Relació de l’IMC amb els determinants sociodemogràfics, els estils de vida i l’estat de salut en la gent gran
Introduction: ageing is a process where changes occur at different levels such as physical, psychological and social, which can affect the nutritional status of older people and have an impact on their quality of life. For this reason it is necessary to investigate the needs and resources of the eld...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/17655 |
| Acceso en línea: | http://hdl.handle.net/10256/17655 |
| Access Level: | acceso abierto |
| Palabra clave: | Índex de massa corporal Body mass index Persones grans -- Salut i higiene Older people -- Health and hygiene Envelliment actiu Active aging Promoció de la salut Health promotion |
| Sumario: | Introduction: ageing is a process where changes occur at different levels such as physical, psychological and social, which can affect the nutritional status of older people and have an impact on their quality of life. For this reason it is necessary to investigate the needs and resources of the elderly in order to promote an active and healthy ageing. Objective: to know the relation between BMI and sociodemographic determinants, lifestyle and health status in individuals aged 50 and over in the province of Girona; to describe the differences in the nutritional status of the elderly according to sex and age group. Methodology: this was a descriptive cross-sectional study. The data analyzed were obtained from the Maturity and Satisfactory Ageing in Girona (MESGI50) study from wave 5 in 2013 linked to the Survey of Health, Ageing and Retirement in Europe (SHARE) study. BMI was the dependent variable, and sociodemographic determinants, lifestyles and health status the independent variables. Binary and multivariate logistic regression models were used. Data were analyzed using SPSS Statistics 22 |
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