The excess costs of childhood food allergy on Canadian families: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: The impact of childhood food allergy on household costs has not been examined in Canada. The current study sought to examine differences in direct, indirect, and intangible costs among Canadian families with and without a food-allergic child. METHODS: Families with a child with a specialist-diagnosed food allergy (cases) were recruited from two tertiary pediatric allergy clinics in the Province of Manitoba, Canada, and matched, based on age and sex, to families without a food-allergic child (controls). Cost data for the two groups were collected via an adapted version of the Food Allergy Economic Questionnaire (FA-EcoQ). Consideration was given to income, defined as above vs. below the provincial annual median income. RESULTS: Results from 35 matched case/control pairs revealed that while total household costs did not significantly differ between cases and controls, food-allergic families did incur higher direct costs ($12,455.69 vs. $10,078.93, p = 0.02), which were largely attributed to spending on food. In contrast, cases reported lower, but not statistically significant, total indirect costs compared to controls ($10,038.76 vs. $12,294.12, p = 0.06). Families also perceived their food-allergic child as having poorer quality of life relative to their healthy peers. Lastly, stratification of the analyses by annual income revealed several differences between the higher and lower income groups. CONCLUSIONS: Relative to families without a food-allergic child, food-allergic families incurred higher direct costs across a number of different areas.
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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) | 0.002 | 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".