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United States Department of Agriculture

Agricultural Research Service

Research Project: DEVELOPMENT AND PREVENTION OF CHILDHOOD OBESITY

Location: Children's Nutrition Research Center

Title: The Automated Self-Administered 24-hour dietary recall (ASA24): A resource for researchers, clinicians, and educators from the National Cancer Institute)

Author
item Subar, Amy
item Kirkpatrick, Sharon
item Mittl, Beth
item Zimmerman, Thea
item Thompson, Frances
item Bingley, Christopher
item Willis, Gordon
item Islam, Noemi
item Baranowski, Tom
item Mcnutt, Suzanne
item Potischman, Nancy

Submitted to: Journal of the Academy of Nutrition and Dietetics
Publication Type: Review Article
Publication Acceptance Date: 4/2/2012
Publication Date: 8/1/2012
Citation: Subar, A.F., Kirkpatrick, S.I., Mittl, B., Zimmerman, T.P., Thompson, F.E., Bingley, C., Willis, G., Islam, N.G., Baranowski, T., McNutt, S., Potischman, N. 2012. The Automated Self-Administered 24-hour dietary recall (ASA24): A resource for researchers, clinicians, and educators from the National Cancer Institute. Journal of the Academy of Nutrition and Dietetics. 112(8):1134-1137.

Interpretive Summary:

Technical Abstract: Extensive evidence has demonstrated that 24-hour dietary recalls (24HDRs) provide high-quality dietary intake data with minimal bias, making them the preferred tool for monitoring the diets of populations and, increasingly, for studying diet and disease associations. Traditional 24HDRs, however, are expensive and impractical for large-scale research because they rely on trained interviewers, and multiple administrations are needed to estimate usual intakes. To address these challenges, the National Cancer Institute (NCI), in collaboration with the research firm Westat (Rockville, MD) and with the support of other institutes and offices at the National Institutes of Health, developed the Automated Self-Administered 24-hour dietary recall (ASA24). ASA24 is a public-access, freely available, web-based tool for researchers, clinicians, and educators that is modeled on the Automated Multiple Pass Method (AMPM).

Last Modified: 8/24/2016
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