The household food insecurity gradient and potential reductions in adverse population mental health outcomes in Canadian adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Household food insecurity is related to poor mental health. This study examines whether the level of household food insecurity is associated with a gradient in the risk of reporting six adverse mental health outcomes. This study further quantifies the mental health impact if severe food insecurity, the extreme of the risk continuum, were eliminated in Canada. METHODS: Using a pooled sample of the Canadian Community Health Survey (N = 302,683), we examined the relationship between level of food insecurity, in adults 18-64 years, and reporting six adverse mental health outcomes. We conducted a probit analysis adjusted for multi-variable models, to calculate the reduction in the odds of reporting mental health outcomes that might accrue from the elimination of severe food insecurity. RESULTS: Controlling for various demographic and socioeconomic covariates, a food insecurity gradient was found in six mental health outcomes. We calculated that a decrease between 8.1% and 16.0% in the reporting of these mental health outcomes would accrue if those who are currently severely food insecure became food secure, after controlling for covariates. CONCLUSION: Household food insecurity has a pervasive graded negative effect on a variety of mental health outcomes, in which significantly higher levels of food insecurity are associated with a higher risk of adverse mental health outcomes. Reduction of food insecurity, particularly at the severe level, is a public health concern and a modifiable structural determinant of health worthy of macro-level policy intervention.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it