Medicinal plants-based foods for breast cancer treatment: An ethnobotanical survey and digitization

Omogbadegun, Zacchaeus Oni (2013) Medicinal plants-based foods for breast cancer treatment: An ethnobotanical survey and digitization. International Journal of Medicinal Plants and Alternative Medicine, 1 (8). pp. 137-163.

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Abstract

One million new breast cancer (BC) cases diagnosed yearly yielded over 400,000 annual deaths. About 4.4 million women are living with BC worldwide, while 15 million new cases yearly are estimated by 2020. About 12.15% of women born today would be diagnosed with BC at some time during their lifetime. Nigerian women’s BC lifetime risk of 10% accounted for about 16% of all cancer-related deaths. Nigeria was ill-equipped in dealing with BC complexities. This paper presented an ethnobotanical survey and digitization of Medicinal and Aromatic Plants (MAPs)-based foods for effective BC treatment. BC’s risk factors were gathered from General Practitioners. Semi-structured questionnaires were randomly administered, in which 70 Physicians and 500 Complementary and Alternative Medicine (CAM) practitioners were interviewed. Internet searches were performed on the NCCAM, EBSCO, and PubMed databases using BC-related keywords. Specific ethnobotanical data of MAPs having anticancer properties were documented through guided fieldworks, local markets, and CAM practitioners’ homes. A total of 10% of the studied MAPs yielded Adzuki bean, Asparagus, Broccoli, Burdock, Cabbage, Chinese yam, Dandelion, Tomato, Watercress, and Watermelon in effectively treating BC menace. A Populated Multimedia-based Medicinal Plants Sustainability Management System was used to address MAPs’ extinction challenge with the BC-related MAPs. Orthodox BC treatments have devastating effects including temporary infertility. However, eating fruits and vegetables daily significantly reduces BC’s risk. Key words: Breast cancer, complementary and alternative medicine, fruits, medicinal plants, vegetables.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Dr ibukun Afolabi
Date Deposited:	16 Jun 2017 14:04
Last Modified:	16 Jun 2017 14:04
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/8279

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