Geographic reach and nutritional quality of foods available from mobile online food delivery service applications: novel opportunities for retail food environment surveillance
Bibliographic record
Abstract
BACKGROUND: Online Food Delivery Services (OFDS) have rapidly expanded in North America, but their implications for geographic access to food and potential dietary outcomes of their use are poorly understood. The purpose of this paper is to examine the extent to which OFDS may geographically expand retail food environments. A secondary objective is to evaluate the healthfulness of foods available on mobile OFDS in a large Canadian city using the Healthy Eating Index-2015 (HEI-2015). METHODS: Retailers' distance from delivery location was assessed on a large ODFS platform using 24 randomly selected urban postal codes in Ontario, Canada (n = 480 retailers). Distance to the first 10 and the last 10 listed retailers in each postal code was examined in relation to a) city population, b) city population density, and c) whether retailers appeared first or last. Second, to determine the healthfulness of food items available, menus of twelve retailers (n = 759 menu items) from four popular OFDS platforms available in Mississauga, Ontario, were coded using the Food and Nutrient Database for Dietary Studies-2015, and Food Patterns Equivalents Database-2015. Coded items were used to derive HEI-2015 scores. RESULTS: Delivery distances from the sample of postal codes in Ontario ranged from 0.3 km to 9.4 km (mean 3.7 km), and the total number of retailers available to each postal code ranged from 33 to 472. Substantial, positive correlations existed between total number of retailers available and both city population (r = 0.71), and population density (r = 0.51). HEI-2015 scores for retailers' full menus were typically low, and ranged from 19.95 to 50.78 out of 100. CONCLUSIONS: OFDS substantially increases geographic access to foods prepared away from home (by up to 9 km and 472 restaurants). Food offerings on OFDS applications do not meet healthy eating recommendations. Given the projected continued rapid expansion of OFDS, particularly in the midst of a global pandemic, surveillance and future research on OFDS and population dietary health is warranted.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".