ArticleFrontiers in nutrition2022
Stakeholder Network Analysis for Front-of-Pack Labeling in China.
Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Color and shape matter: how visual design features of front-of-package warning labels influence attractiveness perception, healthfulness perception and purchase intention.Eating and weight disorders : EWD · 2026Article
- Article
- Consumer preferences for evaluative front-of-package nutrition labels: evidence from a choice experiment in China.Frontiers in nutrition · 2025Article
- Evaluation of the Nutritional Quality of Chinese Processed Meat Products: Comparison of Two Nutrient Profile Models.Nutrients · 2024Article
- Chinese Consumers' Trust in Food Safety Surveillance Sampling of Commonly Consumed Foods.Foods (Basel, Switzerland) · 2022Article
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Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Front-of-pack (FoP) labeling on packaged foods is recommended by the World Health Organization (WHO) to reduce diet-related non-communicable diseases, but it has not yet been implemented in China. The introduction of FoP labeling is driven by multiple institutions and stakeholders. This study aimed to identify key institutional actors involved in FoP labeling and describe links between actors to support future FoP labeling policies and programmes in China. Methods: The Net-Map method was adopted. We conducted Net-map activities with eight participants using face-to-face interviews between November 2020 and May 2021. Participants were asked to identify actors involved in the development and implementation of FoP labeling in China, describe networks among actors according to pre-defined link types (command, dissemination, funding, and technical assistance), and estimate influence of each actor within the FoP labeling landscape. Social network analysis measures of cohesion and centrality were used to describe each network. Gephi software was used for social network analysis and network visualization. Results: Forty-one unique actors were identified across seven actor categories including government agencies ( Conclusions: A variety of multisectoral actors have an interest in the introduction of FoP labeling policies and programmes. Effectively engaging key actors identified in this study can generate a multisectoral commitment to advance FoP labeling policies and programmes in China.
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Registered trials
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