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Association between the systemic immune-inflammation index and sarcopenia in older adults: a cross-sectional study

BMC Geriatrics volume 25, Article number: 28 (2025) Cite this article

Abstract

Background

Chronic inflammation is increasingly recognized as a crucial contributor to sarcopenia pathogenesis, but accurate diagnosis remains a challenge.

Aim

Our study aims to investigate the relationship between sarcopenia and the Systemic Immune-Inflammation Index (SII), a comprehensive indicator of inflammation.

Methods

This cross-sectional study enrolled 632 patients. All participants underwent a comprehensive geriatric assessment. Sarcopenia was assessed through the evaluation of handgrip strength and calf circumference. To determine the SII, we used the formula: Platelet count (109/mm3)×Neutrophil count (109/mm3) / Lymphocyte count (109/mm3).

Results

The average age of the participants was 74.8 ± 6.4, and 62.3% (n = 394) were female. Patients were grouped as non-sarcopenic and sarcopenic. The non-sarcopenic group had 536 patients (84.8%), while the sarcopenic group comprised 96 patients (15.2%). Sarcopenic patients showed a higher median SII score than the non-sarcopenic group (p < 0.001). Multivariate logistic regression analysis revealed that the SII score was significantly and independently associated with sarcopenia even after adjusting for potential confounding factors (β = 1.002, 95% CI = 1.001–1.003, p < 0.001). The ROC analysis identified the optimal cut-off for SII in predicting sarcopenia as > 765. At this threshold, the negative predictive values were determined to be 88.1%, with a specificity of 88%.

Conclusion

SII is significantly associated with sarcopenia in a geriatric outpatient population, and a population-specific SII cut-off may serve as a novel, simple, and practical biomarker for diagnosing sarcopenia.

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Introduction

Sarcopenia is a progressive, age-related condition marked by an involuntary loss of muscle mass, strength, and physical function [1]. It is related to an elevated risk of metabolic conditions such as type 2 diabetes [2] and other chronic conditions like osteoporosis [3]. Furthermore, sarcopenia has the potential to compromise the immune system, increasing vulnerability to infections among older adults and potentially preventing them from recovering from illnesses [4].

The causes and mechanisms underlying the pathophysiology of sarcopenia remain largely unknown [5]. Chronic age-related inflammation, often referred to as “inflammaging” may play a crucial role in the onset and progression of sarcopenia [6]. Inflammation and sarcopenia have a complex and bidirectional relationship. Inflammatory processes within the body can activate catabolic pathways, resulting in increased muscle protein breakdown and decreased muscle synthesis [7]. This shift in the body’s homeostasis not only accelerates muscle loss but also hampers the regenerative capacity of muscle tissue. Conversely, the reduced muscle mass and function observed in sarcopenia may contribute to the increased inflammatory state, creating a vicious cycle that further exacerbates the condition. Recent meta-analyses suggest a link between lower muscle strength and mass and increased levels of inflammation markers in the body compared to healthy individuals [8, 9].

Increasing evidence underlines the importance of the SII as a robust and valid marker for assessing immune and inflammatory responses [10]. This index, originally introduced by Hu and colleagues in 2014, was developed to evaluate the prognosis of hepatocellular carcinoma but quickly gained widespread utilization in clinical research [10].

The SII is based on available blood biomarkers: peripheral lymphocyte (Lym), neutrophil (Neu), and platelet (Plt) count. The measurement consists of Plt × Neu / Lym [11]. Recent studies have identified a strong association between the SII and various medical conditions. For example, it has been linked to the recurrence rates and survival duration in patients with hepatocellular carcinoma [10], bladder cancer [12], and pancreas adenocarcinoma [13]. Additionally, it serves as a valuable prognostic tool for individuals with cardiovascular diseases such as aortic coarctation and cerebrovascular diseases [10]. Furthermore, the SII index has shown utility in reflecting the nutritional status of individuals undergoing dialysis [14].

Although the association between SII and sarcopenia has been explored in prior studies, most have focused on low muscle mass rather than the multidimensional definition of sarcopenia. Therefore, our study aimed to investigate the relationship between SII and sarcopenia in older adults and to evaluate whether SII, a simple and accessible blood measurement, can serve as a practical diagnostic tool.

Methods

Study design

It is a cross-sectional study consisting of 932 patients aged 60 years and over who could comply with verbal commands and applied to the geriatrics outpatient clinic of a university. Our study excluded participants according to the following criteria: patients with acute infection or chronic infection (n = 118), solid or hematologic malignancies (n = 24), iron deficiency anemia (n = 18), rheumatologic diseases (n = 17), heart failure (n = 21), chronic pulmonary disease (n = 74), chronic liver or kidney disease (n = 12) or those currently receiving steroids or immunomodulatory treatments (n = 16). After the exclusion criteria were met, 632 patients were included in the study (Fig. 1). The study protocol was approved by the ethical committee of a university hospital with decision number 912, and informed consent was obtained from all participants.

Fig. 1
figure 1

Flowchart of the participants

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Participants’ demographic data, including age, gender, chronic diseases, and medication history, were recorded. Participants’ weights were measured barefoot using a calibrated scale while wearing light clothing, and heights were measured with a stadiometer while standing. Body mass index (BMI) is the weight (kg) divided by the square of height in meters. Circumference of the calf was assessed at its widest point using a nonelastic tape measure.

All participants underwent comprehensive geriatric assessments, including evaluations of their daily living activities using the Katz Basic and Lawton-Brody Instrumental Activities of Daily Living Scale (ADL [15], IADL [16]). Nutritional status was evaluated with the Mini Nutritional Assessment-short form (MNA-SF) [17], and the mood was assessed using the Yesavage Geriatric Depression Scale short form (GDS) [18]. The physical performance parameters of the patients were evaluated using the 6-meter walking test, and those who walked slower than 0.8 m/s were defined as having low gait speed [19].

Sarcopenia assessment

The participants’ muscle strength was evaluated using a Takei handgrip strength dynamometer, focusing on their dominant hand. The assessment involved three measurements, and the highest value was recorded for each patient. Low muscle strength (dynapenia) is defined as hand grip strength below 22 kg for women and 32 kg for men [20].

Calf circumference (CC) was used as an anthropometric measure to assess skeletal muscle mass. Based on a previous study conducted in the Turkish population, a calf circumference of 33 cm was established as the threshold for identifying low muscle mass in both males and females [20].

Sarcopenia combines low handgrip strength and calf circumference below the cut-off values [19].

Blood sampling

All participants underwent a comprehensive blood analysis after an overnight fast on the same day as their sarcopenia assessment. This analysis included a complete blood count (CBC), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) measurement. CBC was performed with a Beckman Coulter automated analyzer. SII was assessed according to the formula: Plt (109/mm3)×Neu (109/mm3) / Lym(109/mm3) [11].

Statistical analyses

Statistical analysis was conducted using SPSS version 22.0. Visual methods (histogram and probability plots) and analytical techniques were employed to assess the normal distribution of variables. Descriptive statistics were given: mean and standard deviation for normally distributed variables, median (minimum-maximum) for non-normally distributed variables, and number and percentage for nominal variables. For two-group comparisons, the Mann-Whitney U test was used for non-normally distributed data, and the independent-samples t-test was used for normally distributed data. Chi-square tests were used to compare categorical variables. Multivariate logistic regression with the enter method identified independent factors associated with sarcopenia. Receiver Operating Characteristic (ROC) curve analysis was conducted using MedCalc software to evaluate the diagnostic accuracy of the SII. Sensitivity, specificity, positive predictive values (+ PV), and negative predictive values (-PV) were calculated, with the Youden Index used to determine the optimal cut-off value. Statistical significance was set at p < 0.05.

Results

This study enrolled 632 geriatric patients with a mean age of 74.8 ± 6.4 years, and 62.3% (n = 394) were female. Patients were divided into two groups: sarcopenic and non-sarcopenic. The non-sarcopenic group comprised 536 patients (84.8%), while the sarcopenic group comprised 96 patients (15.2%). Sarcopenic patients were found to be older and had a higher median systemic immune-inflammation index score compared to non-sarcopenic individuals (p < 0.001). The demographic characteristics and comprehensive geriatric assessments of the patients are presented in Table 1.

Table 1 Demographic characteristics, comorbidities, and laboratory results with comprehensive geriatric assessments, categorized by Sarcopenia status (Bold values indicate statistically significant results p < 0.05)
Full size table

After accounting for potential confounding factors, multivariate logistic regression analysis revealed that SII significantly increased sarcopenia for model 1 (β = 1.002, 95% CI 1.001–1.003, p < 0.001), including age and gender, and for model 2 (β = 1.002, 95% CI 1.001–1.003, p < 0.001); including model 1 plus mini nutritional assessment score, daily living activities scores, geriatric depression score, and comorbidities (diabetes mellitus, hypertension, atherosclerotic heart disease). Table 2 shows the results of multivariate logistic regression models investigating factors associated with sarcopenia.

Table 2 Association between systemic immune inflammation index, other factors, and Sarcopenia according to unadjusted and adjusted logistic regression models (Bold values indicate statistically significant results p < 0.05)
Full size table

ROC analysis revealed the best cut-offs of SII for sarcopenia as > 765. The negative predictive values were identified as 88.1%, and specificity was identified as 88%. The results of the ROC analysis are presented in Table 3; Fig. 2.

Table 3 ROC curve analysis of systemic Immune-inflammation index (SII) for Sarcopenia (Bold values indicate statistically significant results p < 0.05)
Full size table
Fig. 2
figure 2

ROC curve analysis for assessing the performance of SII in determining sarcopenia

Full size image

Discussion

Recent studies have highlighted the association between systemic immune-inflammation index (SII) and sarcopenia, yet no prior research has specifically proposed a diagnostic cut-off value for SII in older adults. Our study is the first to identify an optimal SII cut-off point of 765, demonstrating considerable accuracy in ruling out sarcopenia with a negative predictive value of 88.1% for the entire cohort. Additionally, elevated SII levels were identified as an independent indicator of sarcopenia, underscoring its potential as a simple and accessible biomarker for use in geriatric clinical practice.

Understanding the role of inflammation in the development of sarcopenia and how the aging immune system contributes to muscle loss is crucial to fully elucidating the pathogenesis of sarcopenia. Moreover, identifying biomarkers that accurately reflect this relationship is of paramount importance. Previous research has shown that chronic inflammation is essential in skeletal muscle mass wasting and deteriorated muscle functions [21]. Immunosenescence, the age-related decline in immune function, contributes to chronic inflammation by elevating pro-inflammatory markers in the blood, ultimately compromising the immune system’s effectiveness [22]. Commonly assessed peripheral pro-inflammatory markers for their correlation with sarcopenia include leukocytes, lymphocytes, interleukin-6 (IL-6), IL-10, C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-alpha) [23]. A meta-analysis has shown that sarcopenic patients have higher CRP levels compared to the control group [24]. In another study, associations were observed between IL-6 and TNF-α levels and reduced muscle mass and strength [25]. In a study, elevated TNF-α and soluble receptors were associated with decreased thigh muscle area over five years [26].

This study demonstrates an association between sarcopenia and white blood cell composition, with elevated neutrophil count and reduced lymphocyte count in sarcopenic patients. This disparity might be explained by the distinct roles of these immune cells, as neutrophils belong to innate immunity, while lymphocytes represent the adaptive immune system [27]. A previous cross-sectional study also found that a higher neutrophil-lymphocyte ratio was associated with an increased risk of sarcopenia [28]. Therefore, cell ratios or indices may better reveal the equilibrium of innate and adaptive immune systems [29] and their potential role in diseases like sarcopenia.

The lack of easily applicable tools in clinical settings underscores the need to identify inflammatory biomarkers that reflect the mechanisms used to diagnose sarcopenia. This may facilitate easier and earlier diagnosis. SII, a new inflammatory index, was first used on individuals with solid cancer [10, 12, 13]. Previous studies suggest the SII, a marker of systemic inflammation, is associated with non-cancerous diseases like dementia and cardiovascular disease [29, 30]. Increased SII levels have been correlated with a higher risk of dementia [31]. A recent study identified SII as a predictor of all causes and cardiovascular mortality [32]. However, its potential connection to sarcopenia, a prevalent age-related condition, remains a significant gap in current research. In a recent study involving patients diagnosed with colorectal cancer, SII was associated with myopenia and myosteatosis [33]. In a cross-sectional study, elevated SII levels were linked to an increased risk of low muscle mass [34]. Another study reported an independent and negative relationship between hand grip strength and SII levels [35]. A recent study has demonstrated a significant association between SII and an increased risk of mortality in individuals with sarcopenia [36]. A recent meta-analysis confirmed the association between high SII levels and sarcopenia [37]. However, among the studies included in the meta-analysis, only two specifically focused on older adults, with the remainder involving patients with cancer, chemotherapy, or younger populations or assessed only muscle mass without considering muscle strength. In contrast, our study uniquely focused on a geriatric outpatient population, excluding conditions like cancer that could independently influence systemic inflammation, providing a novel perspective focused on a geriatric outpatient population.

The present study has several strengths. Firstly, this study identified potentially valuable inflammatory markers for assessing sarcopenia. These markers are likely cost-effective and readily available in clinical settings, offering a potentially more straightforward and accessible method for sarcopenia diagnosis than existing, complex techniques. Secondly, we meticulously excluded individuals with chronic inflammatory conditions such as chronic pulmonary diseases, heart failure, chronic kidney, chronic liver diseases, rheumatological diseases, and malignancies to minimize the influence of these conditions on blood cell and muscle mass measurements, enhancing the specificity of our findings to sarcopenia itself. Additionally, we utilized population-specific cut-off values for calf circumference and handgrip strength, tailored to the Turkish population, to account for inter-population differences. These cut-offs have been validated as effective predictors of low muscle mass identified by BIA, strengthening the applicability of our findings. However, our study has certain limitations. Our cross-sectional design inherently limits our ability to establish causality. Additionally, data on specific inflammatory cytokines (IL-6, IL-10, TNF-α) was unavailable. This study used calf circumference as a proxy for muscle mass assessment, in line with the 2019 EWGSOP-2 guidelines, which recommend its use in settings where advanced diagnostic methods are unavailable. While practical, this method is less precise than imaging techniques such as DXA or BIA. Given the dynamic nature of sarcopenia, the results of our study need to be confirmed by prospective studies, including repeated measurements performed at different times and incorporating imaging-based assessments to validate these findings further.

Conclusion

In conclusion, this is the first study to establish the cut-off value of SII for sarcopenia in community-dwelling older adults. Regular monitoring of SII may provide a cost-effective and straightforward strategy for screening sarcopenia and managing it.

Data availability

This paper does not have linked research data sets. However, all data generated or analyzed during this study is available upon request and can be obtained from the corresponding author.

Abbreviations

ADL:

Activity of daily living

BMI:

Body mass index

CRP:

C-reactive protein

ESR:

Erythrocyte sedimentation rate

GDS:

Geriatric depression scale

IADL:

Instrumental activity of daily living

MNA-SF:

Mini nutritional assessment short form

SII:

Systemic Immune-Inflammation Index

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Authors and Affiliations

  1. Faculty of Medicine, Department of Geriatric Medicine, Gazi University, Ankara, 06560, Turkey

    Esra Cataltepe, Eda Ceker, Ayse Fadiloglu, Fatih Gungor, Nermin Karakurt, Zekeriya Ulger & Hacer Dogan Varan

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Contributions

E. C. contributed to the concept and design of the study, acquisition, analysis, and drafting of the manuscript; E.C., A.F., F.G., and N.K. equally contributed to the acquisition and analysis of data; H.D.V. contributed to the statistical analysis with data interpretation, H.D.V and Z.U equally auditing, and reviewing the manuscript. All authors critically revised the manuscript, agreed to be fully accountable for ensuring the integrity and accuracy of the work, and read and approved the final manuscript.

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Correspondence to Esra Cataltepe.

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Ethical approval and consent to participate

This study was approved by the Gazi University Ethics Committee (27.11.2023/912) and conducted according to the Declarations of Helsinki. Written informed consent was obtained from all participants.

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The authors declare no competing interests.

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Cataltepe, E., Ceker, E., Fadiloglu, A. et al. Association between the systemic immune-inflammation index and sarcopenia in older adults: a cross-sectional study. BMC Geriatr 25, 28 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-05686-2

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BMC Geriatrics

ISSN: 1471-2318

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