Measurement error of dietary self-report in intervention trials

Loki Natarajan, Minya Pu, Juanjuan Fan, Richard A. Levine, Ruth E. Patterson, Cynthia A. Thomson, Cheryl L. Rock, John P. Pierce

Research output: Contribution to journalArticlepeer-review

71 Scopus citations


Dietary intervention trials aim to change dietary patterns of individuals. Participating in such trials could impact dietary self-report in divergent ways: Dietary counseling and training on portion-size estimation could improve self-report accuracy; participant burden could increase systematic error. Such intervention-associated biases could complicate interpretation of trial results. The authors investigated intervention-associated biases in reported total carotenoid intake using data on 3,088 breast cancer survivors recruited between 1995 and 2000 and followed through 2006 in the Women's Healthy Eating and Living Study, a randomized intervention trial. Longitudinal data from 2 self-report methods (24-hour recalls and food frequency questionnaires) and a plasma carotenoid biomarker were collected. A flexible measurement error model was postulated. Parameters were estimated in a Bayesian framework by using Markov chain Monte Carlo methods. Results indicated that the validity (i.e., correlation with "true" intake) of both self-report methods was significantly higher during follow-up for intervention versus nonintervention participants (4-year validity estimates: intervention = 0.57 for food frequency questionnaires and 0.58 for 24-hour recalls; nonintervention = 0.42 for food frequency questionnaires and 0.48 for 24-hour recalls). However, within-and between-instrument error correlations during follow-up were higher among intervention participants, indicating an increase in systematic error. Diet interventions can impact measurement errors of dietary self-report. Appropriate statistical methods should be applied to examine intervention-associated biases when interpreting results of diet trials.

Original languageEnglish (US)
Pages (from-to)819-827
Number of pages9
JournalAmerican journal of epidemiology
Issue number7
StatePublished - Oct 1 2010


  • Markov chain Monte Carlo
  • bias (epidemiology)
  • diet
  • intervention studies
  • measurement error
  • nutrition assessment
  • reproducibility of results
  • validity

ASJC Scopus subject areas

  • General Medicine


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