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Record W4409384123 · doi:10.1038/s41366-025-01771-z

Prevalence of online food delivery platforms, meal kit delivery, and online grocery use in five countries: an analysis of survey data from the 2022 International Food Policy Study

2025· article· en· W4409384123 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Obesity · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsUniversité LavalUniversity of Waterloo
Fundersnot available
KeywordsFood deliveryMealMedicineGrocery shoppingBusinessEnvironmental healthMarketingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Online food retail use is rapidly increasing in popularity, and offers user-friendly apps, and new food delivery models, including online food delivery platforms, online grocery retailers, and online meal kit delivery. We aimed to: (1) quantify the prevalence of online food retail platform use by adults across Australia, Canada, Mexico, the United Kingdom and the United States, and to (2) assess the associations between sociodemographic and behavioural factors and use of online food retail platforms. METHODS: A cross-sectional online survey was conducted with adults as part of the 2022 International Food Policy Survey (n = 19,877). We described the frequency of use and number of meals ordered using different online food retail and delivery platforms. Logistic regression models were fitted to assess associations between the use of online food retail and delivery platforms, and sociodemographic and behavioural factors (including age, sex, household composition, BMI, income adequacy, ethnicity, cooking skills, nutrition knowledge, and frequency of food preparation). RESULTS: Online ordering was more prevalent in Mexico (72%), and in the United States (62%) in comparison with Australia, Canada, or the United Kingdom (45-56%). Overall, across all countries, 58% of participants used online retail and delivery platforms, most commonly online orders from restaurants (36% of participants), online supermarkets (28%), online meal kits (14%), online only grocery stores (11%), and online convenience stores (11%). The odds of using online restaurants was significantly higher for men (OR: 1.23, 95% CI: 1.14-1.33) and participants aged 18-29 (compared to those 60 years or older) (OR: 6.10, 95% CI: 5.34-7.00). Participants aged 18-29 also had the highest odds of using online convenience stores (OR: 7.51, 95% CI: 5.71-9.88). Participants living with primary school aged children had higher odds of using online supermarkets compared to those without children (OR: 2.56, 95% CI: 2.22-2.94). CONCLUSIONS: A substantial proportion of people are buying food online. Efforts to improve population diets need to ensure that online food retail platforms support good health and nutrition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.087
GPT teacher head0.334
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it