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      Using Wearable Cameras to Assess Foods and Beverages Omitted in 24 Hour Dietary Recalls and a Text Entry Food Record App

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          Abstract

          Technology-enhanced methods of dietary assessment may still face common limitations of self-report. This study aimed to assess foods and beverages omitted when both a 24 h recall and a smartphone app were used to assess dietary intake compared with camera images. For three consecutive days, young adults (18–30 years) wore an Autographer camera that took point-of-view images every 30 seconds. Over the same period, participants reported their diet in the app and completed daily 24 h recalls. Camera images were reviewed for food and beverages, then matched to the items reported in the 24 h recall and app. ANOVA (with post hoc analysis using Tukey Honest Significant Difference) and paired t-test were conducted. Discretionary snacks were frequently omitted by both methods ( p < 0.001). Water was omitted more frequently in the app than in the camera images ( p < 0.001) and 24 h recall ( p < 0.001). Dairy and alternatives ( p = 0.001), sugar-based products ( p = 0.007), savoury sauces and condiments ( p < 0.001), fats and oils ( p < 0.001) and alcohol ( p = 0.002) were more frequently omitted in the app than in the 24 h recall. The use of traditional self-report methods of assessing diet remains problematic even with the addition of technology and finding new objective methods that are not intrusive and are of low burden to participants remains a challenge.

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          Most cited references44

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            Addressing Current Criticism Regarding the Value of Self-Report Dietary Data.

            Recent reports have asserted that, because of energy underreporting, dietary self-report data suffer from measurement error so great that findings that rely on them are of no value. This commentary considers the amassed evidence that shows that self-report dietary intake data can successfully be used to inform dietary guidance and public health policy. Topics discussed include what is known and what can be done about the measurement error inherent in data collected by using self-report dietary assessment instruments and the extent and magnitude of underreporting energy compared with other nutrients and food groups. Also discussed is the overall impact of energy underreporting on dietary surveillance and nutritional epidemiology. In conclusion, 7 specific recommendations for collecting, analyzing, and interpreting self-report dietary data are provided: (1) continue to collect self-report dietary intake data because they contain valuable, rich, and critical information about foods and beverages consumed by populations that can be used to inform nutrition policy and assess diet-disease associations; (2) do not use self-reported energy intake as a measure of true energy intake; (3) do use self-reported energy intake for energy adjustment of other self-reported dietary constituents to improve risk estimation in studies of diet-health associations; (4) acknowledge the limitations of self-report dietary data and analyze and interpret them appropriately; (5) design studies and conduct analyses that allow adjustment for measurement error; (6) design new epidemiologic studies to collect dietary data from both short-term (recalls or food records) and long-term (food-frequency questionnaires) instruments on the entire study population to allow for maximizing the strengths of each instrument; and (7) continue to develop, evaluate, and further expand methods of dietary assessment, including dietary biomarkers and methods using new technologies.
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              Performance of the Automated Self-Administered 24-hour Recall relative to a measure of true intakes and to an interviewer-administered 24-h recall.

              The Automated Self-Administered 24-hour Recall (ASA24), a freely available Web-based tool, was developed to enhance the feasibility of collecting high-quality dietary intake data from large samples.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                26 May 2021
                June 2021
                : 13
                : 6
                : 1806
                Affiliations
                [1 ]Charles Perkins Centre, Nutrition and Dietetics Group, School of Life and Environmental Science, The University of Sydney, Camperdown, NSW 2006, Australia; alyse.davies@ 123456sydney.edu.au (A.D.); lyndalw@ 123456nswcc.org.au (L.W.-C.); silu7263@ 123456alumni.sydney.edu.au (S.L.); hong7393@ 123456alumni.sydney.edu.au (H.N.); ltso3453@ 123456alumni.sydney.edu.au (L.T.); atis3011@ 123456alumni.sydney.edu.au (A.T.); anna.rangan@ 123456sydney.edu.au (A.R.); luke.gemming@ 123456sydney.edu.au (L.G.); margaret.allman-farinelli@ 123456sydney.edu.au (M.A.-F.)
                [2 ]Cancer Prevention and Advocacy Division, Cancer Council NSW, Woolloomooloo, NSW 2011, Australia
                [3 ]Health Promotion & Policy Research Unit, Department of Public Health, University of Otago, 6242 Wellington, New Zealand; louise.signal@ 123456otago.ac.nz
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-8839-896X
                https://orcid.org/0000-0002-9448-7539
                https://orcid.org/0000-0003-1514-2135
                https://orcid.org/0000-0003-1815-844X
                https://orcid.org/0000-0002-6478-1374
                Article
                nutrients-13-01806
                10.3390/nu13061806
                8228902
                34073378
                b62df218-bbcd-4ff8-ba0e-d5056106ab86
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 04 May 2021
                : 24 May 2021
                Categories
                Article

                Nutrition & Dietetics
                dietary assessment,nutrition,technologies,wearable cameras,young adults
                Nutrition & Dietetics
                dietary assessment, nutrition, technologies, wearable cameras, young adults

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