{A figure is presented}A New Statistical Method for Estimating the Usual Intake of Episodically Consumed Foods with Application to Their Distribution

Janet A. Tooze, Douglas Midthune, Kevin W. Dodd, Laurence S. Freedman, Susan M. Krebs-Smith, Amy F. Subar, Patricia M. Guenther, Raymond J. Carroll, Victor Kipnis

Research output: Contribution to journalArticlepeer-review

511 Scopus citations

Abstract

Objective: We propose a new statistical method that uses information from two 24-hour recalls to estimate usual intake of episodically consumed foods. Statistical Analyses Performed: The method developed at the National Cancer Institute (NCI) accommodates the large number of nonconsumption days that occur with foods by separating the probability of consumption from the consumption-day amount, using a two-part model. Covariates, such as sex, age, race, or information from a food frequency questionnaire, may supplement the information from two or more 24-hour recalls using correlated mixed model regression. The model allows for correlation between the probability of consuming a food on a single day and the consumption-day amount. Percentiles of the distribution of usual intake are computed from the estimated model parameters. Results: The Eating at America's Table Study data are used to illustrate the method to estimate the distribution of usual intake for whole grains and dark-green vegetables for men and women and the distribution of usual intakes of whole grains by educational level among men. A simulation study indicates that the NCI method leads to substantial improvement over existing methods for estimating the distribution of usual intake of foods. Conclusions: The NCI method provides distinct advantages over previously proposed methods by accounting for the correlation between probability of consumption and amount consumed and by incorporating covariate information. Researchers interested in estimating the distribution of usual intakes of foods for a population or subpopulation are advised to work with a statistician and incorporate the NCI method in analyses.

Original languageEnglish
Pages (from-to)1575-1587
Number of pages13
JournalJournal of the American Dietetic Association
Volume106
Issue number10
DOIs
StatePublished - Oct 2006

Bibliographical note

Funding Information:
Research was supported by a grant from the National Cancer Institute (CA-57030), and by the Texas A&M Center for Environmental and Rural Health via a grant from the National Institute of Environmental Health Sciences (P30-ES09106).

Funding

Research was supported by a grant from the National Cancer Institute (CA-57030), and by the Texas A&M Center for Environmental and Rural Health via a grant from the National Institute of Environmental Health Sciences (P30-ES09106).

FundersFunder number
Texas A&M Center for Environmental and Rural Health
National Cancer InstituteR01CA057030
National Institute of Environmental Health SciencesP30-ES09106

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