The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.
Quercetin and metabolic syndrome: A review
Abstract
Metabolic syndrome (MetS) is a complex of diseases that lead to mortality due to the development of cardiovascular problems. Quercetin, as an important flavonoid, has various properties such as decreasing blood pressure, anti‐hyperlipidemia, anti‐hyperglycemia, anti‐oxidant, antiviral, anticancer, anti‐inflammatory, anti‐microbial, neuroprotective, and cardio‐protective effects. In this review article, we collected original articles from different sources such as Google Scholar, Medline, Scopus, and Pubmed, which is related to the effect of quercetin on the improvement of the signs of MetS, including elevated glucose level, hyperlipidemia, obesity, and blood pressure. According to these data, quercetin may also have a role in the management of metabolic disorders via different mechanisms such as increasing adiponectin, decreasing leptin, anti‐oxidant activity, reduction of insulin resistance, the elevation of insulin level, and blocking of calcium channel. We have attempted to make some recommendations on the quercetin application in patients. However, it needs to do further clinical trials and more investigations to show the real clinical value of quercetin on metabolic syndrome.
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1 retracted
Peng, J., Li, Q., Li, K., Zhu, L., Lin, X., Lin, X., Shen, Q., Li, G., & Xie, X. S. (2017) · Journal of Diabetes Research · doi:10.1155/2017/3417306 · Cited by 141
RetractedChobanian, A. V. (2003) · JAMA · doi:10.1001/jama.289.19.2560 · Cited by 25,386
The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men
Lakka, H.-M. (2002) · JAMA · doi:10.1001/jama.288.21.2709 · Cited by 5,033
Updated clinical classification of pulmonary hypertension
Simonneau, G., Gatzoulis, M. A., Adatia, I., Celermajer, D., Denton, C., Ghofrani, A., Gomez Sanchez, M. A., Krishna Kumar, R., Landzberg, M., Machado, R. F., et al. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.10.029 · Cited by 4,191
A central role for JNK in obesity and insulin resistance
Hirosumi, J., Tuncman, G., Chang, L., Görgün, C. Z., Uysal, K. T., Maeda, K., Karin, M., & Hotamisligil, G. S. (2002) · Nature · doi:10.1038/nature01137 · Cited by 3,359
Overviews of biological importance of quercetin: A bioactive flavonoid
Parasuraman, S., Anand David, A., & Arulmoli, R. (2016) · Pharmacognosy Reviews · doi:10.4103/0973-7847.194044 · Cited by 1,610
Metabolic Syndrome and Risk of Cardiovascular Disease: A Meta-Analysis
Galassi, A., Reynolds, K., & He, J. (2006) · The American Journal of Medicine · doi:10.1016/j.amjmed.2006.02.031 · Cited by 1,207
Hyperlipidemia as a Risk Factor for Cardiovascular Disease
Nelson, R. H. (2013) · Primary Care: Clinics in Office Practice · doi:10.1016/j.pop.2012.11.003 · Cited by 1,093
Adiponectin as an anti-inflammatory factor
Ouchi, N., & Walsh, K. (2007) · Clinica Chimica Acta · doi:10.1016/j.cca.2007.01.026 · Cited by 872
Arai, Y., Watanabe, S., Kimira, M., Shimoi, K., Mochizuki, R., & Kinae, N. (2000) · The Journal of Nutrition · doi:10.1093/jn/130.9.2243 · Cited by 790
Cited by
Health Benefits of Quercetin in Age-Related Diseases
Deepika, & Maurya, P. K. (2022) · Molecules · doi:10.3390/molecules27082498 · Cited by 447
Zeng, J., Bao, T., Yang, K., Zhu, X., Wang, S., Xiang, W., Ge, A., Zeng, L., & Ge, J. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1047550 · Cited by 175
Metabolic syndrome-related kidney injury: a review and update
Lin, L., Tan, W., Pan, X., Tian, E., Wu, Z., & Yang, J. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.904001 · Cited by 139
Olivares-Vicente, M., & Herranz-López, M. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26178544 · Cited by 59
Metadata
- Authors
- Hosseini, A., Razavi, B. M., Banach, M., & Hosseinzadeh, H.
- Venue
- Phytotherapy Research
- Publisher
- Wiley
- Published
- 2021-06-08
- Volume
- 35
- Issue
- 10
- Pages
- 5352-5364
- ISSN
- 0951-418X (ISSN-L)
- 1099-1573
- OpenAlex
- W3171144340
- Cited by
- 386
- References
- 113
- FWCI
- 35.36
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.