Associations between the neighbourhood food environment, neighbourhood socioeconomic status, and diet quality: An observational study
Bibliographic record
Abstract
BACKGROUND: The neighbourhood environment may play an important role in diet quality. Most previous research has examined the associations between neighbourhood food environment and diet quality, and neighbourhood socioeconomic status and diet quality separately. This study investigated the independent and joint effects of neighbourhood food environment and neighbourhood socioeconomic status in relation to diet quality in Canadian adults. METHODS: We undertook a cross-sectional study with n = 446 adults in Calgary, Alberta (Canada). Individual-level data on diet and socio-demographic and health-related characteristics were captured from two self-report internet-based questionnaires, the Canadian Diet History Questionnaire II (C-DHQ II) and the Past Year Physical Activity Questionnaire (PAQ). Neighbourhood environment data were derived from dissemination area level Canadian Census data, and Geographical Information Systems (GIS) databases. Neighbourhood was defined as a 400 m network-based 'walkshed' around each participant's household. Using GIS we objectively-assessed the density, diversity, and presence of specific food destination types within the participant's walkshed. A seven variable socioeconomic deprivation index was derived from Canadian Census variables and estimated for each walkshed. The Canadian adapted Healthy Eating Index (C-HEI), used to assess diet quality was estimated from food intakes reported on C-DHQ II. Multivariable linear regression was used to test for associations between walkshed food environment variables, walkshed socioeconomic status, and diet quality (C-HEI), adjusting for individual level socio-demographic and health-related covariates. Interaction effects between walkshed socioeconomic status and walkshed food environment variables on diet quality (C-HEI) were also tested. RESULTS: After adjustment for covariates, food destination density was positively associated with the C-HEI (β 0.06, 95 % CI 0.01-0.12, p = 0.04) though the magnitude of the association was small. Walkshed socioeconomic status was not significantly associated with the C-HEI. We found no statistically significant interactions between walkshed food environment variables and socioeconomic status in relation to the C-HEI. Self-reported physical and mental health, time spent in neighbourhood, and dog ownership were also significantly (p < .05) associated with diet quality. CONCLUSIONS: Our findings suggest that larger density of local food destinations may is associated with better diet quality in adults.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".