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Longitudinal quantiles of frailty trajectories considering death: new insights into sex and cohort differences in the reference curves for frailty progression of older European
The Journals of Gerontology Series A: Biological Sciences and Medical Sciences ( IF 5.1 ) Pub Date : 2024-02-23 , DOI: 10.1093/gerona/glae060
Alejandra Marroig 1 , Fernando Massa 1 , Annie Robitaille 2 , Scott M Hofer 3 , Erwin Stolz 4 , Graciela Muniz-Terrera 5
Affiliation  

Background Most previous studies of frailty trajectories in older adults focus on the average trajectory and ignore death. Longitudinal quantile analysis of frailty trajectories permits the definition of reference curves, and the application of mortal cohort inference provides more realistic estimates than models that ignore death. Methods Using data from individuals aged 65 or older (n=25446) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) from 2004 to 2020, we derived repeated values of the Frailty Index (FI) based on the accumulation of health deficits. We applied weighted Generalized Estimating Equations to estimate the quantiles of the FI trajectory, adjusting for sample attrition due to death, sex, education, and cohort. Results The FI quantiles increased with age and progressed faster for those with the highest level of frailty (βa0.9=0.0229, p<0.001; βa0.5=0.0067, p<0.001; H0: βa0.5=βa0.9, p<0.001). Education was consistently associated with a slower progression of the FI in all quantiles (βae0.1=-0.0001, p<0.001; βae0.5=-0.0004, p<0.001; βae0.9=-0.0003, p<0.001) but sex differences varied across the quantiles. Women with the highest level of frailty showed a slower progression of the FI than men when considering death. Finally, no cohort effects were observed for the FI progression. Conclusions Quantile FI trajectories varied by age, sex, education, and cohort. These differences could inform the practice of interventions aimed at older adults with the highest level of frailty.

中文翻译:

考虑死亡的衰弱轨迹的纵向分位数:对欧洲老年人衰弱进展参考曲线中性别和队列差异的新见解

背景 以往大多数关于老年人衰弱轨迹的研究都集中在平均轨迹上,而忽略了死亡。衰弱轨迹的纵向分位数分析允许定义参考曲线,并且死亡队列推断的应用提供了比忽略死亡的模型更现实的估计。方法 使用 2004 年至 2020 年欧洲健康、老龄化和退休调查 (SHARE) 中 65 岁或以上个体 (n=25446) 的数据,我们根据以下因素的累积得出衰弱指数 (FI) 的重复值:健康缺陷。我们应用加权广义估计方程来估计 FI 轨迹的分位数,并根据死亡、性别、教育和队列造成的样本流失进行调整。结果 FI 分位数随着年龄的增长而增加,并且对于虚弱程度最高的人,进展更快(βa0.9=0.0229,p<0.001;βa0.5=0.0067,p<0.001;H0:βa0.5=βa0.9,p< ;0.001)。在所有分位数中,教育程度始终与 FI 进展缓慢相关(βae0.1=-0.0001,p<0.001;βae0.5=-0.0004,p<0.001;βae0.9=-0.0003,p<0.001),但性别各分位数之间的差异各不相同。在考虑死亡时,虚弱程度最高的女性的 FI 进展速度比男性慢。最后,没有观察到 FI 进展的队列效应。结论 分位数 FI 轨迹因年龄、性别、教育程度和队列而异。这些差异可以为针对虚弱程度最高的老年人的干预措施的实践提供参考。
更新日期:2024-02-23
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