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      Dietary assessment methods in epidemiological research: current state of the art and future prospects

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          Abstract

          Self-reported dietary intake is assessed by methods of real-time recording (food diaries and the duplicate portion method) and methods of recall (dietary histories, food frequency questionnaires, and 24-hour dietary recalls). Being less labor intensive, recall methods are more frequently employed in nutritional epidemiological investigations. However, sources of error, which include the participants’ inability to fully and accurately recall their intakes as well as limitations inherent in the food composition databases applied to convert the reported food consumption to energy and nutrient intakes, may limit the validity of the generated information. The use of dietary biomarkers is often recommended to overcome such errors and better capture intra-individual variability in intake; nevertheless, it has its own challenges. To address measurement error associated with dietary questionnaires, large epidemiological investigations often integrate sub-studies for the validation and calibration of the questionnaires and/or administer a combination of different assessment methods (e.g. administration of different questionnaires and assessment of biomarker levels). Recent advances in the omics field could enrich the list of reliable nutrition biomarkers, whereas new approaches employing web-based and smart phone applications could reduce respondent burden and, possibly, reporting bias. Novel technologies are increasingly integrated with traditional methods, but some sources of error still remain. In the analyses, food and nutrient intakes always need to be adjusted for total daily energy intake to account for errors related to reporting.

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          Most cited references24

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          Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study.

          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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            The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study.

            Measurement error in explanatory variables and unmeasured confounders can cause considerable problems in epidemiologic studies. It is well recognized that under certain conditions, nondifferential measurement error in the exposure variable produces bias towards the null. Measurement error in confounders will lead to residual confounding, but this is not a straightforward issue, and it is not clear in which direction the bias will point. Unmeasured confounders further complicate matters. There has been discussion about the amount of bias in exposure effect estimates that can plausibly occur due to residual or unmeasured confounding. In this paper, the authors use simulation studies and logistic regression analyses to investigate the size of the apparent exposure-outcome association that can occur when in truth the exposure has no causal effect on the outcome. The authors consider two cases with a normally distributed exposure and either two or four normally distributed confounders. When the confounders are uncorrelated, bias in the exposure effect estimate increases as the amount of residual and unmeasured confounding increases. Patterns are more complex for correlated confounders. With plausible assumptions, effect sizes of the magnitude frequently reported in observational epidemiologic studies can be generated by residual and/or unmeasured confounding alone.
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              Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake.

              We pooled data from 5 large validation studies of dietary self-report instruments that used recovery biomarkers as references to clarify the measurement properties of food frequency questionnaires (FFQs) and 24-hour recalls. The studies were conducted in widely differing US adult populations from 1999 to 2009. We report on total energy, protein, and protein density intakes. Results were similar across sexes, but there was heterogeneity across studies. Using a FFQ, the average correlation coefficients for reported versus true intakes for energy, protein, and protein density were 0.21, 0.29, and 0.41, respectively. Using a single 24-hour recall, the coefficients were 0.26, 0.40, and 0.36, respectively, for the same nutrients and rose to 0.31, 0.49, and 0.46 when three 24-hour recalls were averaged. The average rate of under-reporting of energy intake was 28% with a FFQ and 15% with a single 24-hour recall, but the percentages were lower for protein. Personal characteristics related to under-reporting were body mass index, educational level, and age. Calibration equations for true intake that included personal characteristics provided improved prediction. This project establishes that FFQs have stronger correlations with truth for protein density than for absolute protein intake, that the use of multiple 24-hour recalls substantially increases the correlations when compared with a single 24-hour recall, and that body mass index strongly predicts under-reporting of energy and protein intakes.
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                Author and article information

                Journal
                F1000Res
                F1000Res
                F1000Research
                F1000Research
                F1000Research (London, UK )
                2046-1402
                16 June 2017
                2017
                : 6
                : 926
                Affiliations
                [1 ]Department of Hygiene, Epidemiology and Medical Statistics School of Medicine, National and Kapodistrian University of Athens, 75 M. Asias Street, Goudi, GR-115 27, Athens, Greece
                [2 ]Department of Public Health and Community Health,, School of Health Professions, Athens Technological Educational Institute (TEI Athens), Ag. Spyridonos, Aigaleo GR-122 43, Athens, Greece
                [3 ]Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA-02115, USA
                Author notes

                Competing interests: The authors declare that they have no competing interests.

                Article
                10.12688/f1000research.10703.1
                5482335
                28690835
                87d31c39-5be6-45c2-8e0d-1bc1c07afeb8
                Copyright: © 2017 Naska A et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 June 2017
                Funding
                The author(s) declared that no grants were involved in supporting this work.
                Categories
                Review
                Articles
                Epidemiology
                Integrative Physiology
                Preventive Medicine
                Social & Behavioral Determinants of Health
                Statistical Methodologies & Health Informatics

                dietary questionnaire,nutritional epidemiological investigation,dietary intake assessment

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