Wu Zimu, Woods Robyn L, Chong Trevor T-J, Orchard Suzanne G, McNeil John J, Shah Raj C, Wolfe Rory, Murray Anne M, Storey Elsdon, Ryan Joanne
School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
Front Neurol. 2022 Aug 3;13:950644. doi: 10.3389/fneur.2022.950644. eCollection 2022.
There is variability across individuals in cognitive aging. To investigate the associations of several modifiable factors with high and low cognitive performance.
Data came from 17,724 community-dwelling individuals aged 65-98 years. Global cognition, verbal fluency, episodic memory, and psychomotor speed were assessed over up to seven years. Group-based multi-trajectory modeling identified distinct cognitive trajectories. Structural equation modeling examined the direct/indirect associations of social/behavioral factors and several chronic conditions with cognitive trajectories.
Seven trajectory subgroups were identified. In the structural equation modeling we compared two subgroups-participants with the highest (14.2%) and lowest (4.1%) cognitive performance with the average subgroup. Lower education, never alcohol intake, and frailty directly predicted increased risk of low performance, and decreased likelihood of high performance. Hypertension (RR: 0.69, 95%CI: 0.60-0.80), obesity (RR: 0.84, 95%CI: 0.73-0.97), diabetes (RR: 0.69, 95%CI: 0.56-0.86) and depression (RR: 0.68, 95%CI: 0.54-0.85) only predicted lower likelihood of high cognitive performance, while dyslipidemia was only associated with low performance (RR: 1.30, 95%CI: 1.07-1.57). Living alone predicted increased risk of low cognitive performance and several comorbidities. Smoking did not predict cognitive trajectories but was associated with increased risk of diabetes, obesity and frailty. Findings were similar when examining the direct associations between modifiable risk factors and all seven cognitive subgroups.
Although several modifiable factors were associated with high performance, and reversely with low performance, this was not observed for obesity, hypertension and dyslipidemia. Further, health behaviors may affect cognitive function indirectly, geriatric conditions. This indicates that strategies to promote healthy cognitive aging, may be distinct from those targeting dementia prevention.
认知衰老存在个体差异。旨在研究几个可改变因素与高低认知表现之间的关联。
数据来自17724名年龄在65 - 98岁的社区居民。在长达七年的时间里对整体认知、语言流畅性、情景记忆和精神运动速度进行评估。基于群体的多轨迹模型确定了不同的认知轨迹。结构方程模型研究了社会/行为因素和几种慢性疾病与认知轨迹的直接/间接关联。
确定了七个轨迹亚组。在结构方程模型中,我们将两个亚组——认知表现最高(14.2%)和最低(4.1%)的参与者与平均亚组进行了比较。较低的教育水平、从不饮酒和身体虚弱直接预示着低表现风险增加,以及高表现可能性降低。高血压(风险比:0.69,95%置信区间:0.60 - 0.80)、肥胖(风险比:0.84,95%置信区间:0.73 - 0.97)、糖尿病(风险比:0.69,95%置信区间:0.56 - 0.86)和抑郁症(风险比:0.68,95%置信区间:0.54 - 0.85)仅预示着高认知表现的可能性较低,而血脂异常仅与低表现相关(风险比:1.30,95%置信区间:1.07 - 1.57)。独居预示着低认知表现和几种合并症的风险增加。吸烟不能预测认知轨迹,但与糖尿病、肥胖和身体虚弱的风险增加有关。在研究可改变风险因素与所有七个认知亚组之间的直接关联时,结果相似。
尽管有几个可改变因素与高表现相关,反之与低表现相关,但肥胖、高血压和血脂异常并非如此。此外,健康行为可能间接影响认知功能,即老年疾病。这表明促进健康认知衰老的策略可能与预防痴呆的策略不同。