Evidence map›Paper›PMID 34610024›Full record

SynthesisPLoS medicine2021

Impact of color-coded and warning nutrition labelling schemes: A systematic review and network meta-analysis.

Jing Song, Mhairi K Brown, Monique Tan, Graham A MacGregor, Jacqui Webster, Norm R C Campbell, Kathy Trieu, Cliona Ni Mhurchu, Laura K Cobb, Feng J He

Open access · goldAbstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in PLoS medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 4 pooled it
25.9field-weighted citation impact, top 1% of its field
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

100 citing papers in PubMed, 4 syntheses or guidelines pooled it, 209 citations in OpenAlex.

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40 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

10 authors at 5 institutions in 5 countries.

Jing SongWolfson Institute of Population Health, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, United Kingdom.
Mhairi K BrownWolfson Institute of Population Health, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, United Kingdom.
Monique TanWolfson Institute of Population Health, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, United Kingdom.ORCID 0000-0003-4287-5553
Graham A MacGregorWolfson Institute of Population Health, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, United Kingdom.
Jacqui WebsterThe George Institute for Global Health, University of New South Wales, Newtown, Australia.
Norm R C CampbellDepartment of Medicine and Libin Cardiovascular Institute, University of Calgary, Alberta, Canada.
Kathy TrieuThe George Institute for Global Health, University of New South Wales, Newtown, Australia.ORCID 0000-0003-1848-2741
Cliona Ni MhurchuThe George Institute for Global Health, University of New South Wales, Newtown, Australia.
Laura K CobbResolve to Save Lives, Vital Strategies, New York City, New York, United States of America.
Feng J HeWolfson Institute of Population Health, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, United Kingdom.ORCID 0000-0003-2807-4119
Queen Mary University of London · GBUNSW Sydney · AUUniversity of Auckland · NZUniversity of Calgary · CAVital Strategies · US

Funding

Department of Health
6 · The paper itself

Abstract

backgroundSuboptimal diets are a leading risk factor for death and disability. Nutrition labelling is a potential method to encourage consumers to improve dietary behaviour. This systematic review and network meta-analysis (NMA) summarises evidence on the impact of colour-coded interpretive labels and warning labels on changing consumers' purchasing behaviour. METHODS AND

findingsWe conducted a literature review of peer-reviewed articles published between 1 January 1990 and 24 May 2021 in PubMed, Embase via Ovid, Cochrane Central Register of Controlled Trials, and SCOPUS. Randomised controlled trials (RCTs) and quasi-experimental studies were included for the primary outcomes (measures of changes in consumers' purchasing and consuming behaviour). A frequentist NMA method was applied to pool the results. A total of 156 studies (including 101 RCTs and 55 non-RCTs) nested in 138 articles were incorporated into the systematic review, of which 134 studies in 120 articles were eligible for meta-analysis. We found that the traffic light labelling system (TLS), nutrient warning (NW), and health warning (HW) were associated with an increased probability of selecting more healthful products (odds ratios [ORs] and 95% confidence intervals [CIs]: TLS, 1.5 [1.2, 1.87]; NW, 3.61 [2.82, 4.63]; HW, 1.65 [1.32, 2.06]). Nutri-Score (NS) and warning labels appeared effective in reducing consumers' probability of selecting less healthful products (NS, 0.66 [0.53, 0.82]; NW,0.65 [0.54, 0.77]; HW,0.64 [0.53, 0.76]). NS and NW were associated with an increased overall healthfulness (healthfulness ratings of products purchased using models such as FSAm-NPS/HCSP) by 7.9% and 26%, respectively. TLS, NS, and NW were associated with a reduced energy (total energy: TLS, -6.5%; NS, -6%; NW, -12.9%; energy per 100 g/ml: TLS, -3%; NS, -3.5%; NW, -3.8%), sodium (total sodium/salt: TLS, -6.4%; sodium/salt per 100 g/ml: NS: -7.8%), fat (total fat: NS, -15.7%; fat per 100 g/ml: TLS: -2.6%; NS: -3.2%), and total saturated fat (TLS, -12.9%; NS: -17.1%; NW: -16.3%) content of purchases. The impact of TLS, NS, and NW on purchasing behaviour could be explained by improved understanding of the nutrition information, which further elicits negative perception towards unhealthful products or positive attitudes towards healthful foods. Comparisons across label types suggested that colour-coded labels performed better in nudging consumers towards the purchase of more healthful products (NS versus NW: 1.51 [1.08, 2.11]), while warning labels have the advantage in discouraging unhealthful purchasing behaviour (NW versus TLS: 0.81 [0.67, 0.98]; HW versus TLS: 0.8 [0.63, 1]). Study limitations included high heterogeneity and inconsistency in the comparisons across different label types, limited number of real-world studies (95% were laboratory studies), and lack of long-term impact assessments.

conclusionsOur systematic review provided comprehensive evidence for the impact of colour-coded labels and warnings in nudging consumers' purchasing behaviour towards more healthful products and the underlying psychological mechanism of behavioural change. Each type of label had different attributes, which should be taken into consideration when making front-of-package nutrition labelling (FOPL) policies according to local contexts. Our study supported mandatory front-of-pack labelling policies in directing consumers' choice and encouraging the food industry to reformulate their products. PROTOCOL REGISTRY: PROSPERO (CRD42020161877).

Indexed as

Food LabelingNutritive ValueAdolescentAdultAttentionChildColorConsumer BehaviorFemaleHealth CommunicationHumansLogicMalePerceptionRisk FactorsSelf Report

Identifiers

PMID34610024
PMCPMC8491916
OpenAlexW3203433136

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.