JOURNAL ARTICLE

Immigration Experience and Cognitive Function Trajectories Among Older Chinese Immigrants.

  • Published In: Journals of Gerontology Series B: Psychological Sciences & Social Sciences, 2023, v. 78, n. 1. P. 124 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Tang, Fengyan; Li, Ke; Rauktis, Mary E; Buckley, Tommy D; Chi, Iris 3 of 3

Abstract

This article examines how life-course immigration experiences relate to cognitive trajectories among older Chinese immigrants in the United States, using longitudinal data from the Population Study of Chinese Elderly (PINE). Three distinct cognitive trajectory classes were identified—low, moderate, and high functioning—with lower acculturation levels and speaking Taishanese dialect associated with increased risk of cognitive decline, while higher perceived discrimination and Mandarin preference were linked to better cognitive outcomes after controlling for sociodemographic and health factors. The study highlights the complexity of immigration-related factors such as age at migration, reasons for migration, acculturation, perceived discrimination, and dialect preference in shaping cognitive aging, emphasizing the need for culturally and linguistically tailored support to mitigate cognitive impairment risks in this population. Limitations include the regional focus on the Chicago area and measurement constraints regarding acculturation and discrimination, suggesting further research is needed to clarify underlying mechanisms.

Additional Information

  • Source:Journals of Gerontology Series B: Psychological Sciences & Social Sciences. 2023/01, Vol. 78, Issue 1, p124
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:1079-5014
  • DOI:10.1093/geronb/gbac120
  • Accession Number:161878275
  • Copyright Statement:Copyright of Journals of Gerontology Series B: Psychological Sciences & Social Sciences is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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