Health Care Costs Associated with Household Food Insecurity in Ontario, Canada
Bibliographic record
Abstract
A broad spectrum of health conditions has been linked to household food insecurity in Canada and the US, but the health care costs associated with food insecurity have not been well documented. We examined the relationship between individuals' household food security status over a 12‐month period and their health care utilization and resultant costs during this period, using data for 67,033 Ontario adults 18‐64 yr from the Canadian Community Health Survey for 2005 and 2007‐2010 linked with administrative health care data from Ontario. Two‐part regression analyses were conducted, adjusting for age, sex, education, home ownership, household composition, and neighborhood income quintile. Based on responses to the Household Food Security Survey Module, 12% of the sample was food insecure (4% marginal, 5% moderate and 3% severe). Over the 12 months, 89% used some health care, with odds of utilization 1.71 times higher (95% CI: 1.44, 2.04) for adults in severely food insecure households compared to fully food secure households. Among health care users, total health care costs rose significantly with food insecurity, increasing by 15% with marginal insecurity, 27% with moderate insecurity, and 56% with severe insecurity, when compared to the food secure. Our results suggest that household food security status is a robust predictor of health care costs, independent of other social determinants of health, and that food insecurity contributes significantly to health care expenditures in Ontario. Funded by the Canadian Institutes of Health Research (FRN 115208).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".