INTRODUCTION
Sarcopenic obesity (SO) is a condition characterized by the coexistence of sarcopenia and obesity, which has been attracting increasing attention in recent years. This state is distinguished by the simultaneous progression of fat accumulation and muscle mass reduction, accompanied by increased intramuscular fat infiltration.1) SO is associated with higher health risks compared to obesity or sarcopenia alone.2) The prevalence of SO in the general older population is approximately 9%–11%,3,4) and it is linked to various adverse clinical outcomes, including cardiovascular disease, increased all-cause mortality, metabolic disorders, cognitive impairment, and limitations in physical function.2,5-7) Notably, both obesity and sarcopenia have strong associations with stroke.8-10) Obesity elevates stroke risk through the increase of intermediate risk factors such as hypertension, diabetes, and dyslipidemia, as well as the promotion of atherosclerosis.10) Conversely, post-stroke patients are prone to developing sarcopenia due to the effects of paralysis, functional impairment, and nutritional deficits.11) The prevalence of SO in stroke patients has been reported as 4% in the acute phase12) and 4.5% in the recovery phase.13) In patients undergoing stroke rehabilitation, the presence of SO is suggested to negatively impact activities of daily living (ADL) improvement.13,14) Consequently, the importance of accurate diagnosis and early intervention for SO has become evident. Particularly in stroke patients, appropriate assessment and management of SO are essential to maximize rehabilitation effectiveness and improve long-term functional prognosis.
Diagnostic criteria for SO have been proposed by the Japanese Working Group on Sarcopenic Obesity (JWGSO)15) and other organizations, however, the prevalence rate and association with outcomes using these diagnostic criteria are unknown. Historically, the absence of unified diagnostic criteria for SO has impeded accurate prevalence estimation and assessment of clinical impact, as sarcopenia and obesity were diagnosed independently, and methodological approaches varied across studies. The European Working Group on Sarcopenia in Older People initially proposed international diagnostic criteria for sarcopenia in 2010,16) followed by the Asian Working Group for Sarcopenia (AWGS) in 2014,17) which established evaluation criteria specifically tailored for Asian populations. In response to these developments, in 2017, the JWGSO was established and began working to establish diagnostic criteria for SO. In 2022, the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) collaboratively published unified diagnostic criteria for SO, which have since gained widespread acceptance as a global standard.18) Most recently, the Global Leadership Initiative in Sarcopenia (GLIS) introduced new international criteria in 2023 to further refine the assessment of sarcopenia across diverse populations.19) Nevertheless, for Asian populations, including Japanese individuals, there has been a recognized need for optimized diagnostic criteria due to differences in physique, lifestyle, and cultural background, which tend to result in lower muscle strength and mass compared to other ethnicities. Given this context, evaluating SO using the JWGSO diagnostic criteria, which were developed considering Asian characteristics, and elucidating its prevalence and outcome associations is crucial for validating the new diagnostic criteria's validity and clinical utility. This approach is expected to contribute significantly to the development of tailored prevention and treatment strategies for SO in Asian populations
The purpose of this study is to investigate the prevalence of JWGSO-defined SO in patients with stroke in the convalescent phase, and its association with ADL at discharge and the length of hospital stay.
MATERIAL AND METHODS
Participants and Setting
This retrospective cohort study was conducted at a Japanese subacute hospital with a 135-bed convalescent rehabilitation ward from January 2015 to December 2023. The study population included patients who had completed initial treatment at an acute-phase hospital following a stroke and were subsequently admitted to the subacute hospital for rehabilitation after their condition had stabilized. Inclusion criteria were patients between the ages of 40 and 75 years, according to the JWGSO diagnostic criteria.15) The exclusion criteria were: (1) bioelectrical impedance analysis (BIA) incompatibility (e.g., pacemaker implantation), (2) bilateral paralysis (difficulty in accurate measurement of grip strength), (3) death during hospitalization, (4) transfer to another hospital or ward for treatment of other conditions, and (5) incomplete data.
In this ward, rehabilitation—comprising physical therapy, occupational therapy, and speech and hearing therapy—is provided for up to 3 hours per day, from admission to discharge. The rehabilitation program includes functional recovery exercises for paralyzed limbs, basic mobility training, walking training, ADL training, and muscle strengthening exercises, all of which are tailored to each patient's physical function and disability. In addition, nutritional management, such as energy adjustment for weight optimization and protein enhancement for muscle strengthening, is also provided by a registered dietitian.20)
Data Collection
The basic information such as age, sex, body mass index (BMI), type of stroke, and time from stroke onset to hospital admission was collected from the electronic medical records. The severity of comorbidities was assessed using the Charlson Comorbidity Index (CCI),21) and functional status before stroke onset was assessed by the physician using the modified Rankin Scale (mRS).22) The severity of paralysis on the affected side in stroke patients was assessed by a physical therapist using the Brunnstrom Recovery Stage (BRS).23) The BRS evaluates the extent of paralysis in the fingers, upper limb, and lower limb on a six-point scale, with higher scores indicating less severe paralysis.
The Functional Independence Measure (FIM)24) was used to assess the ability to perform ADL, including both motor (FIM-motor) and cognitive (FIM-cognitive) domains. These assessments were conducted in collaboration with a nurse and a physical or occupational therapist. Handgrip strength was measured by an occupational therapist using a Smedley hand dynamometer (TTM, Tokyo, Japan). The measurement was taken on the non-dominant hand, and the maximum value from three trials was recorded. For patients with hemiplegia, measurements were taken on the unaffected hand, and for those with bilateral hemiplegia, measurements were taken on both hands.9,25) Muscle mass was evaluated by a physical therapist using BIA with a body composition analyzer (Inbody S10, Tokyo, Japan). Patients were assessed in the supine position after fasting for at least 4 hours and refraining from exercise for at least 1 hour. These evaluations were performed within 72 hours of admission. Nutritional intake was assessed by a nurse or dietitian as a percentage of the amount of food provided during the first week after admission and calculated as a mean.26)
Diagnosis of Sarcopenic Obesity
Fig. 1 illustrates the diagnostic algorithm for SO according to the JWGSO criteria. The JWGSO criteria for SO diagnosis15) involves a two-step process: (1) screening for sarcopenia and obesity and (2) assessment of sarcopenia and obesity. While the consensus statement recommends screening for clinical symptoms or suspicion of sarcopenia, this step was considered applicable to all participants in our study. Obesity screening utilized a BMI cutoff of ≥25 kg/m2. Sarcopenia assessment included low handgrip strength (cutoffs: <28 kg for men, <18 kg for women) and low skeletal muscle mass index (SMI) evaluated by skeletal muscle mass (SMM)/BMI (cutoffs: <0.789 for men, <0.512 for women). Obesity assessment used high body fat percentage (FM%) (cutoffs: ≥20% for men, ≥30% for women).
To compare SO defined by JWGSO with the current global criteria for SO, as well as with simple sarcopenia and simple obesity, all patients were also assessed using the ESPEN/EASO criteria, AWGS 2019 sarcopenia criteria, and obesity criteria. The diagnostic criteria are illustrated in Supplementary Fig. S1.
The ESPEN/EASO criteria18) also employed a two-stage process. SO screening used high BMI (cutoff: ≥27.5 kg/m2 for both sexes, as recommended for Asian populations)27) and clinical signs. We also conducted an analysis using BMI >25.0 kg/m2 as a reference.28) SO diagnosis required: (1) reduced muscle function, assessed by low handgrip strength (cutoffs: <28 kg for men, <18 kg for women)29) and (2) altered body composition, determined by increased FM% (cutoffs: >29% for men, >41% for women)30) and decreased SMM/body weight ratio (cutoffs: <31.5% for men, <22.1% for women).31)
Sarcopenia was diagnosed based on the AWGS 2019 criteria,29) requiring both low SMM/the square of the patient’s height (cutoffs: <7.0 kg/m2 for men, <5.7 kg/m2 for women) and low handgrip strength (cutoffs: <28 kg for men, <18 kg for women). Due to the impact of paralysis, physical function assessment is often not feasible in stroke patients. Therefore, sarcopenia was diagnosed based solely on low muscle mass and low muscle strength. This approach is consistent with the latest GLIS criteria,19) which also define sarcopenia using low muscle mass and strength, without incorporating physical function as a diagnostic component.
Obesity was diagnosed using high BMI (cutoff: ≥25.0 kg/m2) and high FM% (cutoffs: ≥20% for men, ≥30% for women), which aligns with the JWGSO criteria for obesity screening and diagnosis.32)
Outcomes
The primary outcome was the FIM-motor score at discharge. The FIM is divided into two domains: the motor domain (FIM-motor), comprising 13 sub-items, and the cognitive domain (FIM-cognitive), consisting of 5 sub-items.24) The FIM-motor is assessed on a 7-point ordinal scale for each of the following activities: self-care, sphincter, transfer, and locomotion, ranging from full assistance to complete independence. Scores range from 13 to 91, with lower scores indicating a higher level of dependence.
The secondary outcome measures were length of hospital stays.
Sample Size Calculation
To determine the sample size, we utilized Power and Sample Size Calculations software version 3.1.6, based on the findings of a previous study. In this prior investigation, the standard deviation (SD) of the FIM-motor score in hospitalized post-stroke patients was reported as 24.4.33) We hypothesized that the true mean difference between the SO and non-SO groups would be 17 points greater than the minimal clinically important difference established in the previous study.34) Assuming a power of 0.8 and an alpha error of 0.05 to reject the null hypothesis, a minimum of 17 patients in the SO group and a total sample size of 323 participants were required. This sample size calculation supports the statistical validity of the present results.
Statistical Analysis
Results are presented as mean and SD for parametric data, median and interquartile range (IQR) for non-parametric data, and numerical percentages for categorical data. IBM SPSS Statistics, version 21.0 (IBM Corp., Armonk, NY, USA) was used for analysis. p<0.05 was set for statistical significance. Bivariate analysis of baseline patient information and outcomes was performed by classification according to JWGSO-defined SO. Comparisons between groups were made using Mann-Whitney U tests, and chi-squared tests, depending on the type of data for the variables. Due to the non-normal distribution of continuous variables, we used the Mann-Whitney U test for between-group comparisons. Despite the imbalance in sample sizes between the SO and non-SO groups, the distributional shapes of variables were similar across both groups, supporting the appropriateness of this test.
Multiple linear regression analysis was used to determine whether SO or sarcopenia or obesity was independently associated with FIM-motor at discharge and length of hospital stays. To account for potential confounders in each outcome, we selected covariates such as age, sex, stroke type, stroke history,35) FIM-motor at admission, FIM-cognition at admission, pre-stroke mRS,36) CCI,37,38) BRS-lower limb,39) and energy intake/actual body weight.40,41) These variables are the higher importance ones that have been shown to be associated with outcomes in previous studies or those that may be clinically relevant to the outcome. To further account for the effect of age, we stratified age into 40–64 and 65–75 years and performed similar multivariate subgroup analyses in each age group. Multicollinearity was evaluated using the variance inflation factor (VIF), and a VIF value of less than 10 was considered to indicate the absence of multicollinearity.
Ethics Approval
The study was conducted in accordance with the Declaration of Helsinki and the ethical guidelines for medical and health research involving human subjects and was approved by the Institutional Review Board of the Kumamoto Rehabilitation Hospital in which the study was conducted (Approval No. 2024-20). No other evaluation or sampling was done for research purposes, and data obtained in routine practice were used. Due to the retrospective study design, written informed consent could not be obtained from the participants; however, they were provided the opportunity to withdraw from the study at any time through an opt-out method.
RESULTS
A total of 1,273 stroke patients were admitted during the study period. After applying age inclusion criteria and excluding patients who died during hospitalization (n=1), were transferred to another hospital or ward (n=42), had pacemaker implantation (n=17), bilateral paralysis (n=13), or had missing data (n=159), 405 patients were included in the final analysis (Fig. 2).
Table 1 presents the baseline characteristics of the study participants. The median age was 65 years (IQR 58–71), with 60.7% being male. Twenty-two patients (5.4%) were classified as having SO according to JWGSO criteria. Patients with JWGSO-defined SO had significantly higher CCI and BMI, and significantly lower BRS scores, FIM scores (total, motor, and cognitive), FILS, energy and protein intake, and handgrip strength compared to non-SO patients. No significant differences were observed in age, sex, stroke type, or pre-stroke mRS.
Univariate analysis (Table 2) revealed that both male and female patients with JWGSO-defined SO had significantly lower FIM motor scores at discharge compared to non-SO patients. Female patients with JWGSO-defined SO also had significantly longer lengths of stay. ESPEN/EASO-defined SO was associated with significantly lower FIM motor scores at discharge and longer lengths of stay in females. In males, when using a BMI cutoff of ≥25 for ESPEN/EASO criteria, FIM motor scores at discharge were significantly lower. Sarcopenia was associated with significantly lower FIM motor scores in both sexes and longer lengths of stay in females. Obesity alone was associated with no significant differences in FIM motor scores and length of stay for either sex (Supplementary Tables S1–S4).
Multivariate regression analysis (Table 3) showed no significant association between JWGSO-defined sarcopenic obesity and FIM-motor at discharge (β=0.015, p=0.664) or length of stay (β=-0.008, p=0.828). However, sarcopenia demonstrated significant independent negative associations with both FIM-motor at discharge (β=-0.150, p<0.001) and length of stay (β=-0.147, p=0.001), after adjusting for potential confounders. It is important to note that no evidence of multicollinearity was observed in the regression models.
DISCUSSION
In this study, we investigated the prevalence of SO as defined by the JWGSO among post-stroke patients in the rehabilitation phase. Additionally, we examined its association with ADL at discharge and length of hospital stay. Our research yielded two novel findings. Firstly, the prevalence of JWGSO-defined SO among post-stroke patients undergoing rehabilitation was 5.4%. Secondly, we found no significant association between JWGSO-defined SO and either ADL or length of hospital stay.
The prevalence of JWGSO-defined SO among post-stroke patients undergoing convalescent rehabilitation was 5.4%. This prevalence falls within the range reported in various populations, albeit on the lower end. A meta-analysis found a global prevalence of 11% in adults aged 60 years or older, with rates varying from 0.8% to 22.3% in women and 1.3% to 15.4% in men, depending on the diagnostic criteria used.7) In stroke patients specifically, a study using ESPEN/EASO criteria reported a 4% prevalence of SO in acute stroke patients.12) Another study in convalescent rehabilitation wards found a higher prevalence of 28% using AWGS criteria combined with FM%.42) The variability in prevalence rates across studies highlights the impact of diagnostic criteria, study populations, and settings on SO prevalence estimates. Our finding of 5.5% using JWGSO criteria reflects the specific characteristics of our post-stroke population in convalescent rehabilitation, emphasizing the need for standardized definitions and consideration of population-specific factors when interpreting SO prevalence.
No significant association between JWGSO-defined SO and either ADL or length of hospital stay among post-stroke patients undergoing convalescent rehabilitation. This study is the first to investigate the association between JWGSO-defined SO and outcomes in post-stroke patients undergoing rehabilitation. This finding contrasts with previous research using different diagnostic criteria which found a negative association between SO and discharge FIM motor scores.13,42) The discrepancy in results may be attributed to the age-specific criteria in the JWGSO definition, which led to a younger cohort in our study. To examine whether this age composition influenced the findings, we conducted a subgroup analysis by stratifying patients into two age groups (40–64 years and 65–75 years); however, no significant association between SO and either ADL or length of hospital stay was observed in either subgroup (Supplementary Table S5). This age difference could explain the divergent outcomes, as younger patients may have better functional reserves and recovery potential.43)
Another possibility is the impact of obesity itself. Previous studies have suggested that moderate obesity, particularly during hospitalization and rehabilitation, may exert a protective effect often referred to as the 'obesity paradox'. Reports from Japan have indicated that a BMI of 27.5 or higher in post-stroke patients is independently associated with ADL at discharge,44) and in community-dwelling elderly individuals, there is a tendency for lower all-cause mortality risk compared to those of normal weight.45) On the other hand, excessive obesity itself can potentially lead to functional impairment, and in post-stroke patients, BMI exhibits a U-shaped relationship with functional disability, with the lowest level of disability observed in the range of 22.1–27.5.46) In our study, the median BMI of the SO group was 27.6, which was not considered severe enough to substantially hinder functional recovery. This degree of obesity may mitigate the adverse effects of sarcopenia and obscure its impact on functional outcomes. Interestingly, while SO showed no significant association, sarcopenia alone demonstrated a negative correlation with discharge ADL and length of stay, even in this younger age group. This finding underscores the importance of addressing sarcopenia in post-stroke rehabilitation, regardless of age, and suggests that the impact of muscle mass and muscle weakness may be more critical than the combined effect of low muscle mass and obesity in this population.
In convalescent stroke patients, greater attention may be warranted towards sarcopenia without obesity rather than JWGSO-defined SO, suggesting a need for nuanced body composition assessment in rehabilitation. While obesity may cause chronic inflammation and delay recovery, the "obesity paradox" remains debated.3) Conversely, sarcopenia directly impedes physical function recovery47) and is associated with malnutrition,48) potentially diminishing rehabilitation effectiveness. To optimize outcomes, assessing body composition and implementing strategies targeting sarcopenia, including nutritional and exercise therapies, is crucial.49) Future research should validate SO prevalence and outcomes using JWGSO criteria across various settings, investigate mechanisms making sarcopenia a critical factor in rehabilitation, and compare the effectiveness of sarcopenia-focused interventions to those targeting SO. These studies could inform personalized rehabilitation protocols by identifying critical intervention time points.
This study has several important limitations that should be considered when interpreting the results. Firstly, the single-center design conducted at a Japanese subacute hospital may limit the generalizability of findings to other healthcare settings or populations. Secondly, the retrospective nature of the study introduces potential biases and confounding factors that may not have been fully accounted for in the analysis, including specific medication use, detailed rehabilitation protocols, comprehensive nutritional intake data, socioeconomic factors, and psychological factors that could affect rehabilitation participation and recovery. Thirdly, due to the retrospective study design, causal relationships could not be established. The cross-sectional assessment of sarcopenic obesity at admission fails to capture dynamic changes in body composition and functional status during the rehabilitation period, limiting insights into the temporal relationship between SO and outcomes, as well as the potential effects of interventions on recovery over time.
In conclusion, the prevalence of SO as defined by JWGSO criteria in post-stroke patients was 5.4%, and it was not associated with ADL or length of hospital stay. However, the significant impact of sarcopenia alone on both outcomes highlights the critical importance of assessing body composition in stroke rehabilitation and emphasizes the need for targeted interventions to address muscle mass and strength in these patients.
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