Literature DB >> 15066609

Correlations between estimated and true dietary intakes.

Gary E Fraser1, David J Shavlik.   

Abstract

PURPOSE: It is unclear how well questionnaire or so-called reference methods of dietary assessment correlate with true dietary intake. We develop a method to estimate such correlations.
METHODS: An error model is described that uses data from a food frequency questionnaire (Q), a reference method (R), and a biological marker (M). The model does not assume the classical error model for either R or M, or that the correlation between errors in the questionnaire and reference data is zero. Credible intervals can be placed about correlations between R, Q, M and true dietary data (T), also about the correlations between errors in reference and questionnaire data.
RESULTS: Application of this model to a validation data set mainly found correlations in the range 0.4 to 0.8, and that correlations (R,T) generally exceeded correlations (Q,T), providing evidence that R is more valid than Q. Estimated correlations between errors in R and Q were often far from zero suggesting that regression calibration to imperfect reference data is problematic unless these error correlations can be estimated.
CONCLUSION: A biological marker in addition to dietary data, allows calculation of correlations between estimated and true dietary intakes under reasonable assumptions about errors. However, sensitivity analyses are necessary on one variable.

Mesh:

Substances:

Year:  2004        PMID: 15066609     DOI: 10.1016/j.annepidem.2003.08.008

Source DB:  PubMed          Journal:  Ann Epidemiol        ISSN: 1047-2797            Impact factor:   3.797


  7 in total

1.  A NEW MULTIVARIATE MEASUREMENT ERROR MODEL WITH ZERO-INFLATED DIETARY DATA, AND ITS APPLICATION TO DIETARY ASSESSMENT.

Authors:  Saijuan Zhang; Douglas Midthune; Patricia M Guenther; Susan M Krebs-Smith; Victor Kipnis; Kevin W Dodd; Dennis W Buckman; Janet A Tooze; Laurence Freedman; Raymond J Carroll
Journal:  Ann Appl Stat       Date:  2011-06-01       Impact factor: 2.083

2.  Race-specific validation of food intake obtained from a comprehensive FFQ: the Adventist Health Study-2.

Authors:  Karen Jaceldo-Siegl; Jing Fan; Joan Sabaté; Synnove F Knutsen; Ella Haddad; W Lawrence Beeson; R Patti Herring; Terrence L Butler; Hannelore Bennett; Gary E Fraser
Journal:  Public Health Nutr       Date:  2011-05-06       Impact factor: 4.022

3.  Missing data in a long food frequency questionnaire: are imputed zeroes correct?

Authors:  Gary E Fraser; Ru Yan; Terry L Butler; Karen Jaceldo-Siegl; W Lawrence Beeson; Jacqueline Chan
Journal:  Epidemiology       Date:  2009-03       Impact factor: 4.822

4.  The association between soya consumption and serum thyroid-stimulating hormone concentrations in the Adventist Health Study-2.

Authors:  Serena Tonstad; Karen Jaceldo-Siegl; Mark Messina; Ella Haddad; Gary E Fraser
Journal:  Public Health Nutr       Date:  2015-10-09       Impact factor: 4.022

5.  Biomarkers of Dietary Intake Are Correlated with Corresponding Measures from Repeated Dietary Recalls and Food-Frequency Questionnaires in the Adventist Health Study-2.

Authors:  Gary E Fraser; Karen Jaceldo-Siegl; Susanne M Henning; Jing Fan; Synnove F Knutsen; Ella H Haddad; Joan Sabaté; W Lawrence Beeson; Hannelore Bennett
Journal:  J Nutr       Date:  2016-02-03       Impact factor: 4.798

Review 6.  Systematic review of statistical approaches to quantify, or correct for, measurement error in a continuous exposure in nutritional epidemiology.

Authors:  Derrick A Bennett; Denise Landry; Julian Little; Cosetta Minelli
Journal:  BMC Med Res Methodol       Date:  2017-09-19       Impact factor: 4.615

7.  Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study.

Authors:  Søren Brage; Kate Westgate; Paul W Franks; Oliver Stegle; Antony Wright; Ulf Ekelund; Nicholas J Wareham
Journal:  PLoS One       Date:  2015-09-08       Impact factor: 3.240

  7 in total

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