Consumption of flavonoids and risk of hormone-related cancers: a systematic review and meta-analysis of observational studies
Abstract
Background: Flavonoids seem to have hormone-like and anti-hormone properties so that the consumption of flavonoids may have potential effects on hormone-related cancers (HRCs), but the findings have been inconsistent so far. This meta-analysis was aimed to explore the association between flavonoids intake and HRCs risk among observational studies.
Methods: Qualified articles, published on PubMed, EMBASE, and China National Knowledge Infrastructure (CNKI) from January 1999 to March 2022 and focused on relationships between flavonoids (total, subclass of and individual flavonoids) and HRCs (breast, ovarian, endometrial, thyroid, prostate and testicular cancer), were retrieved for pooled analysis. Random effects models were performed to calculate the pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Funnel plots and Begg's/Egger's test were used to evaluate the publication bias. Subgroup analyses and sensitivity analyses were conducted to explore the origins of heterogeneity.
Results: All included studies were rated as medium or high quality. Higher consumption of flavonols (OR = 0.85, 95% CI: 0.76-0.94), flavones (OR = 0.85, 95% CI: 0.77-0.95) and isoflavones (OR = 0.87, 95% CI: 0.82-0.92) was associated with a decreased risk of women-specific cancers (breast, ovarian and endometrial cancer), while the higher intake of total flavonoids was linked to a significantly elevated risk of prostate cancer (OR = 1.11, 95% CI: 1.02-1.21). A little evidence…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
Read the paper
Related studies
- Knowledge Management Perspective of Generative Artificial Intelligence
- Navigating Generative Artificial Intelligence Promises and Perils for Knowledge and Creative Work
- Characterizing the evolving research on enterprise content management
- Large language models and multimodal foundation models for precision oncology
- From Generative AI to Extended Reality: Multidisciplinary Perspectives on the Challenges, Opportunities, and Future of Educational Computing
- Generative Artificial Intelligence: A New Engine for Advancing Environmental Science and Engineering
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.