Lívia Maria Santiago1, Robbert J J Gobbens2, Marcel A L M van Assen3, Cleber Nascimento Carmo4, Daniele Bittencourt Ferreira5, Inês Echenique Mattos6. 1. Federal University of Rio de Janeiro, Faculty of Medicine, Rua Rodolpho Paulo Rocco, 255/room 9E11, Cidade Universitária, Zip Code 21941- 913, Rio de Janeiro, RJ, Brazil; National School of Public Health/Oswaldo Cruz Foundation, Department of Epidemiology and Quantitative Methods, Rua Leopoldo Bulhões, 1480/room 817b, Manguinhos, Zip Code 21041-210, Rio de Janeiro, RJ, Brazil. Electronic address: liviamsantiago@gmail.com. 2. Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, De Boelelaan 1109, 1081 HV, Amsterdam, The Netherlands; Zonnehuisgroep Amstelland, Groenelaan 7, 1186 AA, Amstelveen, The Netherlands; Department of General Practice, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium. Electronic address: gobbens.rjj@casema.nl. 3. Department of Methodology and Statistics, Tilburg School of Social and Behavioral Sciences, Warandelaan 2, 90153, Tilburg University, Tilburg, The Netherlands; Department of Sociology, Utrecht University, Padualaan 14, 3584 CH, Utrecht, The Netherlands. Electronic address: m.a.l.m.vanassen@uvt.nl. 4. National School of Public Health/Oswaldo Cruz Foundation, Department of Epidemiology and Quantitative Methods, Rua Leopoldo Bulhões, 1480/room 817b, Manguinhos, Zip Code 21041-210, Rio de Janeiro, RJ, Brazil. Electronic address: cleber.carmo@gmail.com. 5. National School of Public Health/Oswaldo Cruz Foundation, Department of Epidemiology and Quantitative Methods, Rua Leopoldo Bulhões, 1480/room 817b, Manguinhos, Zip Code 21041-210, Rio de Janeiro, RJ, Brazil. Electronic address: danibittfer@hotmail.com. 6. National School of Public Health/Oswaldo Cruz Foundation, Department of Epidemiology and Quantitative Methods, Rua Leopoldo Bulhões, 1480/room 817b, Manguinhos, Zip Code 21041-210, Rio de Janeiro, RJ, Brazil. Electronic address: imattos@ensp.fiocruz.br.
Abstract
PURPOSE: This study aimed to determine the predictive value of the Brazilian Tilburg Frailty Indicator (TFI) for adverse health outcomes (falls, hospitalization, disability and death), in a follow-up period of twelve months. METHODS: This longitudinal study was carried out with a sample of people using primary health care services in Rio de Janeiro, Brazil. At baseline the sample consisted of 963 people aged 60 years and older. A subset of all respondents participated again one year later (n = 640, 66.6% response rate). We used the TFI, the Katz's scale for assessing ADL disability and the Lawton Scale for assessing IADL disability. Falls, hospitalization and death were also assessed using a questionnaire. RESULTS: The prevalence of frailty was 44.2% and the mean score of the TFI was 4.4 (SD = 3.0). There was a higher risk of loss in functional capacity in ADL (OR = 3.03, CI95% 1.45-6.29) and in IADL (OR = 1.51, CI95% 1.05-2.17), falls (OR = 2.08, CI95% 1.21-3.58), hospitalization (OR = 1.83, CI95% 1.10-3.06), and death (HR = 2.73, CI95% 1.04-7.19) for frail when compared to non-frail elderly, in the bivariate analyses. Controlling for the sociodemographic variables, the frailty domains together improved the prediction of hospitalization, falls and loss in functional capacity in ADL, but not loss in functional capacity in IADL. CONCLUSION: The TFI is a good predictor of adverse health outcomes among elderly users of primary care services in Brazil and appears an adequate and easy to administer tool for monitoring their health conditions.
PURPOSE: This study aimed to determine the predictive value of the Brazilian Tilburg Frailty Indicator (TFI) for adverse health outcomes (falls, hospitalization, disability and death), in a follow-up period of twelve months. METHODS: This longitudinal study was carried out with a sample of people using primary health care services in Rio de Janeiro, Brazil. At baseline the sample consisted of 963 people aged 60 years and older. A subset of all respondents participated again one year later (n = 640, 66.6% response rate). We used the TFI, the Katz's scale for assessing ADL disability and the Lawton Scale for assessing IADL disability. Falls, hospitalization and death were also assessed using a questionnaire. RESULTS: The prevalence of frailty was 44.2% and the mean score of the TFI was 4.4 (SD = 3.0). There was a higher risk of loss in functional capacity in ADL (OR = 3.03, CI95% 1.45-6.29) and in IADL (OR = 1.51, CI95% 1.05-2.17), falls (OR = 2.08, CI95% 1.21-3.58), hospitalization (OR = 1.83, CI95% 1.10-3.06), and death (HR = 2.73, CI95% 1.04-7.19) for frail when compared to non-frail elderly, in the bivariate analyses. Controlling for the sociodemographic variables, the frailty domains together improved the prediction of hospitalization, falls and loss in functional capacity in ADL, but not loss in functional capacity in IADL. CONCLUSION: The TFI is a good predictor of adverse health outcomes among elderly users of primary care services in Brazil and appears an adequate and easy to administer tool for monitoring their health conditions.
Authors: Hélio José Coelho-Júnior; Marco Carlos Uchida; Anna Picca; Roberto Bernabei; Francesco Landi; Riccardo Calvani; Matteo Cesari; Emanuele Marzetti Journal: Aging Clin Exp Res Date: 2021-02-15 Impact factor: 3.636
Authors: Ascensión Doñate-Martínez; Tamara Alhambra-Borrás; Estrella Durá-Ferrandis Journal: Int J Environ Res Public Health Date: 2022-10-05 Impact factor: 4.614