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Author(s):
Hao Huang, Lei Zhang, Ding Zhang, Sitong Lu, Jiaqi Lin, Jingyao Huang, Zibo Ni, Jien Pan, Xingxing Hu, Ying Lin, Dongsheng Hu, Ming Zhang, Fulan Hu
Publish date:
29 May 2025
Journal:
International Journal of Cardiology Cardiovascular Risk and Prevention
PubMed ID:
40519233

Abstract

Background: The impact of tea consumption, particularly the differences between sweetened and unsweetened tea, on the risk of cardiovascular disease (CVD) remains underexplored. This study investigates the associations between the consumption of unsweetened, sugar-sweetened, and artificially sweetened tea and the incidence of CVD.

Methods: We included 177,810 participants from the UK Biobank, with a median follow-up period of 12.7 years. Cox proportional hazards models were utilized to assess the associations between tea intake and the risk of CVD, coronary artery disease (CAD), stroke, and heart failure (HF) incidents. Additionally, we investigated potential interactions with polygenic risk scores (PRS) for CVD.

Results: During the follow-up period, 15,003 cases of incident CVD were recorded. A U-shaped association was identified between unsweetened tea consumption and CVD risk, with the lowest risk observed at a consumption level of 0-2 drinks/day (HR: 0.92, 95 % CI: 0.87-0.97). In contrast, no significant associations were found for sugar-sweetened or artificially sweetened tea. The reduced CVD risk associated with unsweetened tea was consistent across various subtypes, including CAD, stroke, and HF. Additionally, no significant interactions were observed between tea consumption and PRS.

Conclusions: Consuming unsweetened tea is associated with a reduced risk of incident CVD, CAD, stroke, and HF. In contrast, no significant associations were observed for sugar-sweetened or artificially sweetened tea. These findings indicate that unsweetened tea may contribute positively to the prevention of CVD, independent of genetic risk factors. Further research is needed to validate these results and explore the underlying mechanisms.

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Institution:
Shenzhen University, China

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