|
|
||||||||
ORIGINAL RESEARCH COMMUNICATION |
1 From the Cancer Prevention Fellowship Program (JAT) and Biometry Research Group (JAT and VK), Division of Cancer Prevention, National Cancer Institute, Bethesda, MD; the Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (AFS, FET, and RT); and the Nutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD (AS).
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 4069 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 (R2 = 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 (R2 = 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 (R2 = 0.22); social desirability, dietary restraint, body mass index, eating frequency, dieting history, and education were the best predictors in men (R2 = 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.
Key Words: Dietary assessment methods epidemiologic methods diet nutrition surveys biological markers energy expenditure doubly labeled water
This article has been cited by other articles:
![]() |
B. Resnick, A. King, D. Riebe, and M. Ory Measuring Physical Activity in Older Adults: Use of the Community Health Activities Model Program for Seniors Physical Activity Questionnaire and the Yale Physical Activity Survey in Three Behavior Change Consortium Studies West J Nurs Res, October 1, 2008; 30(6): 673 - 689. [Abstract] [PDF] |
||||
![]() |
A. J Moshfegh, D. G Rhodes, D. J Baer, T. Murayi, J. C Clemens, W. V Rumpler, D. R Paul, R. S Sebastian, K. J Kuczynski, L. A Ingwersen, et al. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes Am. J. Clinical Nutrition, August 1, 2008; 88(2): 324 - 332. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. L. Neuhouser, L. Tinker, P. A. Shaw, D. Schoeller, S. A. Bingham, L. V. Horn, S. A. A. Beresford, B. Caan, C. Thomson, S. Satterfield, et al. Use of Recovery Biomarkers to Calibrate Nutrient Consumption Self-Reports in the Women's Health Initiative Am. J. Epidemiol., May 15, 2008; 167(10): 1247 - 1259. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. G. Christian, D. H. Bessesen, T. E. Byers, K. K. Christian, M. G. Goldstein, and B. C. Bock Clinic-Based Support to Help Overweight Patients With Type 2 Diabetes Increase Physical Activity and Lose Weight Arch Intern Med, January 28, 2008; 168(2): 141 - 146. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. R. Hebert, T. G. Hurley, K. E. Peterson, K. Resnicow, F. E. Thompson, A. L. Yaroch, M. Ehlers, D. Midthune, G. C. Williams, G. W. Greene, et al. Social Desirability Trait Influences on Self-Reported Dietary Measures among Diverse Participants in a Multicenter Multiple Risk Factor Trial J. Nutr., January 1, 2008; 138(1): 226S - 234S. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. A. Tooze, M. Z. Vitolins, S. L. Smith, T. A. Arcury, C. C. Davis, R. A. Bell, R. F. DeVellis, and S. A. Quandt High Levels of Low Energy Reporting on 24-Hour Recalls and Three Questionnaires in an Elderly Low-Socioeconomic Status Population J. Nutr., May 1, 2007; 137(5): 1286 - 1293. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. Watson, T. Baranowski, D. Thompson, R. Jago, J. Baranowski, and L. M. Klesges Innovative application of a multidimensional item response model in assessing the influence of social desirability on the pseudo-relationship between self-efficacy and behavior Health Educ. Res., December 1, 2006; 21(suppl_1): i85 - i97. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. Wansink and P. Chandon Meal size, not body size, explains errors in estimating the calorie content of meals. Ann Intern Med, September 5, 2006; 145(5): 326 - 332. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Trabulsi, J. I Schall, R. F Ittenbach, I. E Olsen, M. Yudkoff, Y. Daikhin, B. S Zemel, and V. A Stallings Energy balance and the accuracy of reported energy intake in preadolescent children with cystic fibrosis. Am. J. Clinical Nutrition, September 1, 2006; 84(3): 523 - 530. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. L. Carriquiry and G. Camano-Garcia Evaluation of Dietary Intake Data Using the Tolerable Upper Intake Levels J. Nutr., February 1, 2006; 136(2): 507S - 513S. [Abstract] [Full Text] [PDF] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |