Long-Term Consumption of Green Tea Can Reduce the Degree of Depression in Postmenopausal Women by Increasing Estradiol
- PMID: 37960167
- PMCID: PMC10650806
- DOI: 10.3390/nu15214514
Long-Term Consumption of Green Tea Can Reduce the Degree of Depression in Postmenopausal Women by Increasing Estradiol
Abstract
Postmenopausal women face a higher risk of depression due to a combination of social and physiological factors. As a beverage rich in a variety of bioactive substances, green tea has significant effects on metabolism, inflammation and endocrine, and may reduce the risk of depression, but few studies have looked at the effects of green tea on postmenopausal women. Therefore, we designed this study to investigate the effects of long-term green tea consumption on inflammation, endocrine and depression levels in postmenopausal women. We investigated a tea-producing village and eventually included 386 postmenopausal women, both in the tea drinking and control groups. The results showed that there were significant differences in the degree of insomnia, degree of depression, BMI, SII and estradiol between the two groups. And, green tea consumption may reduce the risk of depression through the mediating pathway of sleep, SII and estradiol. In summary, long-term green tea consumption can reduce the risk of depression in postmenopausal women by reducing inflammation and increasing estradiol. This kind of living habit deserves further promotion.
Keywords: depression; green tea; hormone; inflammation.
Conflict of interest statement
The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
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- No.81871072/National Natural Science Foundation of China
- NO. 82071523/National Natural Science Foundation of China
- YCXL-23-06/Open Fund of Yichang City Clinical Research Center for Mental Disorders
- 2021ZD0200701/Major Program of National Science and Technology Innovation 2030 for "Brain Science and Brain-like Research"
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