Yilin Chen , Huachen Xue , Sizhi Ai , Yaping Liu , Yu Nie , Qi-Yong H. Ai , Jihui Zhang , Yannis Yan Liang
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引用次数: 0
Abstract
Aim
This study aimed to investigate the association of social isolation, loneliness, and their trajectory with the risk of developing type 2 diabetes mellitus (T2DM) across genetic risk.
Methods
We included 439,337 participants (mean age 56.3 ± 8.1 years) enrolled in the UK Biobank study who were followed up until May 31, 2021. Social isolation and loneliness were self-reported and were further categorized into never, transient, incident, and persistent patterns.
Results
During a median follow-up of 12.7 years, 15,258 incident T2DM cases were documented. Social isolation (versus no social isolation: hazard ratio (HR) 95 % confidence interval (CI) 1.04 [1.00;1.09]) and loneliness (versus no loneliness: 1.26 [1.19;1.34]) were associated with an increased T2DM risk, independent of the genetic risk for T2DM. The interactions existed between social isolation and loneliness (Pinteraction < 0.05); the increased T2DM risk associated with social isolation was only significant among participants without loneliness. In the longitudinal analysis, only persistent social isolation (versus never social isolation: 1.22 [1.02;1.45]) was associated with an increased T2DM risk, whereas incident loneliness (versus never loneliness: 1.95 [1.40;2.71]) and persistent loneliness (2.00 [1.31;3.04]) were associated with higher T2DM risks.
Conclusion
Social isolation and loneliness, especially their persistent pattern, were independently associated with an increased incident T2DM risk, irrespective of an individual's genetic risk. Loneliness modified the association between social isolation and incident T2DM.
期刊介绍:
A high quality scientific journal with an international readership
Official publication of the SFD, Diabetes & Metabolism, publishes high-quality papers by leading teams, forming a close link between hospital and research units. Diabetes & Metabolism is published in English language and is indexed in all major databases with its impact factor constantly progressing.
Diabetes & Metabolism contains original articles, short reports and comprehensive reviews.