National Cancer Institute Home at the National Institutes of Health |
Please wait while this form is being loaded....
The Applied Research Program Web site is no longer maintained. ARP's former staff have moved to the new Healthcare Delivery Research Program, the Behavioral Research Program, or the Epidemiology & Genetics Research Program, and the content from this Web site is being moved to one of those sites as appropriate. Please update your links and bookmarks!

Publication Abstract

Authors: Subar AF, Midthune D, Kulldorff M, Brown CC, Thompson FE, Kipnis V, Schatzkin A

Title: Evaluation of alternative approaches to assign nutrient values to food groups in food frequency questionnaires.

Journal: Am J Epidemiol 152(3):279-86

Date: 2000 Aug 01

Abstract: Although every food frequency questionnaire (FFQ) requires a nutrient database to produce nutrient intake estimates, it is often unclear how a particular database has been generated. Moreover, alternative methods for constructing a database have not been rigorously evaluated. Using 24-hour recalls from the 1994-1996 Continuing Survey of Food Intake by Individuals, the authors categorized 5,261 individual foods reported by 10,019 adults into 170 food groups consistent with line items on an FFQ. These food groups were used to generate 10 potential nutrient databases for a FFQ that varied by whether the authors 1) used means or medians, 2) did or did not consider age, 3) incorporated collapsing strategies for small age-gender-portion size cells, 4) excluded outliers in a regression, and 5) used weighted median nutrient density x age-gender-portion size-specific median gram weights (Block method). Mean error, mean squared error, and mean absolute error were calculated and compared across methods, with error being the difference in total observed (from recalls for each individual) and total estimated intake (from each of the 10 methods) for seven nutrients. Mean methods for assigning nutrients to food groups were superior to median approaches for all measurements. Among the mean methods, no single variation was consistently better.

Last Modified: 03 Sep 2013