Exploring the role of iron accumulation and muscle parameters as potential risk factors for sarcopenia

Exploring the role of iron accumulation and muscle parameters as potential risk factors for sarcopenia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring the role of iron accumulation and muscle parameters as potential risk factors for sarcopenia Mahamane Rahoufou Tounaoua, Zakari Shaibu, Zhao Guo-yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6176003/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The link between iron accumulation and sarcopenia has become an increasingly important topic in aging and metabolic research. While there is a growing body of literature on this subject, the relationship remains poorly understood. Consequently, this study aims to explore the risk factors associated with sarcopenia by examining iron status through various iron biomarkers in conjunction with skeletal muscle parameters in individuals aged 60 to 80 years. In addition, we examine inflammation and physical performance as secondary risk factors that may contribute to sarcopenia in relation to iron status. Methods : We conducted a cross-sectional study using data collected during the year 2022–2023 from the affiliated hospital of Jiangsu University. Iron status was assessed using serum iron, serum ferritin, transferrin, total iron-binding capacity (TIBC), transferrin saturation. Skeletal muscle health was evaluated through measurements of total skeletal muscle mass (SMM), skeletal muscle index (SMI), body mass index (BMI) and both trunk and limb muscle mass. Inflammation was assessed by C-reactive protein (CRP) levels and white blood cell count. Physical performance was evaluated using handgrip strength and gait speed. Univariate and multivariate regression analyses were performed to explore the associations between these factors and sarcopenia. Results : A total of 102 participants were included. Significant associations were found between sarcopenia and several variables. Higher BMI and SMI were consistently protective against sarcopenia in both univariate and multivariate models (p < 0.05). Interestingly, the comparison Table 2 showed that CRP levels were significantly higher in participants with sarcopenia (1.7 ± 1.3 vs. 1.0 ± 0.7, p = 0.002), which aligns with the conventional understanding of inflammation's role in muscle degradation. However, it exhibited a paradoxical relationship, with higher levels linked to a lower risk of sarcopenia in both models. In the univariate regression, the odds ratio (OR) for CRP was 0.45 (95% CI: 0.25–0.84, p = 0.012), while in the multivariate regression, the OR was 0.51 (95% CI: 0.27–0.96, p = 0.037) This counterintuitive relationship suggests that further investigation into CRP's role in sarcopenia is needed. SMM and Weight showed a significant association in univariate regression (OR = 0.87, 95% CI: 0.79–0.95, p < 0.003) and (OR = 0.82, 95% CI: 0.75–0.90, p < 0.001) respectively. Although higher ferritin levels showed no significant association in the univariate analysis (p = 0.301), they were significantly associated with a slight increase in sarcopenia risk in the multivariate model (OR = 1.01[1.00; 1.02], P = 0.009). However, this finding requires further investigation. Other variables such age, transferrin did not show statistically significant associations with sarcopenia. Physical performance, measured by handgrips and gait speed, was assessed but not analyzed for statistical significance. Conclusion : These findings highlight the protective roles of BMI and SMI in reducing the risk of sarcopenia, while revealing the unexpected protective effect shown by CRP, challenging the traditional view of inflammation as a risk factor for sarcopenia and highlighting the complexity of its role in muscle health. Further research is needed to clarify the mechanisms underlying this relationship. Ferritin, an indicator of iron stores, showed a slight positive association with sarcopenia, suggesting that higher ferritin levels may marginally increase the risk, though this effect is small and warrants further investigation, especially after controlling for potential confounders. Although physical performance was measured, its role in sarcopenia was not a focus of this study. Iron muscle atrophy skeletal muscle ferritin sarcopenia Figures Figure 1 Figure 2 Introduction Sarcopenia is a progressive condition characterized by the loss of skeletal muscle mass, strength, and function due to aging. The Asian Working Group for Sarcopenia describes it as a geriatric syndrome involving the decline of muscle with age, alongside low muscle strength or poor physical performance (1). The European Working Group for Sarcopenia in Older People (EWGSOP) similarly defines sarcopenia as muscle atrophy combined with muscle weakness (measured by hand-grip strength) and/or reduced physical capacity, assessed via gait speed (2). An updated consensus (EWGSOP2) frames sarcopenia as a “muscle disease” linked to long-term changes in muscle health, with classifications ranging from probable sarcopenia (low muscle strength) to severe sarcopenia (low muscle strength and quantity/quality) (3). This phenomenon contributes nowadays to frailty, and increased risk of hospitalization with adverse outcomes such as physical disability, poor quality of life, a higher risk of falls and fractures and even death. Epidemiological surveys have shown that the incidence of sarcopenia ranges from 5–13% in people aged 60 and older, with the estimates increasing to 11–50% in people ages 80 and older (4). Furthermore, the prevalence of sarcopenia may be as high as 24% in patients aged 65 to 70, with older adults losing up to 15% of their total muscle mass during their 7th and 8th decade of life (5). The incidence of sarcopenia is predicted to increase to more than 200 million cases over the next 40 years worldwide (6), highlighting the urgency for understanding the associated biological mechanism, and developing effective interventions. Similarly, Kumari et al. (7) reported that more than 50 million people worldwide experience sarcopenia, and it is estimated that over 200 million people will suffer sarcopenia in the next four decades. Consequently, it has emerged as a significant health concern, placing a substantial burden at both patient and societal levels. Hence, early screening, prevention, and identification of the cause and associated risk factors of sarcopenia are essential, not only for timely intervention but also to improve the patients’ prognosis. Contributing factors of sarcopenia are multiple, involving a complex interplay of aging processes, genetic factors, hormonal changes, inflammation, and lifestyle factors such as reduced physical activity, and inadequate nutrition (8, 9). Recently, there has been a notable interest in skeletal muscles in the context of iron metabolism, as they contain 10–15% of iron in the body (10, 11). Some studies (12–14) demonstrated the impact of iron deficiency in skeletal muscles on the incidence of sarcopenia, while little is known about the impact of iron accumulation in skeletal muscle and how it may contribute to sarcopenia. Iron is a vital mineral necessary for many physiological functions, including oxygen transport, DNA synthesis, energy production, oxidative metabolism, and cellular immune response (15, 16). Its metabolism refers to the processes by which the body absorbs, transports, stores, and utilizes it. The human body tightly regulates iron metabolism to balance its need while preventing both iron deficiency and iron excess, therefore, proper regulation of iron levels is crucial. Although the absorption of iron dietary (1-2mg/d) is tightly regulated and balanced with losses and excess, the initial turnover of iron is essential to meet the requirement for erythropoietic (20-30mg/d) (17). Evidence indicates that increased iron requirement limits external supply whereas increased blood iron may lead to iron deficiency (ID) and iron deficiency anemia (17). On the other hand, excess of iron in any tissue may induce oxidative stress and impair tissue function. In the skeletal muscle, oxidative stress not only causes muscle damage but also negatively impacts its endocrine function (18), and oxidative stress occurs when there’s an imbalance between the production of reactive oxygen species (ROS) and the body’s ability to detoxify these reactive intermediates or repair the resulting damage. Iron excess has been proposed as an essential factor in skeletal muscle wasting. Studies have reported correlations between muscle iron accumulation and atrophy, either through ageing or by using experimental models of secondary iron accumulation (19). Both excess and deficiency of iron have been associated with sarcopenia (6, 20), underscoring the importance of maintaining iron homeostasis to prevent muscle deterioration. While factors like aging, inactivity, and iron metabolism have been identified as influencing sarcopenia, the evidence remains inconclusive. For instance, an observational study (21) showed that patients with sarcopenia had significantly lower serum iron levels compared to those without sarcopenia. Few clinical studies have suggested a relationship between iron accumulation and sarcopenia, evidence of causality in cohort studies is still lacking (22). Additionally, some studies have suggested that abnormalities in iron metabolism may affect the balance of muscle protein synthesis and degradation, further exacerbating the progression of sarcopenia (23). Therefore, timely intervention and enhanced patient outcomes depend on the early detection and assessment of risk factors for sarcopenia. On this matter, extensive research has been conducted on the effects of iron accumulation and iron deficiency on sarcopenia (20, 24). A key aspect of the research was using iron levels as a continuous variable to examine how different levels of iron may affect sarcopenia. To fill this gap, our study intends to explore the connection between iron accumulation and the risk of sarcopenia by including various iron indicators, with primary focus on ferritin, alongside skeletal muscle indexes such as SMI and BMI, while also considering CRP as a marker for inflammation. Materials and method A cross-sectional study was conducted using data collected between the years 2022-2023 at the affiliated hospital of Jiangsu University. Patients’ data including serum ferritin, serum iron, transferrin, total iron binding capacity, transferrin saturation, CRP, white blood cells count, were extracted and analyzed, combined with muscles indexes such as Total skeletal muscle mass (SMM), Skeletal Muscle Index (SMI), and both trunk and limbs muscle mass as shown in Table 1. Laboratory method-Blood indicators Hematologic indicators, especially hemoglobin, are commonly measured in clinics and laboratories using flow cytometry with fully automated cell counters, due to their precision (25). In this study, serum ferritin and transferrin were measured using immunoassay, whereas serum iron, TIBC were measured using colorimetric reaction with ferrozine as a chromogen to form a color complex with iron. On the other hand, CRP, WBC were obtained via a cellometer ascend automated cell counter machine, a benchtop instrument offering fast and reliable cell counts with small volumes. It is worth noting that blood samples from all subjects were collected in the early morning while fasting. Anthropometric measurements We used human body composition analyzer model TANITA(ME180), and Electrochemiluminescence immunoassay combined with BIA (bioelectrical impedance analysis), which are considered the reference and most frequently used tools for assessing skeletal muscle mass. Thus, we measured the SMM via BIA method, and then we calculated the SMI using the following formula: SMI = SMM/Height 2 . BMI was calculated as weight(kg) divided by height 2 (m). The height and weight were measured according to the standard protocol, using a fixed stadiometer and digital scale. Physical performance At this level, we assessed handgrip strength and gait speed. For handgrip strength, the maximum strength of the dominant hand was measured for each participant, using a hand dynamometer while sitting with elbow at a 90-degree angle and forearm resting on a stable surface. A minimum of three trials were conducted and the highest reading was recorded. Speed gait measurements were taken at least twice following a six-meter (6-m) walk at a steady and consistent pace, with the average value calculated from the results. Table 1: Demographics Participants (102) Number (%) Mean±SD Median (IQR) Male 31(30.4%) -- -- Female 71(69.6%) -- -- Sarcopenia (Yes) 27(26.5%) -- -- Sarcopenia (No) 75(73.5%) -- -- Age (years) 65.5±5.2 65.0(8.0) Height (meters) 1.6±0.1 1.6(0.1) Weight (kg) 61.4±9.1 60.4(14.5) BMI 23.5±2.9 23.5(3.8) Serum Iron 22.5±15.8 20.2(6.6) Ferritin 166.7±106.8 145.9(87.4) Transferrin 2.9±0.4 2.9(0.5) Total iron binding cells (TIBC) 60.1±7.0 60.4(8.7) Transferrin saturation 35.5±9.9 34(12.2) CRP 1.5±1.2 1.2(1.1) White blood cells 5.7±2.0 5.4(1.7) SMI 6.6±1.1 6.4(1.0) Skeletal muscle mass (SMM) 38.6±6.4 37.7(7.6) Abbreviations : SD=Standard Deviation; IQR= Interquartile Range Table 2 presents a comparison of various variables, including weight, BMI, CRP, SMI, and SMM, between participants with and without sarcopenia. The comparison revealed several statistically significant differences: Weight was significantly higher in participants with sarcopenia (64.1 ± 8.6) compared to those without sarcopenia (54.0 ± 5.8, p < 0.001), and BMI was significantly higher in participants with sarcopenia (24.4 ± 2.6) compared to those without sarcopenia (21.0 ± 1.8, p < 0.001). CRP levels were significantly higher in participants with sarcopenia (1.7 ± 1.3) compared to those without sarcopenia (1.0 ± 0.7, p = 0.002). SMI was significantly higher in participants with sarcopenia (6.8 ± 1.1) compared to those without sarcopenia (5.9 ± 0.7, p < 0.001), and SMM was significantly higher in participants with sarcopenia (39.8 ± 6.4) compared to those without sarcopenia (35.3 ± 5.0, p = 0.005). No significant differences were found for the remaining variables. Table 2. Comparison of the iron-related makers and muscle parameters between participants with sarcopenia and those without With Sarcopenia (27) Without Sarcopenia (75) p-value Male (Number) 9 22 0.886 Female (Number) 18 53 Age (years) Mean±SD 65.1±5.1 66.4±5.4 0.304 Height (meters) Mean±SD 1.6±0.1 1.6±0.1 0.226 Weight (kg) Mean±SD 64.1±8.6 54.0±5.8 <0.001* BMI (kg/m 2 ) Mean±SD 24.4±2.6 21.0±1.8 <0.001* Serum Iron (micromol/l) Mean±SD 21.1±5.9 20.9±4.8 0.934 Ferritin (ng/ml) Mean±SD 160.1±96.8 185.1±130.9 0.695 Transferrin (g/l) Mean±SD 3.0±0.4 2.9±0.3 0.774 Total iron binding capacity (TIBC) (micromol/l) Mean±SD 60.3±7.3 59.4±6.2 0.701 Transferrin saturation (%) Mean±SD 35.5±10.3 35.6±8.6 0.845 CRP (mg/dl) Mean±SD 1.7±1.3 1.0±0.7 0.002* White blood cells (cells/microliter) Mean±SD 5.6±1.6 5.6±1.7 0.934 SMI (kg/m2) Mean±SD 6.8±1.1 5.9±0.7 <0.001* Total skeletal muscle mass (kg) Mean±SD 39.8±6.4 35.3±5.0 0.005* *Statistically significant difference at 5% level Study population The study focused on participants aged 60 and above, with complete data on specified variables, and who provided informed consent, while excluding individuals with chronic illnesses such as (liver disease, kidney disease, rheumatoid disease, endocrine system disease, chronic inflammatory diseases, and similar conditions), malignant or hematological disease, muscle disease under drug effect, recent blood transfusions, as well as those with missing data. Moreover, the study exclusively gathered clinical data from patients without altering their treatment plans, ensuring any potential physiological risks are mitigated. The researchers involved in this process took extensive measures to safeguard the confidentiality of patient information. Additionally, the study followed ethical protocols and guidelines for research involving human subjects. This study has been reviewed and approved by the Biomedical Research Ethics Committee of the Affiliated Hospital of Jiangsu University (SWYXLL20210401-16). Statistical analysis The statistical analysis was conducted using IBM SPSS Statistics software version 28. Descriptive statistics, such as mean and standard deviation, were calculated for continuous variables, while frequencies and percentages were determined for categorical variables. To compare iron-related markers and muscle parameters between the two groups (with and without sarcopenia), Mann Whitney U test was performed for continuous variables, and the chi-square test was used to compare the distribution for the categorical variables. To explore the relationship between various factors and the risk of sarcopenia, both univariate and multivariate regression analyses were employed. The univariate analysis allowed for the identification of individual associations between each variable and sarcopenia, while the multivariate analysis provided a more comprehensive understanding by adjusting for potential confounders, enabling the assessment of independent associations. In this study, the multivariate analysis was performed using a backward stepwise variable selection, i.e. a process where we begin with a model that contains all variables under consideration (called the full model), and then we remove the least significant variables one after the other. Throughout this study, the statistical significance level was set at a p-value of less than 0.05. Results This cross-sectional study was carried out at the affiliated hospital of Jiangsu University from October 2022 to December 2023, involving 102 participants, of whom 31 (30.4%) were males and 71 (69.6%) females (see Figure 1). The median age is 65 years as shown in Table 1. Sarcopenia was present in 27 (26.5%) of all patients, while 75 (73.5%) of the population was free of sarcopenia. A comparative analysis of participants with and without sarcopenia was also performed, and the results are presented in Table 2. Furthermore, Figure 2 provided an overview of the distribution of some variables, namely BMI, SMI, CRF and Ferritin between two groups. To investigate the relationship between various factors and the risk of sarcopenia, both univariate and multivariate regression analyses were performed. The univariate regression analysis revealed several significant associations between variables and the risk of sarcopenia. Key findings include (i) higher BMI was strongly protective against sarcopenia (OR = 0.49 [0.36; 0.67], p < 0.05); (ii) higher SMI was significantly associated with a reduced risk of sarcopenia (OR = 0.18 [0.08; 0.43], p < 0.05); (iii) higher SMM was protective against sarcopenia (OR = 0.87 [0.79; 0.95], p < 0.05); (iv) higher weight was associated with a lower risk of sarcopenia (OR = 0.82 [0.75; 0.90], p < 0.05). Ferritin has no significant association with sarcopenia (p = 0.301). Interestingly, as shown in Table 2, the comparison table revealed that CRP levels were significantly higher in participants with sarcopenia (mean = 1.7 ± 1.3) compared to those without sarcopenia (mean = 1.0 ± 0.7, p = 0.002), suggesting an association between increased CRP and the presence of sarcopenia. However, surprisingly, in the regression analysis, higher CRP levels were associated with a lower risk of sarcopenia (OR = 0.45 [0.25; 0.84], p < 0.05), which contrasts with the typical understanding of inflammation being detrimental to muscle health. This discrepancy suggests that acute inflammation, as reflected by CRP, might play a protective role in muscle preservation, though further investigation is required. No significant statistical associations were found for the other variables. Using backward stepwise variable selection (defined in the section “Statistical Analysis”), we perform a Multivariate Regression Analysis, adjusting for potential confounders, and several variables remained significantly associated with sarcopenia. For BMI the protective effect, observed in the univariate analysis, remained significant (OR = 0.52 [0.37; 0.74], p < 0.05). Although not significant in the univariate analysis, Ferritin showed a modest increase in sarcopenia risk in the multivariate model (OR = 1.01 [1.00; 1.02], p = 0.009). Like in the univariate analysis, higher CRP levels linked to a lower risk of sarcopenia OR = 0.51 [0.27; 0.96], p = 0.05). SMI also continued to show a strong protective effect against sarcopenia (OR = 0.18 [0.06; 0.62], p = 0.006). Although handgrip strength and gait speed were measured as part of the study to assess physical performance, these variables were not included in the statistical analysis and did not contribute to the final findings. The full regression result, including odds ratios, confidence intervals, and p-values for all variables, were presented in Table 3 and Table 4. Table 3. Potential risk factors for sarcopenia using univariate logistic regression models. Variables Univariate Analysis p-value OR (95%CI) Gender (Male vs Female) 0.920 0.95 [0.36; 2.49] Age 0.257 1.05 [0.97; 1.14] Height 0.220 0.01 [0.0; 15.36] Weight <0.001* 0.82 [0.75; 0.90] BMI <0.001* 0.49 [0.36; 0.67] Serum iron Fe 0.581 0.99 [0.94; 1.04] Ferritin 0.301 1.00 [1.00; 1.01] Transferrin 0.467 0.65 [0.20; 2.08] Total iron binding cells (TIBC) 0.550 0.98 [0.92; 1.05] Transferrin saturation 0.983 1.00 [0.96; 1.05] CRP 0.012* 0.45 [0.25; 0.84] White blood cells 0.499 1.08 [0.87; 1.33] SMI <0.001* 0.18 [0.08; 0.43] Appendicular muscle mass 0.003* 0.87 [0.79; 0.95] Abbreviation: OR=Odd Ratio; CI = Confidence Interval *Statistically significant at 5% level (p-value < 0.05) Table 3 presents the results of the univariate logistic regression analysis to identify potential risk factors for sarcopenia. The analysis reveals several significant variables, including BMI, SMI, and CRP, which are associated with the risk of sarcopenia. Non-significant associations were observed for ferritin and other factors Table 4. Potential risk factors for sarcopenia using a multivariate logistic regression model. Variables Multivariate Analysis p-value OR (95%CI) BMI <0.001* 0.52 [0.37; 0.74] Ferritin 0.009* 1.01 [1.0; 1.02] C-reactive protein (CRP) 0.037* 0.51 [0.27; 0.96] SMI 0.006* 0.18 [0.06; 0.62] Abbreviation: OR=Odd Ratio; CI = Confidence Interval *Statistically significant at 5% level (p-value < 0.05) Table 4 shows the results of the multivariate logistic regression analysis, which adjusted for potential confounders. This analysis identified BMI, CRP, and SMI as significant factors associated with the risk of sarcopenia, while ferritin showed a modest effect in the multivariate model. These findings suggest that muscle mass (SMI) and inflammatory markers (CRP) are strong predictors of sarcopenia risk Discussion Recent research has increasingly focused on the potential connection between iron accumulation and sarcopenia (21, 22, 26). In this study, we aimed to explore the relationship between iron accumulation, as measured by ferritin and other iron indicators, and muscle health, assessed through skeletal muscle indexes (such as BMI, SMM, and SMI), in the context of sarcopenia risk. Sarcopenia refers to the loss of muscle mass, strength, and function that occurs with aging, primarily impacting older adults and leading to increased frailty, reduced mobility, and greater risk of falls (27). Muscle mass loss, a key indicator of sarcopenia, is linked to a higher risk of fractures, compromised physical function and a decline in quality of life (1) . One increasingly investigated factor is iron accumulation and its role in promoting muscle degeneration. Iron is essential for numerous biological processes, including enzymatic activity, mitochondrial function, DNA synthesis, and energy metabolism (28-30). Its dysregulation, particularly in aging, can lead to detrimental effects on health. While the liver and spleen store most of the body’s iron, skeletal muscle also contains smaller amounts, and excessive iron or iron accumulation, could potentially have adverse effects on skeletal muscle health (19, 31) Unlike many other minerals, the body has no active mechanism to eliminate excess iron (32). Small amounts are lost daily through shedding of intestinal cells, sweat, and in women menstrual blood loss (33). However, as people age, iron accumulates due to the lack of an effective excretory pathway, which can lead to the onset of various diseases (34). Despite notable progress in deciphering the etiology of sarcopenia (35, 36), the connection between iron status and sarcopenia is still not well understood. In this context, our analysis revealed that higher levels of ferritin were associated with an increased risk of sarcopenia, while elevated muscle indexes such as SMM, weight, SMI and BMI were protective factors, with SMI and BMI consistently showing a protective effect. These findings are consistent with previous studies that have suggested a relationship between serum ferritin and sarcopenia as well as the role of BMI. For instance, a cohort study involving 639 hospitalized elderly individuals showed significantly higher serum ferritin levels in the sarcopenia group compared to healthy controls, with levels exceeding the normal range (>145 ug/dl) in sarcopenic patients (37). Similarly, a study in 2014 (38), involving 1380 middle-aged and elderly Korean women, discovered that individuals with sarcopenia exhibited significantly higher serum ferritin levels, with those having elevated serum ferritin facing a 2.02-fold increased risk compared to those with normal levels. As mentioned above, our study found that higher BMI was an important variable and acted as a protective factor against sarcopenia. Moroni et al. (39) supported this finding, reporting that, according to random forest analysis, a higher BMI was the most important protective factor for sarcopenia, for sarcopenic obesity (along with Iron) and for osteosarcopenia (along with albumin). Moreover, Sung Jing Moon et al. (40) found that the mean age, the body mass index (BMI), and HOMA-IR were higher and caloric intake, physical activity, and vitamin D level were lower in the sarcopenia groups in both men and women. Altun et al. (41), and Jung et al. (42) observed notably higher non-heme iron levels in the skeletal muscles of elderly rats, while Xu et al. (43) suggested that iron accumulation could be a characteristic feature of aging skeletal muscles. In the same context, some clinical investigations have highlighted a notable link between iron accumulation and sarcopenia. For example, Marzetti et al. (44) reported that iron accumulation in skeletal muscle has been suggested to contribute to the pathogenesis of sarcopenia and acute muscle atrophy. Additionally, in 2017, a study of 639 Italians aged 65 and above found increased serum ferritin levels in sarcopenic patients along with elevated serum inflammatory markers (37). However, contrary to our findings and some supportive studies, Zhi Chen et al. also observed a negative correlation between serum ferritin and muscle mass, even after adjusting for potential confounder (26). Similarly, a 2016 study of 300 hemodialysis patients revealed a significant negative correlation between forearm grip strength and serum ferritin levels (45). Bartali et al. (46), in a longitudinal study involving 698 participants, did not also find a significant association between serum iron levels and physical function, possibly due to differences in study design or participant characteristics. While some studies have shown that inflammation is associated with an increased risk of sarcopenia (47, 48), in our study, Table 2 showed also that CRP levels were significantly higher in participants with sarcopenia. However, both univariate and multivariate regression analyses revealed a paradoxical relationship, where higher CRP levels were associated with a reduced risk of sarcopenia. This contrasts with typical associations between chronic inflammation and muscle loss. Other studies, however, have reported no significant association between inflammatory markers and sarcopenia (49-51), suggesting that the role of inflammation in sarcopenia might be more complex than previously understood. This unexpected finding may indicate that the nature and duration of inflammation influence muscle health differently. For instance, acute or transient inflammatory responses could have a distinct impact compared to chronic inflammation, potentially offering a protective effect. Given this, further investigation is needed to explore how different types of inflammation contribute to muscle health and sarcopenia risk. Future research should consider examining inflammation over time, rather than just at a single point, to better understand its long-term effects on muscle mass. Additionally, intervention studies assessing the role of inflammation modulation or iron chelation in preventing or treating sarcopenia could provide valuable insights into potential therapeutic strategies. Although our study focused primarily on iron biomarkers and muscle mass indicators, we also collected data on physical performance using handgrip strength and gait speed, both of which are widely recognized as important functional measures in sarcopenia research (52-54). However, these variables were not included in our statistical analysis, as the scope of this study was primarily concerned with iron biomarkers and muscle mass indicators. It is possible that handgrip strength and gait speed could offer further insights into the functional consequences of iron accumulation in sarcopenia, and future research with a larger sample size or a more focused analysis on functional outcomes may reveal important relationships. Understanding the broader implications of iron metabolism on sarcopenia is crucial, future studies should incorporate this aspect to better assess the role of iron in muscle health. Moreover, our study did not explore how changes in physical performance over time might interact with iron metabolism. Given the well-established role of handgrip strength and gait speed in predicting sarcopenia risk, longitudinal studies incorporating these measures would be valuable in determining the temporal relationship between iron accumulation and muscle function. The association between higher ferritin levels and sarcopenia risk could be explained by the role of iron in inflammatory processes. Elevated ferritin is often a marker of chronic inflammation, which is known to accelerate muscle wasting (55, 56). Additionally, iron accumulation in tissues may lead to oxidative stress, further contributing to muscle degradation. Although ferritin levels have been associated with sarcopenia, the nature of this relationship (whether higher iron stores contribute to or protect against sarcopenia) remains unclear. These findings suggest that ferritin may not only reflect iron status but also serve as a marker for inflammatory and oxidative processes that promote sarcopenia. Given that the role of iron status (ferritin) in sarcopenia is not yet fully understood, further research is needed. On the other hand, our findings emphasize the importance of maintaining higher BMI and skeletal muscle mass (SMI) in older adults to reduce the risk of sarcopenia, and suggest that iron status, muscle mass, and BMI should be considered when developing interventions for sarcopenia, particularly in aging populations. These findings have clinical implications, suggesting that ferritin could be a potential marker for sarcopenia risk if further validated in future studies. Monitoring ferritin alongside other muscle health indicators could help guide early interventions, especially in older adults. However, additional research into the role of iron metabolism in sarcopenia is needed, particularly to understand how ferritin and other iron biomarkers contribute to detecting muscle loss. Long-term studies are essential to establish causal relationships between iron accumulation and sarcopenia, and to explore interventions targeting iron metabolism, such as iron chelation therapy or supplementation. Strengths and Limitations One strength of this study is the use of multiple iron biomarkers to assess iron accumulation, providing a comprehensive view of iron status. However, there are several limitations that should be considered when interpreting the findings. This study is cross-sectional, meaning that it can identify associations but not establish causality. Longitudinal studies are needed to clarify the temporal relationships between iron status, muscle mass, and sarcopenia. While the study controlled for several demographic and health-related variables, lifestyle factors such as physical activity and dietary intake, as well as comorbid conditions, could influence both inflammation markers and muscle health. It is important to consider these confounding factors in future research to better isolate the impact of iron metabolism on sarcopenia. Moreover, the small sample size in this study is another limitation that may impact the generalizability of the findings. Future research with a larger, more diverse sample is recommended to validate and provide a more robust understanding of the topic. Conclusion This study provides new insights into the relationship between iron accumulation and sarcopenia risk, with ferritin emerging as a potential biomarker for identifying at-risk populations. While significant associations were observed between BMI, SMI, and ferritin with sarcopenia in older adults, the complexity of these relationships highlights the need for further investigation. Notably, our findings also revealed a paradoxical association between CRP levels and sarcopenia risk, which warrants additional exploration. Future research should focus on validating these findings across different populations and exploring potential therapeutic interventions. Understanding how factors like iron status and inflammation interact with muscle health could pave the way for more effective strategies to prevent or treat sarcopenia in aging populations. Declarations Ethical Approval and consent to participate This study was reviewed and approved by the Biomedical Research Ethics Committee of the Affiliate Hospital of Jiangsu University (SWYXLL20210401-16). All participants in this study provided written informed consent. Acknowledgements We acknowledge all individuals who supported and encouraged us during the preparation of this manuscript. Your support has been greatly appreciated. Funding information This work was supported by Scientific Research Project of Jiangsu Provincial Health Committee (M2022119) and Young and Middle-aged Doctors Training Project of Excellent Talent for Osteoporosis and Bone Mineral Disease (G-X-2019-1107). Authors Contributions Tounaoua Mahamane Rahoufou conceptualized the study, analyzed the data, and wrote the manuscript, Zakari Shaibu evaluated the data and edited the manuscript accordingly, and Guoyang Zhao supervised and edited this study. All authors contributed to the writing and reviewing of the manuscript. Availability of data and materials Data are available from the corresponding author upon reasonable request. Consent for publication All authors provided consent for publication. Conflict of interest None. References Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15(2):95-101. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age and ageing. 2010;39(4):412-23. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age and ageing. 2019;48(1):16-31. von Haehling S, Morley JE, Anker SD. An overview of sarcopenia: facts and numbers on prevalence and clinical impact. Journal of cachexia, sarcopenia and muscle. 2010;1(2):129-33. Han A, Bokshan SL, Marcaccio SE, DePasse JM, Daniels AH. Diagnostic Criteria and Clinical Outcomes in Sarcopenia Research: A Literature Review. Journal of clinical medicine. 2018;7(4). Alves FM, Ayton S, Bush AI, Lynch GS, Koopman R. Age-Related Changes in Skeletal Muscle Iron Homeostasis. The journals of gerontology Series A, Biological sciences and medical sciences. 2023;78(1):16-24. Kumari M, Khanna A. Prevalence of Sarcopenic Obesity in Various Comorbidities, Diagnostic Markers, and Therapeutic Approaches: A Review. Annals of geriatric medicine and research. 2022;26(4):296-308. Aslam MA, Ma EB, Huh JY. Pathophysiology of sarcopenia: Genetic factors and their interplay with environmental factors. Metabolism. 2023;149:155711. Robinson SM, Reginster JY, Rizzoli R, Shaw SC, Kanis JA, Bautmans I, et al. Does nutrition play a role in the prevention and management of sarcopenia? Clinical nutrition (Edinburgh, Scotland). 2018;37(4):1121-32. Boulton FE. The myoglobin content of human skeletal muscle. British journal of haematology. 1973;25(2):281. Robach P, Cairo G, Gelfi C, Bernuzzi F, Pilegaard H, Viganò A, et al. Strong iron demand during hypoxia-induced erythropoiesis is associated with down-regulation of iron-related proteins and myoglobin in human skeletal muscle. Blood. 2007;109(11):4724-31. Stugiewicz M, Tkaczyszyn M, Kasztura M, Banasiak W, Ponikowski P, Jankowska EA. The influence of iron deficiency on the functioning of skeletal muscles: experimental evidence and clinical implications. European journal of heart failure. 2016;18(7):762-73. Dziegala M, Josiak K, Kasztura M, Kobak K, von Haehling S, Banasiak W, et al. Iron deficiency as energetic insult to skeletal muscle in chronic diseases. Journal of cachexia, sarcopenia and muscle. 2018;9(5):802-15. Xu B, Guo Z, Jiang B, Zhang K, Zhu W, Lian X, et al. Factors affecting sarcopenia in older patients with chronic diseases. Annals of palliative medicine. 2022;11(3):972-83. Roemhild K, von Maltzahn F, Weiskirchen R, Knüchel R, von Stillfried S, Lammers T. Iron metabolism: pathophysiology and pharmacology. Trends Pharmacol Sci. 2021;42(8):640-56. Abbaspour N, Hurrell R, Kelishadi R. Review on iron and its importance for human health. Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences. 2014;19(2):164-74. Muñoz M, Villar I, García-Erce JA. An update on iron physiology. World journal of gastroenterology. 2009;15(37):4617-26. Halon-Golabek M, Borkowska A, Herman-Antosiewicz A, Antosiewicz J. Iron Metabolism of the Skeletal Muscle and Neurodegeneration. Frontiers in neuroscience. 2019;13:165. Martin D, Nay K, Robin F, Rebillard A, Orfila L, Martin B, et al. Oxidative and glycolytic skeletal muscles deploy protective mechanisms to avoid atrophy under pathophysiological iron overload. Journal of cachexia, sarcopenia and muscle. 2022;13(2):1250-61. Dugan C, Cabolis K, Miles LF, Richards T. Systematic review and meta-analysis of intravenous iron therapy for adults with non-anaemic iron deficiency: An abridged Cochrane review. Journal of cachexia, sarcopenia and muscle. 2022;13(6):2637-49. Huang M, Xu B, Xu Y, Zhang K, Zhu W, Lian X, et al. Serum iron level is independently associated with sarcopenia: a retrospective study. Scientific Reports. 2024;14(1):10554. Zhao G. Is Iron Accumulation a Possible Risk Factor for Sarcopenia? Biological trace element research. 2018;186(2):379-83. Peterson MD, Rhea MR, Sen A, Gordon PM. Resistance exercise for muscular strength in older adults: a meta-analysis. Ageing research reviews. 2010;9(3):226-37. Kohgo Y, Ikuta K, Ohtake T, Torimoto Y, Kato J. Body iron metabolism and pathophysiology of iron overload. International journal of hematology. 2008;88(1):7-15. Pfeiffer CM, Looker AC. Laboratory methodologies for indicators of iron status: strengths, limitations, and analytical challenges. The American journal of clinical nutrition. 2017;106(Suppl 6):1606s-14s. Chen Z, Chen J, Song C, Sun J, Liu W. Association Between Serum Iron Status and Muscle Mass in Adults: Results From NHANES 2015-2018. Frontiers in nutrition. 2022;9:941093. Fielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, et al. Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. 2011;12(4):249-56. Teh MR, Armitage AE, Drakesmith H. Why cells need iron: a compendium of iron utilisation. Trends in Endocrinology & Metabolism. 2024. Jing X, Du T, Li T, Yang X, Wang G, Liu X, et al. The detrimental effect of iron on OA chondrocytes: Importance of pro-inflammatory cytokines induced iron influx and oxidative stress. Journal of cellular and molecular medicine. 2021;25(12):5671-80. Katsura Y, Ohara T, Noma K, Ninomiya T, Kashima H, Kato T, et al. A Novel Combination Cancer Therapy with Iron Chelator Targeting Cancer Stem Cells via Suppressing Stemness. Cancers. 2019;11(2). Nishikawa H, Asai A, Fukunishi S, Nishiguchi S, Higuchi K. Metabolic Syndrome and Sarcopenia. Nutrients. 2021;13(10). Wallace DF. The Regulation of Iron Absorption and Homeostasis. The Clinical biochemist Reviews. 2016;37(2):51-62. Ems T, St Lucia K, Huecker MR. Biochemistry, Iron Absorption. StatPearls. Treasure Island (FL) ineligible companies. Disclosure: Kayla St Lucia declares no relevant financial relationships with ineligible companies. Disclosure: Martin Huecker declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright © 2025, StatPearls Publishing LLC.; 2025. Mangan D. Iron: an underrated factor in aging. Aging. 2021;13(19):23407-15. Rolland Y, Czerwinski S, Abellan Van Kan G, Morley JE, Cesari M, Onder G, et al. Sarcopenia: its assessment, etiology, pathogenesis, consequences and future perspectives. The journal of nutrition, health & aging. 2008;12(7):433-50. Lang T, Streeper T, Cawthon P, Baldwin K, Taaffe DR, Harris TB. Sarcopenia: etiology, clinical consequences, intervention, and assessment. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2010;21(4):543-59. Perna S, Peroni G, Faliva MA, Bartolo A, Naso M, Miccono A, et al. Sarcopenia and sarcopenic obesity in comparison: prevalence, metabolic profile, and key differences. A cross-sectional study in Italian hospitalized elderly. Aging clinical and experimental research. 2017;29(6):1249-58. Kim TH, Hwang HJ, Kim SH. Relationship between serum ferritin levels and sarcopenia in Korean females aged 60 years and older using the fourth Korea National Health and Nutrition Examination Survey (KNHANES IV-2, 3), 2008-2009. PloS one. 2014;9(2):e90105. Moroni A, Perna S, Azzolino D, Gasparri C, Zupo R, Micheletti Cremasco M, et al. Discovering the Individualized Factors Associated with Sarcopenia and Sarcopenic Obesity Phenotypes—A Machine Learning Approach. 2023;15(21):4536. Moon SJ, Kim TH, Yoon SY, Chung JH, Hwang HJ. Relationship between Stage of Chronic Kidney Disease and Sarcopenia in Korean Aged 40 Years and Older Using the Korea National Health and Nutrition Examination Surveys (KNHANES IV-2, 3, and V-1, 2), 2008-2011. PloS one. 2015;10(6):e0130740. Altun M, Edström E, Spooner E, Flores-Moralez A, Bergman E, Tollet-Egnell P, et al. Iron load and redox stress in skeletal muscle of aged rats. Muscle & nerve. 2007;36(2):223-33. Jung SH, DeRuisseau LR, Kavazis AN, DeRuisseau KC. Plantaris muscle of aged rats demonstrates iron accumulation and altered expression of iron regulation proteins. Experimental physiology. 2008;93(3):407-14. Xu J, Knutson MD, Carter CS, Leeuwenburgh C. Iron accumulation with age, oxidative stress and functional decline. PloS one. 2008;3(8):e2865. Marzetti E, Anne Lees H, Eva Wohlgemuth S, Leeuwenburgh C. Sarcopenia of aging: Underlying cellular mechanisms and protection by calorie restriction. 2009;35(1):28-35. Nakagawa C, Inaba M, Ishimura E, Yamakawa T, Shoji S, Okuno S. Association of Increased Serum Ferritin With Impaired Muscle Strength/Quality in Hemodialysis Patients. Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation. 2016;26(4):253-7. Bartali B, Frongillo EA, Guralnik JM, Stipanuk MH, Allore HG, Cherubini A, et al. Serum micronutrient concentrations and decline in physical function among older persons. Jama. 2008;299(3):308-15. Westbury LD, Fuggle NR, Syddall HE, Duggal NA, Shaw SC, Maslin K, et al. Relationships Between Markers of Inflammation and Muscle Mass, Strength and Function: Findings from the Hertfordshire Cohort Study. Calcified tissue international. 2018;102(3):287-95. Tuttle CSL, Thang LAN, Maier AB. Markers of inflammation and their association with muscle strength and mass: A systematic review and meta-analysis. Ageing research reviews. 2020;64:101185. Tang T, Xie L, Tan L, Hu X, Yang M. Inflammatory indexes are not associated with sarcopenia in Chinese community-dwelling older people: a cross-sectional study. BMC geriatrics. 2020;20(1):457. Asoudeh F, Dashti F, Raeesi S, Heshmat R, Bidkhori M, Jalilian Z, et al. Inflammatory cytokines and sarcopenia in Iranian adults-results from SARIR study. Scientific Reports. 2022;12(1):5471. Souza VA, Oliveira D, Barbosa SR, Corrêa J, Colugnati FAB, Mansur HN, et al. Sarcopenia in patients with chronic kidney disease not yet on dialysis: Analysis of the prevalence and associated factors. PloS one. 2017;12(4):e0176230. Zeng D, Ling X-Y, Fang Z-L, Lu Y-F. Optimal exercise to improve physical ability and performance in older adults with sarcopenia: a systematic review and network meta-analysis. Geriatric Nursing. 2023;52:199-207. Cheng F, Li N, Yang J, Yang J, Yang W, Ran J, et al. The effect of resistance training on patients with secondary sarcopenia: a systematic review and meta-analysis. Scientific Reports. 2024;14(1):28784. Merchant RA, Chan YH, Hui RJY, Lim JY, Kwek SC, Seetharaman SK, et al. Possible Sarcopenia and Impact of Dual-Task Exercise on Gait Speed, Handgrip Strength, Falls, and Perceived Health. Frontiers in medicine. 2021;8:660463. Mahroum N, Alghory A, Kiyak Z, Alwani A, Seida R, Alrais M, et al. Ferritin – from iron, through inflammation and autoimmunity, to COVID-19. Journal of Autoimmunity. 2022;126:102778. Kernan KF, Carcillo JA. Hyperferritinemia and inflammation. International immunology. 2017;29(9):401-9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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-6176003","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":425477524,"identity":"bdd35ca2-5245-4687-8ff5-1c09139e9df6","order_by":0,"name":"Mahamane Rahoufou Tounaoua","email":"","orcid":"","institution":"the Affiliated Hospital of Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Mahamane","middleName":"Rahoufou","lastName":"Tounaoua","suffix":""},{"id":425477525,"identity":"09a2fcee-bef5-45ae-be2c-2dfd83da280e","order_by":1,"name":"Zakari Shaibu","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Zakari","middleName":"","lastName":"Shaibu","suffix":""},{"id":425477528,"identity":"aed4011c-59bb-4933-948b-5b3ee39a436a","order_by":2,"name":"Zhao Guo-yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYHACxgcfKmx42NgbGx9+IFILs+GMM2ly/DyHm40liNTCJs3bcshYckZ6mwAPMerl+9eYSfM2HEjccPNhG4MEg52cbgMBLYwz3hhbzt1xJ3HD7cS2BwUMycZmBwhoYZY4Y3jj7ZlnIC3tBhIMBxK3EdLCJnHGQIK37TDQYQfbJHiI0cLD32MkCdQC9D4jkVokJNiKoYGcCAxkAyL8It9/eCM0Ko8/fPihwk6OoBYGiQwDJJ4BTnVIgP/4A2KUjYJRMApGwUgGAD0VSVq1EhflAAAAAElFTkSuQmCC","orcid":"","institution":"the Affiliated Hospital of Jiangsu University, Jiangsu University","correspondingAuthor":true,"prefix":"","firstName":"Zhao","middleName":"","lastName":"Guo-yang","suffix":""}],"badges":[],"createdAt":"2025-03-07 07:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6176003/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6176003/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78224728,"identity":"dbbffac7-b96f-4906-80f6-4fe4a167021d","added_by":"auto","created_at":"2025-03-11 06:52:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":17539,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions of gender, and sarcopenia in the study cohort.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6176003/v1/15a2e5b34763d312046de686.png"},{"id":78224738,"identity":"fa0573b5-c046-4ded-a013-bd261fb21111","added_by":"auto","created_at":"2025-03-11 06:52:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34017,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions of Ferritin, BMI, SMI, and CRP, respectively, for participants with and without sarcopenia in the study cohort.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6176003/v1/5a7375371bafea117d59552a.png"},{"id":80216182,"identity":"72e2183e-6dec-41cc-97df-e6d5f98ba2f0","added_by":"auto","created_at":"2025-04-09 09:38:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":648771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6176003/v1/840636be-9e1e-488e-87f6-888352804585.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the role of iron accumulation and muscle parameters as potential risk factors for sarcopenia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSarcopenia is a progressive condition characterized by the loss of skeletal muscle mass, strength, and function due to aging. The Asian Working Group for Sarcopenia describes it as a geriatric syndrome involving the decline of muscle with age, alongside low muscle strength or poor physical performance (1). The European Working Group for Sarcopenia in Older People (EWGSOP) similarly defines sarcopenia as muscle atrophy combined with muscle weakness (measured by hand-grip strength) and/or reduced physical capacity, assessed via gait speed (2). An updated consensus (EWGSOP2) frames sarcopenia as a \u0026ldquo;muscle disease\u0026rdquo; linked to long-term changes in muscle health, with classifications ranging from probable sarcopenia (low muscle strength) to severe sarcopenia (low muscle strength and quantity/quality) (3). This phenomenon contributes nowadays to frailty, and increased risk of hospitalization with adverse outcomes such as physical disability, poor quality of life, a higher risk of falls and fractures and even death. Epidemiological surveys have shown that the incidence of sarcopenia ranges from 5\u0026ndash;13% in people aged 60 and older, with the estimates increasing to 11\u0026ndash;50% in people ages 80 and older (4). Furthermore, the prevalence of sarcopenia may be as high as 24% in patients aged 65 to 70, with older adults losing up to 15% of their total muscle mass during their 7th and 8th decade of life (5). The incidence of sarcopenia is predicted to increase to more than 200\u0026nbsp;million cases over the next 40 years worldwide (6), highlighting the urgency for understanding the associated biological mechanism, and developing effective interventions. Similarly, Kumari et al. (7) reported that more than 50\u0026nbsp;million people worldwide experience sarcopenia, and it is estimated that over 200\u0026nbsp;million people will suffer sarcopenia in the next four decades. Consequently, it has emerged as a significant health concern, placing a substantial burden at both patient and societal levels. Hence, early screening, prevention, and identification of the cause and associated risk factors of sarcopenia are essential, not only for timely intervention but also to improve the patients\u0026rsquo; prognosis.\u003c/p\u003e \u003cp\u003eContributing factors of sarcopenia are multiple, involving a complex interplay of aging processes, genetic factors, hormonal changes, inflammation, and lifestyle factors such as reduced physical activity, and inadequate nutrition (8, 9). Recently, there has been a notable interest in skeletal muscles in the context of iron metabolism, as they contain 10\u0026ndash;15% of iron in the body (10, 11). Some studies (12\u0026ndash;14) demonstrated the impact of iron deficiency in skeletal muscles on the incidence of sarcopenia, while little is known about the impact of iron accumulation in skeletal muscle and how it may contribute to sarcopenia.\u003c/p\u003e \u003cp\u003eIron is a vital mineral necessary for many physiological functions, including oxygen transport, DNA synthesis, energy production, oxidative metabolism, and cellular immune response (15, 16). Its metabolism refers to the processes by which the body absorbs, transports, stores, and utilizes it. The human body tightly regulates iron metabolism to balance its need while preventing both iron deficiency and iron excess, therefore, proper regulation of iron levels is crucial. Although the absorption of iron dietary (1-2mg/d) is tightly regulated and balanced with losses and excess, the initial turnover of iron is essential to meet the requirement for erythropoietic (20-30mg/d) (17). Evidence indicates that increased iron requirement limits external supply whereas increased blood iron may lead to iron deficiency (ID) and iron deficiency anemia (17). On the other hand, excess of iron in any tissue may induce oxidative stress and impair tissue function. In the skeletal muscle, oxidative stress not only causes muscle damage but also negatively impacts its endocrine function (18), and oxidative stress occurs when there\u0026rsquo;s an imbalance between the production of reactive oxygen species (ROS) and the body\u0026rsquo;s ability to detoxify these reactive intermediates or repair the resulting damage. Iron excess has been proposed as an essential factor in skeletal muscle wasting. Studies have reported correlations between muscle iron accumulation and atrophy, either through ageing or by using experimental models of secondary iron accumulation (19).\u003c/p\u003e \u003cp\u003eBoth excess and deficiency of iron have been associated with sarcopenia (6, 20), underscoring the importance of maintaining iron homeostasis to prevent muscle deterioration. While factors like aging, inactivity, and iron metabolism have been identified as influencing sarcopenia, the evidence remains inconclusive. For instance, an observational study (21) showed that patients with sarcopenia had significantly lower serum iron levels compared to those without sarcopenia. Few clinical studies have suggested a relationship between iron accumulation and sarcopenia, evidence of causality in cohort studies is still lacking (22). Additionally, some studies have suggested that abnormalities in iron metabolism may affect the balance of muscle protein synthesis and degradation, further exacerbating the progression of sarcopenia (23). Therefore, timely intervention and enhanced patient outcomes depend on the early detection and assessment of risk factors for sarcopenia. On this matter, extensive research has been conducted on the effects of iron accumulation and iron deficiency on sarcopenia (20, 24). A key aspect of the research was using iron levels as a continuous variable to examine how different levels of iron may affect sarcopenia.\u003c/p\u003e \u003cp\u003eTo fill this gap, our study intends to explore the connection between iron accumulation and the risk of sarcopenia by including various iron indicators, with primary focus on ferritin, alongside skeletal muscle indexes such as SMI and BMI, while also considering CRP as a marker for inflammation.\u003c/p\u003e"},{"header":"Materials and method","content":"\u003cp\u003eA cross-sectional study was conducted using data collected between the years 2022-2023 at the affiliated hospital of Jiangsu University. Patients\u0026rsquo; data including serum ferritin, serum iron, transferrin, total iron binding capacity, transferrin saturation, CRP, white blood cells count, were extracted and analyzed, combined with muscles indexes such as Total skeletal muscle mass (SMM), Skeletal Muscle Index (SMI), and both trunk and limbs muscle mass as shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory method-Blood indicators\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHematologic indicators, especially hemoglobin, are commonly measured in clinics and laboratories using flow cytometry with fully automated cell counters, due to their precision (25). In this study, serum ferritin and transferrin were measured using immunoassay, whereas serum iron, TIBC were measured using colorimetric reaction with ferrozine as a chromogen to form a color complex with iron. On the other hand, CRP, WBC were obtained via a cellometer ascend automated cell counter machine, a benchtop instrument offering fast and reliable cell counts with small volumes. It is worth noting that blood samples from all subjects were collected in the early morning while fasting.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnthropometric measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;We used human body composition analyzer model TANITA(ME180), and Electrochemiluminescence immunoassay combined with BIA (bioelectrical impedance analysis), which are considered the reference and most frequently used tools for assessing skeletal muscle mass. Thus, we measured the SMM via BIA method, and then we calculated the SMI using the following formula: SMI = SMM/Height\u003csup\u003e2\u003c/sup\u003e. BMI was calculated as weight(kg) divided by height\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e(m). The height and weight were measured according to the standard protocol, using a fixed stadiometer and digital scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical performance\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt this level, we assessed handgrip strength and gait speed. For handgrip strength, the maximum strength of the dominant hand was measured for each participant, using a hand dynamometer while sitting with elbow at a 90-degree angle and forearm resting on a stable surface. A minimum of three trials were conducted and the highest reading was recorded. Speed gait measurements were taken at least twice following a six-meter (6-m) walk at a steady and consistent pace, with the average value calculated from the results.\u003c/p\u003e\n\u003cp\u003eTable 1: Demographics Participants (102)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003eNumber (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003eMean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e31(30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e71(69.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eSarcopenia (Yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e27(26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eSarcopenia (No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e75(73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e65.5\u0026plusmn;5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e65.0(8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eHeight (meters)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e1.6(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e61.4\u0026plusmn;9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e60.4(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e23.5\u0026plusmn;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e23.5(3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eSerum Iron\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e22.5\u0026plusmn;15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e20.2(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eFerritin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e166.7\u0026plusmn;106.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e145.9(87.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eTransferrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e2.9(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eTotal iron binding cells (TIBC)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e60.1\u0026plusmn;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e60.4(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eTransferrin saturation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e35.5\u0026plusmn;9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e34(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e1.2(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eWhite blood cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e5.7\u0026plusmn;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e5.4(1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eSMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e6.6\u0026plusmn;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e6.4(1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.1867%;\"\u003e\n \u003cp\u003eSkeletal muscle mass (SMM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3246%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e38.6\u0026plusmn;6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2443%;\"\u003e\n \u003cp\u003e37.7(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Abbreviations : \u0026nbsp; SD=Standard Deviation; IQR= Interquartile Range\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2 presents a comparison of various variables, including weight, BMI, CRP, SMI, and SMM, between participants with and without sarcopenia. The comparison revealed several statistically significant differences: Weight was significantly higher in participants with sarcopenia (64.1 \u0026plusmn; 8.6) compared to those without sarcopenia (54.0 \u0026plusmn; 5.8, p \u0026lt; 0.001), and BMI was significantly higher in participants with sarcopenia (24.4 \u0026plusmn; 2.6) compared to those without sarcopenia (21.0 \u0026plusmn; 1.8, p \u0026lt; 0.001). CRP levels were significantly higher in participants with sarcopenia (1.7 \u0026plusmn; 1.3) compared to those without sarcopenia (1.0 \u0026plusmn; 0.7, p = 0.002). SMI was significantly higher in participants with sarcopenia (6.8 \u0026plusmn; 1.1) compared to those without sarcopenia (5.9 \u0026plusmn; 0.7, p \u0026lt; 0.001), and SMM was significantly higher in participants with sarcopenia (39.8 \u0026plusmn; 6.4) compared to those without sarcopenia (35.3 \u0026plusmn; 5.0, p = 0.005). No significant differences were found for the remaining variables.\u003c/p\u003e\n\u003cp\u003eTable 2. Comparison of the iron-related makers and muscle parameters between participants with sarcopenia and those without\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"620\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eWith\u0026nbsp;\u003cbr\u003e\u0026nbsp;Sarcopenia (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eWithout\u0026nbsp;\u003cbr\u003e\u0026nbsp;Sarcopenia (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\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: 270px;\"\u003e\n \u003cp\u003eMale (Number)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eFemale (Number)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eAge (years) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e65.1\u0026plusmn;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e66.4\u0026plusmn;5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eHeight (meters) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eWeight (kg) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e64.1\u0026plusmn;8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e54.0\u0026plusmn;5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\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: 270px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e24.4\u0026plusmn;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e21.0\u0026plusmn;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\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: 270px;\"\u003e\n \u003cp\u003eSerum Iron (micromol/l) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e21.1\u0026plusmn;5.9 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e20.9\u0026plusmn;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eFerritin (ng/ml) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e160.1\u0026plusmn;96.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e185.1\u0026plusmn;130.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eTransferrin (g/l) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e3.0\u0026plusmn;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eTotal iron binding capacity (TIBC) (micromol/l) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60.3\u0026plusmn;7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e59.4\u0026plusmn;6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eTransferrin saturation (%) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e35.5\u0026plusmn;10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e35.6\u0026plusmn;8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eCRP (mg/dl) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.7\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.0\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eWhite blood cells (cells/microliter) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.6\u0026plusmn;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e5.6\u0026plusmn;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003eSMI (kg/m2) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e6.8\u0026plusmn;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e5.9\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\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: 270px;\"\u003e\n \u003cp\u003eTotal skeletal muscle mass (kg) Mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39.8\u0026plusmn;6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e35.3\u0026plusmn;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Statistically significant difference at 5% level\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study focused on participants aged 60 and above, with complete data on specified variables, and who provided informed consent, while excluding individuals with chronic illnesses such as (liver disease, kidney disease, rheumatoid disease, endocrine system disease, chronic inflammatory diseases, and similar conditions), malignant or hematological disease, muscle disease under drug effect, recent blood transfusions, as well as those with missing data. Moreover, the study exclusively gathered clinical data from patients without altering their treatment plans, ensuring any potential physiological risks are mitigated. The researchers involved in this process took extensive measures to safeguard the confidentiality of patient information. Additionally, the study followed ethical protocols and guidelines for research involving human subjects. This study has been reviewed and approved by the Biomedical Research Ethics Committee of the Affiliated Hospital of Jiangsu University (SWYXLL20210401-16).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical analysis was conducted using IBM SPSS Statistics software version 28. Descriptive statistics, such as mean and standard deviation, were calculated for continuous variables, while frequencies and percentages were determined for categorical variables. To compare iron-related markers and muscle parameters between the two groups (with and without sarcopenia), Mann Whitney U test was performed for continuous variables, and the chi-square test was used to compare the distribution for the categorical variables. To explore the relationship between various factors and the risk of sarcopenia, both univariate and multivariate regression analyses were employed. The univariate analysis allowed for the identification of individual associations between each variable and sarcopenia, while the multivariate analysis provided a more comprehensive understanding by adjusting for potential confounders, enabling the assessment of independent associations. In this study, the multivariate analysis was performed using a backward stepwise variable selection, i.e. a process where we begin with a model that contains all variables under consideration (called the full model), and then we remove the least significant variables one after the other. Throughout this study, the statistical significance level was set at a p-value of less than 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis cross-sectional study was carried out at the affiliated hospital of Jiangsu University from October 2022 to December 2023, involving 102 participants, of whom 31 (30.4%) were males and 71 (69.6%) females (see Figure 1). The median age is 65 years as shown in Table 1. Sarcopenia was present in 27 (26.5%) of all patients, while 75 (73.5%) of the population was free of sarcopenia. A comparative analysis of participants with and without sarcopenia was also performed, and the results are presented in Table 2. Furthermore, Figure 2 provided an overview of the distribution of some variables, namely BMI, SMI, CRF and Ferritin between two groups. To investigate the relationship between various factors and the risk of sarcopenia, both univariate and multivariate regression analyses were performed. The univariate regression analysis revealed several significant associations between variables and the risk of sarcopenia. Key findings include (i) higher BMI was strongly protective against sarcopenia (OR = 0.49 [0.36; 0.67], p \u0026lt; 0.05); (ii) higher SMI was significantly associated with a reduced risk of sarcopenia (OR = 0.18 [0.08; 0.43], p \u0026lt; 0.05); (iii) higher SMM was protective against sarcopenia (OR = 0.87 [0.79; 0.95], p \u0026lt; 0.05); (iv) higher weight was associated with a lower risk of sarcopenia (OR = 0.82 [0.75; 0.90], p \u0026lt; 0.05). Ferritin has no significant association with sarcopenia (p = 0.301). Interestingly, as shown in Table 2, the comparison table revealed that CRP levels were significantly higher in participants with sarcopenia (mean = 1.7 \u0026plusmn; 1.3) compared to those without sarcopenia (mean = 1.0 \u0026plusmn; 0.7, p = 0.002), suggesting an association between increased CRP and the presence of sarcopenia. However, surprisingly, in the regression analysis, higher CRP levels were associated with a lower risk of sarcopenia (OR = 0.45 [0.25; 0.84], p \u0026lt; 0.05), which contrasts with the typical understanding of inflammation being detrimental to muscle health. This discrepancy suggests that acute inflammation, as reflected by CRP, might play a protective role in muscle preservation, though further investigation is required. No significant statistical associations were found for the other variables. Using backward stepwise variable selection (defined in the section \u0026ldquo;Statistical Analysis\u0026rdquo;), we perform a Multivariate Regression Analysis, adjusting for potential confounders, and several variables remained significantly associated with sarcopenia. For BMI the protective effect, observed in the univariate analysis, remained significant (OR = 0.52 [0.37; 0.74], p \u0026lt; 0.05). Although not significant in the univariate analysis, Ferritin showed a modest increase in sarcopenia risk in the multivariate model (OR = 1.01 [1.00; 1.02], p = 0.009). Like in the univariate analysis, higher CRP levels linked to a lower risk of sarcopenia OR = 0.51 [0.27; 0.96], p = 0.05). SMI also continued to show a strong protective effect against sarcopenia (OR = 0.18 [0.06; 0.62], p = 0.006). Although handgrip strength and gait speed were measured as part of the study to assess physical performance, these variables were not included in the statistical analysis and did not contribute to the final findings. The full regression result, including odds ratios, confidence intervals, and p-values for all variables, were presented in Table 3 and Table 4.\u003c/p\u003e\n\u003cp\u003eTable 3. Potential risk factors for sarcopenia using univariate logistic regression models.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"435\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003eUnivariate Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eGender (Male vs Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.95 [0.36; 2.49]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.05 [0.97; 1.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.01 [0.0; 15.36]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eWeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.82 [0.75; 0.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.49 [0.36; 0.67]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eSerum iron Fe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.99 [0.94; 1.04]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eFerritin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.00 [1.00; 1.01]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eTransferrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.65 [0.20; 2.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eTotal iron binding cells (TIBC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.98 [0.92; 1.05]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eTransferrin saturation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.00 [0.96; 1.05]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.012*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.45 [0.25; 0.84]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eWhite blood cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1.08 [0.87; 1.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eSMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.18 [0.08; 0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eAppendicular muscle mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0.87 [0.79; 0.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 435px;\"\u003e\n \u003cp\u003eAbbreviation: OR=Odd Ratio; CI = Confidence Interval\u003c/p\u003e\n \u003cp\u003e*Statistically significant at 5% level (p-value \u0026lt; 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3 presents the results of the univariate logistic regression analysis to identify potential risk factors for sarcopenia. The analysis reveals several significant variables, including BMI, SMI, and CRP, which are associated with the risk of sarcopenia. Non-significant associations were observed for ferritin and other factors\u003c/p\u003e\n\u003cp\u003eTable 4. Potential risk factors for sarcopenia using a multivariate logistic regression model.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"498\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003eMultivariate Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e0.52 [0.37; 0.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eFerritin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e1.01 [1.0; 1.02]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eC-reactive protein (CRP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.037*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e0.51 [0.27; 0.96]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eSMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.006*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e0.18 [0.06; 0.62]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 498px;\"\u003e\n \u003cp\u003e\u0026nbsp;Abbreviation: OR=Odd Ratio; CI = Confidence Interval\u003c/p\u003e\n \u003cp\u003e*Statistically significant at 5% level (p-value \u0026lt; 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4 shows the results of the multivariate logistic regression analysis, which adjusted for potential confounders. This analysis identified BMI, CRP, and SMI as significant factors associated with the risk of sarcopenia, while ferritin showed a modest effect in the multivariate model. These findings suggest that muscle mass (SMI) and inflammatory markers (CRP) are strong predictors of sarcopenia risk\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRecent research has increasingly focused on the potential connection between iron accumulation and sarcopenia (21, 22, 26). In this study, we aimed to explore the relationship between iron accumulation, as measured by ferritin and other iron indicators, and muscle health, assessed through skeletal muscle indexes (such as BMI, SMM, and SMI), in the context of sarcopenia risk.\u003c/p\u003e\n\u003cp\u003eSarcopenia refers to the loss of muscle mass, strength, and function that occurs with aging, primarily impacting older adults and leading to increased frailty, reduced mobility, and greater risk of falls (27). Muscle mass loss, a key indicator of sarcopenia, is linked to a higher risk of fractures, compromised physical function and a decline in quality of life (1) . One increasingly investigated factor is iron accumulation and its role in promoting muscle degeneration. Iron is essential for numerous biological processes, including enzymatic activity, mitochondrial function, DNA synthesis, and energy metabolism (28-30). Its\u0026nbsp;dysregulation, particularly in aging, can lead to detrimental effects\u0026nbsp;on health.\u0026nbsp;While the liver and spleen\u0026nbsp;store\u0026nbsp;most of the\u0026nbsp;body’s\u0026nbsp;iron, skeletal muscle also contains\u0026nbsp;smaller amounts, and excessive iron or iron\u0026nbsp;accumulation, could potentially have adverse effects on skeletal muscle health\u0026nbsp;(19, 31)\u0026nbsp; \u0026nbsp;Unlike many other minerals, the body has no active mechanism to eliminate excess iron (32). Small amounts are lost daily through shedding of intestinal cells, sweat, and in women menstrual blood loss\u0026nbsp;(33). However, as people age, iron accumulates due to the lack of an effective excretory pathway, which can lead to the onset of various diseases\u0026nbsp;(34).\u003c/p\u003e\n\u003cp\u003eDespite notable progress in deciphering the etiology of sarcopenia (35, 36), the connection between iron status and sarcopenia is still not well understood.\u0026nbsp;In this context, our analysis revealed that higher levels of ferritin were associated with an increased risk of sarcopenia, while elevated muscle indexes such as SMM, weight, SMI and BMI were protective factors, with SMI and BMI consistently showing a protective effect. These findings are consistent with previous studies that have suggested a relationship between serum ferritin and sarcopenia as well as the role of BMI. For instance, a cohort study involving 639 hospitalized elderly individuals showed significantly higher serum ferritin levels in the sarcopenia group compared to healthy controls, with levels exceeding the normal range (\u0026gt;145 ug/dl) in sarcopenic patients (37). Similarly, a study in 2014\u0026nbsp;(38), involving 1380 middle-aged and elderly Korean women, discovered that individuals with sarcopenia exhibited significantly higher serum ferritin levels, with those having elevated serum ferritin facing a 2.02-fold increased risk compared to those with normal levels. As mentioned above, our study found that higher BMI was an important variable and acted as a protective factor against sarcopenia. Moroni et al.\u0026nbsp;(39)\u0026nbsp;supported this finding, reporting that, according to random forest analysis, a higher BMI was the most important protective factor for sarcopenia, for sarcopenic obesity (along with Iron) and for osteosarcopenia (along with albumin). Moreover, Sung Jing Moon et al.\u0026nbsp;(40)\u0026nbsp;found that the\u0026nbsp;mean age, the body mass index (BMI), and HOMA-IR were higher and caloric intake, physical activity, and vitamin D level were lower in the sarcopenia groups in both men and women. Altun et al. (41), and Jung et al.\u0026nbsp;(42)\u0026nbsp;observed notably higher non-heme iron levels in the skeletal muscles of elderly rats, while Xu et al.\u0026nbsp;(43) suggested that iron accumulation could be a characteristic feature of aging skeletal muscles. In the same context, some clinical investigations have highlighted a notable link between iron accumulation and sarcopenia. For example, Marzetti et al. (44) reported that iron accumulation in skeletal muscle has been suggested to contribute to the pathogenesis of sarcopenia and acute muscle atrophy. Additionally, in 2017, a study of 639 Italians aged 65 and above found increased serum ferritin levels in sarcopenic patients along with elevated serum inflammatory markers (37). However, contrary to our findings and some supportive studies, Zhi Chen et al. also observed a negative correlation between serum ferritin and muscle mass, even after adjusting for potential confounder\u0026nbsp;(26). Similarly, a 2016 study of 300 hemodialysis patients revealed a significant negative correlation between forearm grip strength and serum ferritin levels (45). Bartali et al. (46), in a longitudinal study involving 698 participants, did not also find a significant association between serum iron levels and physical function,\u0026nbsp;possibly due to differences in study design or participant characteristics.\u003c/p\u003e\n\u003cp\u003eWhile some studies have shown that inflammation is associated with an increased risk of sarcopenia (47, 48), in our study, Table 2 showed also that CRP levels were significantly higher in participants with sarcopenia. However, both univariate and multivariate regression analyses revealed a paradoxical relationship, where higher CRP levels were associated with a reduced risk of sarcopenia. This contrasts with typical associations between chronic inflammation and muscle loss.\u003c/p\u003e\n\u003cp\u003eOther studies, however, have reported no significant association between inflammatory markers and sarcopenia (49-51), suggesting that the role of inflammation in sarcopenia might be more complex than previously understood. This unexpected finding may indicate that the nature and duration of inflammation influence muscle health differently. For instance, acute or transient inflammatory responses could have a distinct impact compared to chronic inflammation, potentially offering a protective effect.\u003c/p\u003e\n\u003cp\u003eGiven this, further investigation is needed to explore how different types of inflammation contribute to muscle health and sarcopenia risk. Future research should consider examining inflammation over time, rather than just at a single point, to better understand its long-term effects on muscle mass. Additionally, intervention studies assessing the role of inflammation modulation or iron chelation in preventing or treating sarcopenia could provide valuable insights into potential therapeutic strategies.\u003c/p\u003e\n\u003cp\u003eAlthough our study focused primarily on iron biomarkers and muscle mass indicators, we also collected data on physical performance using handgrip strength and gait speed, both of which are widely recognized as important functional measures in sarcopenia research (52-54). However, these variables were not included in our statistical analysis, as the scope of this study was primarily concerned with iron biomarkers and muscle mass indicators. It is possible that handgrip strength and gait speed could offer further insights into the functional consequences of iron accumulation in sarcopenia, and future research with a larger sample size or a more focused analysis on functional outcomes may reveal important relationships. Understanding the broader implications of iron metabolism on sarcopenia is crucial, future studies should incorporate this aspect to better assess the role of iron in muscle health. Moreover, our study did not explore how changes in physical performance over time might interact with iron metabolism. Given the well-established role of handgrip strength and gait speed in predicting sarcopenia risk, longitudinal studies incorporating these measures would be valuable in determining the temporal relationship between iron accumulation and muscle function.\u003c/p\u003e\n\u003cp\u003eThe association between higher ferritin levels and sarcopenia risk could be explained by the role of iron in inflammatory processes. Elevated ferritin is often a marker of chronic inflammation, which is known to accelerate muscle wasting (55, 56). Additionally, iron accumulation in tissues may lead to oxidative stress, further contributing to muscle degradation. Although ferritin levels have been associated with sarcopenia, the nature of this relationship (whether higher iron stores contribute to or protect against sarcopenia) remains unclear. These findings suggest that ferritin may not only reflect iron status but also serve as a marker for inflammatory and oxidative processes that promote sarcopenia. Given that the role of iron status (ferritin) in sarcopenia is not yet fully understood, further research is needed. On the other hand, our findings emphasize the importance of maintaining higher BMI and skeletal muscle mass (SMI) in older adults to reduce the risk of sarcopenia, and suggest that iron status, muscle mass, and BMI should be considered when developing interventions for sarcopenia, particularly in aging populations.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;These findings have clinical implications, suggesting that ferritin could be a potential marker for sarcopenia risk if further validated in future studies. Monitoring ferritin alongside other muscle health indicators could help guide early interventions, especially in older adults. However, additional research into the role of iron metabolism in sarcopenia is needed, particularly to understand how ferritin and other iron biomarkers contribute to detecting muscle loss. Long-term studies are essential to establish causal relationships between iron accumulation and sarcopenia, and to explore interventions targeting iron metabolism, such as iron chelation therapy or supplementation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne strength of this study is the use of multiple iron biomarkers to assess iron accumulation, providing a comprehensive view of iron status. However, there are several limitations that should be considered when interpreting the findings. This study is cross-sectional, meaning that it can identify associations but not establish causality. Longitudinal studies are needed to clarify the temporal relationships between iron status, muscle mass, and sarcopenia. While the study controlled for several demographic and health-related variables, lifestyle factors such as physical activity and dietary intake, as well as comorbid conditions, could influence both inflammation markers and muscle health. It is important to consider these confounding factors in future research to better isolate the impact of iron metabolism on sarcopenia. Moreover, the small sample size in this study is another limitation that may impact the generalizability of the findings. Future research with a larger, more diverse sample is recommended to validate and provide a more robust understanding of the topic.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides new insights into the relationship between iron accumulation and sarcopenia risk, with ferritin emerging as a potential biomarker for identifying at-risk populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile significant associations were observed between BMI, SMI, and ferritin with sarcopenia in older adults, the complexity of these relationships highlights the need for further investigation. Notably, our findings also revealed a paradoxical association between CRP levels and sarcopenia risk, which warrants additional exploration. Future research should focus on validating these findings across different populations and exploring potential therapeutic interventions. Understanding how factors like iron status and inflammation interact with muscle health could pave the way for more effective strategies to prevent or treat sarcopenia in aging populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Biomedical Research Ethics Committee of the Affiliate Hospital of Jiangsu University (SWYXLL20210401-16).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All participants in this study provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge all individuals who\u0026nbsp;supported and encouraged us during the preparation of this manuscript. Your support\u0026nbsp;has been\u0026nbsp;greatly appreciated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Scientific Research Project of Jiangsu Provincial Health Committee (M2022119) and Young and Middle-aged Doctors Training Project of Excellent Talent for Osteoporosis and Bone Mineral Disease (G-X-2019-1107).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTounaoua Mahamane Rahoufou conceptualized the study,\u0026nbsp;analyzed the data, and wrote the manuscript, Zakari Shaibu evaluated the data and edited the manuscript accordingly, and Guoyang Zhao supervised and edited this\u0026nbsp;study. All authors contributed to\u0026nbsp;the\u0026nbsp;writing and reviewing\u0026nbsp;of\u0026nbsp;the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors provided consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eChen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15(2):95-101.\u003c/li\u003e\n \u003cli\u003eCruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age and ageing. 2010;39(4):412-23.\u003c/li\u003e\n \u003cli\u003eCruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruy\u0026egrave;re O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age and ageing. 2019;48(1):16-31.\u003c/li\u003e\n \u003cli\u003evon Haehling S, Morley JE, Anker SD. An overview of sarcopenia: facts and numbers on prevalence and clinical impact. Journal of cachexia, sarcopenia and muscle. 2010;1(2):129-33.\u003c/li\u003e\n \u003cli\u003eHan A, Bokshan SL, Marcaccio SE, DePasse JM, Daniels AH. Diagnostic Criteria and Clinical Outcomes in Sarcopenia Research: A Literature Review. Journal of clinical medicine. 2018;7(4).\u003c/li\u003e\n \u003cli\u003eAlves FM, Ayton S, Bush AI, Lynch GS, Koopman R. Age-Related Changes in Skeletal Muscle Iron Homeostasis. The journals of gerontology Series A, Biological sciences and medical sciences. 2023;78(1):16-24.\u003c/li\u003e\n \u003cli\u003eKumari M, Khanna A. Prevalence of Sarcopenic Obesity in Various Comorbidities, Diagnostic Markers, and Therapeutic Approaches: A Review. Annals of geriatric medicine and research. 2022;26(4):296-308.\u003c/li\u003e\n \u003cli\u003eAslam MA, Ma EB, Huh JY. Pathophysiology of sarcopenia: Genetic factors and their interplay with environmental factors. Metabolism. 2023;149:155711.\u003c/li\u003e\n \u003cli\u003eRobinson SM, Reginster JY, Rizzoli R, Shaw SC, Kanis JA, Bautmans I, et al. Does nutrition play a role in the prevention and management of sarcopenia? Clinical nutrition (Edinburgh, Scotland). 2018;37(4):1121-32.\u003c/li\u003e\n \u003cli\u003eBoulton FE. The myoglobin content of human skeletal muscle. British journal of haematology. 1973;25(2):281.\u003c/li\u003e\n \u003cli\u003eRobach P, Cairo G, Gelfi C, Bernuzzi F, Pilegaard H, Vigan\u0026ograve; A, et al. Strong iron demand during hypoxia-induced erythropoiesis is associated with down-regulation of iron-related proteins and myoglobin in human skeletal muscle. Blood. 2007;109(11):4724-31.\u003c/li\u003e\n \u003cli\u003eStugiewicz M, Tkaczyszyn M, Kasztura M, Banasiak W, Ponikowski P, Jankowska EA. The influence of iron deficiency on the functioning of skeletal muscles: experimental evidence and clinical implications. European journal of heart failure. 2016;18(7):762-73.\u003c/li\u003e\n \u003cli\u003eDziegala M, Josiak K, Kasztura M, Kobak K, von Haehling S, Banasiak W, et al. Iron deficiency as energetic insult to skeletal muscle in chronic diseases. Journal of cachexia, sarcopenia and muscle. 2018;9(5):802-15.\u003c/li\u003e\n \u003cli\u003eXu B, Guo Z, Jiang B, Zhang K, Zhu W, Lian X, et al. Factors affecting sarcopenia in older patients with chronic diseases. Annals of palliative medicine. 2022;11(3):972-83.\u003c/li\u003e\n \u003cli\u003eRoemhild K, von Maltzahn F, Weiskirchen R, Kn\u0026uuml;chel R, von Stillfried S, Lammers T. Iron metabolism: pathophysiology and pharmacology. Trends Pharmacol Sci. 2021;42(8):640-56.\u003c/li\u003e\n \u003cli\u003eAbbaspour N, Hurrell R, Kelishadi R. Review on iron and its importance for human health. Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences. 2014;19(2):164-74.\u003c/li\u003e\n \u003cli\u003eMu\u0026ntilde;oz M, Villar I, Garc\u0026iacute;a-Erce JA. An update on iron physiology. World journal of gastroenterology. 2009;15(37):4617-26.\u003c/li\u003e\n \u003cli\u003eHalon-Golabek M, Borkowska A, Herman-Antosiewicz A, Antosiewicz J. Iron Metabolism of the Skeletal Muscle and Neurodegeneration. Frontiers in neuroscience. 2019;13:165.\u003c/li\u003e\n \u003cli\u003eMartin D, Nay K, Robin F, Rebillard A, Orfila L, Martin B, et al. Oxidative and glycolytic skeletal muscles deploy protective mechanisms to avoid atrophy under pathophysiological iron overload. Journal of cachexia, sarcopenia and muscle. 2022;13(2):1250-61.\u003c/li\u003e\n \u003cli\u003eDugan C, Cabolis K, Miles LF, Richards T. Systematic review and meta-analysis of intravenous iron therapy for adults with non-anaemic iron deficiency: An abridged Cochrane review. Journal of cachexia, sarcopenia and muscle. 2022;13(6):2637-49.\u003c/li\u003e\n \u003cli\u003eHuang M, Xu B, Xu Y, Zhang K, Zhu W, Lian X, et al. Serum iron level is independently associated with sarcopenia: a retrospective study. Scientific Reports. 2024;14(1):10554.\u003c/li\u003e\n \u003cli\u003eZhao G. Is Iron Accumulation a Possible Risk Factor for Sarcopenia? Biological trace element research. 2018;186(2):379-83.\u003c/li\u003e\n \u003cli\u003ePeterson MD, Rhea MR, Sen A, Gordon PM. Resistance exercise for muscular strength in older adults: a meta-analysis. Ageing research reviews. 2010;9(3):226-37.\u003c/li\u003e\n \u003cli\u003eKohgo Y, Ikuta K, Ohtake T, Torimoto Y, Kato J. Body iron metabolism and pathophysiology of iron overload. International journal of hematology. 2008;88(1):7-15.\u003c/li\u003e\n \u003cli\u003ePfeiffer CM, Looker AC. Laboratory methodologies for indicators of iron status: strengths, limitations, and analytical challenges. The American journal of clinical nutrition. 2017;106(Suppl 6):1606s-14s.\u003c/li\u003e\n \u003cli\u003eChen Z, Chen J, Song C, Sun J, Liu W. Association Between Serum Iron Status and Muscle Mass in Adults: Results From NHANES 2015-2018. Frontiers in nutrition. 2022;9:941093.\u003c/li\u003e\n \u003cli\u003eFielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, et al. Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. 2011;12(4):249-56.\u003c/li\u003e\n \u003cli\u003eTeh MR, Armitage AE, Drakesmith H. Why cells need iron: a compendium of iron utilisation. Trends in Endocrinology \u0026amp; Metabolism. 2024.\u003c/li\u003e\n \u003cli\u003eJing X, Du T, Li T, Yang X, Wang G, Liu X, et al. The detrimental effect of iron on OA chondrocytes: Importance of pro-inflammatory cytokines induced iron influx and oxidative stress. Journal of cellular and molecular medicine. 2021;25(12):5671-80.\u003c/li\u003e\n \u003cli\u003eKatsura Y, Ohara T, Noma K, Ninomiya T, Kashima H, Kato T, et al. A Novel Combination Cancer Therapy with Iron Chelator Targeting Cancer Stem Cells via Suppressing Stemness. Cancers. 2019;11(2).\u003c/li\u003e\n \u003cli\u003eNishikawa H, Asai A, Fukunishi S, Nishiguchi S, Higuchi K. Metabolic Syndrome and Sarcopenia. Nutrients. 2021;13(10).\u003c/li\u003e\n \u003cli\u003eWallace DF. The Regulation of Iron Absorption and Homeostasis. The Clinical biochemist Reviews. 2016;37(2):51-62.\u003c/li\u003e\n \u003cli\u003eEms T, St Lucia K, Huecker MR. Biochemistry, Iron Absorption. StatPearls. Treasure Island (FL) ineligible companies. Disclosure: Kayla St Lucia declares no relevant financial relationships with ineligible companies. Disclosure: Martin Huecker declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright \u0026copy; 2025, StatPearls Publishing LLC.; 2025.\u003c/li\u003e\n \u003cli\u003eMangan D. Iron: an underrated factor in aging. Aging. 2021;13(19):23407-15.\u003c/li\u003e\n \u003cli\u003eRolland Y, Czerwinski S, Abellan Van Kan G, Morley JE, Cesari M, Onder G, et al. Sarcopenia: its assessment, etiology, pathogenesis, consequences and future perspectives. The journal of nutrition, health \u0026amp; aging. 2008;12(7):433-50.\u003c/li\u003e\n \u003cli\u003eLang T, Streeper T, Cawthon P, Baldwin K, Taaffe DR, Harris TB. Sarcopenia: etiology, clinical consequences, intervention, and assessment. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2010;21(4):543-59.\u003c/li\u003e\n \u003cli\u003ePerna S, Peroni G, Faliva MA, Bartolo A, Naso M, Miccono A, et al. Sarcopenia and sarcopenic obesity in comparison: prevalence, metabolic profile, and key differences. A cross-sectional study in Italian hospitalized elderly. Aging clinical and experimental research. 2017;29(6):1249-58.\u003c/li\u003e\n \u003cli\u003eKim TH, Hwang HJ, Kim SH. Relationship between serum ferritin levels and sarcopenia in Korean females aged 60 years and older using the fourth Korea National Health and Nutrition Examination Survey (KNHANES IV-2, 3), 2008-2009. PloS one. 2014;9(2):e90105.\u003c/li\u003e\n \u003cli\u003eMoroni A, Perna S, Azzolino D, Gasparri C, Zupo R, Micheletti Cremasco M, et al. Discovering the Individualized Factors Associated with Sarcopenia and Sarcopenic Obesity Phenotypes\u0026mdash;A Machine Learning Approach. 2023;15(21):4536.\u003c/li\u003e\n \u003cli\u003eMoon SJ, Kim TH, Yoon SY, Chung JH, Hwang HJ. Relationship between Stage of Chronic Kidney Disease and Sarcopenia in Korean Aged 40 Years and Older Using the Korea National Health and Nutrition Examination Surveys (KNHANES IV-2, 3, and V-1, 2), 2008-2011. PloS one. 2015;10(6):e0130740.\u003c/li\u003e\n \u003cli\u003eAltun M, Edstr\u0026ouml;m E, Spooner E, Flores-Moralez A, Bergman E, Tollet-Egnell P, et al. Iron load and redox stress in skeletal muscle of aged rats. Muscle \u0026amp; nerve. 2007;36(2):223-33.\u003c/li\u003e\n \u003cli\u003eJung SH, DeRuisseau LR, Kavazis AN, DeRuisseau KC. Plantaris muscle of aged rats demonstrates iron accumulation and altered expression of iron regulation proteins. Experimental physiology. 2008;93(3):407-14.\u003c/li\u003e\n \u003cli\u003eXu J, Knutson MD, Carter CS, Leeuwenburgh C. Iron accumulation with age, oxidative stress and functional decline. PloS one. 2008;3(8):e2865.\u003c/li\u003e\n \u003cli\u003eMarzetti E, Anne Lees H, Eva Wohlgemuth S, Leeuwenburgh C. Sarcopenia of aging: Underlying cellular mechanisms and protection by calorie restriction. 2009;35(1):28-35.\u003c/li\u003e\n \u003cli\u003eNakagawa C, Inaba M, Ishimura E, Yamakawa T, Shoji S, Okuno S. Association of Increased Serum Ferritin With Impaired Muscle Strength/Quality in Hemodialysis Patients. Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation. 2016;26(4):253-7.\u003c/li\u003e\n \u003cli\u003eBartali B, Frongillo EA, Guralnik JM, Stipanuk MH, Allore HG, Cherubini A, et al. Serum micronutrient concentrations and decline in physical function among older persons. Jama. 2008;299(3):308-15.\u003c/li\u003e\n \u003cli\u003eWestbury LD, Fuggle NR, Syddall HE, Duggal NA, Shaw SC, Maslin K, et al. Relationships Between Markers of Inflammation and Muscle Mass, Strength and Function: Findings from the Hertfordshire Cohort Study. Calcified tissue international. 2018;102(3):287-95.\u003c/li\u003e\n \u003cli\u003eTuttle CSL, Thang LAN, Maier AB. Markers of inflammation and their association with muscle strength and mass: A systematic review and meta-analysis. Ageing research reviews. 2020;64:101185.\u003c/li\u003e\n \u003cli\u003eTang T, Xie L, Tan L, Hu X, Yang M. Inflammatory indexes are not associated with sarcopenia in Chinese community-dwelling older people: a cross-sectional study. BMC geriatrics. 2020;20(1):457.\u003c/li\u003e\n \u003cli\u003eAsoudeh F, Dashti F, Raeesi S, Heshmat R, Bidkhori M, Jalilian Z, et al. Inflammatory cytokines and sarcopenia in Iranian adults-results from SARIR study. Scientific Reports. 2022;12(1):5471.\u003c/li\u003e\n \u003cli\u003eSouza VA, Oliveira D, Barbosa SR, Corr\u0026ecirc;a J, Colugnati FAB, Mansur HN, et al. Sarcopenia in patients with chronic kidney disease not yet on dialysis: Analysis of the prevalence and associated factors. PloS one. 2017;12(4):e0176230.\u003c/li\u003e\n \u003cli\u003eZeng D, Ling X-Y, Fang Z-L, Lu Y-F. Optimal exercise to improve physical ability and performance in older adults with sarcopenia: a systematic review and network meta-analysis. Geriatric Nursing. 2023;52:199-207.\u003c/li\u003e\n \u003cli\u003eCheng F, Li N, Yang J, Yang J, Yang W, Ran J, et al. The effect of resistance training on patients with secondary sarcopenia: a systematic review and meta-analysis. Scientific Reports. 2024;14(1):28784.\u003c/li\u003e\n \u003cli\u003eMerchant RA, Chan YH, Hui RJY, Lim JY, Kwek SC, Seetharaman SK, et al. Possible Sarcopenia and Impact of Dual-Task Exercise on Gait Speed, Handgrip Strength, Falls, and Perceived Health. Frontiers in medicine. 2021;8:660463.\u003c/li\u003e\n \u003cli\u003eMahroum N, Alghory A, Kiyak Z, Alwani A, Seida R, Alrais M, et al. Ferritin \u0026ndash; from iron, through inflammation and autoimmunity, to COVID-19. Journal of Autoimmunity. 2022;126:102778.\u003c/li\u003e\n \u003cli\u003eKernan KF, Carcillo JA. Hyperferritinemia and inflammation. International immunology. 2017;29(9):401-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Iron, muscle atrophy, skeletal muscle, ferritin, sarcopenia","lastPublishedDoi":"10.21203/rs.3.rs-6176003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6176003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe link between iron accumulation and sarcopenia has become an increasingly important topic in aging and metabolic research. While there is a growing body of literature on this subject, the relationship remains poorly understood. Consequently, this study aims to explore the risk factors associated with sarcopenia by examining iron status through various iron biomarkers in conjunction with skeletal muscle parameters in individuals aged 60 to 80 years. In addition, we examine inflammation and physical performance as secondary risk factors that may contribute to sarcopenia in relation to iron status.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e: We conducted a cross-sectional study using data collected during the year 2022\u0026ndash;2023 from the affiliated hospital of Jiangsu University. Iron status was assessed using serum iron, serum ferritin, transferrin, total iron-binding capacity (TIBC), transferrin saturation. Skeletal muscle health was evaluated through measurements of total skeletal muscle mass (SMM), skeletal muscle index (SMI), body mass index (BMI) and both trunk and limb muscle mass. Inflammation was assessed by C-reactive protein (CRP) levels and white blood cell count. Physical performance was evaluated using handgrip strength and gait speed. Univariate and multivariate regression analyses were performed to explore the associations between these factors and sarcopenia.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e: A total of 102 participants were included. Significant associations were found between sarcopenia and several variables. Higher BMI and SMI were consistently protective against sarcopenia in both univariate and multivariate models (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Interestingly, the comparison Table\u0026nbsp;2 showed that CRP levels were significantly higher in participants with sarcopenia (1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 vs. 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7, p\u0026thinsp;=\u0026thinsp;0.002), which aligns with the conventional understanding of inflammation's role in muscle degradation. However, it exhibited a paradoxical relationship, with higher levels linked to a lower risk of sarcopenia in both models. In the univariate regression, the odds ratio (OR) for CRP was 0.45 (95% CI: 0.25\u0026ndash;0.84, p\u0026thinsp;=\u0026thinsp;0.012), while in the multivariate regression, the OR was 0.51 (95% CI: 0.27\u0026ndash;0.96, p\u0026thinsp;=\u0026thinsp;0.037) This counterintuitive relationship suggests that further investigation into CRP's role in sarcopenia is needed. SMM and Weight showed a significant association in univariate regression (OR\u0026thinsp;=\u0026thinsp;0.87, 95% CI: 0.79\u0026ndash;0.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.003) and (OR\u0026thinsp;=\u0026thinsp;0.82, 95% CI: 0.75\u0026ndash;0.90, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) respectively. Although higher ferritin levels showed no significant association in the univariate analysis (p\u0026thinsp;=\u0026thinsp;0.301), they were significantly associated with a slight increase in sarcopenia risk in the multivariate model (OR\u0026thinsp;=\u0026thinsp;1.01[1.00; 1.02], P\u0026thinsp;=\u0026thinsp;0.009). However, this finding requires further investigation. Other variables such age, transferrin did not show statistically significant associations with sarcopenia. Physical performance, measured by handgrips and gait speed, was assessed but not analyzed for statistical significance.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e: These findings highlight the protective roles of BMI and SMI in reducing the risk of sarcopenia, while revealing the unexpected protective effect shown by CRP, challenging the traditional view of inflammation as a risk factor for sarcopenia and highlighting the complexity of its role in muscle health. Further research is needed to clarify the mechanisms underlying this relationship. Ferritin, an indicator of iron stores, showed a slight positive association with sarcopenia, suggesting that higher ferritin levels may marginally increase the risk, though this effect is small and warrants further investigation, especially after controlling for potential confounders. Although physical performance was measured, its role in sarcopenia was not a focus of this study.\u003c/p\u003e","manuscriptTitle":"Exploring the role of iron accumulation and muscle parameters as potential risk factors for sarcopenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 06:51:57","doi":"10.21203/rs.3.rs-6176003/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":"3ec9ab98-c7c1-4742-9b57-fff178598821","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-09T09:38:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-11 06:51:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6176003","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6176003","identity":"rs-6176003","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}