Cognitive Trajectories in Subjective Cognitive Decline: Identifying Modifiable Risks and Developing a Web-Based Assessment Tool for Personalized Prevention

Introduction: The escalating global prevalence of dementia poses a significant public health challenge, underscoring the urgent need for effective early prevention. Subjective Cognitive Decline (SCD) is increasingly recognized as a critical pre-clinical stage of dementia; however, the longitudinal course of cognition in individuals with SCD is markedly heterogeneous. While advanced age is a primary determinant, the influence of modifiable risk factors on these divergent trajectories remains poorly understood. This investigation aimed to identify distinct patterns of cognitive decline among older adults with SCD and evaluate associated modifiable risk factors, with the ultimate goal of translating these empirical findings into a practical risk assessment tool for early stratification. Methods This study analyzed five waves of data (2011–2020) from 3097 older adults with SCD in the CHARLS. We employed latent class growth analysis (LCGA) to identify distinct cognitive trajectories and subsequently used multinomial logistic regression to evaluate the modifiable risk factors associated with these patterns.Based on the identified predictors, a web-based risk assessment tool was constructed to facilitate personalized risk profiling. Results Three distinct cognitive trajectories were identified: a Stable group (38.3%), a Slow Decline group (29.8%), and a Rapid Decline group (31.9%). Compared to the Stable group, factors significantly associated with a higher likelihood of belonging to the Rapid Decline group included disability (OR = 1.441, 95%CI: 1.128, 1.841), underweight (OR = 1.661, 95%CI: 1.130, 2.441) or obesity (OR = 1.337, 95%CI: 1.079, 1.658), drinking (OR = 1.326, 95%CI: 1.033, 1.701), smoking (OR = 1.417, 95%CI: 1.153, 1.740), depression (OR = 1.419, 95%CI: 1.143, 1.762), IADL impairment (OR = 5.523, 95%CI: 3.016, 10.115), excessive exercise (OR = 1.562, 95%CI: 1.140, 2.141), fall down (OR = 1.29, 95%CI: 1.005, 1.656), and insufficient night sleep (OR = 1.484, 95%CI: 1.190, 1.852). Conversely, male (OR = 0.525, 95%CI: 0.403, 0.686), higher education (OR = 0.115, 95%CI: 0.049, 0.267), physical activity (OR = 0.391, 95%CI: 0.263, 0.580), social activity (OR = 0.457, 95%CI: 0.265, 0.789), brain activity (OR = 0.405, 95%CI: 0.306, 0.537), voluntary activity (OR = 0.602, 95%CI: 0.385, 0.940), internet use (OR = 0.355, 95%CI: 0.262, 0.481), and indoor tidiness (OR = 0.598, 95%CI: 0.489, 0.732) were associated with a lower likelihood of rapid cognitive decline. Conclusions This study reveals that cognitive progression in SCD is heterogeneous and significantly influenced by modifiable factors. To bridge the gap between research and practice, we translated these findings into a user-friendly online risk assessment tool. This instrument allows clinicians and the public to visualize individual cognitive trajectories and identify specific targets for intervention. Ultimately, this risk-based approach supports proactive health management and aims to mitigate the public health burden of dementia.