Use of online food delivery services among adults in five countries from the International Food Policy Study 2018–2021
Bibliographic record
Abstract
Aim: Online food delivery services (OFDS) are popular for purchasing meals prepared outside home, increasing access to energy-dense and nutrient-poor foods. This adversely impacts dietary choices and health outcomes. Our study examined trends in OFDS use in Australia, Canada, Mexico, the United Kingdom (UK), and the United States (US) from 2018 to 2021. Methods: Repeated annual cross-sectional data was sourced from the International Food Policy Study for five countries among adults over 18 years (N = 83,337). Weighted estimates for trends in i) the proportion of the respondent's purchasing meals per week using OFDS, and ii) average number (and standard deviation (SD)) of meals purchased per week using OFDS were assessed. Logistic regression models were fitted. Findings: OFDS use increased among adults between 2018-2021 (Australia: 17 % of respondents purchased at least one meal in the last 7 days using OFDS in 2018 to 25 % in 2021, Canada: 12 % to 19 %, Mexico: 28 % to 38 %, UK: 19 % to 28 %, and US: 17 % to 21 %). Average number of meals purchased per week outside home remained consistent for all countries over time (e.g., in Australia, 2.70 (SD 0.06) meals in 2018 and 2.63 (SD 0.06) in 2021). However, average number of meals purchased using OFDS nearly doubled between 2018 and 2021 (e.g., in Australia, 0.45 (SD 0.03) meals in 2018 to 0.81 (SD 0.04) in 2021). Conclusion: OFDS use is increasing and are substituting the conventional forms of purchasing meals outside home. Nutritional quality of foods sold, marketing practices and purchasing patterns on OFDS deserve further attention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".