Childhood food insecurity and incident diabetes: A longitudinal cohort study of 34 042 children in Ontario, Canada
Bibliographic record
Abstract
AIM: To examine the association between childhood food insecurity and incident diabetes. METHODS: Using health administrative databases linked to the Canadian Community Health Survey, we conducted a population-based cohort study of children aged <18 years from Ontario, Canada. Children without diabetes who had a household response to the Canadian Community Health Survey Household Food Security Survey Module were followed for a median of 9.5 years for incident diabetes. Multivariable Cox proportional hazards models were used to examine the association between childhood food insecurity and incident diabetes, adjusted sequentially for important clinical and socio-economic risk factors. RESULTS: We included 34 042 children, of whom 5.3% lived in food-insecure households. There were 184 new cases of diabetes, diagnosed at a median age of 16 and 18.5 years in food-secure and food-insecure children, respectively. In unadjusted analysis, childhood food insecurity was associated with an increased risk of incident diabetes (hazard ratio 1.69, 95% CI 1.01 to 2.81). When adjusted for clinical and socio-economic confounders, the relationship was no longer statistically significant (hazard ratio 1.55, 95% CI 0.91 to 2.66, adjusted for clinical confounders; hazard ratio 1.30, 95% CI 0.72 to 2.37, adjusted for clinical/socio-economic confounders). Our results remained robust in sensitivity analyses. CONCLUSIONS: Although food-insecure children are a medically and socially vulnerable population, they do not appear to be at increased risk of incident diabetes over a median of 9.5 years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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".