Cognitive research enhances accuracy of food frequency questionnaire reports: Results of an experimental validation study
ABSTRACT To test whether changing a food frequency questionnaire (FFQ) on the basis of cognitive theory and testing results in greater accuracy. Accuracy was examined for 4 design issues: a) Grouping: asking about foods in a single vs multiple separate questions; b) different forms of a food: asking consumption frequency of each form of a food (eg, skim, 2%, whole milk) vs a nesting approach--asking frequency of the main food (eg, milk) and proportion of times each form was consumed; c) additions (eg, sugar to coffee): asking independent of the main food vs nested under the main foods; d) units: asking frequency and portion size vs frequency of units (eg, cups of coffee).
Participants in two randomly assigned groups completed 30 consecutive daily food reports (DFRs), followed by 1 of 2 FFQs that asked about foods consumed in the past month. One was a new, cognitively-based National Cancer Institute (NCI) Diet History Questionnaire; the other was the 1992 NCI-Block Health Habits and History Questionnaire.
623 participants, age range 25 to 70 years, from metropolitan Washington, DC. Statistical analyses performed Accuracy was assessed by comparing DFR and FFQ responses using categorical (percent agreement) and continuous (rank order correlation, discrepancy scores) agreement statistics.
Grouping: accuracy was greater using separate questions. Different forms of food: accuracy was greater using nesting. Additions: neither approach was consistently superior; accuracy of the addition report was affected by accuracy of the main food report. Units: both approaches were similarly accurate.
Accuracy of FFQ reporting can be improved by restructuring questions based on cognitive theory and testing.
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ABSTRACT: Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs.Journal of the American Academy of Nutrition and Dietetics 04/2014; DOI:10.1016/j.jand.2014.03.014 · 2.44 Impact Factor
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ABSTRACT: Computer-administered food frequency questionnaires (FFQs) can address limitations inherent in paper questionnaires by allowing very complex skip patterns, portion size estimation based on food pictures, and real-time error checking. We evaluated a web-based FFQ, the Graphical Food Frequency System (GraFFS). Participants completed the GraFFS, six telephone-administered 24-hour dietary recalls over the next 12 weeks, followed by a second GraFFS. Participants were 40 men and 34 women, aged 18 to 69 years, living in the Columbus, OH, area. Intakes of energy, macronutrients, and 17 micronutrients/food components were estimated from the GraFFS and the mean of all recalls. Bias (second GraFFS minus recalls) was -9%, -5%, +4%, and -4% for energy and percentages of energy from fat, carbohydrate, and protein, respectively. De-attenuated, energy-adjusted correlations (intermethod reliability) between the recalls and the second GraFFS for fat, carbohydrate, protein, and alcohol were 0.82, 0.79, 0.67, and 0.90, respectively; for micronutrients/food components the median was 0.61 and ranged from 0.40 for zinc to 0.92 for beta carotene. The correlations between the two administrations of the GraFFS (test-retest reliability) for fat, carbohydrate, protein, and alcohol were 0.60, 0.63, 0.73, and 0.87, respectively; among micronutrients/food components the median was 0.67 and ranged from 0.49 for vitamin B-12 to 0.82 for fiber. The measurement characteristics of the GraFFS were at least as good as those reported for most paper FFQs, and its high intermethod reliability suggests that further development of computer-administered FFQs is warranted.Journal of the American Academy of Nutrition and Dietetics 01/2014; 114(4). DOI:10.1016/j.jand.2013.11.017 · 2.44 Impact Factor
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ABSTRACT: The Dietary Patterns Methods Project (DPMP) was initiated in 2012 to strengthen research evidence on dietary indices, dietary patterns, and health for upcoming revisions of the Dietary Guidelines for Americans, given that the lack of consistent methodology has impeded development of consistent and reliable conclusions. DPMP investigators developed research questions and a standardized approach to index-based dietary analysis. This article presents a synthesis of findings across the cohorts. Standardized analyses were conducted in the NIH-AARP Diet and Health Study, the Multiethnic Cohort, and the Women's Health Initiative Observational Study (WHI-OS). Healthy Eating Index 2010, Alternative Healthy Eating Index 2010 (AHEI-2010), alternate Mediterranean Diet, and Dietary Approaches to Stop Hypertension (DASH) scores were examined across cohorts for correlations between pairs of indices; concordant classifications into index score quintiles; associations with all-cause, cardiovascular disease (CVD), and cancer mortality with the use of Cox proportional hazards models; and dietary intake of foods and nutrients corresponding to index quintiles. Across all cohorts in women and men, there was a high degree of correlation and consistent classifications between index pairs. Higher diet quality (top quintile) was significantly and consistently associated with an 11-28% reduced risk of death due to all causes, CVD, and cancer compared with the lowest quintile, independent of known confounders. This was true for all diet index-mortality associations, with the exception of AHEI-2010 and cancer mortality in WHI-OS women. In all cohorts, survival benefit was greater with a higher-quality diet, and relatively small intake differences distinguished the index quintiles. The reductions in mortality risk started at relatively lower levels of diet quality. Higher scores on each of the indices, signifying higher diet quality, were associated with marked reductions in mortality. Thus, the DPMP findings suggest that all 4 indices capture the essential components of a healthy diet. © 2015 American Society for Nutrition.Journal of Nutrition 03/2015; 145(3):393-402. DOI:10.3945/jn.114.205336 · 4.23 Impact Factor