Wei Yifang, Zhang Yi, Li Yuansheng, Meng Fanshuo, Zhang Ruixiang, You Zuming, Xie Chenxi, Zhou Jiyuan
Department of Biostatistics, School of Public Health (State Key Laboratory of Multi-Organ Injury Prevention and Treatment, and Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou 510515, China.
Behav Sci (Basel). 2025 Mar 14;15(3):365. doi: 10.3390/bs15030365.
The analysis of cognitive trajectories is relatively underexplored in China. Furthermore, most previous studies examining the association between cognitive function and mortality have been limited to cross-sectional perspectives. This study aims to identify distinct cognitive trajectories and the corresponding influencing factors and investigate the impact of these trajectories on all-cause mortality in Chinese older adults. A total of 6232 subjects aged 65 years and above were drawn from the Chinese Longitudinal Healthy Longevity Survey. Growth mixture models were utilized to identify different cognitive trajectories, while Cox proportional hazards models were used to examine the association between the cognitive trajectories and all-cause mortality after adjusting for covariates. Four cognitive trajectories were identified: rapid decline group, slow decline group, low-level stable group, and high-level stable group. Some factors such as age, sex, and marital status were significantly associated with trajectories. Compared to the high-level stable group, adjusted hazard ratios and 95% confidence intervals (CIs) for the all-cause mortality were 3.87 (95% CI: 3.35-4.48), 1.41 (95% CI: 1.24-1.59), and 1.37 (95% CI: 1.18-1.58) for the rapid decline group, the slow decline group, and the low-level stable group, respectively, indicating that these three groups had a higher mortality risk. In summary, these findings facilitate the development of targeted health promotion measures, which have implications for reducing the social and economic burdens of cognitive decline.
在中国,对认知轨迹的分析相对较少受到关注。此外,以往大多数研究认知功能与死亡率之间关联的研究都局限于横断面视角。本研究旨在识别不同的认知轨迹及其相应的影响因素,并调查这些轨迹对中国老年人全因死亡率的影响。共有6232名65岁及以上的受试者来自中国老年健康长寿纵向调查。采用生长混合模型识别不同的认知轨迹,同时使用Cox比例风险模型在调整协变量后检验认知轨迹与全因死亡率之间的关联。确定了四种认知轨迹:快速下降组、缓慢下降组、低水平稳定组和高水平稳定组。年龄、性别和婚姻状况等一些因素与轨迹显著相关。与高水平稳定组相比,快速下降组、缓慢下降组和低水平稳定组全因死亡率的调整后风险比及95%置信区间(CI)分别为3.87(95%CI:3.35 - 4.48)、1.41(95%CI:1.24 - 1.59)和1.37(95%CI:1.18 - 1.58),表明这三组有更高的死亡风险。总之,这些发现有助于制定有针对性的健康促进措施,这对减轻认知衰退的社会和经济负担具有重要意义。