Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, UK.
J Gerontol A Biol Sci Med Sci. 2021 Apr 30;76(5):867-875. doi: 10.1093/gerona/glab009.
We aimed to examine the multimorbidity patterns within a representative sample of UK older adults and their association with concurrent and subsequent memory.
Our sample consisted of 11 449 respondents (mean age at baseline was 65.02) from the English Longitudinal Study of Aging (ELSA). We used 14 health conditions and immediate and delayed recall scores (IMRC and DLRC) over 7 waves (14 years of follow-up). Latent class analyses were performed to identify the multimorbidity patterns and linear mixed models were estimated to explore their association with their memory trajectories. Models were adjusted by sociodemographics, body mass index (BMI), and health behaviors.
Results showed 8 classes: Class 1: Heart Disease/Stroke (26%), Class 2: Asthma/Lung Disease (16%), Class 3: Arthritis/Hypertension (13%), Class 4: Depression/Arthritis (12%), Class 5: Hypertension/Cataracts/Diabetes (10%), Class 6: Psychiatric Problems/Depression (10%), Class 7: Cancer (7%), and Class 8: Arthritis/Cataracts (6%). At baseline, Class 4 was found to have lower IMRC and DLRC scores and Class 5 in DLRC, compared to the no multimorbidity group (n = 6380, 55.72% of total cohort). For both tasks, in unadjusted models, we found an accelerated decline in Classes 1, 3, and 8; and, for DLRC, also in Classes 2 and 5. However, it was fully attenuated after adjustments.
These findings suggest that individuals with certain combinations of health conditions are more likely to have lower levels of memory compared to those with no multimorbidity and their memory scores tend to differ between combinations. Sociodemographics and health behaviors have a key role to understand who is more likely to be at risk of an accelerated decline.
本研究旨在调查英国老年人群代表性样本中的共病模式及其与并发和随后记忆的关系。
我们的样本包括来自英国老龄化纵向研究（ELSA）的 11449 名应答者（基线时的平均年龄为 65.02 岁）。我们使用了 14 种健康状况和即时和延迟回忆评分（IMRC 和 DLRC），共 7 个波次（14 年的随访）。采用潜在类别分析来确定共病模式，并使用线性混合模型来探讨其与记忆轨迹的关系。模型通过社会人口统计学、体重指数（BMI）和健康行为进行调整。
结果显示有 8 种共病模式：模式 1：心脏病/中风（26%）、模式 2：哮喘/肺部疾病（16%）、模式 3：关节炎/高血压（13%）、模式 4：抑郁/关节炎（12%）、模式 5：高血压/白内障/糖尿病（10%）、模式 6：精神问题/抑郁（10%）、模式 7：癌症（7%）和模式 8：关节炎/白内障（6%）。在基线时，与无共病组（n=6380，总队列的 55.72%）相比，发现模式 4 的即时回忆和延迟回忆评分较低，而模式 5 仅在延迟回忆中评分较低。在未调整的模型中，对于两个任务，我们都发现模式 1、3 和 8 的记忆下降加速；对于延迟回忆，还发现模式 2 和 5 的记忆下降加速。然而，调整后这些关联完全减弱。
这些发现表明，与无共病者相比，某些健康状况组合的个体更有可能记忆力较低，而且他们的记忆评分在不同组合之间存在差异。社会人口统计学和健康行为在理解谁更容易面临记忆下降加速的风险方面起着关键作用。
