The economic burden of inadequate consumption of vegetables and fruit in Canada
Bibliographic record
Abstract
OBJECTIVE: Public health decision makers not only consider health benefits but also economic implications when articulating and issuing lifestyle recommendations. Whereas various estimates exist for the economic burden of physical inactivity, excess body weight and smoking, estimates of the economic burden associated with our diet are rare. In the present study, we estimated the economic burden attributable to the inadequate consumption of vegetables and fruit in Canada. DESIGN: We accessed the Canadian Community Health Survey to assess the inadequacy in the consumption of vegetables and fruit and published meta-analyses to assemble risk estimates for chronic diseases. Based on these inadequacy and risk estimates, we calculated the population-attributable fraction and avoidable direct and indirect costs to society. Direct costs include those for hospital care, physician services and drugs in 2015. RESULTS: About 80 % of women and 89 % of men consume inadequate amounts of vegetables and fruit. We estimated this to result in an economic burden of $CAN 3·3 billion per year, of which 30·5 % is direct health-care costs and 69·5 % is indirect costs due to productivity losses. A modest 1 percentage point annual reduction in the prevalence of inadequate vegetables and fruit consumption over the next 20 years would avoid approximately $CAN 10·8 billion, and an increase of one serving of vegetables and fruit per day would avoid approximately $CAN 9·2 billion. CONCLUSIONS: Further investments in the promotion of vegetables and fruit will prevent chronic disease and substantially reduce direct and indirect health-care costs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".