Document Detail


Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology.
MedLine Citation:
PMID:  22273536     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
With the advent of Internet-based 24-hour recall (24HR) instruments, it is now possible to envision their use in cohort studies investigating the relation between nutrition and disease. Understanding that all dietary assessment instruments are subject to measurement errors and correcting for them under the assumption that the 24HR is unbiased for usual intake, here the authors simultaneously address precision, power, and sample size under the following 3 conditions: 1) 1-12 24HRs; 2) a single calibrated food frequency questionnaire (FFQ); and 3) a combination of 24HR and FFQ data. Using data from the Eating at America's Table Study (1997-1998), the authors found that 4-6 administrations of the 24HR is optimal for most nutrients and food groups and that combined use of multiple 24HR and FFQ data sometimes provides data superior to use of either method alone, especially for foods that are not regularly consumed. For all food groups but the most rarely consumed, use of 2-4 recalls alone, with or without additional FFQ data, was superior to use of FFQ data alone. Thus, if self-administered automated 24HRs are to be used in cohort studies, 4-6 administrations of the 24HR should be considered along with administration of an FFQ.
Authors:
Raymond J Carroll; Douglas Midthune; Amy F Subar; Marina Shumakovich; Laurence S Freedman; Frances E Thompson; Victor Kipnis
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2012-01-24
Journal Detail:
Title:  American journal of epidemiology     Volume:  175     ISSN:  1476-6256     ISO Abbreviation:  Am. J. Epidemiol.     Publication Date:  2012 Feb 
Date Detail:
Created Date:  2012-02-06     Completed Date:  2012-04-13     Revised Date:  2013-06-26    
Medline Journal Info:
Nlm Unique ID:  7910653     Medline TA:  Am J Epidemiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  340-7     Citation Subset:  IM    
Affiliation:
Department of Statistics, College of Science, Texas A&M University, College Station, 77843-3143, USA. carroll@stat.tamu.edu
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MeSH Terms
Descriptor/Qualifier:
Bias (Epidemiology)
Calibration
Causality
Data Interpretation, Statistical
Diet Surveys / methods*,  standards,  statistics & numerical data
Eating
Energy Intake
Epidemiologic Research Design*
Humans
Logistic Models
Questionnaires*
Sample Size
Self Report
Survival Analysis
Grant Support
ID/Acronym/Agency:
HHSN261200633000//PHS HHS; R37 CA057030/CA/NCI NIH HHS; R37 CA057030-23/CA/NCI NIH HHS; R37 CA057030-24/CA/NCI NIH HHS; R37-CA057030/CA/NCI NIH HHS
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