5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial

      research-article
      1 , 2 , 1 , 3 , 4 , 5 , 6 , 7 , 6 , 7 , 8 , 9 , 9 , 9 , 10 , 11 , 10 , 12 , 13 , 14 , 15 , 16 , 17 , 16 , 18 , 15 , 16 , 9 , 9 , 9 , 9 , 6 , 7 , 8 , 1 , , on behalf of the Food4Me Study
      The International Journal of Behavioral Nutrition and Physical Activity
      BioMed Central
      Discretionary, Discretionary foods and beverages, Personalised nutrition, Internet-based, Intervention, European, Adults, Food4Me

      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

          Background

          The effect of personalised nutrition advice on discretionary foods intake is unknown. To date, two national classifications for discretionary foods have been derived. This study examined changes in intake of discretionary foods and beverages following a personalised nutrition intervention using these two classifications.

          Methods

          Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomised to receive generalised dietary advice (control) or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Dietary intake was derived from an FFQ. An analysis of covariance was used to determine intervention effects at month 6 between personalised nutrition (overall and by levels) and control on i) percentage energy from discretionary items and ii) percentage contribution of total fat, SFA, total sugars and salt to discretionary intake, defined by Food Standards Scotland (FSS) and Australian Dietary Guidelines (ADG) classifications.

          Results

          Of the 1607 adults at baseline, n = 1270 (57% female) completed the intervention. Percentage sugars from FSS discretionary items was lower in personalised nutrition vs control (19.0 ± 0.37 vs 21.1 ± 0.65; P = 0.005). Percentage energy (31.2 ± 0.59 vs 32.7 ± 0.59; P = 0.031), percentage total fat (31.5 ± 0.37 vs 33.3 ± 0.65; P = 0.021), SFA (36.0 ± 0.43 vs 37.8 ± 0.75; P = 0.034) and sugars (31.7 ± 0.44 vs 34.7 ± 0.78; P < 0.001) from ADG discretionary items were lower in personalised nutrition vs control. There were greater reductions in ADG percentage energy and percentage total fat, SFA and salt for those randomised to L3 vs L2.

          Conclusions

          Compared with generalised dietary advice, personalised nutrition advice achieved greater reductions in discretionary foods intake when the classification included all foods high in fat, added sugars and salt. Future personalised nutrition approaches may be used to target intake of discretionary foods.

          Trial registration

          Clinicaltrials.gov NCT01530139. Registered 9 February 2012.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12966-021-01136-5.

          Related collections

          Most cited references47

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

          What's wrong with Bonferroni adjustments

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

            Basal metabolic rate studies in humans: measurement and development of new equations.

            CJK Henry (2005)
            To facilitate the Food and Agriculture Organization/World Health Organization/United Nations University Joint (FAO/WHO/UNU) Expert Consultation on Energy and Protein Requirements which met in Rome in 1981, Schofield et al. reviewed the literature and produced predictive equations for both sexes for the following ages: 0-3, 3-10, 10-18, 18-30, 30-60 and >60 years. These formed the basis for the equations used in 1985 FAO/WHO/UNU document, Energy and Protein Requirements. While Schofield's analysis has served a significant role in re-establishing the importance of using basal metabolic rate (BMR) to predict human energy requirements, recent workers have subsequently queried the universal validity and application of these equations. A survey of the most recent studies (1980-2000) in BMR suggests that in most cases the current FAO/WHO/UNU predictive equations overestimate BMR in many communities. The FAO/WHO/UNU equations to predict BMR were developed using a database that contained a disproportionate number--3388 out of 7173 (47%)--of Italian subjects. The Schofield database contained relatively few subjects from the tropical region. The objective here is to review the historical development in the measurement and application of BMR and to critically review the Schofield et al. BMR database presenting a series of new equations to predict BMR. This division, while arbitrary, will enable readers who wish to omit the historical review of BMR to concentrate on the evolution of the new BMR equations. BMR data collected from published and measured values. A series of new equations (Oxford equations) have been developed using a data set of 10,552 BMR values that (1) excluded all the Italian subjects and (2) included a much larger number (4018) of people from the tropics. In general, the Oxford equations tend to produce lower BMR values than the current FAO/WHO/UNU equations in 18-30 and 30-60 year old males and in all females over 18 years of age. This is an opportune moment to re-examine the role and place of BMR measurements in estimating total energy requirements today. The Oxford equations' future use and application will surely depend on their ability to predict more accurately the BMR in contemporary populations.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Ultra‐processed foods and the nutrition transition: Global, regional and national trends, food systems transformations and political economy drivers

              Understanding the drivers and dynamics of global ultra-processed food (UPF) consumption is essential, given the evidence linking these foods with adverse health outcomes. In this synthesis review, we take two steps. First, we quantify per capita volumes and trends in UPF sales, and ingredients (sweeteners, fats, sodium and cosmetic additives) supplied by these foods, in countries classified by income and region. Second, we review the literature on food systems and political economy factors that likely explain the observed changes. We find evidence for a substantial expansion in the types and quantities of UPFs sold worldwide, representing a transition towards a more processed global diet but with wide variations between regions and countries. As countries grow richer, higher volumes and a wider variety of UPFs are sold. Sales are highest in Australasia, North America, Europe and Latin America but growing rapidly in Asia, the Middle East and Africa. These developments are closely linked with the industrialization of food systems, technological change and globalization, including growth in the market and political activities of transnational food corporations and inadequate policies to protect nutrition in these new contexts. The scale of dietary change underway, especially in highly populated middle-income countries, raises serious concern for global health.
                Bookmark

                Author and article information

                Contributors
                john.mathers@newcastle.ac.uk
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                7 June 2021
                7 June 2021
                2021
                : 18
                : 70
                Affiliations
                [1 ]GRID grid.1006.7, ISNI 0000 0001 0462 7212, Human Nutrition Research Centre, , Population Health Sciences Institute, Newcastle University, ; William Leech Building, Newcastle upon Tyne, NE2 4HH UK
                [2 ]GRID grid.1021.2, ISNI 0000 0001 0526 7079, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, ; Geelong, 3220 VIC Australia
                [3 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, BHF Glasgow Cardiovascular Research Centre, , Institute of Cardiovascular and Medical Sciences, University of Glasgow, ; Glasgow, UK
                [4 ]GRID grid.411964.f, ISNI 0000 0001 2224 0804, Research Unit on Education, Physical Activity and Health (GEEAFyS), , Universidad Católica del Maule, ; Talca, Chile
                [5 ]GRID grid.412199.6, ISNI 0000 0004 0487 8785, Centre of Research in Exercise Physiology (CIFE), , Universidad Mayor, ; Santiago, Chile
                [6 ]GRID grid.5924.a, ISNI 0000000419370271, Department of Nutrition, Food Science and Physiology, , University of Navarra, ; Pamplona, Spain
                [7 ]GRID grid.413448.e, ISNI 0000 0000 9314 1427, CIBERobn, Fisiopatología de la Obesidad y Nutrición, , Instituto de Salud Carlos III, ; Madrid, Spain
                [8 ]GRID grid.482878.9, ISNI 0000 0004 0500 5302, Precision Nutrition and Cardiometabolic Health, , IMDEA-Food Institute (Madrid Institute for Advanced Studies), CEI UAM + CSIC, ; Madrid, Spain
                [9 ]GRID grid.7886.1, ISNI 0000 0001 0768 2743, UCD Institute of Food and Health, University College Dublin, ; Belfield, Dublin 4 Republic of Ireland
                [10 ]GRID grid.15823.3d, ISNI 0000 0004 0622 2843, Department of Nutrition and Dietetics, , Harokopio University, ; Athens, Greece
                [11 ]GRID grid.1018.8, ISNI 0000 0001 2342 0938, Department of Dietetics, Nutrition and Sport, , School of Allied Health, Human Services and Sport, La Trobe University, ; Bundoora, 3086 VIC Australia
                [12 ]GRID grid.13339.3b, ISNI 0000000113287408, Department of Human Nutrition, Faculty of Health Sciences, , Medical University of Warsaw, ; Warsaw, Poland
                [13 ]GRID grid.439075.c, Vitas AS, ; Gaustadalléen 21, 0349 Oslo, Norway
                [14 ]GRID grid.5510.1, ISNI 0000 0004 1936 8921, Department of Nutrition, Faculty of Medicine, , Institute of Basic Medical Sciences, University of Oslo, ; Oslo, Norway
                [15 ]GRID grid.412966.e, ISNI 0000 0004 0480 1382, Department of Human Biology, , NUTRIM, School for Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre, ; Maastricht, The Netherlands
                [16 ]GRID grid.9435.b, ISNI 0000 0004 0457 9566, Department of Food and Nutritional Sciences, , Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, ; Reading, UK
                [17 ]GRID grid.5846.f, ISNI 0000 0001 2161 9644, School of Life and Medical Sciences, University of Hertfordshire, ; Hatfield, UK
                [18 ]GRID grid.6936.a, ISNI 0000000123222966, Molecular Nutrition Unit, Department Food and Nutrition, , Technische Universität München, ; München, Germany
                Author information
                http://orcid.org/0000-0002-9682-7541
                Article
                1136
                10.1186/s12966-021-01136-5
                8183081
                34092234
                abb4cb7b-5b50-45c6-aaf9-7527d3c30678
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 15 October 2020
                : 7 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100011102, Seventh Framework Programme;
                Award ID: 265494
                Award Recipient :
                Funded by: National Health and Medical Research Council
                Award ID: APP1173803
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Nutrition & Dietetics
                discretionary,discretionary foods and beverages,personalised nutrition,internet-based,intervention,european,adults, food4me

                Comments

                Comment on this article