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Am J Clin Nutr. 2004 May;79(5):795-804.

Psychosocial predictors of energy underreporting in a large doubly labeled water study.

Author information

  • 1Cancer Prevention Fellowship Program, National Cancer Institute, Executive Plaza North, Suite 3131, 6130 Executive Boulevard, MSC 7354, Bethesda, MD 20892-7354, USA. toozej@mail.nih.gov

Abstract

BACKGROUND:

Underreporting of energy intake is associated with self-reported diet measures and appears to be selective according to personal characteristics. Doubly labeled water is an unbiased reference biomarker for energy intake that may be used to assess underreporting.

OBJECTIVE:

Our objective was to determine which factors are associated with underreporting of energy intake on food-frequency questionnaires (FFQs) and 24-h dietary recalls (24HRs).

DESIGN:

The study participants were 484 men and women aged 40-69 y who resided in Montgomery County, MD. Using the doubly labeled water method to measure total energy expenditure, we considered numerous psychosocial, lifestyle, and sociodemographic factors in multiple logistic regression models for prediction of the probability of underreporting on the FFQ and 24HR.

RESULTS:

In the FFQ models, fear of negative evaluation, weight-loss history, and percentage of energy from fat were the best predictors of underreporting in women (R(2) = 0.09); body mass index, comparison of activity level with that of others of the same sex and age, and eating frequency were the best predictors in men (R(2) = 0.10). In the 24HR models, social desirability, fear of negative evaluation, body mass index, percentage of energy from fat, usual activity, and variability in number of meals per day were the best predictors of underreporting in women (R(2) = 0.22); social desirability, dietary restraint, body mass index, eating frequency, dieting history, and education were the best predictors in men (R(2) = 0.25).

CONCLUSION:

Although the final models were significantly related to underreporting on both the FFQ and the 24HR, the amount of variation explained by these models was relatively low, especially for the FFQ.

PMID:
15113717
[PubMed - indexed for MEDLINE]
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