Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: The OPEN study. American Journal of Epidemiology, 158, 1-13

Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA.
American Journal of Epidemiology (Impact Factor: 5.23). 08/2003; 158(1):1-13.
Source: PubMed


This paper describes the Observing Protein and Energy Nutrition (OPEN) Study, conducted from September 1999 to March 2000. The purpose of the study was to assess dietary measurement error using two self-reported dietary instruments-the food frequency questionnaire (FFQ) and the 24-hour dietary recall (24HR)-and unbiased biomarkers of energy and protein intakes: doubly labeled water and urinary nitrogen. Participants were 484 men and women aged 40-69 years from Montgomery County, Maryland. Nine percent of men and 7% of women were defined as underreporters of both energy and protein intake on 24HRs; for FFQs, the comparable values were 35% for men and 23% for women. On average, men underreported energy intake compared with total energy expenditure by 12-14% on 24HRs and 31-36% on FFQs and underreported protein intake compared with a protein biomarker by 11-12% on 24HRs and 30-34% on FFQs. Women underreported energy intake on 24HRs by 16-20% and on FFQs by 34-38% and underreported protein intake by 11-15% on 24HRs and 27-32% on FFQs. There was little underreporting of the percentage of energy from protein for men or women. These findings have important implications for nutritional epidemiology and dietary surveillance.

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    • "Given the indirect, pseudo-quantitative nature of the method (i.e., assigning numeric values to subjective data without objective corroboration), nutrition surveys frequently report a range of energy intakes that are not representative of the respondents' habitual intakes [8], and estimates of EI that are physiologically implausible (i.e., incompatible with survival) have been demonstrated to be widespread [9] [10] [11]. For example, in a group of ''highly educated'' participants, Subar et al. (2003) demonstrated that when total energy expenditure (TEE) via doubly labeled water (DLW) was compared to reported energy intake (rEI), the raw correlations between TEE and rEI were 0.39 for men and 0.24 for women. Men and women underreported energy intake by 12– 14% and 16–20%, respectively. "
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    ABSTRACT: Methodological limitations compromise the validity of U.S. nutritional surveillance data and the empirical foundation for formulating dietary guidelines and public health policies. Evaluate the validity of the National Health and Nutrition Examination Survey (NHANES) caloric intake data throughout its history, and examine trends in the validity of caloric intake estimates as the NHANES dietary measurement protocols evolved. Validity of data from 28,993 men and 34,369 women, aged 20 to 74 years from NHANES I (1971-1974) through NHANES 2009-2010 was assessed by: calculating physiologically credible energy intake values as the ratio of reported energy intake (rEI) to estimated basal metabolic rate (BMR), and subtracting estimated total energy expenditure (TEE) from NHANES rEI to create 'disparity values'. 1) Physiologically credible values expressed as the ratio rEI/BMR and 2) disparity values (rEI-TEE). The historical rEI/BMR values for men and women were 1.31 and 1.19, (95% CI: 1.30-1.32 and 1.18-1.20), respectively. The historical disparity values for men and women were -281 and -365 kilocalorie-per-day, (95% CI: -299, -264 and -378, -351), respectively. These results are indicative of significant under-reporting. The greatest mean disparity values were -716 kcal/day and -856 kcal/day for obese (i.e., ≥30 kg/m2) men and women, respectively. Across the 39-year history of the NHANES, EI data on the majority of respondents (67.3% of women and 58.7% of men) were not physiologically plausible. Improvements in measurement protocols after NHANES II led to small decreases in underreporting, artifactual increases in rEI, but only trivial increases in validity in subsequent surveys. The confluence of these results and other methodological limitations suggest that the ability to estimate population trends in caloric intake and generate empirically supported public policy relevant to diet-health relationships from U.S. nutritional surveillance is extremely limited.
    Full-text · Article · Oct 2013 · PLoS ONE
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    • "The 24-h dietary recall has been shown to be a less-biased estimator of calories and protein from foods in adults than a frequency-based questionnaire (10). However, no such comparisons are available for dietary supplements. "
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    ABSTRACT: Background: Dietary supplements are used by one-third of children. We examined motivations for supplement use in children, the types of products used by motivations, and the role of physicians and health care practitioners in guiding choices about supplements. Methods: We examined motivations for dietary supplement use reported for children (from birth to 19 y of age; n = 8,245) using the National Health and Nutrition Examination Survey 2007-2010. Results: Dietary supplements were used by 31% of children; many different reasons were given as follows: to "improve overall health" (41%), to "maintain health" (37%), for "supplementing the diet" (23%), to "prevent health problems" (20%), and to "boost immunity" (14%). Most children (~90%) who use dietary supplements use a multivitamin-mineral or multivitamin product. Supplement users tend to be non-Hispanic white, have higher family incomes, report more physical activity, and have health insurance. Only a small group of supplements used by children (15%) were based on the recommendation of a physician or other health care provider. Conclusion: Most supplements used by children are not under the recommendation of a health care provider. The most common reasons for use of supplements in children are for health promotion, yet little scientific data support this notion in nutrient-replete children.
    Full-text · Article · Sep 2013 · Pediatric Research
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    • "Data from previous studies indicate that under-reporting in women is associated with fear of negative evaluation, weight loss history, percentage of energy from fat and eating less frequently or variability in number of meals per day [10,11]. Under-reporting of energy intake has been found in both older and younger participants [5,10-12] and under-reporters tend to be less physically active, more likely to diet and eat less fat as a percentage of energy intake compared with accurate reporters [13]. "
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    ABSTRACT: The extent to which psychosocial and diet behavior factors affect dietary self-report remains unclear. We examine the contribution of these factors to measurement error of self-report. In 450 postmenopausal women in the Women’s Health Initiative Observational Study doubly labeled water and urinary nitrogen were used as biomarkers of objective measures of total energy expenditure and protein. Self-report was captured from food frequency questionnaire (FFQ), four day food record (4DFR) and 24 hr. dietary recall (24HR). Using regression calibration we estimated bias of self-reported dietary instruments including psychosocial factors from the Stunkard-Sorenson Body Silhouettes for body image perception, the Crowne-Marlowe Social Desirability Scale, and the Three Factor Eating Questionnaire (R-18) for cognitive restraint for eating, uncontrolled eating, and emotional eating. We included a diet behavior factor on number of meals eaten at home using the 4DFR. Three categories were defined for each of the six psychosocial and diet behavior variables (low, medium, high). Participants with high social desirability scores were more likely to under-report on the FFQ for energy (β = -0.174, SE = 0.054, p < 0.05) and protein intake (β = -0.142, SE = 0.062, p < 0.05) compared to participants with low social desirability scores. Participants consuming a high percentage of meals at home were less likely to under-report on the FFQ for energy (β = 0.181, SE = 0.053, p < 0.05) and protein (β = 0.127, SE = 0.06, p < 0.05) compared to participants consuming a low percentage of meals at home. In the calibration equations combining FFQ, 4DFR, 24HR with age, body mass index, race, and the psychosocial and diet behavior variables, the six psychosocial and diet variables explained 1.98%, 2.24%, and 2.15% of biomarker variation for energy, protein, and protein density respectively. The variations explained are significantly different between the calibration equations with or without the six psychosocial and diet variables for protein density (p = 0.02), but not for energy (p = 0.119) or protein intake (p = 0.077). The addition of psychosocial and diet behavior factors to calibration equations significantly increases the amount of total variance explained for protein density and their inclusion would be expected to strengthen the precision of calibration equations correcting self-report for measurement error. Trial registration identifier: NCT00000611
    Full-text · Article · May 2013 · Nutrition Journal
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