Background: Abnormal cognitive aging is closely related to dementia.
Objectives: This study aimed to estimate the effect of cardiovascular health (CVH) metrics on abnormal cognitive aging.
Design: A longitudinal cohort study.
Setting: Participants were recruited from the Chinese Longitudinal Health Longevity Survey.
Participants: A total of 3298 participants aged ≥65 years with normal cognitive performance at baseline were included.
Measurements: Cognitive performance was measured by the Chinese version of the Mini-Mental State Examination (MMSE). CVH was assessed with six metrics, including hypertension, diabetes, exercise, body mass index (BMI), diet, and smoking. Group-based trajectory model was used to identify the trajectory groups of cognitive aging over 12 years (2002-2014 and 2005-2018). The parametric g-formula was applied to estimate the effect of each single six CVH metrics and their combinations on the 12-year cognitive aging trajectory.
Results: Four trajectory groups of cognitive aging were identified: Stable-high (77.4%), Unstable (4.9%), Slow decline (11.1%), and Rapid decline (6.6%). Unstable, Slow decline, and Rapid decline trajectory groups were considered as abnormal cognitive aging (22.6%). Single interventions on hypertension, exercise, BMI, and diet could reduce the risk of abnormal cognitive aging. Moreover, the risk ratios of joint intervention on exercise, BMI, and diet for Unstable, Slow decline, and Rapid decline trajectory groups were 0.38 (95% CI: 0.30-0.48), 0.45 (95% CI: 0.37-0.54), and 0.3 (95% CI: 0.23-0.41), respectively.
Conclusion: A considerable proportion of the participants experienced abnormal cognitive aging during their aging process. Interventions on these CVH metrics (i.e., exercise, BMI, and diet), which are fairly practical and feasible for older adults, may be effective strategies for preventing abnormal cognitive aging.
Keywords: Cognitive aging; cardiovascular health; g-formula; group-based trajectory model.