Association Between Education Levels and Cognitive Decline Trajectories Among Chinese Middle-Aged and Older Adults With Five Waves of Follow-Up: A Group-Based Trajectory Modelling Approach.

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.