Literature DB >> 30462178

Nutrient Profile Models with Applications in Government-Led Nutrition Policies Aimed at Health Promotion and Noncommunicable Disease Prevention: A Systematic Review.

Marie-Ève Labonté1, Theresa Poon1, Branka Gladanac1, Mavra Ahmed1, Beatriz Franco-Arellano1, Mike Rayner2, Mary R L'Abbé1.   

Abstract

Nutrient profile (NP) models, tools used to rate or evaluate the nutritional quality of foods, are increasingly used by government bodies worldwide to underpin nutrition-related policies. An up-to-date and accessible list of existing NP models is currently unavailable to support their adoption or adaptation in different jurisdictions. This study used a systematic approach to develop a global resource that summarizes key characteristics of NP models with applications in government-led nutrition policies. NP models were identified from an unpublished WHO catalog of NP models last updated in 2012 and from searches conducted in different databases of the peer-reviewed (n = 3; e.g., PubMed) and gray literature (n = 15). Included models had to meet the following inclusion criteria (selected) as of 22 December 2016: 1) developed or endorsed by governmental or intergovernmental organizations, 2) allow for the evaluation of individual food items, and 3) have publicly available nutritional criteria. A total of 387 potential NP models were identified, including n = 361 from the full-text assessment of >600 publications and n = 26 exclusively from the catalog. Seventy-eight models were included. Most (73%) were introduced within the past 10 y, and 44% represent adaptations of ≥1 previously built model. Models were primarily built for school food standards or guidelines (n = 27), food labeling (e.g., front-of-pack; n = 12), and restriction of the marketing of food products to children (n = 10). All models consider nutrients to limit, with sodium, saturated fatty acids, and total sugars being included most frequently; and 86% also consider ≥1 nutrient to encourage (e.g., fiber). No information on validity testing could be identified for 58% of the models. Given the proliferation of NP models worldwide, this new resource will be highly valuable for assisting health professionals and policymakers in the selection of an appropriate model when the establishment of nutrition-related policies requires the use of nutrient profiling.

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Year:  2018        PMID: 30462178      PMCID: PMC6247226          DOI: 10.1093/advances/nmy045

Source DB:  PubMed          Journal:  Adv Nutr        ISSN: 2161-8313            Impact factor:   8.701


  20 in total

1.  Nutrition environment measures survey-vending: development, dissemination, and reliability.

Authors:  Carol Voss; Susan Klein; Karen Glanz; Margaret Clawson
Journal:  Health Promot Pract       Date:  2012-07

2.  Product variety in Australian snacks and drinks: how can the consumer make a healthy choice?

Authors:  Karen Z Walker; Julie L Woods; Cassie A Rickard; Carrie K Wong
Journal:  Public Health Nutr       Date:  2007-12-21       Impact factor: 4.022

3.  Developing nutrient profile models: a systematic approach.

Authors:  Peter Scarborough; Mike Rayner; Lynn Stockley
Journal:  Public Health Nutr       Date:  2007-04       Impact factor: 4.022

4.  Applications of nutrient profiling: potential role in diet-related chronic disease prevention and the feasibility of a core nutrient-profiling system.

Authors:  G Sacks; M Rayner; L Stockley; P Scarborough; W Snowdon; B Swinburn
Journal:  Eur J Clin Nutr       Date:  2011-01-19       Impact factor: 4.016

5.  Nutrient profiling and the regulation of marketing to children. Possibilities and pitfalls.

Authors:  Mike Rayner; Peter Scarborough; Asha Kaur
Journal:  Appetite       Date:  2012-08-07       Impact factor: 3.868

6.  Added sugars on nutrition labels: a way to support population health in Canada.

Authors:  Jodi T Bernstein; Mary R L'Abbé
Journal:  CMAJ       Date:  2016-03-14       Impact factor: 8.262

7.  Protecting New Zealand children from exposure to the marketing of unhealthy foods and drinks: a comparison of three nutrient profiling systems to classify foods.

Authors:  Cliona Ni Mhurchu; Tara Mackenzie; Stefanie Vandevijvere
Journal:  N Z Med J       Date:  2016-09-09

Review 8.  Development of international criteria for a front of package food labelling system: the International Choices Programme.

Authors:  A J C Roodenburg; B M Popkin; J C Seidell
Journal:  Eur J Clin Nutr       Date:  2011-06-22       Impact factor: 4.016

9.  Assessing the nutritional quality of diets of Canadian children and adolescents using the 2014 Health Canada Surveillance Tool Tier System.

Authors:  Mahsa Jessri; Stephanie K Nishi; Mary R L'Abbe
Journal:  BMC Public Health       Date:  2016-05-10       Impact factor: 3.295

Review 10.  Food subsidy programs and the health and nutritional status of disadvantaged families in high income countries: a systematic review.

Authors:  Andrew P Black; Julie Brimblecombe; Helen Eyles; Peter Morris; Hassan Vally; Kerin O Dea
Journal:  BMC Public Health       Date:  2012-12-21       Impact factor: 3.295

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  31 in total

1.  Governmental policies to reduce unhealthy food marketing to children.

Authors:  Lindsey Smith Taillie; Emily Busey; Fernanda Mediano Stoltze; Francesca Renee Dillman Carpentier
Journal:  Nutr Rev       Date:  2019-11-01       Impact factor: 7.110

Review 2.  Effect of Formulation, Labelling, and Taxation Policies on the Nutritional Quality of the Food Supply.

Authors:  Stefanie Vandevijvere; Lana Vanderlee
Journal:  Curr Nutr Rep       Date:  2019-09

3.  Evaluating intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model.

Authors:  Priscila Machado; Gustavo Cediel; Julie Woods; Phillip Baker; Sarah Dickie; Fabio S Gomes; Gyorgy Scrinis; Mark Lawrence
Journal:  Eur J Nutr       Date:  2022-01-16       Impact factor: 5.614

4.  Evaluating nutrition quality of packaged foods carrying claims and marketing techniques in Brazil using four nutrient profile models.

Authors:  Rafaela Corrêa Pereira; João de Deus Souza Carneiro; Michel Cardoso de Angelis Pereira
Journal:  J Food Sci Technol       Date:  2021-06-09       Impact factor: 2.701

5.  Nutrition Classification Schemes for Informing Nutrition Policy in Australia: Nutrient-Based, Food-Based, or Dietary-Based?

Authors:  Sarah Dickie; Julie Woods; Priscila Machado; Mark Lawrence
Journal:  Curr Dev Nutr       Date:  2022-07-04

6.  Nutritional Quality of Pre-Packaged Foods in China under Various Nutrient Profile Models.

Authors:  Yuan Li; Huijun Wang; Puhong Zhang; Barry M Popkin; Daisy H Coyle; Jingmin Ding; Le Dong; Jiguo Zhang; Wenwen Du; Simone Pettigrew
Journal:  Nutrients       Date:  2022-06-29       Impact factor: 6.706

7.  Scientific advice related to nutrient profiling for the development of harmonised mandatory front-of-pack nutrition labelling and the setting of nutrient profiles for restricting nutrition and health claims on foods.

Authors:  Dominique Turck; Torsten Bohn; Jacqueline Castenmiller; Stefaan de Henauw; Karen Ildico Hirsch-Ernst; Helle Katrine Knutsen; Alexandre Maciuk; Inge Mangelsdorf; Harry J McArdle; Androniki Naska; Carmen Peláez; Kristina Pentieva; Frank Thies; Sophia Tsabouri; Marco Vinceti; Jean-Louis Bresson; Alfonso Siani
Journal:  EFSA J       Date:  2022-04-19

8.  Recent Trends in Junk Food Intake in U.S. Children and Adolescents, 2003-2016.

Authors:  Elizabeth K Dunford; Barry M Popkin; Shu Wen Ng
Journal:  Am J Prev Med       Date:  2020-04-23       Impact factor: 5.043

9.  Multiple Metrics of Carbohydrate Quality Place Starchy Vegetables Alongside Non-starchy Vegetables, Legumes, and Whole Fruit.

Authors:  Adam Drewnowski; Matthieu Maillot; Florent Vieux
Journal:  Front Nutr       Date:  2022-05-02

10.  Nutritional Quality of Vegetarian and Non-Vegetarian Dishes at School: Are Nutrient Profiling Systems Sufficiently Informative?

Authors:  Romane Poinsot; Florent Vieux; Christophe Dubois; Marlène Perignon; Caroline Méjean; Nicole Darmon
Journal:  Nutrients       Date:  2020-07-28       Impact factor: 5.717

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