B Davies1, F García2, I Ara3, F Rodríguez Artalejo4, L Rodriguez-Mañas5, S Walter6. 1. Fundación para la Investigación Biomédica Getafe University Hospital, Madrid, Spain. 2. Geriatrics Department, Virgen del Valle Hospital, Toledo, Spain; CIBER of Frailty and Healthy Aging-CIBERFES. 3. CIBER of Frailty and Healthy Aging-CIBERFES; Faculty of Sport Sciences, University of Castilla La Mancha, Spain. 4. Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain; CIBER of Epidemiology and Public Health-CIBERESP. 5. Fundación para la Investigación Biomédica Getafe University Hospital, Madrid, Spain; CIBER of Frailty and Healthy Aging-CIBERFES; Geriatrics Department, Getafe University Hospital, Madrid, Spain. Electronic address: leocadio.rodriguez@salud.madrid.org. 6. Fundación para la Investigación Biomédica Getafe University Hospital, Madrid, Spain; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA.
Abstract
INTRODUCTION: Frailty and sarcopenia are correlates of musculoskeletal aging that represent a state of vulnerability increasing the risk of negative health outcomes. Standardized definitions are lacking for both, and sometimes both concepts are used interchangeably. However, no large study has assessed the coexistence of these 2 entities in a cohort of older community-dwelling people. METHODS: Data were taken from the Toledo Study of Healthy Aging (TSHA), a study of community-dwelling elderly (≥65 years). The study population consists of 1611 participants with frailty and sarcopenia assessments. For sarcopenia, we used 3 criteria: European Working Group on Sarcopenia in Older People (EWGSOP), the Foundation for the National Institutes of Health (FNIH), and the FNIH fitted to the cut-off points of our population [standardized FNIH (sFNIH)]. Frailty was assessed according to the Fried criteria with cut-off points adjusted to our population. We used logistic regression to assess the relationship between sarcopenia and frailty and measures of diagnostic accuracy to evaluate the potential use of sarcopenia as a diagnostic marker for frailty. RESULTS: The mean age of the population was 75.42 years (±5.86). Overall, 72 (4.5%) were frail. In addition, 352 (21.8%), 332 (20.6%), and 453 (28.1%) participants were considered sarcopenic according to the EWGSOP, FNIH, and sFNIH criteria, respectively. The prevalence of frailty among those with sarcopenia was 8.2% (29/352), 15.7% (52/332), and 10.4% (47/453). Moreover, among frail people, the prevalence of sarcopenia was 40.27%, 72.2%, and 65.3% according to the used criteria. Sarcopenia showed a low sensitivity (<10%) but high specificity (>97%) for the diagnosis of frailty, with a low intercorrelation (Cramer V = 0.16, 0.40, and 0.30) between the 3 criteria and frailty. Using multivariate logistic regression, frailty was associated with sarcopenia according to EWGSOP [odds ratio (OR) = 1.67, 95% confidence interval (CI) = 0.95, 2.96], FNIH (OR = 10.61, 95% CI = 5.8, 19.4), and sFNIH (OR = 6.63, 95% CI =3.5, 12.53). CONCLUSION: Frailty and sarcopenia are distinct but related conditions. Sarcopenia is not a useful clinical biomarker of frailty, but its absence might be useful to exclude frailty.
INTRODUCTION: Frailty and sarcopenia are correlates of musculoskeletal aging that represent a state of vulnerability increasing the risk of negative health outcomes. Standardized definitions are lacking for both, and sometimes both concepts are used interchangeably. However, no large study has assessed the coexistence of these 2 entities in a cohort of older community-dwelling people. METHODS: Data were taken from the Toledo Study of Healthy Aging (TSHA), a study of community-dwelling elderly (≥65 years). The study population consists of 1611 participants with frailty and sarcopenia assessments. For sarcopenia, we used 3 criteria: European Working Group on Sarcopenia in Older People (EWGSOP), the Foundation for the National Institutes of Health (FNIH), and the FNIH fitted to the cut-off points of our population [standardized FNIH (sFNIH)]. Frailty was assessed according to the Fried criteria with cut-off points adjusted to our population. We used logistic regression to assess the relationship between sarcopenia and frailty and measures of diagnostic accuracy to evaluate the potential use of sarcopenia as a diagnostic marker for frailty. RESULTS: The mean age of the population was 75.42 years (±5.86). Overall, 72 (4.5%) were frail. In addition, 352 (21.8%), 332 (20.6%), and 453 (28.1%) participants were considered sarcopenic according to the EWGSOP, FNIH, and sFNIH criteria, respectively. The prevalence of frailty among those with sarcopenia was 8.2% (29/352), 15.7% (52/332), and 10.4% (47/453). Moreover, among frail people, the prevalence of sarcopenia was 40.27%, 72.2%, and 65.3% according to the used criteria. Sarcopenia showed a low sensitivity (<10%) but high specificity (>97%) for the diagnosis of frailty, with a low intercorrelation (Cramer V = 0.16, 0.40, and 0.30) between the 3 criteria and frailty. Using multivariate logistic regression, frailty was associated with sarcopenia according to EWGSOP [odds ratio (OR) = 1.67, 95% confidence interval (CI) = 0.95, 2.96], FNIH (OR = 10.61, 95% CI = 5.8, 19.4), and sFNIH (OR = 6.63, 95% CI =3.5, 12.53). CONCLUSION: Frailty and sarcopenia are distinct but related conditions. Sarcopenia is not a useful clinical biomarker of frailty, but its absence might be useful to exclude frailty.
Authors: Henning T Langer; Agata A Mossakowski; Keith Baar; Julian Alcazar; Marcos Martin-Rincon; Luis M Alegre; Ignacio Ara; Jose A L Calbet; J Mathew Hinkley; Paul M Coen; Brian A Irving; Timothy D Allerton; Sreekumaran Nair; Ricardo M Lima; Juan Pablo Rey-López; David Scott; Robin M Daly; Peter R Ebeling; Alan Hayes; Anne-Julie Tessier; Stéphanie Chevalier; Brandon A Yates; LeAndra R Brown; Thomas W Storer; Wayne L Westcott; Artemissia-Phoebe Nifli; Robert V Musci; Adam R Konopka; Karyn L Hamilton; Russell T Hepple Journal: J Appl Physiol (1985) Date: 2019-01-01
Authors: E Dent; J E Morley; A J Cruz-Jentoft; H Arai; S B Kritchevsky; J Guralnik; J M Bauer; M Pahor; B C Clark; M Cesari; J Ruiz; C C Sieber; M Aubertin-Leheudre; D L Waters; R Visvanathan; F Landi; D T Villareal; R Fielding; C W Won; O Theou; F C Martin; B Dong; J Woo; L Flicker; L Ferrucci; R A Merchant; L Cao; T Cederholm; S M L Ribeiro; L Rodríguez-Mañas; S D Anker; J Lundy; L M Gutiérrez Robledo; I Bautmans; I Aprahamian; J M G A Schols; M Izquierdo; B Vellas Journal: J Nutr Health Aging Date: 2018 Impact factor: 4.075
Authors: Claudio Franceschi; Paolo Garagnani; Cristina Morsiani; Maria Conte; Aurelia Santoro; Andrea Grignolio; Daniela Monti; Miriam Capri; Stefano Salvioli Journal: Front Med (Lausanne) Date: 2018-03-12