCR: normalized protein catabolic rate\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"hemodialysis, sex differences, SMI, GNRI, grip strength, CRP","lastPublishedDoi":"10.21203/rs.3.rs-6093481/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6093481/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the field of dialysis, studies focusing on sex differences have become increasingly common. However, there are few reports examining whether differences exist between sexes in the association between muscle mass, muscle strength, and nutritional status. This study aimed to investigate the association between muscle mass, muscle strength, and nutrition in dialysis patients, with a specific focus on sex differences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis single-center, retrospective, cross-sectional, and observational study was conducted from October 2018 to February 2019. We enrolled 89 patients undergoing regular hemodialysis (HD) at a single dialysis center (Imus Fujimi General Hospital, Saitama, Japan). The relationship between skeletal muscle index (SMI) measured by bioelectrical impedance analysis (BIA), handgrip strength, and nutritional status as assessed by the geriatric nutritional risk index (GNRI), along with other biochemical parameters, was analyzed separately for men and women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA positive associations was observed between SMI and GNRI (P-for-GNRI \u0026lt; 0.001). In women, the relationship was nonlinear, presenting a U-shaped pattern, although this was not statistically significant (P-for-nonlinear = 0.085). No association was found between SMI and nPCR (P-for-nPCR = 0.628).\u003c/p\u003e\n\u003cp\u003eSMI and CRP showed a significant nonlinear U-shaped relationship (P-for-nonlinear = 0.001). Although a negative associations could not be confirmed, a significant association was observed (P-for-CRP = 0.001). In women, SMI was maintained even at higher CRP levels. GNRI and CRP also exhibited a significant nonlinear U-shaped relationship (P-for-nonlinear = 0.012), with a notable association despite the absence of a clear negative correlation (P-for-CRP = 0.002). In women, GNRI remained preserved even when CRP levels were elevated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn association was found between muscle mass, muscle strength, and nutrition. Women exhibited a nonlinear relationship, distinct from men, suggesting that women may require more robust nutritional management compared to men. Furthermore, the direct association between inflammation and nutrition appeared more prominent in men, whereas the association in women was less distinct. \u0026nbsp;However, the influence of the small sample size of female participants in this study cannot be ruled out, and larger-scale clinical studies are needed.\u003c/p\u003e","manuscriptTitle":"Sex differences in the association between muscle mass or strength and nutrition status in chronic hemodialysis patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 08:09:03","doi":"10.21203/rs.3.rs-6093481/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":"c15ee1c1-4b80-4183-ad57-d7a68dfe24de","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-16T15:58:13+00:00","versionOfRecord":{"articleIdentity":"rs-6093481","link":"https://doi.org/10.1186/s41100-025-00636-5","journal":{"identity":"renal-replacement-therapy","isVorOnly":false,"title":"Renal Replacement Therapy"},"publishedOn":"2025-06-15 15:56:52","publishedOnDateReadable":"June 15th, 2025"},"versionCreatedAt":"2025-04-21 08:09:03","video":"","vorDoi":"10.1186/s41100-025-00636-5","vorDoiUrl":"https://doi.org/10.1186/s41100-025-00636-5","workflowStages":[]},"version":"v1","identity":"rs-6093481","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6093481","identity":"rs-6093481","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}