Evidence map›Paper›PMID 30462178›Full record

SynthesisAdvances in nutrition (Bethesda, Md.)2018

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

Marie-Ève Labonté, Theresa Poon, Branka Gladanac, Mavra Ahmed, Beatriz Franco-Arellano, Mike Rayner, Mary R L'Abbé

Abstract readSystematic Review
In one paragraph

Synthesis in Advances in nutrition (Bethesda, Md.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

85 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Nutrient profiling methods applied to mixed dishes and meals.Asia Pacific journal of clinical nutrition · 2026
    Review
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  16. Developing the Sus-Health Index: a combined measure for describing environmental impact and nutritive value of foods and meals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
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25 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Marie-Ève LabontéDepartment of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Theresa PoonDepartment of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Branka GladanacDepartment of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Mavra AhmedDepartment of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Beatriz Franco-ArellanoDepartment of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Mike RaynerCenter on Population Approaches for Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Mary R L'AbbéDepartment of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.

Funding

British Heart FoundationCanadian Institutes of Health Research MFE-140953
6 · The paper itself

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.

Indexed as

GovernmentNutrition PolicyHealth PromotionHumansNoncommunicable DiseasesPolicy Making

Identifiers

PMID30462178
PMCPMC6247226

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.