Association Between Body Roundness Index and Sarcopenia in Older Adults: Evidence from a Prospective Cohort Study Using CHARLS

Association Between Body Roundness Index and Sarcopenia in Older Adults: Evidence from a Prospective Cohort Study Using CHARLS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association Between Body Roundness Index and Sarcopenia in Older Adults: Evidence from a Prospective Cohort Study Using CHARLS Zhiqiang Xu, Qiannan Zhao, Fengxue Wang, Dongya Zhang, Lixia Xu, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6435227/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 Objective: This study aimed to investigate the association between the Body Roundness Index (BRI) and the risk of sarcopenia in older adults. Methods: A total of 2,798 individuals aged 60 years and older without sarcopenia at baseline were drawn from the China Health and Retirement Longitudinal Study (CHARLS). We investigated the relationship between BRI and sarcopenia using logistic regression analysis. Subgroup analysis was conducted to explore the association between BRI and sarcopenia risk across different groups. Additionally, restricted cubic spline (RCS) and threshold effect analyses were conducted to characterize the potential nonlinear association. Results: Over a median follow-up of two years, 358 participants (12.8%) developed sarcopenia. Quartile-based analysis revealed a significant inverse association between BRI and sarcopenia risk. After adjusting for confounders, individuals in the highest BRI quartile (Q4) exhibited a markedly lower likelihood of developing sarcopenia compared to the lowest quartile (Q1) (OR = 0.03, 95% CI: 0.02–0.06). RCS analysis indicated an L-shaped nonlinear association, with an inflection point at 4.461. The relationship between BRI and sarcopenia risk remained significant on both sides of this threshold. Furthermore, subgroup analysis did not indicate any significant interaction effects between BRI and sarcopenia risk (P for interaction > 0.05). Conclusion: This study suggests a significant negative association between BRI and the risk of sarcopenia, highlighting BRI as a potentially valuable indicator for assessing sarcopenia risk in older adults. Body Roundness Index (BRI) sarcopenia CHARLS prospective cohort study Figures Figure 1 Figure 2 Figure 3 Introduction Sarcopenia is an age-related skeletal muscle disorder characterized by progressive declines in muscle mass, strength, and physical function 1 . It not only impairs mobility but is also associated with various adverse clinical outcomes, including falls, fractures, exacerbation of chronic diseases, disability, and increased mortality risk 2 – 4 . In Asian countries, the prevalence of sarcopenia among older adults has been reported to be as high as 25.7% 5 . As the aging population grows, the incidence of sarcopenia is expected to increase. Early identification and assessment of sarcopenia are essential for geriatric health management and improving quality of life 6 . The Body Roundness Index (BRI) is a novel anthropometric measure primarily designed to estimate total body fat and visceral adipose tissue (VAT) volume 7 . Compared to traditional metrics, BRI provides a more accurate reflection of an individual's metabolic health status 8 – 11 . Previous studies have demonstrated a strong association between BRI and various chronic diseases, including cardiovascular disease, diabetes, and cancer 12 – 15 . Moreover, longitudinal studies have indicated that elevated BRI levels are significantly linked to increased all-cause mortality 16 . However, the potential relationship between BRI and sarcopenia remains underexplored. This study, based on the China Health and Retirement Longitudinal Study (CHARLS), employs a prospective cohort design to systematically evaluate the association between BRI and sarcopenia in older adults. Materials and methods Data Collection The China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative survey that gathers comprehensive data on various aspects, including demographic characteristics, health status, socioeconomic factors, and retirement-related issues 17 . The CHARLS dataset is available for download at the CHARLS official website ( http://charls.pku.edu.cn/en/ ). The Biomedical Ethi cs Review Committee of Peking University approved the collection of CHARLS data (IRB00001052-11015), and all participants signed an informed consent form. In this longitudinal study, we utilized data from the 2011 (Wave 1), which included a total of 17,708 participants. To ensure the appropriateness of the study population, we sequentially excluded the following individuals: (i) those younger than 60 years (n = 10,039); (ii) those with missing Body Roundness Index (BRI) data (n = 1,681); (iii)those with missing information on sarcopenia(n = 319); and (iv) those who had already been diagnosed with sarcopenia or probable sarcopenia at baseline (n = 1,554).As a result,4,112 eligible individuals were followed up for two years. Further exclusion of individuals with missing sarcopenia data during follow-up (n = 1,314) led to a final analytical sample of 2,798 participants (Fig. 1 ). Calculation of BRI BRI = 364.2- 365.5×√(1-(WC/2π) 2 /(0.5×height) 2 ) 7 Assessment of Sarcopenia Sarcopenia was evaluated based on the 2019 criteria set by the AWGS, incorporating assessments of appendicular skeletal muscle mass (ASM), muscle strength, and physical performance 18 .Low muscle strength was defined as grip strength below 28 kg for men and below 18 kg for women. Muscle mass was estimated using ASM, calculated based on a validated anthropometric equation for the Chinese population 19 : ASM = 0.193×Body weight (kg) + 0.107×Height (cm) − 4.157×Sex (Male = 1, Female = 2) − 0.037×Age (years) − 2.631 In this study, values of < 5.43 kg/m2 for women and < 7.08 kg/m2 for men were considered as low muscle mass. Low physical performance was defined as either five-time chair stand test ≥ 12 s or gait speed < 1.0 m/s 20 . Participants exhibiting normal muscle strength, mass, and performance were categorized as not having sarcopenia. Individuals with reduced muscle strength, regardless of physical performance, were considered to have possible sarcopenia, which was not classified as sarcopenia. Sarcopenia was diagnosed when low muscle mass was present along with either reduced muscle strength or impaired physical performance. Severe sarcopenia was identified when all three factors—low muscle mass, decreased strength, and diminished physical performance—were present. Both sarcopenia and severe sarcopenia were classified under sarcopenia. Covariates In this study, baseline data on sociodemographic characteristics and health-related factors were included as covariates. These variables encompassed of age, sex (male, female),residence (rural, urban),education level (elementary school or below, middle school, college or above),marital status(married, unmarried),smoking status, Alcohol consumption status, common chronic diseases, including cancer, heart disease, stroke, arthritis, dyslipidemia, asthma, hypertension, and diabetes, BMI(Table 1 ). Table 1 Baseline Characteristics of the older people in the China Health and Retirement Longitudinal Study 2011. Characteristic Total Non-sarcopenia sarcopenia p-value Participants, N 2798 2440 358 Age, years 66.32 ± 5.48 66.04 ± 5.27 68.19 ± 6.45 < 0.0001 Female, n (%) 1361(48.64) 1177(48.24) 184(51.40) Male, n (%) 1437(51.36) 1263(51.76) 174(48.60) 0.29 Residence place, n (%) < 0.01 Rural 1763(63.01) 1511(61.93) 252(70.39) Urban 1035(36.99) 929(38.07) 106(29.61) Education level, n (%) < 0.01 Elementary school and below 2228(79.66) 1918(78.64) 310(86.59) High school 521(18.63) 478(19.60) 43(12.01) College and higher 48( 1.72) 43( 1.76) 5( 1.40) Marital status, n (%) < 0.01 Married 2324(83.06) 2046(83.85) 278(77.65) Non-Married 474(16.94) 394(16.15) 80(22.35) Smoking, n (%) 1185(42.35) 1026(42.05) 159(44.41) 0.43 Drinking, n (%) 870(31.09) 764(31.31) 106(29.61) 0.56 Cancer, n (%) 17(0.61) 15(0.62) 2(0.56) 1.00 Heart disease, n (%) 427(15.39) 387(15.99) 40(11.30) 0.03 Stroke, n (%) 88(3.16) 77(3.17) 11(3.10) 1.00 Arthritis, n (%) 1099(39.42) 971(39.91) 128(36.06) 0.18 Dyslipidemia, n (%) 322(11.74) 312(13.05) 10(2.84) < 0.0001 Asthma, n (%) 152(5.47) 128(5.28) 24(6.78) 0.30 Hyptension, n (%) 934(33.57) 864(35.57) 70(19.83) < 0.0001 Diabetes, n (%) 220(7.93) 208(8.60) 12(3.39) < 0.01 BMI (kg/m 2 ) 24.18 ± 3.53 24.66 ± 3.36 20.94 ± 2.86 < 0.0001 BRI 4.57 ± 1.56 4.71 ± 1.54 3.58 ± 1.31 < 0.0001 Mean (SD) for continuous variables, % for categorical variables. Abbreviations: body mass index, BMI. body roundness index, BRI. Statistical Analysis Continuous variables were reported as mean ± standard deviation (SD), while categorical variables were presented as numbers (percentages). To assess the relationship between BRI and sarcopenia risk, multivariable logistic regression was utilized to estimate odds ratios (OR) with corresponding 95% confidence intervals (CI). Additionally, restricted cubic spline (RCS) analysis was applied to examine potential nonlinear associations. A threshold effect analysis was conducted to identify critical inflection points. Subgroup analysis was used to explore the impact of potential interactions on the relationship between BRI and sarcopenia. All statistical analyses were conducted using R software (version 4.4.0), with a significance level set at P < 0.05. Results Baseline characteristics of participants This study included a total of 2,798 baseline participants, comprising 1,437 males (51.36%) and 1,361 females (48.64%). The mean age of the study population was 66.32 ± 5.48 years. Over the 2-year follow-up period, a total of 358 participants were diagnosed with sarcopenia (Table 1 ). The relationship between BRI and Sarcopenia Logistic regression analysis was performed to assess the association between BRI and the risk of sarcopenia (Table 2 ). The crude model demonstrated a significant negative association between BRI and sarcopenia risk (OR = 0.09 [0.06, 0.14]). In Model 1, compared to the reference group, participants in Group 4 exhibited a significantly lower risk of sarcopenia (OR = 0.03 [0.02, 0.05]). This association remained statistically significant in Model 2 after further adjustments (OR = 0.03 [0.02, 0.05]). Trend analysis further confirmed this relationship, showing a significant decrease in sarcopenia risk with increasing BRI levels (trend p < 0.0001). Table 2 Odds ratios (95% Confidence Intervals) of BRI for sarcopenia in older adults from CHARLS (n = 2798). Model Crude model(95%CI) P-value Model Ⅰ(95%CI) P-value Model Ⅱ(95%CI) P-value BRI 0.61(0.56,0.66) <0.0001 0.53(0.48,0.58) <0.0001 0.53(0.48,0.58) <0.0001 BRI Quartiles Q1 Reference Reference Reference Q2 0.39(0.29,0.51) <0.0001 0.28(0.21,0.38) <0.0001 0.28(0.21,0.38) <0.0001 Q3 0.23(0.16,0.31) <0.0001 0.13(0.09,0.18) <0.0001 0.13(0.09,0.19) <0.0001 Q4 0.09(0.06,0.14) <0.0001 0.03(0.02,0.05) <0.0001 0.03(0.02,0.06) <0.0001 P for trend < 0.0001 < 0.0001 < 0.0001 Abbreviations: body roundness index, BRI. Model Ⅰ adjusted for age, sex. Model Ⅱ adjusted for age, sex, marital status, education level, residence place, diabetes, cancer, drink, smoke, arthritis. Nonlinear relationship and threshold effect analysis RCS analysis revealed a significant nonlinear association between BRI and the risk of sarcopenia (P < 0.001), characterized by an L-shaped negative association (Fig. 2 ). Further threshold effect analysis identified an inflection point at 4.461. The two-piecewise linear regression model showed that when BRI < 4.461, the risk of sarcopenia gradually decreased with increasing BRI (OR = 0.686, 95% CI: 0.603–0.781, P < 0.0001). However, when BRI ≥ 4.461, this association became more pronounced, with the adjusted OR decreasing to 0.372 (95% CI: 0.262–0.529, P < 0.0001)(Table 3 ). Table 3 Threshold effect analysis of body roundness index on sarcopenia using a two-piecewise linear regression model. Sarcopenia Adjust OR (95% CI) P-value BRI standard logistic model 0.53(0.483,0.582) <0.0001 two-piecewise linear model Inflection point 4.461 < 4.461 0.686(0.603, 0.781) 4.461 0.372(0.262, 0.529) <0.0001 Log-likelihood ratio <0.0001 Abbreviations: body roundness index, BRI. Subgroup Analysis Subgroup analysis was conducted to further explore the relationship between BRI and sarcopenia. The results indicated no significant interaction across subgroups (p for interaction > 0.05) (Fig. 3 ). Discussion This prospective cohort study tracked 2,798 Chinese adults aged 60 and above over a 2-year period to comprehensively assess the link between BRI and sarcopenia risk. Logistic regression analysis demonstrated a significant negative association between BRI and sarcopenia risk, indicating that lower BRI was associated with a higher risk of sarcopenia. RCS analysis indicated an L-shaped nonlinear association between BRI and sarcopenia risk. Subgroup analysis reinforced the consistency of this relationship across various demographic and health characteristics. To the best of our knowledge, this is the first prospective study exploring the connection between BRI and sarcopenia in the Chinese elderly population. BRI is an emerging anthropometric index that effectively represents body fat and visceral adipose tissue levels, outperforming conventional metrics in clinical risk evaluation 8 , 21 . Systematic reviews and meta-analyses have established a strong link between BRI and an elevated risk of metabolic syndrome, with BRI proving to be a superior predictor compared to BMI 22 . A longitudinal cohort study tracking BRI trajectories in middle-aged and older Chinese populations identified a notable correlation between BRI and heightened cardiovascular disease risk 23 . Additionally, an analysis of 11,980 U.S. adults (≥ 20 years) revealed a nonlinear positive association between BRI and the onset of diabetes and prediabetes, supporting its potential role as a predictive marker 24 . In a large-scale cohort study involving 42,022 participants, persistently high BRI levels were significantly linked to an increased cancer risk 25 . Furthermore, a nationwide cohort study uncovered a U-shaped association between BRI and all-cause mortality 16 . A cross-sectional study on the Weight-Adjusted Waist Index (WWI) and sarcopenia indicated that elevated WWI correlated with higher sarcopenia risk, suggesting it as a potential risk factor 26 . However, our findings indicate that a lower Body Roundness Index (BRI) is associated with a higher risk of sarcopenia. Previous studies have proposed the "obesity paradox," suggesting that obesity may, in some contexts, be linked to better clinical outcomes 27 , 28 . Our results are consistent with this perspective, demonstrating that an increase in BRI is significantly associated with a reduced risk of sarcopenia. Therefore, clinical assessments should focus on overall body composition rather than relying solely on Body Mass Index (BMI). Moreover, an appropriate level of body fat may have a protective role in sarcopenia prevention, underscoring the importance of considering individualized body fat composition rather than merely controlling body weight when developing sarcopenia intervention strategies. Several potential mechanisms may explain the association between a lower Body Roundness Index (BRI) and an increased risk of sarcopenia. A lower BRI may indicate insufficient fat reserves, which could exacerbate muscle catabolism and impair the maintenance of muscle mass. Adipose tissue is not only an energy storage organ but also an endocrine organ that secretes various hormones involved in muscle metabolism, such as leptin and adiponectin. These factors play critical roles in promoting muscle protein synthesis, maintaining proteostasis, and regulating anti-inflammatory responses 29 . Consequently, reduced fat levels may lead to decreased adipose-derived hormonal signaling, further impairing muscle protein synthesis and increasing the risk of sarcopenia. Moreover, inadequate adipose tissue may be associated with chronic catabolic conditions, such as chronic inflammation and cachexia 30 – 32 . In a cohort study of Chinese patients, elevated levels of inflammatory cytokines, including TWEAK and TNF-α, were linked to an increased risk of sarcopenia 33 . Given the multifactorial and complex etiology of sarcopenia, further research is needed to elucidate its biological mechanisms and develop effective prevention and intervention strategies. A major strength of this study is the use of a large longitudinal cohort, which allowed us to identify a stronger association between BRI and sarcopenia while adjusting for multiple confounding factors in the statistical analysis. However, this study also has certain limitations. First, the sample primarily consists of older Chinese adults, and the generalizability of the findings needs to be further validated in populations from other regions. Second, we are unable to fully elucidate the underlying biological mechanisms and causal relationship between BRI and sarcopenia. Given the inherent limitations of observational studies, the potential influence of residual confounding factors cannot be entirely ruled out. Future research should further investigate the causal relationship between BRI and sarcopenia. Conclusion This study, based on prospective data from an elderly Chinese population, found that individuals with lower BRI had a significantly increased risk of sarcopenia. This finding underscores the importance of considering body fat distribution in the assessment of muscle health in older adults. Future research should further investigate the applicability of BRI across different populations and incorporate biomarker analyses to elucidate the underlying mechanisms of fat-muscle interactions. Such insights could provide a new perspective for the early identification and intervention of sarcopenia. Declarations Data Availability Statement The CHARLS datasets can be downloaded at the CHARLS home page at http://charls.pku.edu.cn/en/ Funding This study was supported by Zhengzhou Medical and Health Technology Innovation Guidance Plan Project(2024YLZDJH268), Henan Medical Science and Technology Research Project (LHGJ20191042, LHGJ20200763). Author contributions ZX.X., QN.Z. and FX.W. wrote the main manuscript text. MY.P. supervised and provided guidance on the statistical analysis. LX.X., XC.L. and DY.Z. prepared figures 1-2. SN.C.,WW.G. and CH.H . prepared figures 3. RL.G.,MM.Z. and WZ.X. prepared table 1-2. GQ. Y. contributed to the conception and design of the study and supervised the research process. All authors reviewed the manuscript. Ethics approval All procedures involving human participants were conducted in accordance with the Declaration of Helsinki. The study was approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015), and written informed consent was obtained from all participants. Consent for publication The authors provide their consent for the publication of the study results. Declaration of competing interest The author reports no conflicts of interest in this work. Acknowledgments We would like to express our gratitude to the CHARLS team for their diligent efforts and selfless sharing of survey data, as well as to all participants. Clinical trial number: Not applicable. References Sayer AA, Cruz-Jentoft A. Sarcopenia definition, diagnosis and treatment: consensus is growing. Age Ageing. 2022;51(10):afac220. Lars L, Hans, et al. Sarcopenia: Aging-Related Loss of Muscle Mass and Function. PHYSIOLOGICAL REVIEWS; 2019. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31. Cruz-Jentoft AJ, Sayer AA, Sarcopenia. Lancet. 2019;393(10191):2636–46. Kitamura A, Seino S, Abe T et al. Sarcopenia: prevalence, associated factors, and the risk of mortality and disability in Japanese older adults. Journal of Cachexia Sarcopenia and Muscle.. Papadopoulou SK. Sarcopenia: A Contemporary Health Problem among Older Adult Populations. Nutrients. 2020;12(5):1293. Thomas DM, Bredlau C, Bosy-Westphal A, et al. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obes (Silver Spring). 2013;21(11):2264–71. Liu Y, Liu X, Guan H, et al. Body Roundness Index Is a Superior Obesity Index in Predicting Diabetes Risk Among Hypertensive Patients: A Prospective Cohort Study in China. Front Cardiovasc Med. 2021;8:736073. Feng J, He S, Chen X. Body Adiposity Index and Body Roundness Index in Identifying Insulin Resistance Among Adults Without Diabetes. Am J Med Sci. 2019;357(2):116–23. Pan X, Liu F, Fan J, et al. Association of Body Roundness Index and A Body Shape Index with Obstructive Sleep Apnea: insights from NHANES 2015–2018 data. Front Nutr. 2024;11:1492673. Wu L, Pu H, Zhang M, Hu H, Wan Q. Non-linear relationship between the body roundness index and incident type 2 diabetes in Japan: a secondary retrospective analysis. J Transl Med. 2022;20(1):110. Damluji AA, Alfaraidhy M, AlHajri N, et al. Sarcopenia Cardiovasc Dis Circulation. 2023;147(20):1534–53. Yang M, Liu J, Shen Q, et al. Body Roundness Index Trajectories and the Incidence of Cardiovascular Disease: Evidence From the China Health and Retirement Longitudinal Study. J Am Heart Assoc. 2024;13(19):e034768. Wu M, Yu X, Xu L, Wu S, Tian Y. Associations of longitudinal trajectories in body roundness index with mortality and cardiovascular outcomes: a cohort study. Am J Clin Nutr. 2022;115(3):671–8. Wang P, Fan Y, Gao H, Wang B. Body roundness index as a predictor of all-cause and cardiovascular mortality in patients with diabetes and prediabetes. Diabetes Res Clin Pract. 2025;219:111958. Zhang X, Ma N, Lin Q, et al. Body Roundness Index and All-Cause Mortality Among US Adults. JAMA Netw Open. 2024;7(6):e2415051. Zhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol. 2014;43(1):61–8. Chen LK, Woo J, Assantachai P, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21(3):300–e3072. Wen X, Wang M, Jiang CM, Zhang YM. Anthropometric equation for estimation of appendicular skeletal muscle mass in Chinese adults. Asia Pac J Clin Nutr. 2011;20(4):551–6. Wu X, Li X, Xu M, Zhang Z, He L, Li Y. Sarcopenia prevalence and associated factors among older Chinese population: Findings from the China Health and Retirement Longitudinal Study. PLoS ONE. 2021;16(3):e0247617. Wei C, Zhang G. Association between body roundness index (BRI) and gallstones: results of the 2017–2020 national health and nutrition examination survey (NHANES). BMC Gastroenterol. 2024;24(1):192. Rico-Martín S, Calderón-García JF, Sánchez-Rey P, Franco-Antonio C, Martínez Alvarez M, Sánchez, Muñoz-Torrero JF. Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta-analysis. Obes Rev. 2020. 21(7): e13023. Zhang X, Ding L, Hu H, He H, Xiong Z, Zhu X. Associations of Body-Roundness Index and Sarcopenia with Cardiovascular Disease among Middle-Aged and Older Adults: Findings from CHARLS. J Nutr Health Aging. 2023;27(11):953–9. Qiu L, Xiao Z, Fan B, Li L, Sun G. Association of body roundness index with diabetes and prediabetes in US adults from NHANES 2007–2018: a cross-sectional study. Lipids Health Dis. 2024;23(1):252. Chen Y, Wang Y, Zheng X, et al. Body Roundness Index Trajectories and the Risk of Cancer: A Cohort Study. Cancer Med. 2024;13(23):e70447. Zhou H, Su H, Gong Y, et al. The association between weight-adjusted-waist index and sarcopenia in adults: a population-based study. Sci Rep. 2024;14(1):10943. Wang S, Ren J. Obesity Paradox in Aging: From Prevalence to Pathophysiology. Prog Cardiovasc Dis. 2018;61(2):182–9. Lu B, et al. Association between atherogenic index of plasma, body mass index, and sarcopenia: a cross-sectional and longitudinal analysis study based on older adults in China. Aging Clin Exp Res. 2025;37:122. Lu W, Feng W, Lai J, Yuan D, Xiao W, Li Y. Role of adipokines in sarcopenia. Chin Med J (Engl). 2023;136(15):1794–804. Furman D, Campisi J, Verdin E, et al. Chronic inflammation in the etiology of disease across the life span. Nat Med. 2019;25(12):1822–32. Molfino A, Imbimbo G, Muscaritoli M. Metabolic and histomorphological changes of adipose tissue in cachexia. Curr Opin Clin Nutr Metab Care. 2023;26(3):235–42. Rolland Y, van Abellan G, Gillette-Guyonnet S, Vellas B. Cachexia versus sarcopenia. Curr Opin Clin Nutr Metab Care. 2011;14(1):15–21. Li CW, Yu K, Shyh-Chang N, et al. Circulating factors associated with sarcopenia during ageing and after intensive lifestyle intervention. J Cachexia Sarcopenia Muscle. 2019;10(3):586–600. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 15 May, 2025 Editor invited by journal 17 Apr, 2025 Editor assigned by journal 14 Apr, 2025 Submission checks completed at journal 14 Apr, 2025 First submitted to journal 12 Apr, 2025 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-6435227","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457016721,"identity":"ee9739b2-9d4c-410b-9631-daf185832b60","order_by":0,"name":"Zhiqiang Xu","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zhiqiang","middleName":"","lastName":"Xu","suffix":""},{"id":457016722,"identity":"7092d201-19ce-41a5-818a-c75b6822b47e","order_by":1,"name":"Qiannan Zhao","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiannan","middleName":"","lastName":"Zhao","suffix":""},{"id":457016723,"identity":"dffa5f33-6499-450a-8c7d-b81d570a9795","order_by":2,"name":"Fengxue Wang","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fengxue","middleName":"","lastName":"Wang","suffix":""},{"id":457016724,"identity":"89fd7cbb-1a63-4bfb-94d5-9e3f9fb7d44c","order_by":3,"name":"Dongya Zhang","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Dongya","middleName":"","lastName":"Zhang","suffix":""},{"id":457016725,"identity":"c565f2a5-d06f-4901-88c6-004b71ebc3f9","order_by":4,"name":"Lixia Xu","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Lixia","middleName":"","lastName":"Xu","suffix":""},{"id":457016726,"identity":"8b3f8065-b13f-459c-a7c4-cb4bdea6287c","order_by":5,"name":"Xiaochang Li","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xiaochang","middleName":"","lastName":"Li","suffix":""},{"id":457016727,"identity":"c217364a-f38c-496d-8559-cc9133b3487f","order_by":6,"name":"Caihong He","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Caihong","middleName":"","lastName":"He","suffix":""},{"id":457016728,"identity":"eb97e773-b725-4dc3-863c-4abcd8c44476","order_by":7,"name":"Ruilei Guan","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Ruilei","middleName":"","lastName":"Guan","suffix":""},{"id":457016729,"identity":"50ba2c03-f7b2-4b59-9b3f-742715e1af83","order_by":8,"name":"Wenwen Gao","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wenwen","middleName":"","lastName":"Gao","suffix":""},{"id":457016730,"identity":"04a5e869-b168-4fa1-9a53-c072a29c68b2","order_by":9,"name":"Manman Zhou","email":"","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Manman","middleName":"","lastName":"Zhou","suffix":""},{"id":457016731,"identity":"faadf606-24e5-47ef-8aa9-472cc22b29e8","order_by":10,"name":"Minyue Pei","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Minyue","middleName":"","lastName":"Pei","suffix":""},{"id":457016732,"identity":"40002667-9b0e-469d-831f-1260b8e939e0","order_by":11,"name":"Weizhong Xiao","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weizhong","middleName":"","lastName":"Xiao","suffix":""},{"id":457016733,"identity":"a2ff5f54-312f-43b5-877a-540f43134cff","order_by":12,"name":"Gaiqing Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYBADOTb29gOkaTHm4zmTQJqWxHkSDgbEKZWfkWMmzfPLOr1NgiGB4UfFNsJaGHvOmEnz9qXntkk3HgBybhPWwszeA9TSczi3TeZAAjNjGxFa2Jh5wFrS2SQSDIjTwgOyhefH4QTitUjwHCu2nNuQbtgGDOSDRPlFfkbyxhtv/ljLy7e3H3zwo4IILQwMHCZSvG3MYOYBYtQDAfvjjz/+MBOpeBSMglEwCkYkAAAJaDiYJvh8qAAAAABJRU5ErkJggg==","orcid":"","institution":"Zhengzhou Central Hospital Affiliated to Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"Gaiqing","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-04-12 14:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6435227/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6435227/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83127352,"identity":"9757d6d1-9bd4-45f9-9821-bb94feba6b32","added_by":"auto","created_at":"2025-05-20 09:52:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108346,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of study participants.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6435227/v1/7c692a834709f974735076e5.png"},{"id":83127357,"identity":"373e4256-a7dc-440c-a57b-b3a597461d8b","added_by":"auto","created_at":"2025-05-20 09:52:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":196084,"visible":true,"origin":"","legend":"\u003cp\u003eRCS curve fts the Association of BRI with Sarcopenia. Adjusted for age, sex, marital status, education level, residence place, diabetes, cancer, drink, smoke, arthritis.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6435227/v1/8bb5f0c606af414a6376c2d8.png"},{"id":83127355,"identity":"8ba7d2cf-2c78-4914-9ed6-3fd1998bf43d","added_by":"auto","created_at":"2025-05-20 09:52:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":105647,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of the association between BRI and Sarcopenia. Adjusted for age, sex, marital status, education level, residence place, diabetes, cancer, drink, smoke, arthritis.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6435227/v1/0de1f75e462ca048d0cb391d.png"},{"id":83129495,"identity":"e52a5673-4a88-4a26-8824-97f7f74a83fe","added_by":"auto","created_at":"2025-05-20 10:08:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1272697,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6435227/v1/4792ff84-d399-459d-a026-dfec93dc4d48.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Body Roundness Index and Sarcopenia in Older Adults: Evidence from a Prospective Cohort Study Using CHARLS","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSarcopenia is an age-related skeletal muscle disorder characterized by progressive declines in muscle mass, strength, and physical function\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. It not only impairs mobility but is also associated with various adverse clinical outcomes, including falls, fractures, exacerbation of chronic diseases, disability, and increased mortality risk\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. In Asian countries, the prevalence of sarcopenia among older adults has been reported to be as high as 25.7%\u003csup\u003e5\u003c/sup\u003e. As the aging population grows, the incidence of sarcopenia is expected to increase. Early identification and assessment of sarcopenia are essential for geriatric health management and improving quality of life\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Body Roundness Index (BRI) is a novel anthropometric measure primarily designed to estimate total body fat and visceral adipose tissue (VAT) volume\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Compared to traditional metrics, BRI provides a more accurate reflection of an individual's metabolic health status\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Previous studies have demonstrated a strong association between BRI and various chronic diseases, including cardiovascular disease, diabetes, and cancer\u003csup\u003e\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Moreover, longitudinal studies have indicated that elevated BRI levels are significantly linked to increased all-cause mortality\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, the potential relationship between BRI and sarcopenia remains underexplored. This study, based on the China Health and Retirement Longitudinal Study (CHARLS), employs a prospective cohort design to systematically evaluate the association between BRI and sarcopenia in older adults.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eThe China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative survey that gathers comprehensive data on various aspects, including demographic characteristics, health status, socioeconomic factors, and retirement-related issues\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The CHARLS dataset is available for download at the CHARLS official website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://charls.pku.edu.cn/en/\u003c/span\u003e\u003cspan address=\"http://charls.pku.edu.cn/en/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Biomedical Ethi cs Review Committee of Peking University approved the collection of CHARLS data (IRB00001052-11015), and all participants signed an informed consent form.\u003c/p\u003e \u003cp\u003eIn this longitudinal study, we utilized data from the 2011 (Wave 1), which included a total of 17,708 participants. To ensure the appropriateness of the study population, we sequentially excluded the following individuals: (i) those younger than 60 years (n\u0026thinsp;=\u0026thinsp;10,039); (ii) those with missing Body Roundness Index (BRI) data (n\u0026thinsp;=\u0026thinsp;1,681); (iii)those with missing information on sarcopenia(n\u0026thinsp;=\u0026thinsp;319); and (iv) those who had already been diagnosed with sarcopenia or probable sarcopenia at baseline (n\u0026thinsp;=\u0026thinsp;1,554).As a result,4,112 eligible individuals were followed up for two years. Further exclusion of individuals with missing sarcopenia data during follow-up (n\u0026thinsp;=\u0026thinsp;1,314) led to a final analytical sample of 2,798 participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCalculation of BRI\u003c/h3\u003e\n\u003cp\u003eBRI\u0026thinsp;=\u0026thinsp;364.2- 365.5\u0026times;\u0026radic;(1-(WC/2π)\u003csup\u003e2\u003c/sup\u003e /(0.5\u0026times;height)\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eAssessment of Sarcopenia\u003c/h3\u003e\n\u003cp\u003eSarcopenia was evaluated based on the 2019 criteria set by the AWGS, incorporating assessments of appendicular skeletal muscle mass (ASM), muscle strength, and physical performance\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.Low muscle strength was defined as grip strength below 28 kg for men and below 18 kg for women. Muscle mass was estimated using ASM, calculated based on a validated anthropometric equation for the Chinese population\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e \u003cp\u003eASM\u0026thinsp;=\u0026thinsp;0.193\u0026times;Body weight (kg)\u0026thinsp;+\u0026thinsp;0.107\u0026times;Height (cm)\u0026thinsp;\u0026minus;\u0026thinsp;4.157\u0026times;Sex (Male\u0026thinsp;=\u0026thinsp;1, Female\u0026thinsp;=\u0026thinsp;2)\u0026thinsp;\u0026minus;\u0026thinsp;0.037\u0026times;Age (years)\u0026thinsp;\u0026minus;\u0026thinsp;2.631\u003c/p\u003e \u003cp\u003eIn this study, values of \u0026lt;\u0026thinsp;5.43 kg/m2 for women and \u0026lt;\u0026thinsp;7.08 kg/m2 for men were considered as low muscle mass. Low physical performance was defined as either five-time chair stand test\u0026thinsp;\u0026ge;\u0026thinsp;12 s or gait speed\u0026thinsp;\u0026lt;\u0026thinsp;1.0 m/s\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eParticipants exhibiting normal muscle strength, mass, and performance were categorized as not having sarcopenia. Individuals with reduced muscle strength, regardless of physical performance, were considered to have possible sarcopenia, which was not classified as sarcopenia. Sarcopenia was diagnosed when low muscle mass was present along with either reduced muscle strength or impaired physical performance. Severe sarcopenia was identified when all three factors\u0026mdash;low muscle mass, decreased strength, and diminished physical performance\u0026mdash;were present. Both sarcopenia and severe sarcopenia were classified under sarcopenia.\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eIn this study, baseline data on sociodemographic characteristics and health-related factors were included as covariates. These variables encompassed of age, sex (male, female),residence (rural, urban),education level (elementary school or below, middle school, college or above),marital status(married, unmarried),smoking status, Alcohol consumption status, common chronic diseases, including cancer, heart disease, stroke, arthritis, dyslipidemia, asthma, hypertension, and diabetes, BMI(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the older people in the China Health and Retirement Longitudinal Study 2011.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-sarcopenia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esarcopenia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipants, N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2798\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2440\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e358\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.04\u0026thinsp;\u0026plusmn;\u0026thinsp;5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.19\u0026thinsp;\u0026plusmn;\u0026thinsp;6.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1361(48.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1177(48.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e184(51.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1437(51.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1263(51.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e174(48.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence place, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1763(63.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1511(61.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e252(70.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1035(36.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e929(38.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106(29.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElementary school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2228(79.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1918(78.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e310(86.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e521(18.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e478(19.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(12.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege and higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48( 1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43( 1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5( 1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2324(83.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2046(83.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e278(77.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e474(16.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e394(16.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80(22.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1185(42.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1026(42.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159(44.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrinking, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e870(31.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e764(31.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106(29.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCancer, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeart disease, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e427(15.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e387(15.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(11.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStroke, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88(3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77(3.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(3.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eArthritis, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1099(39.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e971(39.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128(36.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDyslipidemia, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e322(11.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e312(13.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAsthma, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152(5.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128(5.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(6.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHyptension, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e934(33.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e864(35.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70(19.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220(7.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208(8.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(3.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBRI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eMean (SD) for continuous variables, % for categorical variables.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations:\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ebody mass index, BMI. body roundness index, BRI.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), while categorical variables were presented as numbers (percentages). To assess the relationship between BRI and sarcopenia risk, multivariable logistic regression was utilized to estimate odds ratios (OR) with corresponding 95% confidence intervals (CI). Additionally, restricted cubic spline (RCS) analysis was applied to examine potential nonlinear associations. A threshold effect analysis was conducted to identify critical inflection points. Subgroup analysis was used to explore the impact of potential interactions on the relationship between BRI and sarcopenia. All statistical analyses were conducted using R software (version 4.4.0), with a significance level set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of participants\u003c/h2\u003e \u003cp\u003eThis study included a total of 2,798 baseline participants, comprising 1,437 males (51.36%) and 1,361 females (48.64%). The mean age of the study population was 66.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.48 years. Over the 2-year follow-up period, a total of 358 participants were diagnosed with sarcopenia (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe relationship between BRI and Sarcopenia\u003c/h3\u003e\n\u003cp\u003eLogistic regression analysis was performed to assess the association between BRI and the risk of sarcopenia (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The crude model demonstrated a significant negative association between BRI and sarcopenia risk (OR\u0026thinsp;=\u0026thinsp;0.09 [0.06, 0.14]). In Model 1, compared to the reference group, participants in Group 4 exhibited a significantly lower risk of sarcopenia (OR\u0026thinsp;=\u0026thinsp;0.03 [0.02, 0.05]). This association remained statistically significant in Model 2 after further adjustments (OR\u0026thinsp;=\u0026thinsp;0.03 [0.02, 0.05]). Trend analysis further confirmed this relationship, showing a significant decrease in sarcopenia risk with increasing BRI levels (trend p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOdds ratios (95% Confidence Intervals) of BRI for sarcopenia in older adults from CHARLS \u003cb\u003e(n\u0026thinsp;=\u0026thinsp;2798).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude model(95%CI) P-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel Ⅰ(95%CI) P-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel Ⅱ(95%CI) P-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61(0.56,0.66) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53(0.48,0.58) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53(0.48,0.58) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRI Quartiles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39(0.29,0.51) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28(0.21,0.38) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28(0.21,0.38) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23(0.16,0.31) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13(0.09,0.18) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13(0.09,0.19) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.09(0.06,0.14) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03(0.02,0.05) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03(0.02,0.06) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: body roundness index, BRI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel Ⅰ adjusted for age, sex.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel Ⅱ adjusted for age, sex, marital status, education level, residence place, diabetes, cancer, drink, smoke, arthritis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eNonlinear relationship and threshold effect analysis\u003c/h2\u003e \u003cp\u003eRCS analysis revealed a significant nonlinear association between BRI and the risk of sarcopenia (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), characterized by an L-shaped negative association (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Further threshold effect analysis identified an inflection point at 4.461. The two-piecewise linear regression model showed that when BRI\u0026thinsp;\u0026lt;\u0026thinsp;4.461, the risk of sarcopenia gradually decreased with increasing BRI (OR\u0026thinsp;=\u0026thinsp;0.686, 95% CI: 0.603\u0026ndash;0.781, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, when BRI\u0026thinsp;\u0026ge;\u0026thinsp;4.461, this association became more pronounced, with the adjusted OR decreasing to 0.372 (95% CI: 0.262\u0026ndash;0.529, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)(Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThreshold effect analysis of body roundness index on sarcopenia using a two-piecewise linear regression model.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSarcopenia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjust OR (95% CI) P-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003estandard logistic model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.53(0.483,0.582) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etwo-piecewise linear model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflection point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.686(0.603, 0.781) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.372(0.262, 0.529) \u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog-likelihood ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eAbbreviations: body roundness index, BRI.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup Analysis\u003c/h2\u003e \u003cp\u003eSubgroup analysis was conducted to further explore the relationship between BRI and sarcopenia. The results indicated no significant interaction across subgroups (p for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis prospective cohort study tracked 2,798 Chinese adults aged 60 and above over a 2-year period to comprehensively assess the link between BRI and sarcopenia risk. Logistic regression analysis demonstrated a significant negative association between BRI and sarcopenia risk, indicating that lower BRI was associated with a higher risk of sarcopenia. RCS analysis indicated an L-shaped nonlinear association between BRI and sarcopenia risk. Subgroup analysis reinforced the consistency of this relationship across various demographic and health characteristics. To the best of our knowledge, this is the first prospective study exploring the connection between BRI and sarcopenia in the Chinese elderly population.\u003c/p\u003e \u003cp\u003eBRI is an emerging anthropometric index that effectively represents body fat and visceral adipose tissue levels, outperforming conventional metrics in clinical risk evaluation\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Systematic reviews and meta-analyses have established a strong link between BRI and an elevated risk of metabolic syndrome, with BRI proving to be a superior predictor compared to BMI\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. A longitudinal cohort study tracking BRI trajectories in middle-aged and older Chinese populations identified a notable correlation between BRI and heightened cardiovascular disease risk\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Additionally, an analysis of 11,980 U.S. adults (\u0026ge;\u0026thinsp;20 years) revealed a nonlinear positive association between BRI and the onset of diabetes and prediabetes, supporting its potential role as a predictive marker\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In a large-scale cohort study involving 42,022 participants, persistently high BRI levels were significantly linked to an increased cancer risk\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Furthermore, a nationwide cohort study uncovered a U-shaped association between BRI and all-cause mortality\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. A cross-sectional study on the Weight-Adjusted Waist Index (WWI) and sarcopenia indicated that elevated WWI correlated with higher sarcopenia risk, suggesting it as a potential risk factor\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. However, our findings indicate that a lower Body Roundness Index (BRI) is associated with a higher risk of sarcopenia. Previous studies have proposed the \"obesity paradox,\" suggesting that obesity may, in some contexts, be linked to better clinical outcomes\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Our results are consistent with this perspective, demonstrating that an increase in BRI is significantly associated with a reduced risk of sarcopenia. Therefore, clinical assessments should focus on overall body composition rather than relying solely on Body Mass Index (BMI). Moreover, an appropriate level of body fat may have a protective role in sarcopenia prevention, underscoring the importance of considering individualized body fat composition rather than merely controlling body weight when developing sarcopenia intervention strategies.\u003c/p\u003e \u003cp\u003eSeveral potential mechanisms may explain the association between a lower Body Roundness Index (BRI) and an increased risk of sarcopenia. A lower BRI may indicate insufficient fat reserves, which could exacerbate muscle catabolism and impair the maintenance of muscle mass. Adipose tissue is not only an energy storage organ but also an endocrine organ that secretes various hormones involved in muscle metabolism, such as leptin and adiponectin. These factors play critical roles in promoting muscle protein synthesis, maintaining proteostasis, and regulating anti-inflammatory responses\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Consequently, reduced fat levels may lead to decreased adipose-derived hormonal signaling, further impairing muscle protein synthesis and increasing the risk of sarcopenia. Moreover, inadequate adipose tissue may be associated with chronic catabolic conditions, such as chronic inflammation and cachexia\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. In a cohort study of Chinese patients, elevated levels of inflammatory cytokines, including TWEAK and TNF-α, were linked to an increased risk of sarcopenia\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Given the multifactorial and complex etiology of sarcopenia, further research is needed to elucidate its biological mechanisms and develop effective prevention and intervention strategies.\u003c/p\u003e \u003cp\u003eA major strength of this study is the use of a large longitudinal cohort, which allowed us to identify a stronger association between BRI and sarcopenia while adjusting for multiple confounding factors in the statistical analysis. However, this study also has certain limitations. First, the sample primarily consists of older Chinese adults, and the generalizability of the findings needs to be further validated in populations from other regions. Second, we are unable to fully elucidate the underlying biological mechanisms and causal relationship between BRI and sarcopenia. Given the inherent limitations of observational studies, the potential influence of residual confounding factors cannot be entirely ruled out. Future research should further investigate the causal relationship between BRI and sarcopenia.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study, based on prospective data from an elderly Chinese population, found that individuals with lower BRI had a significantly increased risk of sarcopenia. This finding underscores the importance of considering body fat distribution in the assessment of muscle health in older adults. Future research should further investigate the applicability of BRI across different populations and incorporate biomarker analyses to elucidate the underlying mechanisms of fat-muscle interactions. Such insights could provide a new perspective for the early identification and intervention of sarcopenia.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CHARLS datasets can be downloaded at the CHARLS home page at http://charls.pku.edu.cn/en/\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was supported by Zhengzhou Medical and Health Technology Innovation Guidance Plan Project(2024YLZDJH268), Henan Medical Science and Technology Research Project (LHGJ20191042, LHGJ20200763).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZX.X., QN.Z. and FX.W. wrote the main manuscript text. MY.P. supervised and provided guidance on the statistical analysis. LX.X., XC.L. and DY.Z. prepared figures 1-2. SN.C.,WW.G. and CH.H . prepared figures 3. RL.G.,MM.Z. and WZ.X. prepared table 1-2. GQ. Y. contributed to the conception and design of the study and supervised the research process. All authors reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll procedures involving human participants were conducted in accordance with the Declaration of Helsinki. The study was approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015), and written informed consent was obtained from all participants.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors provide their consent for the publication of the study results.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe author reports no conflicts of interest in this work.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eWe would like to express our gratitude to the CHARLS team for their diligent efforts and selfless sharing of survey data, as well as to all participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSayer AA, Cruz-Jentoft A. Sarcopenia definition, diagnosis and treatment: consensus is growing. Age Ageing. 2022;51(10):afac220.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLars L, Hans, et al. Sarcopenia: Aging-Related Loss of Muscle Mass and Function. PHYSIOLOGICAL REVIEWS; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz-Jentoft AJ, Sayer AA, Sarcopenia. Lancet. 2019;393(10191):2636\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitamura A, Seino S, Abe T et al. Sarcopenia: prevalence, associated factors, and the risk of mortality and disability in Japanese older adults. Journal of Cachexia Sarcopenia and Muscle..\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapadopoulou SK. Sarcopenia: A Contemporary Health Problem among Older Adult Populations. Nutrients. 2020;12(5):1293.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomas DM, Bredlau C, Bosy-Westphal A, et al. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obes (Silver Spring). 2013;21(11):2264\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y, Liu X, Guan H, et al. Body Roundness Index Is a Superior Obesity Index in Predicting Diabetes Risk Among Hypertensive Patients: A Prospective Cohort Study in China. Front Cardiovasc Med. 2021;8:736073.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng J, He S, Chen X. Body Adiposity Index and Body Roundness Index in Identifying Insulin Resistance Among Adults Without Diabetes. Am J Med Sci. 2019;357(2):116\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan X, Liu F, Fan J, et al. Association of Body Roundness Index and A Body Shape Index with Obstructive Sleep Apnea: insights from NHANES 2015\u0026ndash;2018 data. Front Nutr. 2024;11:1492673.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu L, Pu H, Zhang M, Hu H, Wan Q. Non-linear relationship between the body roundness index and incident type 2 diabetes in Japan: a secondary retrospective analysis. J Transl Med. 2022;20(1):110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDamluji AA, Alfaraidhy M, AlHajri N, et al. Sarcopenia Cardiovasc Dis Circulation. 2023;147(20):1534\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang M, Liu J, Shen Q, et al. Body Roundness Index Trajectories and the Incidence of Cardiovascular Disease: Evidence From the China Health and Retirement Longitudinal Study. J Am Heart Assoc. 2024;13(19):e034768.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu M, Yu X, Xu L, Wu S, Tian Y. Associations of longitudinal trajectories in body roundness index with mortality and cardiovascular outcomes: a cohort study. Am J Clin Nutr. 2022;115(3):671\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang P, Fan Y, Gao H, Wang B. Body roundness index as a predictor of all-cause and cardiovascular mortality in patients with diabetes and prediabetes. Diabetes Res Clin Pract. 2025;219:111958.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Ma N, Lin Q, et al. Body Roundness Index and All-Cause Mortality Among US Adults. JAMA Netw Open. 2024;7(6):e2415051.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol. 2014;43(1):61\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen LK, Woo J, Assantachai P, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21(3):300\u0026ndash;e3072.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWen X, Wang M, Jiang CM, Zhang YM. Anthropometric equation for estimation of appendicular skeletal muscle mass in Chinese adults. Asia Pac J Clin Nutr. 2011;20(4):551\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu X, Li X, Xu M, Zhang Z, He L, Li Y. Sarcopenia prevalence and associated factors among older Chinese population: Findings from the China Health and Retirement Longitudinal Study. PLoS ONE. 2021;16(3):e0247617.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei C, Zhang G. Association between body roundness index (BRI) and gallstones: results of the 2017\u0026ndash;2020 national health and nutrition examination survey (NHANES). BMC Gastroenterol. 2024;24(1):192.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRico-Mart\u0026iacute;n S, Calder\u0026oacute;n-Garc\u0026iacute;a JF, S\u0026aacute;nchez-Rey P, Franco-Antonio C, Mart\u0026iacute;nez Alvarez M, S\u0026aacute;nchez, Mu\u0026ntilde;oz-Torrero JF. Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta-analysis. Obes Rev. 2020. 21(7): e13023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Ding L, Hu H, He H, Xiong Z, Zhu X. Associations of Body-Roundness Index and Sarcopenia with Cardiovascular Disease among Middle-Aged and Older Adults: Findings from CHARLS. J Nutr Health Aging. 2023;27(11):953\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQiu L, Xiao Z, Fan B, Li L, Sun G. Association of body roundness index with diabetes and prediabetes in US adults from NHANES 2007\u0026ndash;2018: a cross-sectional study. Lipids Health Dis. 2024;23(1):252.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Wang Y, Zheng X, et al. Body Roundness Index Trajectories and the Risk of Cancer: A Cohort Study. Cancer Med. 2024;13(23):e70447.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou H, Su H, Gong Y, et al. The association between weight-adjusted-waist index and sarcopenia in adults: a population-based study. Sci Rep. 2024;14(1):10943.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang S, Ren J. Obesity Paradox in Aging: From Prevalence to Pathophysiology. Prog Cardiovasc Dis. 2018;61(2):182\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu B, et al. Association between atherogenic index of plasma, body mass index, and sarcopenia: a cross-sectional and longitudinal analysis study based on older adults in China. Aging Clin Exp Res. 2025;37:122.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu W, Feng W, Lai J, Yuan D, Xiao W, Li Y. Role of adipokines in sarcopenia. Chin Med J (Engl). 2023;136(15):1794\u0026ndash;804.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFurman D, Campisi J, Verdin E, et al. Chronic inflammation in the etiology of disease across the life span. Nat Med. 2019;25(12):1822\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMolfino A, Imbimbo G, Muscaritoli M. Metabolic and histomorphological changes of adipose tissue in cachexia. Curr Opin Clin Nutr Metab Care. 2023;26(3):235\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRolland Y, van Abellan G, Gillette-Guyonnet S, Vellas B. Cachexia versus sarcopenia. Curr Opin Clin Nutr Metab Care. 2011;14(1):15\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi CW, Yu K, Shyh-Chang N, et al. Circulating factors associated with sarcopenia during ageing and after intensive lifestyle intervention. J Cachexia Sarcopenia Muscle. 2019;10(3):586\u0026ndash;600.\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":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Body Roundness Index (BRI), sarcopenia, CHARLS, prospective cohort study","lastPublishedDoi":"10.21203/rs.3.rs-6435227/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6435227/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThis study aimed to investigate the association between the Body Roundness Index (BRI) and the risk of sarcopenia in older adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 2,798 individuals aged 60 years and older without sarcopenia at baseline were drawn from the China Health and Retirement Longitudinal Study (CHARLS). We investigated the relationship between BRI and sarcopenia using logistic regression analysis. Subgroup analysis was conducted to explore the association between BRI and sarcopenia risk across different groups. Additionally, restricted cubic spline (RCS) and threshold effect analyses were conducted to characterize the potential nonlinear association.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOver a median follow-up of two years, 358 participants (12.8%) developed sarcopenia. Quartile-based analysis revealed a significant inverse association between BRI and sarcopenia risk. After adjusting for confounders, individuals in the highest BRI quartile (Q4) exhibited a markedly lower likelihood of developing sarcopenia compared to the lowest quartile (Q1) (OR = 0.03, 95% CI: 0.02–0.06). RCS analysis indicated an L-shaped nonlinear association, with an inflection point at 4.461. The relationship between BRI and sarcopenia risk remained significant on both sides of this threshold. Furthermore, subgroup analysis did not indicate any significant interaction effects between BRI and sarcopenia risk (P for interaction \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study suggests a significant negative association between BRI and the risk of sarcopenia, highlighting BRI as a potentially valuable indicator for assessing sarcopenia risk in older adults.\u003c/p\u003e","manuscriptTitle":"Association Between Body Roundness Index and Sarcopenia in Older Adults: Evidence from a Prospective Cohort Study Using CHARLS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 09:52:10","doi":"10.21203/rs.3.rs-6435227/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-05-15T09:59:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-17T06:59:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-15T03:30:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-15T03:30:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-04-12T14:37:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0586df83-3230-404a-8e4e-0abfb1ca6c12","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-05-20T09:52:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-20 09:52:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6435227","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6435227","identity":"rs-6435227","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}