Examining risk factors for cardiovascular disease among food bank members in Vancouver
Bibliographic record
Abstract
Food banks provide supplemental food to low-income households, yet little is known about the cardiovascular health of food banks members. This study therefore described cardiovascular disease (CVD) risk factors among food bank members and explored associations between food insecurity and CVD risk. Adults ≥18 years (n = 77) from three food bank sites in metro Vancouver, British Columbia completed surveys and physical assessments examining a range of socio-demographic variables and CVD risk factors. A composite measure of myocardial infarction (MI) risk called the INTERHEART score was assessed and household food insecurity was measured using the Household Food Security Survey Module. Regression models were used to explore associations between food insecurity and CVD risk measures, including the INTERHEART score. Ninety-seven percent of food bank members reported experiencing food insecurity, 65% were current smokers, 53% reported either chronic or several periods of stress in the past year, 55% reported low physical activity levels and 80% reported consuming fewer than five servings of fruit and vegetables daily. Prevalence of self-reported diabetes and hypertension were 13% and 29% respectively. Fifty-two percent of the sample were at high risk of non-fatal MI. No statistically significant associations were found between increased severity of food insecurity and CVD risk factors among this sample where both severe food insecurity and high CVD risks were prevalent. Food bank members were at elevated risk for CVD compared with the general population. Strategies are needed to reduce prevalence of food insecurity and CVD risk factors, both of which disproportionately affected food bank members.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".