Background: The effect of tea consumption on conditions such as hypertension, diabetes, and obesity has attracted significant global interest. However, the results of various studies on this topic have been mixed and somewhat contentious. Therefore, we conducted a Mendelian randomization (MR) analysis to investigate the causal relationships between tea consumption and the aforementioned health conditions.

Methods: A bidirectional two-sample MR analysis was used to systematically explores the associations between tea consumption and hypertension, diabetes, and obesity. MR-Egger regression, weighted median, inverse variance weighted, and weighted mode methods were used to evaluate the potential causal associations. Leave-one-out sensitivity test was used to check the robustness of the IVW estimates.

Results: MR analysis indicated that genetically predicted tea consumption is associated with a protective effect against hypertension, with an odds ratio (OR) of 0.78 and a 95% confidence interval (CI) ranging from 0.64 to 0.95. Additionally, tea consumption appeared to have a potential protective effect on type 2 diabetes and obesity related to excessive calorie intake, influenced by specific single nucleotide polymorphisms (SNPs), namely "rs57462170" and "rs17685." No causal link was observed between the consumption of green or herbal tea and hypertension, diabetes, or obesity. However, there was a marginal negative association between type 2 diabetes and tea consumption and (OR = 0.99; 95% CI: 0.97-1.00) and a significant negative correlation between obesity due to excessive calorie intake and green tea consumption (OR = 0.35; 95% CI: 0.16-0.78).

Conclusion: This study demonstrates a protective causal relationship between the consumption of tea (including black and green teas) and reduced risk of hypertension. Furthermore, our results suggest that tea intake may also have a protective effect on type 2 diabetes and obesity. The results recommend further research to verify or refine these findings.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11562749PMC
http://dx.doi.org/10.3389/fnut.2024.1428445DOI Listing

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