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Updated: Jun 30, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
Published on: November 14, 2017
Investigating Modifiable Factors Associated with Cognitive Decline: Insights from the UK Biobank
Xiangge Ma1, Hongjian Gao1, Yutong Wu1
1Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Abstract:
Objectives: Given the escalating global prevalence of age-related cognitive impairments, identifying modifiable factors is crucial for developing targeted interventions. Methods: After excluding participants with dementia and substantial missing data, 453,950 individuals from UK Biobank (UKB) were included. Cognitive decline was assessed across four cognitive domains. The top 10% exhibiting the greatest decline were categorized as the "Cognitively At-Risk Population". Eighty-three potential factors from three categories were analyzed. Univariate and multivariate Cox proportional hazards models were employed to assess the independent and joint effects of these factors on cognitive decline. Population Attributable Fractions (PAFs) were calculated to estimate the potential impact of eliminating each risk category. Results: Our findings revealed a significant impact of unfavorable medical and psychiatric histories on processing speed and visual episodic memory decline (Hazard Ratio (HR) = 1.34, 95% CI: 1.20-1.51, p = 6.06 × 10⁻7; HR = 1.50, 95% CI: 1.22-1.86, p = 1.62 × 10⁻4, respectively). Furthermore, PAF analysis indicated that physiological and biochemical markers were the most critical risk category for preventing processing speed decline (PAF = 7.03%), while social and behavioral factors exerted the greatest influence on preventing visual episodic memory decline (PAF = 9.68%). Higher education, socioeconomic status, and handgrip strength emerged as protective factors, whereas high body mass index (BMI), hypertension, and depression were detrimental. Conclusions: By identifying this high-risk group and quantifying the impact of modifiable factors, this study provides valuable insights for developing targeted interventions to delay cognitive decline and improve public health outcomes in middle-aged and older adults.
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