PREVALENCE OF FOOD INSECURITY IN TWO CANADIAN URBAN PAEDIATRIC EMERGENCY DEPARTMENTS
Bibliographic record
Abstract
BACKGROUND: Food insecurity, defined as when the quality or quantity of food available to an individual is compromised, remains a significant social problem in Canada. Recent data has shown that 7.7% of Canadian homes experience food insecurity and children are disproportionately represented. Risk factors include financial stress, recent immigration, single parent homes and the presence of children in the household. Because food insecurity is linked to poor health outcomes, such as obesity and depression, it is a significant public health issue. Front line health care workers have a role to play in identifying and advocating for these families. OBJECTIVES 1. What is the prevalence of food insecure households among families visiting 2 large, urban pediatric emergency departments? 2. What are the demographic, geographic and social risk factors associated with food insecurity? DESIGN/METHODS: An anonymous cross sectional survey was distributed to all patients and families visiting 2 emergency departments during a 2 week period in order to extrapolate data on prevalence of an associations with food insecurity. RESULTS: A total of 644 patients completed the survey. 22.7% (146) of families were identified as being food insecure. Risk factors associated with food insecurity included having a high school education or less, having a lower income (<$40 000/yr), being from a single caregiver home and being of a non – caucasian ethnicity. CONCLUSION: Food insecurity is significantly over represented in patients presenting to 2 urban pediatric emergency departments relative to the general population. Reasons for this need to be further investigated, but are likely related to the association of lower socioeconomic status patients and emergency department use. Interventions should be designed to identify these patients in order to provide necessary support.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".