Frailty and sarcopenia in Chinese community-dwelling older adults: prevalence, coexistence, and body composition differences

Frailty and sarcopenia in Chinese community-dwelling older adults: prevalence, coexistence, and body composition differences | 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 Article Frailty and sarcopenia in Chinese community-dwelling older adults: prevalence, coexistence, and body composition differences Yu Ye, Jinwei Liu, Mengyu Cao, Shuaixuan Xu, Fang Wang, Zhen Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9131780/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Frailty and sarcopenia are closely related geriatric syndromes that share overlapping clinical features and pathophysiological mechanisms, yet whether they represent the same condition remains unclear. This study aimed to investigate the prevalence, coexistence, and associated body composition characteristics of frailty and sarcopenia in community-dwelling older adults in Beijing, China. Methods This cross-sectional study included 869 community-dwelling adults aged 60 years and older in Beijing, China. Frailty was defined using the Fried Frailty Phenotype, and sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 criteria. Age-stratified analyses were performed to assess changes in the coexistence of frailty and sarcopenia across age groups. To examine the effect of diagnostic thresholds on coexistence, the cut-offs for grip strength and gait speed were harmonized between the 2 criteria. Multinomial logistic regression was used to compare skeletal muscle and fat-related indices between participants with frailty alone and those with sarcopenia alone. Results The mean age of participants was 74.2 years. The prevalence of frailty, sarcopenia, and coexisting frailty and sarcopenia was 30.5%, 12.3%, and 9.9%, respectively. The coexistence rate increased markedly with age, from 1.2% in participants aged 60–69 years to 5.4% in those aged 70–79 years and 25.3% in those aged 80 years or older. Harmonizing the grip strength and gait speed thresholds changed the coexistence rate by no more than 1.1%. Compared with the sarcopenia-alone group, the frailty-alone group had a higher skeletal muscle mass index (7.3 ± 0.8 vs 5.9 ± 0.8 kg/m²) as well as higher visceral fat area and fat mass index. Discussion Frailty was more prevalent than sarcopenia in this Beijing community sample, whereas their coexistence was relatively limited, suggesting that frailty and sarcopenia may not represent the same condition. Compared with sarcopenia, frailty was characterized by a less pronounced reduction in skeletal muscle mass and greater fat accumulation. These findings support the need to distinguish frailty from sarcopenia in the assessment and management of older adults. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research frailty sarcopenia prevalence concurrence ageing skeletal muscle body fat Figures Figure 1 Introduction Frailty is a geriatric syndrome characterized by a decline in multisystem physiological reserve, resulting in reduced resilience to stressors and an increased risk of adverse outcomes, including disability, prolonged hospitalization, and death. It therefore has a substantial negative impact on quality of life [ 1 ]. Although the underlying mechanisms of frailty have not been fully elucidated, chronic inflammation, oxidative stress, and mitochondrial dysfunction have been proposed as key contributors. These processes may lead to structural and functional abnormalities in skeletal muscle, disturbances in fat metabolism, and dysregulation of other physiological systems, ultimately giving rise to clinical manifestations such as weakness, slow gait speed, and fatigue [ 2 – 4 ]. Sarcopenia is another common geriatric syndrome associated with poor outcomes, including falls, fractures, disability, and mortality, and it markedly impairs the ability of older adults to perform daily activities [ 5 ]. Sarcopenia is generally defined by declines in skeletal muscle mass, muscle strength, and physical performance [ 6 ]. At present, however, there are still no universally accepted diagnostic criteria for either frailty or sarcopenia, and the reported prevalence of both conditions varies considerably depending on the assessment tools applied, ranging from 12% to 24% for frailty [ 7 ] and from 9.9% to 40.4% for sarcopenia [ 8 ]. Frailty and sarcopenia overlap substantially in terms of pathophysiology, clinical manifestations, diagnostic components, intervention strategies, and prognosis [ 9 – 12 ]. However, whether they represent the same clinical entity remains uncertain. Early studies suggested that sarcopenia may mediate several adverse outcomes of frailty and may serve as an important pathway through which frailty progresses to disability [ 12 ]. Others have proposed that frailty and sarcopenia are “2 sides of the same coin,” arguing that distinguishing between them may be of limited practical significance because age-related geriatric syndromes cannot be fully explained by a single pathophysiological mechanism [ 13 ]. In contrast, other evidence indicates only partial overlap between the 2 conditions. Previous studies have shown that only 8.2%–15.7% of individuals with sarcopenia were also frail, whereas approximately one-third of frail individuals did not have sarcopenia, suggesting that frailty and sarcopenia may be related but are not identical [ 14 ]. In addition, grip strength and gait speed are included in the diagnostic criteria for both frailty and sarcopenia, although the corresponding cut-off values differ. Whether these differences in diagnostic thresholds influence the observed coexistence of the 2 conditions remains unclear [ 15 ]. Ageing is accompanied by a progressive decline in skeletal muscle mass and a gradual increase in body fat, both of which may contribute to the development of frailty and sarcopenia [ 16 ]. However, few studies have directly compared body composition characteristics, such as skeletal muscle mass and fat accumulation, between individuals with frailty and those with sarcopenia. Moreover, most previous studies examining the relationship between frailty and sarcopenia have focused on European and American populations, whereas evidence from Chinese populations remains limited. Whether frailty and sarcopenia exhibit similar patterns of coexistence in Chinese older adults therefore remains unknown. Accordingly, this study aimed to investigate the prevalence and coexistence of frailty and sarcopenia among Chinese community-dwelling older adults and to explore factors associated with their coexistence. In addition, this study sought to examine whether differences in diagnostic thresholds influence the overlap between frailty and sarcopenia and to compare body composition characteristics between the 2 conditions. By clarifying the relationship between frailty and sarcopenia in a Chinese population, this study may provide evidence to support the assessment and management of geriatric syndromes in clinical practice. Methods Study participants Community-dwelling adults aged 60 years and older were recruited from communities in Beijing, China, between March and December 2022. The inclusion criteria were as follows: (1) age ≥ 60 years; (2) residence in the community for more than 6 months; and (3) voluntary participation in the study. The exclusion criteria were as follows: (1) severe cognitive impairment; (2) severe visual or hearing impairment; (3) incomplete recovery from surgery within the previous 6 months; (4) acute illness; (5) inability to complete functional assessments because of pain; and (6) the presence of metal implants, such as pacemakers. The study was approved by the institutional ethics committee and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants before enrolment. A total of 993 individuals were initially recruited. After excluding 124 individuals who did not meet the eligibility criteria, 869 participants were ultimately included in the analysis. Diagnosis of frailty and sarcopenia Frailty was assessed using the Fried Frailty Phenotype (FP), which includes 5 components: unintentional weight loss, slow gait speed, reduced grip strength, low physical activity, and self-reported exhaustion. Each component was assigned a score of 1, yielding a total score ranging from 0 to 5. Participants were classified as robust (0 points), prefrail (1–2 points), or frail (≥ 3 points) [ 17 ]. Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria, which include skeletal muscle mass, muscle strength, and physical performance. Sarcopenia was defined as low skeletal muscle mass accompanied by either low grip strength or poor physical performance [ 18 ]. Skeletal muscle mass and body fat assessment Bioelectrical impedance analysis (BIA) has shown good agreement with dual-energy X-ray absorptiometry for the assessment of skeletal muscle mass (agreement coefficient = 0.98) [ 19 ]. BIA estimates body composition by introducing alternating electrical currents of different frequencies into the body and measuring impedance in the limbs and trunk, thereby allowing calculation of skeletal muscle mass, fat mass, and body water in different body segments. This method is easy to perform and does not involve radiation exposure. In the present study, skeletal muscle mass, skeletal muscle mass index (SMI; skeletal muscle mass/height²), and body fat indices, including percent body fat (PBF), visceral fat area (VFA), and fat mass index (FMI; fat mass/height²), were measured using a body composition analyser (InBody 770; InBody Co., Ltd., Seoul, South Korea). Grip strength and gait speed assessment Grip strength was measured using a handheld dynamometer (Jamar Plus; Sammons Preston, USA). Participants were seated with the elbow flexed at 90° and the forearm in a neutral position. The grip position was standardized to the second handle position [ 20 , 21 ]. Two measurements were obtained from the dominant hand, with a 30-second interval between assessments. If the dominant hand could not be tested, the contralateral hand was used. The maximum value was recorded for analysis. Gait speed was assessed over a 6-m walking course within a 10-m walkway, with 2 m at each end used for acceleration and deceleration. Participants were instructed to walk at their usual pace from the 0-m mark to the 10-m mark. Timing started when the leading foot crossed the 2-m mark and stopped when it crossed the 8-m mark. The test was performed twice, and the average value was used for analysis. Statistical analysis All statistical analyses were performed using SPSS version 25.0. Normally distributed continuous variables are presented as the mean ± standard deviation (SD) and were compared using the independent-samples t test or analysis of variance (ANOVA), as appropriate. Non-normally distributed continuous variables are presented as the median and interquartile range (IQR) and were analysed using the Kruskal-Wallis test. Categorical variables are presented as frequencies and percentages and were compared using the chi-square test. Logistic regression analysis was performed to examine the associations between body composition and frailty or sarcopenia. Age, sex, multimorbidity, and history of falls were included as covariates in the adjusted model. All statistical tests were two-sided, and P < 0.05 was considered statistically significant. Results Participants ranged in age from 60 to 97 years, with a mean age of 74.2 years. Individuals in the frailty and sarcopenia groups were predominantly aged 80 years or older. Among all participants, the prevalence of frailty, sarcopenia, and coexisting frailty and sarcopenia was 30.5%, 12.3%, and 9.9%, respectively. Among participants with frailty, 32.5% also had sarcopenia, whereas 80.4% of those with sarcopenia were also classified as frail. The baseline characteristics of the study population according to frailty and sarcopenia status are presented in Table 1 . The prevalence of multimorbidity was nearly 60% in both the frailty and sarcopenia groups. In addition, 17.7% and 17.8% of participants in the frailty and sarcopenia groups, respectively, had experienced a fall within the previous year, which was markedly higher than that in the healthy group (2.7%). The skeletal muscle mass index (SMI) was 6.8 ± 1.0 kg/m² in the frailty group and 5.9 ± 0.7 kg/m² in the sarcopenia group, both of which were lower than that in the healthy group (7.7 ± 0.7 kg/m²). Table 1 Characteristics of the participants Male n (%) Neither frailty nor sarcopenia (n = 583) Frailty (n = 265) Sarcopenia (n = 107) P value 550 (94.3) 193 (72.8) 68 (63.6) <0.001 Age (y) 70.7 ± 7.1 81.6 ± 8.1 82.4 ± 7.0 <0.001 60–69 n (%) 295 (50.6) 31 (11.7) 6 (5.6) <0.001 70–79 n (%) 213 (36.5) 55 (20.8) 23 (21.5) ≥ 80 n (%) 75 (12.9) 179 (67.5) 78 (72.9) Height (cm) 171.6 ± 6.0 165.1 ± 8.2 161.6 ± 8.0 <0.001 Weight (kg) 73.2 ± 9.8 66.0 ± 11.8 55.9 ± 8.0 <0.001 BMI (kg/m 2 ) 24.8 ± 2.6 24.1 ± 3.3 21.4 ± 2.7 <0.001 <18.5 n (%) 5 (0.9) 10 (3.8) 13 (12.1) <0.001 18.5–23.9 n (%) 215 (36.9) 115 (43.4) 75 (70.1) 24.0-27.9 n (%) 299 (51.3) 106 (40.0) 17 (15.9) ≥ 28.0 n (%) 64 (11.0) 34 (12.8) 2 (1.9) SMI (kg/m 2 ) 7.7 ± 0.7 6.8 ± 1.0 5.9 ± 0.7 <0.001 SMM (kg) 29.6 ± 4.1 24.5 ± 4.6 21.0 ± 3.2 <0.001 PBF (%) 26.5 ± 5.3 30.5 ± 6.8 29.3 ± 7.6 <0.001 VFA (cm 2 ) 91.4 ± 27.8 103.9 ± 36.4 88.1 ± 34.8 <0.001 FMI (kg/m 2 ) 6.7 ± 1.8 7.5 ± 2.4 6.5 ± 2.3 <0.001 Multimorbidity n (%) 192 (32.9) 157 (59.2) 64 (59.8) <0.001 Hypertension n (%) 251 (43.1) 145 (54.7) 57 (53.3) 0.003 Diabetes n (%) 148 (25.4) 78 (29.4) 32 (29.9) 0.002 Cardiovascular diseases n (%) 83 (14.2) 63 (23.8) 23 (21.5) 0.363 History of falls n (%) 16 (2.7) 47 (17.7) 19 (17.8) <0.001 Handgrip strength (kg) 38.5 ± 6.7 25.0 ± 8.4 22.3 ± 7.0 <0.001 6m walking time (s) 4.5 ± 0.8 8.2 ± 6.4 8.6 ± 6.5 <0.001 SMI skeletal muscle mass index, SMM skeletal muscle mass, PBF percent body fat, VFA visceral fat area, FMI fat mass index, M ultimorbidity a combination of 2 or more chronic diseases, History of falls number of falls ≥ 1 in the last year Coexistence of frailty and sarcopenia across age groups To examine the effect of age on the coexistence of frailty and sarcopenia, participants were stratified into 3 age groups: 60–69 years, 70–79 years, and ≥ 80 years. The prevalence of coexisting frailty and sarcopenia in the overall study population was 1.2%, 5.4%, and 25.3% in these 3 age groups, respectively, indicating a marked increase in coexistence with advancing age (Fig. 1 ). Coexistence of frailty and sarcopenia after adjustment of grip strength and gait speed cut-offs Because the diagnostic cut-off values for grip strength and gait speed differ between the Fried Frailty Phenotype (FP) and the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria, we further examined whether these differences affected the observed coexistence of frailty and sarcopenia. When the grip strength and gait speed cut-offs in the FP were adjusted to match those of the AWGS 2019 criteria, the coexistence rate increased to 11.0%, representing a 1.1% increase from the original rate. Conversely, when the corresponding AWGS 2019 cut-offs were adjusted to match those of the FP, the coexistence rate was 9.7%, representing a 0.2% decrease from the original rate (Tables 2.1 and 2.2). Table 2.1 The concurrence of frailty and sarcopenia after adjusting the diagnostic cut-offs of frailty Frailty (adjusting cut-offs) Sarcopenia Count Non-sarcopenia n(%) Sarcopenia n(%) Non-frailty n(%) 570(65.6) 11(1.3) 581 Frailty n(%) 192(22.1) 96(11.0) 288 Count 762 107 869 Adjustment of diagnostic cut-offs for grip strength and gait speed of FP in line with AWGS 2019: grip strength (< 28kg for men and < 18kg for women), 6m walking speed (< 1.0m/s) Table 2.2 The concurrence of frailty and sarcopenia after adjusting the diagnostic cut-offs of sarcopenia Frailty Sarcopenia (adjusting cut-offs) Count Non-sarcopenia n（%） Sarcopenia n（%） Non-frailty n（%） 604（69.5） 0（0.0） 604 Frailty n（%） 181（20.8） 84（9.7） 265 Count 785 84 869 Adjustment of diagnostic cut-offs for grip strength and gait speed of AWGS 2019 in line with FP: subjects were assessed separately by BMI or height groups Association of body composition with frailty and sarcopenia Among the 286 participants with frailty or sarcopenia, 86 had both frailty and sarcopenia, 179 had frailty alone, and 21 had sarcopenia alone. To further explore the differences between these 2 conditions, participants with coexisting frailty and sarcopenia were excluded, and comparisons were made between the frailty-alone and sarcopenia-alone groups. The SMI was 7.3 ± 0.8 kg/m² in the frailty-alone group and 5.9 ± 0.8 kg/m² in the sarcopenia-alone group, with univariate analysis showing a significant difference between the groups. In addition, visceral fat area (VFA) and fat mass index (FMI) were higher in the frailty-alone group than in the sarcopenia-alone group (Table 3 ). Table 3 Characteristics of the frailty alone group and the sarcopenia alone group SMI skeletal muscle mass index, SMM skeletal muscle mass, PBF percent body fat, VFA visceral fat area, FMI fat mass index, M ultimorbidity a combination of 2 or more chronic diseases, History of falls number of falls ≥ 1 in the last year Male n(%) Frailty alone (n = 179) Sarcopenia alone (n = 21) P value 137(76.5) 12(57.1) 0.054 Age(y) 80.8 ± 8.6 78.8 ± 7.0 0.318 60–69 n(%) 27(15.1) 2(9.5) 0.282 70–79 n(%) 40(22.3) 8(38.1) ≥ 80 n(%) 112(62.6) 11(52.4) Height(cm) 166.9 ± 7.7 162.2 ± 8.4 0.01 Weight(kg) 70.9 ± 10.2 56.8 ± 8.8 <0.001 BMI(kg/m 2 ) 25.4 ± 2.7 21.5 ± 2.2 <0.001 <18.5 n(%) 0(0.0) 3(14.3) <0.001 18.5–23.9 n(%) 55(30.7) 15(71.4) 24.0-27.9 n(%) 92(51.4) 3(14.3) ≥ 28.0 n(%) 32(17.9) 0(0.0) SMI(kg/m 2 ) 7.3 ± 0.8 5.9 ± 0.8 <0.001 SMM(kg) 26.3 ± 4.1 21.1 ± 3.5 <0.001 PBF(%) 31.1 ± 6.1 29.7 ± 6.2 0.323 VFA(cm 2 ) 111.3 ± 34.4 87.6 ± 31.1 0.003 FMI(kg/m 2 ) 8.1 ± 2.3 6.7 ± 1.8 0.025 Multimorbidity n(%) 105(58.7) 12(57.1) 0.894 Hypertension n(%) 101(56.4) 13(61.9) 0.631 Diabetes n(%) 53(29.6) 7(33.3) 0.725 Cardiovascular diseases n(%) 45(25.1) 5(23.8) 0.894 History of falls n(%) 31(17.3) 3(14.3) 0.966 Handgrip strength(kg) 27.0 ± 8.7 27.8 ± 8.1 0.658 6m walking time(s) 8.8 ± 9.8 5.8 ± 1.1 0.237 Table 4 presents the odds ratios (ORs) and 95% confidence intervals (CIs) for skeletal muscle and body fat indices. Differences in SMI, VFA, and FMI between the frailty-alone and sarcopenia-alone groups remained significant after adjustment for age and sex in Model 1 and after further adjustment for age, sex, multimorbidity, and history of falls in Model 2. Table 4 Relationship between body composition and frailty or sarcopenia (frailty alone group as a reference) Unadjusted Model 1 Model 2 OR(95%CI) P value OR(95%CI) P value OR(95%CI) P value SMI 0.150(0.075–0.301) <0.001 0.006(0.001–0.044) <0.001 0.006(0.001–0.040) <0.001 PBF 0.964(0.897–1.036) 0.322 0.938(0.868–1.013) 0.101 0.937(0.867–1.012) 0.096 VFA 0.977(0.962–0.993) 0.004 0.975(0.959–0.991) 0.002 0.975(0.959–0.991) 0.002 FMI 0.744(0.572–0.967) 0.027 0.707(0.541–0.924) 0.011 0.703(0.537–0.921) 0.011 SMI skeletal muscle mass index, PBF percent body fat, VFA visceral fat area, FMI fat mass index, Model 1 adjusted for age and sex, and Model 2 adjusted for age, sex, multimorbidity and history of falls Discussion The relationship between frailty and sarcopenia remains incompletely understood, and whether they should be regarded as the same disease entity or as distinct but overlapping geriatric syndromes is still under debate. Clarifying this issue is of considerable clinical importance. If frailty and sarcopenia represent the same condition, screening and assessment in geriatric practice could be simplified, thereby improving efficiency and reducing the use of medical resources. Conversely, if they are distinct conditions, further evaluation of their differences would be necessary to guide tailored prevention and intervention strategies. Therefore, elucidating the relationship between frailty and sarcopenia is highly relevant to clinical decision-making in geriatric medicine. In the present study, we examined the coexistence of frailty and sarcopenia among community-dwelling adults aged 60 years and older in Beijing, China, and explored factors potentially associated with their overlap. In this study, the coexistence of frailty and sarcopenia was observed in 9.9% of all participants, suggesting that the overlap between these 2 conditions is relatively limited in the community setting. Previous studies have reported coexistence rates of 3.0% in the study by Daehyun et al. [ 22 ] and 9.8% in the study by Cengiz et al. [ 23 ]. The prevalence of frailty and sarcopenia is influenced by multiple factors, including age, sex, ethnicity, geographic region, and the diagnostic criteria applied; accordingly, the coexistence of the 2 conditions varies across populations. Although coexisting frailty and sarcopenia is not highly prevalent, it remains clinically important. Recent evidence suggests that frail individuals with sarcopenia are more likely to experience adverse health outcomes than frail individuals without sarcopenia. In addition, the presence of sarcopenia has been associated with an increased incidence of cardiovascular and respiratory diseases in frail individuals and with higher risks of all-cause and cancer-related mortality [ 24 ]. A cohort study investigating frailty transitions further demonstrated that sarcopenia significantly increased the likelihood of transition from robust to prefrail status and from prefrail to frail status, indicating that sarcopenia may adversely influence the dynamic progression of frailty [ 25 ]. Both frailty and sarcopenia are age-related geriatric syndromes, and the prevalence of both increases with advancing age. In the present study, coexistence was uncommon in younger participants but increased substantially with age. A Korean study investigating the relationship between frailty and sarcopenia reported a coexistence rate of 3.0% in a population with a mean age of 75.9 years [ 22 ], whereas another study with a mean participant age of 86.5 years reported a coexistence rate of 16.3% [ 26 ]. Taken together with our findings, these data suggest that the overlap between frailty and sarcopenia is strongly age-related and becomes more frequent in very old populations. This pattern may indicate that the distinction between frailty and sarcopenia is more evident in younger older adults and becomes less pronounced with advancing age. The Fried Frailty Phenotype and the AWGS 2019 criteria both incorporate grip strength and gait speed, although their cut-off values differ. Sousa-Santos et al. evaluated the coexistence of frailty, sarcopenia, obesity, and malnutrition and found that frailty combined with obesity affected the largest proportion of participants (10.5%), whereas the coexistence of frailty and sarcopenia was observed in only 2.2% [ 15 ]. The authors suggested that inconsistency in the grip strength thresholds used to define frailty and sarcopenia might have contributed to the low overlap between the 2 conditions [ 15 ]. In the present study, we adjusted the cut-off values for grip strength and gait speed to determine whether the relatively low coexistence rate could be explained by differences in diagnostic thresholds. Notably, the change in coexistence was minimal regardless of whether the thresholds were standardized to those of frailty or sarcopenia, indicating that differences in grip strength and gait speed cut-offs had little effect on the observed overlap. This finding is consistent with that of Daehyun et al., who used the Fried Frailty Phenotype and the AWGS 2014 criteria and reported a coexistence rate of 2.4%; when the AWGS 2014 criteria were replaced with the AWGS 2019 criteria, the prevalence of coexistence increased by only 0.6% [ 22 ]. Collectively, these findings suggest that the limited overlap between frailty and sarcopenia is unlikely to be explained solely by differences in diagnostic thresholds. Frailty and sarcopenia are both characterized clinically by impaired physical function and, to varying degrees, reductions in skeletal muscle mass. A growing body of evidence indicates that skeletal muscle plays a central role in the pathophysiology of both conditions [ 27 , 28 ]. Skeletal muscle is essential not only for locomotion and activities of daily living but also as an endocrine organ capable of producing and releasing cytokines and peptides, known as myokines, in response to exercise and other physiological stimuli [ 29 ]. These myokines contribute to the regulation of nutrient sensing, transport, uptake, and utilization and are important for maintaining systemic cellular and physiological homeostasis. They also mediate interorgan communication and exert beneficial effects on cardiovascular, metabolic, immune, and nervous system function [ 2 ]. In the present study, the skeletal muscle mass index was significantly higher in the frailty-alone group than in the sarcopenia-alone group, and this difference remained significant after multivariable adjustment. This finding suggests that the degree of muscle loss is more pronounced in sarcopenia than in frailty. Reduced skeletal muscle mass may impair myokine production and secretion, thereby contributing to the development of frailty or sarcopenia, whereas preservation of muscle mass may help mitigate disease risk. Our findings further support the notion that frailty and sarcopenia are related but distinct: frailty appears to involve multisystem impairment, whereas sarcopenia is characterized by more severe structural and functional deterioration of skeletal muscle. Obesity has been recognized as an important risk factor for frailty, partly because excess adiposity may promote chronic inflammation and thereby contribute to frailty progression [ 30 ]. Sarcopenic obesity is characterized by the coexistence of reduced skeletal muscle mass and increased fat accumulation, which may also involve fat infiltration into muscle tissue [ 31 ]. This condition has been associated with adverse outcomes such as falls, disability, and mortality, potentially through a vicious cycle linking muscle loss and fat accumulation [ 32 ]. Body composition can be divided into protein, fat, water, and inorganic components. Compared with body mass index, the fat mass index more accurately reflects overall adiposity, whereas visceral fat area reflects abdominal fat accumulation around internal organs and is an indicator of central obesity. Excess visceral fat is associated with a higher risk of adverse outcomes, including diabetes and cardiovascular disease [ 33 ]. In the present study, both fat mass index and visceral fat area were significantly higher in the frailty-alone group than in the sarcopenia-alone group, suggesting that general and abdominal obesity were more prominent in frailty than in sarcopenia. This observation is supported by 2 cohort studies with 3.5 years of follow-up, which showed that both general obesity (pooled OR 1.73, 95% CI 1.18–2.28) and abdominal obesity (pooled OR 1.67, 95% CI 1.09–2.25) were associated with incident frailty [ 34 ]. In those studies, general obesity was associated with a higher risk of fatigue, low physical activity, and weakness, whereas abdominal obesity was specifically associated with weakness. Furthermore, both long-standing obesity and weight gain during ageing have been linked to frailty development, suggesting that early management of excess adiposity may help prevent frailty in older adults [ 35 ]. To our knowledge, this is the first study to investigate the coexistence of frailty and sarcopenia in a relatively large sample of Chinese community-dwelling older adults, thereby providing evidence relevant to the assessment and management of these conditions in Chinese populations. Nevertheless, several limitations should be acknowledged. First, because of the cross-sectional design, causal relationships between body composition and the coexistence of frailty and sarcopenia cannot be established. Second, the lack of universally accepted diagnostic criteria for frailty and sarcopenia may have influenced the estimated coexistence rate. Third, the range of baseline variables collected in this study was relatively limited, which may have constrained the adjustment for potential confounding factors in the statistical analyses. Future longitudinal cohort studies are warranted to examine the trajectories of frailty and sarcopenia over time and to clarify the impact of key indicators on clinical outcomes. Declarations Conflict-of-interest The authors declare that they have no conflicts of interest. Funding This study was supported by the National Key Research and Development Program of China (Grant No. 2018YFC2002004). Ethics approval and informed consent Approved by the Ethics Committee of the Chinese PLA General Hospital (Approval No. S2019-140-01), this study was conducted following the guidelines of the Declaration of Helsinki. Author Contribution Y.Y. and J.L. contributed equally to this work. Y.Y., J.L., and N.P. conceived and designed the study. Y.Y., J.L., M.C., S.X., F.W., Z.Z., S.C., and N.Z. collected the data and performed the assessments. Y.Y. and J.L. performed the statistical analyses and drafted the manuscript. M.C., S.X., F.W., Z.Z., S.C., and N.Z. contributed to data interpretation and manuscript revision. N.P. supervised the study and critically revised the manuscript. All authors reviewed and approved the final manuscript. Data Availability The datasets generated and/or analysed during the current study are not publicly available due privacy reasons but are available from the corresponding author on reasonable request. References Orkaby, A. R., Schwartz, A. W., Callahan, K. E. & Frailty Ann. Intern. Med. ; 179 (2):ITC17–ITC32. (2026). Barros, D., Marques, E. A., Magalhães, J. & Carvalho, J. Energy metabolism and frailty: The potential role of exercise-induced myokines - A narrative review. Ageing Res. Rev. 82 , 101780 (2022). Rao, X. & Cai, X. Aging-Driven Inter-Organ Crosstalk in Postmenopausal Osteoporosis: From Immunometabolic Drift to Multisystem Frailty. FASEB J. 40 (4), e71541 (2026). He, D. et al. Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts. J. Cachexia Sarcopenia Muscle . 14 (1), 632–641 (2023). Jeyaraman, M. et al. Sarcopenia in Aging: Pathogenesis, Diagnosis, and Emerging Therapeutic Frontiers. Mol. Imaging Biol. ; 28 (1). (2025). Zhao, Y. et al. Sarcopenia interventions targeted at improving muscle health in adults with cancer: a systematic review and meta-analysis. Front. Nutr. 12 , 1671720 (2026). Hoogendijk, E. O. et al. Frailty: implications for clinical practice and public health. Lancet 394 (10206), 1365–1375 (2019). van der Steen-Dieperink, M. J. M. M., Koekkoek, W. A. C. & Kouw, I. W. K. Sarcopenia and frailty in critical illness. Curr. Opin. Clin. Nutr. Metab. Care . 28 (3), 192–199 (2025). Picca, A., Coelho-Junior, H. J., Calvani, R., Marzetti, E. & Vetrano, D. L. Biomarkers shared by frailty and sarcopenia in older adults: A systematic review and meta-analysis. Ageing Res. Rev. 73 , 101530 (2022). Gao, Y. et al. Exploration of Pathogenesis and Cutting-Edge Treatment Strategies of Sarcopenia: A Narrative Review. Clin. Interv Aging . 20 , 659–684 (2025). Dun, Y. et al. Effectiveness of a multicomponent exercise program to reverse pre-frailty in community-dwelling Chinese older adults: a randomised controlled trial. Age Ageing ; 51 (3). (2022). Kilaitė, J. et al. Causal relationships between sarcopenia, frailty, and health outcomes: A systematic review of Mendelian randomization studies. Exp. Gerontol. 212 , 112953 (2025). Viña, J. & Gomez-Cabrera, M. C. Molecular mechanism involved in sarcopenia and frailty, diagnosis and therapy. Mol. Aspects Med. 105 , 101387 (2025). Davies, B. et al. Relationship Between Sarcopenia and Frailty in the Toledo Study of Healthy Aging: A Population Based Cross-Sectional Study. J. Am. Med. Dir. Assoc. 19 (4), 282–286 (2018). Sousa-Santos, A. R. et al. Sarcopenia, physical frailty, undernutrition and obesity cooccurrence among Portuguese community-dwelling older adults: results from Nutrition UP 65 cross-sectional study. BMJ Open. 10 (6), e033661 (2020). Taylor, J. A. et al. Multisystem physiological perspective of human frailty and its modulation by physical activity. Physiol. Rev. 103 (2), 1137–1191 (2023). Fried, L. P. et al. Frailty in older adults: evidence for a phenotype. J. Gerontol. Biol. Sci. Med. Sci. 56 (3), M146–M156 (2001). Chen, L. K. et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J. Am. Med. Dir. Assoc. 21 (3), 300–7e2 (2020). Hurt, R. T. et al. The Comparison of Segmental Multifrequency Bioelectrical Impedance Analysis and Dual-Energy X-ray Absorptiometry for Estimating Fat Free Mass and Percentage Body Fat in an Ambulatory Population. JPEN J. Parenter. Enter. Nutr. 45 (6), 1231–1238 (2021). Nakade, T. et al. Frailty Scale Captures Multidimensional Vulnerability and Predicts Mortality in Heart Failure. J. Am. Coll. Cardiol. 87 (1), 20–32 (2025). Patrizio, E., Calvani, R., Marzetti, E. & Cesari, M. Physical Functional Assessment in Older Adults. J. Frailty Aging . 10 (2), 141–149 (2021). Lee, D., Kim, M. & Won, C. W. Common and different characteristics among combinations of physical frailty and sarcopenia in community-dwelling older adults: The Korean Frailty and Aging Cohort Study. Geriatr. Gerontol. Int. 22 (1), 42–49 (2022). Cengiz, B. E., Ozer, N. T., Cengiz, C. B., Akgul, Y. S. S. & Akın, S. The Concurrent Challenges of Sarcopenia and Frailty: A 5-Year Mortality Risk Evaluation in Geriatric Patients with Type 2 Diabetes Mellitus. Diabetes Metab. J. (2025). Shimizu, K. et al. Prognostic Significance of Preoperative Respiratory Sarcopenia for Functional Recovery After Cardiovascular Surgery. Can. J. Cardiol. (2026). Álvarez-Bustos, A. et al. Role of sarcopenia in the frailty transitions in older adults: a population-based cohort study. J. Cachexia Sarcopenia Muscle . 13 (5), 2352–2360 (2022). Faxén-Irving, G. et al. Do Malnutrition, Sarcopenia and Frailty Overlap in Nursing-Home Residents? J. Frailty Aging . 10 (1), 17–21 (2021). Fernandes, A. L. et al. Obesity and low lean mass are associated with dysregulated IGFBP-3, inflammatory biomarkers, and physical impairment in older adult women with frailty. Front. Aging . 7 , 1765052 (2026). Liu, C-H. et al. Sarcopenia and MASLD: novel insights and the future. Nat. Rev. Endocrinol. 22 (3), 139–152 (2025). Chow, L. S. et al. Exerkines in health, resilience and disease. Nat. Rev. Endocrinol. 18 (5), 273–289 (2022). Gengxin, Y. et al. Association between sarcopenic obesity and risk of frailty in older adults: a systematic review and meta-analysis. Age Ageing ; 54 (1). (2025). Zhang, F-M., Zhang, X-Z., Yu, Z., Zhuang, C-L. & Han, L-L. Rethinking Muscle Aging Through the Lens of Fibro-Adipogenic Progenitors. Aging Dis. (2025). Ji, T., Li, Y. & Ma, L. Sarcopenic Obesity: An Emerging Public Health Problem. Aging Dis. 13 (2), 379–388 (2022). Piché, M. E., Tchernof, A. & Després, J. P. Obesity Phenotypes, Diabetes, and Cardiovascular Diseases. Circ. Res. 126 (11), 1477–1500 (2020). García-Esquinas, E. et al. Obesity, fat distribution, and risk of frailty in two population-based cohorts of older adults in Spain. Obes. (Silver Spring) . 23 (4), 847–855 (2015). Di Vincenzo, O. et al. European Association for the Study of Obesity Position Statement on the Diagnosis and Management of Obesity in Older Adults. Obes. Facts (2025). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 08 Apr, 2026 Editor invited by journal 25 Mar, 2026 Submission checks completed at journal 21 Mar, 2026 First submitted to journal 21 Mar, 2026 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-9131780","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":622642379,"identity":"ae717815-6661-49f2-8f57-34a4409d8871","order_by":0,"name":"Yu Ye","email":"","orcid":"","institution":"Chinese PLA Medical School","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Ye","suffix":""},{"id":622642380,"identity":"6dbcb285-9542-4897-bc84-4c14e2e0e4e7","order_by":1,"name":"Jinwei Liu","email":"","orcid":"","institution":"Chinese PLA Medical School","correspondingAuthor":false,"prefix":"","firstName":"Jinwei","middleName":"","lastName":"Liu","suffix":""},{"id":622642381,"identity":"607709c0-f63d-45c8-bb71-7dc6ccd6ce2c","order_by":2,"name":"Mengyu Cao","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mengyu","middleName":"","lastName":"Cao","suffix":""},{"id":622642382,"identity":"2b65191e-4f22-4407-bd53-b01b3c08277f","order_by":3,"name":"Shuaixuan Xu","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuaixuan","middleName":"","lastName":"Xu","suffix":""},{"id":622642383,"identity":"7cfe37ac-8cfe-4a29-be2d-39497970fa14","order_by":4,"name":"Fang Wang","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Wang","suffix":""},{"id":622642384,"identity":"c0d5eeb2-49b0-498c-bdd7-43c471382bdb","order_by":5,"name":"Zhen Zhang","email":"","orcid":"","institution":"Chinese PLA Medical School","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Zhang","suffix":""},{"id":622642385,"identity":"65694635-7ad5-452f-9647-436d1d7fccd8","order_by":6,"name":"Chenghao Chang","email":"","orcid":"","institution":"Chinese PLA Medical School","correspondingAuthor":false,"prefix":"","firstName":"Chenghao","middleName":"","lastName":"Chang","suffix":""},{"id":622642386,"identity":"a981f3bf-77de-44f0-92c0-0aac9c6e2f9d","order_by":7,"name":"Nihui Zhang","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nihui","middleName":"","lastName":"Zhang","suffix":""},{"id":622642387,"identity":"02019ff9-150e-4929-b1ab-22f3dbd24b14","order_by":8,"name":"Nan Peng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBAC+wYIbcfGzHzgwIcfRGgxOAChk/nZ2RIPzuwhQQvjzH4e48McbMRoOd57+HVBzR1mg8M8Hw4z8DDI84sdwK/FvudcmvWMY8/4DA7zbjhcYMFgOHN2AgFbJHLMjHnYDjODtczgYUgwuE1Ii/wboJZ/hxk3HOZ5cJiHjRgtEjzGj3nbDjPObOZhIFILT44ZM2/f4WR+ZjYDYCBLEOEX9jPGn3m+HbZj4z/8+MOHHzby/NIEtAABmwQSRwKnMmTA/IEoZaNgFIyCUTByAQC0OkTHToXnFAAAAABJRU5ErkJggg==","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Nan","middleName":"","lastName":"Peng","suffix":""}],"badges":[],"createdAt":"2026-03-16 01:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9131780/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9131780/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107243540,"identity":"ae64f6e5-fe38-44e4-b726-e2b953dbe90c","added_by":"auto","created_at":"2026-04-19 07:52:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":365609,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram of overlap between frailty and sarcopenia in different groups\u003c/p\u003e\n\u003cp\u003eA: Participants aged 60-69 years B: Participants aged 70-79 years C: Participants aged ≥80 years D: All participants\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9131780/v1/2d3850a14e8fe3cb4fafb370.png"},{"id":107484307,"identity":"bd03a54c-7e62-4897-83df-225d3fa3f3c9","added_by":"auto","created_at":"2026-04-22 02:31:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1225280,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9131780/v1/810e1797-7a3a-4a49-8d97-ba78f11f180b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Frailty and sarcopenia in Chinese community-dwelling older adults: prevalence, coexistence, and body composition differences","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFrailty is a geriatric syndrome characterized by a decline in multisystem physiological reserve, resulting in reduced resilience to stressors and an increased risk of adverse outcomes, including disability, prolonged hospitalization, and death. It therefore has a substantial negative impact on quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although the underlying mechanisms of frailty have not been fully elucidated, chronic inflammation, oxidative stress, and mitochondrial dysfunction have been proposed as key contributors. These processes may lead to structural and functional abnormalities in skeletal muscle, disturbances in fat metabolism, and dysregulation of other physiological systems, ultimately giving rise to clinical manifestations such as weakness, slow gait speed, and fatigue [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Sarcopenia is another common geriatric syndrome associated with poor outcomes, including falls, fractures, disability, and mortality, and it markedly impairs the ability of older adults to perform daily activities [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Sarcopenia is generally defined by declines in skeletal muscle mass, muscle strength, and physical performance [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. At present, however, there are still no universally accepted diagnostic criteria for either frailty or sarcopenia, and the reported prevalence of both conditions varies considerably depending on the assessment tools applied, ranging from 12% to 24% for frailty [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and from 9.9% to 40.4% for sarcopenia [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrailty and sarcopenia overlap substantially in terms of pathophysiology, clinical manifestations, diagnostic components, intervention strategies, and prognosis [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, whether they represent the same clinical entity remains uncertain. Early studies suggested that sarcopenia may mediate several adverse outcomes of frailty and may serve as an important pathway through which frailty progresses to disability [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Others have proposed that frailty and sarcopenia are \u0026ldquo;2 sides of the same coin,\u0026rdquo; arguing that distinguishing between them may be of limited practical significance because age-related geriatric syndromes cannot be fully explained by a single pathophysiological mechanism [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In contrast, other evidence indicates only partial overlap between the 2 conditions. Previous studies have shown that only 8.2%\u0026ndash;15.7% of individuals with sarcopenia were also frail, whereas approximately one-third of frail individuals did not have sarcopenia, suggesting that frailty and sarcopenia may be related but are not identical [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, grip strength and gait speed are included in the diagnostic criteria for both frailty and sarcopenia, although the corresponding cut-off values differ. Whether these differences in diagnostic thresholds influence the observed coexistence of the 2 conditions remains unclear [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgeing is accompanied by a progressive decline in skeletal muscle mass and a gradual increase in body fat, both of which may contribute to the development of frailty and sarcopenia [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, few studies have directly compared body composition characteristics, such as skeletal muscle mass and fat accumulation, between individuals with frailty and those with sarcopenia. Moreover, most previous studies examining the relationship between frailty and sarcopenia have focused on European and American populations, whereas evidence from Chinese populations remains limited. Whether frailty and sarcopenia exhibit similar patterns of coexistence in Chinese older adults therefore remains unknown.\u003c/p\u003e \u003cp\u003eAccordingly, this study aimed to investigate the prevalence and coexistence of frailty and sarcopenia among Chinese community-dwelling older adults and to explore factors associated with their coexistence. In addition, this study sought to examine whether differences in diagnostic thresholds influence the overlap between frailty and sarcopenia and to compare body composition characteristics between the 2 conditions. By clarifying the relationship between frailty and sarcopenia in a Chinese population, this study may provide evidence to support the assessment and management of geriatric syndromes in clinical practice.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003eCommunity-dwelling adults aged 60 years and older were recruited from communities in Beijing, China, between March and December 2022. The inclusion criteria were as follows: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;60 years; (2) residence in the community for more than 6 months; and (3) voluntary participation in the study. The exclusion criteria were as follows: (1) severe cognitive impairment; (2) severe visual or hearing impairment; (3) incomplete recovery from surgery within the previous 6 months; (4) acute illness; (5) inability to complete functional assessments because of pain; and (6) the presence of metal implants, such as pacemakers. The study was approved by the institutional ethics committee and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants before enrolment. A total of 993 individuals were initially recruited. After excluding 124 individuals who did not meet the eligibility criteria, 869 participants were ultimately included in the analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDiagnosis of frailty and sarcopenia\u003c/h3\u003e\n\u003cp\u003eFrailty was assessed using the Fried Frailty Phenotype (FP), which includes 5 components: unintentional weight loss, slow gait speed, reduced grip strength, low physical activity, and self-reported exhaustion. Each component was assigned a score of 1, yielding a total score ranging from 0 to 5. Participants were classified as robust (0 points), prefrail (1\u0026ndash;2 points), or frail (\u0026ge;\u0026thinsp;3 points) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria, which include skeletal muscle mass, muscle strength, and physical performance. Sarcopenia was defined as low skeletal muscle mass accompanied by either low grip strength or poor physical performance [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eSkeletal muscle mass and body fat assessment\u003c/h3\u003e\n\u003cp\u003eBioelectrical impedance analysis (BIA) has shown good agreement with dual-energy X-ray absorptiometry for the assessment of skeletal muscle mass (agreement coefficient\u0026thinsp;=\u0026thinsp;0.98) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. BIA estimates body composition by introducing alternating electrical currents of different frequencies into the body and measuring impedance in the limbs and trunk, thereby allowing calculation of skeletal muscle mass, fat mass, and body water in different body segments. This method is easy to perform and does not involve radiation exposure. In the present study, skeletal muscle mass, skeletal muscle mass index (SMI; skeletal muscle mass/height\u0026sup2;), and body fat indices, including percent body fat (PBF), visceral fat area (VFA), and fat mass index (FMI; fat mass/height\u0026sup2;), were measured using a body composition analyser (InBody 770; InBody Co., Ltd., Seoul, South Korea).\u003c/p\u003e\n\u003ch3\u003eGrip strength and gait speed assessment\u003c/h3\u003e\n\u003cp\u003eGrip strength was measured using a handheld dynamometer (Jamar Plus; Sammons Preston, USA). Participants were seated with the elbow flexed at 90\u0026deg; and the forearm in a neutral position. The grip position was standardized to the second handle position [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Two measurements were obtained from the dominant hand, with a 30-second interval between assessments. If the dominant hand could not be tested, the contralateral hand was used. The maximum value was recorded for analysis.\u003c/p\u003e \u003cp\u003eGait speed was assessed over a 6-m walking course within a 10-m walkway, with 2 m at each end used for acceleration and deceleration. Participants were instructed to walk at their usual pace from the 0-m mark to the 10-m mark. Timing started when the leading foot crossed the 2-m mark and stopped when it crossed the 8-m mark. The test was performed twice, and the average value was used for analysis.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SPSS version 25.0. Normally distributed continuous variables are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and were compared using the independent-samples t test or analysis of variance (ANOVA), as appropriate. Non-normally distributed continuous variables are presented as the median and interquartile range (IQR) and were analysed using the Kruskal-Wallis test. Categorical variables are presented as frequencies and percentages and were compared using the chi-square test. Logistic regression analysis was performed to examine the associations between body composition and frailty or sarcopenia. Age, sex, multimorbidity, and history of falls were included as covariates in the adjusted model. All statistical tests were two-sided, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eParticipants ranged in age from 60 to 97 years, with a mean age of 74.2 years. Individuals in the frailty and sarcopenia groups were predominantly aged 80 years or older. Among all participants, the prevalence of frailty, sarcopenia, and coexisting frailty and sarcopenia was 30.5%, 12.3%, and 9.9%, respectively. Among participants with frailty, 32.5% also had sarcopenia, whereas 80.4% of those with sarcopenia were also classified as frail. The baseline characteristics of the study population according to frailty and sarcopenia status are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The prevalence of multimorbidity was nearly 60% in both the frailty and sarcopenia groups. In addition, 17.7% and 17.8% of participants in the frailty and sarcopenia groups, respectively, had experienced a fall within the previous year, which was markedly higher than that in the healthy group (2.7%). The skeletal muscle mass index (SMI) was 6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 kg/m\u0026sup2; in the frailty group and 5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 kg/m\u0026sup2; in the sarcopenia group, both of which were lower than that in the healthy group (7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 kg/m\u0026sup2;).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\n \u003cp\u003eNeither frailty nor sarcopenia (n\u0026thinsp;=\u0026thinsp;583)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eFrailty\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;265)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eSarcopenia\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;107)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e550 (94.3)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e193 (72.8)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e68 (63.6)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (y)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e70.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e81.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e82.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e60\u0026ndash;69 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e295 (50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e31 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e6 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e70\u0026ndash;79 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e213 (36.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e55 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e23 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;80 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e75 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e179 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e78 (72.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e171.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e165.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e161.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e73.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e66.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e55.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e24.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18.5 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e10 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e13 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.5\u0026ndash;23.9 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e215 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e115 (43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e75 (70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e24.0-27.9 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e299 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e106 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e17 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;28.0 n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e64 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e34 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI (kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMM (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e24.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e21.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003ePBF (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e26.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eVFA (cm\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e91.4\u0026thinsp;\u0026plusmn;\u0026thinsp;27.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e103.9\u0026thinsp;\u0026plusmn;\u0026thinsp;36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e88.1\u0026thinsp;\u0026plusmn;\u0026thinsp;34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFMI (kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultimorbidity n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e192 (32.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e157 (59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e64 (59.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e251 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e145 (54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e57 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e148 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e78 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e32 (29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular diseases\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e83 (14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e63 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e23 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of falls n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e16 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e47 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e19 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHandgrip strength (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e38.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e25.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e22.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e6m walking time (s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\n \u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cem\u003eSMI\u003c/em\u003e skeletal muscle mass index, \u003cem\u003eSMM\u003c/em\u003e skeletal muscle mass, \u003cem\u003ePBF\u003c/em\u003e percent body fat, \u003cem\u003eVFA\u003c/em\u003e visceral fat area, \u003cem\u003eFMI\u003c/em\u003e fat mass index, \u003cem\u003eM\u003c/em\u003eultimorbidity a combination of 2 or more chronic diseases, \u003cem\u003eHistory of falls\u003c/em\u003e number of falls\u0026thinsp;\u0026ge;\u0026thinsp;1 in the last year\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eCoexistence of frailty and sarcopenia across age groups\u003c/h3\u003e\n\u003cp\u003eTo examine the effect of age on the coexistence of frailty and sarcopenia, participants were stratified into 3 age groups: 60\u0026ndash;69 years, 70\u0026ndash;79 years, and \u0026ge;\u0026thinsp;80 years. The prevalence of coexisting frailty and sarcopenia in the overall study population was 1.2%, 5.4%, and 25.3% in these 3 age groups, respectively, indicating a marked increase in coexistence with advancing age (Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eCoexistence of frailty and sarcopenia after adjustment of grip strength and gait speed cut-offs\u003c/h3\u003e\n\u003cp\u003eBecause the diagnostic cut-off values for grip strength and gait speed differ between the Fried Frailty Phenotype (FP) and the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria, we further examined whether these differences affected the observed coexistence of frailty and sarcopenia. When the grip strength and gait speed cut-offs in the FP were adjusted to match those of the AWGS 2019 criteria, the coexistence rate increased to 11.0%, representing a 1.1% increase from the original rate. Conversely, when the corresponding AWGS 2019 cut-offs were adjusted to match those of the FP, the coexistence rate was 9.7%, representing a 0.2% decrease from the original rate (Tables \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e and 2.2).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2.1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe concurrence of frailty and sarcopenia after adjusting the diagnostic cut-offs of frailty\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eFrailty\u003c/p\u003e\n \u003cp\u003e(adjusting cut-offs)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\n \u003cp\u003eSarcopenia\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNon-sarcopenia n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSarcopenia n(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNon-frailty n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e570(65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e11(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e581\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFrailty n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e192(22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e96(11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e869\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eAdjustment of diagnostic cut-offs for grip strength and gait speed of FP in line with AWGS 2019: grip strength (\u0026lt;\u0026thinsp;28kg for men and \u0026lt;\u0026thinsp;18kg for women), 6m walking speed (\u0026lt;\u0026thinsp;1.0m/s)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.2\u003c/strong\u003e The concurrence of frailty and sarcopenia after adjusting the diagnostic cut-offs of sarcopenia\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrailty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSarcopenia (adjusting cut-offs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 9px;\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eNon-sarcopenia n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eSarcopenia n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eNon-frailty n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e604（69.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e0（0.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eFrailty n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e181（20.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e84（9.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e869\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAdjustment of diagnostic cut-offs for grip strength and gait speed of AWGS 2019 in line with FP: subjects were assessed separately by BMI or height groups\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eAssociation of body composition with frailty and sarcopenia\u003c/h2\u003e\n \u003cp\u003eAmong the 286 participants with frailty or sarcopenia, 86 had both frailty and sarcopenia, 179 had frailty alone, and 21 had sarcopenia alone. To further explore the differences between these 2 conditions, participants with coexisting frailty and sarcopenia were excluded, and comparisons were made between the frailty-alone and sarcopenia-alone groups. The SMI was 7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 kg/m\u0026sup2; in the frailty-alone group and 5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 kg/m\u0026sup2; in the sarcopenia-alone group, with univariate analysis showing a significant difference between the groups. In addition, visceral fat area (VFA) and fat mass index (FMI) were higher in the frailty-alone group than in the sarcopenia-alone group (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the frailty alone group and the sarcopenia alone group \u003cem\u003eSMI\u003c/em\u003e skeletal muscle mass index, \u003cem\u003eSMM\u003c/em\u003e skeletal muscle mass, \u003cem\u003ePBF\u003c/em\u003e percent body fat, \u003cem\u003eVFA\u003c/em\u003e visceral fat area, \u003cem\u003eFMI\u003c/em\u003e fat mass index, \u003cem\u003eM\u003c/em\u003eultimorbidity a combination of 2 or more chronic diseases, \u003cem\u003eHistory of falls\u003c/em\u003e number of falls\u0026thinsp;\u0026ge;\u0026thinsp;1 in the last year\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFrailty alone\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSarcopenia alone\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e137(76.5)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e12(57.1)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(y)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e80.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e78.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e60\u0026ndash;69 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e27(15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e2(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e70\u0026ndash;79 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e40(22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e8(38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;80 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e112(62.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e11(52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight(cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e166.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e162.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight(kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e70.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e56.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI(kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e21.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18.5 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0(0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.5\u0026ndash;23.9 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e55(30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e15(71.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e24.0-27.9 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e92(51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;28.0 n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e32(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0(0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI(kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMM(kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e26.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e21.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003ePBF(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e29.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eVFA(cm\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e111.3\u0026thinsp;\u0026plusmn;\u0026thinsp;34.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e87.6\u0026thinsp;\u0026plusmn;\u0026thinsp;31.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFMI(kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultimorbidity n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e105(58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e12(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e101(56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e13(61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e53(29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e7(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular diseases\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e45(25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5(23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of falls n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e31(17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHandgrip strength(kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e27.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.658\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e6m walking time(s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the odds ratios (ORs) and 95% confidence intervals (CIs) for skeletal muscle and body fat indices. Differences in SMI, VFA, and FMI between the frailty-alone and sarcopenia-alone groups remained significant after adjustment for age and sex in Model 1 and after further adjustment for age, sex, multimorbidity, and history of falls in Model 2.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship between body composition and frailty or sarcopenia (frailty alone group as a reference)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.150(0.075\u0026ndash;0.301)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.006(0.001\u0026ndash;0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.006(0.001\u0026ndash;0.040)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003ePBF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.964(0.897\u0026ndash;1.036)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.938(0.868\u0026ndash;1.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.937(0.867\u0026ndash;1.012)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eVFA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.977(0.962\u0026ndash;0.993)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.975(0.959\u0026ndash;0.991)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.975(0.959\u0026ndash;0.991)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.744(0.572\u0026ndash;0.967)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.707(0.541\u0026ndash;0.924)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.703(0.537\u0026ndash;0.921)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\n \u003cp\u003e\u003cem\u003eSMI\u003c/em\u003e skeletal muscle mass index, \u003cem\u003ePBF\u003c/em\u003e percent body fat, \u003cem\u003eVFA\u003c/em\u003e visceral fat area, \u003cem\u003eFMI\u003c/em\u003e fat mass index, Model 1 adjusted for age and sex, and Model 2 adjusted for age, sex, multimorbidity and history of falls\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe relationship between frailty and sarcopenia remains incompletely understood, and whether they should be regarded as the same disease entity or as distinct but overlapping geriatric syndromes is still under debate. Clarifying this issue is of considerable clinical importance. If frailty and sarcopenia represent the same condition, screening and assessment in geriatric practice could be simplified, thereby improving efficiency and reducing the use of medical resources. Conversely, if they are distinct conditions, further evaluation of their differences would be necessary to guide tailored prevention and intervention strategies. Therefore, elucidating the relationship between frailty and sarcopenia is highly relevant to clinical decision-making in geriatric medicine. In the present study, we examined the coexistence of frailty and sarcopenia among community-dwelling adults aged 60 years and older in Beijing, China, and explored factors potentially associated with their overlap.\u003c/p\u003e \u003cp\u003eIn this study, the coexistence of frailty and sarcopenia was observed in 9.9% of all participants, suggesting that the overlap between these 2 conditions is relatively limited in the community setting. Previous studies have reported coexistence rates of 3.0% in the study by Daehyun et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and 9.8% in the study by Cengiz et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The prevalence of frailty and sarcopenia is influenced by multiple factors, including age, sex, ethnicity, geographic region, and the diagnostic criteria applied; accordingly, the coexistence of the 2 conditions varies across populations. Although coexisting frailty and sarcopenia is not highly prevalent, it remains clinically important. Recent evidence suggests that frail individuals with sarcopenia are more likely to experience adverse health outcomes than frail individuals without sarcopenia. In addition, the presence of sarcopenia has been associated with an increased incidence of cardiovascular and respiratory diseases in frail individuals and with higher risks of all-cause and cancer-related mortality [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A cohort study investigating frailty transitions further demonstrated that sarcopenia significantly increased the likelihood of transition from robust to prefrail status and from prefrail to frail status, indicating that sarcopenia may adversely influence the dynamic progression of frailty [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBoth frailty and sarcopenia are age-related geriatric syndromes, and the prevalence of both increases with advancing age. In the present study, coexistence was uncommon in younger participants but increased substantially with age. A Korean study investigating the relationship between frailty and sarcopenia reported a coexistence rate of 3.0% in a population with a mean age of 75.9 years [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], whereas another study with a mean participant age of 86.5 years reported a coexistence rate of 16.3% [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Taken together with our findings, these data suggest that the overlap between frailty and sarcopenia is strongly age-related and becomes more frequent in very old populations. This pattern may indicate that the distinction between frailty and sarcopenia is more evident in younger older adults and becomes less pronounced with advancing age.\u003c/p\u003e \u003cp\u003eThe Fried Frailty Phenotype and the AWGS 2019 criteria both incorporate grip strength and gait speed, although their cut-off values differ. Sousa-Santos et al. evaluated the coexistence of frailty, sarcopenia, obesity, and malnutrition and found that frailty combined with obesity affected the largest proportion of participants (10.5%), whereas the coexistence of frailty and sarcopenia was observed in only 2.2% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The authors suggested that inconsistency in the grip strength thresholds used to define frailty and sarcopenia might have contributed to the low overlap between the 2 conditions [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In the present study, we adjusted the cut-off values for grip strength and gait speed to determine whether the relatively low coexistence rate could be explained by differences in diagnostic thresholds. Notably, the change in coexistence was minimal regardless of whether the thresholds were standardized to those of frailty or sarcopenia, indicating that differences in grip strength and gait speed cut-offs had little effect on the observed overlap. This finding is consistent with that of Daehyun et al., who used the Fried Frailty Phenotype and the AWGS 2014 criteria and reported a coexistence rate of 2.4%; when the AWGS 2014 criteria were replaced with the AWGS 2019 criteria, the prevalence of coexistence increased by only 0.6% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Collectively, these findings suggest that the limited overlap between frailty and sarcopenia is unlikely to be explained solely by differences in diagnostic thresholds.\u003c/p\u003e \u003cp\u003eFrailty and sarcopenia are both characterized clinically by impaired physical function and, to varying degrees, reductions in skeletal muscle mass. A growing body of evidence indicates that skeletal muscle plays a central role in the pathophysiology of both conditions [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Skeletal muscle is essential not only for locomotion and activities of daily living but also as an endocrine organ capable of producing and releasing cytokines and peptides, known as myokines, in response to exercise and other physiological stimuli [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These myokines contribute to the regulation of nutrient sensing, transport, uptake, and utilization and are important for maintaining systemic cellular and physiological homeostasis. They also mediate interorgan communication and exert beneficial effects on cardiovascular, metabolic, immune, and nervous system function [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the present study, the skeletal muscle mass index was significantly higher in the frailty-alone group than in the sarcopenia-alone group, and this difference remained significant after multivariable adjustment. This finding suggests that the degree of muscle loss is more pronounced in sarcopenia than in frailty. Reduced skeletal muscle mass may impair myokine production and secretion, thereby contributing to the development of frailty or sarcopenia, whereas preservation of muscle mass may help mitigate disease risk. Our findings further support the notion that frailty and sarcopenia are related but distinct: frailty appears to involve multisystem impairment, whereas sarcopenia is characterized by more severe structural and functional deterioration of skeletal muscle.\u003c/p\u003e \u003cp\u003eObesity has been recognized as an important risk factor for frailty, partly because excess adiposity may promote chronic inflammation and thereby contribute to frailty progression [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Sarcopenic obesity is characterized by the coexistence of reduced skeletal muscle mass and increased fat accumulation, which may also involve fat infiltration into muscle tissue [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This condition has been associated with adverse outcomes such as falls, disability, and mortality, potentially through a vicious cycle linking muscle loss and fat accumulation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Body composition can be divided into protein, fat, water, and inorganic components. Compared with body mass index, the fat mass index more accurately reflects overall adiposity, whereas visceral fat area reflects abdominal fat accumulation around internal organs and is an indicator of central obesity. Excess visceral fat is associated with a higher risk of adverse outcomes, including diabetes and cardiovascular disease [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In the present study, both fat mass index and visceral fat area were significantly higher in the frailty-alone group than in the sarcopenia-alone group, suggesting that general and abdominal obesity were more prominent in frailty than in sarcopenia. This observation is supported by 2 cohort studies with 3.5 years of follow-up, which showed that both general obesity (pooled OR 1.73, 95% CI 1.18\u0026ndash;2.28) and abdominal obesity (pooled OR 1.67, 95% CI 1.09\u0026ndash;2.25) were associated with incident frailty [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In those studies, general obesity was associated with a higher risk of fatigue, low physical activity, and weakness, whereas abdominal obesity was specifically associated with weakness. Furthermore, both long-standing obesity and weight gain during ageing have been linked to frailty development, suggesting that early management of excess adiposity may help prevent frailty in older adults [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first study to investigate the coexistence of frailty and sarcopenia in a relatively large sample of Chinese community-dwelling older adults, thereby providing evidence relevant to the assessment and management of these conditions in Chinese populations. Nevertheless, several limitations should be acknowledged. First, because of the cross-sectional design, causal relationships between body composition and the coexistence of frailty and sarcopenia cannot be established. Second, the lack of universally accepted diagnostic criteria for frailty and sarcopenia may have influenced the estimated coexistence rate. Third, the range of baseline variables collected in this study was relatively limited, which may have constrained the adjustment for potential confounding factors in the statistical analyses. Future longitudinal cohort studies are warranted to examine the trajectories of frailty and sarcopenia over time and to clarify the impact of key indicators on clinical outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict-of-interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Key Research and Development Program of China (Grant No. 2018YFC2002004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproved by the Ethics Committee of the Chinese PLA General Hospital (Approval No. S2019-140-01), this study was conducted following the guidelines of the Declaration of Helsinki.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.Y. and J.L. contributed equally to this work. Y.Y., J.L., and N.P. conceived and designed the study. Y.Y., J.L., M.C., S.X., F.W., Z.Z., S.C., and N.Z. collected the data and performed the assessments. Y.Y. and J.L. performed the statistical analyses and drafted the manuscript. M.C., S.X., F.W., Z.Z., S.C., and N.Z. contributed to data interpretation and manuscript revision. N.P. supervised the study and critically revised the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due privacy reasons but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrkaby, A. R., Schwartz, A. W., Callahan, K. E. \u0026amp; Frailty \u003cem\u003eAnn. Intern. Med.\u003c/em\u003e ;\u003cb\u003e179\u003c/b\u003e(2):ITC17\u0026ndash;ITC32. (2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarros, D., Marques, E. A., Magalh\u0026atilde;es, J. \u0026amp; Carvalho, J. Energy metabolism and frailty: The potential role of exercise-induced myokines - A narrative review. \u003cem\u003eAgeing Res. Rev.\u003c/em\u003e \u003cb\u003e82\u003c/b\u003e, 101780 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao, X. \u0026amp; Cai, X. Aging-Driven Inter-Organ Crosstalk in Postmenopausal Osteoporosis: From Immunometabolic Drift to Multisystem Frailty. \u003cem\u003eFASEB J.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e (4), e71541 (2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe, D. et al. Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts. \u003cem\u003eJ. Cachexia Sarcopenia Muscle\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (1), 632\u0026ndash;641 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeyaraman, M. et al. Sarcopenia in Aging: Pathogenesis, Diagnosis, and Emerging Therapeutic Frontiers. \u003cem\u003eMol. Imaging Biol.\u003c/em\u003e ;\u003cb\u003e28\u003c/b\u003e(1). (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, Y. et al. Sarcopenia interventions targeted at improving muscle health in adults with cancer: a systematic review and meta-analysis. \u003cem\u003eFront. Nutr.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 1671720 (2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoogendijk, E. O. et al. Frailty: implications for clinical practice and public health. \u003cem\u003eLancet\u003c/em\u003e \u003cb\u003e394\u003c/b\u003e (10206), 1365\u0026ndash;1375 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan der Steen-Dieperink, M. J. M. M., Koekkoek, W. A. C. \u0026amp; Kouw, I. W. K. Sarcopenia and frailty in critical illness. \u003cem\u003eCurr. Opin. Clin. Nutr. Metab. Care\u003c/em\u003e. \u003cb\u003e28\u003c/b\u003e (3), 192\u0026ndash;199 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePicca, A., Coelho-Junior, H. J., Calvani, R., Marzetti, E. \u0026amp; Vetrano, D. L. Biomarkers shared by frailty and sarcopenia in older adults: A systematic review and meta-analysis. \u003cem\u003eAgeing Res. Rev.\u003c/em\u003e \u003cb\u003e73\u003c/b\u003e, 101530 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao, Y. et al. Exploration of Pathogenesis and Cutting-Edge Treatment Strategies of Sarcopenia: A Narrative Review. \u003cem\u003eClin. Interv Aging\u003c/em\u003e. \u003cb\u003e20\u003c/b\u003e, 659\u0026ndash;684 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDun, Y. et al. Effectiveness of a multicomponent exercise program to reverse pre-frailty in community-dwelling Chinese older adults: a randomised controlled trial. \u003cem\u003eAge Ageing\u003c/em\u003e ;\u003cb\u003e51\u003c/b\u003e(3). (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKilaitė, J. et al. Causal relationships between sarcopenia, frailty, and health outcomes: A systematic review of Mendelian randomization studies. \u003cem\u003eExp. Gerontol.\u003c/em\u003e \u003cb\u003e212\u003c/b\u003e, 112953 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVi\u0026ntilde;a, J. \u0026amp; Gomez-Cabrera, M. C. Molecular mechanism involved in sarcopenia and frailty, diagnosis and therapy. \u003cem\u003eMol. Aspects Med.\u003c/em\u003e \u003cb\u003e105\u003c/b\u003e, 101387 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies, B. et al. Relationship Between Sarcopenia and Frailty in the Toledo Study of Healthy Aging: A Population Based Cross-Sectional Study. \u003cem\u003eJ. Am. Med. Dir. Assoc.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (4), 282\u0026ndash;286 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSousa-Santos, A. R. et al. Sarcopenia, physical frailty, undernutrition and obesity cooccurrence among Portuguese community-dwelling older adults: results from Nutrition UP 65 cross-sectional study. \u003cem\u003eBMJ Open.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e (6), e033661 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor, J. A. et al. Multisystem physiological perspective of human frailty and its modulation by physical activity. \u003cem\u003ePhysiol. Rev.\u003c/em\u003e \u003cb\u003e103\u003c/b\u003e (2), 1137\u0026ndash;1191 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFried, L. P. et al. Frailty in older adults: evidence for a phenotype. \u003cem\u003eJ. Gerontol. Biol. Sci. Med. Sci.\u003c/em\u003e \u003cb\u003e56\u003c/b\u003e (3), M146\u0026ndash;M156 (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, L. K. et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. \u003cem\u003eJ. Am. Med. Dir. Assoc.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (3), 300\u0026ndash;7e2 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHurt, R. T. et al. The Comparison of Segmental Multifrequency Bioelectrical Impedance Analysis and Dual-Energy X-ray Absorptiometry for Estimating Fat Free Mass and Percentage Body Fat in an Ambulatory Population. \u003cem\u003eJPEN J. Parenter. Enter. Nutr.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (6), 1231\u0026ndash;1238 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakade, T. et al. Frailty Scale Captures Multidimensional Vulnerability and Predicts Mortality in Heart Failure. \u003cem\u003eJ. Am. Coll. Cardiol.\u003c/em\u003e \u003cb\u003e87\u003c/b\u003e (1), 20\u0026ndash;32 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatrizio, E., Calvani, R., Marzetti, E. \u0026amp; Cesari, M. Physical Functional Assessment in Older Adults. \u003cem\u003eJ. Frailty Aging\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (2), 141\u0026ndash;149 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee, D., Kim, M. \u0026amp; Won, C. W. Common and different characteristics among combinations of physical frailty and sarcopenia in community-dwelling older adults: The Korean Frailty and Aging Cohort Study. \u003cem\u003eGeriatr. Gerontol. Int.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (1), 42\u0026ndash;49 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCengiz, B. E., Ozer, N. T., Cengiz, C. B., Akgul, Y. S. S. \u0026amp; Akın, S. The Concurrent Challenges of Sarcopenia and Frailty: A 5-Year Mortality Risk Evaluation in Geriatric Patients with Type 2 Diabetes Mellitus. \u003cem\u003eDiabetes Metab. J.\u003c/em\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShimizu, K. et al. Prognostic Significance of Preoperative Respiratory Sarcopenia for Functional Recovery After Cardiovascular Surgery. \u003cem\u003eCan. J. Cardiol.\u003c/em\u003e (2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Aacute;lvarez-Bustos, A. et al. Role of sarcopenia in the frailty transitions in older adults: a population-based cohort study. \u003cem\u003eJ. Cachexia Sarcopenia Muscle\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e (5), 2352\u0026ndash;2360 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFax\u0026eacute;n-Irving, G. et al. Do Malnutrition, Sarcopenia and Frailty Overlap in Nursing-Home Residents? \u003cem\u003eJ. Frailty Aging\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (1), 17\u0026ndash;21 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFernandes, A. L. et al. Obesity and low lean mass are associated with dysregulated IGFBP-3, inflammatory biomarkers, and physical impairment in older adult women with frailty. \u003cem\u003eFront. Aging\u003c/em\u003e. \u003cb\u003e7\u003c/b\u003e, 1765052 (2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, C-H. et al. Sarcopenia and MASLD: novel insights and the future. \u003cem\u003eNat. Rev. Endocrinol.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (3), 139\u0026ndash;152 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChow, L. S. et al. Exerkines in health, resilience and disease. \u003cem\u003eNat. Rev. Endocrinol.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e (5), 273\u0026ndash;289 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGengxin, Y. et al. Association between sarcopenic obesity and risk of frailty in older adults: a systematic review and meta-analysis. \u003cem\u003eAge Ageing\u003c/em\u003e ;\u003cb\u003e54\u003c/b\u003e(1). (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, F-M., Zhang, X-Z., Yu, Z., Zhuang, C-L. \u0026amp; Han, L-L. Rethinking Muscle Aging Through the Lens of Fibro-Adipogenic Progenitors. \u003cem\u003eAging Dis.\u003c/em\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJi, T., Li, Y. \u0026amp; Ma, L. Sarcopenic Obesity: An Emerging Public Health Problem. \u003cem\u003eAging Dis.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (2), 379\u0026ndash;388 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePich\u0026eacute;, M. E., Tchernof, A. \u0026amp; Despr\u0026eacute;s, J. P. Obesity Phenotypes, Diabetes, and Cardiovascular Diseases. \u003cem\u003eCirc. Res.\u003c/em\u003e \u003cb\u003e126\u003c/b\u003e (11), 1477\u0026ndash;1500 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a-Esquinas, E. et al. Obesity, fat distribution, and risk of frailty in two population-based cohorts of older adults in Spain. \u003cem\u003eObes. (Silver Spring)\u003c/em\u003e. \u003cb\u003e23\u003c/b\u003e (4), 847\u0026ndash;855 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Vincenzo, O. et al. European Association for the Study of Obesity Position Statement on the Diagnosis and Management of Obesity in Older Adults. \u003cem\u003eObes. Facts\u003c/em\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"frailty, sarcopenia, prevalence, concurrence, ageing, skeletal muscle, body fat","lastPublishedDoi":"10.21203/rs.3.rs-9131780/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9131780/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFrailty and sarcopenia are closely related geriatric syndromes that share overlapping clinical features and pathophysiological mechanisms, yet whether they represent the same condition remains unclear. This study aimed to investigate the prevalence, coexistence, and associated body composition characteristics of frailty and sarcopenia in community-dwelling older adults in Beijing, China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study included 869 community-dwelling adults aged 60 years and older in Beijing, China. Frailty was defined using the Fried Frailty Phenotype, and sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 criteria. Age-stratified analyses were performed to assess changes in the coexistence of frailty and sarcopenia across age groups. To examine the effect of diagnostic thresholds on coexistence, the cut-offs for grip strength and gait speed were harmonized between the 2 criteria. Multinomial logistic regression was used to compare skeletal muscle and fat-related indices between participants with frailty alone and those with sarcopenia alone.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age of participants was 74.2 years. The prevalence of frailty, sarcopenia, and coexisting frailty and sarcopenia was 30.5%, 12.3%, and 9.9%, respectively. The coexistence rate increased markedly with age, from 1.2% in participants aged 60\u0026ndash;69 years to 5.4% in those aged 70\u0026ndash;79 years and 25.3% in those aged 80 years or older. Harmonizing the grip strength and gait speed thresholds changed the coexistence rate by no more than 1.1%. Compared with the sarcopenia-alone group, the frailty-alone group had a higher skeletal muscle mass index (7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 vs 5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 kg/m\u0026sup2;) as well as higher visceral fat area and fat mass index.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eFrailty was more prevalent than sarcopenia in this Beijing community sample, whereas their coexistence was relatively limited, suggesting that frailty and sarcopenia may not represent the same condition. Compared with sarcopenia, frailty was characterized by a less pronounced reduction in skeletal muscle mass and greater fat accumulation. These findings support the need to distinguish frailty from sarcopenia in the assessment and management of older adults.\u003c/p\u003e","manuscriptTitle":"Frailty and sarcopenia in Chinese community-dwelling older adults: prevalence, coexistence, and body composition differences","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 07:52:38","doi":"10.21203/rs.3.rs-9131780/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-08T10:29:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-08T10:24:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-25T19:11:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-21T05:58:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-21T05:53:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0d315e23-7378-4e5c-a19f-c7d50207e4a6","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66256778,"name":"Health sciences/Diseases"},{"id":66256779,"name":"Health sciences/Health care"},{"id":66256780,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-04-19T07:52:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 07:52:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9131780","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9131780","identity":"rs-9131780","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}