Ma Xiangge, Gao Hongjian, Wu Yutong, Zhu Xinyu, Wu Shuicai, Lin Lan
Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Biomedicines. 2025 Feb 21;13(3):549. doi: 10.3390/biomedicines13030549.
: Given the escalating global prevalence of age-related cognitive impairments, identifying modifiable factors is crucial for developing targeted interventions. : 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. : 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, = 6.06 × 10; HR = 1.50, 95% CI: 1.22-1.86, = 1.62 × 10, 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. 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.
鉴于全球与年龄相关的认知障碍患病率不断攀升,确定可改变的因素对于制定针对性干预措施至关重要。在排除患有痴呆症和大量缺失数据的参与者后,纳入了来自英国生物银行(UKB)的453,950名个体。对四个认知领域的认知衰退进行了评估。表现出最大衰退的前10%被归类为“认知风险人群”。分析了来自三类的83个潜在因素。采用单变量和多变量Cox比例风险模型来评估这些因素对认知衰退的独立和联合影响。计算人群归因分数(PAF)以估计消除每个风险类别后的潜在影响。我们的研究结果显示,不良的医学和精神病史对处理速度和视觉情景记忆衰退有显著影响(风险比(HR)分别为1.34,95%置信区间:1.20 - 1.51,P = 6.06×10⁻⁴;HR = 1.50,95%置信区间:1.22 - 1.86,P = 1.62×10⁻³)。此外,PAF分析表明,生理和生化标志物是预防处理速度衰退的最关键风险类别(PAF = 7.03%),而社会和行为因素对预防视觉情景记忆衰退的影响最大(PAF = 9.68%)。高等教育、社会经济地位和握力是保护因素,而高体重指数(BMI)、高血压和抑郁症则有害。通过识别这一高风险群体并量化可改变因素的影响,本研究为制定针对性干预措施以延缓认知衰退和改善中老年人群的公共卫生结果提供了有价值的见解。