Canadian Potential Healthcare and Societal Cost Savings from Consumption of Pulses: A Cost-Of-Illness Analysis
Bibliographic record
Abstract
Consumption of dietary pulses, including beans, peas and lentils, is recommended by health authorities across jurisdictions for their nutritional value and effectiveness in helping to prevent and manage major diet-related illnesses of significant socioeconomic burden. The aim of this study was to estimate the potential annual healthcare and societal cost savings relevant to rates of reduction in complications from type 2 diabetes (T2D) and incidence of cardiovascular disease (CVD) following a low glycemic index (GI) or high fiber diet that includes pulses, or 100 g/day pulse intake in Canada, respectively. A four-step cost-of-illness analysis was conducted to: (1) estimate the proportions of individuals who are likely to consume pulses; (2) evaluate the reductions in established risk factors for T2D and CVD; (3) assess the percent reduction in incidences or complications of the diseases of interest; and (4) calculate the potential annual savings in relevant healthcare and related costs. A low GI or high fiber diet that includes pulses and 100 g/day pulse intake were shown to potentially yield Can$6.2 (95% CI $2.6-$9.9) to Can$62.4 (95% CI $26-$98.8) and Can$31.6 (95% CI $11.1-$52) to Can$315.5 (95% CI $110.6-$520.4) million in savings on annual healthcare and related costs of T2D and CVD, respectively. Specific provincial/territorial analyses suggested annual T2D and CVD related cost savings that ranged from up to Can$0.2 million in some provinces to up to Can$135 million in others. In conclusion, with regular consumption of pulse crops, there is a potential opportunity to facilitate T2D and CVD related socioeconomic cost savings that could be applied to Canadian healthcare or re-assigned to other priority domains. Whether these potential cost savings will be offset by other healthcare costs associated with longevity and diseases of the elderly is to be investigated over the long term.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".