Prague College of Psychosocial Studies, Hekrova 805, 149 00, Prague 11, Háje, Czech Republic.
Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
BMC Psychol. 2023 Feb 2;11(1):34. doi: 10.1186/s40359-023-01069-7.
SuperAging is one of the current concepts related to elite, resilient or high-functioning cognitive aging. The main aim of our study was to find possible predictors of SuperAgers (SA).
Community-dwelling older persons (N = 96) aged 80-101 years in 2018 were repeatedly tested (year 2012 and 2018). SA were defined based on their performance in 2018 as persons of 80+ years of age who recalled ≥ 9 words in the delayed recall of the Philadelphia Verbal Learning Test, and had a normal performance in non-memory tasks [the Boston Naming Test, the Trail Making Test Part B, and Category Fluency ("Animals")], which was defined as a score within or above one standard deviation from the age and education appropriate average. Three composite scores (CS; immediate memory, processing speed, and executive functions) were created from the performance in 2012, and analysed as possible predictors of SA status in 2018.
We identified 19 SA (15 females) and 77 nonSA (42 females), groups did not significantly differ in age, years of education, and sex. The logistic regression model (p = 0.028) revealed three predictors of SA from the baseline (year 2012), including processing speed (p = 0.006; CS-speed: the Prague Stroop Test-Dots and the Digit Symbol Substitution Test), sex (p = 0.015), and age (p = 0.045).
Thus, SA may be predicted based on the level of processing speed, which supports the hypothesis of the processing speed theory of healthy aging.
超级老化是与精英、有弹性或高功能认知老化相关的当前概念之一。我们研究的主要目的是寻找超级老年人（SA）的可能预测因素。
2018 年，我们对居住在社区中的年龄在 80-101 岁的老年人（N=96）进行了多次测试（2012 年和 2018 年）。根据他们在 2018 年的表现，将 SA 定义为 80 岁以上的人，在费城词语学习测试的延迟回忆中回忆了≥9 个单词，并且在非记忆任务（波士顿命名测试、轨迹制作测试 B 部分和类别流畅性（“动物”））中表现正常，定义为得分在年龄和教育适当平均值的一个标准差内或以上。从 2012 年的表现中创建了三个综合分数（CS；即时记忆、处理速度和执行功能），并分析了它们是否为 2018 年 SA 状态的可能预测因素。
我们确定了 19 名 SA（15 名女性）和 77 名非 SA（42 名女性），两组在年龄、受教育年限和性别方面没有显著差异。逻辑回归模型（p=0.028）揭示了来自基线（2012 年）的三个 SA 预测因素，包括处理速度（p=0.006；CS-速度：布拉格斯特鲁普测试点和数字符号替代测试）、性别（p=0.015）和年龄（p=0.045）。
因此，可能可以根据处理速度水平预测 SA，这支持了健康老化处理速度理论的假设。
