ArticleHealth promotion international2025
Unhealthy food advertising on social media: policy lessons from the Australian Ad Observatory.
Article in Health promotion international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
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Who cites it
8 citing papers in PubMed.
- Digital determinants of nutrition: the case for a distinct domain to guide health promotion research and policy.Health promotion international · 2026Review
- Public knowledge of ultra-processed foods: Insights from a national survey of Australian adults.Nutrition journal · 2026Article
- Consumption of four unhealthy commodities and exposure to advertising, sponsorship, and promotion in Bamako, Mali.Health promotion international · 2026Article
- Length and Framing of Anti-Junk Food Ads Impact Inclinations to Consume Junk Food Among Normal Weight, Overweight, and Adults With Obesity.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2026Article
- Global market trends and financial performance of the corporate fast-food industry and their potential contributions to diets high in meat and ultra-processed foods.Globalization and health · 2025Article
- Using Photovoice to explore adults' perceptions towards obesity and factors influencing food choice and physical activity in North Lebanon.Public health nutrition · 2025Article
- Unhealthy food advertising on social media: policy lessons from the Australian Ad Observatory.Health promotion international · 2025Article
- What do we talk about when we talk about digital determinants of health? - A systematic review.Digital healthReview
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The World Health Organization and public health experts are calling for urgent restrictions on the online marketing of unhealthy food. The harmful effects of exposure to advertising for 'unhealthy foods', including discretionary foods high in fat, salt or sugar, particularly for children, has prompted a proposed policy action in Australia to prohibit all online unhealthy food marketing. We used a novel data donation infrastructure, the Australian Ad Observatory, to create a dataset of 1703 ads promoting top-selling unhealthy food brands that had been placed by 141 different advertisers on 367 individual Australians' Facebook feeds. We used this dataset to identify any targeting of unhealthy food ads towards young people (18-24), investigate harmful marketing practices by four of the top advertisers (KFC, McDonald's, Cadbury and 7-Eleven); and demonstrate how online advertising may be made observable and accountable. We find indications that young people (18-24), especially young men, are being targeted by unhealthy food, especially fast food, ads. We also find that unhealthy food brands use potentially harmful marketing strategies to appeal to children, young people, parents and the broader community, including cartoon characters, and associations with popular sports and greenwashing. The policy implications of our findings are that a broad prohibition on all forms of unhealthy food advertising online is desirable to protect not only children but also young people and the broader community. Such a prohibition will go one step towards addressing the commercial and digital determinants of health caused by harmful industries' use of online automated advertising.
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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.