Thinking critically about whole-grain definitions: Summary report of an interdisciplinary roundtable discussion at the 2015 Whole Grains Summit
Korczak, R., Marquart, L., Slavin, J. L., Ringling, K., . . . Unnevehr, L. (2016). Thinking critically about whole-grain definitions: Summary report of an interdisciplinary roundtable discussion at the 2015 Whole Grains Summit. American Journal of Clinical Nutrition, 104(6), 1508-1514. doi:10.3945/ajcn.115.126672
Abstract:
Definitions for whole grain (WG) have been published by governments, the food industry, and grain organizations and generally fall into 2 categories: WG and WG food. WG definitions focus on the principal components of the WGs and their proportions, whereas WG-food definitions describe the quantity of WGs present in food. In the United States, widespread agreement exists on the main parts of a definition for a WG, with a definition for a WG food still in its early stages; a standard definition that has been universally accepted does not exist. Furthermore, nutrition policy advises consumers to eat WGs for at least one-half of their total grain intake (2010 and 2015 Dietary Guidelines for Americans), but confusion exists over which foods are considered WGs and how much is needed to achieve health benefits. In December 2014, a workshop sponsored by the subcommittee on collaborative process of the US Government’s Interagency Committee on Human Nutrition Research convened in Washington, DC, and recognized WG definitions as a key nutrition and public health–related issue that could benefit from further collaboration. As a follow-up to that meeting, an interdisciplinary roundtable meeting was organized at the Whole Grains Summit on 25 June 2015 in Portland, Oregon, to help resolve the issue. This article summarizes the main opportunities and challenges that were identified during the meeting for defining WGs and WG foods internationally. Definitions of WGs and WG foods that are uniformly adopted by research, food industry, consumer, and public health communities are needed to enable comparison of research results across populations.
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