17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber ( r = 0.58–0.84, all p < 0.05), and for micronutrients both including ( r = 0.47–0.94, all p < 0.05) and excluding ( r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women.

          Related collections

          Most cited references42

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Strengthening the Reporting of Observational Studies in Epidemiology—Nutritional Epidemiology (STROBE-nut): An Extension of the STROBE Statement

          Background Concerns have been raised about the quality of reporting in nutritional epidemiology. Research reporting guidelines such as the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement can improve quality of reporting in observational studies. Herein, we propose recommendations for reporting nutritional epidemiology and dietary assessment research by extending the STROBE statement into Strengthening the Reporting of Observational Studies in Epidemiology—Nutritional Epidemiology (STROBE-nut). Methods and Findings Recommendations for the reporting of nutritional epidemiology and dietary assessment research were developed following a systematic and consultative process, coordinated by a multidisciplinary group of 21 experts. Consensus on reporting guidelines was reached through a three-round Delphi consultation process with 53 external experts. In total, 24 recommendations for nutritional epidemiology were added to the STROBE checklist. Conclusion When used appropriately, reporting guidelines for nutritional epidemiology can contribute to improve reporting of observational studies with a focus on diet and health.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Need for technological innovation in dietary assessment.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Number of days of food intake records required to estimate individual and group nutrient intakes with defined confidence.

              The number of days of food intake data needed to estimate the intake of 29 male (n = 13) and female (n = 16) adult subjects, individually and as a group, was determined for food energy and 18 nutrients. The food intake records were collected in a year-long study conducted by the U.S. Department of Agriculture's Beltsville Human Nutrition Research Center. Each individual's average intake of nutrients and standard deviation over the year were assumed to reflect his or her "usual" intake and day-to-day variability. Confidence intervals (P less than 0.05) for each individual's usual intake were constructed, and from these the number of days of dietary records needed for estimated individual and group intake to be within 10% of usual intake was calculated. The results indicated that the number of days of food intake records needed to predict the usual nutrient intake of an individual varied substantially among individuals for the same nutrient and within individuals for different nutrients; e.g., food energy required the fewest days (averaging 31) and vitamin A the most (averaging 433). This was considerably higher than the number of days needed to estimate mean nutrient intake for this group, which ranged from 3 for food energy to 41 for vitamin A. Fewer days would be needed for larger groups.
                Bookmark

                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                18 January 2017
                January 2017
                : 9
                : 1
                : 73
                Affiliations
                [1 ]School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, University Drive, Callaghan 2308, New South Wales, Australia; amy.ashman@ 123456uon.edu.au (A.M.A.); clare.collins@ 123456newcastle.edu.au (C.E.C.)
                [2 ]Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, University Drive, Callaghan 2308, New South Wales, Australia
                [3 ]Gomeroi gaaynggal Centre, Faculty of Health and Medicine, University of Newcastle, 2/1 Hinkler Street, Tamworth 2340, New South Wales, Australia; kym.rae@ 123456newcastle.edu.au
                [4 ]Department of Rural Health, Faculty of Health and Medicine, University of Newcastle, 114-148 Johnston Street, Tamworth 2340, New South Wales, Australia; leanne.brown@ 123456newcastle.edu.au
                [5 ]Priority Research Centre in Reproduction, Faculty of Health and Medicine, University of Newcastle, University Drive, Callaghan 2308, New South Wales, Australia
                Author notes
                [* ]Correspondence: megan.rollo@ 123456newcastle.edu.au ; Tel.: +61-02-4921-5649
                Article
                nutrients-09-00073
                10.3390/nu9010073
                5295117
                28106758
                4c02a7b3-2a78-420c-a5ac-875ee68de889
                © 2017 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 ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 27 November 2016
                : 13 January 2017
                Categories
                Article

                Nutrition & Dietetics
                nutrition assessment,pregnancy,mhealth,image-based dietary records,indigenous

                Comments

                Comment on this article