Food allergy-related concerns during the transition to self-management
Bibliographic record
Abstract
BACKGROUND: Compared to non-allergic individuals, food allergic individuals have impaired health-related quality of life (HRQL). However, effects of gender and age are unclear. The objective of our study was to describe associations between allergies to common foods and HRQL with consideration to gender and age. METHODS: Adolescents and adults (N = 137; 49.6% males) with specialist-diagnosed allergy to milk, egg and/or wheat completed age-appropriate versions of the Food Allergy Quality of Life Questionnaire (FAQLQ). We pooled common questions and calculated overall- and domain-specific HRQL in association with number and severity of symptoms and time elapse since worst reaction. RESULTS: In the entire study population, HRQL was not affected by gender or age, whereas gender-specific age categories affected HRQL among males only. For example, males 18-39 years had worse overall- (β = 0.77; 95% CI 0.08-1.45) and domain-specific HRQL vs. males < 18 years. Among participants with 1-3 food allergy symptoms, no associations were found. Among participants with 4-6 symptoms, the domain allergen avoidance and dietary restrictions was worse among older participants (e.g. 40+ years: β = 0.71; 95% CI 0.05-1.37 vs. < 18 years), and males 18-39 vs. < 18 years. Among participants with severe symptoms, females vs. males, and participants 18-39 vs. < 18 years had worse HRQL. At least 4 years since worst reaction was associated with worse HRQL for participants 40+ years vs. < 18 years, and older males vs. males < 18 years. Nearly all differences exceeded the clinical relevance threshold of ≥ 0.5. CONCLUSIONS: Associations between allergies to common foods and HRQL are affected by gender and age. Most affected are males 18-39 years. Among females, HRQL is more stable across age groups.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".