ArticleNutrients2023
How Foods and Beverages Are Promoted Online: A Content Analysis of the Digital Food Environment in China.
Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Fast food, fast aging? A cross-sectional study in the UK.BMC public health · 2026Article
- Digital food environments, food literacy, and sustainable eating among children in China: evidence from National Panel Data on supermarket availability and nutritional status.Frontiers in nutrition · 2026Article
- Editorial on Nutrition Education, Food Literacy, and Healthy Diets in Childhood and Adolescence.Nutrients · 2024Article
- Exploring Socioeconomic Disparities in Adults' Interactions with the Digital Food Environment: A Qualitative Study.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Digital platforms such as social media and e-commerce platforms have become a major space where foods and beverages (F&B) are promoted. Prior research has found that online, unhealthy F&B receive more presence than healthy F&B. This obesogenic food environment may increase the obesity rate. Therefore, it is critical to understand how healthy and unhealthy F&B are promoted online. A content analysis of 2906 posts related to F&B via five digital platforms was conducted in China, where the obesity rate has increased in recent years. Firstly, the results show that unhealthy F&B received more presence on digital platforms than healthy F&B. Secondly, healthy F&B posts tended to highlight the healthiness of the products, whereas unhealthy F&B posts leveraged a wide range of promotional strategies, specifically use cues, food cues, chewing sounds, sensory descriptions, friend cues, local cultural appeal, nostalgia appeal, price information, discount information, and trending hashtags or topics. Next, use cues, chewing sounds, sensory descriptions, family cues, and friend cues increased the quantity of audience feedback, whereas price information and using trending hashtags or topics lowered the quantity of audience feedback. Moreover, local cultural appeal and social proof exhibited the opposite impact on audience feedback. Finally, health benefit statements lowered audience feedback for healthy F&B posts, whereas brand visibility and purchase links inhibited audience feedback for unhealthy F&B posts. In addition to describing the digital food environment in China, the present research provides implications on how to promote healthy F&B. Particularly, we suggest that healthy F&B businesses and healthy eating campaigns should leverage the strategies unhealthy F&B use to receive more consumer attention, in order to increase their own products' public visibility and attractiveness.
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Identifiers
What OpenQuestion holds
Registered trials
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.