JOURNAL ARTICLE

Association of Plasma Fatty Acid Profile With Trajectory of Multimorbidity and Mortality: A Community-Based Longitudinal Study.

  • Published In: Journals of Gerontology Series A: Biological Sciences & Medical Sciences, 2025, v. 80, n. 5. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Li, Yang; Wang, Jiao; Miao, Yuyang; Dunk, Michelle M; Maioli, Silvia; Fang, Zhongze; Zhang, Qiang; Xu, Weili 3 of 3

Abstract

This article investigates the association between plasma fatty acid profiles, quantified by a healthy fatty acid score (HFAS), and the trajectory of multimorbidity as well as event-free survival in a large cohort of 138,685 chronic disease-free participants from the UK Biobank followed for up to 16 years. The study found that higher HFAS, reflecting a healthier plasma fatty acid metabolic profile, was linked to a lower risk of chronic diseases or death, prolonged event-free survival by approximately 0.6 years, and a slower accumulation of multimorbidity over time. Additionally, a healthy lifestyle—defined by factors such as normal body mass index, nonsmoking, nondrinking, and regular physical activity—strengthened the protective association of HFAS with chronic disease risk and multimorbidity progression. These findings suggest that both plasma fatty acid composition and lifestyle factors may play important roles in modulating the development of multiple chronic conditions and overall healthspan.

Additional Information

  • Source:Journals of Gerontology Series A: Biological Sciences & Medical Sciences. 2025/05, Vol. 80, Issue 5, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:1079-5006
  • DOI:10.1093/gerona/glaf031
  • Accession Number:184925840
  • 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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