Trajectories of healthy ageing among older adults with multimorbidity: A growth mixture model using harmonised data from eight ATHLOS cohorts.
Trajectories of healthy ageing among older adults with multimorbidity: A growth mixture model using harmonised data from eight ATHLOS cohorts.
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DOI：
10.1371/journal.pone.0248844
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Prina AM
中科院分区：
文献类型：
--
作者：
Nguyen H;Moreno-Agostino D;Chua KC;Vitoratou S;Prina AM
在这项研究中，我们的目的是1）描述健康老龄化轨迹模式，2）检查多发病与健康老龄化轨迹模式之间的关联，3）评估不同疾病组如何影响健康老龄化轨迹随时间的预测。我们的研究是基于130880个人从健康的老龄化轨迹：纵向机会和协同作用（ATHLOS）协调数据集，以及9171个人从波2-7的英国老龄化纵向研究（艾尔莎）。使用健康老龄化指数得分，其中包括41个项目，涵盖健康和老龄化的各个领域，作为结果，我们采用增长混合模型的方法来识别具有不同健康老龄化轨迹的个人的潜在类别。进行多项logistic回归以评估多发病状态和多发病模式是否以及如何与健康老龄化的变化相关，控制社会人口统计学和生活方式风险因素。在ATHLOS和艾尔莎数据集中确定了三种相似的健康老龄化轨迹模式：1）“高稳定”组（ATHLOS为76%，艾尔莎为61%），2）“低稳定”组（ATHLOS为22%，艾尔莎为36%）和3）“快速下降”组（ATHLOS为2%，艾尔莎为3%）。与未患多项抑郁症的人相比，多项抑郁症患者进入“快速下降”组的可能性高1.7倍（OR = 1.7，95%CI：1.4-2.1），进入“低稳定”组的可能性高11.7倍（OR = 11.7，95%CI：10.9-12.6）。心肺/关节炎/白内障组与“快速下降”和“低稳定”组均相关（OR = 2.1，95% CI：1.2-3.8和OR = 9.8，95% CI：7.5-12.7）。健康老龄化是异质的。虽然多重死亡与健康老龄化轨迹较差的几率较高有关，但健康老龄化轨迹预计下降的程度取决于多重死亡的具体模式。
In this study we aimed to 1) describe healthy ageing trajectory patterns, 2) examine the association between multimorbidity and patterns of healthy ageing trajectories, and 3) evaluate how different groups of diseases might affect the projection of healthy ageing trajectories over time. Our study was based on 130880 individuals from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) harmonised dataset, as well as 9171 individuals from Waves 2–7 of the English Longitudinal Study of Ageing (ELSA). Using a healthy ageing index score, which comprised 41 items, covering various domains of health and ageing, as outcome, we employed the growth mixture model approach to identify the latent classes of individuals with different healthy ageing trajectories. A multinomial logistic regression was conducted to assess if and how multimorbidity status and multimorbidity patterns were associated with changes in healthy ageing, controlled for sociodemographic and lifestyle risk factors. Three similar patterns of healthy ageing trajectories were identified in the ATHLOS and ELSA datasets: 1) a ‘high stable’ group (76% in ATHLOS, 61% in ELSA), 2) a ‘low stable’ group (22% in ATHLOS, 36% in ELSA) and 3) a ‘rapid decline’ group (2% in ATHLOS, 3% in ELSA). Those with multimorbidity were 1.7 times (OR = 1.7, 95% CI: 1.4–2.1) more likely to be in the ‘rapid decline’ group and 11.7 times (OR = 11.7 95% CI: 10.9–12.6) more likely to be in the ‘low stable’ group, compared with people without multimorbidity. The cardiorespiratory/arthritis/cataracts group was associated with both the ‘rapid decline’ and the ‘low stable’ groups (OR = 2.1, 95% CI: 1.2–3.8 and OR = 9.8, 95% CI: 7.5–12.7 respectively). Healthy ageing is heterogeneous. While multimorbidity was associated with higher odds of having poorer healthy ageing trajectories, the extent to which healthy ageing trajectories were projected to decline depended on the specific patterns of multimorbidity.
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影响因子：
4.6
作者：
Caballero FF;Soulis G;Engchuan W;Sánchez-Niubó A;Arndt H;Ayuso-Mateos JL;Haro JM;Chatterji S;Panagiotakos DB
通讯作者：
Panagiotakos DB
影响因子：
4.6
作者：
Daskalopoulou, Christina;Koukounari, Artemis;Prina, Matthew
通讯作者：
Prina, Matthew
影响因子：
3.9
作者：
Hsu, Hui-Chuan
通讯作者：
Hsu, Hui-Chuan
DOI：
10.1007/s40271-013-0041-0
发表时间：
2014
期刊：
The patient
影响因子：
--
作者：
Nguyen TH;Han HR;Kim MT;Chan KS
通讯作者：
Chan KS
影响因子：
3
作者：
BOZDOGAN, H
通讯作者：
BOZDOGAN, H