Stolz Erwin, Hoogendijk Emiel O, Mayerl Hannes, Freidl Wolfgang
Institute of Social Medicine and Epidemiology, Medical University of Graz, Austria.
Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC-Location VU University Medical Center, The Netherlands.
J Gerontol A Biol Sci Med Sci. 2021 Aug 13;76(9):1619-1626. doi: 10.1093/gerona/glaa266.
Baseline frailty index (FI) values have been shown to predict mortality among older adults, but little is known about the effects of changes in FI on mortality.
In a coordinated approach, we analyzed data from 4 population-based cohorts: the Health and Retirement Study (HRS), the Survey of Health, Ageing and Retirement in Europe (SHARE), the English Longitudinal Survey of Ageing (ELSA), and the Longitudinal Aging Study Amsterdam (LASA), comprising a total of 24 961 respondents (65+), 95 897 observations, up to 9 repeated FI assessments, and up to 23 years of mortality follow-up. The effect of time-varying FI on mortality was modeled with joint regression models for longitudinal and time-to-event data.
Differences (of 0.01) in current FI levels (hazard ratio [HR] = 1.04, 95% credible interval [CI] = 1.03-1.05) and baseline FI levels (HR = 1.03, 95% CI = 1.03-1.05) were consistently associated with mortality across studies. Importantly, individuals with steeper FI growth also had a higher mortality risk: An increase in annual FI growth by 0.01 was associated with an increased mortality risk of HR = 1.56 (95% CI = 1.49-1.63) in HRS, HR = 1.24 (95% CI = 1.13-1.35) in SHARE, HR = 1.40 (95% CI = 1.25-1.52) in ELSA, and HR = 1.71 (95% CI = 1.46-2.01) in LASA.
FI changes predicted mortality independently of baseline FI differences. Repeated assessment of frailty and individual's frailty trajectory could provide a means to anticipate further health deterioration and mortality and could thus support clinical decision making.
基线衰弱指数（FI）值已被证明可预测老年人的死亡率，但关于FI变化对死亡率的影响知之甚少。
我们采用协调一致的方法，分析了来自4个基于人群的队列的数据：健康与退休研究（HRS）、欧洲健康、老龄化与退休调查（SHARE）、英国老龄化纵向调查（ELSA）以及阿姆斯特丹纵向老龄化研究（LASA），共纳入24961名受访者（65岁及以上），95897次观察，多达9次重复的FI评估，以及长达23年的死亡率随访。使用纵向和事件发生时间数据的联合回归模型对随时间变化的FI对死亡率的影响进行建模。
在各项研究中，当前FI水平（风险比[HR]=1.04，95%可信区间[CI]=1.03 - 1.05）和基线FI水平（HR = 1.03，95% CI = 1.03 - 1.05）相差0.01均与死亡率持续相关。重要的是，FI增长较快的个体也有较高的死亡风险：在HRS中，年度FI增长增加0.01与死亡风险增加相关，HR = 1.56（95% CI = 1.49 - 1.63）；在SHARE中，HR = 1.24（95% CI = 1.13 - 1.35）；在ELSA中，HR = 1.40（95% CI = 1.25 - 1.52）；在LASA中，HR = 1.71（95% CI = 1.46 - 2.01）。
FI变化可独立于基线FI差异预测死亡率。对衰弱和个体衰弱轨迹的重复评估可为预测进一步的健康恶化和死亡率提供一种方法，从而支持临床决策。
