Beyond Hormone Replacement: Multifaceted Effects of Phytoestrogens for Optimizing Kinesiological and Physiological Adaptations in Postmenopausal Women
Yingjia Hu, Yi Hu, Tao Li, Rengfei Shi School of Health and Exercise, Shanghai University of Sport, Shanghai, People’s Republic of ChinaCorrespondence: Rengfei Shi, School of Health and Exercise, Shanghai University of Sport, Shanghai, People’s Republic of China, Tel +86 13661498054, Email [email protected]: Phytoestrogens (PEs), a class of naturally occurring plant compounds primarily categorized into isoflavones, lignans, flavonoids, coumarins, and stilbenes, exhibit structural similarity to endogenous estrogens and exert regulatory effects through estrogen receptors. This comprehensive review examines the multifaceted roles of PEs in enhancing exercise performance and promoting health among postmenopausal women. Current evidence demonstrates that PEs not only ameliorate characteristic menopausal symptoms but, more significantly, improve physical function through multiple mechanisms: (1) augmenting muscle protein synthesis while mitigating inflammation and oxidative stress to optimize muscular performance; (2) modulating glucolipid metabolism and cardiovascular function to establish physiological foundations for exercise; and (3) preserving bone mineral density and regulating neurotransmitter activity to maintain motor coordination. Although combined PE-exercise interventions demonstrate synergistic benefits, their efficacy is influenced by dosage variations and interindividual metabolic differences. Future investigations should prioritize the development of precision PE applications to optimize kinesiological outcomes and health parameters in postmenopausal populations.Keywords: phytoestrogens, elderly, exercise performance, physical activity, menopausal symptoms
Institutions
- Center for Health, Exercise and Sport Sciences (RS)
- Institute for Exercise and Environmental Medicine (US)
Publication Details
- Journal
- SHILAP Revista de lepidopterología
- Published
- 2025-10-01
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00