JOURNAL ARTICLE

Investigating Biological Pathways Underpinning the Longitudinal Association Between Loneliness and Cognitive Impairment.

  • Published In: Journals of Gerontology Series A: Biological Sciences & Medical Sciences, 2023, v. 78, n. 8. P. 1417 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Yu, Kexin; Ng, Ted Kheng Siang 3 of 3

Abstract

This article investigates whether specific biomarkers mediate the longitudinal relationship between loneliness and cognitive impairment (CI) in older adults, using data from the Health and Retirement Study (N = 7,037) over an eight-year period. Loneliness was measured by the 3-item University of California-Los Angeles (UCLA) loneliness scale, and cognitive status was assessed via the modified telephone interview for cognitive status (TICSm). The study examined five biomarkers—hemoglobin A1c (HbA1C), high-density lipoprotein (HDL), low-density lipoprotein (LDL), C-reactive protein (CRP), and cystatin C (CYSC)—as potential mediators. Results showed that while loneliness was initially associated with worse cognitive status and HbA1C partially mediated this relationship, all associations became nonsignificant after controlling for sociodemographic and health-related confounders, and none of the biomarkers consistently mediated the loneliness-CI link longitudinally. The findings highlight the importance of accounting for confounders and suggest that other factors, such as self-rated health and chronic disease burden, may better explain the association between loneliness and cognitive decline.

Additional Information

  • Source:Journals of Gerontology Series A: Biological Sciences & Medical Sciences. 2023/08, Vol. 78, Issue 8, p1417
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:1079-5006
  • DOI:10.1093/gerona/glac213
  • Accession Number:169728840
  • Copyright Statement:Copyright of Journals of Gerontology Series A: Biological Sciences & Medical 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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