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Prevalence, risks and outcomes of frailty in People Experiencing Homelessness: a protocol for secondary analysis of Health Needs Audit data.
Dawes, Jo; Walters, Kate; Frost, Rachael; Bagkeris, Emmanouil; Burton, Alexandra; Hertzberg, Debra; Hayward, Andrew.
Afiliación
  • Dawes J; Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
  • Walters K; Primary Care and Population Health, University College London, Rowland Hill Street, London, NW3 2PF, UK.
  • Frost R; Primary Care and Population Health, University College London, Rowland Hill Street, London, NW3 2PF, UK.
  • Bagkeris E; Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, London, WC1N 1EH, UK.
  • Burton A; Department of Behavioural Science and Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
  • Hertzberg D; Homeless Link, London, England, UK.
  • Hayward A; Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
NIHR Open Res ; 4: 9, 2024.
Article en En | MEDLINE | ID: mdl-39238901
ABSTRACT
Frailty describes a health state related to ageing where people become less resilient to health challenges and more likely to have adverse outcomes if they become unwell. People experiencing homelessness (PEH) are known to have poor health, with research suggesting that many become frail at a younger age than the general population. Previous research using small-scale primary data collection suggests that the prevalence of frailty in homeless populations varies widely (16-55%), with variations in sample sizes and settings partially accounting for differences in current estimates. The prevalence, risks, and outcomes of frailty in PEH are poorly understood. We propose to carry out a secondary analysis of existing health survey data collected from 2,792 PEH. This will involve creating a Frailty Index (FI) to identify frail people within the dataset. Regression analyses will be used to identify associations between potential risk factors and outcomes of frailty in this population. This protocol will 1) Outline the creation of a FI to assess the frailty prevalence within a dataset of health information collected from a cohort of PEH and 2) Describe proposed methods of regression analysis for identification of associations between frailty and risks factors/outcomes of frailty in the cohort of PEH within the dataset. The processes described in this paper can inform future development of FIs in other datasets. It is expected that the FI created will be an appropriate and robust method for identifying frailty in a cohort of PEH and results of the secondary data analysis will provide a more robust estimate of the associations between frailty and risk factors/outcomes.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: NIHR Open Res Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: NIHR Open Res Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Reino Unido