Household food insecurity and health service use for mental and substance use disorders among children and adolescents in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Food insecurity is a serious public health problem and is linked to the mental health of children and adolescents; however, its relationship with mental health service use is unknown. We sought to estimate the association between household food insecurity and contact with health services for mental or substance use disorders among children and adolescents in Ontario, Canada. METHODS: We used health administrative data, linked to 5 waves of the Canadian Community Health Survey, to identify children and adolescents (aged 1-17 yr) who had a household response to the Household Food Security Survey Module. We identified contacts with outpatient and acute care services for mental or substance use disorders in the year before survey completion using administrative data. We estimated prevalence ratios for the association between household food insecurity and use of mental health services, adjusting for several confounding factors. RESULTS: The sample included 32 321 children and adolescents, of whom 5216 (16.1%) were living in food-insecure households. Of the total sample, 9.0% had an outpatient contact and 0.6% had an acute care contact for a mental or substance use disorder. Children and adolescents in food-insecure households had a 55% higher prevalence of outpatient contacts (95% confidence interval [CI] 41%-70%), and a 74% higher prevalence of acute care contacts (95% CI 24%-145%) for a mental or substance use disorder, although contacts for substance use disorders were uncommon. INTERPRETATION: Children and adolescents living in a food-insecure household have greater use of health services for mental or substance use disorders than those living in households without food insecurity. Focused efforts to support food-insecure families could improve child and adolescent mental health and reduce strain on the mental health system.
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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 | 0.004 |
| 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".