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Predictors of ageing-related decline across multiple cognitive functions

机译:多种认知功能中与衰老相关的衰退的预测因子

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It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years (n = 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. We tested the association of a wide variety of sociodemographic, fitness, health, and genetic variables with each of these cognitive change factors. Models that simultaneously included all covariates accounted for appreciable proportions of variance in the cognitive change factors (e.g. approximately one third of the variance in general cognitive change). However, beyond physical fitness and possession of the APOE e4 allele, very few predictors were incrementally associated with cognitive change at statistically significant levels. The results highlight a small number of factors that predict differences in cognitive ageing, and underscore that correlates of cognitive level are not necessarily predictors of decline. Even larger samples will likely be required to identify additional variables with more modest associations with normal-range heterogeneity in aging-related cognitive declines.
机译:重要的是要发现为什么某些人的认知能力比其他人的年龄要好。我们将多元增长曲线模型应用于来自在11岁时通过多领域智商测度的狭窄年龄队列数据以及在70岁,73岁,13岁时对视觉空间,记忆,结晶和加工速度能力的13种测度的综合电池组和76岁(n = 901岁,年龄70岁)。我们发现,十三项认知指标的表现变化方差的48%在所有指标之间均得到共享,另外26%的指标针对四个能力领域,而26%的指标针对测试。我们测试了各种社会人口统计学,适应性,健康状况和遗传变量与这些认知变化因素的相关性。同时包含所有协变量的模型在认知变化因子中占相当大的方差比例(例如,约占一般认知变化方差的三分之一)。但是,除了身体健康和拥有APOE e4等位基因外,很少有预测因子在统计学上显着水平上与认知变化相关。结果强调了少数几个预测认知老化差异的因素,强调认知水平相关性的下划线不一定是下降的预测因素。在衰老相关的认知能力下降中,甚至可能需要更大的样本来确定与正常范围异质性更适度关联的其他变量。

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