Bai Wangyang, Luo Xiao, Chen Hangqi, Ye Xiaofei, Xu Jinfang, Guo Xiaojing, He Jia
School of Medicine, Tongji University, Shanghai, China.
Department of Health Statistics, Navy Medical University, Shanghai, China.
Psychogeriatrics. 2025 Sep;25(5):e70077. doi: 10.1111/psyg.70077.
This study aimed to investigate the trajectory of cognitive decline and explore the association between education levels and the trajectory of cognitive decline among Chinese middle-aged and older adults.
Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) among Chinese middle-aged and older adults with five waves of follow-up, 2011-2020. Education levels were self-reported by the participants at baseline. To explore the trajectories of cognitive decline, a group-based trajectory modelling (GBTM) approach was employed. Multivariable logistic regression models were conducted to measure the association between education levels and the trajectories of cognitive decline. Subgroup and sensitivity analyses were also conducted to further explore and validate the association.
A total of 6384 Chinese adults were enrolled in the study, with a median age of 56 (P, P: 49, 62); 2953 (46.3%) were females. A total of 1402 (22.0%) participants had no formal education at baseline. Three trajectories of cognitive decline were considered in the best GBTM model, including a stable group (37.92%), a mild decline group (42.28%), and a rapid decline group (19.80%). Education levels were associated with cognitive decline trajectories in multivariable logistic regression models (p < 0.05). The subgroup and sensitivity analyses demonstrated comparable results as well.
Three trajectories of cognitive decline (stable, mild and rapid decline) were identified using the GBTM approach. A higher level of education could reduce the risk of cognitive decline among Chinese middle-aged and older adults. Our findings suggest that improving access to education holds significant potential for reducing public health burdens associated with cognitive decline.
本研究旨在调查认知衰退的轨迹，并探讨中国中老年人群教育水平与认知衰退轨迹之间的关联。
数据来源于中国健康与养老追踪调查（CHARLS），该调查对中国中老年人群进行了2011年至2020年的五轮随访。教育水平由参与者在基线时自我报告。为了探索认知衰退的轨迹，采用了基于群体的轨迹建模（GBTM）方法。进行多变量逻辑回归模型以衡量教育水平与认知衰退轨迹之间的关联。还进行了亚组分析和敏感性分析，以进一步探索和验证这种关联。
本研究共纳入6384名中国成年人，中位年龄为56岁（四分位间距：49，62）；2953名（46.3%）为女性。共有1402名（22.0%）参与者在基线时未接受过正规教育。最佳GBTM模型考虑了三种认知衰退轨迹，包括稳定组（37.92%）、轻度衰退组（42.28%）和快速衰退组（19.80%）。在多变量逻辑回归模型中，教育水平与认知衰退轨迹相关（p < 0.05）。亚组分析和敏感性分析也显示了类似的结果。
使用GBTM方法确定了三种认知衰退轨迹（稳定、轻度和快速衰退）。较高的教育水平可以降低中国中老年人群认知衰退的风险。我们的研究结果表明，改善教育机会对于减轻与认知衰退相关的公共卫生负担具有巨大潜力。
