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在一个基于人群的样本中识别图片命名纵向变化的潜在类别。

Identifying latent classes of longitudinal change in picture naming in a population-based sample.

作者信息

Finkel Deborah, Liu Ying, Gatz Margaret, Schneider Stefan, Hernandez Raymond, Orriens Bart, Kapteyn Arie

机构信息

Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA.

Institute for Gerontology, School of Health and Welfare, Jönköping University, Jönköping, Sweden.

出版信息

Aging Clin Exp Res. 2025 Aug 29;37(1):262. doi: 10.1007/s40520-025-03169-3.

Abstract

Although cognitive changes may not become apparent until after age 65, many factors associated with late-life decline are already well-established in midlife. In particular, deficits in picture naming have been associated with early and accelerated cognitive change. A measure of picture vocabulary, requiring participants to name drawings of objects, was collected in 4 waves (each separated by 2 years) of the Understanding America Study, a nationally representative internet panel (mean follow-up = 5.60 years). Participants were 5005 adults ranging in age from 18 to 98 at intake (mean = 48.81); 58% women. Growth mixture models were used to identify latent class structure in age-based quadratic growth models (centered at median age of 53). The best-fitting model identified 3 classes: high intercept and scores increase with age (60% of the sample), medium intercept and scores increase with age (37%), low intercept and no change with age (3%). Analyses of variance indicated that the class for which picture naming did not change with age had a significantly elevated probability of cognitive impairment. Multinomial logistic regression indicated that probability of cognitive impairment contributed to estimation of class membership even in the context of related demographic and cognitive variables. Tasks like Picture Vocabulary may be useful early indicators of onset of cognitive impairment.

摘要

尽管认知变化可能直到65岁之后才会明显显现,但许多与晚年衰退相关的因素在中年时期就已确立。特别是,图片命名缺陷与早期和加速的认知变化有关。在一项具有全国代表性的互联网面板研究“了解美国研究”的4个阶段(每个阶段相隔2年)中,收集了一项图片词汇量测量数据,该测量要求参与者说出物体的图片名称。参与者为5005名成年人,入组时年龄在18岁至98岁之间(平均年龄=48.81岁);女性占58%。使用增长混合模型在基于年龄的二次增长模型(以53岁的中位数年龄为中心)中识别潜在类别结构。拟合度最佳的模型识别出3个类别:高截距且分数随年龄增长(占样本的60%)、中等截距且分数随年龄增长(37%)、低截距且分数不随年龄变化(3%)。方差分析表明,图片命名不随年龄变化的类别出现认知障碍的概率显著升高。多项逻辑回归表明,即使在考虑相关人口统计学和认知变量的情况下,认知障碍的概率也有助于类别归属的估计。像图片词汇这样的任务可能是认知障碍发作的有用早期指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1efa/12397163/4c3cc4703a02/40520_2025_3169_Fig1_HTML.jpg

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