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Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy).
Strozza, Cosmo; Pasqualetti, Patrizio; Egidi, Viviana; Loreti, Claudia; Vannetti, Federica; Macchi, Claudio; Padua, Luca.
Afiliação
  • Strozza C; Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, J.B. Winsløws Vej 9B, 2nd floor, 5000, Odense C, Denmark. cstrozza@health.sdu.dk.
  • Pasqualetti P; Department of Statistical Sciences, Sapienza University of Rome, Viale Regina Elena 295, 00161, Rome, Italy. cstrozza@health.sdu.dk.
  • Egidi V; Fatebenefratelli Foundation for Health Research and Education, Via della Lungaretta 177, 00153, Rome, Italy.
  • Loreti C; Department of Statistical Sciences, Sapienza University of Rome, Viale Regina Elena 295, 00161, Rome, Italy.
  • Vannetti F; Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00136, Rome, Italy.
  • Macchi C; IRCCS Fondazione Don Carlo Gnocchi, Via di Scandicci 269, 50143, Florence, Italy.
BMC Geriatr ; 20(1): 289, 2020 08 15.
Article em En | MEDLINE | ID: mdl-32799807
BACKGROUND: Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. METHODS: Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. RESULTS: This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: "healthy", "physically healthy with cognitive impairment", "unhealthy", and "severely unhealthy". Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. CONCLUSIONS: Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nível de Saúde / Disfunção Cognitiva Tipo de estudo: Prognostic_studies Limite: Aged80 / Female / Humans / Male País/Região como assunto: Europa Idioma: En Revista: BMC Geriatr Assunto da revista: GERIATRIA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Dinamarca

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nível de Saúde / Disfunção Cognitiva Tipo de estudo: Prognostic_studies Limite: Aged80 / Female / Humans / Male País/Região como assunto: Europa Idioma: En Revista: BMC Geriatr Assunto da revista: GERIATRIA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Dinamarca