Dawes Jo, Walters Kate, Frost Rachael, Bagkeris Emmanouil, Burton Alexandra, Hertzberg Debra, Hayward Andrew
Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
Primary Care and Population Health, University College London, Rowland Hill Street, London, NW3 2PF, UK.
NIHR Open Res. 2024 Mar 12;4:9. doi: 10.3310/nihropenres.13545.1. eCollection 2024.
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.
衰弱描述了一种与衰老相关的健康状态，在这种状态下，人们对健康挑战的恢复力下降，如果身体不适，更有可能出现不良后果。已知无家可归者健康状况不佳，研究表明，许多人比一般人群更早出现衰弱。以往使用小规模原始数据收集的研究表明，无家可归人群中衰弱的患病率差异很大（16%-55%），样本量和研究背景的差异部分解释了当前估计值的差异。无家可归者衰弱的患病率、风险和后果尚不清楚。我们建议对从2792名无家可归者收集的现有健康调查数据进行二次分析。这将包括创建一个衰弱指数（FI），以识别数据集中的衰弱人群。回归分析将用于识别该人群中潜在风险因素与衰弱后果之间的关联。本方案将：1）概述创建一个FI，以评估从一组无家可归者收集的健康信息数据集中的衰弱患病率；2）描述用于识别数据集中无家可归者队列中衰弱与风险因素/衰弱后果之间关联的拟议回归分析方法。本文所述的过程可为其他数据集中FI的未来发展提供参考。预计创建的FI将是识别无家可归者队列中衰弱的一种合适且稳健的方法，二次数据分析的结果将为衰弱与风险因素/后果之间的关联提供更可靠的估计。
