Study protocol for CELLAR (COVID-related Eating Limitations and Latent dietary effects in the Atlantic Region): population-based observational study to monitor dietary intakes and purchasing during COVID-19 in four Atlantic Canadian provinces
Bibliographic record
Abstract
INTRODUCTION: Poor diet is a leading preventable risk for the global burden of non-communicable disease. Robust measurement is needed to determine the effect of COVID-19 on dietary intakes and consumer purchasing, given the widespread changes to consumer food environments and economic precarity. The research objectives are as follows: (1) describe dietary intakes of foods, beverages and nutrients of concern during the COVID-19 pandemic; (2) quantify change in diet during COVID-19 as compared with prepandemic, previously captured in the provincial samples of the population-representative 2015 Canadian Community Health Survey-Nutrition and (3) examine how household purchasing practices predict dietary intakes during COVID-19. METHODS AND ANALYSES: Observational study of diet, using a population-based stratified probability sampling strategy allocated via dual-frame (landline and cellphone) calls to random-digit dialled numbers, followed by age-sex group quotas. The base population comprises the four provinces of the Atlantic region of Canada, jurisdictions with an excess burden of pre-existing dietary risk, compared with the rest of Canada. Our aim is n=1000 to obtain reliable estimates at a regional level to describe intakes and compare with prepandemic baseline. Data collection entails 12 weeks participation: (1) enrolment with sociodemographics (key dietary risk predictors such as age, sex, gender, pre-COVID-19 income, employment, household composition, receipt of economic relief, rural residence); (2) two 24hour diet recalls using the online ASA-24 Canada 2018 tool; and (3) online uploads of household food purchase receipts over the 12 weeks enrolled. Participation incentives will be offered. ETHICS AND DISSEMINATION: This research protocol received funding from the Canadian Institutes of Health Research (FRN VR5 172691) and ethics review approval from the Dalhousie University Research Ethics Board. Study protocol and instruments and a de-identified dataset will be made publicly available. We will submit the findings to peer-reviewed journals, as well as conferences geared towards scientific and decision-maker audiences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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 source (direct Gemma or distilled Codex), 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".