JOURNAL ARTICLE

Oat β-Glucan Intake Facilitates Glycemic Control and Prebiotic Activity Among Patients with Type 2 Diabetes: A Mini Review.

  • Published In: International Journal of Probiotics & Prebiotics, 2023, v. 18, n. 1. P. 21 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Alarifi, Sehad N. 3 of 3

Abstract

Uncontrolled diabetes raises the risk of many noncommunicable diseases, including cardiovascular diseases. Sufficient intake of dietary fiber facilitates glycemic control and reduces the health risks associated with diabetes. Oat β-glucan is one such dietary fiber known to lower cholesterol; however, its ability to improve glycemic control remains to be determined. This review explores the effect of oat β-glucan on glycemic control in relation to prebiotic activity among patients with type 2 diabetes. There are data to support the idea that intake of 2--3 g of oat β-glucan can reduce HbA1c by 0.5%, whereas 1 g of oat β-glucan reduces postprandial glucose by 7%. In vivo and in vitro studies have shown that Bifidobacteria, Roseburia, and butyrate-producing bacteria were increased after oat β-glucan consumption, which might be responsible for the regulation of glycemic control. Additionally, oat β-glucan intake is known to increase the levels of short-chain fatty acids in the circulation, resulting in greater feelings of fullness and satiety. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Probiotics & Prebiotics. 2023/01, Vol. 18, Issue 1, p21
  • Document Type:Article
  • Subject Area:Nutrition and Dietetics
  • Publication Date:2023
  • ISSN:1555-1431
  • DOI:10.37290/ijpp2641-7197.18:21-29
  • Accession Number:175180767
  • Copyright Statement:Copyright of International Journal of Probiotics & Prebiotics is the property of New Century Health Publishers, LLC and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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