Local food procurement behavior and overall diet quality among adults in Québec: results from the NutriQuébec project
Bibliographic record
Abstract
BACKGROUND: Consumption of locally produced foods is generally perceived as being part of a healthy dietary pattern. Accordingly, in 2020, the provincial government of Québec (Canada) promoted the purchase of local foods for economic and health benefits. The present cross-sectional study aimed to document the association between the behavior of local food procurement and overall diet quality in a sample of adults from the province of Québec. METHODS: Data were collected in a sample of 834 adults (86.6% females) from the NutriQuébec project, a web-based longitudinal population study that aims to document the lifestyle and eating habits of adults in Québec, Canada. Dietary intakes were measured using a validated web-based 24-h recall tool and diet quality was assessed using the Healthy Eating Food Index (HEFI-2019), which measures adherence to the 2019-Canada's Food Guide recommendations on healthy food choices. Local food procurement behavior was measured using the Locavore-I-SF score, which assesses the frequency of short food supply chain use as well as the geographical origin of three locally produced foods. RESULTS: The Locavore-I-SF score was weakly correlated with the HEFI-2019 score (r = 0.08, p < 0.02). Positive correlations were observed for the Vegetables and fruits (r = 0.09, p = 0.005), Beverages (r = 0.08, p = 0.04) and Free sugars (r = 0.14, p < 0.001) components of the HEFI-2019. Associations between the Locavore-I-SF and the HEFI-2019 scores were found in specific subgroups of participants: males (r = 0.33, p < 0.001), participants aged between 50 and 70 years (r = 0.16, p = 0.003), participants with a greater education level (r = 0.13, p = 0.003) and higher income (r = 0.12, p = 0.02), non-vegetarian participants (r = 0.10, p = 0.008) and participants living in Census Metropolitan Areas (r = 0.11, p = 0.004). CONCLUSION: These results suggest that the behavior of local food procurement is only weakly associated with better overall diet quality among a sample of adults from Québec, raising doubts on the relevance of promoting local food procurement as an effective public health measure for improving diet quality in Québec. STUDY REGISTRATION NUMBER: NCT04140071.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".