Beyond Body Composition: Regional Variations in Physical Function and Sarcopenia Among Older Adults in San José, Costa Rica and Baltimore, United States

Beyond Body Composition: Regional Variations in Physical Function and Sarcopenia Among Older Adults in San José, Costa Rica and Baltimore, United States | 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 Beyond Body Composition: Regional Variations in Physical Function and Sarcopenia Among Older Adults in San José, Costa Rica and Baltimore, United States Kathleen Dondero, Julie Rekant, Isaura M. Castillo-Hernández, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8866638/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background As life span increases globally, so does the risk of aging with chronic health conditions. Differences in life span and health span between Costa Rica, a middle-income country, and the United States, a high-income country, suggest cultural context may influence how age-related changes in muscle mass, body composition, and physical function affect older adults. This analysis compared body composition, physical function, and sarcopenia prevalence among aging adults from two major metropolitan cities: San José, Costa Rica and Baltimore, Maryland, US. Methods Baseline data from study participants at the Baltimore Veterans Affairs Medical Center were matched with publicly available baseline data from a similar cohort at Universidad de Costa Rica. All participants had assessments of body composition (dual energy x-ray absorptiometry), physical function (handgrip strength, Six Minute Walk Test [6MWT]), and general health characteristics (vitals, comorbidities). Sarcopenia prevalence was defined using European Working Group on Sarcopenia in Older Persons criteria. Participants were age- and sex- matched between sites prior to analysis. Results Seventy-eight participants (San José n = 39; Baltimore n = 39) were included. Compared to participants from Baltimore, participants from San José had lower lean mass (54.97 ± 7.36 vs. 62.45 ± 6.91% bodyweight, p < 0.01) and higher fat mass (43.17 ± 7.78 vs. 33.95 ± 7.37% bodyweight, p < 0.01). Participants from San José also had lower grip strength (27.43 ± 8.48 vs. 32.54 ± 9.27 kg, p = 0.04) but greater 6MWT distance (486.18 ± 99.47 vs. 387.53 ± 102.95 m, p < 0.01) compared to those from Baltimore. Regional differences in grip strength were no longer significant after adjusting for body composition, though 6MWT differences remained significant after controlling for absolute (kg) and relative (% bodyweight) lean and fat mass. Sarcopenia prevalence was greater in San José based on appendicular lean mass/height 2 (74.4% vs. 2.6%, p < 0.001) and grip strength (65.2% vs. 16.2%, p < 0.001) criteria. Conclusions Regional differences in muscle composition and physical function highlight the potential influence of cultural, cardiometabolic, and environmental factors beyond body composition alone. These findings underscore the importance of culturally and contextually tailored strategies to support physical function and mitigate sarcopenia risk in aging populations globally. global aging sarcopenia body composition physical function Background The global older adult population is exponentially growing. The World Health Organization predicts that by the year 2030, 1 in 6 people in the world will be aged 60 years or older.[ 1 ] Global lifespan is also increasing, with the number of persons aged 80 years or older expected to triple between 2020 and 2050, reaching approximately 426 million people.[ 1 ] However, a growing aging population that is living longer can also result in higher rates of chronic health conditions and disability, such as obesity and frailty. Physiologically, older adults often experience decreases in muscle mass, strength, and physical function - each of which are predictors of frailty, sarcopenia, and mortality.[ 2 ] Although we expect that older adults around the world will experience these physiological changes, the rate of decline may vary across countries depending on genetics, cultural lifestyle differences, socioeconomic status, and healthcare systems[ 3 ]. Costa Rica, classified as a middle‑income country, has one of the highest life expectancies in across North, Central, and South America with an average life expectancy of 78.6 years[ 4 , 5 ] and reports a lower likelihood of frailty compared to older adults in the United States (US). Previous research hypothesizes that this is, in part, due to universal healthcare and strong social support for the aging population.[ 6 ] Comparatively, the US has a lower life expectancy around 76.4 years and higher rates of frailty and obesity than Costa Rica.[ 6 ] Despite its advanced medical infrastructure, the US has substantial differences in rates of morbidity and mortality across socioeconomic statuses, race, and region that are compounded by healthcare access inequities, increasing rates of disability and chronic disease-related mortality for those in certain socioeconomic categories[ 7 ]. These differing patterns of frailty and chronic disease between the US and Costa Rica suggest that sarcopenia prevalence may likewise differ in their respective older adult populations. Obesity, which is strongly associated with both cardiovascular mortality and all-cause mortality in both countries,[ 8 , 9 ] has also increased globally in the past several decades.[ 10 ] Further, when obesity and sarcopenia coexist, disruptions to the quality of life of an older adult are significant. For example, a nationally representative sample of older adults in the US found that adults with sarcopenic obesity were 6.4 times more likely to experience frailty, had difficulty completing one or more activities of daily living independently, and experienced more social isolation than older adults with obesity alone.[ 11 ] Given Costa Rica’s comparatively lower rates of frailty and mortality[ 6 ], understanding how risk factors for sarcopenia and obesity differ between these two countries could be helpful for developing strategies to enhance health span globally. Thus, the purpose of the present analysis was to compare body composition, physical function, and sarcopenia prevalence among aging adults from two major metropolitan cities: San José, Costa Rica and Baltimore, Maryland, US. A secondary goal of this analysis was to determine which factors are associated with physical function and performance in these cohorts. Methods Study participants Baseline assessments from older adults recruited from a larger study in the Geriatric Research Education and Clinical Center in Baltimore, Maryland, US were compared to publicly available data from baseline assessments of participants recruited for an exercise intervention at the Centro de Investigación en Ciencias del Movimiento Humano (CIMOHU) in San José, Costa Rica. Participants were included if they were 55–80 years old, could walk independently without the assistance of another person, and were free from contraindications to exercise. Exclusion criteria were conditions indicating unstable medical status such as active cancer with or without treatment, uncontrolled hypertension, diffuse proliferative retinopathy, uncontrolled diabetes, and/or unstable angina. Participants were recruited from flyers, brochures, mailings, word of mouth, and provider referrals. All study participants completed written informed consent prior to participating in the exercise programs. Study protocols and analyses were approved by the University of Maryland Baltimore Institutional Review Board (HP-00096177) and all study procedures adhered to the Declaration of Helsinki. Data collection Demographics Participant age, sex, and self-reported race and ethnicity were collected. Body height and mass were measured with light clothing and without shoes using a calibrated electronic scale and stadiometer and were used to calculate body mass index (BMI, in kg/m2). Participants between cohorts were age-matched (within 3 years) and sex-matched prior to analysis. Body composition Whole-body dual energy x-ray absorptiometry (DEXA) was conducted and used to measure total body mass, appendicular lean mass, total lean mass, total fat mass, and lean mass and fat mass as percentages of total body mass (percent lean mass and percent fat mass, respectively). Measures were collected with the Lunar Prodigy Advance (GE Medical Systems Lunar, Madison, WI) in San José and the Lunar iDXA (GE Medical Systems Lunar, Madison, WI) in Baltimore. Physical function Functional endurance was captured by distance covered during the Six-Minute Walk Test (6MWT) on a 50 foot long course for participants in San José and 100 foot long for participants in Baltimore. Dominant hand grip strength was captured as the best of two trials measured with isometric dynamometry (Jamar Hydraulic Hand Dynamometer, Lafayette Instrument Company). Statistical analysis Data were inspected for outliers and assessed for normality using Shapiro-Wilk tests and were found not to violate normality assumptions. Descriptive statistics (means, standard deviations, frequencies, and percentages) were obtained for participants characteristics and outcome variables. Therefore, independent samples t-tests were used to compare demographic, body composition, and physical function variables between regions (San José, Baltimore). A series of analysis of covariance (ANCOVA) models were run with region as the independent variable, physical function as the dependent variables (6MWT distance, grip strength), and body composition variables as covariates (total lean mass, percent lean mass, total fat mass, percent fat mass). An alpha level of < 0.05 was considered for statistical significance. To explore the prevalence of sarcopenic factors in both groups, appendicular lean mass (ALM), grip strength, and 6MWT performance were compared against European Working Group of Sarcopenia in Older Persons Revised (EWGSOP-2) cut-points for defining probable or confirmed sarcopenia.[ 12 ] Specifically, ALM/ht 2 < 7.0 kg/m 2 for males or < 5.5 kg/m 2 for females; grip strength < 27 kg for males or < 16 kg for females; 6MWT distance ≤ 400 m. Differences by region in the prevalence of meeting each or any of these criteria were evaluated with Pearson Chi-squared tests. Results Baseline data were obtained from 124 participants (San José n = 49, Baltimore n = 75). After age- and sex-matching datasets, 78 participants were included in the final analysis (San José n = 39, Baltimore n = 39). Most participants in the San José cohort identified as White/Caucasian while more than two thirds of all participants in the Baltimore cohort identified as Black/African American. Blood pressure and diabetes prevalence were higher in Baltimore when compared to San José. Baltimore participants were taller and weighed more than participants in San José, though BMI was not statistically different between cohorts. All data are presented in Table 1 . Table 1 Participant demographics, compared with independent samples t-tests. San José (n = 39) Baltimore (n = 39) p-value Age (years) 66.96 ± 6.11 67.79 ± 6.40 0.56 Sex, Female 7 (17.9%) 7 (17.9%) 1.00 Race White/Caucasian 37 (94.9%) 6 (15.4%) < 0.01 Black/African American 0 (0.0%) 28 (71.8%) Asian 2 (5.1%) 1 (2.6%) More than 1 race 0 (0.0%) 4 (10.3%) Ethnicity, Hispanic/Latino 37 (94.9%) 2 (2.6%) < 0.01 BMI (kg/m 2 ) 27.81 ± 4.13 28.77 ± 4.35 0.32 Height (m) 1.58 ± 0.08 1.75 ± 0.09 < 0.01 Body mass (kg) 69.67 ± 10.89 88.30 ± 17.14 < 0.01 Diabetes, Yes 7 (7.9%) 17 (44.6%) 0.01 Resting SBP (mmHg) 118.46 ± 11.74 n=26 133.74 ± 13.43 n=38 < 0.01 Resting DBP (mmHg) 66.69 ± 6.16 n=26 77.68 ± 9.80 n=38 < 0.01 Resting HR (bpm) 69.42 ± 11.29 n=26 70.79 ± 10.58 n=38 0.62 Notes: Bolded values are statistically significant at p < 0.05. kilograms (kg); Body mass index (BMI); meters (m); Systolic Blood Pressure (SBP); Diastolic Blood Pressure (DBP); Heart rate (HR); beats per minute (bpm); millimeters of mercury (mmHg). Older adults in San José had significantly less lean mass and a greater percentage of body fat when compared to the older adults from Baltimore. Despite a shorter 6MWT course requiring more turns during the test, the group from San José covered a clinically meaningfully more distance during the 6MWT compared to older adults in the Baltimore cohort (Table 2 ). Participants from San José had lower grip strength compared to those from Baltimore. Table 2 Descriptive and inferential statistics for physical function and body composition outcomes by region. San José (n = 39) Baltimore (n = 39) p-value Total lean mass (kg) 37.65 ± 7.35 53.75 ± 10.01 < 0.01 Percent lean mass (% bodyweight) 54.97 ± 7.36 62.45 ± 6.91 < 0.01 Total fat (kg) 28.86 ± 7.88 29.97 ± 10.06 0.59 Percent fat mass (% bodyweight) 43.17 ± 7.78 33.95 ± 7.37 < 0.01 Grip strength (kg) 27.43 ± 8.48 n=23 32.54 ± 9.27 n=37 0.04 6MWT Distance (m) 486.18 ± 99.47 n=17 387.53 ± 102.95 < 0.01 Notes: Bolded values are statistically significant (p < 0.05). kilograms (kg); meters (m); Six-Minute Walk Test (6MWT) ANCOVAs were performed to assess the influence of region (San José vs. Baltimore) on 6MWT and grip strength performance after controlling for body composition measures (total lean mass, percent lean mass, total fat mass, percent fat mass) (Table 3 ). For grip strength, models were significant for total lean mass, percent lean mass, and percent fat mass, though no main effects of region were observed. All models for 6MWT were significant with significant main effects. Table 3 Explained variance (η 2 ) of region on physical performance measures, controlling for body composition covariates. Covariate Overall Model Main Effect (Region) Covariate effect Grip strength Total lean mass F(2,57) = 18.27 η 2 = 0.392 p < 0.001 F(1,57) = 2.49 η 2 = 0.042 p = 0.120 F(1,57) = 29.87 η 2 = 0.344 p < 0.001 Percent lean mass F(2,57) = 9.17 η 2 = 0.244 p < 0.001 F(1,57) = 0.242 η 2 = 0.004 p = 0.625 F(1,57) = 12.83 η 2 = 0.184 p < 0.001 Total fat mass F(2,57) = 2.46 η 2 = 0.079 p = 0.094 F(1,57) = 4.74 η 2 = 0.077 p = 0.034 F(1,57) = 0.383 η 2 = 0.007 p = 0.538 Percent fat mass F(2,57) = 8.94 η 2 = 0.239 p < 0.001 F(1,57) = 0.076 η 2 = 0.001 p = 0.784 F(1,57) = 12.39 η 2 = 0.179 p < 0.001 6MWT Total lean mass F(2,53) = 5.83 η 2 = 0.180 p = 0.005 F(1,53) = 10.04 η 2 = 0.159 p = 0.003 F(1,53) = 0.64 η 2 = 0.012 p = 0.426 Percent lean mass F(2,53) = 6.41 η 2 = 0.195 p = 0.003 F(1,53) = 12.82 η 2 = 0.195 p < 0.001 F(1,53) = 1.61 η 2 = 0.029 p = 0.210 Total fat mass F(2,53) = 6.24 η 2 = 0.191 p = 0.004 F(1,53) = 9.91 η 2 = 0.158 p = 0.003 F(1,53) = 1.32 η 2 = 0.024 p = 0.255 Percent fat mass F(2,53) = 6.38 η 2 = 0.194 p = 0.003 F(1,53) = 12.72 η 2 = 0.193 p < 0.001 F(1,53) = 1.56 η 2 = 0.029 p = 0.217 Notes: Results are presented as F(df effect , df error ), with the explained variance (η 2 ) and p-values for the model, main, and covariate effects. Bolded values indicate meeting statistical significance with p < 0.05. Six-Minute Walk Test (6MWT); degrees of freedom (df) Participants from San José had a greater prevalence of sarcopenia based on appendicular lean mass and grip strength diagnostic criteria. Although not statistically significant, older adults in Baltimore tended to have a higher prevalence of low aerobic capacity (≤ 400 m on the 6MWT) compared to those in San José. Older adults in the San José group had a significantly higher prevalence of meeting at least one sarcopenia criterion compared to older adults in the Baltimore group (Table 4 ). Table 4 Prevalence of meeting sarcopenia criteria by region. San José Baltimore Pearson Chi-squared test Total Low ALM/h 2 29 (74.4%) 1 (2.6%) 42.47; <0.001 30 (38.5%) Low grip 15 (65.2%) n=23 6 (16.2%) n=27 14.97; <0.001 21 (35.0%) 6MWT ≤ 400 m 4 (23.5%) n=17 17 (43.6%) 2.03; 0.154 21 (37.5%) Met at least 1 criterion 31 (79.5%) 19 (48.7%) 8.02; 0.005 60 (64.1%) Bolded values are statistically significant at p < 0.05. Discussion This analysis compared body composition, physical function, and sarcopenia prevalence among aging adults from San José, Costa Rica and Baltimore, Maryland, US. After age, sex, and BMI-matching groups between regions, older adults in San José were found to have poorer body composition than those in Baltimore, with less lean mass and a greater amount of relative fat mass. Older adults in Baltimore were stronger as measured with hand grip strength compared to older adults in San José. However, grip strength was no longer meaningfully different between regions after controlling for body composition. The significant covariate effect in these models indicates total lean mass, total lean percent, and total fat percent may be driving differences in grip strength observed between regions. Older adults from San José had better functional performance on the 6MWT compared to older adults from Baltimore. These regional differences remained significant even after accounting for body composition measures. This suggests something other than body composition is driving differences in 6MWT performance observed between regions. Participants from San José appear healthier from a cardiometabolic standpoint than those from Baltimore, with lower resting blood pressures and a lower prevalence of diabetes, which may help explain differences observed on the 6MWT[ 13 ]. Racial and ethnic differences between participants from the two regions alongside additional cultural factors may also help further explain regional differences in 6MWT performance. Questions of covariation by racial identity or ethnicity could not be answered in the present analysis given the absence of Black/African American adults in the San José cohort and absence of Hispanic/Latino participants in the Baltimore cohort. Future work should explore this question with a larger, more racially and ethnically diverse sample. Differences in sarcopenia prevalence between cohorts were observed when body composition, grip strength, and 6MWT performance were compared to cut scores used to establish presence or risk of sarcopenia. In particular, appendicular lean mass and grip strength diagnostic criteria identified a considerably higher prevalence of sarcopenia among participants from San José compared to those from Baltimore, however a non-significant trend towards greater sarcopenia prevalence by 6MWT criteria was observed among participants in Baltimore. This aligns with work from Glei et al. who found US older adults had better grip strength compared to Costa Rican older adults[ 14 ]. However, this same study found cardiorespiratory capacity was greater for US older adults compared to Costa Rican older adults; while cardiorespiratory capacity was not directly captured in the present study, 6MWT performance is a well-established proxy for evaluating this metric[ 15 ]. Looking at the findings of the present analysis together, a picture emerges indicating participants from San José demonstrate muscle weakness, which can be explained by a lower amount of lean mass and higher amount of fat mass for this cohort, translating to a higher prevalence of sarcopenia diagnosis in this cohort. However, sociocultural, cardiometabolic health, lifestyle, or other influences may enable these Costa Ricans to function at a higher level for functional mobility tasks like prolonged walking[ 7 ]. These regional differences may have clinical implications, requiring tailored rehabilitation strategies to improve muscle mass and function in older adults from San José and Baltimore. While this analysis includes measures of whole-body composition, it does not specifically evaluate composition and quality of key muscle groups required for functional mobility (e.g. knee extensors, hip extensors, hip abductors). Future investigations including measures of computed tomography or ultrasound imaging of these key muscle groups can provide important information on size and composition of these muscles, which would provide a more comprehensive understanding of muscle wasting and myosetatotic changes[16]. Additionally, future work may explore a more robust clinical evaluation to understand how domains of physical function and performance like walking ability, balance, and transfers are influenced by the present findings. Nonetheless, this initial analysis provides evidence that whole-body composition, including lean and fat mass, plays a role in explaining strength but not functional endurance differences observed between older adults in San José and Baltimore. It is important to acknowledge the cross-sectional nature of this analysis. This analysis identifies unique contributions of body composition and physical function, which differ between San José and Baltimore. Future work should evaluate body composition and physical function longitudinally to better understand how these components influence one another and to answer questions of causality and directionality of these relationships. Additionally, future work capturing exercise, diet, and social engagement habits, all of which play large roles in health with aging, can further contextualize how these cultural factors influence the presented outcomes. Conclusions Observed regional differences in muscle mass and physical function demonstrate that aging outcomes may be shaped by cultural, cardiometabolic, and environmental factors beyond body composition. These findings underscore the importance of culturally tailored strategies within global health frameworks to support physical function and reduce sarcopenia risk across diverse aging populations. Abbreviations United States US Kilograms kg Body mass index BMI Dual energy x-ray absorptiometry DEXA Analysis of covariance ANCOVA Appendicular lean mass ALM European Working Group of Sarcopenia in Older Persons Revised EWGSOP-2 Meters m Systolic Blood Pressure SBP Diastolic Blood Pressure DBP Heart rate HR Beats per minute bpm Millimeters of mercury mmHg Declarations Ethics approval and consent to participate: All study participants completed written informed consent prior to participation. Study protocols and analyses were approved by the University of Maryland Baltimore Institutional Review Board (HP-00096177). Consent for publication: Not applicable. Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: This study was supported by the Alicia and Yaya Fellowship in Global Aging through the University of Maryland, Baltimore and Universidad de Costa Rica. Data for this manuscript was supported by a Department of Veterans Affairs Merit Award (RX003484-01A2). This material is based upon work as part of the Advanced Fellowship in Geriatrics, supported by the U.S. Department of Veterans Affairs Office of Academic Affiliations, the Veterans Affairs Maryland Health Care System, and the Department of Veterans Affairs Baltimore Geriatric Research, Education, and Clinical Center. Authors' contributions: KD, JR, AGG, and IMCH designed the study, collected data, and interpreted the statistical analyses. KD and JR drafted the initial manuscript and tables, and performed the initial statistical analysis. ESL contributed to data collection and analysis. OA contributed to data collection and study supervision. All authors read and approved the final manuscript. Acknowledgements: We thank our research subjects for their time and participation in the study. References Ageing. World Health Organization. 2018. https://data.who.int/countries/840 . Accessed 16 December 2025. Goodpaster BH, Carlson CL, Visser M, Kelley DE, Scherzinger A, Harris TB, et al. Attenuation of skeletal muscle and strength in the elderly: The Health ABC Study. J Appl Physiol. 2001;90:2157–65. https://doi.org/10.1152/jappl.2001.90.6.2157 . Pan American Health Organization. Country Profile - Costa Rica. Health in the Americas + 2021. https://www.paho.org/es/costa-rica . Accessed 11 December 2025. World Health Organization. United States of America: Health data overview for the United States of America. Https://DataWhoInt/Countries/840. Accessed 16 December 2025. Santamaría-Ulloa C, Lehning AJ, Cortés-Ortiz MV, Méndez-Chacón E. Frailty as a predictor of mortality: a comparative cohort study of older adults in Costa Rica and the United States. BMC Public Health 2023;23:1960. https://doi.org/10.1186/s12889-023-16900-4 Rosero-Bixby L, Dow WH. Exploring why Costa Rica outperforms the United States in life expectancy: A tale of two inequality gradients. Proceedings of the National Academy of Sciences. 2016;113:1130–7. https://doi.org/10.1073/pnas.1521917112 Santamaría-Ulloa C, Chinnock A, Montero-López M. Association between obesity and mortality in the Costa Rican elderly: a cohort study. BMC Public Health. 2022;22:1007. https://doi.org/10.1186/s12889-022-13381-9 . Visaria A, Setoguchi S. Body mass index and all-cause mortality in a 21st century U.S. population: A National Health Interview Survey analysis. PLoS ONE. 2023;18:e0287218. https://doi.org/10.1371/journal.pone.0287218 . Trends in adult. body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet. 2016;387:1377–96. https://doi.org/10.1016/S0140-6736(16)30054-X . Dondero KR, Falvey JR, Beamer BA, Addison O. Geriatric Vulnerabilities Among Obese Older Adults With and Without Sarcopenia : Findings From a Nationally Representative Cohort Study. J Geriatr Phys Ther 2022:1–6. https://doi.org/10.1519/JPT.0000000000000358 Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16–31. https://doi.org/10.1093/ageing/afy169 . Camara M, Lima KC, Freire YA, Souto GC, Macêdo GAD, de Silva R. Independent and joint associations of cardiorespiratory fitness and lower-limb muscle strength with cardiometabolic risk in older adults. PLoS ONE. 2023;18:e0292957. https://doi.org/10.1371/journal.pone.0292957 . Glei DA, Goldman N, Ryff CD, Weinstein M. Physical Function in U.S. Older Adults Compared With Other Populations: A Multinational Study. J Aging Health. 2019;31:1067–84. https://doi.org/10.1177/0898264318759378 . ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002;166:111–7. https://doi.org/10.1164/ajrccm.166.1.at1102 . Li L, Xia Z, Zeng X, Tang A, Wang L, Su Y. The agreement of different techniques for muscle measurement in diagnosing sarcopenia: a systematic review and meta-analysis. Quant Imaging Med Surg. 2024;14:2177–92. https://doi.org/10.21037/qims-23-1089 . Additional Declarations No competing interests reported. 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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-8866638","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595172601,"identity":"e35eba36-7031-4000-b3a8-aa7f0789bc7c","order_by":0,"name":"Kathleen Dondero","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBACCYYEBgYeIIMfIZZApBbJNpK1GBwjVotke/KxB28q7skZ328+Jvmj4g4DP3uOAV4t0jzP0g3nnCk2NjvGlibNc+YZg2TPG/xa5CRyzKR52xIStx3jMbvN2HaYweAGAVsgWv4lJG5u4zG7+ROoxZ6QFmmwloaExA1sPGY3eEG2SBDQItnzLE1yzrEEY4ljaem/ec4c5pE486wArxaJ48nHJN7UJMjxNx8+bPij4rAcf3vyBrxaMAAPacpHwSgYBaNgFGAFAD+hQ3qSK4gjAAAAAElFTkSuQmCC","orcid":"","institution":"Towson University","correspondingAuthor":true,"prefix":"","firstName":"Kathleen","middleName":"","lastName":"Dondero","suffix":""},{"id":595172602,"identity":"e925a32c-94e2-4957-ae0c-12fd22c71856","order_by":1,"name":"Julie Rekant","email":"","orcid":"","institution":"University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Julie","middleName":"","lastName":"Rekant","suffix":""},{"id":595172603,"identity":"2755654e-f68b-4db5-bc86-8007bba96058","order_by":2,"name":"Isaura M. Castillo-Hernández","email":"","orcid":"","institution":"Universidad de Costa Rica","correspondingAuthor":false,"prefix":"","firstName":"Isaura","middleName":"M.","lastName":"Castillo-Hernández","suffix":""},{"id":595172604,"identity":"be70b195-9eed-426e-a6b7-41c396ff6452","order_by":3,"name":"Ana Gómez-Granados","email":"","orcid":"","institution":"Universidad de Costa Rica","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"","lastName":"Gómez-Granados","suffix":""},{"id":595172605,"identity":"16ae7ccd-5ffa-4282-a7ea-9ae05efe3e3b","order_by":4,"name":"Eduardo Santiago López","email":"","orcid":"","institution":"Universidad de Costa Rica","correspondingAuthor":false,"prefix":"","firstName":"Eduardo","middleName":"Santiago","lastName":"López","suffix":""},{"id":595172606,"identity":"ce704031-4e0a-4e59-a843-dcb6bd2a6a84","order_by":5,"name":"Odessa Addison","email":"","orcid":"","institution":"University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Odessa","middleName":"","lastName":"Addison","suffix":""}],"badges":[],"createdAt":"2026-02-13 02:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8866638/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8866638/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104397265,"identity":"71f030fd-a8e7-497e-ab31-6765ea4e68cd","added_by":"auto","created_at":"2026-03-11 11:45:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":971931,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8866638/v1/79de534b-6e8c-4330-8183-5cf06a843837.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond Body Composition: Regional Variations in Physical Function and Sarcopenia Among Older Adults in San José, Costa Rica and Baltimore, United States","fulltext":[{"header":"Background","content":"\u003cp\u003eThe global older adult population is exponentially growing. The World Health Organization predicts that by the year 2030, 1 in 6 people in the world will be aged 60 years or older.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Global lifespan is also increasing, with the number of persons aged 80 years or older expected to triple between 2020 and 2050, reaching approximately 426\u0026nbsp;million people.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] However, a growing aging population that is living longer can also result in higher rates of chronic health conditions and disability, such as obesity and frailty. Physiologically, older adults often experience decreases in muscle mass, strength, and physical function - each of which are predictors of frailty, sarcopenia, and mortality.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Although we expect that older adults around the world will experience these physiological changes, the rate of decline may vary across countries depending on genetics, cultural lifestyle differences, socioeconomic status, and healthcare systems[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCosta Rica, classified as a middle‑income country, has one of the highest life expectancies in across North, Central, and South America with an average life expectancy of 78.6 years[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and reports a lower likelihood of frailty compared to older adults in the United States (US). Previous research hypothesizes that this is, in part, due to universal healthcare and strong social support for the aging population.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Comparatively, the US has a lower life expectancy around 76.4 years and higher rates of frailty and obesity than Costa Rica.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Despite its advanced medical infrastructure, the US has substantial differences in rates of morbidity and mortality across socioeconomic statuses, race, and region that are compounded by healthcare access inequities, increasing rates of disability and chronic disease-related mortality for those in certain socioeconomic categories[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These differing patterns of frailty and chronic disease between the US and Costa Rica suggest that sarcopenia prevalence may likewise differ in their respective older adult populations.\u003c/p\u003e \u003cp\u003eObesity, which is strongly associated with both cardiovascular mortality and all-cause mortality in both countries,[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] has also increased globally in the past several decades.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] Further, when obesity and sarcopenia coexist, disruptions to the quality of life of an older adult are significant. For example, a nationally representative sample of older adults in the US found that adults with sarcopenic obesity were 6.4 times more likely to experience frailty, had difficulty completing one or more activities of daily living independently, and experienced more social isolation than older adults with obesity alone.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] Given Costa Rica\u0026rsquo;s comparatively lower rates of frailty and mortality[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], understanding how risk factors for sarcopenia and obesity differ between these two countries could be helpful for developing strategies to enhance health span globally. Thus, the purpose of the present analysis was to compare body composition, physical function, and sarcopenia prevalence among aging adults from two major metropolitan cities: San Jos\u0026eacute;, Costa Rica and Baltimore, Maryland, US. A secondary goal of this analysis was to determine which factors are associated with physical function and performance in these cohorts.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003eBaseline assessments from older adults recruited from a larger study in the Geriatric Research Education and Clinical Center in Baltimore, Maryland, US were compared to publicly available data from baseline assessments of participants recruited for an exercise intervention at the Centro de Investigaci\u0026oacute;n en Ciencias del Movimiento Humano (CIMOHU) in San Jos\u0026eacute;, Costa Rica. Participants were included if they were 55\u0026ndash;80 years old, could walk independently without the assistance of another person, and were free from contraindications to exercise. Exclusion criteria were conditions indicating unstable medical status such as active cancer with or without treatment, uncontrolled hypertension, diffuse proliferative retinopathy, uncontrolled diabetes, and/or unstable angina.\u003c/p\u003e \u003cp\u003eParticipants were recruited from flyers, brochures, mailings, word of mouth, and provider referrals. All study participants completed written informed consent prior to participating in the exercise programs. Study protocols and analyses were approved by the University of Maryland Baltimore Institutional Review Board (HP-00096177) and all study procedures adhered to the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003e \u003cstrong\u003eDemographics\u003c/strong\u003e \u003cp\u003eParticipant age, sex, and self-reported race and ethnicity were collected. Body height and mass were measured with light clothing and without shoes using a calibrated electronic scale and stadiometer and were used to calculate body mass index (BMI, in kg/m2). Participants between cohorts were age-matched (within 3 years) and sex-matched prior to analysis.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eBody composition\u003c/strong\u003e \u003cp\u003eWhole-body dual energy x-ray absorptiometry (DEXA) was conducted and used to measure total body mass, appendicular lean mass, total lean mass, total fat mass, and lean mass and fat mass as percentages of total body mass (percent lean mass and percent fat mass, respectively). Measures were collected with the Lunar Prodigy Advance (GE Medical Systems Lunar, Madison, WI) in San Jos\u0026eacute; and the Lunar iDXA (GE Medical Systems Lunar, Madison, WI) in Baltimore.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePhysical function\u003c/strong\u003e \u003cp\u003eFunctional endurance was captured by distance covered during the Six-Minute Walk Test (6MWT) on a 50 foot long course for participants in San Jos\u0026eacute; and 100 foot long for participants in Baltimore. Dominant hand grip strength was captured as the best of two trials measured with isometric dynamometry (Jamar Hydraulic Hand Dynamometer, Lafayette Instrument Company).\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were inspected for outliers and assessed for normality using Shapiro-Wilk tests and were found not to violate normality assumptions. Descriptive statistics (means, standard deviations, frequencies, and percentages) were obtained for participants characteristics and outcome variables. Therefore, independent samples t-tests were used to compare demographic, body composition, and physical function variables between regions (San Jos\u0026eacute;, Baltimore). A series of analysis of covariance (ANCOVA) models were run with region as the independent variable, physical function as the dependent variables (6MWT distance, grip strength), and body composition variables as covariates (total lean mass, percent lean mass, total fat mass, percent fat mass). An alpha level of \u0026lt;\u0026thinsp;0.05 was considered for statistical significance.\u003c/p\u003e \u003cp\u003eTo explore the prevalence of sarcopenic factors in both groups, appendicular lean mass (ALM), grip strength, and 6MWT performance were compared against European Working Group of Sarcopenia in Older Persons Revised (EWGSOP-2) cut-points for defining probable or confirmed sarcopenia.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Specifically, ALM/ht\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;7.0 kg/m\u003csup\u003e2\u003c/sup\u003e for males or \u0026lt;\u0026thinsp;5.5 kg/m\u003csup\u003e2\u003c/sup\u003e for females; grip strength\u0026thinsp;\u0026lt;\u0026thinsp;27 kg for males or \u0026lt;\u0026thinsp;16 kg for females; 6MWT distance\u0026thinsp;\u0026le;\u0026thinsp;400 m. Differences by region in the prevalence of meeting each or any of these criteria were evaluated with Pearson Chi-squared tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBaseline data were obtained from 124 participants (San Jos\u0026eacute; n\u0026thinsp;=\u0026thinsp;49, Baltimore n\u0026thinsp;=\u0026thinsp;75). After age- and sex-matching datasets, 78 participants were included in the final analysis (San Jos\u0026eacute; n\u0026thinsp;=\u0026thinsp;39, Baltimore n\u0026thinsp;=\u0026thinsp;39). Most participants in the San Jos\u0026eacute; cohort identified as White/Caucasian while more than two thirds of all participants in the Baltimore cohort identified as Black/African American. Blood pressure and diabetes prevalence were higher in Baltimore when compared to San Jos\u0026eacute;. Baltimore participants were taller and weighed more than participants in San Jos\u0026eacute;, though BMI was not statistically different between cohorts. All data are presented in 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\u003eParticipant demographics, compared with independent samples t-tests.\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSan Jos\u0026eacute; (n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBaltimore (n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.96\u0026thinsp;\u0026plusmn;\u0026thinsp;6.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.79\u0026thinsp;\u0026plusmn;\u0026thinsp;6.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSex, Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite/Caucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack/African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (71.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 1 race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEthnicity, Hispanic/Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.81\u0026thinsp;\u0026plusmn;\u0026thinsp;4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.77\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHeight (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBody mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.67\u0026thinsp;\u0026plusmn;\u0026thinsp;10.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.30\u0026thinsp;\u0026plusmn;\u0026thinsp;17.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiabetes, Yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (44.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eResting SBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118.46\u0026thinsp;\u0026plusmn;\u0026thinsp;11.74 \u003csup\u003en=26\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133.74\u0026thinsp;\u0026plusmn;\u0026thinsp;13.43 \u003csup\u003en=38\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eResting DBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.69\u0026thinsp;\u0026plusmn;\u0026thinsp;6.16 \u003csup\u003en=26\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.68\u0026thinsp;\u0026plusmn;\u0026thinsp;9.80 \u003csup\u003en=38\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eResting HR (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.42\u0026thinsp;\u0026plusmn;\u0026thinsp;11.29 \u003csup\u003en=26\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.79\u0026thinsp;\u0026plusmn;\u0026thinsp;10.58 \u003csup\u003en=38\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNotes: Bolded\u003c/b\u003e values are statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. kilograms (kg); Body mass index (BMI); meters (m); Systolic Blood Pressure (SBP); Diastolic Blood Pressure (DBP); Heart rate (HR); beats per minute (bpm); millimeters of mercury (mmHg).\u003c/p\u003e \u003cp\u003eOlder adults in San Jos\u0026eacute; had significantly less lean mass and a greater percentage of body fat when compared to the older adults from Baltimore. Despite a shorter 6MWT course requiring more turns during the test, the group from San Jos\u0026eacute; covered a clinically meaningfully more distance during the 6MWT compared to older adults in the Baltimore cohort (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Participants from San Jos\u0026eacute; had lower grip strength compared to those from Baltimore.\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\u003eDescriptive and inferential statistics for physical function and body composition outcomes by region.\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSan Jos\u0026eacute; (n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaltimore (n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal lean mass (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e37.65\u0026thinsp;\u0026plusmn;\u0026thinsp;7.35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e53.75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePercent lean mass (% bodyweight)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e54.97\u0026thinsp;\u0026plusmn;\u0026thinsp;7.36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e62.45\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal fat (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.86\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.97\u0026thinsp;\u0026plusmn;\u0026thinsp;10.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePercent fat mass (% bodyweight)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e43.17\u0026thinsp;\u0026plusmn;\u0026thinsp;7.78\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e33.95\u0026thinsp;\u0026plusmn;\u0026thinsp;7.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrip strength (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e27.43\u0026thinsp;\u0026plusmn;\u0026thinsp;8.48\u003c/b\u003e \u003csup\u003e\u003cb\u003en=23\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e32.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.27\u003c/b\u003e \u003csup\u003e\u003cb\u003en=37\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6MWT Distance (m)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e486.18\u0026thinsp;\u0026plusmn;\u0026thinsp;99.47\u003c/b\u003e \u003csup\u003e\u003cb\u003en=17\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e387.53\u0026thinsp;\u0026plusmn;\u0026thinsp;102.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNotes: Bolded\u003c/b\u003e values are statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). kilograms (kg); meters (m); Six-Minute Walk Test (6MWT)\u003c/p\u003e \u003cp\u003eANCOVAs were performed to assess the influence of region (San Jos\u0026eacute; vs. Baltimore) on 6MWT and grip strength performance after controlling for body composition measures (total lean mass, percent lean mass, total fat mass, percent fat mass) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For grip strength, models were significant for total lean mass, percent lean mass, and percent fat mass, though no main effects of region were observed. All models for 6MWT were significant with significant main effects.\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\u003eExplained variance (η\u003csup\u003e2\u003c/sup\u003e) of region on physical performance measures, controlling for body composition covariates.\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCovariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMain Effect (Region)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCovariate effect\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGrip strength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal lean mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,57)\u0026thinsp;=\u0026thinsp;18.27\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.392\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1,57)\u0026thinsp;=\u0026thinsp;2.49\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.042\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1,57)\u0026thinsp;=\u0026thinsp;29.87\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.344\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent lean mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,57)\u0026thinsp;=\u0026thinsp;9.17\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.244\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1,57)\u0026thinsp;=\u0026thinsp;0.242\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.004\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1,57)\u0026thinsp;=\u0026thinsp;12.83\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.184\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal fat mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF(2,57)\u0026thinsp;=\u0026thinsp;2.46\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.079\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1,57)\u0026thinsp;=\u0026thinsp;4.74\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.077\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.034\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1,57)\u0026thinsp;=\u0026thinsp;0.383\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.007\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent fat mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,57)\u0026thinsp;=\u0026thinsp;8.94\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.239\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1,57)\u0026thinsp;=\u0026thinsp;0.076\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1,57)\u0026thinsp;=\u0026thinsp;12.39\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.179\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e6MWT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal lean mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,53)\u0026thinsp;=\u0026thinsp;5.83\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.180\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1,53)\u0026thinsp;=\u0026thinsp;10.04\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.159\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1,53)\u0026thinsp;=\u0026thinsp;0.64\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.012\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent lean mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,53)\u0026thinsp;=\u0026thinsp;6.41\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.195\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1,53)\u0026thinsp;=\u0026thinsp;12.82\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.195\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1,53)\u0026thinsp;=\u0026thinsp;1.61\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.029\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal fat mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,53)\u0026thinsp;=\u0026thinsp;6.24\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.191\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1,53)\u0026thinsp;=\u0026thinsp;9.91\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.158\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1,53)\u0026thinsp;=\u0026thinsp;1.32\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.024\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent fat mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(2,53)\u0026thinsp;=\u0026thinsp;6.38\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.194\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1,53)\u0026thinsp;=\u0026thinsp;12.72\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eη\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.193\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1,53)\u0026thinsp;=\u0026thinsp;1.56\u003c/p\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.029\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes: Results are presented as F(df\u003csub\u003eeffect\u003c/sub\u003e, df\u003csub\u003eerror\u003c/sub\u003e), with the explained variance (η\u003csup\u003e2\u003c/sup\u003e) and p-values for the model, main, and covariate effects. \u003cb\u003eBolded\u003c/b\u003e values indicate meeting statistical significance with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Six-Minute Walk Test (6MWT); degrees of freedom (df)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants from San Jos\u0026eacute; had a greater prevalence of sarcopenia based on appendicular lean mass and grip strength diagnostic criteria. Although not statistically significant, older adults in Baltimore tended to have a higher prevalence of low aerobic capacity (\u0026le;\u0026thinsp;400 m on the 6MWT) compared to those in San Jos\u0026eacute;. Older adults in the San Jos\u0026eacute; group had a significantly higher prevalence of meeting at least one sarcopenia criterion compared to older adults in the Baltimore group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of meeting sarcopenia criteria by region.\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSan Jos\u0026eacute;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaltimore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePearson Chi-squared test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow ALM/h\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (74.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e42.47;\u003c/b\u003e \u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow grip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (65.2%) \u003csup\u003en=23\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (16.2%) \u003csup\u003en=27\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14.97;\u003c/b\u003e \u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6MWT\u0026thinsp;\u0026le;\u0026thinsp;400 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (23.5%) \u003csup\u003en=17\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (43.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.03; \u003cem\u003e0.154\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMet at least 1 criterion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (79.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (48.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.02;\u003c/b\u003e \u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60 (64.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eBolded\u003c/b\u003e values are statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis analysis compared body composition, physical function, and sarcopenia prevalence among aging adults from San Jos\u0026eacute;, Costa Rica and Baltimore, Maryland, US. After age, sex, and BMI-matching groups between regions, older adults in San Jos\u0026eacute; were found to have poorer body composition than those in Baltimore, with less lean mass and a greater amount of relative fat mass. Older adults in Baltimore were stronger as measured with hand grip strength compared to older adults in San Jos\u0026eacute;. However, grip strength was no longer meaningfully different between regions after controlling for body composition. The significant covariate effect in these models indicates total lean mass, total lean percent, and total fat percent may be driving differences in grip strength observed between regions.\u003c/p\u003e \u003cp\u003eOlder adults from San Jos\u0026eacute; had better functional performance on the 6MWT compared to older adults from Baltimore. These regional differences remained significant even after accounting for body composition measures. This suggests something other than body composition is driving differences in 6MWT performance observed between regions. Participants from San Jos\u0026eacute; appear healthier from a cardiometabolic standpoint than those from Baltimore, with lower resting blood pressures and a lower prevalence of diabetes, which may help explain differences observed on the 6MWT[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Racial and ethnic differences between participants from the two regions alongside additional cultural factors may also help further explain regional differences in 6MWT performance. Questions of covariation by racial identity or ethnicity could not be answered in the present analysis given the absence of Black/African American adults in the San Jos\u0026eacute; cohort and absence of Hispanic/Latino participants in the Baltimore cohort. Future work should explore this question with a larger, more racially and ethnically diverse sample.\u003c/p\u003e \u003cp\u003eDifferences in sarcopenia prevalence between cohorts were observed when body composition, grip strength, and 6MWT performance were compared to cut scores used to establish presence or risk of sarcopenia. In particular, appendicular lean mass and grip strength diagnostic criteria identified a considerably higher prevalence of sarcopenia among participants from San Jos\u0026eacute; compared to those from Baltimore, however a non-significant trend towards greater sarcopenia prevalence by 6MWT criteria was observed among participants in Baltimore. This aligns with work from Glei et al. who found US older adults had better grip strength compared to Costa Rican older adults[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, this same study found cardiorespiratory capacity was greater for US older adults compared to Costa Rican older adults; while cardiorespiratory capacity was not directly captured in the present study, 6MWT performance is a well-established proxy for evaluating this metric[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Looking at the findings of the present analysis together, a picture emerges indicating participants from San Jos\u0026eacute; demonstrate muscle weakness, which can be explained by a lower amount of lean mass and higher amount of fat mass for this cohort, translating to a higher prevalence of sarcopenia diagnosis in this cohort. However, sociocultural, cardiometabolic health, lifestyle, or other influences may enable these Costa Ricans to function at a higher level for functional mobility tasks like prolonged walking[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These regional differences may have clinical implications, requiring tailored rehabilitation strategies to improve muscle mass and function in older adults from San Jos\u0026eacute; and Baltimore.\u003c/p\u003e \u003cp\u003eWhile this analysis includes measures of whole-body composition, it does not specifically evaluate composition and quality of key muscle groups required for functional mobility (e.g. knee extensors, hip extensors, hip abductors). Future investigations including measures of computed tomography or ultrasound imaging of these key muscle groups can provide important information on size and composition of these muscles, which would provide a more comprehensive understanding of muscle wasting and myosetatotic changes[16]. Additionally, future work may explore a more robust clinical evaluation to understand how domains of physical function and performance like walking ability, balance, and transfers are influenced by the present findings. Nonetheless, this initial analysis provides evidence that whole-body composition, including lean and fat mass, plays a role in explaining strength but not functional endurance differences observed between older adults in San Jos\u0026eacute; and Baltimore.\u003c/p\u003e \u003cp\u003eIt is important to acknowledge the cross-sectional nature of this analysis. This analysis identifies unique contributions of body composition and physical function, which differ between San Jos\u0026eacute; and Baltimore. Future work should evaluate body composition and physical function longitudinally to better understand how these components influence one another and to answer questions of causality and directionality of these relationships. Additionally, future work capturing exercise, diet, and social engagement habits, all of which play large roles in health with aging, can further contextualize how these cultural factors influence the presented outcomes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eObserved regional differences in muscle mass and physical function demonstrate that aging outcomes may be shaped by cultural, cardiometabolic, and environmental factors beyond body composition. These findings underscore the importance of culturally tailored strategies within global health frameworks to support physical function and reduce sarcopenia risk across diverse aging populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eUnited States US\u003c/p\u003e\n\u003cp\u003eKilograms kg\u003c/p\u003e\n\u003cp\u003eBody mass index BMI\u003c/p\u003e\n\u003cp\u003eDual energy x-ray absorptiometry DEXA\u003c/p\u003e\n\u003cp\u003eAnalysis of covariance ANCOVA\u003c/p\u003e\n\u003cp\u003eAppendicular lean mass ALM\u003c/p\u003e\n\u003cp\u003eEuropean Working Group of Sarcopenia in Older Persons Revised EWGSOP-2\u003c/p\u003e\n\u003cp\u003eMeters m\u003c/p\u003e\n\u003cp\u003eSystolic Blood Pressure SBP\u003c/p\u003e\n\u003cp\u003eDiastolic Blood Pressure DBP\u003c/p\u003e\n\u003cp\u003eHeart rate HR\u003c/p\u003e\n\u003cp\u003eBeats per minute bpm\u003c/p\u003e\n\u003cp\u003eMillimeters of mercury mmHg\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate:\u003c/em\u003e All study participants completed written informed consent prior to participation. Study protocols and analyses were approved by the University of Maryland Baltimore Institutional Review Board (HP-00096177).\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eConsent for publication:\u003c/em\u003e Not applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eAvailability of data and materials:\u003c/em\u003e The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eCompeting interests:\u003c/em\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eFunding:\u003c/em\u003e This study was supported by the Alicia and Yaya Fellowship in Global Aging through the University of Maryland, Baltimore and Universidad de Costa Rica. Data for this manuscript was supported by a Department of Veterans Affairs Merit Award (RX003484-01A2). This material is based upon work as part of the Advanced Fellowship in Geriatrics, supported by the U.S. Department of Veterans Affairs Office of Academic Affiliations, the Veterans Affairs Maryland Health Care System, and the Department of Veterans Affairs Baltimore Geriatric Research, Education, and Clinical Center.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eAuthors\u0026apos; contributions:\u003c/em\u003e KD, JR, AGG, and IMCH designed the study, collected data, and interpreted the statistical analyses. KD and JR drafted the initial manuscript and tables, and performed the initial statistical analysis. ESL contributed to data collection and analysis. OA contributed to data collection and study supervision. All authors read and approved the final manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eAcknowledgements:\u003c/em\u003e We thank our research subjects for their time and participation in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgeing. World Health Organization. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.who.int/countries/840\u003c/span\u003e\u003cspan address=\"https://data.who.int/countries/840\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 16 December 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodpaster BH, Carlson CL, Visser M, Kelley DE, Scherzinger A, Harris TB, et al. Attenuation of skeletal muscle and strength in the elderly: The Health ABC Study. 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The agreement of different techniques for muscle measurement in diagnosing sarcopenia: a systematic review and meta-analysis. Quant Imaging Med Surg. 2024;14:2177\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21037/qims-23-1089\u003c/span\u003e\u003cspan address=\"10.21037/qims-23-1089\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"global aging, sarcopenia, body composition, physical function","lastPublishedDoi":"10.21203/rs.3.rs-8866638/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8866638/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAs life span increases globally, so does the risk of aging with chronic health conditions. Differences in life span and health span between Costa Rica, a middle-income country, and the United States, a high-income country, suggest cultural context may influence how age-related changes in muscle mass, body composition, and physical function affect older adults. This analysis compared body composition, physical function, and sarcopenia prevalence among aging adults from two major metropolitan cities: San Jos\u0026eacute;, Costa Rica and Baltimore, Maryland, US.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e Baseline data from study participants at the Baltimore Veterans Affairs Medical Center were matched with publicly available baseline data from a similar cohort at Universidad de Costa Rica. All participants had assessments of body composition (dual energy x-ray absorptiometry), physical function (handgrip strength, Six Minute Walk Test [6MWT]), and general health characteristics (vitals, comorbidities). Sarcopenia prevalence was defined using European Working Group on Sarcopenia in Older Persons criteria. Participants were age- and sex- matched between sites prior to analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSeventy-eight participants (San Jos\u0026eacute; n\u0026thinsp;=\u0026thinsp;39; Baltimore n\u0026thinsp;=\u0026thinsp;39) were included. Compared to participants from Baltimore, participants from San Jos\u0026eacute; had lower lean mass (54.97\u0026thinsp;\u0026plusmn;\u0026thinsp;7.36 vs. 62.45\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91% bodyweight, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and higher fat mass (43.17\u0026thinsp;\u0026plusmn;\u0026thinsp;7.78 vs. 33.95\u0026thinsp;\u0026plusmn;\u0026thinsp;7.37% bodyweight, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Participants from San Jos\u0026eacute; also had lower grip strength (27.43\u0026thinsp;\u0026plusmn;\u0026thinsp;8.48 vs. 32.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.27 kg, p\u0026thinsp;=\u0026thinsp;0.04) but greater 6MWT distance (486.18\u0026thinsp;\u0026plusmn;\u0026thinsp;99.47 vs. 387.53\u0026thinsp;\u0026plusmn;\u0026thinsp;102.95 m, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to those from Baltimore. Regional differences in grip strength were no longer significant after adjusting for body composition, though 6MWT differences remained significant after controlling for absolute (kg) and relative (% bodyweight) lean and fat mass. Sarcopenia prevalence was greater in San Jos\u0026eacute; based on appendicular lean mass/height\u003csup\u003e2\u003c/sup\u003e (74.4% vs. 2.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and grip strength (65.2% vs. 16.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) criteria.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eRegional differences in muscle composition and physical function highlight the potential influence of cultural, cardiometabolic, and environmental factors beyond body composition alone. These findings underscore the importance of culturally and contextually tailored strategies to support physical function and mitigate sarcopenia risk in aging populations globally.\u003c/p\u003e","manuscriptTitle":"Beyond Body Composition: Regional Variations in Physical Function and Sarcopenia Among Older Adults in San José, Costa Rica and Baltimore, United States","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 09:28:42","doi":"10.21203/rs.3.rs-8866638/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0985864-8153-4470-8568-4ba1808cadf8","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T16:08:59+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 09:28:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8866638","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8866638","identity":"rs-8866638","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}