Food Insecurity Status and Mortality in Ontario, Canada
Bibliographic record
Abstract
Multiple negative health outcomes are linked to household food insecurity in Canada and the US. What has not been examined, though, is whether food insecurity is associated with higher risks of mortality. We examined the relationship between individuals’ food security status over a 12‐ month period and their mortality status (a) at any point since the survey and (b) within four years of the survey. We used data for 67,033 Ontario adults from the Canadian Community Health Survey linked with administrative health care data. Among individuals 18 to 64, 2.3% of food secure individuals had died at some point after the survey while over twice as many severely food insecure individuals (6.1%) had died. Among individuals over the age of 65, the figures are 24.5% and 33.1%. Even after adjusting for age, sex, education, homeownership, household composition, and neighborhood income quintile, when we look at all adults, mortality rates at any time after the survey are 95.3% higher for severely food insecure, 40.4% higher for moderately food insecure, and 26.8% higher for marginally food insecure adults versus food secure adults; when mortality within four years is considered, that rate is 83.6% higher for severely food insecure and 49.4% higher for moderately food insecure adults. Our results suggest that household food security status is a robust predictor of mortality, further indicating the importance of pursuing policies to reduce food insecurity. Support or Funding Information 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 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) | 0.005 | 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".