Evidence map›Paper›PMID 42249433›Full record

ArticleNutrition journal2026

Public knowledge of ultra-processed foods: Insights from a national survey of Australian adults.

Priscila Machado, Emily Denniss, Catherine G Russell, Neha Khandpur, Jennifer Lacy-Nichols, Cherie Russell, Kamila Gabe, Sarah A McNaughton

Abstract read
In one paragraph

Article in Nutrition journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Priscila MachadoInstitute for Physical Activity and Nutrition, Deakin University, Geelong, Australia. p.machado@deakin.edu.au.
Emily DennissInstitute for Physical Activity and Nutrition, Deakin University, Geelong, Australia.
Catherine G RussellInstitute for Physical Activity and Nutrition, Deakin University, Geelong, Australia.
Neha KhandpurDivision of Human Nutrition and Health, Wageningen University, Wageningen, Netherlands.
Jennifer Lacy-NicholsCentre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Cherie RussellGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Medicine, Deakin University, Geelong, Australia.
Kamila GabeCenter for Epidemiological Research in Nutrition and Health, University of Sao Paulo, Sao Paulo, Brazil.
Sarah A McNaughtonSchool of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.

Funding

National Health and Medical Research Council APP2033569National Health and Medical Research Council APP2034008National Heart Foundation of Australia 107268Wellcome Trust 107268
6 · The paper itself

Abstract

backgroundUltra-processed foods (UPFs) are increasingly recognised as major contributors to diet-related chronic diseases, environmental deterioration and cultural impacts. While the salience of the UPF concept in societal discourse has also grown substantially in recent years, public knowledge of UPFs remains unclear. This study aimed to explore public knowledge of, and attributes associated with, UPFs in Australia.

methodsData included cross-sectional national survey involving 1,086 adults (20-64 years) living in Australia. Data collection occurred between June and July 2024 using a piloted questionnaire administered via Qualtrics market research services. Sociodemographic characteristics and prior awareness about UPFs were collected. The survey included open-ended questions, free-listing tasks, UPF functional knowledge measures (e.g., identification of UPFs among 20 images of products; Food Processing Knowledge (FoodProK) Score), and triadic sorting techniques (used to identify attributes associated with UPFs). Multivariable linear regression models were fitted to examine associations between the number of items correctly identified as UPFs, and FoodProK scores, with socio-demographic characteristics. Open-ended responses to the main survey question 'What comes to your mind when you think of the term 'ultra-processed foods' were analysed using Leximancer, a content analysis software, to identify dominant concepts and themes. Attributes reported through the triad sorting techniques were thematically analysed.

resultsSixty-four percent of participants reported awareness of the UPF term. The dominant concepts and themes in participants' responses reflected key characteristics of UPFs (e.g., presence of industrial ingredients) and main examples were fast-food meals and soft drinks. Most participants (85%) were able to correctly identify non-UPFs, and 45% were able to correctly identify UPFs, with multigrain bread and flavoured yoghurt misclassified most often. Socio-demographic differences were observed, with women, people with higher education, Non-Indigenous people and those with prior awareness about UPFs being more likely to correctly identify UPFs. Attributes associated with UPFs included presence of artificial ingredients, low nutritional quality, convenience, and affordability.

conclusionsIn this national survey, most participants were aware of the concept of UPFs and could identify key UPF characteristics, however some UPF items were often misclassified. Future research could explore how UPF knowledge influences diet, the factors shaping this knowledge, and interventions and policies to improve knowledge and reduce UPF consumption.

Indexed as

Fast FoodsHealth Knowledge, Attitudes, PracticeAdultAustraliaCross-Sectional StudiesFemaleFood HandlingHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultAdultsAwarenessFood processingKnowledgeLiteracyNova system

Identifiers

PMID42249433
PMCPMC13459941

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.